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Moderate concordance was found between case-only and parallel group designs in systematic comparison.
Koen Bernardus Pouwels1, Bianca Mulder1, Eelko Hak2
1Unit of PharmacoEpidemiology & PharmacoEconomics, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands.
Journal of Clinical Epidemiology
|October 13, 2015
Summary
Effect estimates from case-only and parallel group study designs show moderate agreement. Discrepancies in epidemiological research can be predicted by factors like intermittent exposure and rare events, suggesting careful design is needed.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Case-only designs (case crossover, self-controlled case series) and parallel group designs (cohort, case-control) are used in epidemiological research.
- Evaluating the concordance of effect estimates between these designs is crucial for reliable research.
Purpose of the Study:
- To empirically assess the agreement between effect estimates derived from case-only and parallel group study designs.
- To identify key predictors that contribute to discrepancies in effect estimates between these epidemiological study designs.
Main Methods:
- A systematic literature search of MEDLINE and EMBASE databases was conducted up to June 31, 2013.
- Studies employing both case-only and parallel group designs were included, with 519 comparisons analyzed.
- Spearman correlation and Z-scores evaluated concordance, while a prediction model identified discrepancy predictors.
Main Results:
- A moderate correlation (0.64) was observed between effect estimates from case-only and parallel group designs.
- Significant discrepancies exceeding a threshold were found in 43% of comparisons.
- Predictors of discrepancy included intermittent exposure, rare events, acute outcomes, hazard period length, case-only design type, and sample size.
Conclusions:
- The concordance between case-only and parallel group designs is moderate, indicating potential for divergent results.
- Discrepancies can often be predicted by violations of the assumptions underlying case-only study designs.
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