| Title: | Is Body Roundness Index a Predictor of Cancer Incidence and Mortality? A Prospective Cohort Study |
| Journal: | International Journal of Cancer |
| Published: | 22 Aug 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42631431/ |
| DOI: | https://doi.org/10.1002/ijc.70716 |
Publication 20929
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Abstract
Body Roundness Index (BRI) is a novel measure of visceral and total body fat. Its association with multiple cancers and predictive value relative to Body Mass Index (BMI) remain unclear. The associations between BRI and the incidence and mortality (specific, overall and all causes death) risk of 23 site-specific cancers were evaluated using Cox proportional hazards models in UK Biobank participants. Restricted cubic spline (RCS) was further employed to assess the nonlinear association between BRI and 23 cancers. Additionally, we used the C-index and NRI to compare the predictive ability of BRI and BMI for cancer incidence and mortality risk. During a median follow-up of 13.7 years, higher BRI significantly increased overall cancer risk (hazard ratio [HR] = 1.04, 95% confidence interval [CI]: 1.03-1.14), persisting after BMI or residual adjustment. Positive linear associations were observed for 10 cancers (esophagus, stomach, colorectal, gallbladder, pancreas, corpus uteri, kidney, bladder, thyroid, and Hodgkin's; HRs: 1.05-1.31). Nonlinear patterns included inverted U-shaped (breast, prostate) and U-shaped (liver) associations (Pnon-linear < 0.05). Higher BRI also predicted increased overall cancer mortality (HR = 1.04, 95% CI: 1.02-1.06) and all-cause mortality (HR = 1.07, 95% CI: 1.05-1.09), especially among breast and prostate cancer patients. However, BRI and BMI showed comparable predictive ability for both incidence and mortality (all PΔC-indices > 0.05). BRI is significantly associated with the incidence and mortality of various cancers. With predictive performance comparable to BMI, BRI serves as a valuable anthropometric indicator for assessing cancer risks.</p>
15 Authors
- Yangyang Liu
- Xuanli Zhao
- Shuting Shen
- Yizi Chen
- Le Wang
- Yiqin Wu
- Fuhua Wu
- Zichen Liu
- Shiyuan Li
- Jiayu Li
- Ding Ye
- Jing Guo
- Yingying Mao
- Yehua Lin
- Xiaohui Sun
1 Application
| Application ID | Title |
|---|---|
| 99685 | Integrating genetics and omics data with epidemiologic and EHR data to improve the understanding of etiology of major cancers |
Enabling scientific discoveries that improve human health