A Bayesian Sensitivity Analysis to Partition Body Mass Index Into Components of Body Composition: An Application to Head and Neck Cancer Survival.

ABSTRACT: Previous studies have suggested a "J-shaped" relationship between body mass index (BMI, calculated as weight (kg)/height (m)2) and survival among head and neck cancer (HNC) patients. However, BMI is a vague measure of body composition. To provide greater resolution, we used Bayesian sensitivity analysis, informed by external data, to model the relationship between predicted fat mass index (FMI, adipose tissue (kg)/height (m)2), lean mass index (LMI, lean tissue (kg)/height (m)2), and survival. We estimated posterior median hazard ratios and 95% credible intervals for the BMI-mortality relationship in a Bayesian framework using data from 1,180 adults in North Carolina with HNC diagnosed between 2002 and 2006. Risk factors were assessed by interview shortly after diagnosis and vital status t

SUBMITTER: Bradshaw PT 

PROVIDER: S-EPMC6825827 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature