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Hernando-Calvo A, Nguyen P, Bedard PL, Chan KK, Saleh RR, Weymann D, Yu C, Amir E, Regier DA, Gyawali B, Kain D, Wilson B, Earle CC, Mittmann N, Abdul Razak AR, Isaranuwatchai W, Sabatini P, Spreafico A, Stockley TL, Pugh TJ, Williams C, Siu LL, Hanna TP. Impact on costs and outcomes of multi-gene panel testing for advanced solid malignancies: a cost-consequence analysis using linked administrative data. EClinicalMedicine 2024; 69:102443. [PMID: 38380071 PMCID: PMC10876574 DOI: 10.1016/j.eclinm.2024.102443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/22/2024] Open
Abstract
Background To date, economic analyses of tissue-based next generation sequencing genomic profiling (NGS) for advanced solid tumors have typically required models with assumptions, with little real-world evidence on overall survival (OS), clinical trial enrollment or end-of-life quality of care. Methods Cost consequence analysis of NGS testing (555 or 161-gene panels) for advanced solid tumors through the OCTANE clinical trial (NCT02906943). This is a longitudinal, propensity score-matched retrospective cohort study in Ontario, Canada using linked administrative data. Patients enrolled in OCTANE at Princess Margaret Cancer Centre from August 2016 until March 2019 were matched with contemporary patients without large gene panel testing from across Ontario not enrolled in OCTANE. Patients were matched according to 19 patient, disease and treatment variables. Full 2-year follow-up data was available. Sensitivity analyses considered alternative matched cohorts. Main Outcomes were mean per capita costs (2019 Canadian dollars) from a public payer's perspective, OS, clinical trial enrollment and end-of-life quality metrics. Findings There were 782 OCTANE patients with 782 matched controls. Variables were balanced after matching (standardized difference <0.10). There were higher mean health-care costs with OCTANE ($79,702 vs. $59,550), mainly due to outpatient and specialist visits. Publicly funded drug costs were less with OCTANE ($20,015 vs. $24,465). OCTANE enrollment was not associated with improved OS (restricted mean survival time [standard error]: 1.50 (±0.03) vs. 1.44 (±0.03) years, log-rank p = 0.153), varying by tumor type. In five tumor types with ≥35 OCTANE patients, OS was similar in three (breast, colon, uterus, all p > 0.40), and greater in two (ovary, biliary, both p < 0.05). OCTANE was associated with greater clinical trial enrollment (25.4% vs. 9.5%, p < 0.001) and better end-of-life quality due to less death in hospital (10.2% vs. 16.4%, p = 0.003). Results were robust in sensitivity analysis. Interpretation We found an increase in healthcare costs associated with multi-gene panel testing for advanced cancer treatment. The impact on OS was not significant, but varied across tumor types. OCTANE was associated with greater trial enrollment, lower publicly funded drug costs and fewer in-hospital deaths suggesting important considerations in determining the value of NGS panel testing for advanced cancers. Funding T.P H holds a research grant provided by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (#IA-035 and P.HSR.158) and through funding of the Canadian Network for Learning Healthcare Systems and Cost-Effective 'Omics Innovation (CLEO) via Genome Canada (G05CHS).
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Affiliation(s)
- Alberto Hernando-Calvo
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Paul Nguyen
- ICES Queen's. Queen's University, Kingston, ON, Canada
| | - Philippe L. Bedard
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kelvin K.W. Chan
- Sunnybrook Health Sciences Centre, Odette Cancer Centre, University of Toronto, Toronto, ON, Canada
| | - Ramy R. Saleh
- Department of Medical Oncology, McGill University Health Centre, Montreal, QC, Canada
| | | | - Celeste Yu
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Eitan Amir
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Dean A. Regier
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Bishal Gyawali
- Department of Oncology, Queen's University, Kingston, ON, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada
| | - Danielle Kain
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Brooke Wilson
- Department of Oncology, Queen's University, Kingston, ON, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada
| | - Craig C. Earle
- Sunnybrook Health Sciences Centre, Odette Cancer Centre, University of Toronto, Toronto, ON, Canada
| | - Nicole Mittmann
- Sunnybrook Health Sciences Centre, Odette Cancer Centre, University of Toronto, Toronto, ON, Canada
| | - Albiruni R. Abdul Razak
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Wanrudee Isaranuwatchai
- St. Michael's Hospital Centre for Excellence in Economic Analysis Research, University of Toronto, Toronto, ON, Canada
| | - Peter Sabatini
- Advanced Molecular Diagnostic Laboratory, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Anna Spreafico
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Tracy L. Stockley
- Advanced Molecular Diagnostic Laboratory, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Trevor J. Pugh
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | | | - Lillian L. Siu
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Timothy P. Hanna
- ICES Queen's. Queen's University, Kingston, ON, Canada
- Department of Oncology, Queen's University, Kingston, ON, Canada
- Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada
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2
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Pataky RE, Bryan S, Sadatsafavi M, Peacock S, Regier DA. Real-World Cost Effectiveness of a Policy of KRAS Testing to Inform Cetuximab or Panitumumab for Third-Line Therapy of Metastatic Colorectal Cancer in British Columbia, Canada. PHARMACOECONOMICS - OPEN 2023; 7:997-1006. [PMID: 37819586 PMCID: PMC10721761 DOI: 10.1007/s41669-023-00444-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/14/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND Cetuximab and panitumumab, two anti-EGFR therapies, are widely used for third-line therapy of metastatic colorectal cancer (mCRC) with wild-type KRAS, but there remains uncertainty around their cost effectiveness. The objective of this analysis was to conduct a real-world cost-effectiveness analysis of the policy change introducing KRAS testing and third-line anti-EGFR therapy mCRC in British Columbia (BC), Canada. METHODS We conducted secondary analysis of administrative data for a cohort of mCRC patients treated in BC in 2006-2015. Patients potentially eligible for KRAS testing and third-line therapy after the policy change (July 2009) were matched 2:1 to pre-policy patients using genetic matching on propensity score and baseline covariates. Costs and survival time were calculated over an 8-year time horizon, with bootstrapping to characterize uncertainty around endpoints. Cost effectiveness was expressed using incremental cost-effectiveness ratios (ICER) and the probability of cost effectiveness at a range of thresholds. RESULTS The cohort included 1757 mCRC patients (n = 456 pre-policy and n = 1304 post-policy; of those, n = 420 received cetuximab or panitumumab). There was a significant increase in survival and cost following the policy change. Adoption of KRAS testing and anti-EGFR therapy had an ICER of CA$73,759 per life-year gained (LYG) (95% CI 46,133-186,446). In scenario analysis, a reduction in cetuximab and panitumumab cost of at least 50% was required to make the policy change cost effective at a threshold of CA$50,000/LYG. CONCLUSION A policy of third-line anti-EGFR therapy informed by KRAS testing may be considered cost effective at thresholds above CA$70,000/LYG. Reduction in drug costs, through price discounts or potential future biosimilars, would make anti-EGFR therapy considerably more cost effective. By using real-world data for a large cohort with long follow-up we can assess the value of a policy of KRAS testing and anti-EGFR therapy achieved in practice.
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Affiliation(s)
- Reka E Pataky
- Canadian Centre for Applied Research in Cancer Control, Cancer Control Research, BC Cancer, Vancouver, BC, Canada.
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.
- BC Cancer Research Centre, 675 W. 10th Ave, Vancouver, BC, V5Z 1L3, Canada.
| | - Stirling Bryan
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
| | - Mohsen Sadatsafavi
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Stuart Peacock
- Canadian Centre for Applied Research in Cancer Control, Cancer Control Research, BC Cancer, Vancouver, BC, Canada
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Dean A Regier
- Canadian Centre for Applied Research in Cancer Control, Cancer Control Research, BC Cancer, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
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3
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Wilson BE, Hay AE, Chan KKW, Cheung MC, Hanna TP. Augmenting clinical trial economic analysis by linking cancer trial data to administrative data: current landscape and future opportunities. BMJ Open 2023; 13:e073353. [PMID: 37567744 PMCID: PMC10423795 DOI: 10.1136/bmjopen-2023-073353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Economic analyses based on clinical trial data are costly and time consuming, and alternative methods for performing economic analyses should be explored. OBJECTIVE AND METHODS In this perspective, we examine the emerging role of administrative data for economic analyses in cancer. RESULTS Compared with routinely collected clinical trial data, routinely collected administrative data have several strengths including high capture rates for healthcare encounters, less resource utilisation, low rates of misclassification, long follow-up periods and the opportunity to collect data points not traditionally captured in clinical trials. However, there are also limitations including the need for accurate data linkage across multiple databases and systems, the costs and time associated with data linkage, the potential time lag between trial data collection and the availability of administrative data, and limited data on quality of life, toxicity and indirect costs. In this perspective, we identify important barriers and potential solutions to performing economic analyses for oncology using administrative data, and outline strategies to increase research in this field. CONCLUSION The use of routinely collected administrative data sets for economic analyses of clinical trials presents a unique opportunity that could complement and validate economic analyses based on trial-level data.
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Affiliation(s)
- Brooke E Wilson
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
- Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, Ontario, Canada
| | - Annette E Hay
- Department of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Kelvin Kar-Wing Chan
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Division of Hematology and Oncology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Matthew C Cheung
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Division of Hematology and Oncology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Timothy P Hanna
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
- Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, Ontario, Canada
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Shah H, Wolfe D, Clemons M, Liu M, Thavorn K, Veroniki AA, Lunny C, Pond G, McGee S, Skidmore B, Arnaout A, Hutton B. Can routinely collected administrative data effectively be used to evaluate and validate endpoints used in breast cancer clinical trials? Protocol for a scoping review of the literature. Syst Rev 2023; 12:117. [PMID: 37422656 PMCID: PMC10329388 DOI: 10.1186/s13643-023-02283-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/25/2023] [Indexed: 07/10/2023] Open
Abstract
BACKGROUND Randomized controlled trials (RCTs) are a critical component of evidence-based medicine and the evolution of patient care. However, the costs of conducting a RCT can be prohibitive. A promising approach toward reduction of costs and lessening of the burden of intensive and lengthy patient follow-up is the use of routinely collected healthcare data (RCHD), commonly called real-world data. We propose a scoping review to identify existing RCHD case definitions of breast cancer progression and survival and their diagnostic performance. METHODS We will search MEDLINE, EMBASE, and CINAHL to identify primary studies of women with either early-stage or metastatic breast cancer, managed with established therapies, that evaluated the diagnostic accuracy of one or more RCHD-based case definitions or algorithms of disease progression (i.e., recurrence, progression-free survival, disease-free survival, or invasive disease-free survival) or survival (i.e., breast-cancer-free survival or overall survival) compared with a reference standard measure (e.g., chart review or a clinical trial dataset). Study characteristics and descriptions of algorithms will be extracted along with measures of the diagnostic accuracy of each algorithm (e.g., sensitivity, specificity, positive predictive value, negative predictive value), which will be summarized both descriptively and in structured figures/tables. DISCUSSION Findings from this scoping review will be clinically meaningful for breast cancer researchers globally. Identification of feasible and accurate strategies to measure patient-important outcomes will potentially reduce RCT budgets as well as lessen the burden of intensive trial follow-up on patients. SYSTEMATIC REVIEW REGISTRATION Open Science Framework ( https://doi.org/10.17605/OSF.IO/6D9RS ).
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Affiliation(s)
- Hely Shah
- Department of Oncology, Ottawa Hospital, Ottawa, ON Canada
| | - Dianna Wolfe
- Ottawa Hospital Research Institute, Ottawa, ON Canada
| | - Mark Clemons
- Department of Oncology, Ottawa Hospital, Ottawa, ON Canada
- Ottawa Hospital Research Institute, Ottawa, ON Canada
| | - Michelle Liu
- Ottawa Hospital Research Institute, Ottawa, ON Canada
| | | | - Areti-Angeliki Veroniki
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON Canada
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON Canada
| | - Carole Lunny
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON Canada
| | - Greg Pond
- Department of Oncology, McMaster University, Hamilton, ON Canada
| | - Sharon McGee
- Department of Oncology, Ottawa Hospital, Ottawa, ON Canada
| | | | - Angel Arnaout
- Department of Oncology, Ottawa Hospital, Ottawa, ON Canada
| | - Brian Hutton
- Ottawa Hospital Research Institute, Ottawa, ON Canada
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5
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Gupta A, O'Callaghan CJ, Zhu L, Jonker DJ, Wong RPW, Colwell B, Moore MJ, Karapetis CS, Tebbutt NC, Shapiro JD, Tu D, Booth CM. Evaluating the Time Toxicity of Cancer Treatment in the CCTG CO.17 Trial. JCO Oncol Pract 2023:OP2200737. [PMID: 36881786 DOI: 10.1200/op.22.00737] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
PURPOSE The time spent in pursuing treatments for advanced cancer can be substantial. We have previously proposed a pragmatic and patient-centered metric of these time costs-which we term time toxicity-as any day with physical health care system contact. This includes outpatient visits (eg, bloodwork, scans, etc), emergency department visits, and overnight stays in a health care facility. Herein, we sought to assess time toxicity in a completed randomized controlled trial (RCT). METHODS We conducted a secondary analysis of the Canadian Cancer Trials Group CO.17 RCT that evaluated weekly cetuximab infusions versus supportive care alone in 572 patients with advanced colorectal cancer. Initial results reported a 6-week improvement in median overall survival (OS) with cetuximab (6.1 v 4.6 months). Subsequent analyses reported that benefit was restricted to patients with K-ras wild-type tumors. We calculated patient-level time toxicity by analyzing trial forms. We considered days without health care contact as home days. We compared medians of time measures across arms and stratified results by K-ras status. RESULTS In the overall population, median time toxic days were higher in the cetuximab arm (28 v 10, P < .001) although median home days were not statistically different between arms (140 v 121, P = .09). In patients with K-ras-mutated tumors, cetuximab was associated with almost numerically equal home days (114 days v 112 days, P = .571) and higher time toxicity (23 days v 11 days, P < .001). In patients with K-ras wild-type tumors, cetuximab was associated with more home days (186 v 132, P < .001). CONCLUSION This proof-of-concept feasibility study demonstrates that measures of time toxicity can be extracted through secondary analyses of RCTs. In CO.17, despite an overall OS benefit with cetuximab, home days were statistically similar across arms. Such data can supplement traditional survival end points in RCTs. Further work should refine and validate the measure prospectively.
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Affiliation(s)
| | | | - Liting Zhu
- Canadian Cancer Trials Group, Kingston, ON, Canada
| | | | | | | | | | | | | | | | - Dongsheng Tu
- Canadian Cancer Trials Group, Kingston, ON, Canada
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6
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The Past, Present, and Future of Economic Evaluations of Precision Medicine at the Committee for Economic Analyses of the Canadian Cancer Trials Group. Curr Oncol 2021; 28:3649-3658. [PMID: 34590616 PMCID: PMC8482104 DOI: 10.3390/curroncol28050311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/13/2021] [Accepted: 09/16/2021] [Indexed: 11/16/2022] Open
Abstract
Precision medicine in oncology poses unique challenges to the generation of clinical and economic evidence used for cost-effectiveness analyses that can inform health technology assessment. The conduct of randomized controlled trials for biomarker-specific therapies targeted towards small populations has limitations in regard to feasibility, timeliness, and cost. These limitations result in associated challenges for groups involved in the generation of economic evidence to inform treatment-related decision making, including the Committee of Economic Analysis (CEA) at the Canadian Cancer Trials Group (CCTG). We provide a high-level description and vision about the new paradigm of clinical trial design, generation of economic evidence, and novel approaches to economic evaluations necessary in the space of precision medicine in oncology in Canada. The CEA's previous approach to precision medicine, including master protocol designs and single-arm studies, is reviewed. Methods and approaches currently under consideration by the CEA and national collaborators, such as the role of real-world and clinical trial evidence in enabling life-cycle assessment of therapies, are explored. Finally, future initiatives being planned in the space of precision medicine at CCTG, such as the incorporation of correlative studies to identify and test high-performing biomarkers in trials, are discussed.
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Cheung MC, Chan KK, Golden S, Hay A, Pater J, Prica A, Chen BE, Leighl N, Mittmann N. Minimization of resource utilization data collected within cost-effectiveness analyses conducted alongside Canadian Cancer Trials Group phase III trials. Clin Trials 2021; 18:500-504. [PMID: 33866856 PMCID: PMC8290988 DOI: 10.1177/17407745211005045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Background Cost-effectiveness analyses embedded within randomized trials allow for evaluation of value alongside conventional efficacy outcomes; however, collection of resource utilization data can require considerable trial resources. Methods We re-analyzed the results from four phase III Canadian Cancer Trials Group trials that embedded cost-effectiveness analyses to determine the impact of minimizing potential cost categories on the incremental cost-effectiveness ratios. For each trial, we disaggregated total costs into component incremental cost categories and recalculated incremental cost-effectiveness ratios using (1) only the top 3 cost categories, (2) the top 5 cost categories, and (3) all cost components. Using individual trial-level data, confidence intervals for each incremental cost-effectiveness ratio simulation were generated by bootstrapping and descriptively presented with the original confidence intervals (and incremental cost-effectiveness ratios) from the publications. Results Drug acquisition costs represented the highest incremental cost category in three trials, while hospitalization costs represented the other consistent cost driver and the top incremental cost category in the fourth trial. Recalculated incremental cost-effectiveness ratios based on fewer cost components (top 3 and top 5) did not differ meaningfully from the original published results. Based on conventional willingness-to-pay thresholds (US$50,000–US$100,000 per quality-adjusted life-year), none of the re-analyses would have changed the original perception of whether the experimental therapies were considered cost-effective. Conclusions These results suggest that the collection of resource utilization data within cancer trials could be narrowed. Omission of certain cost categories that have minimal impact on incremental cost-effectiveness ratio, such as routine laboratory investigations, could reduce the costs and undue burden associated with the collection of data required for cancer trial cost-effectiveness analyses.
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Affiliation(s)
- Matthew C Cheung
- Division of Hematology, Department of Medicine, Odette Cancer Centre and University of Toronto, Toronto, ON, Canada.,Committee on Economic Analysis, Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada.,Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Kelvin Kw Chan
- Division of Hematology, Department of Medicine, Odette Cancer Centre and University of Toronto, Toronto, ON, Canada.,Committee on Economic Analysis, Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada
| | - Shane Golden
- Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada
| | - Annette Hay
- Committee on Economic Analysis, Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada
| | - Joseph Pater
- Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada
| | - Anca Prica
- Division of Hematology, Department of Medicine, Princess Margaret Hospital and University of Toronto, Toronto, ON, Canada
| | - Bingshu E Chen
- Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada
| | - Natasha Leighl
- Division of Hematology, Department of Medicine, Princess Margaret Hospital and University of Toronto, Toronto, ON, Canada
| | - Nicole Mittmann
- Committee on Economic Analysis, Canadian Cancer Trials Group, Queens University, Kingston, ON, Canada.,Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
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8
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Hay AE, Mittmann N, Crump M, Cheung MC, Sleeth J, Needham J, Broekhoven M, Djurfeldt M, Shepherd LE, Meyer RM, Chen BE, Pater JL. A Canadian Prospective Study of Linkage of Randomized Clinical Trial to Cancer and Mortality Registry Data. ACTA ACUST UNITED AC 2021; 28:1153-1160. [PMID: 33800281 PMCID: PMC8025743 DOI: 10.3390/curroncol28020111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 02/20/2021] [Accepted: 03/03/2021] [Indexed: 01/11/2023]
Abstract
In a prospective study, we sought to determine acceptability of linkage of administrative and clinical trial data among Canadian patients and Research Ethics Boards (REBs). The goal is to develop a more harmonized approach to data, with potential to improve clinical trial conduct through enhanced data quality collected at reduced cost and inconvenience for patients. On completion of the original LY.12 randomized clinical trial in lymphoma (NCT00078949), participants were invited to enrol in the Long-term Innovative Follow-up Extension (LIFE) component. Those consenting to do so provided comprehensive identifying information to facilitate linkage with their administrative data. We prospectively designed a global assessment of this innovative approach to clinical trial follow-up including rates of REB approval and patient consent. The pre-specified benchmark for patient acceptability was 80%. Of 16 REBs who reviewed the research protocol, 14 (89%) provided approval; two in Quebec declined due to small patient numbers. Of 140 patients invited to participate, 115 (82%, 95% CI 76 to 88%) from across 9 Canadian provinces provided consent and their full name, date of birth, health insurance number and postal code to facilitate linkage with their administrative data for long-term follow-up. Linkage of clinical trial and administrative data is feasible and acceptable. Further collaborative work including many stakeholders is required to develop an optimized secure approach to research. A more coordinated national approach to health data could facilitate more rapid testing and identification of new effective treatments across multiple jurisdictions and diseases from diabetes to COVID-19.
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Affiliation(s)
- Annette E Hay
- Department of Medicine, Queen’s University, Kingston, ON K7L 2V6, Canada
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
- Correspondence:
| | - Nicole Mittmann
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON M4N 3M5, Canada; (N.M.); (M.CC.)
| | - Michael Crump
- Princess Margaret Cancer Centre, University of Toronto, Toronto, ON M5G 2C1, Canada;
| | - Matthew C Cheung
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON M4N 3M5, Canada; (N.M.); (M.CC.)
| | - Jessica Sleeth
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Judy Needham
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Mike Broekhoven
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Marina Djurfeldt
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Lois E Shepherd
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Ralph M Meyer
- Juravinski Cancer Centre/Hamilton Health Sciences, McMaster University, Hamilton, ON L8V 5C2, Canada;
| | - Bingshu E Chen
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
| | - Joseph L Pater
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON K7L 3N6, Canada; (J.S.); (J.N.); (M.B.); (M.D.); (L.ES.); (B.EC.); (J.LP.)
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9
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Malone ER, Saleh RR, Yu C, Ahmed L, Pugh T, Torchia J, Bartlett J, Virtanen C, Hotte SJ, Hilton J, Welch S, Robinson A, McCready E, Lo B, Sadikovic B, Feilotter H, Hanna TP, Kamel-Reid S, Stockley TL, Siu LL, Bedard PL. OCTANE (Ontario-wide Cancer Targeted Nucleic Acid Evaluation): a platform for intraprovincial, national, and international clinical data-sharing. ACTA ACUST UNITED AC 2019; 26:e618-e623. [PMID: 31708655 DOI: 10.3747/co.26.5235] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Cancer is a genetic disease resulting from germline or somatic genetic aberrations. Rapid progress in the field of genomics in recent years is allowing for increased characterization and understanding of the various forms of the disease. The Ontario-wide Cancer Targeted Nucleic Acid Evaluation (octane) clinical trial, open at cancer centres across Ontario, aims to increase access to genomic sequencing of tumours and to facilitate the collection of clinical data related to enrolled patients and their clinical outcomes. The study is designed to assess the clinical utility of next-generation sequencing (ngs) in cancer patient care, including enhancement of treatment options available to patients. A core aim of the study is to encourage collaboration between cancer hospitals within Ontario while also increasing international collaboration in terms of sharing the newly generated data. The single-payer provincial health care system in Ontario provides a unique opportunity to develop a province-wide registry of ngs testing and a repository of genomically characterized, clinically annotated samples. It also provides an important opportunity to use province-wide real-world data to evaluate outcomes and the cost of ngs for patients with advanced cancer. The octane study is attempting to translate knowledge to help deliver precision oncology in a Canadian environment. In this article, we discuss the background to the study and its implementation, current status, and future directions.
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Affiliation(s)
- E R Malone
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - R R Saleh
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - C Yu
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - L Ahmed
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - T Pugh
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - J Torchia
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - J Bartlett
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - C Virtanen
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - S J Hotte
- Hamilton, ON-Laboratory Genetic Services Division, Hamilton Regional Laboratory Medicine Program (McCready); McMaster University (Hotte); Juravinski Cancer Centre (Hotte)
| | - J Hilton
- Ottawa, ON-The Ottawa Hospital Research Institute (Lo); University of Ottawa (Hilton); The Ottawa Hospital Cancer Program (Hilton)
| | - S Welch
- London, ON-Department of Pathology and Laboratory Medicine, Western University, and Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre (Sadikovic); University of Western Ontario (Welch); London Health Sciences Health Centre (Welch)
| | - A Robinson
- Kingston, ON-Department of Pathology and Molecular Medicine, Queen's University (Feilotter); Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University (Hanna, Robinson); Kingston General Hospital (Hanna, Robinson)
| | - E McCready
- Hamilton, ON-Laboratory Genetic Services Division, Hamilton Regional Laboratory Medicine Program (McCready); McMaster University (Hotte); Juravinski Cancer Centre (Hotte)
| | - B Lo
- Ottawa, ON-The Ottawa Hospital Research Institute (Lo); University of Ottawa (Hilton); The Ottawa Hospital Cancer Program (Hilton)
| | - B Sadikovic
- London, ON-Department of Pathology and Laboratory Medicine, Western University, and Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre (Sadikovic); University of Western Ontario (Welch); London Health Sciences Health Centre (Welch)
| | - H Feilotter
- Kingston, ON-Department of Pathology and Molecular Medicine, Queen's University (Feilotter); Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University (Hanna, Robinson); Kingston General Hospital (Hanna, Robinson)
| | - T P Hanna
- Kingston, ON-Department of Pathology and Molecular Medicine, Queen's University (Feilotter); Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University (Hanna, Robinson); Kingston General Hospital (Hanna, Robinson)
| | - S Kamel-Reid
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - T L Stockley
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - L L Siu
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
| | - P L Bedard
- Toronto, ON-Laboratory Medicine Program, University Health Network (Kamel-Reid, Stockley); Department of Laboratory Medicine and Pathobiology, University of Toronto (Kamel-Reid, Stockley); Cancer Genomics Program, Princess Margaret Cancer Centre (Ahmed, Bedard, Kamel-Reid, Pugh, Siu, Stockley, Yu); Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre (Bedard, Malone, Saleh, Siu); Department of Medicine, University of Toronto (Bedard); Department of Medical Biophysics, University of Toronto (Kamel-Reid, Pugh, Siu); Princess Margaret Research Institute, Princess Margaret Cancer Centre (Pugh); Bioinformatics and High Performance Computing Core, University Health Network (Virtanen); Ontario Institute for Cancer Research (Torchia, Bartlett)
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