Statistical methods for studying disease subtype heterogeneity

Abstract

A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome, and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, as well as non-neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular disease, autism and autoimmune disease. In this article, we discuss analytic options for studying disease subtype heterogeneity, emphasizing methods for evaluating whether the association of a potential risk factor with disease varies by disease subtype. Methods are described for scenarios where disease subtypes are categorical and ordinal, and for cohort studies, matched and unmatched case-control studies, and case-case study designs. For illustration, we apply the methods to a molecular pathological epidemiology study of alcohol intake and colon cancer risk by tumor LINE-1 methylation subtypes. User-friendly software to implement the methods is publicly available.

Association Between Inflammatory Diet Pattern and Risk of Colorectal Carcinoma Subtypes Classified by Immune Responses to Tumor

“…For each participant, we calculated follow-up time (in month) from the date of the questionnaire return at the study baseline until the date of death, colorectal cancer diagnosis, or end of follow-up, whichever came first. We used duplication-method time-varying Cox proportional cause-specific hazards regression analysis weighted by inverse probabilities for competing risks data 21, 22 to assess the associations of EDIP scores with risks of colorectal cancer subtypes classified by the degrees of lymphocytic reaction. Testing for trend across quintiles of EDIP scores was performed using the median value of each quintile group in the Cox regression models.…”

“…The primary hypothesis testing was set as a heterogeneity test (with its significance measure being P heterogeneity ) on the associations of EDIP scores with differential cancer subtypes classified by four different lymphocytic reaction markers. 22, 23 Hence, we adjusted the alpha level to 0.01 (≈ 0.05/4) by Bonferroni correction. All other analyses including evaluation of individual hazard ratios (HRs) represent secondary analyses.…”

Type II Diabetes and Incidence of Estrogen Receptor Negative Breast Cancer in African American Women

“…We also stratified on menopausal status because BMI has been shown to have different associations for pre- and postmenopausal breast cancer (22,23). We used interaction terms and Wald statistics to test for multiplicative interaction, and we performed a contrast test to assess heterogeneity of associations across ER subtypes (24). …”

Association of Physical Activity by Type and Intensity With Digestive System Cancer Risk

“…Potential heterogeneity in the relationship by digestive tract cancers versus digestive accessory organ cancers was checked using competing Cox proportional hazards model with a data augmentation method. 18 As sensitivity analyses to examine potential influence of residual confounding, we ran the primary multivariable analyses across strata of potential confounders; after excluding health conscious individuals as indicated by having family history of cancer or undergoing screening physical examination. There was no evidence of departure from the proportional hazard assumption, given P >0.05 from the Wald test performed for an additionally added interaction term between continuous PA and continuous age.…”