Title | Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine. |
Publication Type | Journal Article |
Year of Publication | 2022 |
Authors | Xu J, Guo Y, Wang F, Xu H, Lucero R, Bian J, Prosperi M |
Journal | BMJ Open |
Volume | 12 |
Issue | 6 |
Pagination | e059715 |
Date Published | 2022 Jun 20 |
ISSN | 2044-6055 |
Keywords | Causality, Checklist, Humans, Research Design, Systematic Reviews as Topic |
Abstract | INTRODUCTION: While there are guidelines for reporting on observational studies (eg, Strengthening the Reporting of Observational Studies in Epidemiology, Reporting of Studies Conducted Using Observational Routinely Collected Health Data Statement), estimation of causal effects from both observational data and randomised experiments (eg, A Guideline for Reporting Mediation Analyses of Randomised Trials and Observational Studies, Consolidated Standards of Reporting Trials, PATH) and on prediction modelling (eg, Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis), none is purposely made for deriving and validating models from observational data to predict counterfactuals for individuals on one or more possible interventions, on the basis of given (or inferred) causal structures. This paper describes methods and processes that will be used to develop a Reporting Guideline for Causal and Counterfactual Prediction Models (PRECOG). METHODS AND ANALYSIS: PRECOG will be developed following published guidance from the Enhancing the Quality and Transparency of Health Research (EQUATOR) network and will comprise five stages. Stage 1 will be meetings of a working group every other week with rotating external advisors (active until stage 5). Stage 2 will comprise a systematic review of literature on counterfactual prediction modelling for biomedical sciences (registered in Prospective Register of Systematic Reviews). In stage 3, a computer-based, real-time Delphi survey will be performed to consolidate the PRECOG checklist, involving experts in causal inference, epidemiology, statistics, machine learning, informatics and protocols/standards. Stage 4 will involve the write-up of the PRECOG guideline based on the results from the prior stages. Stage 5 will seek the peer-reviewed publication of the guideline, the scoping/systematic review and dissemination. ETHICS AND DISSEMINATION: The study will follow the principles of the Declaration of Helsinki. The study has been registered in EQUATOR and approved by the University of Florida's Institutional Review Board (#202200495). Informed consent will be obtained from the working groups and the Delphi survey participants. The dissemination of PRECOG and its products will be done through journal publications, conferences, websites and social media. |
DOI | 10.1136/bmjopen-2021-059715 |
Alternate Journal | BMJ Open |
PubMed ID | 35725267 |
PubMed Central ID | PMC9214357 |
Grant List | R01 AI141810 / AI / NIAID NIH HHS / United States U18 DP006512 / DP / NCCDPHP CDC HHS / United States R01 CA246418 / CA / NCI NIH HHS / United States R01 AI145552 / AI / NIAID NIH HHS / United States U18DP006512 / ACL / ACL HHS / United States R21 AG068717 / AG / NIA NIH HHS / United States R21 CA253394 / CA / NCI NIH HHS / United States R21 CA245858 / CA / NCI NIH HHS / United States R33 AG062884 / AG / NIA NIH HHS / United States |
Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine.
Submitted by chz4003 on April 11, 2023 - 5:36pm
Division:
Institute of Artificial Intelligence for Digital Health
Category:
Faculty Publication