Article type
Abstract
Univariable meta-regression may be more conservative compared to chi-square in sub-group analyses.
Background: Authors of systematic reviews exploring heterogeneity typically use the chi-square test, the default statistical method for sub-group analysis in most statistical packages. Another analytical method to assess effect modification or heterogeneity of both binary and continuous variables is meta-regression.
Objectives: To explore the extent to which chi-square and meta-regression provide different results for subgroup analysis.
Methods: We present our experience with applying both the chi-square method and a random-effects univariable meta-regression to a recent subgroup analysis in a prognostic review on deterioration of transcatheter aortic valve implants. For this analysis, we used the DerSimonian and Laired random effect model with a Freeman-Tukey transformation. R (version 3.3.2) provided the statistical package for our analyses.
Results: The pooled incidence rate of valve deterioration from 13 observational studies was 28 (95% CI: 2 to 73) per 10 000 patient years. We observed a higher incidence rate in the subgroup of studies with no anti-coagulation at discharge (126, 95% CI: 97 to 160, I2 = 0%) than in the subgroup of studies not reporting on anticoagulation (14, 95% CI: 0.2 to 40, I2 = 87%). The chi-square test showed an interaction p-value of
Background: Authors of systematic reviews exploring heterogeneity typically use the chi-square test, the default statistical method for sub-group analysis in most statistical packages. Another analytical method to assess effect modification or heterogeneity of both binary and continuous variables is meta-regression.
Objectives: To explore the extent to which chi-square and meta-regression provide different results for subgroup analysis.
Methods: We present our experience with applying both the chi-square method and a random-effects univariable meta-regression to a recent subgroup analysis in a prognostic review on deterioration of transcatheter aortic valve implants. For this analysis, we used the DerSimonian and Laired random effect model with a Freeman-Tukey transformation. R (version 3.3.2) provided the statistical package for our analyses.
Results: The pooled incidence rate of valve deterioration from 13 observational studies was 28 (95% CI: 2 to 73) per 10 000 patient years. We observed a higher incidence rate in the subgroup of studies with no anti-coagulation at discharge (126, 95% CI: 97 to 160, I2 = 0%) than in the subgroup of studies not reporting on anticoagulation (14, 95% CI: 0.2 to 40, I2 = 87%). The chi-square test showed an interaction p-value of