Purpose When studying nosocomial infections, resource-efficient sampling designs such as nested case-control, case-cohort, and point prevalence studies are preferred. However, standard analyses of these study designs can introduce selection bias, especially when interested in absolute rates and risks. Moreover, nosocomial infection studies are often subject to competing risks. We aim to demonstrate in this tutorial how to address these challenges for all three study designs using simple weighting techniques. Patients and Methods We discuss the study designs and explain how inverse probability weights (IPW) are applied to obtain unbiased hazard ratios (HR), odds ratios and cumulative incidences. We illustrate these methods in a multi-state framework using a dataset from a nosocomial infections study (n = 2286) in Moscow, Russia. Results Including IPW in the analysis corrects the unweighted naïve analyses and enables the estimation of absolute risks. Resulting estimates are close to the full cohort estimates using substantially smaller numbers of patients. Conclusion IPW is a powerful tool to account for the unequal selection of controls in case-cohort, nested case-control and point prevalence studies. Findings can be generalized to the full population and absolute risks can be estimated. When applied to a multi-state model, competing risks are also taken into account.

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Patient registries are a very important and essential tool for investigating rare diseases, as most physicians only see a limited number of cases during their career. Diseases of multi-organ autoimmunity and autoinflammation are especially challenging, as they are characterized by diverse clinical phenotypes and highly variable expressivity. The GAIN consortium (German multi-organ Auto Immunity Network) developed a dataset addressing these challenges. ICD-11, HPO, and ATC codes were incorporated to document various clinical manifestations and medications with a defined terminology. The GAIN dataset comprises detailed information on genetics, phenotypes, medication, and laboratory values. Between November 2019 and July 2022, twelve centers from Europe have registered 419 patients with multi-organ autoimmunity or autoinflammation. The median age at onset of symptoms was 13 years (IQR 3–28) and the median delay from onset to diagnosis was 5 years (IQR 1–14). Of 354 (84.5%) patients who were genetically tested, 248 (59.2%) had a defined monogenetic cause. For 87 (20.8%) patients, no mutation was found and for 19 (4.5%), the result was pending. The most common gene affected was NFkB1 (48, 11.5%), and the second common was CTLA4 (40, 9.5%), both genetic patient groups being fostered by specific research projects within GAIN. The GAIN registry may serve as a valuable resource for research in the inborn error of immunity community by providing a platform for etiological and diagnostic research projects, as well as observational trials on treatment options.

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