BACKGROUND Previous studies provide conflicting evidence on whether metformin is protective against cancer. When studying time-varying exposure to metformin, covariates such as body mass index (BMI) and glycated haemoglobin (HbA1c) may act as both confounders and causal pathway variables, and so cannot be handled adequately by standard regression methods. Marginal structural models (MSMs) with inverse probability of treatment weights (IPTW) can correctly adjust for such confounders. Using this approach, the main objective of this study was to estimate the effect of metformin on cancer risk compared with risk in patients with T2DM taking no medication. METHODS Patients with incident type 2 diabetes (T2DM) were identified in the Clinical Practice Research Datalink (CPRD), a database of electronic health records derived from primary care in the UK. Patients entered the study at diabetes diagnosis or the first point after this when they had valid HbA1c and BMI measurements, and follow-up was split into 1-month intervals. Logistic regression was used to calculate IPTW; then the effect of metformin on all cancers (including and excluding non-melanoma skin cancer) and breast, prostate, lung, colorectal and pancreatic cancers was estimated in the weighted population. RESULTS A total of 55 629 T2DM patients were alive and cancer-free at their study entry; 2530 people had incident cancer during a median follow-up time of 2.9 years [interquartile range (IQR) 1.3-5.4 years]. Using the MSM approach, the hazard ratio (HR) for all cancers, comparing treatment with metformin with no glucose-lowering treatment, was 1.02 (0.88-1.18). Results were robust to a range of sensitivity analyses and remained consistent when estimating the treatment effect by length of exposure. We also found no evidence of a protective effect of metformin on individual cancer outcomes. CONCLUSIONS We find no evidence that metformin has a causal association with cancer risk.

中文翻译：

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二甲双胍在2型糖尿病患者中的使用和患癌症的风险：一项使用边际结构模型的逆概率加权对基层医疗记录进行的队列研究。

背景技术先前的研究提供了关于二甲双胍是否对癌症具有保护作用的相互矛盾的证据。研究二甲双胍随时间变化的暴露时，诸如体重指数（BMI）和糖化血红蛋白（HbA1c）的协变量可能同时成为混杂因素和因果关系变量，因此无法通过标准回归方法充分处理。具有权重反比概率（IPTW）的边际结构模型（MSM）可以正确地调整此类混杂因素。使用这种方法，本研究的主要目的是评估二甲双胍对癌症风险的影响（与未服用药物的T2DM患者的风险相比）。方法在临床实践研究数据链（CPRD）中确定了2型糖尿病事件（T2DM）患者，该数据库是英国基层医疗机构提供的电子健康记录数据库。患者在进行有效的HbA1c和BMI测量后，即在糖尿病诊断时或之后的第一点进入研究，并将随访分为1个月的时间间隔。使用逻辑回归法计算IPTW。然后在加权人群中评估了二甲双胍对所有癌症（包括但不包括非黑素瘤皮肤癌）以及乳腺癌，前列腺癌，肺癌，结肠直肠癌和胰腺癌的影响。结果共有55 629名T2DM患者在研究开始时还活着并且没有癌症。2530人在中位随访时间为2.9年[四分位间距（IQR）1.3-5.4年]中发生了癌症。使用MSM方法，与未采用降糖治疗的二甲双胍比较，所有癌症的风险比（HR）为1.02（0.88-1.18）。结果对于一系列敏感性分析是可靠的，并且在根据暴露时间估算治疗效果时保持一致。我们也没有发现二甲双胍对个体癌症结局具有保护作用的证据。结论我们没有发现二甲双胍与癌症风险有因果关系的证据。