Research Paper Volume 12, Issue 5 pp 4230—4246
Development, validation and clinical impact of a prediction model for 6-month mortality in older cancer patients: the GRADE
- 1 APHP, Avicenne Hospital, Department of Medical Oncology, Bobigny F-93000, France
- 2 INSERM, U942, Paris F-75010, France
- 3 APHP, Henri-Mondor Hospital, Public Health Department, Créteil F-94000, France
- 4 Université Paris-Est, UPEC, DHU A-TVB, IMRB- EA 7376 CEpiA (Clinical Epidemiology And Ageing Unit), Créteil F-94000, France
- 5 Université Paris 13, Sorbonne Paris Cite, Villetaneuse F-93000, France
- 6 APHP, Avicenne Hospital, Department of Gastroenterology, Bobigny F-93000, France
- 7 APHP, Georges Pompidou European Hospital, Geriatric Department, Paris F-75015, France
- 8 APHP, Avicenne Hospital, Geriatric department, Coordination Unit in Geriatric Oncology, Bobigny F-93000, France
Received: January 3, 2020 Accepted: February 20, 2020 Published: March 10, 2020https://doi.org/10.18632/aging.102876
How to Cite
Copyright © 2020 Angeli et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.