J Cachexia Sarcopenia Muscle. 2023 Nov 23.
Hailun Xie,
Heyang Zhang,
Guotian Ruan,
Lishuang Wei,
Yizhong Ge,
Shiqi Lin,
Mengmeng Song,
Ziwen Wang,
Chenan Liu,
Jinyu Shi,
Xiaoyue Liu,
Ming Yang,
Xin Zheng,
Yue Chen,
Xiaowei Zhang,
Hanping Shi.
BACKGROUND: Involuntary weight loss (WL) is a common symptom in cancer patients and is associated with poor outcomes. However, there is no standardized definition of WL, and it is unclear what magnitude of weight loss should be considered significant for prognostic purposes. This study aimed to determine an individualized threshold for WL that can be used for prognostic assessment in cancer patients.METHODS: Univariate and multivariate analyses of overall survival (OS) were performed using Cox proportional hazard models. The Kaplan-Meier method was performed to estimate the survival distribution of different WL levels. Logistic regression analysis was used to determine the relationship between WL and 90-day outcomes. Restricted cubic splines with three knots were used to examine the effects of WL on survival under different body mass index (BMI) conditions.
RESULTS: Among the 8806 enrolled patients with cancer, median survival time declined as WL increased, from 25.1 to 20.1, 17.8 and 16.4 months at <2%, 2-5%, 5-10% and ≥10% WL, respectively (P < 0.001). Multivariate adjusted Cox regression analysis showed that the risk of adverse prognosis increased by 18.1% based on the SD of WL (5.45 U) (HR: 1.181, 95% CI: 1.144-1.219, P < 0.001). Similarly, categorical WL was independently associated with OS in patients with cancer. With the worsening of WL, the risk of a poor prognosis in patients increases stepwise. Compared with <2% WL, all-cause mortalities were 15.1%, 37% and 64.2% higher in 2-5%, 5-10%, and ≥10% WL, respectively. WL can effectively stratify the prognosis of both overall and site-specific cancers. The clinical prognostic thresholds for WL based on different BMI levels were 4.21% (underweight), 5.03% (normal), 6.33% (overweight), and 7.60% (obese). Multivariate logistic regression analysis showed that WL was independently associated with 90-day outcomes in patients with cancer. Compared with patients with <2% WL, those with ≥10% WL had more than twice the risk of 90-day outcomes (OR: 3.277, 95% CI: 2.287-4.694, P < 0.001). Systemic inflammation was a cause of WL deterioration. WL mediates 6.3-10.3% of the overall association between systemic inflammation and poor prognoses in patients with cancer.
CONCLUSIONS: An individualized threshold for WL based on baseline BMI can be used for prognostic assessment in cancer patients. WL and BMI should be evaluated simultaneously in treatment decision-making, nutritional intervention, and prognosis discussions of patients with cancer.
Keywords: Cancer; Nutrition; Prognosis; Weight loss