Measuring Representativeness in Clinical Trials

A Allen Sanyi (Department of Medicine (A.S.), Emory University School of Medicine, Atlanta, GA.) S Samuel Byiringiro (Johns Hopkins School of Nursing, Baltimore, MD (S.B.).) S Sanaz Dabiri (Leonard D. Schaeffer Center for Health Policy and Economics (S.D., M.J.), University of Southern California, Los Angeles.) M Mireille Jacobson A Amanda Boyd (Elson S. Floyd College of Medicine, Washington State University, Spokane (A.B.).) M Modele O. Ogunniyi A Alanna A. Morris (Division of Cardiology (M.O.O., A.A.M., N.W.D.), Emory University School of Medicine, Atlanta, GA.) R Rachel Kohn N Neal W. Dickert M Meghan B. Lane-Fall E Eldrin F. Lewis (Department of Medicine, Stanford University School of Medicine, CA (E.F.L.).) S Scott D. Halpern (Behavioral Economics to Transform Trial Enrollment Representativeness (BETTER) Center (A.S., M.O.O., A.A.M., R.K., N.W.D., M.B.L.-F., S.D.H., A.C.F.), University of Pennsylvania, Philadelphia.) A Alexander C. Fanaroff (Behavioral Economics to Transform Trial Enrollment Representativeness (BETTER) Center (A.S., M.O.O., A.A.M., R.K., N.W.D., M.B.L.-F., S.D.H., A.C.F.), University of Pennsylvania, Philadelphia.)

Abstract

Representativeness in randomized clinical trials remains a critical concern, affecting the external validity of trial results, equitable access to the risks and benefits of research participation, and public trust in clinical research. Although representative participation by members of groups traditionally underrepresented in clinical trials is just a surrogate for true diversity, equity, inclusion, and belonging in clinical trials, it can be quantified, allowing stakeholders to add empirical rigor to diversity, equity, inclusion, and belonging efforts. Multiple ways to measure representativeness have been proposed, including the participation-to-prevalence ratio, raw participation proportions or numbers for relevant subgroups, and enrollment fraction for relevant subgroups. These methods have strengths and weaknesses and may be appropriate to report in certain circumstances, depending on why stakeholders seek to assess representativeness. Stakeholders—including regulatory agencies, journal editors, clinical trial investigators, and trial sponsors—may use quantitative measures of representativeness to establish trial enrollment standards, monitor equitable participation in ongoing trials, and condition funding or drug or device approval on achieving specific representativeness targets. However, using quantitative measures of representativeness in this way could have unintended consequences, including researchers “gaming” recruitment strategies to meet target numbers, overlooking nuanced variations within communities, and potentially incentivizing problematic and exploitative recruitment strategies. Although no single method of measuring representativeness offers a comprehensive solution for increasing diversity, equity, inclusion, and belonging in all randomized clinical trials, a carefully designed, multifaceted approach to measuring representativeness may provide stakeholders with useful perspectives for measuring progress in increasing the diversity of clinical trial participation. For stakeholders seeking a single number to assess the representativeness of a trial enrolling patients with a disease state with well-delineated demographics, the participation-to-prevalence ratio is ideal; however, for a more nuanced view of representativeness, the combination of enrollment fraction in subgroups of relevance plus a full report of the demographics of patients approached for enrollment may be more appropriate.

Article Details

Journal Circulation
Volume / Issue Vol. 151, Issue 5
Published February 04, 2025
Pages 318-330
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (13)

A

Allen Sanyi

Department of Medicine (A.S.), Emory University School of Medicine, Atlanta, GA.

S

Samuel Byiringiro

Johns Hopkins School of Nursing, Baltimore, MD (S.B.).

S

Sanaz Dabiri

Leonard D. Schaeffer Center for Health Policy and Economics (S.D., M.J.), University of Southern California, Los Angeles.

M

Mireille Jacobson

A

Amanda Boyd

Elson S. Floyd College of Medicine, Washington State University, Spokane (A.B.).

M

Modele O. Ogunniyi

A

Alanna A. Morris

Division of Cardiology (M.O.O., A.A.M., N.W.D.), Emory University School of Medicine, Atlanta, GA.

R

Rachel Kohn

N

Neal W. Dickert

M

Meghan B. Lane-Fall

E

Eldrin F. Lewis

Department of Medicine, Stanford University School of Medicine, CA (E.F.L.).

S

Scott D. Halpern

Behavioral Economics to Transform Trial Enrollment Representativeness (BETTER) Center (A.S., M.O.O., A.A.M., R.K., N.W.D., M.B.L.-F., S.D.H., A.C.F.), University of Pennsylvania, Philadelphia.

A

Alexander C. Fanaroff

Behavioral Economics to Transform Trial Enrollment Representativeness (BETTER) Center (A.S., M.O.O., A.A.M., R.K., N.W.D., M.B.L.-F., S.D.H., A.C.F.), University of Pennsylvania, Philadelphia.