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Pharmacogenomics. 2012 Jan;13(2):233-40. doi: 10.2217/pgs.11.161.

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

Author information

1
Institute of Psychiatry, King's College London, 16 De Crespigny Park, SE5 8AF, London, UK. rudolf.uher@kcl.ac.uk

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.

PMID:
22256872
PMCID:
PMC3566553
DOI:
10.2217/pgs.11.161
[Indexed for MEDLINE]
Free PMC Article
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