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

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


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antidepressive Agents / therapeutic use*
  • Biomarkers, Pharmacological*
  • Clinical Trials as Topic
  • Computer Simulation
  • Cost-Benefit Analysis
  • Depression / drug therapy*
  • Genotype
  • Humans
  • Reference Standards
  • Treatment Outcome*


  • Antidepressive Agents
  • Biomarkers, Pharmacological