دورية أكاديمية

Cost-effectiveness of the McGill interactive pediatric oncogenetic guidelines in identifying Li-Fraumeni syndrome in female patients with osteosarcoma.

التفاصيل البيبلوغرافية
العنوان: Cost-effectiveness of the McGill interactive pediatric oncogenetic guidelines in identifying Li-Fraumeni syndrome in female patients with osteosarcoma.
المؤلفون: Rios JD; Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada., Simbulan F; Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada.; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada., Reichman L; Child Health and Human Development, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada., Caswell K; Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada., Tachdjian M; Child Health and Human Development, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada., Malkin D; Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.; Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada.; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada., Cotton C; Department of Statistics and Actuarial Sciences, University of Waterloo, Waterloo, Ontario, Canada., Nathan PC; Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada.; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.; Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.; Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada., Goudie C; Child Health and Human Development, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.; Department of Pediatrics, Division of Hematology-Oncology, McGill University Health Centre, Montreal, Quebec, Canada., Pechlivanoglou P; Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada.; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
المصدر: Pediatric blood & cancer [Pediatr Blood Cancer] 2024 Aug; Vol. 71 (8), pp. e31077. Date of Electronic Publication: 2024 May 23.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: John Wiley Country of Publication: United States NLM ID: 101186624 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1545-5017 (Electronic) Linking ISSN: 15455009 NLM ISO Abbreviation: Pediatr Blood Cancer Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Hoboken, N.J. : John Wiley, c 2004-
مواضيع طبية MeSH: Osteosarcoma*/economics , Osteosarcoma*/genetics , Osteosarcoma*/diagnosis , Li-Fraumeni Syndrome*/genetics , Li-Fraumeni Syndrome*/diagnosis , Li-Fraumeni Syndrome*/economics , Cost-Benefit Analysis*, Humans ; Female ; Child ; Adolescent ; Bone Neoplasms/genetics ; Bone Neoplasms/economics ; Genetic Testing/economics ; Genetic Testing/methods ; Practice Guidelines as Topic ; Quality-Adjusted Life Years ; Breast Neoplasms/genetics ; Breast Neoplasms/economics
مستخلص: Background: Li-Fraumeni syndrome (LFS) is a penetrant cancer predisposition syndrome (CPS) associated with the development of many tumor types in young people including osteosarcoma and breast cancer (BC). The McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG) decision-support tool provides a standardized approach to identify patients at risk of CPSs.
Methods: We conducted a cost-utility analysis, from the healthcare payer perspective, to compare MIPOGG-guided, physician-guided, and universal genetic testing strategies to detect LFS in female patients diagnosed at an age of less than 18 years with osteosarcoma. We developed a decision tree and discrete-event simulation model to simulate the clinical and cost outcomes of the three genetic referral strategies on a cohort of female children diagnosed with osteosarcoma, especially focused on BC as subsequent cancer. Outcomes included BC incidence, quality-adjusted life-years (QALYs), healthcare costs, and incremental cost-utility ratios (ICURs). We conducted probabilistic and scenario analyses to assess the uncertainty surrounding model parameters.
Results: Compared to the physician-guided testing, the MIPOGG-guided strategy was marginally more expensive by $105 (-$516; $743), but slightly more effective by 0.003 (-0.04; 0.045) QALYs. Compared to MIPOGG, the universal testing strategy was $1333 ($732; $1953) more costly and associated with 0.011 (-0.043; 0.064) additional QALYs. The ICUR for the MIPOGG strategy was $33,947/QALY when compared to the physician strategy; the ICUR for universal testing strategy was $118,631/QALY when compared to the MIPOGG strategy.
Discussion: This study provides evidence for clinical and policy decision-making on the cost-effectiveness of genetic referral strategies to identify LFS in the setting of osteosarcoma. MIPOGG-guided strategy was most likely to be cost-effective at a willingness-to-pay threshold value of $50,000/QALY.
(© 2024 The Authors. Pediatric Blood & Cancer published by Wiley Periodicals LLC.)
References: Knapke S, Nagarajan R, Correll J, Kent D, Burns K. Hereditary cancer risk assessment in a pediatric oncology follow‐up clinic. Pediatr Blood Cancer. 2011;58:85‐89.
Rahman N. Realizing the promise of cancer predisposition genes. Nature. 2014;505:302‐308.
Nichols KE, Malkin D, Garber JE, Fraumeni JF, Li FP. Germ‐line p53 mutations predispose to a wide spectrum of early‐onset cancers. Cancer Epidemiol Biomarkers Prev. 2001;10:83‐87.
de Andrade KC, Khincha PP, Hatton JN, et al. Cancer incidence, patterns, and genotype–phenotype associations in individuals with pathogenic or likely pathogenic germline TP53 variants: an observational cohort study. Lancet Oncol. 2021;22:1787‐1798.
Foulkes WD, Kamihara J, Evans DGR, et al. Cancer surveillance in Gorlin syndrome and rhabdoid tumor predisposition syndrome. Clin Cancer Res. 2017;23:e62‐e67.
Villani A, Shore A, Wasserman JD, et al. Biochemical and imaging surveillance in germline TP53 mutation carriers with Li–Fraumeni syndrome: 11 year follow‐up of a prospective observational study. Lancet Oncol. 2016;17:1295‐1305.
Tak CR, Biltaji E, Kohlmann W, et al. Cost‐effectiveness of early cancer surveillance for patients with Li–Fraumeni syndrome. Pediatr Blood Cancer. 2019;66:e27629.
Mirabello L, Troisi RJ, Savage SA. Osteosarcoma incidence and survival rates from 1973 to 2004. Cancer. 2009;115:1531‐1543.
Druker H, Zelley K, McGee RB, et al. Genetic counselor recommendations for cancer predisposition evaluation and surveillance in the pediatric oncology patient. Clin Cancer Res. 2017;23:e91‐e97.
Sun L, Brentnall A, Patel S, et al. A cost‐effectiveness analysis of multigene testing for all patients with breast cancer. JAMA Oncol. 2019;5:1718.
Hayeems RZ, Bhawra J, Tsiplova K, et al. Care and cost consequences of pediatric whole genome sequencing compared to chromosome microarray. Eur J Hum Genet. 2017;25:1303‐1312.
Codori A‐M, Zawacki KL, Petersen GM, et al. Genetic testing for hereditary colorectal cancer in children: long‐term psychological effects. Am J Med Genet. 2003;116A:117‐128.
Goudie C, Witkowski L, Cullinan N, et al. Performance of the McGill interactive pediatric oncogenetic guidelines for identifying cancer predisposition syndromes. JAMA Oncol. 2021;7(12):1806‐1814.
Cullinan N, Schiller I, Di Giuseppe G, et al. Utility of a cancer predisposition screening tool for predicting subsequent malignant neoplasms in childhood cancer survivors. J Clin Oncol. 2021;39:3207‐3216.
Guidelines for the Economic Evaluation of Health Technologies: Canada. 4th ed. Canadian Agency For Drugs And Technologies In Health; 2017.
Briggs AH, Weinstein MC, Fenwick EAL, Karnon J, Sculpher MJ, Paltiel AD. Model parameter estimation and uncertainty: a report of the ISPOR‐SMDM Modeling Good Research Practices Task Force‐6. Value Health. 2012;15:835‐842.
Alderfer MA, Zelley K, Lindell RB, et al. Parent decision‐making around the genetic testing of children for germline TP53 mutations. Cancer. 2015;121:286‐293.
Furzer J, Tessier L, Hodgson D, et al. Cost–utility of early breast cancer surveillance in survivors of thoracic radiation‐treated adolescent Hodgkin lymphoma. J Natl Cancer Inst. 2019;112:63‐70.
Hodgson DC, Cotton C, Crystal P, Nathan PC. Impact of early breast cancer screening on mortality among young survivors of childhood Hodgkin's lymphoma. J Natl Cancer Inst. 2016;108:djw010.
Children's Oncology Group. Long‐Term Follow‐Up Guidelines for Survivors of Childhood, Adolescent, and Young Adult Cancers, Version 5.0. Children's Oncology Group; 2018.
SEER. SEER*Stat Database: incidence ‐ SEER research data, 9 registries, Nov 2019 Sub (1975–2017) ‐ linked to county attributes ‐ time dependent (1990–2017) income/rurality, 1969‐20. Surveillance, Epidemiology, and End Results; 2020.
SEER. SEER*Stat Database: incidence ‐ SEER 18 Regs research data + hurricane Katrina impacted Louisiana cases, Nov 2019 Sub (2000–2017 varying) ‐ linked to county attributes ‐ Tot. Surveillance, Epidemiology, and End Results (SEER); 2020.
Mai PL, Best AF, Peters JA, et al. Risks of first and subsequent cancers among∖emphTP53mutation carriers in the National Cancer Institute Li–Fraumeni syndrome cohort. Cancer. 2016;122:3673‐3681.
Mirabello L, Yeager M, Mai PL, et al. Germline TP53 variants and susceptibility to osteosarcoma. J Natl Cancer Inst. 2015;107:djv101. doi:10.1093/jnci/djv101.
Tieu MT, Cigsar C, Ahmed S, et al. Breast cancer detection among young survivors of pediatric Hodgkin lymphoma with screening magnetic resonance imaging. Cancer. 2014;120:2507‐2513.
Ontario Health. The Ontario Cancer Screening Performance Report 2020. Ontario Health (Cancer Care Ontario); 2021.
Mittmann N, Stout NK, Lee P, et al. Total cost‐effectiveness of mammography screening strategies. Health Rep. 2015;26:16.
Alyacoob H. Cost‐effectiveness of combining MRI with mammography for breast cancer screening among high‐risk population in Ottawa. ProQuest Dissertations and Theses; 2014.
Ontario Ministry of Healh and Long‐Term Care. OHIP Schedule of Benefits and Fees, Physician Services under the Health Insurance Act. Ontario Ministry of Healh and Long‐Term Care; 2016.
Mittmann N, Porter JM, Rangrej J, et al. Health system costs for stage‐specific breast cancer: a population‐based approach. Curr Oncol. 2014;21:281‐293.
de Oliveira C, Pataky R, Bremner KE, et al. Phase‐specific and lifetime costs of cancer care in Ontario, Canada. BMC Cancer. 2016;16:809. doi:10.1186/s12885‐016‐2835‐7.
Cott Chubiz JE, Lee JM, Gilmore ME, et al. Cost‐effectiveness of alternating magnetic resonance imaging and digital mammography screening in BRCA1 and BRCA2 gene mutation carriers. Cancer. 2012;119:1266‐1276.
Technical Supplement for the November 2020 Consumer Price Index. Statistics Canada; 2020.
Yeh JM, Hanmer J, Ward ZJ, et al. Chronic conditions and utility‐based health‐related quality of life in adult childhood cancer survivors. J Natl Cancer Inst. 2016;108:djw046.
Ara R, Wailoo A. NICE DSU Technical Support Document 12: The Use of Health State Utility Values in Decision Models. National Institute for Health and Care Excellence (NICE), UK; 2011.
Barton GR, Briggs AH, Fenwick EAL. Optimal cost‐effectiveness decisions: the role of the cost‐effectiveness acceptability curve (CEAC), the cost‐effectiveness acceptability frontier (CEAF), and the expected value of perfection information (EVPI). Value Health. 2008;11:886‐897.
R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing; 2021. Accessed May 15, 2024. https://www.R‐project.org/.
Alarid‐Escudero F, Krijkamp EM, Pechlivanoglou P, et al. A need for change! A coding framework for improving transparency in decision modeling. Pharmacoeconomics. 2019;37:1329‐1339.
Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer‐Verlag; 2016. Accessed May 15, 2024. https://ggplot2.tidyverse.org.
Wickham H, François R, Henry L, Müller K. dplyr: a grammar of data manipulation. R Foundation for Statistical Computing; 2021. Accessed May 15, 2024. https://CRAN.R‐project.org/package=dplyr.
Jackson C. flexsurv: a platform for parametric survival modeling in R. J Stat Softw. 2016;70:1‐33.
The Childhood Cancer Survivor Study (CCSS). 2015. https://www.cancer.gov/types/childhood-cancers/ccss.
Varley J, Evans D, Birch J. Li–Fraumeni syndrome—a molecular and clinical review. Br J Cancer. 1997;76:1‐14.
Olivier M, Goldgar DE, Sodha N, et al. Li–Fraumeni and related syndromes: correlation between tumor type, family structure, and TP53 genotype. Cancer Res. 2003;63:6643‐6650.
Plevritis SK, Salzman P, Sigal BM, Glynn PW. A natural history model of stage progression applied to breast cancer. Stat Med. 2006;26:581‐595.
معلومات مُعتمدة: 23445 Cancer Research Society; FDN143234 Canadian Institutes for Health Research
فهرسة مساهمة: Keywords: Li–Fraumeni syndrome; MIPOGG; cost–utility analysis; osteosarcoma
تواريخ الأحداث: Date Created: 20240524 Date Completed: 20240626 Latest Revision: 20240626
رمز التحديث: 20240627
DOI: 10.1002/pbc.31077
PMID: 38783403
قاعدة البيانات: MEDLINE
الوصف
تدمد:1545-5017
DOI:10.1002/pbc.31077