McShane and Hayes and Ginsburg and Kuderer in the special series issue of the Journal provide a comprehensive vision for improved conduct and reporting of predictive/prognostic biomarker research in personalized cancer medicine. Their visions are prompted by the need for more methodologic rigor for validation studies in this field as highlighted by a critical appraisal of 37 published reports in a systematic review. They invoke three strategies for improving study quality: first, comparative effectiveness research (CER) that addresses population-level effects of alternative interventions; second, quality improvement (QI) tools as methodologic standards; and third, infrastructure development for informatics and data linkage, and institutional networking with data sharing.
No takes yet. Share an insight, caveat, or question.
George P. Browman (2012) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: