Association between Obesity and Cancer: An Analysis Using the Competing Risk Regression Approach
Author(s) -
Milan Bimali,
Jianghua He
Publication year - 2015
Publication title -
advances in epidemiology
Language(s) - English
Resource type - Journals
eISSN - 2356-6701
pISSN - 2314-7628
DOI - 10.1155/2015/132961
Subject(s) - proportional hazards model , obesity , regression analysis , hazard ratio , medicine , population , cancer , demography , hazard , statistics , oncology , environmental health , mathematics , confidence interval , biology , ecology , sociology
Cox model has been the commonly used method in past analyses of association between obesity and the risk estimates of cancer in situations where the subjects have also died (or could die) of noncancer events (competing events). The Cox model does not address the presence of competing events convincingly. The competing risk approach accommodates the fact that individuals who died of other causes (competing events) will never die of cancer and thus provides more realistic estimates. This study uses the competing risk approach to study the association of obesity and cancer mortality and compare the analysis results with those based on the traditional Cox model. It was seen that while the cause-specific hazard rate of cancer is significantly higher for obese population compared to normal weight population, the difference is not significant using competing risk approach. We demonstrated that higher cause-specific hazard rate does not necessarily imply higher incidence rate and in situations involving competing events we recommend using competing risk approach in addition to the Cox regression model
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom