Journal
CLINICAL CANCER RESEARCH
Volume 10, Issue 21, Pages 7252-7259Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-04-0713
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Funding
- NCI NIH HHS [R21 CA100825] Funding Source: Medline
- NIEHS NIH HHS [K0-8 ES11571] Funding Source: Medline
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The ability to parse tumors into subsets based on biomarker expression has many clinical applications; however, there is no global way to visualize the best cut-points for creating such divisions. We have developed a graphical method, the X-tile plot that illustrates the presence of substantial tumor subpopulations and shows the robustness of the relationship between a biomarker and outcome by construction of a two dimensional projection of every possible subpopulation. We validate X-tile plots by examining the expression of several established prognostic markers (human epidermal growth factor receptor-2, estrogen receptor, p53 expression, patient age, tumor size, and node number) in cohorts of breast cancer patients and show how X-tile plots of each marker predict population subsets rooted in the known biology of their expression.
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