Prediagnosis weight loss, a stronger factor than BMI, to predict survival in patients with lung cancer

Objectives: Recent studies have demonstrated that elevated BMI is associated with improved survival in patients with lung cancer. According to the authors, this obesity paradox could be a true benefit or a spurious relationship. In this context, data from the French KBP-2010-CPHG cohort (7,051 patients followed up for primary lung cancer diagnosed in 2010 in the respiratory medicine departments of 104 nonacademic hospitals) were analyzed. Methods: Patients were stratified according to BMI at diagnosis using the definition of the French-Speaking Society of Clinical Nutrition and Metabolism (Societe Francophone de Nutrition Clinique et Metabolisme). Survival was analyzed using log-rank and a univariate Cox model. Prognostic factors were identified using a multivariate Cox model with backward elimination procedure, and with or without inclusion of prediagnosis weight loss in the model. Results: Patients were followed for a median 20.2 months. At diagnosis, respectively 12%, 28%, 45%, and 15% of the 6,595 patients with BMI data were obese, overweight, normal-weight, and underweight; 35%, 43%, 57%, and 75% reported prediagnosis weight loss (i.e., weight loss within the 3 months prior to diagnosis). One-year survival (% [95% CI]) was 53% [50%-57%], 50%, [48%-52%], 43%, [42%-45%], and 32% [29%-35%] in obese, overweight, normal-weight, and underweight patients, respectively (p < 0.001). It was particularly low in underweight patients with prediagnosis weight loss: 27% [24-30%]. BMI did not remain an independent prognostic factor associated with survival when prediagnosis weight loss was introduced in the Cox model. Risk of death was increased by 17%, 23%, and 46% in patients with < 5 kg, 5-10 kg, or >= 10 kg prediagnosis weight loss, respectively (p < 0.001). Conclusion: BMI is an easy but crude assessment tool. Other variables should be used to improve management of patients, and understanding of how prediagnosis body size and nutritional status are associated with cancer survival.