Stat Med 2016 06 5;35(13):2133-48. Epub 2016 Jan 5.
Department of Statistics, Texas A&M University, College Station, TX, U.S.A.
Vitamin D measurements are influenced by seasonal variation and specific assay used. Motivated by multicenter 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 the following: (1) failure to adjust for season and calibrate increased variance, bias, and mean square error and (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 multicenter Vitamin D Pooling Project for Breast and Colorectal Cancer. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.