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. 2024 May 21;331(19):1646-1654.
doi: 10.1001/jama.2024.4175.

Associations Between Surrogate Markers and Clinical Outcomes for Nononcologic Chronic Disease Treatments

Joshua D Wallach  1   2 , Samuel Yoon  2   3 , Harry Doernberg  2   3 , Laura R Glick  3 , Oriana Ciani  4 , Rod S Taylor  5   6 , Maryam Mooghali  2   7 , Reshma Ramachandran  2   7   8 , Joseph S Ross  2   7   8   9   10
Affiliations

Associations Between Surrogate Markers and Clinical Outcomes for Nononcologic Chronic Disease Treatments

Joshua D Wallach et al. JAMA. .

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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Conflict of interest statement

Conflict of Interest Disclosures: Dr Wallach reported receiving grants from the Food and Drug Administration (FDA) (through the Yale University–Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America. Dr Ross reported receiving grants from FDA, Johnson & Johnson, Medical Device Innovation Consortium, the Agency for Healthcare Research and Quality, and National Institutes of Health/National Heart, Lung, and Blood Institute outside the submitted work; and serving as an expert witness at the request of relator's attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen that was settled September 2022. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Surrogate Marker Selection Flowchart
FDA indicates Food and Drug Administration. aThe FDA has a separate Pediatric Surrogate Endpoint Table.
Figure 2.
Figure 2.. Study Flowchart
aeFigures 1 through 31 in Supplement 1 provide flowcharts for the individual chronic diseases. bFour meta-analyses were applicable to 2 disease indications.
Figure 3.
Figure 3.. Strength of the Associations Between 109 Surrogate Marker–Clinical Outcome Pairs
Strong evidence: correlation coefficients or coefficients of determination values reported for all associations examined, and all associations classified as statistically significant and high strength according to criteria proposed by the Institute for Quality and Efficiency in Health Care (r ≥ 0.85 or R2 ≥ 0.72).14 Moderate evidence: r or R2 values reported for all associations examined, and 1 or more (but not all) classified as statistically significant and high strength. Modest evidence: r or R2 values reported for some associations examined, and 1 or more (but not all) classified as statistically significant and high strength. Any other r, R2, slopes, effect estimates, or results from meta-regression analyses classified as statistically significant. Weak evidence: no r or R2 values classified as both statistically significant and high strength, but all r, R2, slopes, effect estimates, or results from meta-regression analyses classified as statistically significant. Limited evidence: no r or R2 values classified as both statistically significant and high strength; some r, R2, slopes, effect estimates, or results from meta-regression analyses classified as statistically significant and some not. No evidence: no r or R2 values classified as statistically significant and high strength, and all r, R2, slopes, effect estimates, or results from meta-regression analyses classified as nonstatistically significant.
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Comment in

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