Low fat mass index outperforms handgrip weakness and GLIM-defined malnutrition in predicting cancer survival: Derivation of cutoff values and joint analysis in an observational cohort

The optimal thresholds to define a survival-related low fat mass index (FMI) in Asian oncology populations remains largely unknown. This study sought to derive the sex-specific FMI cutoffs and analyze the independent and joint associations of a low FMI, handgrip weakness, and the Global Leadership Initiative on Malnutrition (GLIM)-defined malnutrition with cancer survival.We performed a multicenter cohort study including 2376 patients with cancer. The FMI was measured by bioelectrical impedance analysis and the best thresholds were determined using an optimal stratification (OS) method. Low handgrip strength (HGS) and malnutrition were defined based on the Asian Working Group for Sarcopenia 2019 framework and the GLIM, respectively. The associations of a low FMI, handgrip weakness and malnutrition with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HRs).The study enrolled 1303 women and 1073 men with a mean age of 57.7 years and a median follow-up of 1267 days. The OS-defined FMI cutoffs were <5 kg/m2 in women and <7.7 kg/m2 in men. A low FMI, low HGS and malnutrition were identified in 1188 (50%), 1106 (46.5%) and 910 (38.3%) patients, respectively. A low FMI was adversely associated with the nutritional status, physical performance, quality of life and hospitalization costs. A low FMI (HR = 1.50, 95%CI = 1.16 to 1.92) and malnutrition (HR = 1.31, 95%CI = 1.08 to 1.59) were independently associated with mortality. Overall, the FMI plus GLIM-defined malnutrition showed the maximal joint prognostic impact, and patients with a combined low FMI and malnutrition had the worst survival (HR = 1.93, 95%CI = 1.48 to 2.52).Low FMI-indicated fat depletion outperforms and strengthens the prognostic value of handgrip weakness and GLIM-defined malnutrition for cancer survival. These findings indicate the importance of including fat mass assessment during routine cancer care to help guide strategies to optimize survival outcomes.