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Schwartz MLB, McDonald WS, Hallquist MLG, Hu Y, McCormick CZ, Walters NL, Tsun J, Zimmerman K, Decker A, Gray C, Malinowski J, Sturm AC, Buchanan AH. Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results. JAMA Netw Open 2024; 7:e242388. [PMID: 38488794 PMCID: PMC10943406 DOI: 10.1001/jamanetworkopen.2024.2388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/23/2024] [Indexed: 03/18/2024] Open
Abstract
Importance Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.
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Affiliation(s)
- Marci L. B. Schwartz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | | | | | - Jessica Tsun
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | | | - Amie Decker
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- University of Arkansas Medical Sciences, Little Rock
| | - Celia Gray
- Phenomics and Clinical Data Core, Geisinger, Danville, Pennsylvania
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- 23andMe, Sunnyvale, California
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Mitchell LA, Jivani K, Young MA, Jacobs C, Willis AM. Systematic review of the uptake and outcomes from returning secondary findings to adult participants in research genomic testing. J Genet Couns 2024. [PMID: 38197527 DOI: 10.1002/jgc4.1865] [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: 06/19/2023] [Revised: 12/06/2023] [Accepted: 12/09/2023] [Indexed: 01/11/2024]
Abstract
The increasing use of genomic sequencing in research means secondary findings (SF) is more frequently detected and becoming a more pressing issue for researchers. This is reflected by the recent publication of multiple guidelines on this issue, calling for researchers to have a plan for managing SF prior to commencing their research. A deeper understanding of participants' experiences and outcomes from receiving SF is needed to ensure that the return of SF is conducted ethically and with adequate support. This review focuses on the uptake and outcomes of receiving actionable SF for research participants. This review included studies from January 2010 to January 2023. Databases searched included Medline, Embase, PsycINFO, and Scopus. Of the 3903 studies identified, 29 were included in the analysis. The uptake of SF ranged between 20% and 97%, and outcomes were categorized into psychological, clinical, lifestyle and behavioral, and family outcomes. The results indicate there is minimal psychological impact from receiving SF. Almost all participants greatly valued receiving SF. These findings highlight considerations for researchers when returning results, including the importance of involving genetic health professionals in consenting, results return process, and ensuring continuity of care by engaging healthcare providers.
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Affiliation(s)
- Lucas A Mitchell
- Clinical Translation and Engagement Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Karishma Jivani
- Graduate School of Health, University of Technology Sydney, Ultimo, New South Wales, Australia
| | - Mary-Anne Young
- Clinical Translation and Engagement Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Chris Jacobs
- Graduate School of Health, University of Technology Sydney, Ultimo, New South Wales, Australia
| | - Amanda M Willis
- Clinical Translation and Engagement Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
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Linder JE, Tao R, Chung WK, Kiryluk K, Liu C, Weng C, Connolly JJ, Hakonarson H, Harr M, Leppig KA, Jarvik GP, Veenstra DL, Aufox S, Chisholm RL, Gordon AS, Hoell C, Rasmussen-Torvik LJ, Smith ME, Holm IA, Miller EM, Prows CA, Elskeally O, Kullo IJ, Lee C, Jose S, Manolio TA, Rowley R, Padi-Adjirackor NA, Wilmayani NK, City B, Wei WQ, Wiesner GL, Rahm AK, Williams JL, Williams MS, Peterson JF. Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing. Am J Hum Genet 2023; 110:1950-1958. [PMID: 37883979 PMCID: PMC10645563 DOI: 10.1016/j.ajhg.2023.10.006] [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: 07/05/2023] [Revised: 10/05/2023] [Accepted: 10/08/2023] [Indexed: 10/28/2023] Open
Abstract
As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.
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Affiliation(s)
- Jodell E Linder
- Vanderbilt University Medical Center, Nashville, TN 37203, USA.
| | - Ran Tao
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | | | | | - Cong Liu
- Columbia University, New York, NY 10032, USA
| | | | - John J Connolly
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Hakon Hakonarson
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Margaret Harr
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kathleen A Leppig
- Genetic Services, Kaiser Permanente of Washington, Seattle, WA 98195, USA
| | - Gail P Jarvik
- University of Washington Medical Center, Departments of Medicine (Medical Genetics) and Genome Sciences, Seattle, WA 98195, USA
| | - David L Veenstra
- University of Washington, Department of Pharmacy, Seattle, WA 98195, USA
| | - Sharon Aufox
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Rex L Chisholm
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Adam S Gordon
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Christin Hoell
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | | | - Maureen E Smith
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | | | - Erin M Miller
- Division of Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, OH, USA
| | - Cynthia A Prows
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | | | | | | | - Sheethal Jose
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Teri A Manolio
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | | | | | - Brittany City
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Wei-Qi Wei
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | | | | | - Janet L Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
| | - Marc S Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
| | - Josh F Peterson
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
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4
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Guo B, Knerr S, Kauffman TL, Mittendorf KF, Keast E, Gilmore MJ, Feigelson HS, Lynch FL, Muessig KR, Okuyama S, Zepp JM, Veenstra DL, Hsu L, Phipps AI, Lindström S, Leo MC, Goddard KAB, Wilfond BS, Devine B. Risk management actions following genetic testing in the Cancer Health Assessments Reaching Many (CHARM) Study: A prospective cohort study. Cancer Med 2023; 12:19112-19125. [PMID: 37644850 PMCID: PMC10557878 DOI: 10.1002/cam4.6485] [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: 06/20/2023] [Revised: 08/07/2023] [Accepted: 08/18/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Genetic testing can identify cancer risk early, enabling prevention and early detection. We describe use of risk management interventions following genetic testing in the Cancer Health Assessment Reaching Many (CHARM) study. CHARM assessed risk and provided genetic testing to low income, low literacy, and other underserved populations that historically face barriers to accessing cancer genetic services. METHODS CHARM was implemented in Kaiser Permanente Northwest (KPNW) and Denver Health (DH) between 2018 and 2020. We identified post-testing screening (mammography, breast MRI, colonoscopy) and surgical (mastectomy, oophorectomy) procedures using electronic health records. We examined utilization in participants who did and did not receive actionable risk management recommendations from study genetic counselors following national guidelines. RESULTS CHARM participants were followed for an average of 15.4 months (range: 0.4-27.8 months) after results disclosure. Less than 2% (11/680) received actionable risk management recommendations (i.e., could be completed in the initial years following testing) based on their test result. Among those who received actionable recommendations, risk management utilization was moderate (54.5%, 6/11 completed any procedure) and varied by procedure (mammogram: 0/3; MRI: 2/4; colonoscopy: 4/5; mastectomy: 1/5; oophorectomy: 0/3). Cancer screening and surgery procedures were rare in participants without actionable recommendations. CONCLUSION Though the number of participants who received actionable risk management recommendations was small, our results suggest that implementing CHARM's risk assessment and testing model increased access to evidence-based genetic services and provided opportunities for patients to engage in recommended preventive care, without encouraging risk management overuse.
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Affiliation(s)
- Boya Guo
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - Sarah Knerr
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - Tia L. Kauffman
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Kathleen F. Mittendorf
- Vanderbilt‐Ingram Cancer CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Erin Keast
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Marian J. Gilmore
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | | | - Frances L. Lynch
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Kristin R. Muessig
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - Sonia Okuyama
- Division of Oncology, Denver Health and Hospital AuthorityDenverColoradoUSA
| | - Jamilyn M. Zepp
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - David L. Veenstra
- The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Li Hsu
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Amanda I. Phipps
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Sara Lindström
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Michael C. Leo
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Katrina A. B. Goddard
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - Benjamin S. Wilfond
- Treuman Katz Center for Pediatric BioethicsSeattle Children's Research InstituteSeattleWashingtonUSA
- Department of Pediatrics, Division of Bioethics and Palliative CareUniversity of WashingtonSeattleWashingtonUSA
| | - Beth Devine
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
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5
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Davies L, Angelos P. Medullary Thyroid Carcinoma and Population Screening-The Promise and Pitfalls of Genetic Testing. JAMA Otolaryngol Head Neck Surg 2023; 149:202-203. [PMID: 36602793 DOI: 10.1001/jamaoto.2022.4196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Louise Davies
- VA Outcomes Group, Department of Veterans Affairs Medical Center, White River Junction, Vermont.,Section of Otolaryngology-Head & Neck Surgery, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.,The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.,Associate Editor, JAMA Otolaryngology-Head & Neck Surgery
| | - Peter Angelos
- Section of General Surgery and Surgical Oncology, Department of Surgery, The University of Chicago, Chicago, Illinois.,MacLean Center for Clinical Medical Ethics, The University of Chicago, Chicago, Illinois
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6
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Jones LK, Strande NT, Calvo EM, Chen J, Rodriguez G, McCormick CZ, Hallquist MLG, Savatt JM, Rocha H, Williams MS, Sturm AC, Buchanan AH, Glasgow RE, Martin CL, Rahm AK. A RE-AIM Framework Analysis of DNA-Based Population Screening: Using Implementation Science to Translate Research Into Practice in a Healthcare System. Front Genet 2022; 13:883073. [PMID: 35692820 PMCID: PMC9174580 DOI: 10.3389/fgene.2022.883073] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction: DNA-based population screening has been proposed as a public health solution to identify individuals at risk for serious health conditions who otherwise may not present for medical care. The clinical utility and public health impact of DNA-based population screening is a subject of active investigation. Geisinger, an integrated healthcare delivery system, was one of the first healthcare systems to implement DNA screening programs (MyCode Community Health Initiative (MyCode) and clinical DNA screening pilot) that leverage exome data to identify individuals at risk for developing conditions with potential clinical actionability. Here, we demonstrate the use of an implementation science framework, RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance), to conduct a post-hoc evaluation and report outcomes from these two programs to inform the potential impact of DNA-based population screening. Methods: Reach and Effectiveness outcomes were determined from the MyCode research program, while Adoption and Implementation outcomes were measured using the clinical DNA screening pilot. Reach was defined as the number of patients who were offered and consented to participate in MyCode. Effectiveness of DNA screening was measured by reviewing MyCode program publications and synthesizing findings from themes. Adoption was measured by the total number of DNA screening tests ordered by clinicians at the clinical pilot sites. Implementation was assessed by interviewing a subset of clinical pilot clinicians about the deployment of and recommended adaptations to the pilot that could inform future program dissemination. Results:Reach: As of August 2020, 68% (215,078/316,612) of individuals approached to participate in the MyCode program consented. Effectiveness: Published evidence reported from MyCode demonstrates that DNA screening identifies at-risk individuals more comprehensively than clinical ascertainment based on phenotypes or personal/family history. Adoption: From July 2018 to June 2021, a total of 1,026 clinical DNA screening tests were ordered by 60 clinicians across the three pilot clinic sites. Implementation: Interviews with 14 clinicians practicing at the pilot clinic sites revealed motivation to provide patients with DNA screening results and yielded future implementation strategies. Conclusion: The RE-AIM framework offers a pragmatic solution to organize, analyze, and report outcomes across differently resourced and designed precision health programs that include genomic sequencing and return of clinically actionable genomic information.
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Affiliation(s)
- Laney K. Jones
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Natasha T. Strande
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Evan M. Calvo
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Jingheng Chen
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | | | | | | | - Juliann M. Savatt
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Amy C. Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Russell E. Glasgow
- University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Christa L. Martin
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Alanna Kulchak Rahm
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- *Correspondence: Alanna Kulchak Rahm,
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7
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Espinel W, Champine M, Hampel H, Jeter J, Sweet K, Pilarski R, Pearlman R, Shane K, Brock P, Westman JA, Kipnis L, Sotelo J, Chittenden A, Culver S, Stopfer JE, Schneider KA, Sacca R, Koeller DR, Gaonkar S, Vaccari E, Kane S, Michalski ST, Yang S, Nielsen SM, Bristow SL, Lincoln SE, Nussbaum RL, Esplin ED. Clinical Impact of Pathogenic Variants in DNA Damage Repair Genes beyond BRCA1 and BRCA2 in Breast and Ovarian Cancer Patients. Cancers (Basel) 2022; 14:cancers14102426. [PMID: 35626031 PMCID: PMC9139211 DOI: 10.3390/cancers14102426] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary The clinical utility of positive findings in DNA damage-repair (DDR) genes BRCA1 and BRCA2 for the treatment of patients with breast or ovarian cancer is well established. However, multigene panel genetic testing for patients with breast and ovarian cancer now commonly includes DDR genes in addition to BRCA1 and BRCA2, a number of which are considered moderate or low-risk genes. This study aimed to describe the clinical utility of positive results from genetic testing when the findings were in one of these other DDR genes. In a group of 101 women with positive findings in a cancer gene other than BRCA1 or BRCA2 (often in a DDR gene), nearly three-fifths (58%) had a clinical recommendation made based on their positive genetic test result and two-thirds (65%) had the clinician make recommendations for family members that may be at risk. This real-world data provides evidence that positive findings from genetic testing for moderate and low-risk genes, including DDR genes, can have clinical utility and can impact a patient’s clinical management. Abstract Consensus guidelines for hereditary breast and ovarian cancer include management recommendations for pathogenic/likely pathogenic (P/LP) variants in ATM, CHEK2, PALB2, and other DNA damage repair (DDR) genes beyond BRCA1 or BRCA2. We report on clinical management decisions across three academic medical centers resulting from P/LP findings in DDR genes in breast/ovarian cancer patients. Among 2184 patients, 156 (7.1%) carried a P/LP variant in a DDR gene. Clinical follow-up information was available for 101/156 (64.7%) patients. Genetic test result-based management recommendations were made for 57.8% (n = 59) of patients and for 64.7% (n = 66) of patients’ family members. Most recommendations were made for moderate-to-high risk genes and were consistent with guidelines. Sixty-six percent of patients (n = 39/59) implemented recommendations. This study suggests that P/LP variants in DDR genes beyond BRCA1 and BRCA2 can change clinical management recommendations for patients and their family members, facilitate identification of new at-risk carriers, and impact treatment decisions. Additional efforts are needed to improve the implementation rates of genetic-testing-based management recommendations for patients and their family members.
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Affiliation(s)
- Whitney Espinel
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA; (W.E.); (M.C.)
| | - Marjan Champine
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA; (W.E.); (M.C.)
| | - Heather Hampel
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Joanne Jeter
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Kevin Sweet
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Robert Pilarski
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Rachel Pearlman
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Kate Shane
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Pamela Brock
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Judith A. Westman
- Ohio State University Medical Center, Columbus, OH 43210, USA; (H.H.); (J.J.); (K.S.); (R.P.); (R.P.); (K.S.); (P.B.); (J.A.W.)
| | - Lindsay Kipnis
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Jilliane Sotelo
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Anu Chittenden
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Samantha Culver
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Jill E. Stopfer
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Katherine A. Schneider
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Rosalba Sacca
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Diane R. Koeller
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Shraddha Gaonkar
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Erica Vaccari
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Sarah Kane
- Dana Farber Cancer Institute, Boston, MA 02215, USA; (L.K.); (J.S.); (A.C.); (S.C.); (J.E.S.); (K.A.S.); (R.S.); (D.R.K.); (S.G.); (E.V.); (S.K.)
| | - Scott T. Michalski
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Shan Yang
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Sarah M. Nielsen
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Sara L. Bristow
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Stephen E. Lincoln
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Robert L. Nussbaum
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
| | - Edward D. Esplin
- Invitae, San Francisco, CA 94103, USA; (S.T.M.); (S.Y.); (S.M.N.); (S.L.B.); (S.E.L.); (R.L.N.)
- Correspondence: ; Tel.: +1-800-436-3037
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8
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The promise and pitfalls of gene testing for cancer risk. Nature 2021. [PMID: 34912097 DOI: 10.1038/d41586-021-03720-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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9
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A Cost Decision Model Supporting Treatment Strategy Selection in BRCA1/2 Mutation Carriers in Breast Cancer. J Pers Med 2021; 11:jpm11090847. [PMID: 34575624 PMCID: PMC8470684 DOI: 10.3390/jpm11090847] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/21/2021] [Accepted: 08/25/2021] [Indexed: 01/08/2023] Open
Abstract
In this paper, a cost decision-making model that compares the healthcare costs for diverse treatment strategies is built for BRCA-mutated women with breast cancer. Moreover, this model calculates the cancer treatment costs that could potentially be prevented, if the treatment strategy with the lowest total cost, along the entire lifetime of the patient, is chosen for high-risk women with breast cancer. The benchmark of the healthcare costs for diverse treatment strategies is selected in the presence of uncertainty, i.e., considering, throughout the lifetime of the patient, the risks and complications that may arise in each strategy and, therefore, the costs associated with the management of such events. Our results reveal a clear economic advantage of adopting the cost decision-making model for benchmarking the healthcare costs for various treatment strategies for BRCA-mutated women with breast cancer. The cost savings were higher when all breast cancer patients underwent counseling and genetic testing before deciding on any diagnostic-therapeutic path, with a probability of obtaining savings of over 75%.
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10
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Sapp JC, Facio FM, Cooper D, Lewis KL, Modlin E, van der Wees P, Biesecker LG. A systematic literature review of disclosure practices and reported outcomes for medically actionable genomic secondary findings. Genet Med 2021; 23:2260-2269. [PMID: 34433902 PMCID: PMC9017985 DOI: 10.1038/s41436-021-01295-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 07/15/2021] [Accepted: 07/20/2021] [Indexed: 01/14/2023] Open
Abstract
Purpose: Secondary findings (SF) are present in 1–4% of individuals undergoing genome/exome sequencing. A review of how SF are disclosed and what outcomes result from their receipt is urgent and timely. Methods: We conducted a systematic literature review of SF disclosure practices and outcomes after receipt including cascade testing, family and provider communication, and healthcare actions. Of the 1,184 non-duplicate records screened we summarize findings from 27 included research articles describing SF disclosure practices, outcomes after receipt, or both. Results: The included articles reported 709 unique SF index recipients/families. Referrals and/or recommendations were provided 647 SF recipients and outcome data were available for 236. At least one recommended evaluation was reported for 146 SF recipients; 16 reports of treatment or prophylactic surgery were identified. We found substantial variations in how the constructs of interest were defined and described. Conclusion: Variation in how SF disclosure and outcomes were described limited our ability to compare findings. We conclude the literature provided limited insight into how the ACMG guidelines have been translated into precision health outcomes for SF recipients. Robust studies of SF recipients are needed and should be prioritized for future research.
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Affiliation(s)
- Julie C Sapp
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA. .,Translational Health Sciences, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
| | - Flavia M Facio
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Diane Cooper
- National Institutes of Health Library, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Katie L Lewis
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Emily Modlin
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Philip van der Wees
- Translational Health Sciences, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Radboud University Medical Center, IQ Healthcare and Rehabilitation, Nijmegen, Netherlands
| | - Leslie G Biesecker
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
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11
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Ficarazzi F, Vecchi M, Ferrari M, Pierotti MA. Towards population-based genetic screenings for breast and ovarian cancer: A comprehensive review from economic evaluations to patient perspectives. Breast 2021; 58:121-129. [PMID: 34022715 PMCID: PMC8164087 DOI: 10.1016/j.breast.2021.04.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/28/2021] [Accepted: 04/30/2021] [Indexed: 12/16/2022] Open
Abstract
Genetic testing for hereditary breast and ovarian cancer following genetic counseling is based on guidelines that take into account particular features of the personal and family history, and clinical criteria conferring a probability of having a BRCA mutation greater than 10% as a threshold for accessing the test. However, besides reducing mortality and social impact, the extension of screening programs also for healthy family members would allow a huge saving of the rising costs associated with these pathologies, supporting the choice of the "Test" strategy versus a "No Test" one. Analyses of different health care systems show that by applying the "Test" strategy on patients and their families, a decrease in breast and ovarian cancer cases is achieved, as well as a substantial decrease in costs of economic resources, including the costs of the clinical management of early detected tumors. In this review, we analyzed the most recent papers published on this topic and we summarized the findings on the economic evaluations related to breast and ovarian cancer population screenings. These results proved and validated that the population-wide testing approach is a more accurate screening and preventive intervention than traditional guidelines based on personal/family history and clinical criteria to reduce breast and ovarian cancer risk.
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Affiliation(s)
| | - Manuela Vecchi
- Cogentech Ltd Benefit Corp, Via Adamello 16, 20139, Milan, Italy
| | - Maurizio Ferrari
- Cogentech Ltd Benefit Corp, Via Adamello 16, 20139, Milan, Italy; Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy
| | - Marco A Pierotti
- Cogentech Ltd Benefit Corp, Via Adamello 16, 20139, Milan, Italy; IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Via Adamello 16, 20139, Milan, Italy.
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12
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Fan X, Wynn J, Shang N, Liu C, Fedotov A, Hallquist MLG, Buchanan AH, Williams MS, Smith ME, Hoell C, Rasmussen-Torvik LJ, Peterson JF, Wiesner GL, Murad AM, Jarvik GP, Gordon AS, Rosenthal EA, Stanaway IB, Crosslin DR, Larson EB, Leppig KA, Henrikson NB, Williams JL, Li R, Hebbring S, Weng C, Shen Y, Crew KD, Chung WK. Penetrance of Breast Cancer Susceptibility Genes From the eMERGE III Network. JNCI Cancer Spectr 2021; 5:pkab044. [PMID: 34377931 PMCID: PMC8346699 DOI: 10.1093/jncics/pkab044] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/08/2021] [Accepted: 04/22/2021] [Indexed: 01/03/2023] Open
Abstract
Background Unbiased estimates of penetrance are challenging but critically important to make informed choices about strategies for risk management through increased surveillance and risk-reducing interventions. Methods We studied the penetrance and clinical outcomes of 7 breast cancer susceptibility genes (BRCA1, BRCA2, TP53, CHEK2, ATM, PALB2, and PTEN) in almost 13 458 participants unselected for personal or family history of breast cancer. We identified 242 female participants with pathogenic or likely pathogenic variants in 1 of the 7 genes for penetrance analyses, and 147 women did not previously know their genetic results. Results Out of the 147 women, 32 women were diagnosed with breast cancer at an average age of 52.8 years. Estimated penetrance by age 60 years ranged from 17.8% to 43.8%, depending on the gene. In clinical-impact analysis, 42.3% (95% confidence interval = 31.3% to 53.3%) of women had taken actions related to their genetic results, and 2 new breast cancer cases were identified within the first 12 months after genetic results disclosure. Conclusions Our study provides population-based penetrance estimates for the understudied genes CHEK2, ATM, and PALB2 and highlights the importance of using unselected populations for penetrance studies. It also demonstrates the potential clinical impact of genetic testing to improve health care through early diagnosis and preventative screening.
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Affiliation(s)
- Xiao Fan
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Julia Wynn
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Ning Shang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Alexander Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY, USA
| | | | | | | | - Maureen E Smith
- Department of Medicine, Northwestern University, Chicago Feinberg School of Medicine, Chicago, IL, USA
| | - Christin Hoell
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Georgia L Wiesner
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrea M Murad
- Division of Genetic Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Gail P Jarvik
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Adam S Gordon
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Ian B Stanaway
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - David R Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington Medical Center, Seattle, WA, USA
| | - Eric B Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Kathleen A Leppig
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nora B Henrikson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Rongling Li
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic, Marshfield, WI, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Katherine D Crew
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
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13
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Kelly MA, Leader JB, Wain KE, Bodian D, Oetjens MT, Ledbetter DH, Martin CL, Strande NT. Leveraging population-based exome screening to impact clinical care: The evolution of variant assessment in the Geisinger MyCode research project. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2021; 187:83-94. [PMID: 33576083 DOI: 10.1002/ajmg.c.31887] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 12/24/2020] [Accepted: 12/28/2020] [Indexed: 02/06/2023]
Abstract
Exome and genome sequencing are increasingly utilized in research studies and clinical care and can provide clinically relevant information beyond the initial intent for sequencing, including medically actionable secondary findings. Despite ongoing debate about sharing this information with patients and participants, a growing number of clinical laboratories and research programs routinely report secondary findings that increase the risk for selected diseases. Recently, there has been a push to maximize the potential benefit of this practice by implementing proactive genomic screening at the population level irrespective of medical history, but the feasibility of deploying population-scale proactive genomic screening requires scaling key elements of the genomic data evaluation process. Herein, we describe the motivation, development, and implementation of a population-scale variant-first screening pipeline combining bioinformatics-based filtering with a manual review process to screen for clinically relevant findings in research exomes generated through the DiscovEHR collaboration within Geisinger's MyCode® research project. Consistent with other studies, this pipeline yields a screen-positive detection rate between 2.1 and 2.6% (depending on inclusion of those with prior indication-based testing) in 130,048 adult MyCode patient-participants screened for clinically relevant findings in 60 genes. Our variant-first pipeline affords cost and time savings by filtering out negative cases, thereby avoiding analysis of each exome one-by-one, as typically employed in the diagnostic setting. While research is still needed to fully appreciate the benefits of population genomic screening, MyCode provides the first demonstration of a program at scale to help shape how population genomic screening is integrated into routine clinical care.
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Affiliation(s)
| | | | - Karen E Wain
- Geisinger Medical Center, Danville, Pennsylvania, USA
| | - Dale Bodian
- Geisinger Medical Center, Danville, Pennsylvania, USA
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14
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Guzauskas GF, Garbett S, Zhou Z, Spencer SJ, Smith HS, Hao J, Hassen D, Snyder SR, Graves JA, Peterson JF, Williams MS, Veenstra DL. Cost-effectiveness of Population-Wide Genomic Screening for Hereditary Breast and Ovarian Cancer in the United States. JAMA Netw Open 2020; 3:e2022874. [PMID: 33119106 PMCID: PMC7596578 DOI: 10.1001/jamanetworkopen.2020.22874] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
IMPORTANCE Genomic screening for hereditary breast and ovarian cancer (HBOC) in unselected women offers an opportunity to prevent cancer morbidity and mortality, but the potential clinical impact and cost-effectiveness of such screening have not been well studied. OBJECTIVE To estimate the lifetime incremental incidence of HBOC and the quality-adjusted life-years (QALYs), costs, and cost-effectiveness of HBOC genomic screening in an unselected population vs family history-based testing. DESIGN, SETTING, AND PARTICIPANTS In this study conducted from October 27, 2017, to May 3, 2020, a decision analytic Markov model was developed that included health states for precancer, for risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), for earlier- and later-stage HBOC, after cancer, and for death. A complimentary cascade testing module was also developed to estimate outcomes in first-degree relatives. Age-specific RRM and RRSO uptake probabilities were estimated from the Geisinger MyCode Community Health Initiative and published sources. Parameters including RRM and RRSO effectiveness, variant-specific cancer risk, costs, and utilities were derived from published sources. Sensitivity and scenario analyses were conducted to evaluate model assumptions and uncertainty. MAIN OUTCOMES AND MEASURES Lifetime cancer incidence, QALYs, life-years, and direct medical costs for genomic screening in an unselected population vs family history-based testing only were calculated. The incremental cost-effectiveness ratio (ICER) was calculated as the difference in cost between strategies divided by the difference in QALYs between strategies. Earlier-stage and later-stage cancer cases prevented and total cancer cases prevented were also calculated. RESULTS The model found that population screening of 30-year-old women was associated with 75 (95% credible range [CR], 60-90) fewer overall cancer cases and 288 QALYs (95% CR, 212-373 QALYs) gained per 100 000 women screened, at an incremental cost of $25 million (95% CR, $21 millon to $30 million) vs family history-based testing; the ICER was $87 700 (78% probability of being cost-effective at a threshold of $100 000 per QALY). In contrast, population screening of 45-year-old women was associated with 24 (95% CR, 18-29) fewer cancer cases and 97 QALYs (95% CR, 66-130 QALYs) gained per 100 000 women screened, at an incremental cost of $26 million (95% CR, $22 million to $30 million); the ICER was $268 200 (0% probability of being cost-effective at a threshold of $100 000 per QALY). A scenario analysis without cascade testing increased the ICER to $92 600 for 30-year-old women and $354 500 for 45-year-old women. A scenario analysis assuming a 5% absolute decrease in mammography screening in women without a variant was associated with the potential for net harm (-90 QALYs per 100 000 women screened; 95% CR, -180 to 10 QALYs). CONCLUSIONS AND RELEVANCE The results of this study suggest that population HBOC screening may be cost-effective among younger women but not among older women. Cascade testing of first-degree relatives added a modest improvement in clinical and economic value. The potential for harm conferred by inappropriate reduction in mammography among noncarriers should be quantified.
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Affiliation(s)
- Gregory F. Guzauskas
- The Comparative Health Outcomes, Policy & Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle
| | - Shawn Garbett
- Department of Biostatistics, Vanderbilt University, Nashville, Tennessee
| | - Zilu Zhou
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Scott J. Spencer
- Institute for Public Health Genetics, University of Washington, Seattle
| | - Hadley S. Smith
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas
| | - Jing Hao
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Dina Hassen
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Susan R. Snyder
- Department of Health Policy and Behavioral Sciences, Georgia State University, Atlanta
| | - John A. Graves
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - David L. Veenstra
- The Comparative Health Outcomes, Policy & Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle
- Institute for Public Health Genetics, University of Washington, Seattle
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