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Wallach JD, Yoon S, Doernberg H, Glick LR, Ciani O, Taylor RS, Mooghali M, Ramachandran R, Ross JS. Associations Between Surrogate Markers and Clinical Outcomes for Nononcologic Chronic Disease Treatments. JAMA 2024; 331:1646-1654. [PMID: 38648042 PMCID: PMC11036312 DOI: 10.1001/jama.2024.4175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/04/2024] [Indexed: 04/25/2024]
Abstract
Importance Surrogate markers are increasingly used as primary end points in clinical trials supporting drug approvals. Objective To systematically summarize the evidence from meta-analyses, systematic reviews and meta-analyses, and pooled analyses (hereafter, meta-analyses) of clinical trials examining the strength of association between treatment effects measured using surrogate markers and clinical outcomes in nononcologic chronic diseases. Data sources The Food and Drug Administration (FDA) Adult Surrogate Endpoint Table and MEDLINE from inception to March 19, 2023. Study Selection Three reviewers selected meta-analyses of clinical trials; meta-analyses of observational studies were excluded. Data Extraction and Synthesis Two reviewers extracted correlation coefficients, coefficients of determination, slopes, effect estimates, or results from meta-regression analyses between surrogate markers and clinical outcomes. Main Outcomes and Measures Correlation coefficient or coefficient of determination, when reported, was classified as high strength (r ≥ 0.85 or R2 ≥ 0.72); primary findings were otherwise summarized. Results Thirty-seven surrogate markers listed in FDA's table and used as primary end points in clinical trials across 32 unique nononcologic chronic diseases were included. For 22 (59%) surrogate markers (21 chronic diseases), no eligible meta-analysis was identified. For 15 (41%) surrogate markers (14 chronic diseases), at least 1 meta-analysis was identified, 54 in total (median per surrogate marker, 2.5; IQR, 1.3-6.0); among these, median number of trials and patients meta-analyzed was 18.5 (IQR, 12.0-43.0) and 90 056 (IQR, 20 109-170 014), respectively. The 54 meta-analyses reported 109 unique surrogate marker-clinical outcome pairs: 59 (54%) reported at least 1 r or R2, 10 (17%) of which reported at least 1 classified as high strength, whereas 50 (46%) reported slopes, effect estimates, or results of meta-regression analyses only, 26 (52%) of which reported at least 1 statistically significant result. Conclusions and Relevance Most surrogate markers used as primary end points in clinical trials to support FDA approval of drugs treating nononcologic chronic diseases lacked high-strength evidence of associations with clinical outcomes from published meta-analyses.
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Affiliation(s)
- Joshua D. Wallach
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
| | - Samuel Yoon
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
- Department of Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Harry Doernberg
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
- Department of Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Laura R. Glick
- Department of Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Oriana Ciani
- Center for Research on Health and Social Care Management, SDA Bocconi School of Management, Milan, Italy
| | - Rod S. Taylor
- MRC/CSO Social and Public Health Sciences Unit, School of Health & Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
- Robertson Centre for Biostatistics, School of Health & Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Maryam Mooghali
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
- Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Reshma Ramachandran
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
- Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale National Clinicians Scholars Program, Yale School of Medicine, New Haven, Connecticut
| | - Joseph S. Ross
- Collaboration for Regulatory Rigor, Integrity, and Transparency, Yale School of Medicine, New Haven, Connecticut
- Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale National Clinicians Scholars Program, Yale School of Medicine, New Haven, Connecticut
- Department of Health Policy and Management, Yale School of Public Health, Yale–New Haven Health System, New Haven, Connecticut
- Center for Outcomes Research and Evaluation, Yale–New Haven Health System, New Haven, Connecticut
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Manyara AM, Davies P, Stewart D, Weir CJ, Young A, Butcher NJ, Bujkiewicz S, Chan AW, Collins GS, Dawoud D, Offringa M, Ouwens M, Ross JS, Taylor RS, Ciani O. Protocol for the development of SPIRIT and CONSORT extensions for randomised controlled trials with surrogate primary endpoints: SPIRIT-SURROGATE and CONSORT-SURROGATE. BMJ Open 2022; 12:e064304. [PMID: 36220321 PMCID: PMC9557267 DOI: 10.1136/bmjopen-2022-064304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 09/27/2022] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Randomised controlled trials (RCTs) may use surrogate endpoints as substitutes and predictors of patient-relevant/participant-relevant final outcomes (eg, survival, health-related quality of life). Translation of effects measured on a surrogate endpoint into health benefits for patients/participants is dependent on the validity of the surrogate; hence, more accurate and transparent reporting on surrogate endpoints is needed to limit misleading interpretation of trial findings. However, there is currently no explicit guidance for the reporting of such trials. Therefore, we aim to develop extensions to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines to improve the design and completeness of reporting of RCTs and their protocols using a surrogate endpoint as a primary outcome. METHODS AND ANALYSIS The project will have four phases: phase 1 (literature reviews) to identify candidate reporting items to be rated in a Delphi study; phase 2 (Delphi study) to rate the importance of items identified in phase 1 and receive suggestions for additional items; phase 3 (consensus meeting) to agree on final set of items for inclusion in the extensions and phase 4 (knowledge translation) to engage stakeholders and disseminate the project outputs through various strategies including peer-reviewed publications. Patient and public involvement will be embedded into all project phases. ETHICS AND DISSEMINATION The study has received ethical approval from the University of Glasgow College of Medical, Veterinary and Life Sciences Ethics Committee (project no: 200210051). The findings will be published in open-access peer-reviewed publications and presented in conferences, meetings and relevant forums.
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Affiliation(s)
- Anthony Muchai Manyara
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, Glasgow, UK, University of Glasgow, Glasgow, UK
| | - Philippa Davies
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Amber Young
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nancy J Butcher
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Child Health Evaluation Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Sylwia Bujkiewicz
- Biostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - An-Wen Chan
- Women's College Institute Research Institute, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Gary S Collins
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, Oxford University, Oxford, UK
| | - Dalia Dawoud
- National Institute for Health and Care Excellence, London, UK
| | - Martin Offringa
- Child Health Evaluation Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Joseph S Ross
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, USA
- Section of General Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Rod S Taylor
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, Glasgow, UK, University of Glasgow, Glasgow, UK
- Robertson Centre for Biostatistics, School of Health and Well Being, University of Glasgow, Glasgow, UK
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