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Orphanet Journal of Rare Diseases

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Open Access 01-12-2011 | Research

Reducing selection bias in case-control studies from rare disease registries

Authors: J Alexander Cole, John S Taylor, Thomas N Hangartner, Neal J Weinreb, Pramod K Mistry, Aneal Khan

Published in: Orphanet Journal of Rare Diseases | Issue 1/2011

Abstract

Background

In clinical research of rare diseases, where small patient numbers and disease heterogeneity limit study design options, registries are a valuable resource for demographic and outcome information. However, in contrast to prospective, randomized clinical trials, the observational design of registries is prone to introduce selection bias and negatively impact the validity of data analyses.

The objective of the study was to demonstrate the utility of case-control matching and the risk-set method in order to control bias in data from a rare disease registry. Data from the International Collaborative Gaucher Group (ICGG) Gaucher Registry were used as an example.

Methods

A case-control matching analysis using the risk-set method was conducted to identify two groups of patients with type 1 Gaucher disease in the ICGG Gaucher Registry: patients with avascular osteonecrosis (AVN) and those without AVN. The frequency distributions of gender, decade of birth, treatment status, and splenectomy status were presented for cases and controls before and after matching. Odds ratios (and 95% confidence intervals) were calculated for each variable before and after matching.

Results

The application of case-control matching methodology results in cohorts of cases (i.e., patients with AVN) and controls (i.e., patients without AVN) who have comparable distributions for four common parameters used in subject selection: gender, year of birth (age), treatment status, and splenectomy status. Matching resulted in odds ratios of approximately 1.00, indicating no bias.

Conclusions

We demonstrated bias in case-control selection in subjects from a prototype rare disease registry and used case-control matching to minimize this bias. Therefore, this approach appears useful to study cohorts of heterogeneous patients in rare disease registries.

Available only for authorised users

Office of Rare Disease Research. [http://rarediseases.info.nih.gov/RareDiseaseList.aspx?PageID=1].

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Title: Reducing selection bias in case-control studies from rare disease registries
Authors: J Alexander Cole
John S Taylor
Thomas N Hangartner
Neal J Weinreb
Pramod K Mistry
Aneal Khan
Publication date: 01-12-2011
Publisher: BioMed Central
Published in: Orphanet Journal of Rare Diseases / Issue 1/2011
Electronic ISSN: 1750-1172
DOI: https://doi.org/10.1186/1750-1172-6-61

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Reducing selection bias in case-control studies from rare disease registries

Abstract

Background

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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