Biomarkers predicting treatment outcome in depression: what is clinically significant?

Rudolf Uher, Katherine E. Tansey, Karim Malki, Roy H. Perlis

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


Aim: To extend to biomarker studies the consensus clinical significance criterion of a three-point difference in Hamilton Rating Scale for Depression. Materials & methods: We simulated datasets modeled on large clinical trials. Results: In a typical clinical trial comparing active treatment and placebo, a difference of three Hamilton Rating Scale for Depression (HRSD) points at the end of treatment corresponds to 6.3% of variance in outcome explained. To achieve a similar explanatory power, genotypes with minor allele frequencies of 5, 10, 20, 30 and 50% need to attain a per allele difference of 4.7, 3.6, 2.8, 2.4 and 2.2 HRSD points, respectively. A normally distributed continuous biomarker will need an effect size of 1.5 HRSD points per standard deviation. A number needed to assess of three suggests that with this effect size, a biomarker will significantly improve the prediction of outcome in one out of every three patients assessed. Conclusion: This report provides guidance on assessing clinical significance of biomarkers predictive of outcome in depression treatment.
Original languageEnglish
Pages (from-to)233 - 240
Number of pages8
Issue number2
Publication statusPublished - Jan 2012


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