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Association of Visceral Obesity Indices With Survival Among Cancer Survivors: Evidence From Two Nationally
Qiang Li1, Yao Wang2, Qingchun Liu1
1Department of Thoracic Surgery, Hanzhong Central Hospital, Hanzhong, Shaanxi, China.
Background:
Obesity is critical for cancer prognosis, but the impact of visceral obesity indices on survival in cancer survivors remains unclear. This study explored associations between six visceral obesity indices, BMI, and overall survival using two large population-based cohorts of cancer survivors.
Methods:
A retrospective cohort study was conducted using data from the 2001 to 2018 National Health and Nutrition Examination Survey (NHANES) and China Health and Retirement Longitudinal Study (CHARLS). Visceral obesity was assessed by a body shape index (ABSI), conicity index (ConI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), metabolic score for visceral fat (METS-VF), and lipid accumulation product (LAP). Kaplan-Meier curves, multivariable Cox regression, restricted cubic splines (RCS), mediation analysis, subgroup, and sensitivity analyses were employed.
Results:
The study included 1783 NHANES survivors (weighted population: 8,556,033; weighted median follow-up 85 months) and 162 CHARLS patients (weighted population: 5,631,233; weighted median follow-up 37 months). Only ABSI was significantly associated with increased all-cause mortality risk in both cohorts (p < 0.05). In NHANES, individuals in the highest ABSI level had 80% increased mortality risk compared to the lowest level (adjusted HR 1.80; p for trend = 0.004), consistent with CHARLS. RCS showed a linear ABSI-mortality relationship. Mediation analyses indicated that neutrophil mediated 16.77% proportion of the ABSI-mortality association in NHANES. Subgroup analyses and sensitivity analyses further confirmed these findings.
Conclusion:
Compared to other indices, ABSI may be a valuable, potentially independent predictor of survival in cancer survivors, highlighting its value for clinical assessment to identify high-risk individuals and guide targeted interventions.
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