In:
European Journal of Epidemiology, Springer Science and Business Media LLC, Vol. 35, No. 7 ( 2020-07), p. 619-630
Kurzfassung:
In this paper we study approaches for dealing with treatment when developing a clinical prediction model. Analogous to the estimand framework recently proposed by the European Medicines Agency for clinical trials, we propose a ‘predictimand’ framework of different questions that may be of interest when predicting risk in relation to treatment started after baseline. We provide a formal definition of the estimands matching these questions, give examples of settings in which each is useful and discuss appropriate estimators including their assumptions. We illustrate the impact of the predictimand choice in a dataset of patients with end-stage kidney disease. We argue that clearly defining the estimand is equally important in prediction research as in causal inference.
Materialart:
Online-Ressource
ISSN:
0393-2990
,
1573-7284
DOI:
10.1007/s10654-020-00636-1
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2020
ZDB Id:
2004992-4