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Do Case-Control Studies Always Estimate Odds Ratios?

ABSTRACT: Case-control studies are an important part of the epidemiologic literature, yet there remains a lot of confusion about how to interpret estimates from different case-control study designs. We demonstrate that not all case-control study designs estimate odds ratios. In contrast, case-control studies in the literature often report odds ratios as their main parameter even when using designs that do not estimate odds ratios. Therefore, only studies using specific case-control designs should report odds ratios, whereas the case-cohort and incidence density sampled case-control studies must report risk ratio and incidence rate ratios, respectively. This also applies to case-control studies conducted in open cohorts which often estimate incidence rate ratios. We also demonstrate the misinterpretation of case-control study estimates in a small sample of highly-cited case-control studies in general epidemiologic and medical journals. We therefore suggest greater care be taken when considering which parameter is to be reported from a case-control study.

SUBMITTER: Labrecque JA

PROVIDER: S-EPMC7850067 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Do Case-Control Studies Always Estimate Odds Ratios?

Labrecque Jeremy A JA Hunink Myriam M G MMG Ikram M Arfan MA Ikram M Kamran MK

American journal of epidemiology 20210201 2

Case-control studies are an important part of the epidemiologic literature, yet confusion remains about how to interpret estimates from different case-control study designs. We demonstrate that not all case-control study designs estimate odds ratios. On the contrary, case-control studies in the literature often report odds ratios as their main parameter even when using designs that do not estimate odds ratios. Only studies using specific case-control designs should report odds ratios, whereas th ...[more]

PMID: 32889542

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Project description:Recent successful discoveries of potentially causal single nucleotide polymorphisms (SNPs) for complex diseases hold great promise, and commercialization of genomics in personalized medicine has already begun. The hope is that genetic testing will benefit patients and their families, and encourage positive lifestyle changes and guide clinical decisions. However, for many complex diseases, it is arguable whether the era of genomics in personalized medicine is here yet. We focus on the clinical validity of genetic testing with an emphasis on two popular statistical methods for evaluating markers. The two methods, logistic regression and receiver operating characteristic (ROC) curve analysis, are applied to our age-related macular degeneration dataset. By using an additive model of the CFH, LOC387715, and C2 variants, the odds ratios are 2.9, 3.4, and 0.4, with p-values of 10(-13), 10(-13), and 10(-3), respectively. The area under the ROC curve (AUC) is 0.79, but assuming prevalences of 15%, 5.5%, and 1.5% (which are realistic for age groups 80 y, 65 y, and 40 y and older, respectively), only 30%, 12%, and 3% of the group classified as high risk are cases. Additionally, we present examples for four other diseases for which strongly associated variants have been discovered. In type 2 diabetes, our classification model of 12 SNPs has an AUC of only 0.64, and two SNPs achieve an AUC of only 0.56 for prostate cancer. Nine SNPs were not sufficient to improve the discrimination power over that of nongenetic predictors for risk of cardiovascular events. Finally, in Crohn's disease, a model of five SNPs, one with a quite low odds ratio of 0.26, has an AUC of only 0.66. Our analyses and examples show that strong association, although very valuable for establishing etiological hypotheses, does not guarantee effective discrimination between cases and controls. The scientific community should be cautious to avoid overstating the value of association findings in terms of personalized medicine before their time.

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Do Case-Control Studies Always Estimate Odds Ratios?

Publications

Do Case-Control Studies Always Estimate Odds Ratios?

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