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Dilley J, Gentry-Maharaj A, Ryan A, Burnell M, Manchanda R, Kalsi J, Singh N, Woolas R, Sharma A, Williamson K, Mould T, Fallowfield L, Campbell S, Skates SJ, McGuire A, Parmar M, Jacobs I, Menon U. Ovarian cancer symptoms in pre-clinical invasive epithelial ovarian cancer - An exploratory analysis nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Gynecol Oncol 2023; 179:123-130. [PMID: 37980767 DOI: 10.1016/j.ygyno.2023.11.005] [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: 08/01/2023] [Revised: 11/02/2023] [Accepted: 11/06/2023] [Indexed: 11/21/2023]
Abstract
OBJECTIVE UKCTOCS provides an opportunity to explore symptoms in preclinical invasive epithelial ovarian cancer (iEOC). We report on symptoms in women with pre-clinical (screen-detected) cancers (PC) compared to clinically diagnosed (CD) cancers. METHODS In UKCTOCS, 202638 postmenopausal women, aged 50-74 were randomly allocated (April 17, 2001-September 29, 2005) 2:1:1 to no screening or annual screening till Dec 31,2011, using a multimodal or ultrasound strategy. Follow-up was through national registries. An outcomes committee adjudicated on OC diagnosis, histotype, stage. Eligible women were those diagnosed with iEOC at primary censorship (Dec 31, 2014). Symptom details were extracted from trial clinical-assessment forms and medical records. Descriptive statistics were used to compare symptoms in PC versus CD women with early (I/II) and advanced (III/IV/unable to stage) stage high-grade-serous (HGSC) cancer. ISRCTN-22488978; ClinicalTrials.gov-NCT00058032. RESULTS 1133 (286PC; 847CD) women developed iEOC. Median age (years) at diagnosis was earlier in PC compared to CD (66.8PC, 68.7CD, p = 0.0001) group. In the PC group, 48% (112/234; 90%, 660/730CD) reported symptoms when questioned. Half PC (50%, 13/26PC; 36%, 29/80CD; p = 0.213) women with symptomatic HGSC had >1symptom, with abdominal symptoms most common, both in early (62%, 16/26, PC; 53% 42/80, CD; p = 0.421) and advanced (57%, 49/86, PC; 74%, 431/580, CD; p = 0.001) stages. In symptomatic early-stage HGSC, compared to CD, PC women reported more gastrointestinal (change in bowel habits and dyspepsia) (35%, 9/26PC; 9%, 7/80CD; p = 0.001) and systemic (mostly lethargy/tiredness) (27%, 7/26PC; 9%, 7/80CD; p = 0.017) symptoms. CONCLUSIONS Our findings, add to the growing evidence, that we should reconsider what constitutes alert symptoms for early tubo-ovarian cancer. We need a more nuanced complex of key symptoms which is then evaluated and refined in a prospective trial.
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Affiliation(s)
- James Dilley
- Department of Gynaecological Oncology, Barts Health NHS Trust, London, UK
| | - Aleksandra Gentry-Maharaj
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK; Department of Women's Cancer, Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Andy Ryan
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Matthew Burnell
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Ranjit Manchanda
- Department of Gynaecological Oncology, Barts Health NHS Trust, London, UK; Wolfson Institute of Population Health, CRUK Barts Cancer Centre, Queen Mary University of London, London, UK
| | - Jatinderpal Kalsi
- Department of Women's Cancer, Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Naveena Singh
- Department of Cellular Pathology, Barts Health NHS Trust, London, UK
| | - Robert Woolas
- Department of Gynaecological Oncology, Queen Alexandra Hospital, Portsmouth, UK
| | - Aarti Sharma
- Department of Obstetrics and Gynaecology, University Hospital of Wales, Cardiff, UK
| | - Karin Williamson
- Department of Gynaecological Oncology, Nottingham University Hospitals, Nottingham, UK
| | - Tim Mould
- Department of Gynaecological Oncology, University College London Hospitals NHS Trust, London, UK
| | - Lesley Fallowfield
- Sussex Health Outcomes Research and Education in Cancer (SHORE-C), Brighton and Sussex Medical School, University of Sussex, Sussex, UK
| | | | - Steven J Skates
- Massachusetts General Hospital and Harvard Medical School, Harvard, MA, USA
| | | | - Mahesh Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Ian Jacobs
- Department of Women's Cancer, Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Usha Menon
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK.
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Bednar EM, Chen M, Walsh MT, Eppolito AL, Klein MH, Teed K, Hodge B, Hunter J, Chao HG, Davis D, Serchion W, Yobbi C, Krukenberg R, Jenkinson SB, Moore JJ, Garcia C, Gonzalez F, Murray T, Nielsen LD, Ho B, Haas M, Greenzweig SB, Anderson A, Johnson C, Morman NA, Bowdish E, Wise E, Cooper JN, Russ PK, Tondo-Steele K, de Gracia BF, Levin B, Mattie K, Zarnawski K, Kalasinski M, Stone J, O'Brien C, Bream A, Kennedy AM, Paul RA, Bilbao M, Romero M, Carr RL, Siettmann JM, Vercruyssen AK, Leon K, Arun BK, Grainger AV, Warshal DP, Bowman E, Goedde TA, Halaharvi D, Rath K, Grana G, Mina L, Lu KH. Outcomes of the "BRCA Quality Improvement Dissemination Program": An initiative to improve patient receipt of cancer genetics services at five health systems. Gynecol Oncol 2023; 172:106-114. [PMID: 37004303 PMCID: PMC10192022 DOI: 10.1016/j.ygyno.2023.03.016] [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: 02/10/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 04/03/2023]
Abstract
OBJECTIVE A quality improvement initiative (QII) was conducted with five community-based health systems' oncology care centers (sites A-E). The QII aimed to increase referrals, genetic counseling (GC), and germline genetic testing (GT) for patients with ovarian cancer (OC) and triple-negative breast cancer (TNBC). METHODS QII activities occurred at sites over several years, all concluding by December 2020. Medical records of patients with OC and TNBC were reviewed, and rates of referral, GC, and GT of patients diagnosed during the 2 years before the QII were compared to those diagnosed during the QII. Outcomes were analyzed using descriptive statistics, two-sample t-test, chi-squared/Fisher's exact test, and logistic regression. RESULTS For patients with OC, improvement was observed in the rate of referral (from 70% to 79%), GC (from 44% to 61%), GT (from 54% to 62%) and decreased time from diagnosis to GC and GT. For patients with TNBC, increased rates of referral (from 90% to 92%), GC (from 68% to 72%) and GT (81% to 86%) were observed. Effective interventions streamlined GC scheduling and standardized referral processes. CONCLUSION A multi-year QII increased patient referral and uptake of recommended genetics services across five unique community-based oncology care settings.
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Affiliation(s)
- Erica M Bednar
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States of America.
| | - Minxing Chen
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States of America
| | - Michael T Walsh
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States of America
| | - Amanda L Eppolito
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Molly H Klein
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Kelly Teed
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Brittany Hodge
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Jordan Hunter
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Han Gill Chao
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Dillon Davis
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Wilshauna Serchion
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Cara Yobbi
- Community Health Network, Indianapolis, IN, United States of America
| | | | | | - Jennifer J Moore
- Community Health Network, Indianapolis, IN, United States of America
| | - Cassandra Garcia
- Community Health Network, Indianapolis, IN, United States of America
| | | | - Towanna Murray
- Community Health Network, Indianapolis, IN, United States of America
| | - Linda D Nielsen
- Community Health Network, Indianapolis, IN, United States of America
| | - Brenda Ho
- Community Health Network, Indianapolis, IN, United States of America
| | - Megan Haas
- Community Health Network, Indianapolis, IN, United States of America
| | | | - Abby Anderson
- Community Health Network, Indianapolis, IN, United States of America
| | - Christina Johnson
- Community Health Network, Indianapolis, IN, United States of America
| | | | | | - Emaline Wise
- OhioHealth, Columbus, OH, United States of America
| | | | | | | | | | - Brooke Levin
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Kristin Mattie
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Kathryn Zarnawski
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Molly Kalasinski
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Jennifer Stone
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Caitlin O'Brien
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Alexa Bream
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Aidan M Kennedy
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Rachel A Paul
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Michelle Bilbao
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Maureen Romero
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Rebecca L Carr
- Banner MD Anderson Cancer Center, Gilbert, AZ, United States of America
| | | | | | - Kaycee Leon
- Banner MD Anderson Cancer Center, Gilbert, AZ, United States of America
| | - Banu K Arun
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States of America
| | | | - David P Warshal
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Erin Bowman
- Piedmont Oncology at Piedmont Healthcare, Atlanta, GA, United States of America
| | - Timothy A Goedde
- Community Health Network, Indianapolis, IN, United States of America
| | | | - Kellie Rath
- OhioHealth, Columbus, OH, United States of America
| | - Generosa Grana
- MD Anderson Cancer Center at Cooper University Health Care, Camden, NJ, United States of America
| | - Lida Mina
- Banner MD Anderson Cancer Center, Gilbert, AZ, United States of America
| | - Karen H Lu
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States of America
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Miller AC, Arakkal AT, Koeneman SH, Cavanaugh JE, Polgreen PM. A clinically-guided unsupervised clustering approach to recommend symptoms of disease associated with diagnostic opportunities. Diagnosis (Berl) 2023; 10:43-53. [PMID: 36127310 PMCID: PMC9934811 DOI: 10.1515/dx-2022-0044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/26/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVES A first step in studying diagnostic delays is to select the signs, symptoms and alternative diseases that represent missed diagnostic opportunities. Because this step is labor intensive requiring exhaustive literature reviews, we developed machine learning approaches to mine administrative data sources and recommend conditions for consideration. We propose a methodological approach to find diagnostic codes that exhibit known patterns of diagnostic delays and apply this to the diseases of tuberculosis and appendicitis. METHODS We used the IBM MarketScan Research Databases, and consider the initial symptoms of cough before tuberculosis and abdominal pain before appendicitis. We analyze diagnosis codes during healthcare visits before the index diagnosis, and use k-means clustering to recommend conditions that exhibit similar trends to the initial symptoms provided. We evaluate the clinical plausibility of the recommended conditions and the corresponding number of possible diagnostic delays based on these diseases. RESULTS For both diseases of interest, the clustering approach suggested a large number of clinically-plausible conditions to consider (e.g., fever, hemoptysis, and pneumonia before tuberculosis). The recommended conditions had a high degree of precision in terms of clinical plausibility: >70% for tuberculosis and >90% for appendicitis. Including these additional clinically-plausible conditions resulted in more than twice the number of possible diagnostic delays identified. CONCLUSIONS Our approach can mine administrative datasets to detect patterns of diagnostic delay and help investigators avoid under-identifying potential missed diagnostic opportunities. In addition, the methods we describe can be used to discover less-common presentations of diseases that are frequently misdiagnosed.
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Affiliation(s)
- Aaron C Miller
- Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Alan T Arakkal
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA
| | - Scott H Koeneman
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA
| | - Joseph E Cavanaugh
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA
| | - Philip M Polgreen
- Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
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