Evidence map›Paper›PMID 41664130›Full record

ReviewDiagnostic and prognostic research2026

Protocol for development of a reporting guideline (TRIPOD-Code) for code repositories associated with diagnostic and prognostic prediction model studies.

Tom Pollard, Thomas Sounack, Catherine A Gao, Leo Anthony Celi, Charlotta Lindvall, Hyeonhoon Lee, Hyung-Chul Lee, Karel G M Moons, Gary S Collins

Abstract readReview
In one paragraph

Review in Diagnostic and prognostic research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Tom Pollard *MIT Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA. tpollard@mit.edu.
Thomas Sounack *Dana-Farber Cancer Institute, Boston, MA, USA.
Catherine A GaoNorthwestern Feinberg School of Medicine, Chicago, Illinois, USA.
Leo Anthony CeliMIT Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
Charlotta LindvallDana-Farber Cancer Institute, Boston, MA, USA.
Hyeonhoon LeeHealthcare AI Research Institute, Seoul National University Hospital, Seoul, Korea.
Hyung-Chul LeeHealthcare AI Research Institute, Seoul National University Hospital, Seoul, Korea.
Karel G M MoonsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Gary S CollinsDepartment of Applied Health Sciences, School of Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.

Funding

Research Resource for Complex Physiologic SignalsR01EB030362 · NIBIB · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GOLDBERGER, ARY LOUIS · 2020 to 2025
$5.8M
NIBIB NIH HHS R01 EB030362
6 · The paper itself

Abstract

introductionThe Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement was published to improve the reporting and critical appraisal of prediction model studies for diagnosis and prognosis. This paper describes the processes and methods that will be used to develop an extension to the TRIPOD statement (TRIPOD-Code) for the management of code associated with prediction model studies. TRIPOD-Code focuses specifically on the transparent reporting of analytical code used in prediction model studies, including code for data preprocessing, model development, and model evaluation. METHODS AND ANALYSIS: TRIPOD-Code will be developed following published guidance from the EQUATOR Network and will comprise five stages. Stage 1 will involve a methodological review of how code availability is reported in published prediction model studies. In Stage 2, we will consult a diverse group of key stakeholders using a Delphi process to identify items to be considered for inclusion in TRIPOD-Code. Stage 3 will consist of virtual consensus meetings to consolidate and prioritise the key items. Stage 4 will involve developing the TRIPOD-Code checklist. In the final stage, Stage 5, we will disseminate TRIPOD-Code via journals, conferences, blogs, websites (including TRIPOD and the EQUATOR Network) and social media. TRIPOD-Code will provide researchers working on prediction model studies with a reporting checklist and accompanying guidance to promote code completeness and availability. ETHICS AND DISSEMINATION: This study has been determined to be exempt from ongoing IRB oversight by the Massachusetts Institute of Technology Committee on the Use of Humans as Experimental Subjects (COUHES) under Exempt ID: E-6675. Findings from this study will be disseminated through peer-reviewed publications.

Identifiers

PMID41664130
PMCPMC12888484

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.