Literature DB >> 22256872

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

Rudolf Uher1, Katherine E Tansey, Karim Malki, Roy H Perlis.   

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.

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Year:  2012        PMID: 22256872      PMCID: PMC3566553          DOI: 10.2217/pgs.11.161

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  28 in total

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6.  Power considerations when a continuous outcome variable is dichotomized.

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  18 in total

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