Évaluation de prédictions dynamiques : quelques méthodes et applications au pronostic de la démence

Blanche, Paul

Journal de la société française de statistique, Tome 157 (2016) no. 2, pp. 1-18.

L’utilisation de données longitudinales pour calculer des prédictions individuelles de risque dites “dynamiques” gagne actuellement en popularité. Les prédictions sont dites dynamiques car leur calcul est actualisé au fur et à mesure que l’information sur le profil de santé des sujets évolue au cours de leur suivi. Cet article papier présente des méthodes pour quantifier et comparer des capacités pronostiques pour ce type de prédictions. Une évaluation basée sur les deux concepts de discrimination et de calibration est suggérée et une approche non paramétrique de pondération par l’inverse de la probabilité de censure est présentée pour l’inférence. Cette approche permet de s’adapter naturellement à la présence de données censurées et de risques concurrents, deux situations fréquentes en recherche médicale. Quelques résultats asymptotiques sont présentés. Des tests et des régions de confiance en sont dérivés. Une application sur des prédictions du risque de démence chez les personnes âgées est discutée. Les prédictions sont basées sur les mesures répétées de deux tests psychométriques et sont issues de deux modèles précédemment estimés sur les données de la cohorte Paquid. Leurs capacités pronostiques sont quant à elles évaluées et comparées avec les données externes de la cohorte des Trois-Cités.

The computation of dynamic predictions, using longitudinal data, has recently become popular. The term dynamic emphasizes that the predictions can be updated when the information on the subjects’ health profiles increases with follow-up time. This paper presents methods to quantify and compare prognostic abilities of such dynamic predictions. The methods aim to evaluate the calibration and discrimination performances of the dynamic predictions. We focus on methods which handle censoring and which can be applied in the competing risks setting. Inverse probability of censoring weighting estimators are suggested. Tests and both pointwise and simultaneous confidence intervals are derived from asymptotic results. We illustrate the methods by comparing predictions of dementia in the elderly, accounting for the competing risk of death. Predictions are computed from two models which model the risk of dementia given repeated measures of two psychometric tests. The models are estimated on the Paquid cohort and prediction abilities are evaluated and compared using external data from the Three-City cohort.

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