Sera Francesco, Ferrari Pietro
Molecular and Nutritional Epidemiology Unit, Cancer Prevention and Research, ISPO, Florence, Italy.
Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
PLoS One. 2015 Mar 18;10(3):e0117815. doi: 10.1371/journal.pone.0117815. eCollection 2015.
In a multicenter study, the overall relationship between exposure and the risk of cancer can be broken down into a within-center component, which reflects the individual level association, and a between-center relationship, which captures the association at the aggregate level. A piecewise exponential proportional hazards model with random effects was used to evaluate the association between dietary fiber intake and colorectal cancer (CRC) risk in the EPIC study. During an average follow-up of 11.0 years, 4,517 CRC events occurred among study participants recruited in 28 centers from ten European countries. Models were adjusted by relevant confounding factors. Heterogeneity among centers was modelled with random effects. Linear regression calibration was used to account for errors in dietary questionnaire (DQ) measurements. Risk ratio estimates for a 10 g/day increment in dietary fiber were equal to 0.90 (95%CI: 0.85, 0.96) and 0.85 (0.64, 1.14), at the individual and aggregate levels, respectively, while calibrated estimates were 0.85 (0.76, 0.94), and 0.87 (0.65, 1.15), respectively. In multicenter studies, over a straightforward ecological analysis, random effects models allow information at the individual and ecologic levels to be captured, while controlling for confounding at both levels of evidence.
在一项多中心研究中,暴露与癌症风险之间的总体关系可分解为反映个体水平关联的中心内成分和反映总体水平关联的中心间关系。在欧洲癌症与营养前瞻性调查(EPIC)研究中,采用了具有随机效应的分段指数比例风险模型来评估膳食纤维摄入量与结直肠癌(CRC)风险之间的关联。在平均11.0年的随访期间,来自10个欧洲国家28个中心招募的研究参与者中发生了4517例结直肠癌事件。模型根据相关混杂因素进行了调整。中心间的异质性采用随机效应进行建模。使用线性回归校准来处理饮食问卷(DQ)测量中的误差。膳食纤维摄入量每增加10克/天,在个体和总体水平上的风险比估计值分别为0.90(95%CI:0.85,0.96)和0.85(0.64,1.14),而校准后的估计值分别为0.85(0.76,0.94)和0.87(0.65,1.15)。在多中心研究中,与直接的生态分析相比,随机效应模型能够在控制两个证据水平混杂因素的同时,获取个体和生态水平的信息。