The relative responsiveness of test instruments can be estimated using a meta-analytic approach: an illustration with treatments for depression

Objectives

We present a meta-analytic method that combines information on treatment effects from different instruments from a network of randomized trials to estimate instrument relative responsiveness.

Study Design and Setting

Five depression-test instruments [Beck Depression Inventory (BDI I/II), Patient Health Questionnaire (PHQ9), Hamilton Rating for Depression 17 and 24 items, Montgomery-Asberg Depression Rating] and three generic quality of life measures [EuroQoL (EQ-5D), SF36 mental component summary (SF36 MCS), and physical component summary (SF36 PCS)] were compared. Randomized trials of treatments for depression reporting outcomes on any two or more of these instruments were identified. Information on the within-trial ratios of standardized treatment effects was pooled across the studies to estimate relative responsiveness.

Results

The between-instrument ratios of standardized treatment effects vary across trials, with a coefficient of variation of 13% (95% credible interval: 6%, 25%). There were important differences between the depression measures, with PHQ9 being the most responsive instrument and BDI the least. Responsiveness of the EQ-5D and SF36 PCS was poor. SF36 MCS performed similarly to depression instruments.

Conclusion

Information on relative responsiveness of several test instruments can be pooled across networks of trials reporting at least two outcomes, allowing comparison and ranking of test instruments that may never have been compared directly.