Background Handgrip strength (HGS) is associated with poor clinical outcomes, including all-cause, non-cardiovascular, and cardiovascular mortalities. The published cutoff points for HGS are mostly based on community populations from Western countries, lacking information on cancer patients from China. The objective of this study was to establish sex-specific cutoff points for Chinese cancer patients and investigate the effect of low HGS on cancer mortality. Methods We did a retrospective cohort study of patients who were diagnosed with malignant cancer from June 2012 to December 2018. HGS was measured using a hand dynamometer in 8257 cancer patients. Optimal stratification was used to solve threshold points. The hazard ratio (HR) of all cancer mortality and cancer-specific mortality was calculated using Cox proportional hazard regression models. Results Among all participants, there were 3902 (47.3%) women and 4355 (52.7%) men. The median age was 58 years old. The cutoff points of HGS to best classify patients with respect to time to mortality were <16.1 kg for women and <22 kg for men. Low HGS was associated with overall cancer mortality in both women and men [
Background
The skeletal muscle mass index (SMI) and skeletal muscle radiodensity (SMD) are important components of sarcopenia and malnutrition. However, their assessment requires additional resources in cancer patients, which is inconvenient for the early detection of sarcopenia and malnutrition.
Objectives
This study aimed to develop and validate nomograms for the prediction of low muscle mass and muscle radiodensity and to examine the application value of the nomograms in the diagnoses of sarcopenia and malnutrition.
Methods
A total of 1315 patients diagnosed with gastric cancer between July 2014 and May 2019 were included. Random resampling with an 80/20 split ratio was performed to obtain a training cohort (n = 1056) and a validation cohort (n = 259). Nomograms were separately constructed for low SMI (LSMI) and low SMD (LSMD) in the training cohort based on prospectively collected preoperative data. The performance of the nomograms was assessed using the AUC, calibration curve, and Hosmer-Lemeshow test. The application values of the nomograms in the diagnoses of sarcopenia and malnutrition were also evaluated.
Results
Age, BMI, hemoglobin concentration, and gait speed were included in the nomogram for LSMI predictions. These variables, in addition to sex, were included in the nomogram for LSMD predictions. The diagnostic nomograms exhibited good discrimination, with AUCs of 0.818 (95% CI, 0.791−0.845) for the LSMI nomogram and 0.788 (95% CI, 0.761−0.815) for the LSMD diagnostic nomogram in the training cohort. Calibration was also excellent. The agreement ratios between the nomograms and actual observations in the total population were 92.3% and 95.6% for sarcopenia and malnutrition, respectively. Prognostic nomograms exhibited similar performance in the validation cohort.
Conclusions
Diagnostic nomograms consisting of preoperative factors can successfully predict LSMI and LSMD. These models facilitate early identification and timely interventions for at-risk populations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.