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The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.

Publication ,  Journal Article
Kent, DM; Paulus, JK; van Klaveren, D; D'Agostino, R; Goodman, S; Hayward, R; Ioannidis, JPA; Patrick-Lake, B; Morton, S; Pencina, M; Raman, G ...
Published in: Ann Intern Med
January 7, 2020

Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

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Published In

Ann Intern Med

DOI

EISSN

1539-3704

Publication Date

January 7, 2020

Volume

172

Issue

1

Start / End Page

35 / 45

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Risk Assessment
  • Randomized Controlled Trials as Topic
  • Models, Statistical
  • Individuality
  • Humans
  • General & Internal Medicine
  • Evidence-Based Medicine
  • Clinical Decision-Making
  • Clinical Decision Rules
 

Citation

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Kent, D. M., Paulus, J. K., van Klaveren, D., D’Agostino, R., Goodman, S., Hayward, R., … Steyerberg, E. W. (2020). The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement. Ann Intern Med, 172(1), 35–45. https://doi.org/10.7326/M18-3667
Kent, David M., Jessica K. Paulus, David van Klaveren, Ralph D’Agostino, Steve Goodman, Rodney Hayward, John P. A. Ioannidis, et al. “The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.Ann Intern Med 172, no. 1 (January 7, 2020): 35–45. https://doi.org/10.7326/M18-3667.
Kent DM, Paulus JK, van Klaveren D, D’Agostino R, Goodman S, Hayward R, et al. The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement. Ann Intern Med. 2020 Jan 7;172(1):35–45.
Kent, David M., et al. “The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.Ann Intern Med, vol. 172, no. 1, Jan. 2020, pp. 35–45. Pubmed, doi:10.7326/M18-3667.
Kent DM, Paulus JK, van Klaveren D, D’Agostino R, Goodman S, Hayward R, Ioannidis JPA, Patrick-Lake B, Morton S, Pencina M, Raman G, Ross JS, Selker HP, Varadhan R, Vickers A, Wong JB, Steyerberg EW. The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement. Ann Intern Med. 2020 Jan 7;172(1):35–45.

Published In

Ann Intern Med

DOI

EISSN

1539-3704

Publication Date

January 7, 2020

Volume

172

Issue

1

Start / End Page

35 / 45

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Risk Assessment
  • Randomized Controlled Trials as Topic
  • Models, Statistical
  • Individuality
  • Humans
  • General & Internal Medicine
  • Evidence-Based Medicine
  • Clinical Decision-Making
  • Clinical Decision Rules