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Asiri IM, Chen RC, Master V, Mi L, James SE, Bryce AH, Afzal U, Riaz IB, Ahmed Naqvi SA, Beach SRH, Cobran EK. Thromboembolic Events in Castration-Resistant Prostate Cancer Patients With and Without Cardiovascular Comorbidities Receiving Oral Androgen Receptor Pathway Inhibitors. Prostate 2025. [PMID: 40312772 DOI: 10.1002/pros.24902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2024] [Revised: 03/21/2025] [Accepted: 04/04/2025] [Indexed: 05/03/2025]
Abstract
BACKGROUND This study investigates the association between thromboembolic events (TE) and castration-resistant prostate cancer (CRPC) patients receiving oral androgen receptor pathway inhibitors (ARPi) compared to those undergoing chemotherapy, both with and without a pre-existing history of cardiovascular disease (CVD). METHODS A total of 2779 men diagnosed with CRPC were identified using the Surveillance, Epidemiology, and End Results (SEER) Medicare Linked Database from 2012 to 2016. Patients were stratified based on their CVD history. Within each CVD stratum (pre-existing CVD vs. no pre-existing CVD), patients were further categorized into two treatment groups: those receiving oral ARPi and those undergoing chemotherapy. Unadjusted and inverse probability treatment weight (IPTW)-adjusted proportional hazards models, using Fine and Gray's method, were applied to evaluate the potential association between ARPi treatment and TE. RESULTS Patients with pre-existing CVD treated with ARPi exhibited a significantly lower crude hazard ratio (HR) for TE compared to chemotherapy (HR 0.39, 95% CI 0.27-0.58, p < 0.001). However, after adjustment using IPTW, this association was no longer significant (adjusted hazard ratio [AHR] 1.00, 95% CI 0.75-1.32, p = 0.99). For patients without CVD, ARPi use was also associated with a reduced risk of TE in the crude analysis (HR 0.53, 95% CI 0.32-0.87, p = 0.01), but this effect was not statistically significant after IPTW adjustment (HR 0.99, 95% CI 0.69-1.41, p = 0.94). CONCLUSION ARPi demonstrated no significant effect on TE risk compared to chemotherapy, regardless of pre-existing CVD status. Similarly, when excluding patients with a prior history of TE, ARPi use remained non-significantly associated with new TE in the IPTW-adjusted competing risk analysis, highlighting the need for further investigation.
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Affiliation(s)
- Ibrahim M Asiri
- Saudi Food & Drug Authority, Riyadh, Saudi Arabia
- Department of Quantitative Health Science, Mayo Clinic College of Medicine and Sciences, Scottsdale, Arizona, USA
| | - Ronald C Chen
- Department of Radiation Oncology, University of Kansas, School of Medicine, Kansas City, Missouri, USA
| | - Viraj Master
- Department of Urology, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - Lanyu Mi
- Department of Quantitative Health Science, Mayo Clinic College of Medicine and Sciences, Scottsdale, Arizona, USA
| | - Sarah E James
- Department of Radiation Oncology, Mayo Clinic College of Medicine and Sciences, Phoenix, Arizona, USA
| | - Alan H Bryce
- City of Hope, Department of Medical Oncology & Therapeutics Research, Phoenix, Arizona, USA
| | - Umar Afzal
- Department of Quantitative Health Science, Mayo Clinic College of Medicine and Sciences, Scottsdale, Arizona, USA
| | - Irbaz B Riaz
- Department of Medicine, Mayo Clinic College of Medicine and Sciences, Phoenix, Arizona, USA
| | | | - Steven R H Beach
- Department of Psychology, University of Georgia, Franklin College of Arts and Sciences, Athens, Georgia, USA
| | - Ewan K Cobran
- Department of Quantitative Health Science, Mayo Clinic College of Medicine and Sciences, Scottsdale, Arizona, USA
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Bölek H, Sertesen E, Kuzu OF, Tural D, Sim S, Nahit Şendur MA, Uçar G, Işık S, Hacıoğlu B, Çiçin İ, Arslan Ç, Göksu SS, Sever ÖN, Karaçin C, Karadurmuş N, Özgüroğlu M, Yekedüz E, Ürün Y. Treatment Patterns and Attrition in Metastatic Renal Cell Carcinoma: Real-Life Experience from the Turkish Oncology Group Kidney Cancer Consortium (TKCC) Database. Clin Genitourin Cancer 2025; 23:102282. [PMID: 39709686 DOI: 10.1016/j.clgc.2024.102282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 11/24/2024] [Accepted: 11/25/2024] [Indexed: 12/24/2024]
Abstract
INTRODUCTION Despite the rapid evolution in management of metastatic renal cell carcinoma (mRCC) over the past decade, challenges remain in accessing new therapies in some parts of the world. Despite therapeutic advancements, attrition rates remain persistently high. This study aims to assess the treatment patterns and attrition rates of patients with mRCC in oncology clinics across Turkey. PATIENTS AND METHODS Patients diagnosed with mRCC between January 1, 2008, and December 31, 2022, with first-line systemic treatment data, were retrospectively evaluated using the Turkish Oncology Group Kidney Cancer Consortium (TKCC) Database. RESULTS The final analysis included a total of 1126 patients. The percentages of patients treated in the 2nd, 3rd, 4th, and 5th lines of therapy were 62.8%, 27.4%, 8.9%, and 2.1%, respectively. The drugs that were most commonly used in the groups were tyrosine kinase inhibitors (TKIs) (52.2%) and interferon (IFN)-alpha (43.3%) for the first line, TKIs (66.3%) and immunotherapy (IO) monotherapy (25.9%) for the second line, TKI (41.4%) and mTOR inhibitors (28.8%) for the third line, TKI (44.4%) and mTOR inhibitors (29%) for the fourth line, and IO monotherapy (37.5%) and TKI (25%) for the fifth line. For the first-line treatment, the primary cause of attrition was disease progression (66.4%), followed by toxicity (16.5%), death (11.2%), and patient preference (5.9%). The primary reason for attrition across all treatment lines was disease progression. Over time, the use of TKIs in first-line treatment increased, while IFN-alpha usage declined. IOs began to be utilized in earlier lines, predominantly in second-line treatment, though use of IO-based combination therapies remains limited. CONCLUSION This study underscores that despite significant progress in therapeutic options, the adoption of novel agents remains slow, and attrition rates are still high. These findings indicate a disparity in systemic therapy compared to developed countries.
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Affiliation(s)
- Hatice Bölek
- Ankara University School of Medicine, Department of Medical Oncology, Ankara, Turkey; Ankara University Cancer Institute, Ankara, Turkey
| | - Elif Sertesen
- University of Health Science, Dr Abdurrahman Yurtaslan Oncology Training and Research Hospital, Department of Medical Oncology, Ankara Turkey
| | - Omer Faruk Kuzu
- University of Health Science, Gülhane Training and Research Hospital, Department of Medical Oncology, Ankara Turkey
| | - Deniz Tural
- University of Health Science, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Department of Medical Oncology, Istanbul, Turkey
| | - Saadet Sim
- Ege University School of Medicine, Department of Medical Oncology, İzmir, Turkey
| | | | - Gökhan Uçar
- Bilkent City Hospital, Department of Medical Oncology, Ankara Turkey
| | - Selver Işık
- Marmara University School of Medicine, Department of Medical Oncology, Istanbul, Turkey
| | - Bekir Hacıoğlu
- Trakya University School of Medicine, Department of Medical Oncology, Edirne, Turkey
| | - İrfan Çiçin
- Istinye University, Department of Medical Oncology, Istanbul, Turkey
| | - Çağatay Arslan
- Izmir University of Economics, Medical Point Hospital, Izmir, Turkey
| | - Sema Sezgin Göksu
- Akdeniz University School of Medicine, Department of Medical Oncology, Antalya, Turkey
| | - Özlem Nuray Sever
- Kartal Dr Lutfi Kirdar City Hospital, Department of Medical Oncology, Istanbul, Turkey
| | - Cengiz Karaçin
- University of Health Science, Dr Abdurrahman Yurtaslan Oncology Training and Research Hospital, Department of Medical Oncology, Ankara Turkey
| | - Nuri Karadurmuş
- University of Health Science, Gülhane Training and Research Hospital, Department of Medical Oncology, Ankara Turkey
| | - Mustafa Özgüroğlu
- Cerrahpasa School of Medicine, Department of Medical Oncology, Istanbul, Turkey
| | - Emre Yekedüz
- Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, MA
| | - Yüksel Ürün
- Ankara University School of Medicine, Department of Medical Oncology, Ankara, Turkey; Ankara University Cancer Institute, Ankara, Turkey.
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Orcutt X, Chen K, Mamtani R, Long Q, Parikh RB. Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations. Nat Med 2025; 31:457-465. [PMID: 39753967 PMCID: PMC11835724 DOI: 10.1038/s41591-024-03352-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 10/10/2024] [Indexed: 01/11/2025]
Abstract
Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk remains unclear. In this study, we developed TrialTranslator, a framework designed to systematically evaluate the generalizability of RCTs for oncology therapies. Using a nationwide database of electronic health records from Flatiron Health, this framework emulates RCTs across three prognostic phenotypes identified through machine learning models. We applied this approach to 11 landmark RCTs that investigated anti-cancer regimens considered standard of care for the four most prevalent advanced solid malignancies. Our analyses reveal that patients in low-risk and medium-risk phenotypes exhibit survival times and treatment-associated survival benefits similar to those observed in RCTs. In contrast, high-risk phenotypes show significantly lower survival times and treatment-associated survival benefits compared to RCTs. Our results were corroborated by a comprehensive robustness assessment, including examinations of specific patient subgroups, holdout validation and semi-synthetic data simulation. These findings suggest that the prognostic heterogeneity among real-world oncology patients plays a substantial role in the limited generalizability of RCT results. Machine learning frameworks may facilitate individual patient-level decision support and estimation of real-world treatment benefits to guide trial design.
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Affiliation(s)
| | - Kan Chen
- Department of Biostatistics, Harvard University, Boston, MA, USA
| | - Ronac Mamtani
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA
| | - Qi Long
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA.
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ravi B Parikh
- Emory University School of Medicine, Atlanta, GA, USA.
- Winship Cancer Institute, Atlanta, GA, USA.
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Yanaizumi R, Nagamine Y, Harada S, Goto T. Immune-related adverse events in cancer patients referred to the palliative care team of a tertiary care center: a retrospective observational study. Support Care Cancer 2024; 32:793. [PMID: 39542927 DOI: 10.1007/s00520-024-09012-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Accepted: 11/11/2024] [Indexed: 11/17/2024]
Abstract
PURPOSE The application of immune checkpoint inhibitors (ICIs) can cause multi-organ adverse events, namely immune-related adverse events (irAEs) in patients with cancer. This study aimed to characterize the epidemiological information on irAEs in patients with cancer referred to the palliative care team (PCT). METHODS The medical records of cancer patients with a history of ICI therapy referred to the PCT at a tertiary care center between January 2017 and July 2022 were retrospectively reviewed in this single-center, observational study. RESULTS The median age of the 140 patients was 68 years, and lung (39.3%) being the most common primary site. We observed irAEs in 46 patients (32.9%), and hypothyroidism was the most common irAE. For irAEs graded ≥ 3 in 21 patients, pneumonitis was the most common adverse event. As for strategies for management with irAEs, seventeen patients were treated with systemic steroids. irAEs ( +) had a significantly lower Performance Status at the start of ICI, a higher total number of ICI doses, and longer duration from start of ICI to date of death than irAEs (-). CONCLUSIONS Among 140 cancer patients with a history of ICIs therapy consulted to the PCT, the prevalence of irAEs was 32.9%, and 21 patients (15.0%) developed irAEs with grade ≥ 3. As the use of ICI is expected to increase in the future, it is important for palliative care physicians to increase their awareness of the management of irAEs and collaborate with oncologists from an early stage.
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Affiliation(s)
- Ryota Yanaizumi
- Department of Anesthesiology, Yokohama City University Medical Center, Yokohama, Japan
| | - Yusuke Nagamine
- Department of Anesthesiology and Critical Care Medicine, Yokohama City University Hospital, 3-9 Fukuura, Kanazawa-Ku, Yokohama, Kanagawa, 236-0004, Japan.
| | | | - Takahisa Goto
- Department of Anesthesiology and Critical Care Medicine, Yokohama City University Hospital, 3-9 Fukuura, Kanazawa-Ku, Yokohama, Kanagawa, 236-0004, Japan
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Arnaoutakis K, Wan Y, Elliott J, Young M, Yin Y, Leventakos K, Lin HM, Dimou A. Real-World Treatment Patterns and Outcomes Across Three Lines of Therapy in Patients with ALK+ NSCLC. Adv Ther 2024; 41:3217-3231. [PMID: 38916812 PMCID: PMC11263478 DOI: 10.1007/s12325-024-02899-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 05/10/2024] [Indexed: 06/26/2024]
Abstract
INTRODUCTION Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) are standard first- and second-line treatment for advanced ALK+ non-small cell lung cancer (NSCLC). We evaluated outcomes in patients with ALK+ NSCLC receiving third-line ALK TKI versus non-ALK-directed therapy. METHODS Flatiron Health OncoEMR data were extracted for patients with ALK+ NSCLC initiating first-line ALK TKI between January 2015 and March 2022 followed by second-line ALK TKI and third-line ALK TKI (group A) or non-TKI therapy (group B). Time-to-treatment discontinuation (TTD) and overall survival (OS) were analyzed using multivariate modelling. RESULTS Among patients receiving third-line ALK TKI (A, n = 85) or non-TKI therapy (B, n = 43), most received first-line crizotinib (A/B: 64%/60%) and second-line alectinib (36%/30%), ceritinib (24%/19%), or lorlatinib (15%/30%). Common third-line treatments were lorlatinib/alectinib (41%/33%) in A and immunotherapy, chemotherapy, or chemotherapy + immunotherapy (30%/28%/21%) in B. Group A versus B had longer TTD of first-line treatment (hazard ratio [HR] 0.62, 95% confidence interval [CI] 0.41-0.93; p = 0.020) and second-line treatment (HR 0.50, 95% CI 0.33-0.75; p < 0.001) and longer OS from start of first-line treatment (HR 0.32, 95% CI 0.19-0.54; p < 0.001) and second-line treatment (HR 0.40, 95% CI 0.24-0.66; p < 0.001). For third-line treatment, median TTD (A/B) was 6.2/2.4 months (HR 0.61, 95% CI 0.37-1.00; p = 0.049) and OS was 17.6/6.5 months (HR 0.57, 95% CI 0.33-0.98; p = 0.042). CONCLUSIONS Patients receiving third-line non-ALK-directed therapy had suboptimal outcomes on prior TKIs. Patients with longer duration of prior ALK TKI treatment appeared to benefit from third-line ALK TKIs.
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Affiliation(s)
| | - Yin Wan
- Takeda Development Center Americas, Inc., 500 Kendall Street, Cambridge, MA, 02142, USA
| | | | - Matt Young
- Takeda Pharmaceuticals America, Inc., Lexington, MA, USA
| | - Yu Yin
- Takeda Development Center Americas, Inc., 500 Kendall Street, Cambridge, MA, 02142, USA
| | | | - Huamao M Lin
- Global Evidence and Outcomes Research, Takeda Development Center Americas, Inc., 500 Kendall Street, Cambridge, MA, 02142, USA.
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Benz S, Sherman KA, Dasanu CA, Alvarez-Argote J. Immune checkpoint inhibitor-related adverse events: Real-world experience from a single veterans' affairs medical center. J Oncol Pharm Pract 2024; 30:697-704. [PMID: 37350125 DOI: 10.1177/10781552231184178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
BACKGROUND Immune checkpoint inhibitors (ICIs) are antineoplastic agents associated with a multitude of immune-related adverse events (irAEs). Available data from clinical trials include highly selective patient populations which may limit their applicability to real-world clinical practice. METHODS We present a retrospective cohort study of cancer patients treated with ICI therapy at the Zablocki VA Medical Center between 2014 and 2021. Information on demographics, cancer diagnosis, type of therapy, treatment duration, comorbidities, irAE type, and overall survival were collected. RESULTS We identified 187 patients who received at least one dose of ICI. About half the patients experienced at least one irAE, the most common categories being fatigue, pulmonary, and endocrine irAEs. Approximately half of the irAEs were diagnosed within the first three months of starting ICI therapy, and 60.38% of those who experienced irAEs discontinued ICI therapy. Patients who experienced endocrine or intestinal irAEs had a significantly longer overall survival. CONCLUSION Immune-related complications due to ICI therapy are common and can frequently lead to treatment discontinuation in the real-world setting. Endocrine and intestinal irAEs may correlate with improved survival. The ICI-treated patients who received palliative radiation therapy to the bone had less irAEs, possibly due to immunogenic cell death.
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Affiliation(s)
- Samantha Benz
- Department of Medicine, Zablocki Veterans Affairs Medical Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Katherine A Sherman
- Department of Research Health, Zablocki Veterans Affairs Medical Center, Milwaukee, WI, USA
| | - Constantin A Dasanu
- Lucy Curci Cancer Center, Eisenhower Health, Rancho Mirage, CA, USA
- Department of Medical Oncology and Hematology, University of California in San Diego Health System, San Diego, CA, USA
| | - Juliana Alvarez-Argote
- Division of Hematology-Oncology, Department of Medicine, Zablocki Veterans Affairs Medical Center, Medical College of Wisconsin, Milwaukee, WI, USA
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Badiola LB, Milagro NL, Lavín DC, Peraita SL, Ibarbia MA, Kareaga MM, Fernández Del Rivero TDP, Otero DSDP, López VA, Fernández CÁ, Emborujo AL, Arnaiz IG, Rodríguez RF, Verdún-Aguilar J, Sagastibeltza N, Duran I. RENO Study: Clinical characteristics, treatment patterns and survival results in patients with metastatic renal cell carcinoma in Northern Spain. Semin Oncol 2024; 51:77-86. [PMID: 38604897 DOI: 10.1053/j.seminoncol.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The current available evidence on the management of metastatic renal cell cancer (mRCC) in real life is scarce in our environment. We present a summary of the existing real-world data and the results of an analysis describing the clinical characteristics, treatments, and health outcomes of patients with mRCC in northern Spain. METHODS Retrospective observational study. Adult patients diagnosed with mRCC between Jan 2007 and Dec 2019 were included. Epidemiological, efficacy and toxicity data were collected. Median overall survival (OS) and progression-free survival (PFS) were determined using the Kaplan-Meier method. RESULTS A total of 829 patients were included (median age at diagnosis:63 years;73% men). Median follow-up was 180 months. The preponderant histology was clear cell (85%). In 50% the initial diagnosis was advanced disease. The distribution according to IMDC prognosis was good (24%), intermediate (50%) and poor (26%). The most frequent metastatic locations were lung (68.3%) and lymph node (41.0%). Most patients (95%) received a first line (1L) systemic treatment, 60% were treated with a second line (2L) of therapy and 37% received third line (3L). A VEGFR-TKIs was the most common treatment (1L: 90%, n = 507; 2L: 49%, n = 233; 3L: 54%, n = 156) followed by mTOR inhibitors (1L: 2%, n = 4; 2L: 27%, n = 126; 3L: 23%, n = 68) and immunotherapy (1L: 3.7%, n = 25; 2L: 27%, n = 126). Median OS was 24.5 months in the general population. According to IMDC prognostic groups, OS was 52.5, 25.7 and 9 months respectively. From the start of the 1L, 2L, and 3L treatment, median PFS was: 1L: 7.8 (6.8-9.0); 2L: 4.9 (4.3-5.5); 3L: 4.3 (3.8-4.8) months. No unexpected toxicity was reported. CONCLUSIONS The Real-World Data on the management of mRCC in Northern Spain are comparable in epidemiology, efficacy, and safety to studies conducted in other areas of the world. The significant reduction in the number of patients receiving second and subsequent lines of therapy hampers the access to new therapies developed in this context.
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Affiliation(s)
| | | | - Diego Cacho Lavín
- Hospital Universitario Marqués de Valdecilla-IDIVAL, Santander, Spain
| | | | | | | | | | | | | | | | | | | | - Ricardo Fernández Rodríguez
- Hospital Universitario de Cruces e Instituto Oncológico IMQ Bilbao, Bilbao, Spain - Clínica IMQ Zorrotzaurre, Bizkaia, Spain
| | | | - Naiara Sagastibeltza
- Medical Oncology Departments: Hospital Universitario Donostia-OSI Donostialdea, Gipuzkoa, Spain
| | - Ignacio Duran
- Hospital Universitario Marqués de Valdecilla-IDIVAL, Santander, Spain.
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van Nassau SCMW, Bol GM, van der Baan FH, Roodhart JML, Vink GR, Punt CJA, May AM, Koopman M, Derksen JWG. Harnessing the Potential of Real-World Evidence in the Treatment of Colorectal Cancer: Where Do We Stand? Curr Treat Options Oncol 2024; 25:405-426. [PMID: 38367182 PMCID: PMC10997699 DOI: 10.1007/s11864-024-01186-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/17/2024] [Indexed: 02/19/2024]
Abstract
OPINION STATEMENT Treatment guidelines for colorectal cancer (CRC) are primarily based on the results of randomized clinical trials (RCTs), the gold standard methodology to evaluate safety and efficacy of oncological treatments. However, generalizability of trial results is often limited due to stringent eligibility criteria, underrepresentation of specific populations, and more heterogeneity in clinical practice. This may result in an efficacy-effectiveness gap and uncertainty regarding meaningful benefit versus treatment harm. Meanwhile, conduct of traditional RCTs has become increasingly challenging due to identification of a growing number of (small) molecular subtypes. These challenges-combined with the digitalization of health records-have led to growing interest in use of real-world data (RWD) to complement evidence from RCTs. RWD is used to evaluate epidemiological trends, quality of care, treatment effectiveness, long-term (rare) safety, and quality of life (QoL) measures. In addition, RWD is increasingly considered in decision-making by clinicians, regulators, and payers. In this narrative review, we elaborate on these applications in CRC, and provide illustrative examples. As long as the quality of RWD is safeguarded, ongoing developments, such as common data models, federated learning, and predictive modelling, will further unfold its potential. First, whenever possible, we recommend conducting pragmatic trials, such as registry-based RCTs, to optimize generalizability and answer clinical questions that are not addressed in registrational trials. Second, we argue that marketing approval should be conditional for patients who would have been ineligible for the registrational trial, awaiting planned (non) randomized evaluation of outcomes in the real world. Third, high-quality effectiveness results should be incorporated in treatment guidelines to aid in patient counseling. We believe that a coordinated effort from all stakeholders is essential to improve the quality of RWD, create a learning healthcare system with optimal use of trials and real-world evidence (RWE), and ultimately ensure personalized care for every CRC patient.
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Affiliation(s)
- Sietske C M W van Nassau
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands.
| | - Guus M Bol
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands
| | - Frederieke H van der Baan
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands
- Department of Epidemiology & Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeanine M L Roodhart
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands
| | - Geraldine R Vink
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands
| | - Cornelis J A Punt
- Department of Epidemiology & Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anne M May
- Department of Epidemiology & Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Miriam Koopman
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, PO Box 85500, Utrecht, 3584 CX, The Netherlands
| | - Jeroen W G Derksen
- Department of Epidemiology & Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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Wilson BE, Hanna TP, Booth CM. Efficacy-effectiveness gaps in oncology: Looking beyond survival. Cancer 2024; 130:335-338. [PMID: 37916831 DOI: 10.1002/cncr.35075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/03/2023] [Indexed: 11/03/2023]
Abstract
The efficacy-effectiveness (EE) gap describes the differences in survival seen in clinical trials and routine clinical practice, where patients in real-world practice often have inferior outcomes compared to trial populations. However, EE gaps may exist beyond survival outcomes, including gaps in quality of life, toxicity, cost-effectiveness, and patient time, and these EE gaps should also influence patient and clinician treatment decisions. Failure to clearly acknowledge these EE gaps may cause patients, clinicians, and health care systems to have unrealistic expectations of the benefits of therapy across a range of important clinical and economic domains. In this commentary, the authors review the evidence supporting the existence of EE gaps in quality of life, time toxicity, cost and toxicities, and urge for further research into this important topic.
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Affiliation(s)
- Brooke E Wilson
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, Ontario, Canada
| | - Timothy P Hanna
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, Ontario, Canada
| | - Christopher M Booth
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, Ontario, Canada
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Schärer M, Heesen P, Bode-Lesniewska B, Studer G, Fuchs B. Benchmarking Time-to-Treatment Initiation in Sarcoma Care Using Real-World-Time Data. Cancers (Basel) 2023; 15:5849. [PMID: 38136394 PMCID: PMC10741448 DOI: 10.3390/cancers15245849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/03/2023] [Accepted: 12/13/2023] [Indexed: 12/24/2023] Open
Abstract
Benchmarking is a fundamental tool for enhancing quality within a patient-centered healthcare framework. This study presents an analysis of time-to-treatment initiation (TTI) for sarcoma patients, utilizing a database encompassing 266 cases from the Swiss Sarcoma Network. Our findings indicate a median TTI of 30 days across the cohort, with bone sarcomas and deep soft tissue sarcomas demonstrating a shorter median TTI of 28 days, followed by superficial soft tissue sarcomas at 42 days. The data reveal that the use of real-world-time data (RWTD) may account for a longer TTI observed, as it offers more comprehensive capture of patient journeys, unlike conventional datasets. Notably, variability in TTI was observed between different treatment institutions, which underscores the need for standardized processes across centers. We advocate for a selective referral system to specialized centers to prevent capacity overload and ensure timely treatment initiation. Our analysis also identified significant delays in TTI for unplanned 'whoops'-resections, highlighting the importance of early specialist referral in optimizing treatment timelines. This study emphasizes the potential benefits of a streamlined, data-informed approach to sarcoma care. However, further research is required to establish the direct impact of integrated care models on TTI and patient outcomes in the context of sarcoma treatment.
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Affiliation(s)
- Markus Schärer
- Sarcoma Service, Department of Orthopaedics and Trauma, University Teaching Hospital LUKS, 6000 Lucerne, Switzerland;
- Health Sciences and Medical Faculty, University of Lucerne, 6001 Lucerne, Switzerland
- Sarcoma Service, Department of Orthopaedics and Trauma, Kantonsspital Winterthur, 8400 Winterthur, Switzerland
| | - Philip Heesen
- Sarcoma Service, University Hospital USZ, University of Zurich, 8000 Zurich, Switzerland;
| | | | - Gabriela Studer
- Health Sciences and Medical Faculty, University of Lucerne, 6001 Lucerne, Switzerland
| | - Bruno Fuchs
- Sarcoma Service, Department of Orthopaedics and Trauma, University Teaching Hospital LUKS, 6000 Lucerne, Switzerland;
- Health Sciences and Medical Faculty, University of Lucerne, 6001 Lucerne, Switzerland
- Sarcoma Service, University Hospital USZ, University of Zurich, 8000 Zurich, Switzerland;
- Pathologie Institut Enge, University of Zurich, 8000 Zurich, Switzerland
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11
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Shayegan B, Wallis CJD, Hamilton RJ, Morgan SC, Cagiannos I, Basappa NS, Ferrario C, Gotto GT, Fernandes R, Roy S, Noonan KL, Niazi T, Hotte SJ, Saad F, Hew H, Park-Wyllie L, Chan KFY, Malone S. Real-world utilization and outcomes of docetaxel among older men with metastatic prostate cancer: a retrospective population-based cohort study in Canada. Prostate Cancer Prostatic Dis 2023; 26:74-79. [PMID: 35197558 DOI: 10.1038/s41391-022-00514-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/22/2022] [Accepted: 02/09/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND The adoption of docetaxel for systemic treatment of metastatic prostate cancer (PCa), in both castration-sensitive (mCSPC) and castration-resistant (mCRPC) settings, is poorly understood. This study examined the real-world utilization of docetaxel in these patients and their outcomes. METHODS A retrospective population-based study used administrative data from Ontario, Canada, to identify men aged ≥66 years who were diagnosed with de novo mCSPC or mCRPC between 2014 and 2019 and received docetaxel. The study assessed treatment tolerability and toxicity, and survival in both cohorts. Descriptive and comparative statistical analysis were conducted. RESULTS The study identified 11.2% (399/3556) and 13.2% (203/1534) patients diagnosed with de novo mCSPC and with mCRPC who received docetaxel respectively. The median age in both cohorts was 72 years (IQR: 68-76). Overall, 43.9% (n = 175) patients with de novo mCSPC and 52.1% (n = 85) with mCRPC completed ≥6 cycles of docetaxel. Over two-fifth also needed dose adjustments in both cohorts. Hospitalization or emergency department visit for febrile neutropenia were noted in 15.8% (n = 63) of de novo mCSPC patients and similarly in 19% (n = 31) of mCRPC cohort. The median survival of PCa patients who completed ≥6 cycles of docetaxel was significantly longer relative to those who completed <4 cycles: 32.7 vs. 23.5 months (p < 0.001) for mCSPC and 20.5 vs. 10.7 (p = 0.012) for mCRPC respectively. CONCLUSIONS In this population-based study of elderly patients with metastatic PCa, treatment with docetaxel was associated with poor tolerability and higher toxicity compared with clinical trials. Receipt of limited cycles and reduced overall dose of docetaxel were associated with inferior overall survival.
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Affiliation(s)
- Bobby Shayegan
- St. Joseph's Healthcare, McMaster University, Hamilton, ON, Canada
| | | | - Robert J Hamilton
- Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada
| | - Scott C Morgan
- The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | | | - Naveen S Basappa
- Cross Cancer Institute, University of Alberta, Edmonton, AB, Canada
| | - Cristiano Ferrario
- Segal Cancer Centre, Jewish General Hospital, McGill University, Montreal, QC, Canada
| | - Geoffrey T Gotto
- Southern Alberta Institute of Urology, University of Calgary, Calgary, AB, Canada
| | | | - Soumyajit Roy
- Radiation Oncology, Rush University Cancer Center, Chicago, IL, USA
| | - Krista L Noonan
- BC Cancer Agency, University of British Columbia, Surrey, BC, Canada
| | - Tamim Niazi
- Jewish General Hospital, McGill University, Montreal, QC, Canada
| | | | - Fred Saad
- Centre Hospitalier de l'Université de Montréal, University of Montreal, Montreal, QC, Canada
| | | | | | | | - Shawn Malone
- The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
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12
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Tang M, Pearson SA, Simes RJ, Chua BH. Harnessing Real-World Evidence to Advance Cancer Research. Curr Oncol 2023; 30:1844-1859. [PMID: 36826104 PMCID: PMC9955401 DOI: 10.3390/curroncol30020143] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/16/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Randomized controlled trials (RCTs) form a cornerstone of oncology research by generating evidence about the efficacy of therapies in selected patient populations. However, their implementation is often resource- and cost-intensive, and their generalisability to patients treated in routine practice may be limited. Real-world evidence leverages data collected about patients receiving clinical care in routine practice outside of clinical trial settings and provides opportunities to identify and address gaps in clinical trial evidence. This review outlines the strengths and limitations of real-world and RCT evidence and proposes a framework for the complementary use of the two bodies of evidence to advance cancer research. There are challenges to the implementation of real-world research in oncology, including heterogeneity of data sources, timely access to high-quality data, and concerns about the quality of methods leveraging real-world data, particularly causal inference. Improved understanding of the strengths and limitations of real-world data and ongoing efforts to optimise the conduct of real-world evidence research will improve its reliability, understanding and acceptance, and enable the full potential of real-world evidence to be realised in oncology practice.
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Affiliation(s)
- Monica Tang
- Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Randwick 2031, Australia
- Correspondence:
| | | | - Robert J. Simes
- NHMRC Clinical Trials Centre, University of Sydney, Camperdown 2050, Australia
| | - Boon H. Chua
- Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Randwick 2031, Australia
- Faculty of Medicine and Health, UNSW Sydney, Sydney 2052, Australia
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13
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Nghiem V, Wood S, Ramachandran R, Williams G, Outlaw D, Paluri R, Kim YI, Gbolahan O. Short- and Long-Term Survival of Metastatic Biliary Tract Cancer in the United States From 2000 to 2018. Cancer Control 2023; 30:10732748231211764. [PMID: 37926828 PMCID: PMC10668577 DOI: 10.1177/10732748231211764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/05/2023] [Accepted: 10/13/2023] [Indexed: 11/07/2023] Open
Abstract
INTRODUCTION Information about survival outcomes in metastatic biliary tract cancer (BTC) is sparse, and the numbers often quoted are based on reports of clinical trials data that may not be representative of patients treated in the real world. Furthermore, the impact of more widespread adoption of a standardized combination chemotherapy regimen since 2010 on survival is unclear. METHODS We performed an analysis of the Surveillance, Epidemiology, and End Results database to determine the real-world overall survival trends in a cohort of patients with metastatic BTC diagnosed between the years 2000 and 2017 with follow-up until 2018. We analyzed data for the entire cohort, evaluated short-term and long-term survival rates, and compared survival outcomes in the pre-2010 and post-2010 periods. Survival analysis was performed using the Kaplan-Meier method, and Cox proportional hazard models were used to evaluate factors associated with survival. RESULTS Among 13, 287 patients, the median age was 68 years. There was a preponderance of female (57%) and white (77%) patients. Forty-one percent died within 3 months of diagnosis (short-term survivors) and 20% were long-term survivors (12 months or longer). The median overall survival (OS) for the entire cohort was 4.5 months. Median OS improved post-2010 (4.5 months) compared to pre-2010 (3.5 months) (P < .0001). On multivariate analysis, age <55 years, intrahepatic cholangiocarcinoma, surgical resection, and diagnosis post-2010 were associated with lower hazard of death. CONCLUSION The real-world prognosis of metastatic BTC is remarkably poorer than described in clinical trials because a large proportion of patients survive less than three months. Over the last decade, the improvement in survival has been minimal.
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Affiliation(s)
- Van Nghiem
- University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Sarah Wood
- Department of Hematology and Oncology, Emory University School of Medicine, Atlanta, GA, USA
| | - Rekha Ramachandran
- Division of Preventive Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Grant Williams
- Division of Hematology/Oncology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Darryl Outlaw
- Division of Hematology/Oncology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Ravikumar Paluri
- Section of Hematology/Oncology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Young-il Kim
- Division of Preventive Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Olumide Gbolahan
- Department of Hematology and Oncology, Emory University School of Medicine, Atlanta, GA, USA
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Zhang D, Li S, Zhang X, Peng J, Zhang S. What predicts the clinical benefits of PARP inhibitors in platinum-sensitive recurrent ovarian cancer: A real-world single-center retrospective cohort study from China. Front Oncol 2022; 12:955124. [PMID: 36059631 PMCID: PMC9433773 DOI: 10.3389/fonc.2022.955124] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 07/26/2022] [Indexed: 11/20/2022] Open
Abstract
Objective This study assessed the real-world application, effectiveness, and safety of olaparib and niraparib as maintenance therapies in patients with platinum-sensitive recurrent ovarian cancer (PSROC) in China and investigated clinical factors associated with prolonged benefits of poly ADP-ribose polymerase (PARP) inhibitors to help guide clinician treatment-decision making in daily practice. Methods This real-world single-center retrospective cohort study was conducted at the Shandong Cancer Hospital and Institute. Archival data of consecutive patients diagnosed with PSROC who achieved a complete response (CR) or partial response (PR) after the last platinum-based chemotherapy and treated with olaparib or niraparib as maintenance therapy from August 2018 to September 2021 were collected. Results Overall, 106 women were included in the cohort. Seventy-two (68%) patients were treated with olaparib, while 34 (32%) received niraparib; 99.1% of the patients were diagnosed with high-grade serous carcinoma, and 73.6% had FIGO stages III–IV. Approximately 71.7% of the patients had received PARP inhibitors after the second platinum-based line and 44.3% of the patients achieved a CR in their last platinum-based therapy. The median platinum-free interval (PFI) after the penultimate platinum-based therapy was 10 (95% CI: 10–13.6) months. The median PFS was 21 (95% CI: 13–24.5) months and the median CFI was 22 (95% CI: 16–26.5) months. Consistent with the univariate analysis, the multivariate analysis identified three independent factors associated with prolonged progression-free survival (PFS) and chemotherapy-free interval (CFI): breast cancer susceptibility gene (BRCA) mutant type (p = 0.005 and p = 0.003); PFI ≥12 months (p = 0.01 and p = 0.006); and CR to last platinum-based therapy (p = 0.016 and p = 0.019). It was found that there was no appreciable difference in any grade 3–4 hematological AE between patients who received olaparib and niraparib. Conclusion Maintenance treatment with olaparib and niraparib is effective and well tolerated for PSROC patients in real-world clinical practice. Three clinical factors were identified that predicted prolonged survival under maintenance therapy with PARP inhibitors: BRCA mutant type, PFI ≥12 months, and CR to last platinum-based therapy. These findings should be further confirmed with an appropriately powered analysis in studies with larger sample sizes.
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Affiliation(s)
- Depu Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China
- Department of Gynecology Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Shuo Li
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xinxin Zhang
- Department of Gynecology Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jingwei Peng
- Department of Gynecology Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Shiqian Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China
- *Correspondence: Shiqian Zhang,
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Abstract
PURPOSE OF REVIEW To summarize the role of chemotherapy and offer some guidance regarding the selection of chemotherapy in mPC. RECENT FINDINGS Patients with mHSPC have varied prognoses with testosterone suppression alone (androgen deprivation therapy, ADT) and differential responses to docetaxel with ADT. Patients with de novo and metachronous high-volume disease have a robust survival benefit with the addition of docetaxel to hormonal therapies. Patients with synchronous low-volume disease have a more modest survival benefit from docetaxel and there is no evidence of survival benefit with docetaxel in patients with metachronous low-volume disease. Integration of biomarkers may refine treatment selection regardless of volume of disease. Docetaxel and cabazitaxel also impart an OS benefit in patients with metastatic castration-resistant prostate cancer (mCRPC). The choice of chemotherapy in mCRPC depends on treatment received in mHSPC setting. Docetaxel remains the first line chemotherapy in castration-resistant patients who have not received it in mHSPC followed by cabazitaxel, otherwise cabazitaxel can be deployed without docetaxel retreatment. SUMMARY Chemotherapy is a key class of therapy for selected patients with mHSPC and mCRPC.
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Affiliation(s)
- Irbaz B Riaz
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Harvard Medical School
- Brigham and Women Hospital, Harvard Medical, Massachusetts
- Division of Medical Oncology, Department of Internal Medicine, Mayo Clinic, Arizona, USA
| | - Christopher J Sweeney
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Harvard Medical School
- Brigham and Women Hospital, Harvard Medical, Massachusetts
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16
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Development and validation of a coding framework to identify severe acute toxicity from systemic anti-cancer therapy using hospital administrative data. Cancer Epidemiol 2022; 77:102096. [DOI: 10.1016/j.canep.2022.102096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/28/2021] [Accepted: 01/01/2022] [Indexed: 01/05/2023]
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17
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Aung TN, Bickell NA, Jagannath S, Kamath G, Meltzer J, Kunzel B, Egorova NN. Do Patients With Multiple Myeloma Enrolled in Clinical Trials Live Longer? Am J Clin Oncol 2021; 44:603-612. [PMID: 34753885 DOI: 10.1097/coc.0000000000000873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Enrollment in clinical trials is thought to improve survival outcomes through the trial effect. In this retrospective observational cohort study, we aimed to discern differences in survival outcomes by clinical trial enrollment and race-ethnicity. MATERIALS AND METHODS Of 1285 patients receiving care for multiple myeloma at an National Cancer Institute designated cancer center from 2012 to 2018, 1065 (83%) were nontrial and 220 (17%) were trial participants. Time to event analyses were used to adjust for baseline characteristics and account for clinical trial enrollment as a time-varying covariate. We analyzed propensity-matched cohorts of trial and nontrial patients to reduce potential bias in observational data. RESULTS Trial patients were younger (mean age in years: 60 vs. 63; P<0.001), underwent more lines of therapy (treatment lines ≥6: 39% vs. 17%; P<0.001), and had more comorbidities than nontrial patients. After controlling for baseline characteristics and clinical trial enrollment as a time-varying covariate, no significant difference in survival was found between trial and nontrial participants (hazard ratio [HR]=1.34, 95% confidence intervals [CIs]: 0.90-1.99), or between propensity-matched trial and nontrial participants (205 patients in each cohort, HR=1.36, 95% CIs: 0.83-2.23). Subgroup analyses by lines of therapy confirmed results from overall analyses. We did not observe survival differences by race-ethnicity (Logrank P=0.09), though hazard of death was significantly increased for nontrial Black/Hispanic patients compared with trial White patients (HR=1.76, 95% CIs=1.01-3.08). CONCLUSIONS This study did not find evidence of a significant survival benefit to trial enrollment among patients with multiple myeloma. Patients enrolled in clinical trials underwent more lines of therapy, suggesting they may have had more treatment-resistant cancers. A small survival benefit in this cohort may be obscured by the lack of difference in survival between trial and nontrial patients.
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Affiliation(s)
- Taing N Aung
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY
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18
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Schnog JJB, Samson MJ, Gans ROB, Duits AJ. An urgent call to raise the bar in oncology. Br J Cancer 2021; 125:1477-1485. [PMID: 34400802 PMCID: PMC8365561 DOI: 10.1038/s41416-021-01495-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 06/09/2021] [Accepted: 07/09/2021] [Indexed: 02/07/2023] Open
Abstract
Important breakthroughs in medical treatments have improved outcomes for patients suffering from several types of cancer. However, many oncological treatments approved by regulatory agencies are of low value and do not contribute significantly to cancer mortality reduction, but lead to unrealistic patient expectations and push even affluent societies to unsustainable health care costs. Several factors that contribute to approvals of low-value oncology treatments are addressed, including issues with clinical trials, bias in reporting, regulatory agency shortcomings and drug pricing. With the COVID-19 pandemic enforcing the elimination of low-value interventions in all fields of medicine, efforts should urgently be made by all involved in cancer care to select only high-value and sustainable interventions. Transformation of medical education, improvement in clinical trial design, quality, conduct and reporting, strict adherence to scientific norms by regulatory agencies and use of value-based scales can all contribute to raising the bar for oncology drug approvals and influence drug pricing and availability.
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Affiliation(s)
- John-John B. Schnog
- Department of Hematology-Medical Oncology, Curaçao Medical Center, Willemstad, Curaçao ,Curaçao Biomedical and Health Research Institute, Willemstad, Curaçao
| | - Michael J. Samson
- Department of Radiation Oncology, Curaçao Medical Center, Willemstad, Curaçao
| | - Rijk O. B. Gans
- grid.4494.d0000 0000 9558 4598Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ashley J. Duits
- Curaçao Biomedical and Health Research Institute, Willemstad, Curaçao ,grid.4494.d0000 0000 9558 4598Institute for Medical Education, University Medical Center Groningen, Groningen, The Netherlands ,Red Cross Blood Bank Foundation, Willemstad, Curaçao
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Predicting toxicity-related docetaxel discontinuation and overall survival in metastatic castration-resistant prostate cancer: a pooled analysis of open phase 3 clinical trial data. Prostate Cancer Prostatic Dis 2021; 24:743-749. [PMID: 33531652 DOI: 10.1038/s41391-021-00326-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 11/30/2020] [Accepted: 01/15/2021] [Indexed: 02/01/2023]
Abstract
BACKGROUND Docetaxel is widely used in metastatic castration-resistant prostate cancer (mCRPC), however its optimal use remains unclear in the current treatment landscape. Biomarkers to predict Docetaxel toxicity may help optimize treatment selection. We aimed to create a predictive model for toxicity-related Docetaxel discontinuation (TRDD). METHODS Through Project Data Sphere, we accessed individual patient data from the control arms of three frontline mCRPC trials: ASCENT2, VENICE, and MAINSAIL. The inclusion criteria for these trials were all similar and included patients with chemotherapy-naïve mCRPC. The primary outcome was occurrence of TRDD. A competing risks regression (CRR) was used to predict TRDD, after accounting for the occurrence of competing events (death or progression). The output of the model was used as the dependent variable on a classification and regression tree (CART) to identify risk groups for TRDD. RESULTS Overall, 1568 patients were considered. Pooled CI of TRDD was 19% after accounting for competing events (death: 474; progression: 59) within 12 months of starting treatment. To build a risk calculator we relied on a CRR that ultimately included age, ECOG performance status, AST, bilirubin, use of analgesics, and presence of diabetes and chronic kidney disease. The CART analysis identified three risk groups that were named: low (model-derived TRDD risk ≤24%), intermediate (25-64%), and high (≥65%) risk group. In each risk group, probability of TRDD during treatment was 14%, 58%, and 79%, and median OS was 24 months, 20 months, and 13 months, respectively (p < 0.001). CONCLUSIONS Treatment selection in mCRPC remains a challenge. Our model can help clinicians balance Docetaxel toxicity and efficacy. The three risk categories that we identified correlated with OS and this is particularly useful for an optimal shared decision-making process.
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20
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Petinrin OO, Li X, Wong KC. Particle Swarm Optimized Gaussian Process Classifier for Treatment Discontinuation Prediction in Multicohort Metastatic Castration-Resistant Prostate Cancer Patients. IEEE J Biomed Health Inform 2021; 26:1309-1317. [PMID: 34379600 DOI: 10.1109/jbhi.2021.3103989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Prostate cancer is the second leading cancer in men, according to the WHO world cancer report. Its prevention and treatment demand proper attention. Despite numerous attempts for disease prevention, prostate tumours can still become metastatic by blood circulation to other organs. Several treatments have been adopted. However, findings show that the docetaxel treatment induces adverse reactions in patients. Particle Swarm Optimized Gaussian Process Classifier (PSO-GPC) is proposed to determine when to discontinue treatment. Based on three cohorts of prostate cancer patients, we propose and compare several classifiers for the best performance in determining treatment discontinuation. Given the data skewness and class imbalance, the models are evaluated based on both the area under receiver operating characteristics curve (AUC) and area under precision recall curve (AUPRC). With the AUCs ranging between 0.6717 - 0.8499, and AUPRCs ranging between 0.1392 - 0.5423, PSO-GPC performs better than the state-of-the-art. We have carried out statistical analysis for ranking methods and analyzed independent cohort data with PSO-GPC, demonstrating its unbiased performance. A proper determination of treatment discontinuation in metastatic castration-resistant prostate cancer patients will reduce the mortality rate in cancer patients.
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Čerina D, Matković V, Katić K, Belac Lovasić I, Šeparović R, Canjko I, Jakšić B, Petrić-Miše B, Bajić Ž, Boban M, Vrdoljak E. Real-World Efficacy and Safety of Bevacizumab in the First-Line Treatment of Metastatic Cervical Cancer: A Cohort Study in the Total Population of Croatian Patients. JOURNAL OF ONCOLOGY 2021; 2021:2815623. [PMID: 34394349 PMCID: PMC8363452 DOI: 10.1155/2021/2815623] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 08/01/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND Although today it is almost preventable, cervical cancer still represents a significant cancer burden, especially in some developing parts of the world. Since the introduction of bevacizumab in the first-line treatment of metastatic disease, improvements of the outcomes were noted. However, results from randomized controlled trials are often hard to recreate in the real-world setting. OBJECTIVE To assess the real-world efficacy and safety of bevacizumab as a first-line treatment of advanced cervical cancer. METHODS We conducted a retrospective cohort study on the total population of Croatian patients diagnosed with metastatic cervical cancer from 2016 to 2019 who were treated with bevacizumab in combination with cisplatin and paclitaxel (TCB) in the first line. The comparison group was the consecutive sample of patients treated with chemotherapy alone. The primary endpoint was overall survival (OS). Secondary endpoints were progression-free survival (PFS), objective response rate, incidence of adverse events, and the proportion of treatment discontinuation. RESULTS We enrolled 67 patients treated with TCB and a control group of 62 patients treated with chemotherapy alone. The TCB cohort had significantly longer unadjusted OS with a median of 27.0 (95% CI 18.5; not calculable) months, compared to 15.5 (10.7; 30.1) months in the chemotherapy-alone cohort. Adjusted OS was not significantly different. PFS was significantly longer for the TCB cohort, with a median of 10.6 (95% CI 8.5; 15.4) months, than for the chemotherapy-alone cohort, with a median of 5.4 (95% CI 3.9; 9.1) months, even after adjustment for baseline covariates (HRadjusted = 0.60; 95% CI 0.39; 0.94; p=0.027; false discovery rate <5%). CONCLUSIONS In a real-world setting, TCB as a first-line treatment of metastatic cervical cancer was associated with longer PFS, better objective disease control rate, and acceptable toxicity profile in comparison to chemotherapy alone. These results may indicate its utility and potential applicability in other parts of the developing world.
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Affiliation(s)
- Dora Čerina
- Department of Oncology, University Hospital Center Split, School of Medicine, University of Split, Spinčićeva 1, HR-21000 Split, Croatia
| | - Višnja Matković
- Department of Gynecologic Oncology, University Hospital Center Zagreb, Petrova 13, HR-10000 Zagreb, Croatia
| | - Kristina Katić
- Department of Gynecologic Oncology, University Hospital Center Zagreb, Petrova 13, HR-10000 Zagreb, Croatia
| | - Ingrid Belac Lovasić
- Department of Radiotherapy and Oncology, University Hospital Center Rijeka, Krešimirova 42, HR-51000 Rijeka, Croatia
| | - Robert Šeparović
- Department of Medical Oncology, Division of Medical Oncology, University Hospital for Tumors, Sestre Milosrdnice University Hospital Center, Ilica 197, HR-10000 Zagreb, Croatia
| | - Ivana Canjko
- Department of Radiotherapy Oncology, University Hospital Center Osijek, Josipa Huttlera 4, HR-31000 Osijek, Croatia
| | - Blanka Jakšić
- Department of Oncology and Nuclear Medicine, University Hospital Center Zagreb, Kišpatićeva 12, HR-10000 Zagreb, Croatia
| | - Branka Petrić-Miše
- Department of Oncology, University Hospital Center Split, School of Medicine, University of Split, Spinčićeva 1, HR-21000 Split, Croatia
| | - Žarko Bajić
- Research Unit “Dr. Mirko Grmek”, University Psychiatric Hospital “Sveti Ivan”, Jankomir 11, HR-10.090 Zagreb, Croatia
| | - Marijo Boban
- Department of Oncology, University Hospital Center Split, School of Medicine, University of Split, Spinčićeva 1, HR-21000 Split, Croatia
| | - Eduard Vrdoljak
- Department of Oncology, University Hospital Center Split, School of Medicine, University of Split, Spinčićeva 1, HR-21000 Split, Croatia
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22
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Wilson BE, Desnoyers A, Nadler MB, Tibau A, Amir E. Fragility of randomized trials supporting cancer drug approvals stratified by approval pathway and review designations. Cancer Med 2021; 10:5405-5414. [PMID: 34323019 PMCID: PMC8366090 DOI: 10.1002/cam4.4029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/21/2021] [Accepted: 04/23/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND It has been suggested that the results from fragile trials are less likely to translate into benefit in routine clinical practice. METHODS We searched the Food and Drug Administration (FDA) archives to identify drug approvals for solid organ malignancies between 2010 and 2019. We calculated the Fragility Index (FI) supporting each approval, using methods to account for time-to-event. We compared FI and trial and approval characteristics using Mann-Whitney U and Kruskal-Wallis test. Using logistic regression, we examined study characteristics associated with withdrawal of consent or lost to follow-up (WCLFU) exceeding the calculated FI. RESULTS The median FI among 125 included studies was 23 (range 1-322). The FI was ≤10 in 35 studies (28%), 11-20 in 21 (17%), and >20 in 69 (55%). The median FI/Nexp was 7.7% (range 0.1-51.7%). The median FI was significantly lower among approvals processed through the accelerated vs regular pathway (5.5 vs 25, p = 0.001), but there was no difference in median FI/Nexp. The WCLFU exceeded FI in 42% of studies. Overall survival endpoints were more likely to have a WCLFU exceeding FI (OR 3.16, p = 0.003). WCLFU exceeding FI was also associated with a lesser magnitude of effect (median HR 0.69 vs 0.55, p < 0.001). In a sensitivity analysis including only studies with 1:1 randomization, 51% of studies had WCLFU >FI. CONCLUSION The median FI among all trials was 23, and WCLFU exceeded FI in 42%. Comparative trials in solid tumors supporting approval through the accelerated pathway are more fragile compared to trials approved through the regular pathway, an observation likely explained by a lower sample size in the experimental arm.
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Affiliation(s)
- Brooke E Wilson
- Princess Margaret Cancer Centre, Department of Medical Oncology, University of Toronto, Toronto, ON, Canada.,University of New South Wales, Kensington, NSW, Australia
| | - Alexandra Desnoyers
- Princess Margaret Cancer Centre, Department of Medical Oncology, University of Toronto, Toronto, ON, Canada
| | - Michelle B Nadler
- Princess Margaret Cancer Centre, Department of Medical Oncology, University of Toronto, Toronto, ON, Canada
| | - Ariadna Tibau
- Oncology Department, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau, and Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Eitan Amir
- Princess Margaret Cancer Centre, Department of Medical Oncology, University of Toronto, Toronto, ON, Canada
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23
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Ethier JL, Desautels D, Robinson A, Amir E, Kong W, Booth CM. Practice Patterns and Outcomes of Novel Targeted Agents for the Treatment of ERBB2-Positive Metastatic Breast Cancer. JAMA Oncol 2021; 7:e212140. [PMID: 34236387 DOI: 10.1001/jamaoncol.2021.2140] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance Clinical trials have shown that the addition of pertuzumab to trastuzumab-based chemotherapy for first-line treatment of ERBB2-positive metastatic breast cancer is associated with considerable improvement in overall survival (OS). In the second-line setting, trastuzumab emtansine (T-DM1) improves OS compared with capecitabine/lapatinib in patients previously treated with trastuzumab-based chemotherapy. However, there are few data describing long-term real-world outcomes with these agents. Objective To describe practice patterns and outcomes associated with pertuzumab and T-DM1 in routine clinical practice. Design, Setting, and Participants This population-based retrospective cohort study used the Ontario Cancer Registry linked to electronic treatment databases to identify all patients treated with pertuzumab and T-DM1 following reimbursement approval in Ontario, Canada, which has a single-payer public health system. Participants included women with stage IV ERBB2-positive metastatic breast cancer receiving treatment with pertuzumab for first-line metastatic indication from December 2013 through December 2017, and those treated with T-DM1 from May 2014 through December 2017. Pertuzumab and T-DM1 cohorts were analyzed separately. Data were analyzed December 2019 to December 2020. Exposures Treatment with pertuzumab or T-DM1. Main Outcomes and Measures The primary outcome was OS, determined using the Kaplan-Meier method. Factors associated with OS were identified using a Cox proportional hazard model. Results The median (interquartile range [IQR]) age of the 795 women who received pertuzumab and 506 women who received T-DM1 was 57 (49-67) and 56 (48-66) years, respectively. Among the entire population, the median (IQR) OS and time on treatment was 43 (16.2-unavailable) and 14 (6.0-26.2) months, respectively. In the T-DM1 cohort, the proportion of pertuzumab-naive patients decreased over time from 68 of 91 [74.7%] in 2014 to 16 of 89 [18.0%] in 2017 (P < .001). The median (IQR) OS and time on treatment was 15 (6.7-27.7) and 4 (1.4-9.0) months, respectively. Median OS was shorter for patients with prior pertuzumab treatment than in the pertuzumab-naive subgroup (12 vs 19 months; adjusted hazard ratio, 0.70; 95% CI, 0.55-0.89; P = .004). Conclusions and Relevance In this population-based cohort study, the survival of patients treated with pertuzumab and T-DM1 in routine practice appeared inferior to results from pivotal clinical trials. Differences in outcome likely reflect differences in patient population and previous lines of therapy in routine practice. Further work is needed to understand the effectiveness of T-DM1 after pertuzumab exposure.
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Affiliation(s)
- Josee-Lyne Ethier
- Department of Oncology, School of Medicine, Queen's University, Kingston, Ontario, Canada.,Division of Cancer Care and Epidemiology, Cancer Research Institute, School of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Danielle Desautels
- Department of Medical Oncology and Hematology, CancerCare Manitoba, Winnipeg, Manitoba, Canada
| | - Andrew Robinson
- Department of Oncology, School of Medicine, Queen's University, Kingston, Ontario, Canada.,Division of Cancer Care and Epidemiology, Cancer Research Institute, School of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Eitan Amir
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Weidong Kong
- Division of Cancer Care and Epidemiology, Cancer Research Institute, School of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Christopher M Booth
- Department of Oncology, School of Medicine, Queen's University, Kingston, Ontario, Canada.,Division of Cancer Care and Epidemiology, Cancer Research Institute, School of Medicine, Queen's University, Kingston, Ontario, Canada
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24
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Poon DMC, Chan K, Chan TW, Ng B, Siu S, Ng J, Johnson D, Lee KC. Prevention of docetaxel-associated febrile neutropenia with primary granulocyte colony-stimulating factor in Chinese metastatic hormone-sensitive and castration-resistant prostate cancer patients. Asia Pac J Clin Oncol 2021; 17 Suppl 3:39-47. [PMID: 33860642 DOI: 10.1111/ajco.13578] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Asian prostate cancer (PC) patients are particularly susceptible to docetaxel-related febrile neutropenia (FN). We evaluated primary granulocyte colony-stimulating factor (GCSF) for preventing FN in Chinese patients with metastatic hormone-sensitive PC (mHSPC) and castration-resistant PC (mCRPC). PATIENTS AND METHODS Data from two cohorts of 377 Chinese patients with mHSPC (100; 26.5%) and mCRPC (277; 73.5%) treated with docetaxel at six public oncology centres were analysed with multivariate regression. Primary GCSF prophylaxis was defined as administration within 5 days of starting docetaxel. The primary outcome was FN within 21 days of the first docetaxel cycle (1st FN). RESULTS Primary GCSF was given to 71 (18.8%) patients. FN occurred in 61 patients (16.2%) including 37 (9.8%) during the first cycle. Among patients who developed 1st cycle FN (n = 37) or not (n = 340), 2 and 69 received primary GCSF (5.4 vs. 20.3%, P = .03). Primary GCSF was associated with an overall reduced risk of 1st cycle FN (odds ratio [OR] = 0.22; 95% confidence interval [CI]: 0.05-0.96, P = .04), and similar trends were observed in the mHSPC (OR = 0.36, P = .35) and mCRPC (OR = 0.16, P = .08) subgroups. Poor Eastern Cooperative Oncology Group performance status (>1) was associated with an increased risk of 1st FN (OR = 3.90; 95% CI: 1.66-9.13, P = .002). CONCLUSIONS To alleviate the risk of docetaxel-related FN, primary GCSF prophylaxis is suggested for Asian mCRPC and mHSPC patients, particularly those with poor performance status.
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Affiliation(s)
- Darren M C Poon
- Department of Clinical Oncology, State Key Laboratory in Oncology in South China, Sir Y.K. Pao Centre for Cancer, Hong Kong Cancer Institute and Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong.,Comprehensive Oncology Centre, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong
| | - Kuen Chan
- Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong
| | - Tim-Wai Chan
- Department of Clinical Oncology, Queen Elizabeth Hospital, Kowloon, Hong Kong
| | - Bryan Ng
- Department of Oncology, Princess Margaret Hospital, Kowloon, Hong Kong
| | - Steven Siu
- Department of Clinical Oncology, Queen Mary Hospital, Hong Kong Island, Hong Kong
| | - Joyce Ng
- Department of Clinical Oncology, State Key Laboratory in Oncology in South China, Sir Y.K. Pao Centre for Cancer, Hong Kong Cancer Institute and Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong
| | - David Johnson
- Department of Clinical Oncology, State Key Laboratory in Oncology in South China, Sir Y.K. Pao Centre for Cancer, Hong Kong Cancer Institute and Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong
| | - Ka Chai Lee
- Department of Clinical Oncology, Tuen Mun Hospital, New Territories, Hong Kong
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25
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Alibhai SMH, Breunis H, Hansen AR, Gregg R, Warde P, Timilshina N, Tomlinson G, Joshua AM, Hotte S, Fleshner N, Emmenegger U. Examining the ability of the Cancer and Aging Research Group tool to predict toxicity in older men receiving chemotherapy or androgen-receptor-targeted therapy for metastatic castration-resistant prostate cancer. Cancer 2021; 127:2587-2594. [PMID: 33798267 DOI: 10.1002/cncr.33523] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/11/2021] [Accepted: 02/12/2021] [Indexed: 01/26/2023]
Abstract
BACKGROUND Because multiple treatments are available for metastatic castrate-resistant prostate cancer (mCRPC) and most patients are elderly, the prediction of toxicity risk is important. The Cancer and Aging Research Group (CARG) tool predicts chemotherapy toxicity in older adults with mixed solid tumors, but has not been validated in mCRPC. In this study, its ability to predict toxicity risk with docetaxel chemotherapy (CHEMO) was validated, and its utility was examined in predicting toxicity risk with abiraterone or enzalutamide (A/E) among older adults with mCRPC. METHODS Men aged 65+ years were enrolled in a prospective observational study at 4 Canadian academic cancer centers. All clinically relevant grade 2 to 5 toxicities over the course of treatment were documented via structured interviews and chart review. Logistic regression was used to identify predictors of toxicity. RESULTS Seventy-one men starting CHEMO (mean age, 73 years) and 104 men starting A/E (mean age, 76 years) were included. Clinically relevant grade 3+ toxicities occurred in 56% and 37% of CHEMO and A/E patients, respectively. The CARG tool was predictive of grade 3+ toxicities with CHEMO, which occurred in 36%, 67%, and 91% of low, moderate, and high-risk groups (P = .003). Similarly, grade 3+ toxicities occurred among A/E users in 23%, 48%, and 86% with low, moderate, and high CARG risk (P < .001). However, it was not predictive of grade 2 toxicities with either treatment. CONCLUSIONS There is external validation of the CARG tool in predicting grade 3+ toxicity in older men with mCRPC undergoing CHEMO and demonstrated utility during A/E therapy. This may aid with treatment decision-making.
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Affiliation(s)
- Shabbir M H Alibhai
- Department of Medicine, University Health Network, Toronto, Ontario, Canada.,Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Henriette Breunis
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Aaron R Hansen
- Department of Medicine, University Health Network, Toronto, Ontario, Canada.,Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Richard Gregg
- Department of Medical Oncology, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Padraig Warde
- Radiation Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Narhari Timilshina
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - George Tomlinson
- Department of Medicine, University Health Network, Toronto, Ontario, Canada.,Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.,Biostatistics Research Unit, University Health Network, Toronto, Ontario, Canada
| | - Anthony M Joshua
- Department of Medicine, University Health Network, Toronto, Ontario, Canada.,Kinghorn Cancer Centre, University of New South Wales, Sydney, New South Wales, Australia
| | | | - Neil Fleshner
- Division of Urology, University Health Network, Toronto, Ontario, Canada
| | - Urban Emmenegger
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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26
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Chen WJ, Kong DM, Li L. Prognostic value of ECOG performance status and Gleason score in the survival of castration-resistant prostate cancer: a systematic review. Asian J Androl 2021; 23:163-169. [PMID: 33159024 PMCID: PMC7991808 DOI: 10.4103/aja.aja_53_20] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 07/12/2020] [Indexed: 01/06/2023] Open
Abstract
Eastern Cooperative Oncology Group (ECOG) performance status and Gleason score are commonly investigated factors for overall survival (OS) in men with castration-resistant prostate cancer (CRPC). However, there is a lack of consistency regarding their prognostic or predictive value for OS. Therefore, we performed this meta-analysis to assess the associations of ECOG performance status and Gleason score with OS in CRPC patients and compare the two markers in patients under different treatment regimens or with different chemotherapy histories. A systematic literature review of monotherapy studies in CRPC patients was conducted in the PubMed database until May 2019. The data from 8247 patients in 34 studies, including clinical trials and real-world data, were included in our meta-analysis. Of these, twenty studies reported multivariate results and were included in our main analysis. CRPC patients with higher ECOG performance statuses (≥ 2) had a significantly increased mortality risk than those with lower ECOG performance statuses (<2), hazard ratio (HR): 2.10, 95% confidence interval (CI): 1.68-2.62, and P < 0.001. The synthesized HR of OS stratified by Gleason score was 1.01, with a 95% CI of 0.62-1.67 (Gleason score ≥ 8 vs <8). Subgroup analysis showed that there was no significant difference in pooled HRs for patients administered taxane chemotherapy (docetaxel and cabazitaxel) and androgen-targeting therapy (abiraterone acetate and enzalutamide) or for patients with different chemotherapy histories. ECOG performance status was identified as a significant prognostic factor in CRPC patients, while Gleason score showed a weak prognostic value for OS based on the available data in our meta-analysis.
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Affiliation(s)
- Wen-Jun Chen
- Center of Clinical Pharmacology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Da-Ming Kong
- Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System, Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing 100191, China
| | - Liang Li
- Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System, Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing 100191, China
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27
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Fragility index of trials supporting approval of anti-cancer drugs in common solid tumours. Cancer Treat Rev 2021; 94:102167. [PMID: 33652263 DOI: 10.1016/j.ctrv.2021.102167] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/01/2021] [Accepted: 02/03/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND The Fragility Indexquantifies the reliability of positive trials by estimating the number of events, which would change statistically significant results to non-significant results. METHODS We identified randomized trials supporting drug approvals by the US FDA between 2009 and 2019 in lung, breast, prostate, and colon cancers and in melanoma. We reconstructed survival tablesand calculated the number of events, which would result in a non-significant result for the primary endpoint. The FI was then compared to the number of patients in each trial who withdrew consent or were lost to follow-up. Regression analyses were used to explore associations between RCT characteristics and FI and trials in which FI was lower or equal to number of participants who withdrew consent or were lost to follow-up. RESULTS Among 81 RCTs, the median FI was 28. The median number of patients who withdrew consent or were lost to follow up was 27. FI was equal or lower than the number of patients who withdrew consent or were lost to follow-up in 47 trials (58%). There was a modest increase in FI over time (p = 0.02). Trials with overall survival as the primary endpoint (p = 0.006) and those in the palliative setting (p < 0.001) had lower FI. There was no association with trial sample size or duration of follow-up. FINDINGS Statistical significance of RCTs in common solid tumours can be reversed often with a small number of additional events. Post-approval RCTs or real-world data analyses should be performed to ensure results of registration trials are robust.
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28
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Omland LH, Lindberg H, Carus A, Als AB, Jensen NV, Taarnhøj GA, Trepiakas R, Suetta C, Omland LH, Pappot H. Real-world Treatment Patterns and Overall Survival in Locally Advanced and Metastatic Urothelial Tract Cancer Patients Treated with Chemotherapy in Denmark in the Preimmunotherapy Era: A Nationwide, Population-based Study. EUR UROL SUPPL 2021; 24:1-8. [PMID: 34337488 PMCID: PMC8317834 DOI: 10.1016/j.euros.2020.12.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2020] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Real-world treatment patterns and survival outcomes of locally advanced, unresectable, and metastatic urinary tract cancer (mUTC) patients have not previously been studied in a nationwide, population-based cohort. OBJECTIVE To describe treatment patterns and survival outcomes in mUTC patients treated in the real-world clinical setting. DESIGN SETTING AND PARTICIPANTS This nationwide, population-based study included all mUTC patients initiating first-line chemotherapy at Danish oncology departments from January 2010 to March 2016. Data were retrospectively obtained from electronic medical records. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Outcome measurements were descriptive. Kaplan-Meier was used for survival analysis. RESULTS AND LIMITATIONS Of 952 patients included in the study, 46.2% initiated standard gemcitabine/cisplatin (GC) and 21.1% gemcitabine/carboplatin (CaG); the remaining patients initiated other treatment regimens. Median follow-up was 11.6 mo. The overall response rate and disease control rate were 43.0% and 61.7% in all patients, 51.4% and 69.1% in GC-treated patients, and 34.4% and 58.8% in CaG-treated patients, respectively. Median overall survival (OS) was 11.7 (95% confidence interval [CI]: 10.8-12.5) mo in all patients, 14.0 (95% CI: 12.5-15.5) mo in GC-treated patients, and 9.8 (95% CI: 8.7-10.9) mo in CaG-treated patients. Limitations include the retrospective study design. CONCLUSIONS Real-world mUTC patients are older and less fit than patients enrolled in clinical trials; despite this, tumor responses and survival are comparable. Survival in our patient cohort is also comparable with that reported from other real-world studies in this patient group. PATIENT SUMMARY We studied treatment patterns and survival in urinary tract cancer patients receiving chemotherapy in the real-world clinical practice. Survival in our patient cohort was comparable with that reported from clinical trials and other real-world studies in this patient group.
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Affiliation(s)
- Lise H. Omland
- Department of Oncology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Henriette Lindberg
- Department of Oncology, Herlev and Gentofte University Hospital, Herlev, Denmark
| | - Andreas Carus
- Department of Oncology, Aalborg University Hospital, Aalborg, Denmark
| | | | | | - Gry A. Taarnhøj
- Department of Oncology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Redas Trepiakas
- Department of Oncology, Zealand University Hospital, Næstved, Denmark
| | - Charlotte Suetta
- Department of Geriatrics and Palliative Medicine, Frederiksberg and Bispebjerg University Hospital, Copenhagen, Denmark
- Department of Medicine, Herlev and Gentofte University Hospital, Herlev, Denmark
| | - Lars H. Omland
- Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Helle Pappot
- Department of Oncology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
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29
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Procopio G, Chiuri VE, Giordano M, Mantini G, Maisano R, Bordonaro R, Calvani N, Facchini G, De Placido S, Airoldi M, Sbrana A, Gasparro D, Ludovico GM, Guglielmini P, Naglieri E, Fagnani D, Aglietta M, Schips L, Beccaglia P, Sciarra A, Livi L, Santini D. Effectiveness of abiraterone acetate plus prednisone in chemotherapy-naïve patients with metastatic castration-resistant prostate cancer in a large prospective real-world cohort: the ABItude study. Ther Adv Med Oncol 2020; 12:1758835920968725. [PMID: 33193831 PMCID: PMC7604981 DOI: 10.1177/1758835920968725] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 10/02/2020] [Indexed: 12/24/2022] Open
Abstract
Background: Real-world data on chemotherapy-naïve patients with metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone plus prednisone are limited, largely deriving from small retrospective studies. Methods: ABitude is an Italian, observational, prospective, multicenter study of mCRPC patients receiving abiraterone plus prednisone in clinical practice. Chemotherapy-naïve mCRPC patients were consecutively enrolled at abiraterone start (February 2016 to June 2017) and are being followed for 3 years, with evaluation approximately every 6 months. Several clinical and patients reported outcomes were examined. Results: In this second interim analysis, among 481 enrolled patients, 453 were evaluable for analyses. At baseline, the median age was 77 years and ~69% of patients had comorbidities (mainly cardiovascular diseases). Metastases were located mainly at bones and lymph nodes; 8.4% of patients had visceral metastases. During a median follow-up of 18 months, 1- and 2-year probability of radiographic progression-free survival were 73.9% and 56.2%, respectively; the corresponding rates for overall survival were 87.3% and 70.4%. In multivariable analyses, the number of bone metastases significantly affected radiographic progression-free survival and overall survival. During abiraterone plus prednisone treatment, 65% of patients had a ⩾50% prostate-specific antigen decline, and quality of life remained appreciably high. Among symptomatic patients according to the Brief Pain Inventory) (32%), scores significantly declined after 6 months of treatment. Overall, eight patients (1.7%) had serious adverse reactions to abiraterone. Conclusions: Abiraterone plus prednisone is effective and safe for chemotherapy-naïve mCRPC patients in clinical practice.
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Affiliation(s)
- Giuseppe Procopio
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, via Venezian 1, Milan, 20133, Italy
| | | | - Monica Giordano
- Medical Oncology Division, ASST-Lariana, Como, Lombardia, Italy
| | - Giovanna Mantini
- Radiochemotherapy Unit, Department of Diagnostics for Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico A. Gemelli IRCCS, Rome - University Department of Radiological and Hematological Sciences, Università Cattolica Sacro Cuore, Italy
| | - Roberto Maisano
- Department of Oncology, A.O. Bianchi-Melacrino-Morelli, Reggio Calabria, Calabria, Italy
| | | | - Nicola Calvani
- Medical Oncology Unit, Antonio Perrino Hospital, Brindisi, Puglia, Italy
| | - Gaetano Facchini
- Departmental Unit of Experimental Uro-Andrological Clinical Oncology, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Naples, Italy
| | - Sabino De Placido
- Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Campania, Italy
| | - Mario Airoldi
- Oncology Unit 2 - Città della Salute e della Scienza di Torino, Turin, Piemonte, Italy
| | - Andrea Sbrana
- Medical Oncology Unit 2, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Donatello Gasparro
- Medical Oncology Unit, Department of General and Specialistic Medicine, University Hospital of Parma, Parma, Italy
| | | | - Pamela Guglielmini
- Oncology Unit, SS Antonio e Biagio e Cesare Arrigo Hospital, Alessandria, Italy
| | | | | | - Massimo Aglietta
- Department of Oncology, University of Turin; Candiolo Cancer Institute - FPO- IRCCS, Candiolo, Italy
| | - Luigi Schips
- Department of Medical, Oral and Biotechnological Sciences, G. d'Annunzio University of Chieti, Urology unit, "SS. Annunziata Hospital", Chieti, Italy
| | | | - Alessandro Sciarra
- Department of Urology, Sapienza Rome University Policlinico Umberto I, Rome, Italy
| | - Lorenzo Livi
- Department of Radiation Oncology, Azienda Ospedaliero-Universitaria Careggi, University of Florence, Florence, Italy
| | - Daniele Santini
- Department of Medical Oncology, University Campus Biomedico, Rome, Italy
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30
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Moussa M, Lazarou L, Dellis A, Abou Chakra M, Papatsoris A. An up-to-date evaluation of darolutamide for the treatment of prostate cancer. Expert Opin Pharmacother 2020; 22:397-402. [PMID: 33135506 DOI: 10.1080/14656566.2020.1845650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Introduction: Currently, in prostate cancer, an increasing number of novel drugs are being used to delay its advancement to metastatic castration-resistant prostate cancer (mCRPC). Apalutamide, enzalutamide, and most recently, darolutamide (novel androgen receptor antagonists) have been approved for nonmetastatic castration-resistant prostate cancer (nmCRPC).Areas covered: The authors have evaluated darolutamide, covering all aspects of the clinical development, competence, and safety profile of the drug.Expert opinion: The unique structure of darolutamide is characterized by a high affinity for androgen receptors and detainment of antagonist activity in mutant isoforms of androgen receptors. In clinical practice, this is the main reason that makes darolutamide exceptional in terms of safety and efficacy compared to other drugs in this category. Darolutamide is considered to have the lowest probability for adverse events (AEs) compared to apalutamide and enzalutamide. Future studies, along with real-world clinical data are warranted to improve personalized treatment strategies as well as sequencing treatment between approved novel drugs.
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Affiliation(s)
- Mohamad Moussa
- Department of Urology, Al Zahraa Hospital, University Medical Center, Lebanese University, Beirut, Lebanon
| | - Lazaros Lazarou
- 2nd Department of Urology, School of Medicine, Sismanoglio Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Athanasios Dellis
- 2nd Department of Urology, School of Medicine, Sismanoglio Hospital, National and Kapodistrian University of Athens, Athens, Greece.,Department of Surgery, School of Medicine, Aretaieion Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Mohamed Abou Chakra
- Department of Urology, Al Zahraa Hospital, University Medical Center, Lebanese University, Beirut, Lebanon
| | - Athanasios Papatsoris
- 2nd Department of Urology, School of Medicine, Sismanoglio Hospital, National and Kapodistrian University of Athens, Athens, Greece
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González-Domingo M, Ulloa C, Olivares J, Estrada S, González P, Cardozo N. Adjuvant radiochemotherapy in locally advanced gastric cancer: from evidence to daily clinical practice in a single institution. Ecancermedicalscience 2020; 14:1137. [PMID: 33281929 PMCID: PMC7685767 DOI: 10.3332/ecancer.2020.1137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Indexed: 12/24/2022] Open
Abstract
Background Gastric cancer is one of the main important causes of cancer death in Chile. Objective To report the results of adjuvant radiochemotherapy in advanced gastric cancer. Material and Methods Between 2000 and 2018, 214 subjects aged 23-85 (median, 62) years with lymph node and/or serosa involvement were treated with adjuvant chemoradiotherapy after curative resection. Results With a median follow-up of 41 months, overall 3- and 5-year survival was 54.9% and 40.85%, respectively. On multivariate analysis, the factors associated with lower survival were aged >65 years, stage group and number of lymph nodes involved. Conclusion In patients with locoregionally advanced gastric cancer treated with curative intent with surgery and adjuvant radiochemotherapy, the overall 5-year survival reported from local clinical practice is similar to that reported in randomised series and supports its use as an effective treatment for this type of patients in our country.
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Affiliation(s)
| | | | - Jorge Olivares
- Oncology and Radiotherapy resident, University of Valparaíso, Chile
| | | | - Pablo González
- Department of Radiation Oncology, Arturo López Pérez Foundation, Santiago, Chile
| | - Neyla Cardozo
- Department of Radiation Oncology, Instituto Oncológico, Viña del Mar, 2540364, Chile
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Sugavanam T, Williamson E, Fordham B, Hansen Z, Richmond H, Hall A, Ali U, Copsey B, Lamb SE. Evaluation of the implementation of the Back Skills Training (BeST) programme using online training: a cohort implementation study. Physiotherapy 2020; 109:4-12. [PMID: 32795621 DOI: 10.1016/j.physio.2020.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES 1) Evaluate implementation of the Back Skills Training (BeST) programme, a group cognitive behavioural approach for patients with low back pain (LBP) developed for a clinical trial, into the National Health Service (NHS) in the United Kingdom; 2) Compare patient outcomes with the BeST Trial results. DESIGN Two stage observational cohort implementation study. PARTICIPANTS Stage 1: NHS Clinicians enrolled in BeST online training. Stage 2: Patients with LBP attending NHS physiotherapy departments and enrolled in the BeST programme. INTERVENTION An online training and implementation programme. OUTCOMES Stage 1: LBP attitudes and beliefs, self-rated competence, intention and actual implementation were collected before, immediately, 4- and 12-months post-training. Stage 2: Patients rated pain, function, recovery and satisfaction before and up to one year after attending the BeST programme. RESULTS Stage 1: 1324 clinicians (157 NHS Trusts) enrolled in the training; 586 (44%) clinicians (101 NHS Trusts) completed training; 443/586 (76%) clinicians provided post-training data; 253/443 (57%) clinicians intended to implement the programme; 148/381 (39%) clinicians (54 NHS Trusts) provided follow-up data; 49/148 (33.1%) clinicians (27 NHS Trusts) implemented the programme. Attitudes and beliefs shifted towards a biopsychosocial model post-training. Stage 2: 923 patients were enrolled. Patients reported improvements in function (mean change: 1.55; 95%CI: 1.25, 1.86) and pain (-0.84; -1.1, -0.58) at follow-up. The majority rated themselves improved and satisfied with the programme. CONCLUSION Online training had good reach into NHS Trusts although, not everyone went onto implement the programme. Improvements in function that were consistent with the original trial were demonstrated.
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Affiliation(s)
- Thavapriya Sugavanam
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Esther Williamson
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, United Kingdom.
| | - Beth Fordham
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, United Kingdom.
| | - Zara Hansen
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, United Kingdom.
| | - Helen Richmond
- Primary Healthcare Research Unit, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada.
| | - Amanda Hall
- Primary Healthcare Research Unit, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada.
| | - Usama Ali
- Nuffield Department of Population Health, University of Oxford, United Kingdom.
| | - Bethan Copsey
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, United Kingdom.
| | - Sarah E Lamb
- Medical School, University of Exeter, United Kingdom.
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Matsuyama H, Matsubara N, Kazama H, Seto T, Tsukube S, Suzuki K. Real-world efficacy and safety of two doses of cabazitaxel (20 or 25 mg/m 2) in patients with castration-resistant prostate cancer: results of a Japanese post-marketing surveillance study. BMC Cancer 2020; 20:649. [PMID: 32660451 PMCID: PMC7359263 DOI: 10.1186/s12885-020-07131-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 07/02/2020] [Indexed: 11/10/2022] Open
Abstract
Background The recommended starting dose of cabazitaxel for castration-resistant prostate cancer (CRPC) is 25 mg/m2 in Japan and Europe. Although lower doses are established alternatives based on randomized controlled trials, the safety and efficacy of 25 and 20 mg/m2 in real-world settings are not well established. Therefore, we investigated the safety and efficacy of cabazitaxel at the recommended starting dose or a lower dose (20 mg/m2) in real-world clinical practice. Methods We compared the safety and efficacy of cabazitaxel between patients who received cabazitaxel at starting doses of 25 and 20 mg/m2 (C25 and C20, respectively) in a Japanese post-marketing surveillance study of 662 patients with docetaxel-refractory CRPC. Safety was assessed in terms of adverse drug reactions (ADRs). Prostate-specific antigen (PSA) response rate, overall survival (OS), and time-to-treatment failure (TTF) were compared between the C25 and C20 groups in unmatched patients and after applying propensity score matching. Results The C20 and C25 groups comprised 190 and 159 patients without matching and 112 patients per group after matching. In unmatched patients, any-grade (C25 vs C20: 89.3% vs 78.4%, Fisher’s p < 0.01) and grade ≥ 3 (81.1% vs 61.1%) ADRs were more frequent in the C25 group. Neutropenia (any grade: 61.6% vs 54.2%; grade ≥ 3: 55.3% vs 42.6%) and febrile neutropenia (grade ≥ 3: 30.2% vs 14.7%) were more frequent in the C25 group. In matched patients, the PSA response rate (reduction in PSA ≥30% from a baseline ≥5 ng/mL) was 26.4 and 32.0% in the C20 and C25 groups, respectively, median OS was 291 days (95% CI 230–not reached) versus not reached (hazard ratio 0.73, 95% CI 0.50–1.08), and TTF favored C25 (hazard ratio 0.75, 95% CI 0.57–0.99). Conclusions Clinicians should consider the patient’s risk of clinically significant ADRs and prophylactic granulocyte colony stimulating factor when selecting the starting dose of cabazitaxel for CRPC. Some patients at high risk of ADRs or unfit patients may benefit from a lower starting dose of 20 mg/m2, whereas fit patients may be candidates for a starting dose of 25 mg/m2. Trial registration Not applicable.
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Affiliation(s)
- Hideyasu Matsuyama
- Department of Urology, Graduate School of Medicine, Yamaguchi University, Yamaguchi, Japan.
| | - Nobuaki Matsubara
- Department of Breast and Medical Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | | | | | - Shoko Tsukube
- Sanofi Genzyme Oncology Medical, Sanofi K.K., Tokyo, Japan.,Medical Affairs, Sanofi K.K., Tokyo, Japan
| | - Kazuhiro Suzuki
- Department of Urology, Gunma University Graduate School of Medicine, Maebashi, Japan
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Olaparib Outcomes in Patients with BRCA 1-2 Mutated, Platinum-Sensitive, Recurrent Ovarian Cancer in Croatia: A Retrospective Noninterventional Study. JOURNAL OF ONCOLOGY 2020; 2020:6423936. [PMID: 32655639 PMCID: PMC7322596 DOI: 10.1155/2020/6423936] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 06/01/2020] [Indexed: 12/25/2022]
Abstract
Our objective was to assess the safety and efficacy of olaparib in maintenance therapy of BRCA 1-2 mutated, platinum-sensitive, recurrent ovarian carcinoma after the partial or complete response to the second or further lines platinum-based chemotherapy in a real-world setting. We performed a multicenter, real-world observational population-based cohort study on the whole population of Croatian patients initiated to olaparib maintenance therapy between 2016 and 2020. The primary endpoints were progression-free survival and the discontinuation of treatment because of adverse events. We enrolled the total population of 69 patients with the median (interquartile range; IQR) age of 53 (48–59), 56 (81%) of them with BRCA1 mutation. The median (IQR) follow-up was 16 (9–25) months. Treatment had to be discontinued because of toxicity in 2 (3%) and temporarily interrupted in 14 (20%), while dose was reduced because of toxicity in 18 (26%) of patients. Toxicity of any grade was observed in 61 (88%) patients and toxicity of grade 3 or 4 in 12 (17%). Median progression-free survival was 21 (95% CI 16-not calculable) months from the introduction of olaparib, and the median overall survival was not reached. Our study confirmed efficacy and safety of olaparib as the maintenance therapy of BRCA 1-2 mutated, platinum-sensitive, recurrent ovarian carcinoma. We observed the real-world efficacy and safety comparable to those observed in the randomized controlled trials. We found the interesting observation of better efficacy of 300 mg tablets, compared to 400 mg capsules, an issue that should be addressed on much larger real-world populations.
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Templeton AJ, Booth CM, Tannock IF. Informing Patients About Expected Outcomes: The Efficacy-Effectiveness Gap. J Clin Oncol 2020; 38:1651-1654. [DOI: 10.1200/jco.19.02035] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Arnoud J. Templeton
- Department of Medical Oncology, St Claraspital Basel, and Faculty of Medicine, University of Basel, Basel, Switzerland
| | - Christopher M. Booth
- Division of Cancer Care and Epidemiology, Queen’s University Cancer Research Institute, Kingston, Ontario, Canada
| | - Ian F. Tannock
- Division of Medical Oncology & Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Engelbak Nielsen Z, Eriksson S, Schram Harsløf LB, Petri S, Helgesson G, Mangset M, Godskesen TE. Are cancer patients better off if they participate in clinical trials? A mixed methods study. BMC Cancer 2020; 20:401. [PMID: 32384883 PMCID: PMC7206768 DOI: 10.1186/s12885-020-06916-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 04/30/2020] [Indexed: 01/10/2023] Open
Abstract
Background Research and cancer care are closely intertwined; however, it is not clear whether physicians and nurses believe that clinical trials offer the best treatment for patients and, if so, whether this belief is justified. The aim of this study was therefore: (i) to explore how physicians and nurses perceive the benefits of clinical trial participation compared with standard care and (ii) whether it is justified to claim that clinical trial participation improves outcomes for cancer patients. Methods A mixed methods approach was used employing semi-structured interviews with 57 physicians and nurses in oncology and haematology and a literature review of the evidence for trial superiority, i.e. the idea that receiving treatment in a clinical trial leads to a better outcome compared with standard care. Inductive thematic analysis was used to examine the interview data. A literature review comprising nine articles was conducted according to a conceptual framework developed by Peppercorn et al. and evaluated recent evidence on trial superiority. Results Our findings show that many physicians and nurses make claims supporting trial superiority, however very little evidence is available in the literature comparing outcomes for trial participants and non-participants that supports their assertions. Conclusions Despite the recent rapid development and use of targeted therapy and immunotherapy, we find no support for trial participation to provide better outcomes for cancer patients than standard care. Hence, our present results are in line with previous results from Peppercorn et al. A weaker version of the superiority claim is that even if a trial does not bring about a direct positive effect, it brings about indirect positive effects. However, as the value of such indirect effects is dependent on the individual’s specific circumstances and preferences, their existence cannot establish the general claim that treatment in trials is superior. Belief in trial superiority is therefore unfounded. Hence, if such beliefs are communicated to patients in a trial recruitment context, it would provide misleading information. Instead emphasis should be on patients volunteering to give an altruistic contribution to the furthering of knowledge and to the potential benefit of future patients.
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Affiliation(s)
- Zandra Engelbak Nielsen
- Department of Oncology, Copenhagen University Hospital, Copenhagen, Section 5073, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Stefan Eriksson
- Centre for Research Ethics & Bioethics, Uppsala University, Box 564, 751 22, Uppsala, Sweden
| | - Laurine Bente Schram Harsløf
- Department of Oncology, Copenhagen University Hospital, Copenhagen, Section 5073, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Suzanne Petri
- Department of Oncology, Copenhagen University Hospital, Copenhagen, Section 5073, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Gert Helgesson
- Stockholm Centre for Healthcare Ethics (CHE), LIME, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Margrete Mangset
- Department of Geriatric Medicine, Oslo University Hospital, Kirkeveien 166, Bygg 20, 0450, Oslo, Norway
| | - Tove E Godskesen
- Centre for Research Ethics & Bioethics, Uppsala University, Box 564, 751 22, Uppsala, Sweden. .,Department of Health Care Sciences, Ersta Sköndal Bräcke University College, Box 11189, 100 61, Stockholm, Sweden.
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Rosenzweig B, Laitman Y, Zilberman DE, Raz O, Ramon J, Dotan ZA, Portnoy O. Effects of "real life" prostate MRI inter-observer variability on total needle samples and indication for biopsy. Urol Oncol 2020; 38:793.e13-793.e18. [PMID: 32303407 DOI: 10.1016/j.urolonc.2020.03.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 03/07/2020] [Accepted: 03/19/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE Prostate multiparametric magnetic resonance imaging (mpMRI) improves diagnosis of clinically significant cancer and reduces over-detection of nonsignificant cancer. Disagreement in the interpretation of mpMRI readings is well-known, with a reported discrepancy rate of 10% to 42%. We report the clinical repercussions of this variability on prostate biopsy candidates. MATERIALS AND METHODS Medical records of patients referred from 11 medical centers for MR-guided prostate biopsy (MRGpB) between October, 2017 and January, 2019 were retrospectively analyzed. Patients with at least one prostate imaging reporting and data system (PI-RADS) 3 or greater prostate lesion were selected, and the mpMRI studies (all read by others) were reviewed by our prostate mpMRI reader. Outcomes included changes in PI-RADS score and the subsequent effect on total needle samples and indication for biopsy. RESULTS Eighty-two patients with 128 lesions were suitable for analysis (mean age 66.5 ± 7.1 years, mean PSA 6.8 ± 8.5 ng/ml). Nine (11%) patients had suspicious rectal exams (T2a). Following our prostate mpMRI reader's imaging revisions, the PI-RADS score was downgraded in 66 (52%) lesions, upgraded in 15 (12%), and unchanged in 47 (37%), leaving a total of 84 suspected lesions (kappa = 0.17). Biopsy was deferred in 22 (27%) patients, and an estimated 136.4 (34.4%) samples were avoided (P = 0.0001 for both). There was a trend toward prostate size to correlate with imaging revision and abortion of biopsy (P = 0.06) while enrollment in active surveillance correlated with proof from such outcome (P = 0.007). CONCLUSION These data suggest that high interobserver disagreement in prostate mpMRIs from diverse institutes significantly affects prostate biopsy practice. The clinical consequences of this discord are significant.
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Affiliation(s)
- Barak Rosenzweig
- Department of Urology, Chaim Sheba Medical Center, Ramat Gan, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel; The Dr. Pinchas Borenstein Talpiot Medical Leadership Program 2013, Chaim Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.
| | - Yael Laitman
- Oncogenetics Unit, Institute of Human Genetics, and Meirav High Risk Clinic, Chaim Sheba Medical Center, Tel-Hashomer, Israel
| | - Dorit E Zilberman
- Department of Urology, Chaim Sheba Medical Center, Ramat Gan, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Orit Raz
- Assuta Ashdod University Hospital, Ashdod, Israel
| | - Jacob Ramon
- Department of Urology, Chaim Sheba Medical Center, Ramat Gan, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Zohar A Dotan
- Department of Urology, Chaim Sheba Medical Center, Ramat Gan, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Orith Portnoy
- The Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel; Department of Diagnostic Imaging, Chaim Sheba Medical Center, Ramat Gan, Israel
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Schulte B, Morgans AK, Shore ND, Pezaro C. Sorting Through the Maze of Treatment Options for Metastatic Castration-Sensitive Prostate Cancer. Am Soc Clin Oncol Educ Book 2020; 40:1-10. [PMID: 32182139 DOI: 10.1200/edbk_278845] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Since 1944, when Huggins and Hodges demonstrated the effectiveness of bilateral orchiectomy for metastatic prostate cancer (PCa), androgen deprivation therapy (ADT) has been the first-line treatment for men with advanced PCa. The proportion of PCa cases that are metastatic at diagnosis ranges globally, from 5%-20% in countries with widespread screening practices to upward of 30%-60% where screening is minimal. In the United States alone, there will be an estimated 191,000 new cases of PCa diagnosed in the year 2020, of which approximately 20% will be metastatic.1 Ongoing controversy around prostate-specific antigen (PSA) screening practices, increased access to novel imaging modalities, and a globally aging population will drive increased rates of metastatic castration-sensitive prostate cancer (mCSPC).2,3 At the same time, advances in upfront hormonal or chemohormonal therapy have driven a dramatic shift in treatment paradigms. In this article, we review recent advances in treatment choices for men with newly diagnosed mCSPC and the impact of upfront treatment on subsequent disease biology. Options include treatment with chemohormonal therapy, androgen receptor (AR)-directed therapy in addition to ADT, or, less commonly, ADT alone. Treatment choice must include consideration of clinical and disease characteristics, as well as patient preferences and limitations of geography and financial concerns.
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Affiliation(s)
- Brian Schulte
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL
| | - Alicia K Morgans
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL
| | - Neal D Shore
- Carolina Urologic Research Center, Myrtle Beach, SC
| | - Carmel Pezaro
- Yorkshire Cancer Research Weston Park Hospital, Sheffield, United Kingdom
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Deng K, Li H, Guan Y. Treatment Stratification of Patients with Metastatic Castration-Resistant Prostate Cancer by Machine Learning. iScience 2020; 23:100804. [PMID: 31978751 PMCID: PMC6976944 DOI: 10.1016/j.isci.2019.100804] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 11/22/2019] [Accepted: 12/19/2019] [Indexed: 11/28/2022] Open
Abstract
Prostate cancer is the most common cancer in men in the Western world. One-third of the patients with prostate cancer will develop resistance to hormonal therapy and progress into metastatic castration-resistant prostate cancer (mCRPC). Currently, docetaxel is a preferred treatment for mCRPC. However, about 20% of the patients will undergo early therapeutic failure owing to adverse events induced by docetaxel-based chemotherapy. There is an emergent need for a computational model that can accurately stratify patients into docetaxel-tolerable and docetaxel-intolerable groups. Here we present the best-performing algorithm in the Prostate Cancer DREAM Challenge for predicting adverse events caused by docetaxel treatment. We integrated the survival status and severity of adverse events into our model, which is an innovative way to complement and stratify the treatment discontinuation information. Critical stratification biomarkers were further identified in determining the treatment discontinuation. Our model has the potential to improve future personalized treatment in mCRPC.
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Affiliation(s)
- Kaiwen Deng
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
| | - Hongyang Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
| | - Yuanfang Guan
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA; Department of Internal Medicine, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA.
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Sundar S. Prostate cancer: trial data meet the real world. BMJ 2020; 368:m519. [PMID: 32051122 DOI: 10.1136/bmj.m519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Santhanam Sundar
- Nottingham University Hospitals NHS Trust, Nottingham NG5 1PB, UK
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Carrigan G, Whipple S, Capra WB, Taylor MD, Brown JS, Lu M, Arnieri B, Copping R, Rothman KJ. Using Electronic Health Records to Derive Control Arms for Early Phase Single-Arm Lung Cancer Trials: Proof-of-Concept in Randomized Controlled Trials. Clin Pharmacol Ther 2020; 107:369-377. [PMID: 31350853 PMCID: PMC7006884 DOI: 10.1002/cpt.1586] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 06/21/2019] [Indexed: 11/11/2022]
Abstract
Oncology drug development increasingly relies on single-arm clinical trials. External controls (ECs) derived from electronic health record (EHR) databases may provide additional context. Patients from a US-based oncology EHR database were aligned with patients from randomized controlled trials (RCTs) and trial-specific eligibility criteria were applied to the EHR dataset. Overall survival (OS) in the EC-derived control arm was compared with OS in the RCT experimental arm. The primary outcome was OS, defined as time from randomization or treatment initiation (EHR) to death. Cox regression models were used to obtain effect estimates using EHR data. EC-derived hazard ratio estimates aligned closely with those from the corresponding RCT with one exception. Comparing log HRs among all RCT and EC results gave a Pearson correlation coefficient of 0.86. Properly selected control arms from contemporaneous EHR data could be used to put single-arm trials of OS in advanced non-small cell lung cancer into context.
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Affiliation(s)
| | | | | | | | - Jeffrey S. Brown
- Department of Population MedicineHarvard Medical School and Harvard Pilgrim Health Care InstituteBostonMassachusettsUSA
| | - Michael Lu
- GenentechSouth San FranciscoCaliforniaUSA
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Gillessen S, Attard G, Beer TM, Beltran H, Bjartell A, Bossi A, Briganti A, Bristow RG, Chi KN, Clarke N, Davis ID, de Bono J, Drake CG, Duran I, Eeles R, Efstathiou E, Evans CP, Fanti S, Feng FY, Fizazi K, Frydenberg M, Gleave M, Halabi S, Heidenreich A, Heinrich D, Higano CTS, Hofman MS, Hussain M, James N, Kanesvaran R, Kantoff P, Khauli RB, Leibowitz R, Logothetis C, Maluf F, Millman R, Morgans AK, Morris MJ, Mottet N, Mrabti H, Murphy DG, Murthy V, Oh WK, Ost P, O'Sullivan JM, Padhani AR, Parker C, Poon DMC, Pritchard CC, Reiter RE, Roach M, Rubin M, Ryan CJ, Saad F, Sade JP, Sartor O, Scher HI, Shore N, Small E, Smith M, Soule H, Sternberg CN, Steuber T, Suzuki H, Sweeney C, Sydes MR, Taplin ME, Tombal B, Türkeri L, van Oort I, Zapatero A, Omlin A. Management of Patients with Advanced Prostate Cancer: Report of the Advanced Prostate Cancer Consensus Conference 2019. Eur Urol 2020; 77:508-547. [PMID: 32001144 DOI: 10.1016/j.eururo.2020.01.012] [Citation(s) in RCA: 272] [Impact Index Per Article: 54.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 01/10/2020] [Indexed: 01/06/2023]
Abstract
BACKGROUND Innovations in treatments, imaging, and molecular characterisation in advanced prostate cancer have improved outcomes, but there are still many aspects of management that lack high-level evidence to inform clinical practice. The Advanced Prostate Cancer Consensus Conference (APCCC) 2019 addressed some of these topics to supplement guidelines that are based on level 1 evidence. OBJECTIVE To present the results from the APCCC 2019. DESIGN, SETTING, AND PARTICIPANTS Similar to prior conferences, experts identified 10 important areas of controversy regarding the management of advanced prostate cancer: locally advanced disease, biochemical recurrence after local therapy, treating the primary tumour in the metastatic setting, metastatic hormone-sensitive/naïve prostate cancer, nonmetastatic castration-resistant prostate cancer, metastatic castration-resistant prostate cancer, bone health and bone metastases, molecular characterisation of tissue and blood, inter- and intrapatient heterogeneity, and adverse effects of hormonal therapy and their management. A panel of 72 international prostate cancer experts developed the programme and the consensus questions. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The panel voted publicly but anonymously on 123 predefined questions, which were developed by both voting and nonvoting panel members prior to the conference following a modified Delphi process. RESULTS AND LIMITATIONS Panellists voted based on their opinions rather than a standard literature review or formal meta-analysis. The answer options for the consensus questions had varying degrees of support by the panel, as reflected in this article and the detailed voting results reported in the Supplementary material. CONCLUSIONS These voting results from a panel of prostate cancer experts can help clinicians and patients navigate controversial areas of advanced prostate management for which high-level evidence is sparse. However, diagnostic and treatment decisions should always be individualised based on patient-specific factors, such as disease extent and location, prior lines of therapy, comorbidities, and treatment preferences, together with current and emerging clinical evidence and logistic and economic constraints. Clinical trial enrolment for men with advanced prostate cancer should be strongly encouraged. Importantly, APCCC 2019 once again identified important questions that merit assessment in specifically designed trials. PATIENT SUMMARY The Advanced Prostate Cancer Consensus Conference provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference, which has been held three times since 2015, aims to share the knowledge of world experts in prostate cancer management with health care providers worldwide. At the end of the conference, an expert panel discusses and votes on predefined consensus questions that target the most clinically relevant areas of advanced prostate cancer treatment. The results of the voting provide a practical guide to help clinicians discuss therapeutic options with patients as part of shared and multidisciplinary decision making.
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Affiliation(s)
- Silke Gillessen
- Oncology Institute of Southern Switzerland, Bellinzona, Switzerland; Universita della Svizzera Italiana, Lugano, Switzerland; Cantonal Hospital, St. Gallen, Switzerland; University of Bern, Bern, Switzerland; Division of Cancer Science, University of Manchester, Manchester, UK.
| | | | - Tomasz M Beer
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Himisha Beltran
- Dana-Farber Cancer Institute, Boston, MA, USA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Anders Bjartell
- Department of Urology, Skåne University Hospital, Malmö, Sweden
| | - Alberto Bossi
- Genito Urinary Oncology, Prostate Brachytherapy Unit, Goustave Roussy, Paris, France
| | - Alberto Briganti
- Unit of Urology/Division of Oncology, URI, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Milan, Italy
| | - Rob G Bristow
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; Christie NHS Trust, Manchester, UK; CRUK Manchester Institute and Cancer Centre, Manchester, UK
| | - Kim N Chi
- BC Cancer, Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Noel Clarke
- The Christie and Salford Royal Hospitals, Manchester, UK
| | - Ian D Davis
- Monash University and Eastern Health, Victoria, Australia
| | - Johann de Bono
- The Institute of Cancer Research/Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Charles G Drake
- Division of Haematology/Oncology, Columbia University Medical Center, New York, NY, USA
| | - Ignacio Duran
- Department of Medical Oncology, Hospital Universitario Marques de Valdecilla, IDIVAL, Santander, Cantabria, Spain
| | - Ros Eeles
- The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK
| | | | | | | | - Felix Y Feng
- University of California San Francisco, San Francisco, CA, USA
| | - Karim Fizazi
- Institut Gustave Roussy, University of Paris Sud, Villejuif, France
| | - Mark Frydenberg
- Department of Surgery, Monash University, Melbourne, Australia; Prostate Cancer Research Program, Monash University, Melbourne, Australia; Department Anatomy & Developmental Biology, Faculty of Nursing, Medicine & Health Sciences, Monash University, Melbourne, Australia
| | - Martin Gleave
- Urological Sciences, Vancouver Prostate Centre, University of British Columbia, Vancouver, Canada
| | - Susan Halabi
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Axel Heidenreich
- Department of Urology, Uro-Oncology, Robot-Assisted and Reconstructive Urology, University of Cologne, Cologne, Germany; Department of Urology, Medical University, Vienna, Austria
| | - Daniel Heinrich
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway
| | - Celestia Tia S Higano
- University of Washington, Seattle, WA, USA; Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Michael S Hofman
- Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Maha Hussain
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA
| | | | | | - Philip Kantoff
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA
| | - Raja B Khauli
- Department of Urology, American University of Beirut Medical Center, Beirut, Lebanon; Naef K. Basile Cancer Institute (NKBCI), American University of Beirut Medical Center, Beirut, Lebanon
| | - Raya Leibowitz
- Oncology institute, Shamir Medical Center and Faculty of medicine, Tel-Aviv University, Israel
| | - Chris Logothetis
- Department of Genitourinary Medical Oncology, MD Anderson Cancer Centre, Houston, TX, USA; Department of Clinical Therapeutics, David H. Koch Centre, University of Athens Alexandra Hospital, Athens, Greece
| | - Fernando Maluf
- Beneficiência Portuguesa de São Paulo, São Paulo, SP, Brazil; Departamento de Oncologia, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | | | - Alicia K Morgans
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA
| | | | | | - Hind Mrabti
- National Institute of Oncology, University hospital, Rabat, Morocco
| | - Declan G Murphy
- Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
| | | | - William K Oh
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, The Tisch Cancer Institute, New York, NY, USA
| | - Piet Ost
- Radiation Oncology, Ghent University Hospital, Ghent, Belgium
| | - Joe M O'Sullivan
- Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, Northern Ireland, UK; Radiotherapy Department, Cancer Centre, Belfast City Hospital, Belfast, Northern Ireland, UK
| | - Anwar R Padhani
- Mount Vernon Cancer Centre and Institute of Cancer Research, London, UK
| | - Chris Parker
- Royal Marsden Hospital and Institute of Cancer Research, Sutton, UK
| | - Darren M C Poon
- Comprehensive Oncology Centre, Hong Kong Sanatorium & Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Colin C Pritchard
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | | | - Mack Roach
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Mark Rubin
- Bern Center for Precision Medicine, Bern, Switzerland; Department for Biomedical Research, University of Bern, Bern, Switzerland
| | - Charles J Ryan
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Fred Saad
- Centre Hospitalier de Université de Montréal, Montreal, Canada
| | | | | | - Howard I Scher
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Neal Shore
- Carolina Urologic Research Center, Myrtle Beach, SC, USA
| | - Eric Small
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Matthew Smith
- Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | - Howard Soule
- Prostate Cancer Foundation, Santa Monica, CA, USA
| | - Cora N Sternberg
- Division of Hematology and Oncology, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Steuber
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | | | - Christopher Sweeney
- Dana-Farber Cancer Institute, Boston, MA, USA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Mary-Ellen Taplin
- Dana-Farber Cancer Institute, Boston, MA, USA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Levent Türkeri
- Department of Urology, M.A. Aydınlar Acıbadem University, Altunizade Hospital, Istanbul, Turkey
| | - Inge van Oort
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Almudena Zapatero
- Department of Radiation Oncology, University Hospital La Princesa, Health Research Institute, Madrid, Spain
| | - Aurelius Omlin
- University of Bern, Bern, Switzerland; Department of Medical Oncology and Haematology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
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Phillips CM, Parmar A, Guo H, Schwartz D, Isaranuwatchai W, Beca J, Dai W, Arias J, Gavura S, Chan KKW. Assessing the efficacy-effectiveness gap for cancer therapies: A comparison of overall survival and toxicity between clinical trial and population-based, real-world data for contemporary parenteral cancer therapeutics. Cancer 2020; 126:1717-1726. [PMID: 31913522 DOI: 10.1002/cncr.32697] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 11/29/2019] [Accepted: 12/09/2019] [Indexed: 12/16/2022]
Abstract
BACKGROUND Although increasing evidence has suggested that an efficacy-effectiveness gap exists between clinical trial (CT) and real-world evidence (RWE), to the authors' knowledge, the magnitude of this difference remains undercharacterized. The objective of the current study was to quantify the magnitude of survival and toxicity differences between CT and RWE for contemporary cancer systemic therapies. METHODS Patients receiving cancer therapies funded under Cancer Care Ontario's New Drug Funding Program (NDFP) were identified. Landmark CTs with data regarding survival and adverse events (AEs) for each drug indication were identified. RWE for survival and hospitalization rates during treatment were ascertained through Canadian population-based databases. The efficacy-effectiveness gap for each drug indication was calculated as the difference between RWE and CT data for median overall survival (OS), 1-year OS, and generated hazard ratios (HRs) with 95% CIs from Kaplan-Meier OS curves. Toxicity differences were calculated as the difference between RWE of hospitalization rates and CT serious AE rates. RESULTS Twenty-nine indications from 20 systemic therapies were included. Twenty-eight of 29 indications (97%) demonstrated worse survival in RWE, with a median OS difference of 5.2 months (interquartile range, 3.0-12.1 months). Lower effectiveness in RWE also was demonstrated through a meta-analysis of an OS hazard ratio of 1.58 (95% CI, 1.39-1.80). The median difference between RWE for hospitalization rates and CT serious AEs was 14% (95% CI, 9%-22%). CONCLUSIONS An efficacy-effectiveness gap exists for contemporary cancer systemic therapies, with a 5.2-month lower median OS observed in RWE compared with CT data. These data supports the use of RWE to better inform real-world decision making regarding the use of cancer systemic therapies.
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Affiliation(s)
- Cameron M Phillips
- Division of Medical Oncology and Hematology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ambica Parmar
- Division of Medical Oncology and Hematology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Helen Guo
- Cancer Care Ontario, Toronto, Ontario, Canada
| | | | - Wanrudee Isaranuwatchai
- Division of Medical Oncology and Hematology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Canadian Centre for Applied Research in Cancer Control, Toronto, Ontario, Canada
| | - Jaclyn Beca
- Cancer Care Ontario, Toronto, Ontario, Canada.,Canadian Centre for Applied Research in Cancer Control, Toronto, Ontario, Canada
| | - Wei Dai
- Cancer Care Ontario, Toronto, Ontario, Canada.,Canadian Centre for Applied Research in Cancer Control, Toronto, Ontario, Canada
| | | | | | - Kelvin K W Chan
- Division of Medical Oncology and Hematology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Cancer Care Ontario, Toronto, Ontario, Canada.,Canadian Centre for Applied Research in Cancer Control, Toronto, Ontario, Canada
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44
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Labeur TA, Berhane S, Edeline J, Blanc J, Bettinger D, Meyer T, Van Vugt JLA, Ten Cate DWG, De Man RA, Eskens FALM, Cucchetti A, Bonnett LJ, Van Delden OM, Klümpen H, Takkenberg RB, Johnson PJ. Improved survival prediction and comparison of prognostic models for patients with hepatocellular carcinoma treated with sorafenib. Liver Int 2020; 40:215-228. [PMID: 31579990 PMCID: PMC6973249 DOI: 10.1111/liv.14270] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 09/18/2019] [Accepted: 09/19/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND The 'Prediction Of Survival in Advanced Sorafenib-treated HCC' (PROSASH) model addressed the heterogeneous survival of patients with hepatocellular carcinoma (HCC) treated with sorafenib in clinical trials but requires validation in daily clinical practice. This study aimed to validate, compare and optimize this model for survival prediction. METHODS Patients treated with sorafenib for HCC at five tertiary European centres were retrospectively staged according to the PROSASH model. In addition, the optimized PROSASH-II model was developed using the data of four centres (training set) and tested in an independent dataset. These models for overall survival (OS) were then compared with existing prognostic models. RESULTS The PROSASH model was validated in 445 patients, showing clear differences between the four risk groups (OS 16.9-4.6 months). A total of 920 patients (n = 615 in training set, n = 305 in validation set) were available to develop PROSASH-II. This optimized model incorporated fewer and less subjective parameters: the serum albumin, bilirubin and alpha-foetoprotein, and macrovascular invasion, extrahepatic spread and largest tumour size on imaging. Both PROSASH and PROSASH-II showed improved discrimination (C-index 0.62 and 0.63, respectively) compared with existing prognostic scores (C-index ≤0.59). CONCLUSIONS In HCC patients treated with sorafenib, individualized prediction of survival and risk group stratification using baseline prognostic and predictive parameters with the PROSASH model was validated. The refined PROSASH-II model performed at least as good with fewer and more objective parameters. PROSASH-II can be used as a tool for tailored treatment of HCC in daily practice and to define pre-planned subgroups for future studies.
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Affiliation(s)
- Tim A. Labeur
- Cancer Center AmsterdamAmsterdamThe Netherlands,Department of Medical OncologyAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands,Department of Gastroenterology and HepatologyAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands,Department of Radiology and Nuclear MedicineAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Sarah Berhane
- Department of BiostatisticsUniversity of LiverpoolLiverpoolUK
| | | | | | - Dominik Bettinger
- Department of Medicine IIMedical Center University of FreiburgFaculty of MedicineUniversity of FreiburgFreiburgGermany
| | - Tim Meyer
- UCL Cancer InstituteUniversity College LondonLondonUK
| | | | - David W. G. Ten Cate
- Department of SurgeryErasmus MC University Medical CenterRotterdamThe Netherlands
| | - Robert A. De Man
- Department of Gastroenterology and HepatologyErasmus MC University Medical CenterRotterdamThe Netherlands
| | - Ferry A. L. M. Eskens
- Department of Medical OncologyErasmus MC University Medical CenterRotterdamThe Netherlands
| | - Alessandro Cucchetti
- Department of Medical and Surgical SciencesAlma Mater StudiorumUniversity of BolognaBolognaItaly
| | | | - Otto M. Van Delden
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Heinz‐Josef Klümpen
- Department of Medical OncologyAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - R. Bart Takkenberg
- Department of Gastroenterology and HepatologyAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Philip J. Johnson
- Department of Molecular and Clinical Cancer MedicineUniversity of LiverpoolLiverpoolUK
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Di Maio M, Perrone F, Conte P. Real-World Evidence in Oncology: Opportunities and Limitations. Oncologist 2019; 25:e746-e752. [PMID: 31872939 DOI: 10.1634/theoncologist.2019-0647] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 11/13/2019] [Indexed: 12/22/2022] Open
Affiliation(s)
- Massimo Di Maio
- Department of Oncology, University of Turin; Ordine Mauriziano Hospital, Torino, Italy
| | - Francesco Perrone
- Clinical Trial Unit, National Cancer Institute, IRCCS Fondazione Pascale, Napoli, Italy
| | - Pierfranco Conte
- Department of Surgery, Oncology and Gastroenterology, University of Padova and Oncologia Medica 2, Istituto Oncologico Veneto, I.R.C.C.S., Padova, Italy
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Cheng S, Arciero V, Goldberg H, Tajzler C, Manganaro A, Kozlowski N, Rowbottom L, McDonald R, Chow R, Vasisht G, Shaji S, Wong ECL, Petrovic M, Zhang L, Phillips C, Zalewski P, Kapoor A, Fleshner NE, Chow E, Emmenegger U. Population-Based Analysis Of The Use Of Radium-223 For Bone-Metastatic Castration-Resistant Prostate Cancer In Ontario, And Of Factors Associated With Treatment Completion And Outcome. Cancer Manag Res 2019; 11:9307-9319. [PMID: 31802949 PMCID: PMC6827438 DOI: 10.2147/cmar.s213051] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 09/25/2019] [Indexed: 11/23/2022] Open
Abstract
Introduction Radium-223 (Ra223) prolongs the survival and improves the quality of life of men with metastatic, castration-resistant prostate cancer (mCRPC) to bones. However, compared to other mCRPC therapies, using Ra223 comes with its unique challenges. Hence, we aimed to identify Ra223 utilization patterns under real-world conditions, as well as factors predicting treatment completion and outcome. Methods In this retrospective chart analysis, 198 mCRPC patients were identified that had received Ra223 outside of clinical trials or access programs from January 2015 to October 2016 at four cancer centres in Ontario. The main outcomes studied were Ra223 completion rate, reasons for early treatment discontinuation, overall survival, and survival differences in patients completing Ra223 therapy versus patients receiving <6 cycles of Ra223. In addition, patient and disease characteristics were analysed to identify predictors of treatment completion and survival. Results In this cohort of patients mostly pretreated with abiraterone and/or enzalutamide (92.4%), almost half of which had also received docetaxel (48.5%), the Ra223 completion rate was 46.5%, and the actuarial median survival was 13.3 months. The main reason for early Ra223 discontinuation was disease progression, and Ra223 non-completion was associated with poorer outcome (median survival 8.1 months [6.0-12.2] versus 18.7 months [15.3-22.3] in men completing Ra223, p<0.0001). Lymph node metastases and a high baseline prostate-specific antigen (PSA) were independent predictors of early treatment discontinuation. Multivariable Cox proportional hazards models revealed early Ra223 discontinuation, baseline anemia, high PSA, prior skeletal-related events, visceral metastases, and being referred to another centre for Ra223 therapy as predictors of worse outcome. Conclusion Despite a lower completion rate than observed under clinical trial conditions, the real-world results achieved with Ra223 are encouraging. If prospectively validated, predictive patient and disease characteristics identified in our cohort might become instrumental to identify mCRPC patients likely to complete and to most benefit from Ra223 therapy.
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Affiliation(s)
- Sierra Cheng
- Sunnybrook Odette Cancer Centre, Toronto, Ontario, Canada
| | | | - Hanan Goldberg
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | | | | | | | | | | | - Ronald Chow
- Sunnybrook Odette Cancer Centre, Toronto, Ontario, Canada
| | | | - Sharon Shaji
- Juravinski Cancer Centre, Hamilton, Ontario, Canada
| | | | | | - Liying Zhang
- Sunnybrook Odette Cancer Centre, Toronto, Ontario, Canada
| | | | | | - Anil Kapoor
- Juravinski Cancer Centre, Hamilton, Ontario, Canada
| | | | - Edward Chow
- Sunnybrook Odette Cancer Centre, Toronto, Ontario, Canada
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Sweeney CJ, Beltran H. The Balancing Act: Assessing Treatment Burden Versus Treatment Benefit with Evolving Metastatic Hormone-sensitive Prostate Cancer Data. Eur Urol 2019; 76:729-731. [PMID: 31590937 DOI: 10.1016/j.eururo.2019.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 09/10/2019] [Indexed: 11/26/2022]
Affiliation(s)
| | - Himisha Beltran
- Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA
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Kapoor A, Wong NC, Wang Y, Mukherjee S, Hotte S, Dayes I, Lukka H. Single-center experience with radium-223 in patients with castration-resistant prostate cancer and bone metastases. Asian J Androl 2019; 22:437-438. [PMID: 31535625 PMCID: PMC7406098 DOI: 10.4103/aja.aja_66_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Affiliation(s)
- Anil Kapoor
- Division of Urology, Department of Surgery, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Nathan C Wong
- Division of Urology, Department of Surgery, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Yuding Wang
- Division of Urology, Department of Surgery, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Som Mukherjee
- Department of Oncology, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Sebastien Hotte
- Department of Oncology, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Ian Dayes
- Department of Oncology, McMaster University, Hamilton, ON L8N 4A6, USA
| | - Himu Lukka
- Department of Oncology, McMaster University, Hamilton, ON L8N 4A6, USA
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Mortality and Hospitalization Risk Following Oral Androgen Signaling Inhibitors Among Men with Advanced Prostate Cancer by Pre-existing Cardiovascular Comorbidities. Eur Urol 2019; 77:158-166. [PMID: 31420248 DOI: 10.1016/j.eururo.2019.07.031] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 07/12/2019] [Indexed: 11/23/2022]
Abstract
BACKGROUND Elderly patients (≥65yr) with advanced prostate cancer and cardiovascular disease (CVD) conditions are often excluded from clinical trials of abiraterone acetate (AA) or enzalutamide (ENZ). Consequently, little is known about the effects of these medications on these vulnerable patients. OBJECTIVE To assess the short-term outcomes of AA and ENZ in patients with pre-existing CVDs. DESIGN, SETTING, AND PARTICIPANTS A population-based retrospective study. The Surveillance, Epidemiology, and End Results-Medicare-linked database was used to identify prostate cancer patients using AA or ENZ. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The primary endpoint was 6-mo all-cause mortality, analyzed using modified Poisson regression modeling of relative risk (RR) adjusted for confounders and comorbidities. RESULTS AND LIMITATIONS Among eligible patients (2845 with AA and 1031 with ENZ), 67% had at least one pre-existing CVD. Compared with those without pre-existing CVDs, having one to two pre-existing CVDs was associated with 16% higher 6-mo mortality (RR=1.16, 95% confidence interval [CI]: 1.00-1.36), and the risk increased further among those having three or more CVDs (RR=1.56, 95% CI: 1.29-1.88). Most of the differences in survival of patients with pre-existing CVD condition occurred within the first 6mo of treatment. CONCLUSIONS After treatment with AA or ENZ, elderly prostate cancer patients with pre-existing CVDs experienced higher short-term mortality than otherwise similar patients without CVDs. Mortality associated with CVDs did not depend on having received AA versus ENZ. PATIENT SUMMARY Patients with pre-existing cardiovascular diseases (CVDs) experienced higher short-term mortality after abiraterone acetate or enzalutamide than those without pre-existing CVDs. It is recommended that a multidisciplinary team, including a cardiologist, evaluate patients having pre-existing CVDs in the process of making treatment decisions and monitoring potential side effects.
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Seyednasrollah F, Koestler DC, Wang T, Piccolo SR, Vega R, Greiner R, Fuchs C, Gofer E, Kumar L, Wolfinger RD, Kanigel Winner K, Bare C, Neto EC, Yu T, Shen L, Abdallah K, Norman T, Stolovitzky G, Soule HR, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Elo LL, Zhou FL, Guinney J, Costello JC. A DREAM Challenge to Build Prediction Models for Short-Term Discontinuation of Docetaxel in Metastatic Castration-Resistant Prostate Cancer. JCO Clin Cancer Inform 2019; 1:1-15. [PMID: 30657384 PMCID: PMC6874023 DOI: 10.1200/cci.17.00018] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Purpose Docetaxel has a demonstrated survival benefit for patients with metastatic castration-resistant prostate cancer (mCRPC); however, 10% to 20% of patients discontinue docetaxel prematurely because of toxicity-induced adverse events, and the management of risk factors for toxicity remains a challenge. Patients and Methods The comparator arms of four phase III clinical trials in first-line mCRPC were collected, annotated, and compiled, with a total of 2,070 patients. Early discontinuation was defined as treatment stoppage within 3 months as a result of adverse treatment effects; 10% of patients discontinued treatment. We designed an open-data, crowd-sourced DREAM Challenge for developing models with which to predict early discontinuation of docetaxel treatment. Clinical features for all four trials and outcomes for three of the four trials were made publicly available, with the outcomes of the fourth trial held back for unbiased model evaluation. Challenge participants from around the world trained models and submitted their predictions. Area under the precision-recall curve was the primary metric used for performance assessment. Results In total, 34 separate teams submitted predictions. Seven models with statistically similar area under precision-recall curves (Bayes factor ≤ 3) outperformed all other models. A postchallenge analysis of risk prediction using these seven models revealed three patient subgroups: high risk, low risk, or discordant risk. Early discontinuation events were two times higher in the high-risk subgroup compared with the low-risk subgroup. Simulation studies demonstrated that use of patient discontinuation prediction models could reduce patient enrollment in clinical trials without the loss of statistical power. Conclusion This work represents a successful collaboration between 34 international teams that leveraged open clinical trial data. Our results demonstrate that routinely collected clinical features can be used to identify patients with mCRPC who are likely to discontinue treatment because of adverse events and establishes a robust benchmark with implications for clinical trial design.
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Affiliation(s)
- Fatemeh Seyednasrollah
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Devin C Koestler
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Tao Wang
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Stephen R Piccolo
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Roberto Vega
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Russell Greiner
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Christiane Fuchs
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Eyal Gofer
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Luke Kumar
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Russell D Wolfinger
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Kimberly Kanigel Winner
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Chris Bare
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Elias Chaibub Neto
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Thomas Yu
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Liji Shen
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Kald Abdallah
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Thea Norman
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Gustavo Stolovitzky
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Howard R Soule
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Christopher J Sweeney
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Charles J Ryan
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Howard I Scher
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Oliver Sartor
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Laura L Elo
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Fang Liz Zhou
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - Justin Guinney
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
| | - James C Costello
- Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA
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