HOMEPRODUCTSCOMPANYCONTACTFAQResearchDictionaryPharmaSign Up FREE or Login

Evaluation of treatment-effect heterogeneity using biomarkers measured on a continuous scale: subpopulation treatment effect pattern plot.

Abstract
The discovery of biomarkers that predict treatment effectiveness has great potential for improving medical care, particularly in oncology. These biomarkers are increasingly reported on a continuous scale, allowing investigators to explore how treatment efficacy varies as the biomarker values continuously increase, as opposed to using arbitrary categories of expression levels resulting in a loss of information. In the age of biomarkers as continuous predictors (eg, expression level percentage rather than positive v negative), alternatives to such dichotomized analyses are needed. The purpose of this article is to provide an overview of an intuitive statistical approach-the subpopulation treatment effect pattern plot (STEPP)-for evaluating treatment-effect heterogeneity when a biomarker is measured on a continuous scale. STEPP graphically explores the patterns of treatment effect across overlapping intervals of the biomarker values. As an example, STEPP methodology is used to explore patterns of treatment effect for varying levels of the biomarker Ki-67 in the BIG (Breast International Group) 1-98 randomized clinical trial comparing letrozole with tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer. STEPP analyses showed patients with higher Ki-67 values who were assigned to receive tamoxifen had the poorest prognosis and may benefit most from letrozole.
AuthorsAnn A Lazar, Bernard F Cole, Marco Bonetti, Richard D Gelber
JournalJournal of clinical oncology : official journal of the American Society of Clinical Oncology (J Clin Oncol) Vol. 28 Issue 29 Pg. 4539-44 (Oct 10 2010) ISSN: 1527-7755 [Electronic] United States
PMID20837942 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
Chemical References
  • Antineoplastic Agents
  • Biomarkers, Tumor
  • Ki-67 Antigen
  • Nitriles
  • Triazoles
  • Tamoxifen
  • Letrozole
Topics
  • Antineoplastic Agents (therapeutic use)
  • Biomarkers, Tumor (analysis)
  • Breast Neoplasms (diagnosis, drug therapy, metabolism)
  • Female
  • Humans
  • Ki-67 Antigen (analysis)
  • Letrozole
  • Models, Statistical
  • Neoplasms (diagnosis, metabolism, therapy)
  • Nitriles (therapeutic use)
  • Outcome Assessment, Health Care (methods, statistics & numerical data)
  • Predictive Value of Tests
  • Prognosis
  • Reproducibility of Results
  • Tamoxifen (therapeutic use)
  • Triazoles (therapeutic use)

Join CureHunter, for free Research Interface BASIC access!

Take advantage of free CureHunter research engine access to explore the best drug and treatment options for any disease. Find out why thousands of doctors, pharma researchers and patient activists around the world use CureHunter every day.
Realize the full power of the drug-disease research graph!


Choose Username:
Email:
Password:
Verify Password:
Enter Code Shown: