Real-world use and clinical impact of an electronic patient-reported outcome tool in patients with solid tumors treated with immuno-oncology therapy

BACKGROUND

Utilization of electronic patient-reported outcome (ePRO) tools to monitor symptoms in patients undergoing cancer treatment has shown clinical benefits. Tennessee Oncology (TO) implemented an ePRO platform in 2019, allowing patients to report their health status online. We conducted a real-world, multicenter, observational, non-interventional cohort study to evaluate utilization of this platform in adults with solid tumors who initiated immuno-oncology (IO) therapy as monotherapy or in combination at TO clinics.

METHODS

Patients initiating IO therapy prior to platform implementation were included in a historical control (HC) cohort; those initiating treatment after implementation were included in the ePRO cohort, which was further divided into ePRO users (platform enrollment ≤ 45 days from IO initiation) and non-users. Data were extracted from electronic medical records; patients were followed for up to 6 months (no minimum follow up). Outcomes included patient characteristics, treatment patterns, duration of therapy (DoT), and overall survival (OS).

RESULTS

Data were collected for 538 patients in the HC and 1014 in the ePRO cohort; 319 in the ePRO cohort were ePRO users (uptake rate 31%). Baseline age was higher, more patients had stage IV disease at diagnosis, and more received monotherapy (82 vs 52%, respectively) in the HC vs the ePRO cohort. Median follow-up was 181.0 days (range 0.0-182.6) in the HC and 175.0 (0.0-184.0) in the ePRO cohort. Median DoT of index IO regimen was 5.1 months (95% confidence interval [CI], 4.4-NE) in the HC cohort vs not estimable (NE) in the ePRO cohort. Multivariable regression adjusting for baseline differences confirmed lower risk of treatment discontinuation in the ePRO vs HC cohort: hazard ratio (HR) 0.83 (95% CI, 0.71-0.97); p < 0.05. The estimated 6-month OS rate was 65.5% in the HC vs 72.4% in the ePRO cohort (p < 0 .01). Within the ePRO cohort, DoT of index IO regimen and OS did not differ between users and non-users. In ePRO users, patient platform use was durable over 6 months.

CONCLUSION

Improvements in DoT and OS were seen after ePRO platform implementation. Conclusions are limited by challenges in separating the impact of platform implementation from other changes affecting outcomes.

Building Efficiency and Scaling With a Remote Genetic Counseling Program

Purpose A third-party telemedicine (TM) genetic counseling program was initiated at a large community oncology practice spanning 35 clinical sites with 110 clinicians and 97 advanced practice providers throughout Tennessee and Georgia. Patients and Methods Appropriate patients were referred through the electronic health record (EHR) based on current National Comprehensive Cancer Network guidelines. A combination of TM and genetic counseling assistants enhanced convenience, broadened access, and decreased no-show rates. Physician education for mutation-positive screening recommendations was provided through deep integration of dedicated genetic counseling notes in the EHR. Results From 2019 to 2022, the program expanded from 1 to 20 clinics with referrals growing from 195 to 885. An average of 82% of patients completed genetic counseling consultations over TM with more than 70% completing genetic testing. The average was 4 to 6 days from referral to consultation. The no-show rate was maintained at less than 7%. In 2023, this model supported all 35 clinics across the state. Conclusion Our program illustrates how remote genetic counseling programs are an effective choice for scaling genetics care across a large community oncology practice. Deep integration of TM genetic counseling within the EHR helps identify patients who are high risk and improves test adoption, patient keep rate, and turnaround time, helping to achieve better patient outcomes.

Health care resource utilization, quality metrics, and costs of bladder cancer within the Oncology Care Model

OBJECTIVES

New and emerging therapies have significantly changed the bladder cancer (BC) treatment landscape and can potentially affect spending and patient care in CMS' Oncology Care Model (OCM), a service delivery and payment model for voluntarily participating practices. The objectives of this analysis were to estimate health care resource utilization (HCRU) and benchmark spending per OCM episode of BC, and to model spending drivers and quality metrics.

STUDY DESIGN

Retrospective cohort study.

METHODS

A retrospective cohort study was conducted of OCM episodes triggered by receipt of anticancer therapy among Medicare beneficiaries from 2016 to 2018. Based on this, an average performance estimation was conducted to assess the impact of hypothetical changes in novel therapy use by OCM practices.

RESULTS

BC accounted for approximately 3% (n = 60,099) of identified OCM episodes. Relative to low-risk episodes, high-risk episodes were associated with greater HCRU and worse OCM quality metrics. Mean spending per high-risk episode was $37,857 (low-risk episode: $9204), with $11,051 spent on systemic therapies and $7158 on inpatient services. In the estimation, high- and low-risk BC exceeded the spending target by 1.7% and 9.4%, respectively. This did not affect payments to practices and no retrospective payments were necessary.

CONCLUSIONS

As 3% of OCM episodes were attributed to BC, with only one-third classified as high-risk, controlling expenditure on novel therapies for advanced BC is unlikely to affect overall practice performance. The average performance estimation further emphasized the minimal impact that novel therapy spending in high-risk BC has on OCM payments to practices.

Impact of early detection on cancer curability: A modified Delphi panel study

Expert consensus on the potential benefits of early cancer detection does not exist for most cancer types. We convened 10 practicing oncologists using a RAND/UCLA modified Delphi panel to evaluate which of 20 solid tumors, representing >40 American Joint Committee on Cancer (AJCC)-identified cancer types and 80% of total cancer incidence, would receive potential clinical benefits from early detection. Pre-meeting, experts estimated how long cancers take to progress and rated the current curability and benefit (improvement in curability) of an annual hypothetical multi-cancer screening blood test. Post-meeting, experts rerated all questions. Cancers had varying estimates of the potential benefit of early cancer detection depending on estimates of their curability and progression by stage. Cancers rated as progressing quickly and being curable in earlier stages (stomach, esophagus, lung, urothelial tract, melanoma, ovary, sarcoma, bladder, cervix, breast, colon/rectum, kidney, uterus, anus, head and neck) were estimated to be most likely to benefit from a hypothetical screening blood test. Cancer types rated as progressing quickly but having comparatively lower cure rates in earlier stages (liver/intrahepatic bile duct, gallbladder, pancreas) were estimated to have medium likelihood of benefit from a hypothetical screening blood test. Cancer types rated as progressing more slowly and having higher curability regardless of stage (prostate, thyroid) were estimated to have limited likelihood of benefit from a hypothetical screening blood test. The panel concluded most solid tumors have a likelihood of benefit from early detection. Even among difficult-to-treat cancers (e.g., pancreas, liver/intrahepatic bile duct, gallbladder), early-stage detection was believed to be beneficial. Based on the panel consensus, broad coverage of cancers by screening blood tests would deliver the greatest potential benefits to patients.

Real-world use and clinical impact of electronic patient-reported outcomes (ePROs) in patients with solid tumors treated with immuno-oncology (IO) therapy

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Background: Patients with cancer can experience disease- and treatment-related symptoms that are underreported and underestimated by physicians. This observational, non-interventional study evaluated the use of ePROs and their impact on duration of treatment (DoT) in patients with solid tumors receiving IO therapy in community practice. Methods: Patients initiating index IO therapy immediately prior to (Jan-2017 to Dec-2018) and after (Sep-2019 to Dec-2020) implementation of Noona, the ePRO platform at Tennessee Oncology clinics, were included in a retrospective historical control (HC) and ePRO cohort, respectively, and followed for up to 6 months. The ePRO cohort was further divided into ePRO users (platform enrollment ≤45 days from index) and non-users. ePRO questionnaires, based on Common Terminology Criteria for Adverse Events (CTCAE), were sent within a week after each IO infusion and could be completed using an internet browser or smartphone app. Patient characteristics and DoT were described and compared between the HC and ePRO cohorts and between the HC cohort and ePRO users subgroup. Use of ePROs was evaluated within the ePRO cohort. Differences in baseline characteristics between cohorts were adjusted using Cox proportional hazards models. Results: Data were collected for 538 HC and 1014 ePRO patients (319 ePRO users and 695 non-users). Patient characteristics were generally similar between cohorts, but more HC patients were diagnosed with Stage IV disease (54% vs 47%; p < 0.01) and initiated IO as monotherapy (82% vs 52%), while more ePRO patients initiated IO as combination therapy (48% vs 18%). ePRO users were more likely than non-users to be female, white, married, living with a spouse, and have higher education (college or graduate degree) (all p < 0.05). Use of ePROs was durable over follow-up, with a consistent number of questionnaires sent over Months 1-3 and Months 4-6 (median: 6 questionnaires in each period) and a slight decrease in the number answered (median: 4 vs 3 questionnaires). ePRO patients had a longer DoT than HC patients (median time to end of first IO regimen: not estimable vs 5.1 months). Significantly more ePRO than HC patients remained on their first IO regimen at 6 months (54% vs 46%; p < 0.05). Multivariate Cox regression showed the risk of ending first IO therapy was lower for ePRO versus HC patients (p < 0.05). Conclusions: The increased DoT observed in the ePRO versus HC cohort in this study suggests that use of ePROs may facilitate improved care coordination and enable patients to remain on IO therapy longer. However, ePRO uptake was only 31% in the ePRO cohort, with several social determinants appearing to influence use. Overcoming barriers in ePRO uptake is an area for future study.

Implementation of a telemedicine-based genetic counseling program in a large community oncology practice

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Background: Genetic testing is an integral part of cancer care. To optimally facilitate testing, genetic counselors (GC) provide interpretation and direction for treatments in certain applicable solid tumors. A telemedicine (TM) genetic counseling program was initiated in 2019 at Tennessee Oncology, a large community oncology practice spanning over 30 clinical sites throughout Tennessee and Georgia. Methods: Appropriate patients were identified and referred through the Electronic Medical Record (EMR) for genetic testing based on current National Comprehensive Cancer Network (NCCN) guidelines. All counseling sessions were scheduled over TM to the patient’s home to enhance convenience, broaden access, and decrease no-show rates. Physician education regarding result-dependent appropriate screening recommendations per NCCN for mutation positive patients were provided through email communication and dedicated GC notes in the EMR. Results: Between 2019 and 2021, GC referrals per year grew from 195 to 840. Of these referrals, 84.6% of patients completed GC consultations, all of which were facilitated through TM. Of completed consultations, 81.4% underwent testing. Average time from referral to GC consultation was 8-13 business days. The no-show rate was low (< 7%). This program started at 1 clinic in 2019 and is now offered for patient care in 16 clinics across the state. Conclusions: Our program illustrates how remote GC programs are an effective choice for scaling genetics care across a large community oncology practice. Deep integration of TM-based genetic counseling within the EMR helps identify high-risk patients, improves test adoption, patient keep-rate and turn-around-time therefore helping to better patient outcomes. This quality assurance program is an important part of comprehensive cancer care that we can provide to our patients and their families.

Differences in the utilization of palliative care support services among patients with metastatic solid tumor cancer in a community oncology setting: A retrospective review

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Background: Palliative care has been underutilized in the setting of advanced cancer despite its established benefit in improving the quality of life in cancer patients. Few studies have evaluated socioeconomic disparities in receiving palliative care in the outpatient oncology setting. We aimed to evaluate for disparities in utilization of palliative care among patients with metastatic solid tumor malignancies at Tennessee Oncology, a large outpatient community oncology practice with an established palliative care program. Methods: We completed a retrospective review of medical records of 1513 patients that were seen in Tennessee Oncology clinics from 12/2020 to 12/2021. We compared the baseline characteristics of patients with metastatic solid tumor malignancies who did and did not receive palliative care. Chi-square and two-sample t-tests were used for data analysis with the 5% significance level using R statistical software. Results: Male patients utilized palliative care less often than female patients (17% versus 24% for females, p =.0002; 95% CI,.05-1.0). Of payer types, Medicare had the least palliative care utilization (14%) compared to commercial (25%) and other payers (23%). Utilization also varied by cancer type, with melanoma (9%), lung cancer (15%) and renal cancer (21%) being least likely to receive palliative care (p <.00005; 95% CI,.19-1.0). We did examine racial differences in palliative care utilization, but those did not reach statistical significance. Conclusions: There are multiple disparities in the utilization of on-site palliative care support services among patients with metastatic solid tumor cancer in this outpatient community oncology setting. Further research is needed to gain insight into why this is, including an in-depth analysis of both patient and provider utilization/referral practices.[Table: see text]

Implementation of a scalable integrative oncology (IO) program in a large community oncology network

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Background: Integrative Oncology (IO) has become a specialized area of cancer care because of patient desire for holistic approach to care and in response to unmet symptom burden. Until now most IO programs have been limited to large academic medical centers. At Tennessee Oncology (TO), a large community oncology program spanning over 30 clinical sites of care throughout Tennessee and Georgia, an IO program was developed and implemented to bring IO to patients in the community. Methods: In June 2021, the IO program was launched with a physician and a nurse practitioner, both trained in Integrative Oncology. The program started at 8 clinics with visits primarily performed through telemedicine to allow access to each clinic. Providers were educated via email communication and a short video describing the program. Patient education was provided through our website and flyers placed in clinics. A referral order was created within the electronic health record. Results: Within one year, the IO program grew from seeing less than 20 patients per month to seeing over 100 patients per month. To date we have provided approximately 1,050 IO visits for 432 unique patients. Of these patients, 362 (83%) were female and 70 were male. The average age was 59 years old. The top three associated malignancies for patients were breast (n = 182), colorectal (n = 30), and gynecologic oncology (n = 29). Our IO program has expanded from eight to 16 clinics during this time frame. 75% of visits were provided through telemedicine. The most common reasons for IO referral were nutrition and symptom management (fatigue, neuropathy, etc). Conclusions: Implementation of an IO program is possible and scalable in a large community oncology setting. Future directions include studying the impact of our program on patient experience and overall health and wellness.

Provider-led advance care planning in community oncology: A successful multidisciplinary quality improvement intervention

209

Background: Advanced care planning (ACP) is an important aspect of shared decision making in cancer treatment. Due to its importance, in 2016, Medicare expanded coverage and reimbursement for advance care planning (ACP) services (CPT codes 99497 and 99498). Despite this, ACP has been underutilized in practice. Methods: Tennessee Oncology aimed to increase knowledge and utilization of this service by medical oncologists and advance practice providers and corresponding CPT codes through an educational and quality improvement project. We formed a multidisciplinary team with individuals representing medical oncology providers, palliative care team, billing and accounting, information technology and informatics, nursing, navigation team, and operations. This team created an educational video, incorporating the “PAUSE” framework for addressing advance care planning and its role in community oncology, and details of documentation and billing. We also built in documentation templates into the medical oncology note and created a process to automate the charge capture to avoid additional steps for oncology providers. Results: Prior to this initiative, there was no baseline method to measure ACP and corresponding documentation. After two months of launching our educational video and new documentation templates, 120 documented ACP discussions were completed. ACP documentation was performed by 61 total providers practicing across 16 clinics. Providers completing documentation included both medical oncology (n = 53, 86%) and palliative care (n = 8). Of medical oncology providers, 39 (73%) were physicians and 14 (27%) were advanced practice providers. The three most common cancer diagnoses in ACP encounters were lung (20%), breast (13%), and prostate (8%). Conclusions: This combination of education and automation with multidisciplinary team input helped establish a baseline for ACP measurement that will help identify gaps and improve ACP discussions and documentation in our practice going forward.

Growth and scalability of a palliative care program in a large community oncology practice

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Background: Tennessee Oncology (TO) is a large community oncology practice with over 180 oncology providers spanning over 30 clinics throughout Tennessee and northern Georgia. In 2017, TO began embedding palliative care (PC) providers in clinics. However, the program growth was slow and by the end of 2019, TO offered PC services within only five clinics. In early 2020, TO implemented various initiatives to expand access and improve utilization of palliative care. Methods: In May 2020, TO hired a palliative care physician to grow and oversee the program. TO physician leadership established and communicated the importance of PC to providers and began providing feedback to each provider on utilization of PC for metastatic lung and pancreatic cancer patients. These diseases were selected due to poor prognosis, high morbidity, and known benefit of palliative care. Expansion of telemedicine reimbursement helped our PC team offer in person and telemedicine visits. Increasing demand allowed for expansion of the team and hiring of additional physicians, advanced practice providers (APPs), and a PC nurse coordinator to provide triage, follow-up and scheduling for PC providers. Results: Between the end of 2019 and the end of 2021, the average number of PC visits per quarter (averaged across three quarters) increased from 1,279 to 2,480, representing a growth of 194%. During this time, TO provided over 19,600 PC visits for 3,955 unique patients, of which 53% were female and 47% were male. Of visits provided, 40% were performed through telemedicine. The program has grown from five providers to 11 providers (three physicians, eight APPs). The number of clinics offering in person PC services has grown from five to 13. The three most common malignancies associated with patient visits were lung (16%), breast (10%), and colorectal (7%). Conclusions: Embedding palliative care within a large community oncology practice is feasible and can grow rapidly. A combination of in-person and telemedicine visits can expand reach to improve accessibility across a large patient population.

Bridging New Technology Into Clinical Practice With Mobile Apps, Electronic Patient-Reported Outcomes, and Wearables

With sophisticated mobile and wearable technologies available, there has been interest in leveraging these devices to help gather and analyze patient-generated health data (PGHD). This information could be used to better address health concerns, aid in treatment decision-making, and guide interventional strategies to improve outcomes. Among PGHD, electronic patient-reported outcomes, direct reports of patient experience usually collected via validated scales and questionnaires, are increasingly integrated into routine clinical practice to monitor patient status. Electronic patient-reported outcomes have been shown to improve outcomes, including symptom control, quality of life, and overall survival, in several clinical trials. Electronic patient-reported outcome collection is now being implemented across broader clinical practice settings but with limited evaluation of impact thus far. Wearable devices and mobile apps provide opportunities to collect additional PGHD, including continuous physiologic measures, and to generate algorithms with which to monitor patients with cancer and guide interventions. In this article, we discuss several topics related to PGHD and technology, including electronic patient-reported outcomes, mobile apps, and wearable devices and how their introduction into oncology care has the potential to improve the collection and use of PGHD in the future. We also highlight the challenges and future directions needed for mobile and wearable technologies to provide meaningful information that can be acted upon and thus can improve oncologic care.

Biomarker testing patterns and actionability in advanced non-small cell lung cancer (aNSCLC) at OneOncology (OneOnc)

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Background: Recent approvals of targeted treatments (tx) have improved personalized care in aNSCLC. Biomarker testing is crucial for patients (pts) to receive optimal tx expeditiously. This study examined aNSCLC biomarker testing and tx patterns at OneOnc. Methods: Pts diagnosed with aNSCLC (stage ≥ IIIb) from 1/1/2015 to 5/31/2020, aged ≥ 18 years, and with ≥ 1 visit ≤ 90 days of advanced (Adv) diagnosis (Dx) were retrospectively evaluated using the nationwide Flatiron Health electronic health record derived de-identified database from selected OneOnc sites. Descriptive analyses were conducted to evaluate testing patterns for ALK, BRAF, EGFR, KRAS, PD-L1, and ROS-1 biomarkers and actionable mutation tx pattern. Results: Overall 3,860 aNSCLC pts were included, median age was 69 years, 47% females, 66% non-squamous, 29% squamous, 4% histology NOS, and 23% with ECOG performance status 0-1. Of the 3,152 (82%) pts tested for any biomarker, 64% received next-generation sequencing (NGS) vs. 36% received other biomarker tests only. Testing rates varied by biomarker: EGFR (74%), ALK (72%), ROS-1 (66%), PD-L1 (57%), BRAF (56%), KRAS (54%). Pts who received all 6 biomarker tests increased from 12% (2015), 23% (2016), 40% (2017), 41% (2018), 48% (2019) to 56% (2020). Among the tested pts, the median time from Adv Dx to the first test result was 20 days (d) and from specimen collection after Adv Dx to the first test result was 12 d. Pts tested and treated before test result available declined from 28% (2015) to 16% (2020). Of 1,207 pts with actionable mutations, 390 (32%) received tx before the test result: 35% chemotherapy (chemo) only, 28% chemo + cancer immunotherapy (CIT), and 15% CIT only. After the test result, 26% to 81% of pts received no or other tx not specific to actionable mutations [Table]. Conclusions: Findings from this study demonstrated an increase in aNSCLC biomarker testing at OneOnc over time, while 44% pts in 2020 did not receive testing on all 6 biomarkers. Some pts had tx prior to the test result, but this trend appeared to decline. Further studies are warranted to better understand the reasons for pts receiving tx that were not specific to their actionable mutations.[Table: see text]

NGS testing patterns in advanced non-small cell lung cancer (aNSCLC) and metastatic breast cancer (mBC): OneOncology (OO) sites compared to Flatiron Health Nationwide (NAT)

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Background: Personalized treatment (tx) decisions can be improved through diagnostic tests with NGS by detecting different actionable mutations. OO, a research-focused network of community practices, has a network-wide precision oncology initiative and has advocated for NGS testing in advanced cancers since 2019. This study evaluated NGS testing patterns in aNSCLC and mBC populations descriptively in OO community sites and Flatiron Health NAT. Methods: This study used the Flatiron Health EHR derived de-identified database from [1] four OO sites, and [2] NAT. Patients (pts) diagnosed (Dx) with aNSCLC (stage ≥ IIIb) or mBC from 1/1/2015 to 5/31/2020, aged ≥ 18 years, had ≥ 1 visit ≤ 90 days (d) of advanced or metastatic Dx, and had ≥ 1 biomarker test were included. NAT NGS was confirmed via abstraction from patient records. Descriptive analyses were conducted to assess NGS testing patterns and pts characteristics by tumor type. Results: Of biomarker tested pts at OO vs. NAT (community:academic: 90%:10% aNSCLC; 93%:7% mBC), 2,029 of 3,152 (64%) OO vs. 13,681 of 29,572 (46%) NAT in aNSCLC and 514 of 1,282 (40%) OO vs. 2,458 of 12,175 (20%) NAT in mBC received NGS ± other tests. Testing rate of all 5 aNSCLC biomarkers (ALK, BRAF, EGFR, ROS-1, and KRAS) was higher with NGS vs. other tests for OO (87% vs. 6%) and NAT (87% vs. 11%). In mBC, a higher testing rate of BRCA with NGS vs. other tests (OO: 68% vs. 26%, NAT: 71% vs. 28%) and similar testing rate on HER2 (OO: 98% vs. 98%, NAT: 100% vs. 99%). Median time from Dx to NGS test result at OO vs. NAT was 33 d vs. 32 d in aNSCLC and 70 d vs. 188 d in mBC. NGS testing rates increased over time, with higher rates at OO vs. NAT [Table]. Pts with NGS vs. other tests were slightly younger in aNSCLC (OO: 68 y vs. 70 y, p = 0.001; NAT: 69 y vs. 70 yr, p < 0.001) and mBC (OO: 61 y vs. 67 y, p < 0.001; NAT: 61 y vs. 66 y, p < 0.001), and slightly more commercially insured in aNSCLC (OO: 48% vs. 45%, p = 0.3; NAT: 37% vs. 33%, p < 0.001) and mBC (OO: 54% vs. 48% OO, p = 0.053; NAT: 42 % vs. 36 %, p < 0.001). Conclusions: The adoption of NGS differed by cancer type and NGS testing rates have increased over time in aNSCLC and mBC. While some pts may have received testing outside of the Flatiron network, OO had a higher NGS uptake than NAT, and had a shorter time to testing in mBC that was possibly related to a network wide strategy recommending testing at Dx of advanced disease. Future studies on tx pattern after NGS testing are warranted to improve the actionability of NGS to foster personalized tx. [Table: see text]

Healthcare resource utilization, quality metrics, and costs of bladder cancer within the oncology care model

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Background: The Oncology Care Model (OCM) incentivizes practices to provide higher quality, lower cost care for Medicare beneficiaries through payment arrangements that include financial and performance accountability for 6-month care episodes. We sought to describe the existing experience with bladder cancer (BC) for OCM practices, in the context of all OCM cancer types, given the dynamic treatment landscape in which new and emerging therapies will impact spending and patient care in this payment model. Objective: To estimate healthcare resource utilization (HRU), OCM quality metrics, and costs for OCM episodes among Medicare beneficiaries with BC. Methods: OCM episodes triggered by receipt of cancer therapy (index event) were identified among Medicare beneficiaries (100% Research Identifiable Files) from 2016-18. Other inclusion criteria were enrollment in Parts A & B for the entire OCM episode (6 months or until death) and 6 months pre-index date, Medicare as primary payer, and ≥1 qualifying Evaluation & Management visit during the episode. A cancer type was assigned to each episode. BC episodes were stratified as low- (defined by receipt of BCG and/or mitomycin without other systemic therapy) or high-risk (receipt of systemic therapy other than BCG or mitomycin) based on OCM definitions. Results: Of the 2.2 million OCM cancer episodes identified among 1 million beneficiaries, 60,099 (̃3%) were BC episodes. Our analytic cohort consisted of 43,621 BC episodes (69% low-risk and 31% high-risk) among 33,497 beneficiaries. Across BC episodes, average patient age was 76.6 years and 77% were male. Relative to low-risk episodes, high-risk episodes included higher metastatic cases (40 vs 2%), and more comorbidity burden (7.4 vs 4.3 Charlson comorbidity score). High-risk episodes had more hospital admissions (0.7 vs 0.2) and intensive care unit use (17 vs 5%), longer length of stay (5.9 vs 4.9 days), and higher rates of surgery (7 vs 1%) and mortality (17 vs 2%). Among OCM quality metrics, high-risk episodes had higher inpatient admissions (42 vs 15%) and emergency department visits (37 vs 20%) relative to low-risk episodes. Average spending per high-risk BC episode was ̃$38,000 (vs $9,204 for low-risk), with ̃$11,000 spent on systemic therapies and ̃$7,000 on inpatient services. Conclusions: High-risk OCM episodes of BC, which included 40% metastatic BC, had higher HRU and costs, and lower quality performance, than low-risk episodes. Novel therapies offer a significant opportunity to optimize BC management and improve quality of care, particularly for high-risk episodes. Further, as < 3% of OCM episodes were attributed to BC, and only one-third of BC episodes were classified as high-risk, controlling expenditure on novel therapies in BC episodes is unlikely to impact overall performance for practices participating in OCM.

Impact of clinical trial enrollment on episode costs in the Oncology Care Model (OCM)

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Background: Clinical trials are critical for improving outcomes for patients with cancer. However, there is some concern from health insurers that clinical trial participation can increase total cost of care for cancer patients. We investigated the impact of clinical trial participation on total costs paid by Medicare during the OCM program in a large community-based practice. Methods: Tennessee Oncology (TO) is a community oncology practice comprising over 90 oncologists across 30 sites of care. We linked TO trial data and electronic medical record data with OCM data for episodes of care from 2016-2018. To assess the impact of trial participation on total cost relative to routine care, we created matched comparator groups for each OCM episode based on cancer type, metastatic status, number of comorbidities, performance status, and age. Patients with breast cancer receiving hormone therapy only were excluded. Absolute and percent cost differences between groups were calculated for episodes that had a comparator group size of five or greater. Differences in total cost for trial episodes were compared to non-trial episodes, and significance was assessed using the Mann–Whitney U test. We also studied the impact of trial participation on receipt of active treatment in the last 14 days of life (TxEOL), hospice use, and hospitalizations. Results: During the study period, 8,026 completed OCM episodes met study criteria. Patients were enrolled in a clinical trial for 459 of these episodes. On average, episodes during which patients were on trial cost $5,973 less than matched non-trial episodes (Table), independent of early versus late-phase trial. Most savings resulted from decreased drug costs. There were no differences in rates of TxEOL (15% vs. 14% p=1.0), rates of hospitalizations (31% vs. 30% p=0.54), or hospice use (52% vs. 62% p=0.08) between trial and non-trial episodes. Median difference from comparator group average cost was significantly lower for clinical trial episodes (-18% vs. -6%, p<0.01). Conclusions: In the community setting, total costs paid by Medicare for patients participating in clinical trials during OCM episodes were lower than costs for similar patients receiving routine care. Clinical trial participation did not adversely impact end-of-life care or likelihood of hospitalization. These findings suggest that patient participation in clinical trials does not increase total cost of care nor enhance financial risk to payers.[Table: see text]

Clinical pathways implementation in a community-based oncology practice: Real-world outcomes in patients with non-small cell lung cancer segmented by disease stage at diagnosis

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Background: Clinical pathways have been introduced as tools to optimize cancer care delivery, but evidence of their value in the real world is limited. This retrospective study was performed to assess treatment patterns and clinical outcomes in patients with non-small cell lung cancer (NSCLC) before and after pathway implementation at Tennessee Oncology (TO). Methods: Chart data were abstracted for patients (≥18 years) diagnosed with Stage I-IV NSCLC who initiated first-line (1L) systemic treatment at a TO clinic and had follow-up for ³6 months or until death. Patients were divided into two cohorts: pre-pathways (treatment initiation 2014–2015) and post-pathways (treatment initiation 2016–2018). Patient characteristics, treatment patterns, and outcomes were described and compared across cohorts. An exploratory study endpoint was the evaluation of outcomes based on disease stage at diagnosis. Results: Among 501 patients (251 pre-pathways and 250 post-pathways), most had advanced or metastatic NSCLC at diagnosis (Stage III: 40%; Stage IV: 42%). Chemotherapy comprised almost all 1L systemic therapy used pre-pathways (Stage I/II: 100%; Stage III: 96%; Stage IV: 83%). Post-pathways, chemotherapy remained the most common 1L therapy in patients with Stage I/II (89%) and Stage III (72%) disease, but among patients with Stage IV disease, use of chemotherapy decreased (47%) and immuno-oncology (IO) therapy alone or in combination became common (45%). Median duration of 1L therapy was longer post-pathways in patients with Stage III (2.1 months vs 1.4 months pre-pathways; P < 0.01) and Stage IV disease (3.3 months vs 2.3 months pre-pathways; P < 0.01) but did not differ among Stage I/II patients. Median progression-free survival was significantly longer post-pathways in patients with Stage IV disease (7.0 months vs 4.2 months pre-pathways; P < 0.05), but not in other disease-stage subgroups. Median overall survival increased non-significantly post-pathways for all disease stage subgroups (Stage I/II: 26 months vs 20 months pre-pathways; Stage III: 26 months vs 20 months; Stage IV: 10 months vs 9 months). For each disease stage, rates of severe adverse events were similar between cohorts. Conclusions: While outcomes for patients diagnosed with Stage III/IV NSCLC were generally improved following the implementation of clinical pathways, this change coincided with a dramatic shift in available treatment options. Improvements post-pathways were mainly observed in patients diagnosed with advanced disease. Thus, differences in outcomes between pre-pathways and post-pathways cohorts in our study are more likely attributable to other evolving practices in cancer care, particularly the availability of newer, more effective treatments such as IO therapy as part of standard practice, than implementation of the clinical pathways.

New drug approvals and their effect on performance for participants in the Oncology Care Model

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Background: The Oncology Care Model (OCM) is an oncology-specific value-based care model that holds participating practices accountable for all costs of care. Medicare implements quantitative adjustments to model target costs in OCM, including a trend factor to reflect aggregate cost growth and a novel therapy adjustment for new indications. However, it is unclear how well these adjustments account for the emergence of new therapies that are evidence based and influence standard of care for an individual cancer type. We sought to investigate this by studying the impact that FDA approval for brentuximab vedotin (BV) in the first line setting in March 2018 had on OCM practice performance in Hodgkin’s Lymphoma (HL). Methods: We identified all HL OCM episodes attributed to Tennessee Oncology (TO), a large community oncology network of over 90 oncologists, during performance periods (PP) 3 through 6. HL episodes within the lymphoma bundle were identified through the use of individual ICD-10 coded diagnoses on claims for antineoplastic infusions and E&M visits. Using OCM performance data, our electronic health record, and claims data analytics software, we calculated average episode target costs, drug spending by drug type, and hospitalization costs to determine key determinants of OCM performance. Results: During the study period, there were 577 episodes of lymphoma attributed to TO, of which 28 were for patients with HL. TO’s OCM performance in HL was significantly under target in PP4 (under target by $13.5K) and significantly over target in PP5 (over target by $32.1K) after the updated BV FDA approval. Average episode spending on BV increased by over $45K during this timeframe, while OCM target cost increased only by approximately $19K. Despite the change in OCM performance, hospitalization costs and hospice utilization remained relatively stable. Conclusions: In the OCM, despite quantitative payment factors that in principle are intended to adjust target prices to reflect changing cost dynamics, significant gaps exist. These gaps can inappropriately shift risk to providers for the appropriate use of new indications, including those that change standard of care. The example of brentuximab vedotin in HL illustrates the difficulty in reaching performance benchmarks due to dynamics associated with the rising cost of drugs. Further methodological changes are needed in future oncology value-based care models to ensure accurate prediction of rapidly changing treatment costs for appropriate therapies. Hodgkin’s lymphoma OCM payment period cost and utilization comparison data.[Table: see text]

Estimates of stage-specific preclinical sojourn time across 21 cancer types

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Background: Cancer progression rates following diagnosis are readily measured. However, the progression rate of cancer during the preclinical sojourn time is generally unobserved. Understanding the duration of preclinical stages (“dwell time”) would allow clinicians to better identify appropriate screening intervals for cancer. We therefore elicited estimates of progression rate during the preclinical sojourn time for a wide variety of malignancies from a panel of clinical experts. Methods: We used a validated consensus methodology (RAND/UCLA modified Delphi panel method) to elicit per-stage dwell time estimates for 20 solid cancers and lymphoma from experts. Eleven experienced oncologists (general and subspecialists) from community and academic centers reviewed literature on the natural history of disease and estimated in number of years (<1 to 9+ years) how long it would take each cancer to progress from the beginning of clinically detectable Stage I/II/III to the beginning of the next stage in untreated adults. Cancer histological subtypes were grouped and experts were asked to provide an overall rating. Ratings were completed before and after a discussion of areas of disagreement. Results: Expert estimates and range of dwell time for 21 cancer types are provided in Table. Prostate and thyroid cancer were estimated to be the slowest growing, taking approximately 7 and 5 years respectively to progress through Stage I (range 4-8), 5 years to progress through Stage II (range 3-7), and 3 and 4 (range 2-5) years respectively to progress through Stage III. Esophageal, lung, liver/intrahepatic bile-duct, gallbladder, and pancreatic cancers were estimated to progress quickly through all three stages (1-2 years per stage). Conclusions: These findings summarize practicing oncologists’ estimates of dwell time in preclinical disease. Experts agreed on dwell times although ranges were large and differences in cancer subtypes were not captured. Generally, estimates trend with published data on survival with treatment: cancers with higher survival (e.g., prostate, thyroid) were estimated to grow slower, while cancers with lower survival (e.g., pancreatic, liver/intrahepatic bile-duct, gallbladder) were estimated to grow faster. These estimates could be useful when determining screening intervals for these or any subset of these cancers. [Table: see text]

Electronic patient-reported outcomes (ePRO) platform engagement in cancer patients during COVID-19

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Background: Tennessee Oncology partnered with an ePRO platform solution to support patients during their cancer care journey. This cloud-based ePRO platform is designed to assist in improving the management of symptoms. Providing two core pieces of functionality allow both the patient and care teams to retrieve information quickly and communicate effectively. The patient portal is patient input driven and allows the patient to communicate with their care team, track symptoms, and access their health records via website or mobile app. The clinician portal provides multiple care teams the ability to manage and prioritize patient needs as well as communicate directly with patients. In March 2020, due to the pandemic, patients needed a convenient and remote way to communicate with the care team. Our communication plan had to be nimble and provide immediate updates to our large patient population. We leveraged our ePRO platform to meet this need. Methods: We focused efforts on increasing patient engagement by educating them on the benefits of this communication platform. We utilized secure messaging to send appointment details and for Telehealth visits a link to the visit was sent. We were able to provide weekly updates outlining our latest information regarding our safety protocols. Results: We noted an increase in the activation of patient accounts and patient-initiated messages in our ePRO platform. We saw an average of 1,000 new patient accounts activated each month during March, April and May. We saw that patient-initiated messages through the platform showed a 15% increase from February to March. The response rate for patients completing post-treatment questionnaires increased 8% from February to May. Conclusions: By providing patients with a single communication platform to contact their care teams outside of their office visits, patients become an active part of their care journey. As an organization, we continue to identify ways to connect our patients to their care team in a meaningful way through technology. Whether during normal business hours or after-hours, patients need a simple, reliable and consistent way to engage with their care team.

Maintaining treatment volumes during the COVID-19 pandemic

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Background: Uninterrupted care is essential for optimal outcomes in cancer care. The COVID-19 pandemic presented numerous challenges in providing continuity of care for many facilities. Our practice was able to deliver ongoing treatment for a large volume of our patients while maintaining a safe environment. Methods: A practice-wide effort to continue therapy in cancer patients undergoing active treatment began in March 2020 as the peak of the pandemic was beginning in Tennessee. Those patients who were receiving active treatment continued the planned treatment while reducing non-acute treatment visits. We assessed the volume of patients receiving treatments in our facilities for two periods: JanuaryDecember 2019 and January-May 2020. We compared the aggregate number of chemotherapy infusions, therapeutic infusions and injections as well as total treatments. Results: Overall, treatments remained relatively stable without a significant change in treatment volumes. There was a 3.69% decline in total treatment with therapeutic infusions (-9.68%) and injections (-7.85%) which accounted for the majority of deferred treatments. Chemotherapy infusions remained stable with an average increase (1.90%) in treatments. Conclusions: During the COVID-19 pandemic, our facility was able to maintain stable treatment numbers while providing safe care to our patients. We had no known diagnosed COVID-19 cases from potential exposures in our clinics. Decreases in treatment reflected less critical therapies. There did seem to be a delay for chemotherapy/immunotherapy that seemed to resolve as the peak passed for this region. Offloading of less critical treatments can result in continued treatment of cancer patients during a pandemic. [Table: see text]

Utilization of telemedicine to meet the demand throughout the COVID-19 pandemic at a community oncology practice

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Background: A large community oncology practice in Tennessee participates in value-based payment arrangements, the success of which depends on close patient monitoring. Telemedicine as an innovative solution was initiated in 2017. The service was limited, due to regulation, licensure requirements, and lack of reimbursement, to survivorship visits, clinical trial consent visits, rural hospital consults and genetic counseling. During the COVID pandemic and loosening of restrictions, telemedicine services were expanded. Methods: We identified a cloud-based platform that allowed patients to use any device with a camera and microphone and required no software downloads. On-line training sessions were provided to clinical staff. All training and workflow implementation were completed in a 2-week time frame. Telemedicine was expanded to include surveillance, urgent care, psychology, palliative care and post-BMT visits as well as new patient consults for medical, radiation and gynecologic oncology patients. Patient satisfaction surveys were administered. Results: Our telemedicine visits increased weekly beginning March 1, peaking in the month of April with an average of 77 scheduled telemedicine visits per day across the practice. During the month of April, our practice saw a record clinical trial accrual in our Phase-1 Drug Development Unit with a 22% increase over the previous average. Patients who responded to a satisfaction survey were highly satisfied with the telemedicine visit with a 73% positive response rate. Nearly half of our eligible patients did not have the technology or broad-band access to be able to participate in telemedicine. Conclusions: Our prior experience with telemedicine, though limited, facilitated the development of an infrastructure that provided adequate number of devices and internet bandwidth capacity to support rapid expansion of telemedicine. We were able to maintain high quality care and access to clinical trials during the pandemic and see the value of this service long-term. We hope to add tele-pharmacy and care coordination services. Political leadership and patient advocacy groups should explore ways to ensure that all patients may benefit from this technology, especially those in under-served areas.

Launch of telemedicine in community oncology practice

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Background: Tennessee Oncology (TO) is a community medical, radiation and gynecology oncology practice with 90 physicians and 40 advanced practice providers (APPs) in 33 locations in Tennessee. TO participates in the Oncology Care Model (OCM), a CMMI experimental payment model to improve access, quality of care, patient experience and lower costs. Methods: To promote provider-patient communication to improve outcomes and lower healthcare costs, TO launched a telemedicine pilot. The pilot was designed to understand Tennessee’s rules and regulations, reimbursement policies for Medicare, Medicaid and commercial payers and technology requirements. As survivorship was aligned with clinical workflow, supported by existing technology and required minimal staff training, the Survivorship Program for OCM was selected as proof of concept for telemedicine. Education surrounding Survivorship is required as part of the OCM model. A portion of the MEOS payment was considered as reimbursement for this initiative. The goal was to increase the delivery and review of survivorship documents to eligible breast cancer patients using the telemedicine platform from 0% to 80%. Results: 4000 potential patients were eligible for survivorship visits within TO. The selection was narrowed to include only OCM patients with breast cancer. TO identified 4 APPs who were given special training. TO’s front office staff coordinated scheduling of the technology, provider and space available. There were 99 patients eligible for a Telemedicine visit. 36 patients completed a Telemedicine visit with 23 patients declining. 19 patients did not respond to requests for these visits. 10 patients completed surveys and were 100% satisfied with their visits. The APPs felt Telemedicine visits were more productive than in person visits. Conclusions: Telemedicine is an effective tool for delivery of health care. There are challenges that make this technology difficult to implement such as reimbursement and limitations to the use of technology in elderly. In our pilot we found that the APPs and patients found this to be an effective way of communication and delivery of care. In the future telemedicine could answer some of the shortages in health care delivery and could also improve coordination of care.

Safety analysis of regorafenib prior to selective internal radiation therapy (SIRT) using 90Y resin microspheres for the treatment (tx) of patients (pts) with refractory metastatic colorectal cancer (mCRC) with liver metastases (mets)

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Background: SIRT (or radioembolization) has been successfully used in the tx of mCRC patients with liver mets who are not surgical candidates. The addition of the multi-kinase inhibitor, regorafenib to SIRT is an attractive option as anti-tumor and maintenance tx for refractory CRC. Here we present the safety analysis of the 1st of 2 cohorts of our Phase II, open-label study comparing the safety of the combination of SIRT and regorafenib where chemotherapy occurs either before or after SIRT. Methods: mCRC pts with evidence of liver mets not treatable by surgical resection or local ablation were tx with 160 mg regorafenib QD PO on days 1-21 of a 28-day cycle followed by a 1 week (wk) washout then SIRT infusion (SIR-Spheres; Sirtex, North Sydney, Australia). Liver function was evaluated 2 wks and 4 wks after SIRT, and regorafenib was re-initiated if liver function was normal. Pts were evaluated for safety, and restaged on wk 6 and 12 following SIRT. The primary objective was to evaluate the safety of this tx schema. Results: 25 pts were enrolled from 7/15 to 8/16: median age 56 yrs, 48% male; 88% colon cancer, 12%, rectal cancer; 48% KRASmt, 4% BRAFmt. 68% of pts had prior systemic therapy for metastatic disease and 80% of pts had prior CRC surgeries. Pts received a median 11 wks regorafenib. 3 pts received regorafenib, but not SIRT due to disease progression. The median activity of SIRT delivered to the liver was 38 mCi and the median lung shunt fraction was 4%. The median tumor volume treated was 76 mL. The most common tx-related adverse events (AEs) were fatigue (60% all grades [G]; 8% G3/4), decreased appetite (32% all G; 0 G 3/4), and nausea (32%, all G; G 3/4). There were 4 tx-related serious AEs (bowel perforation, intractable abdominal pain, portal hypertension, and diarrhea) and no tx-related deaths. The overall response rate was 4%. The median PFS was 4 months and the median OS was 12 months. Conclusions: The treatment of mCRC pts with liver mets with regorafenib followed by SIRT infusion was found to be tolerable in this pt population. Further efficacy analysis of this treatment schema is merited. Clinical trial information: NCT02195011.

Randomized phase II study of carboplatin and etoposide with or without obatoclax mesylate in extensive-stage small cell lung cancer

OBJECTIVE

This randomized phase II study assessed the efficacy and safety of obatoclax mesylate, a small-molecule Bcl-2 inhibitor, added to carboplatin/etoposide chemotherapy as initial treatment for extensive-stage small-cell lung cancer (ES-SCLC).

MATERIALS AND METHODS

Chemotherapy-naïve subjects with ES-SCLC and Eastern Cooperative Oncology Group performance status (ECOG PS) 0-2 received carboplatin/etoposide with (CbEOb) or without (CbE) obatoclax for up to six cycles. Responders to CbEOb could receive maintenance obatoclax until disease progression. The primary endpoint was objective response rate (ORR).

RESULTS

155 subjects (median age 62, 58% male, 10% ECOG PS 2) were treated with CbEOb (n=77) or CbE (n=78); 65% and 59% of subjects, respectively, completed six cycles. ORR was 62% with CbEOb versus 53% with CbE (1-sided p=0.143). Clinical benefit (ORR+ stable disease) trended better with CbEOb (81% versus 68%; p=0.054). Median progression-free survival (PFS) and overall survival (OS) were 5.8 months (95% confidence interval [CI]: 5.3-6.5) and 10.5 months (8.9-13.8) with CbEOb and 5.2 months (95% CI: 4.1-5.7) and 9.8 months (7.2-11.2) with CbE. Median OS was 10.5 months (95% CI: 8.9-13.8) and 9.8 months (7.2-11.2) with a nonsignificant hazard ratio for OS, 0.823; 1-sided p=0.121. Grade 3/4 adverse events (AEs) were primarily hematologic and similar in frequency between treatment arms. Obatoclax-related somnolence and euphoria were grade 1/2, transient, and did not require treatment discontinuation.

CONCLUSION

Obatoclax was well tolerated when added to carboplatin/etoposide in first-line treatment of ES-SCLC, but failed to significantly improve ORR, PFS, or OS.

Phase II trial of fulvestrant with metronomic capecitabine for postmenopausal women with hormone receptor-positive, HER2-negative metastatic breast cancer

BACKGROUND

In this phase II study, we explored efficacy and toxicity of combined endocrine and low-dose metronomic chemotherapy therapy consisting of fulvestrant and capecitabine in estrogen and/or progesterone receptor-positive, HER2-negative MBC.

PATIENTS AND METHODS

Patients with ≤ 1 previous hormonal treatment in the metastatic setting received an injection fulvestrant loading dose 500 mg on day 1, 250 mg on days 15 and 29 followed by 250 mg every 28 days along with continuous oral capecitabine in divided doses. The total fixed daily dose of capecitabine was either 1500 mg or 2000 mg, depending on the patient's weight (< 80 kg vs. ≥ 80 kg). Primary end points were PFS and TTP. Toxicity was assessed by continuous evaluations of treatment-emergent adverse events (AEs) and changes from baseline in laboratory values.

RESULTS

Forty-one women, with a mean age of 64.5 years, were enrolled. Patients completed a median of 11 monthly treatment cycles. Median PFS was 14.98 months (95% confidence interval [CI], 7.26-upper limit [UL] not estimated) and median TTP was 26.94 months (95% CI, 7.26-UL not estimated). Median overall survival was 28.65 months (95% CI, 23.95-UL not estimated). Treatment was well tolerated with < 10% Grade 3 palmar-plantar erythrodysesthesia. Overall, the most frequent AEs were palmar-plantar erythrodysesthesia, fatigue, and nausea.

CONCLUSION

Fulvestrant with metronomic capecitabine demonstrates substantial activity in hormone receptor-positive MBC and is well tolerated. Combined chemoendocrine approaches should be further explored considering the low toxicity of the combination with meaningful TTP.

Phase II study of the anti-insulin-like growth factor type 1 receptor antibody CP-751,871 in combination with paclitaxel and carboplatin in previously untreated, locally advanced, or metastatic non-small-cell lung cancer

PURPOSE

We conducted a phase II study of combination of the anti-insulin-like growth factor 1 receptor antibody CP-751,871 with paclitaxel and carboplatin (PCI) in advanced treatment-naïve non-small-cell lung cancer (NSCLC).

PATIENTS AND METHODS

Patients were randomly assigned (2:1) to paclitaxel 200 mg/m(2), carboplatin (area under the plasma concentration-time curve of 6), and CP-751,871 10 to 20 mg/kg (PCI(10), PCI(20)) or paclitaxel and carboplatin alone (PC) every 3 weeks for up to six cycles. PCI(10-20) patients could continue CP-751,871 (figitumumab) treatment after chemotherapy discontinuation. Patients treated with PC experiencing disease progression were eligible to receive CP-751,871 at investigator's discretion. An additional nonrandomized single-arm cohort of 30 patients with nonadenocarcinoma tumor histology receiving PCI(20) was enrolled on completion of the randomized study.

RESULTS

A total of 156 patients were enrolled onto the randomized portion of the study. Safety and efficacy information are available for 151 patients (98 patients treated with PCI and 53 patients treated with PC). Forty-eight patients treated with PCI received PCI(10) and 50 patients received PCI(20) in two sequential stages. Twenty of 53 patients treated with PC received CP-751,871 after disease progression. PCI was well tolerated. Fifty-four percent of patients treated with PCI and 42% of patients treated with PC had objective responses. Sixteen of 23 patients assessable for efficacy in the nonrandomized single-arm extension cohort also responded to treatment. Of note, 14 of 18 randomly assigned and 11 of 14 nonrandomly assigned patients treated with PCI with squamous cell carcinoma histology had response to treatment, including nine objective responses in bulky disease. Responses were also observed in two patients with squamous histology receiving CP-751,871 on PC discontinuation. PCI(20)/PC hazard ratio for progression-free survival was 0.8 to 0.56, according to censorship.

CONCLUSION

These data suggest that PCI(20) is safe and effective in patients with NSCLC.

The relation of trouble sleeping, depressed mood, pain, and fatigue in patients with cancer

STUDY OBJECTIVES

To evaluate the relation among several symptoms that occur commonly in cancer patients: trouble sleeping, fatigue/sleepiness, depressed mood, and pain in a large cohort of cancer patients undergoing treatment in a community oncology practice.

METHODS

Demographic, clinical, and patient reported outcomes data from 11,445 cancer patients undergoing treatment in a large community oncology practice were analyzed using structural equation modeling. The data were split so that a model was constructed using half of the patients; this model was then cross-validated on the remaining patients.

RESULTS

Fatigue was best represented as a latent variable, and significant direct effects were found for trouble sleeping, depressed mood, and pain. Also, there were significant indirect effects of these variables on fatigue. The effect of depressed mood on fatigue and pain was mediated by trouble sleeping, and the effect of trouble sleeping on fatigue was mediated by pain.

CONCLUSIONS

These results predict that interventions aimed at treatment of trouble sleeping, depressed mood, and pain will improve fatigue in patients with cancer. Further, these data predict that treatment of trouble sleeping will improve pain management in this population.

A Phase I and Pharmacokinetic Study of TAS-108 in Postmenopausal Female Patients with Locally Advanced, Locally Recurrent Inoperable, or Progressive Metastatic Breast Cancer

PURPOSE

TAS-108 is a novel steroidal anti-estrogen compound that has a strong binding affinity to the estrogen receptor and, in preclinical studies, has antitumor activity against tamoxifen-resistant breast cancer cell lines. The objective of this study was to investigate the safety and the pharmacokinetics in patients with previously treated advanced breast cancer.

EXPERIMENTAL DESIGN

TAS-108 was administered orally once daily starting at 40 mg/day, with dose escalations of 60, 80, 120, and 160 mg/day. A minimum of three patients were enrolled in each dose level, and, if no drug-related grade 3 or higher adverse events were seen in the first 14 days, the next cohort of patients was treated at the next level. Pharmacokinetic data were obtained on day 1, 2, 15, and 28 of the first course.

RESULTS

A total of 16 patients were enrolled, and most had received six to seven prior therapies. Clinical toxicities included nausea, vomiting, hot flashes, headache, weakness and fatigue; all were grade 1-2. TAS-108 had no effect on endometrial thickness based on trans-vaginal ultrasound evaluation. The average duration of therapy was 17.4 weeks (range, 4-60 weeks). The mean terminal half-life ranged from 8.0 to 10.7 hour in the interval of 12 to 24 hours postdose. The mean C(max) ranged from 2.8 to 21.0 ng/mL and AUC(0-t) from 15.1 to 148.7 ng.h/mL, this showed a linear correlation with the dose.

CONCLUSIONS

TAS-108 was well tolerated in the doses studied with no maximum tolerated dose. The drug has linear pharmacokinetics, and in this heavily treated patient population, there was evidence of biological antitumor activity. A multi-institutional phase II study is planned.

Effects of pregnancy after treatment for breast carcinoma on survival and risk of recurrence

BACKGROUND

The goal of the current study was to assess the effect of pregnancy on the subsequent risk of recurrence after treatment for breast carcinoma, adjusting for established prognostic factors.

METHODS

Between 1974 and 1998, 383 patients age < or =35 years were treated for breast carcinoma with adjuvant chemotherapy at The University of Texas M. D. Anderson Cancer Center (Houston, TX). The median follow-up period was 13 years. Of these, 13 patients were excluded from analysis, as no history was available regarding pregnancy; 240 (65%) were >30 years old; 47 (13%) had at least 1 pregnancy after therapy; 32 had full-term pregnancies; 10 had spontaneous or elective abortions; 4 had miscarriages; and 1 had a premature delivery. Estrogen receptor (ER) status, lymph node involvement, and disease stage were evaluated as potential risk factors for recurrence. Information on ER status was unavailable for 123 (33%) patients.

RESULTS

Patients who experienced a pregnancy tended to have earlier-stage disease (Stage I/II: 80% vs. 73%), fewer positive lymph nodes (<4: 87% vs. 52%), more ER negativity (68% vs. 58%), and younger age (<30 years: 57% vs. 32%) than patients who did not. The incidence of disease recurrence was 23% for women who experienced a pregnancy and 54% for women who did not. The hazard ratio (using the multivariate Cox proportional hazards model) for disease recurrence in patients with posttreatment pregnancy was 0.71 (P=0.4).

CONCLUSIONS

In the current study population, pregnancy was not associated with an increased risk of disease recurrence or poorer survival in patients previously treated for breast carcinoma.

Molecular targets in therapy for human soft-tissue and bone sarcomas

Sarcomas represent a heterogeneous group of tumors with different natural histories and therapeutic approaches. Recent discoveries have identified molecular alterations in the pathogenesis of these tumors that lead to distinct effects on sarcoma cell biology. These tumor cell characteristics include independence from growth factors, evasion of apoptosis, and maintenance of genomic integrity. Inhibition of these molecular alterations represents a therapeutic opportunity to reverse the biologic basis of tumor formation in soft-tissue sarcomas and bone tumors.