Table 1

Features of selected approaches to analysis of HTE
Meta-analysis CART N of 1 trials LGM/GMM* QTE** Nonparametric Predictive risk models
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

* LGM/GMM: Latent growth modeling/Growth mixture modeling.

**QTE: Quantile treatment effect.

Willke et al.

Willke et al. BMC Medical Research Methodology 2012 12:185   doi:10.1186/1471-2288-12-185

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