How accurate are physicians in the prediction of patient survival in advanced lung cancer?
Fiche publication
Date publication
janvier 2010
Auteurs
Membres identifiés du Cancéropôle Est :
Dr CLEMENT-DUCHENE Christelle, Pr GUILLEMIN Francis, Pr MARTINET Yves
Tous les auteurs :
Clement-Duchene C, Carnin C, Guillemin F, Martinet Y
Lien Pubmed
Résumé
BACKGROUND: Because most cases of non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage with a poor prognosis, patient inclusion in clinical trials is critical. Most trials require an estimated life expectancy >3 months, based on clinician estimates of patient survival probability, without providing formal guidelines. The aim of this study was to assess the accuracy of clinicians' predictions of survival in NSCLC patients (stages IIIB, and IV) and the possible impact of patient quality of life on survival estimation. METHODS: At diagnosis, clinical, biological, and quality of life data (QLQ-C30 questionnaire) were recorded, and doctors "forecast" each patient's estimated survival. Concordance between predicted and actual survival was assessed with the intraclass correlation coefficient. RESULTS: Eighty-five patients with a mean age of 62.2 years, 81.1% male, were included (squamous cell carcinoma, 33; adenocarcinoma, 42; large cell carcinoma, 8; neuroendocrine carcinoma, 2). The mean follow-up was 40 months and median survival time was 11.7 (range, 0.4-143.7) weeks. All clinicians (residents, registrars, and consultants) overestimated patient survival time, with a moderate concordance between predicted and actual survival time. A worse global health status was associated with a lower discrepancy between estimated and actual patient survival, and a worse role functioning was associated with a larger difference between estimated and actual patient survival. CONCLUSION: The absence of specific recommendations to estimate patient survival may introduce major selection in clinical studies. Further research should investigate whether the accuracy of patient survival estimates by clinicians would be improved by taking into account patient quality of life.
Référence
Oncologist. 2010;15(7):782-9