Table 1 Features of selected approaches to analysis of HTE

Intent of HTE Analysis

· Exploratory and confirmatory

· Exploratory

· Exploratory and initial testing

· Exploratory, initial testing, and confirmatory

· Exploratory, initial testing, and confirmatory

· Exploratory and confirmatory

· Initial testing and confirmatory

Data Structure

· Trial summary results, possibly with subgroup results

· Panel or cross-section

· Repeated measures for a single patient: time series

· Time series and panel

· Panel and cross-sectional

· Panel, time series, and cross-sectional

· Panel or cross-sectional

Data Size Consideration

· Advantage of combining small sample sizes

· Large sample sizes

· Small sample sizes

· LGM: small to large sample sizes

· Moderate to large sample sizes

· Large sample sizes

· Sample sizes depends on specific risk function

· GMM: Large sample sizes

Key Strength(s)

· Increase statistical power by pooling of results

· Does not require assumptions around normality of distribution

· Patient is own control

· Accounting for unobserved characteristics

· Robust to outcome outliers

· No functional form assumptions

· Multivariate approach to identifying risk factors or HTE

· Estimates patient-specific effects

· Heterogeneous response across quantiles

· Flexible regressions

·Heterogeneous response across time

· Possible to identify HTE across trials

· Can utilize different types of response variables

· Possibility to measure and explain covariate's effect on treatment effect

Key Limitation(s)

· Included studies need to be similar enough to be meaningful

· Fairly sensitive to changes in underlying data

· Requires de novo study

· Criteria for optimization solutions not clear

· Treatment effect designed for a quantile, not a specific patient

·Computationally demanding

· May be more or less interpretable or useful clinically

· Not applicable to all conditions or treatments

· Smoothing parameters required for kernel methods

· May not fully identify additive impacts of multiple variables

· Assumed distribution

· Selection bias