Statistical analysis
death, cancer, Deaths, Death, deaths, diabetes
CANCER, EVENT, SECONDARY, REGRESSION, DIABETES
The purpose of this secondary data analysis was to explore the long-term associations between metformin use and cancer based on the principles of intention to treat. Therefore, metformin exposure was defined as baseline metformin use only. A review of metformin use or nonuse over the follow-up period revealed that 83% of participants maintained consistency of either use or non-use of metformin. Cox proportional hazards regression models were used to analyze the relationship between metformin exposure at study baseline and cancer outcomes. For cancer incidence, the analysis was performed on the first cancer event (date of diagnosis) of any in-trial cancer, and censoring was defined at death if non–cancer-related death occurred (as a non–cancer-related death strongly indicated that cancer was not present) or the last date on which clinical event data were collected. For cancer mortality, the date of death was used as the event date, and censoring was defined at the end of the study, when the National Death Indices search was performed. Adjusted hazard ratios (HRs) were determined for incident cancer and mortality, which controlled for baseline factors identified as potential confounders. Because of limited sample size, cancer location site and stage were not analyzed. Competing-risks Nelson-Aalen cumulative incidence curves of cancer incidence and mortality are presented for participants with diabetes who do and do not use metformin.To assess whether the association of metformin on outcome varied by therapeutic efficacy, additional Cox proportional hazard regression models included an interaction term between baseline blood glucose and metformin. Using these models, the log adjusted hazard ratio of metformin, across varying levels of blood glucose, were visualized using line plots.The random allocation of ASPREE participants to aspirin or placebo was used to compare the aspirin effect between those who do and do not use metformin. Thus, these Cox proportional hazard regression models included an interaction between metformin and aspirin and were not adjusted for baseline factors.Supplementary analysis was conducted using competing risks regression through Fine-Gray subdistribution hazard models. Deaths that occurred when participants were still at risk of cancer incidence were considered a competing risk of cancer incidence, but non–cancer-related deaths in participants with a cancer diagnosis were considered a competing risk of cancer mortality.The proportional hazards assumption was assessed using tests of the Schoenfeld residuals against time (