Article type
Year
Abstract
Background:
Individual participant data meta-analyses (IPD-MA) provide the best evidence regarding treatment effects and offer opportunities and benefits when investigating subgroup effects. IPD-MA may be conducted either in one or two stages. Both procedures offer a variety of methods.
Objectives:
To compare the performance of five common regression-based approaches to detect subgroups in meta-analysis (MA) of individual participant data (IPD): meta-regression; per-subgroup MA (PS-MA); MA of interaction terms (MA-IT); naive one-stage IPD-MA (ignoring potential study-level confounding); and centered one-stage IPD-MA (accounting for potential study-level confounding).
Methods:
We conducted a simulation study where we varied the magnitude of subgroup effect (0%, 25%, 50% relative reduction), between-study treatment effect heterogeneity (none, medium, large), trial size (50,100, 200), and number of trials (5,10) for binary, continuous and time-to-event outcomes. For each scenario, we assessed the power and false positive rate (FPR) of the aforementioned five approaches.
Results:
Naive and centered one-stage IPD-MA yielded the highest power, whilst preserving acceptable FPR around the nominal 5%. Similar results were obtained for MA-IT, except when analysing binary outcomes (where it yielded less power and FPR < 5%). PS-MA showed similar power as MA-IT in non-heterogeneous scenarios, but power collapsed as heterogeneity increased, and PS-MA suffered from too high FPR, in non-heterogeneous settings. Meta-regression showed poor power (
Individual participant data meta-analyses (IPD-MA) provide the best evidence regarding treatment effects and offer opportunities and benefits when investigating subgroup effects. IPD-MA may be conducted either in one or two stages. Both procedures offer a variety of methods.
Objectives:
To compare the performance of five common regression-based approaches to detect subgroups in meta-analysis (MA) of individual participant data (IPD): meta-regression; per-subgroup MA (PS-MA); MA of interaction terms (MA-IT); naive one-stage IPD-MA (ignoring potential study-level confounding); and centered one-stage IPD-MA (accounting for potential study-level confounding).
Methods:
We conducted a simulation study where we varied the magnitude of subgroup effect (0%, 25%, 50% relative reduction), between-study treatment effect heterogeneity (none, medium, large), trial size (50,100, 200), and number of trials (5,10) for binary, continuous and time-to-event outcomes. For each scenario, we assessed the power and false positive rate (FPR) of the aforementioned five approaches.
Results:
Naive and centered one-stage IPD-MA yielded the highest power, whilst preserving acceptable FPR around the nominal 5%. Similar results were obtained for MA-IT, except when analysing binary outcomes (where it yielded less power and FPR < 5%). PS-MA showed similar power as MA-IT in non-heterogeneous scenarios, but power collapsed as heterogeneity increased, and PS-MA suffered from too high FPR, in non-heterogeneous settings. Meta-regression showed poor power (