@article{aac564d9586a43c4b8494061cfeb879e,
title = "The Predictive Approaches to Treatment effect Heterogeneity (PATH) statement: Explanation and elaboration",
abstract = "The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneity of treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risk with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made on the basis of only an overall average treatment effect. The authors distinguished 2 categories of predictive HTE approaches (a {"}riskmodeling{"} and an {"}effect-modeling{"} approach) and developed 4 sets of guidance statements: Criteria to determine when riskmodeling approaches are likely to identify clinically meaningful HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. They discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation and discusses related analytic considerations, caveats, and reservations.",
author = "Kent, {David M.} and {Van Klaveren}, David and Paulus, {Jessica K.} and Ralph D'Agostino and Steve Goodman and Rodney Hayward and Ioannidis, {John P.A.} and Bray Patrick-Lake and Sally Morton and Michael Pencina and Gowri Raman and Ross, {Joseph S.} and Selker, {Harry P.} and Ravi Varadhan and Andrew Vickers and Wong, {John B.} and Steyerberg, {Ewout W.}",
note = "Funding Information: Financial Support: Development of the PATH Statement was supported through contract SA.Tufts.PARC.OSCO.2018.01.25 from the PCORI Predictive Analytics Resource Center. This work was also informed by a 2018 conference (“Evidence and the Individual Patient: Understanding Heterogeneous Treatment Effects for Patient-Centered Care”) convened by the National Academy of Medicine and funded through a PCORI Eugene Washington Engagement Award (1900-TMC). Funding Information: Disclosures: Dr. Kent reports grants from PCORI during the conduct of the study. Dr. Goodman reports personal fees from PCORI outside the submitted work. Dr. Pencina reports grants from PCORI (Tufts Subaward) during the conduct of the study; grants from Sanofi/Regeneron, Amgen, and Bristol-Myers Squibb outside the submitted work; and personal fees from Boehringer Ingelheim and Merck outside the submitted work. Dr. Ross reports personal fees from PCORI during the conduct of the study and grants from the U.S. Food and Drug Administration, Medtronic, Johnson & Johnson, the Centers for Medicare & Medicaid Services, Blue Cross Blue Shield Association, the Agency for Healthcare Research and Quality, the National Institutes of Health (National Heart, Lung, and Blood Institute), and Laura and John Arnold Foundation outside the submitted work. Dr. Varadhan reports personal fees from Tufts University during the conduct of the study. Dr. Vick-ers reports grants from the National Institutes of Health during the conduct of the study. Dr. Wong reports grants from PCORI during the conduct of the study. Dr. Steyerberg reports royalties from Springer for his book Clinical Prediction Models. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors /icmje/ConflictOfInterestForms.do?msNum=M18-3668. Publisher Copyright: {\textcopyright} 2020 American College of Physicians.",
year = "2020",
month = jan,
day = "7",
doi = "10.7326/M18-3668",
language = "English (US)",
volume = "172",
pages = "W1--W25",
journal = "Annals of Internal Medicine",
issn = "0003-4819",
publisher = "American College of Physicians",
number = "1",
}