1. Development, validation and clinical impact of a prediction model for 6-month mortality in older cancer patients: the GRADE
- Author
-
Elena Paillaud, Laurent Zelek, Eurydice Angeli, Frédéric Pamoukdjian, Florence Canoui-Poitrine, Thomas Aparicio, Kader Chouahnia, B. Duchemann, Guilhem Bousquet, Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Marqueurs cardiovasculaires en situation de stress (MASCOT (UMR_S_942 / U942)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Clinical Epidemiology and Ageing : Geriatrie Soins Primaires et Santé Publique (CEpiA), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), CHU Henri Mondor, Université Paris 13 (UP13), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Ratajczak, Philippe, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord, Service d'Oncologie Médicale [AP-HP Hôpital Avicenne], Université Paris 13 (UP13)-Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de Santé Publique [Créteil], Groupe Henri Mondor-Albert Chenevier, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, Service de pneumologie [Avicenne], Service de Gastro-entérologie [Hôpital Avicenne - APHP], service d'Oncologie Gériatrique [Hôpital Avicenne - APHP], IMRB - CEPIA/'Clinical Epidemiology And Ageing : Geriatrics, Primary Care and Public Health' [Créteil] (U955 Inserm - UPEC), Institut Mondor de Recherche Biomédicale (IMRB), and Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)
- Subjects
Male ,Aging ,medicine.medical_specialty ,Multivariate statistics ,Scoring system ,[SDV.BIO]Life Sciences [q-bio]/Biotechnology ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,Risk Assessment ,03 medical and health sciences ,0302 clinical medicine ,[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system ,[SDV.CAN] Life Sciences [q-bio]/Cancer ,Weight loss ,Internal medicine ,Neoplasms ,Medicine ,cancer ,Humans ,Lung cancer ,Geriatric Assessment ,older adults ,030304 developmental biology ,Aged ,Aged, 80 and over ,0303 health sciences ,Univariate analysis ,decision support techniques ,business.industry ,Age Factors ,Cancer ,Cell Biology ,Models, Theoretical ,medicine.disease ,Prognosis ,3. Good health ,[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system ,[SDV.BIO] Life Sciences [q-bio]/Biotechnology ,[SDV.TOX] Life Sciences [q-bio]/Toxicology ,Survival Rate ,030220 oncology & carcinogenesis ,[SDV.TOX]Life Sciences [q-bio]/Toxicology ,Multivariate prediction ,Female ,medicine.symptom ,business ,gait speed ,Cohort study ,Research Paper - Abstract
International audience; Background: To develop, validate, and assess the clinical impact of a clinical score to predict a 6-month mortality risk among older cancer patients.Results: The mean age was 81.2 ± 6.1 years (women: 54%, various cancers, metastatic cancer: 45%). The score, namely the GRADE, included two geriatric variables (unintentional weight loss, impaired mobility), two oncological variables (cancer site, cancer extension), and exclusively supportive care. Up to a 14% risk of early death, the decision curves suggest that cancer treatment should be instated.Conclusion: We have developed and validated a simple score, easy to implement in daily oncological practice, to predict early death among older cancer patients which could guide oncologists in their treatment decisions.Methods: 603 outpatients prospectively included in the Physical Frailty in Elderly Cancer patients cohort study. We created a multivariate prediction model by evaluating the strength of the individual components of the Geriatric Assessment regarding risk of death at 6 months. Each component was evaluated by univariate analysis and the significant variables (P ≤ 0.20) were carried on as covariates in the multivariate cox proportion hazard analysis. The beta coefficients from the model were used to build a point-based scoring system. Clinical impact was assessed using decision curves.
- Published
- 2020