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Excess Body Mass Index and Risk of Liver Cancer: A Nonlinear Dose-Response Meta-Analysis of Prospective Studies

Author

Listed:
  • Rui Rui
  • Jiao Lou
  • Li Zou
  • Rong Zhong
  • Ji Wang
  • Ding Xia
  • Qi Wang
  • Heng Li
  • Jing Wu
  • Xuzai Lu
  • Chuanqi Li
  • Li Liu
  • Jiahong Xia
  • Hua Xu

Abstract

Background: Excess body weight measured as body mass index (BMI) has a positive association with risk of common cancers. However, previous meta-analyses related to BMI and liver cancer had inconsistent results. The purpose of the current study is to establish a nonlinear dose-response relationship between BMI and incidence risk of liver cancer. Methods: A systematic literature search for relevant articles published from 1966 to November 2011 was conducted in PUBMED and EMBASE digital databases. Additional articles were manually searched by using the reference lists of identified papers. Restricted cubic splines and generalized least-squares regression methods were used to model a potential curvilinear relationship and to make a dose-response meta-analysis. Stratified analysis, sensitivity analysis and assessment of bias were performed in our meta-analysis. Results: 8 articles including 1,779,471 cohort individuals were brought into meta-analysis. A non-linear dose-response association between BMI and risk of liver cancer was visually significant (P for nonlinearity 0.1), and all value of BMI still presented significantly increased risk of cancer. Conclusions: The findings from meta-analysis provided that excess BMI had significant increased association with risk of liver cancer, although the biological mechanisms underlying the obesity-cancer link still need to be clarified.

Suggested Citation

  • Rui Rui & Jiao Lou & Li Zou & Rong Zhong & Ji Wang & Ding Xia & Qi Wang & Heng Li & Jing Wu & Xuzai Lu & Chuanqi Li & Li Liu & Jiahong Xia & Hua Xu, 2012. "Excess Body Mass Index and Risk of Liver Cancer: A Nonlinear Dose-Response Meta-Analysis of Prospective Studies," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-7, September.
    • Handle: RePEc:plo:pone00:0044522
    DOI: 10.1371/journal.pone.0044522
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    References listed on IDEAS

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    1. Nicola Orsini & Rino Bellocco & Sander Greenland, 2006. "Generalized least squares for trend estimation of summarized dose–response data," Stata Journal, StataCorp LP, vol. 6(1), pages 40-57, March.
    2. Nicola Orsini & Sander Greenland, 2011. "A procedure to tabulate and plot results after flexible modeling of a quantitative covariate," Stata Journal, StataCorp LP, vol. 11(1), pages 1-29, March.
    3. Aurelio Tobias, 1999. "Assessing the influence of a single study in the meta-anyalysis estimate," Stata Technical Bulletin, StataCorp LP, vol. 8(47).
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    1. Jie Dong & Yi Chen & Yuchen Tang & Fei Xu & Chaohui Yu & Youming Li & Prasoon Pankaj & Ning Dai, 2015. "Body Mass Index Is Associated with Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-19, December.

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