Peer review of clinical and translational research manuscripts: Perspectives from statistical collaborators

Sep 13, 2026

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Research articles in the clinical and translational science literature commonly rely on quantitative data to evaluate interventions, investigate disease etiology, and develop diagnostic testing or risk prediction methods. The peer review process must judge the underlying methodology, including the use of quantitative statistical methods. This manuscript offers guidance for reviewers assessing quantitative approaches in manuscript submissions, covering study design, hypothesis evaluation, sampling and data acquisition, interventions, measurement, statistical analysis, result presentation, interpretation, and communications about fixable versus irreparable errors, emphasizing transparency and editor-oriented acceptance/revision criteria.

LanguageEnglish

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Pages9

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Abstract

Introduction

Scope of statistical methods in peer review

Need for structured guidance for reviewers

Corresponding author and publication details

Journal of Clinical and Translational Science [www.cambridge.org/cts](www.cambridge.org/cts) Translational Research, Design and Analysis Review Article Cite this article: Schulte PJ, Goldberg JD, Oster RA, Ambrosius WT, Bonner LB, Cabral H, Carter RE, Chen Y, Desai M, Li D, Lindsell CJ, Pomann G-M, Slade E, Tosteson TD, Yu F, and Spratt H. Peer review of clinical and translational research manuscripts: Perspectives from statistical collaborators. Journal of Clinical and Translational Science 8: e20, 1–9 . doi: 10. 1017/cts.2023.707 Received: 23 August 2023 Revised: 29 November 2023 Accepted: 19 December 2023 Keywords: Biostatistics; peer review; reviewer guidance; clinical and translational science; study design Corresponding author: H. Spratt, PhD; Email: [hespratt@utmb.edu](hespratt@utmb.edu) © The Author(s), 2024 . Published by Cambridge University Press on behalf of Association for Clinical and Translational Science. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ([http://creativecommons.org/licenses/](http://creativecommons.org/licenses/)[ ](http://creativecommons.org/licenses/)[by/4.0/](by/4.0/)), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. Peer review of clinical and translational research manuscripts: Perspectives from statistical collaborators Phillip J. Schulte1 , Judith D. Goldberg2, Robert A. Oster3 , Walter T. Ambrosius4, Lauren Balmert Bonner5, Howard Cabral6, Rickey E. Carter7, Ye Chen8, Manisha Desai9 , Dongmei Li10, Christopher J. Lindsell11 , Gina-Maria Pomann11, Emily Slade12 , Tor D. Tosteson13 , Fang Yu14 and Heidi Spratt15 1Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; 2Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA; 3Department of Medicine, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA; 4Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA; 5Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; 6Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; 7Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA; 8Biostatistics, Epidemiology and Research Design (BERD), Tufts Clinical and Translational Science Institute (CTSI), Boston, MA, USA; 9Quantitative Sciences Unit, Departments of Medicine, Biomedical Data Science, and Epidemiology and Population Health, Stanford University, Stanford, CA, USA; 10Department of Clinical and Translational Research, Obstetrics and Gynecology and Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA; 11Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA; 12Department of Biostatistics, University of Kentucky, Lexington, KY, USA; 13Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA; 14Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA and 15Department of Biostatistics and Data Science, School of Public and Population Health, University of Texas Medical Branch, Galveston, TX, USA Abstract Research articles in the clinical and translational science literature commonly use quantitative data to inform evaluation of interventions, learn about the etiology of disease, or develop methods for diagnostic testing or risk prediction of future events. The peer review process must evaluate the methodology used therein, including use of quantitative statistical methods. In this manuscript, we provide guidance for peer reviewers tasked with assessing quantitative methodology, intended to complement guidelines and recommendations t

FAQs

What does the manuscript focus on regarding peer review?

It focuses on how peer review should assess quantitative statistical methodology used in clinical and translational research manuscripts.

Which manuscript components does the guidance cover?

It covers study design and hypothesis evaluation, sampling and data acquisition, interventions, measurement, statistical analysis methods, presentation of results, and interpretation of results.

How should reviewers communicate issues during peer review?

The guidance distinguishes between fixable errors or omissions and uncorrectable or irreparable errors, and it stresses transparent communication with journal editors regarding acceptance or revision.

Sep 13, 2026

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