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Rodrigues C, Odutayo A, Patel S, Agarwal A, da Costa BR, Lin E, Yeh RW, Jüni P, Goodman SG, Farkouh ME, Udell JA. Accuracy of Cardiovascular Trial Outcome Ascertainment and Treatment Effect Estimates from Routine Health Data: A Systematic Review and Meta-Analysis. CIRCULATION. CARDIOVASCULAR QUALITY AND OUTCOMES 2021; 14:e007903. [PMID: 33993728 DOI: 10.1161/circoutcomes.120.007903] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Registry-based randomized controlled trials allow for outcome ascertainment using routine health data (RHD). While this method provides a potential solution to the rising cost and complexity of clinical trials, comparative analyses of outcome ascertainment by clinical end point committee (CEC) adjudication compared with RHD sources are sparse. Among cardiovascular trials, we set out to systematically compare the incidence of cardiovascular events and estimated randomized treatment effects ascertained from RHD versus traditional clinical evaluation and adjudication. METHODS We searched MEDLINE (1976 to August 2020) for studies where outcome ascertainment was performed by both RHD and CEC adjudication to compare the incidence of cardiovascular events and treatment effects. We derived ratios of hazard ratios to compare treatment effects from RHD and CEC adjudication. We pooled ratios of hazard ratios using an inverse variance random-effects meta-analysis. RESULTS Nine studies (1988-2020; 32 156 patients) involving 10 randomized control trials compared outcome ascertainment with RHD and CEC in patients with or at risk of cardiovascular disease. There was a high degree of agreement and interrater reliability between CEC and RHD outcome determination for all-cause mortality (agreement percentage: 98.4%-100% and κ: 0.95-1.0) and cardiovascular mortality (agreement percentage: 97.8%-99.9% and κ: 0.66-0.99). For myocardial infarction, the κ values ranged from 0.67-0.98, and for stroke the values ranged from 0.52-0.89. In contrast, the κ value for peripheral artery disease was low (κ: 0.27). There was little difference in the randomized treatment effect derived from CEC and RHD ascertainment of events based on the ratios of hazard ratio, with pooled ratios of hazard ratios ranging from 0.93 (95% CI, 0.63-1.39) for cardiovascular mortality to 1.27 (95% CI, 0.67-2.41) for stroke. CONCLUSIONS Clinical outcome ascertainment using retrospectively acquired RHD displayed high levels of agreement with CEC adjudication for identifying all-cause mortality and cardiovascular outcomes. Importantly, cardiovascular treatment effects in randomized control trials determined from RHD and CEC resulted in similar point estimates. Overall, our review supports the use of RHD as a potential alternative source for clinical outcome ascertainment in cardiovascular trials. Validation studies with prospectively planned linkage are warranted.
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Affiliation(s)
- Craig Rodrigues
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,School of Medicine, Queen's University, Kingston, Canada (C.R.)
| | - Ayodele Odutayo
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Sagar Patel
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Arnav Agarwal
- Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Bruno Roza da Costa
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Primary Health Care (BIHAM), University of Bern, Switzerland (B.R.d.C.)
| | - Ethan Lin
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Faculty of Medicine, University of Ottawa, Canada (E.L.)
| | - Robert W Yeh
- Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA (R.W.Y.)
| | - Peter Jüni
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada
| | - Shaun G Goodman
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Michael E Farkouh
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Peter Munk Cardiac Centre, University Health Network, Toronto, Canada (M.E.F., J.A.U.)
| | - Jacob A Udell
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada.,Peter Munk Cardiac Centre, University Health Network, Toronto, Canada (M.E.F., J.A.U.).,ICES, Toronto, Canada (J.A.U.).,Cardiovascular Division, Department of Medicine, Women's College Hospital, Toronto, Canada (J.A.U.)
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Brag J, Auffret M, Ramos C, Liu Y, Baudot P. iBiopsy® for Precision Medicine. EUROPEAN MEDICAL JOURNAL 2018. [DOI: 10.33590/emj/10310309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
A high-throughput artificial intelligence-powered image-based phenotyping platform, iBiopsy® (Median Technologies, Valbonne, France), which aims to improve precision medicine, is discussed in the presented review. The article introduces novel concepts, including high-throughput, fully automated imaging biomarker extraction; unsupervised predictive learning; large-scale content- based image-based similarity search; the use of large-scale clinical data registries; and cloud-based big data analytics to the problems of disease subtyping and treatment planning. Unlike electronic health record-based approaches, which lack the detailed radiological, pathological, genomic, and molecular data necessary for accurate prediction, iBiopsy generates unique signatures as fingerprints of disease and tumour subtypes from target images. These signatures are then merged with any additional omics data and matched against a large-scale reference registry of deeply phenotyped patients. Initial applications targeted include hepatocellular carcinoma and other chronic liver diseases, such as nonalcoholic steatohepatitis. This new disruptive technology is expected to lead to the identification of appropriate therapies targeting specific molecular pathways involved in the detected phenotypes to bring personalised treatment to patients, taking into account individual biological variability, which is the principal aim of precision medicine.
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Affiliation(s)
- Johan Brag
- iBiopsy® Clinical Development, Median Technologies, Valbonne, France
| | - Michaël Auffret
- iBiopsy® Clinical Development, Median Technologies, Valbonne, France
| | - Corinne Ramos
- iBiopsy® Clinical Development, Median Technologies, Valbonne, France
| | - Yan Liu
- iBiopsy® Clinical Development, Median Technologies, Valbonne, France
| | - Pierre Baudot
- iBiopsy® Science & Image Processing, Median Technologies, Valbonne, France
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