TY - JOUR
T1 - Biomarkers predicting treatment outcome in depression
T2 - What is clinically significant?
AU - Uher, Rudolf
AU - Tansey, Katherine E.
AU - Malki, Karim
AU - Perlis, Roy H.
PY - 2012/1
Y1 - 2012/1
N2 - 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.
AB - 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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U2 - 10.2217/pgs.11.161
DO - 10.2217/pgs.11.161
M3 - Article
C2 - 22256872
AN - SCOPUS:84855916364
SN - 1462-2416
VL - 13
SP - 233
EP - 240
JO - Pharmacogenomics
JF - Pharmacogenomics
IS - 2
ER -