Biomarkers predicting treatment outcome in depression: what is clinically significant?. (January 2012)

• Record Type: Journal Article
• Authors: Uher, Rudolf; Tansey, Katherine E; Malki, Karim; Perlis, Roy H
• Is Part Of: Pharmacogenomics. Volume 13:Number 2(2012)
• Page Start: 233
• Page End: 240
• Publication Date: 2012-01
• Subjects: antidepressant medication -- biomarkers -- clinical significance -- major depressive disorder -- number needed to assess; Pharmacogenomics -- Periodicals; 615.1
• DOI: 10.2217/pgs.11.161
• Languages: English
• ISSNs: 1462-2416

Abstract

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.