Several studies have reported bidirectional inverse associations between cancer and Alzheimer's disease (AD). This study evaluates these relationships in a Medicare population. Using Surveillance, Epidemiology, and End Results (SEER) linked to Medicare data, 1992–2005, we evaluated cancer risks following AD in a case–control study of 836,947 cancer cases and 142,869 controls as well as AD risk after cancer in 742,809 cancer patients and a non‐cancer group of 420,518. We applied unconditional logistic regression to estimate odds ratios (ORs) and Cox proportional hazards models to estimate hazards ratios (HRs). We also evaluated cancer in relation to automobile injuries as a negative control to explore potential study biases. In the case–control analysis, cancer cases were less likely to have a prior diagnosis of AD than controls (OR = 0.86; 95% CI = 0.81–0.92). Cancer cases were also less likely than controls to have prior injuries from automobile accidents to the same degree (OR = 0.83; 95% CI = 0.78–0.88). In the prospective cohort, there was a lower risk observed in cancer survivors, HR = 0.87 (95% CI = 0.84–0.90). In contrast, there was no association between cancer diagnosis and subsequent automobile accident injuries (HR = 1.03; 95% CI = 0.98–1.07). That cancer risks were similarly reduced after both AD and automobile injuries suggest biases against detecting cancer in persons with unrelated medical conditions. The modestly lower AD risk in cancer survivors may reflect underdiagnosis of AD in those with a serious illness. This study does not support a relationship between cancer and AD.

Vitamin D measurements are influenced by seasonal variation and specific assay used. Motivated by multi-center studies of associations of vitamin D with cancer, we formulated an analytic framework for matched case-control data that accounts for seasonal variation and calibrates to a reference assay. Calibration data were obtained from controls sampled within decile strata of the uncalibrated vitamin D values. Seasonal sine-cosine series were fit to control data. Practical findings included: (1) Failure to adjust for season and calibrate increased variance, bias and mean square error. (2) Analysis of continuous vitamin D requires a variance adjustment for variation in the calibration estimate. An advantage of the continuous linear risk model is that results are independent of the reference date for seasonal adjustment. (3) For categorical risk models, procedures based on categorizing the seasonally adjusted and calibrated vitamin D have near nominal operating characteristics; estimates of log odds ratios are not robust to choice of seasonal reference date, however. Thus public health recommendations based on categories of vitamin D should also define the time of year to which they refer. This work supports the use of simple methods for calibration and seasonal adjustment and is informing analytic approaches for the multi-center Vitamin D Pooling Project for Breast and Colorectal Cancer.

In totality, our data do not support a biological relationship between PD and cancer.