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Table 4 Addressing and reporting treatment use in prognostic model studies

From: Treatment use in prognostic model research: a systematic review of cardiovascular prognostic studies

Design

 

  Collect information on treatments used at the study baseline (see Fig. 1)

 

  Collect information on treatment drop-in or discontinuation during follow-up (see Fig. 1).

 

  If using readily available data (e.g. from an existing cohort or register), consider whether sufficient information on treatment use has been recorded.

 

Analysis

 

 Model development

 

  Guided treatments: Consider explicitly including treatment use in the prognostic model. If a treatment was randomly allocated (e.g. data from an RCT), consider using only the subset of untreated individuals [8].

 

 Model validation

 

  Guided treatments: If treatments were randomly allocated, exclude treated individuals from the analysis. If treatment use is non-random (e.g. data from an observational study or register), consider first using inverse treatment probability weighting before validating the model in the untreated subset [11].

 

  Background treatments: Consider differences in treatment use between the development and validation cohorts when exploring the impact of case-mix on model performance [24,25,26].

 

Reporting

 

  Report information on treatment use at baseline. List any treatments that may have affected the prognosis of individuals in the study and the absolute number (%) treated.

 

  Report information on effective treatments used during follow-up and, where relevant, the duration of treatment use.

 

  Discuss the potential impact of treatment use on the validity and transportability of the developed prognostic model or estimates of model performance.

 
  1. “Treatment” refers to any medical or non-medical intervention undertaken by an individual that lowers their risk of a certain outcome