Body composition parameters predict survival in pancreatic cancer-A retrospective multicenter analysis

Anthropometrics and cancer prognosis: a multicenter cohort study

BACKGROUND

Anthropometric indicators have been shown to be associated with the prognosis of patients with cancer. However, any single anthropometric index has limitation in predicting the prognosis.

OBJECTIVES

This study aimed to observe the predictive role of 7 anthropometric indicators based on body size on the prognosis of patients with cancer.

METHODS

A principal component analysis (PCA) on 7 anthropometric measurements: height, weight, BMI, hand grip strength (HGS), triceps skinfold thickness (TSF), mid-upper arm circumference (MAC), and calf circumference (CAC) was conducted. Principal components (PCs) were derived from this analysis. Cox regression analysis was used to investigate the association between the prognosis of patients with cancer and the PCs. Subgroups and sensitivity analyses were also conducted.

RESULTS

Through PCA, 4 distinct PCs were identified, collectively explaining 88.3% of the variance. PC1, primarily characterized by general obesity, exhibited a significant inverse association with risk of cancer-related death (adjusted hazard ratio [HR]: 0.86; 95% confidence interval [CI]: 0.83, 0.88). PC2 (short stature with high TSF) was not significantly associated with cancer prognosis. PC3 (high BMI coupled with low HGS) demonstrated a significant increase with risk of cancer-related death (adjusted HR: 1.08; 95% CI: 1.05, 1.11). PC4 (tall stature with high TSF) exhibited a significant association with increased cancer risk (adjusted HR: 1.05; 95% CI: 1.02, 1.07). These associations varied across different cancer stages. The stability of the results was confirmed through sensitivity analyses.

CONCLUSIONS

Different body sizes are associated with distinct prognostic outcomes in patients with cancer. The impact of BMI on prognosis is influenced by both HGS and subcutaneous fat. This finding may influence the clinical care of cancer and improve the survival of cancer patients.

Body composition parameters predict survival in pancreatic cancer-A retrospective multicenter analysis

BACKGROUND

Parameters to adapt individual treatment strategies for patients with pancreatic ductal adenocarcinoma (PDAC) are urgently needed. The present study aimed to evaluate body composition parameters as predictors of overall survival (OS) in PDAC patients.

METHODS

Measurements of body composition parameters were performed on computed tomography scans at diagnosis. Height-standardized and Body Mass Index- and sex-adjusted regression formulas deriving cut-offs from a healthy population were used. The Kaplan-Meier method with the log-rank test was performed for survival analysis. Independent prognostic factors were identified with uni- and multivariable Cox regression analyses.

RESULTS

In total, 354 patients were analyzed. In a multivariable Cox model, besides tumor stage and resection status, only myosteatosis (HR 1.53; 95% CI 1.10-2.14, p = 0.01) was an independent prognostic factor of OS among body composition parameters. Subgroup analyses revealed that the prognostic impact of myosteatosis was higher in patients ≤68 years of age, with advanced tumor stages and patients without curative intended resection.

CONCLUSIONS

The analysis of one of the largest Caucasian cohorts to date, demonstrated myosteatosis to be an independent prognostic factor of OS in PDAC. To improve outcomes, prospective trials aiming to investigate the utility of an early assessment of myosteatosis with subsequent intervention by dieticians, sports medicine physicians, and physiotherapists are warranted.