The Uncertain Science of Predicting Death
Menée à partir de données clinico-pathologiques portant sur 255 494 patients atteints d'un cancer diagnostiqué entre 2008 et 2015 (âge médian : 65 ans ; 53% de femmes), cette étude évalue la performance d'un modèle, basé notamment sur le statut de performance ainsi que la présence de symptômes et de comorbidités, pour prédire la survie des patients
With their study, Seow et al call attention to the complementary role that patients play in shaping end-of-life (EOL) care and the potential utility of a patient-oriented prognostic tool in influencing their experience. The investigators sought to develop a prognostic tool that is geared toward patients and families, making excellent use of a large and representative data set from Ontario, Canada, that is unique for its longitudinal measurement of patient-reported outcomes and symptom scores that are not available in most other cancer registries. Using the Edmonton Symptom Assessment Scale and Palliative Performance Scale to predict mortality, along with various other clinical factors, the investigators created a novel model for predicting mortality among patients with cancer irrespective of cancer type and laboratory values.
JAMA Network Open , commentaire en libre accès, 2019