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DOI: 10.1055/s-0038-1634826
Multivariate Procedures to Describe Clinical Staging of Melanoma
Dr. Manton’s efforts in this research were supported by NIA Grant No.AG01159. Dr. Woodbury’s efforts were supported by NIA Grant No.AG03188. Dr. Wrigley’s efforts were supported, while he was a postdoctoral fellow at Duke University, by NIA Grant No. T32AG00139. Dr. Cohen’s efforts were supported by USPHS grant nos. CA14236 and CA36566.
Publication History
Publication Date:
07 February 2018 (online)
Abstract
Analyzing multivariate clinical data to identify subclasses of patients being treated for a specific disease may improve patient management and increase understanding of the behavior of disease under clinical conditions. In some cases, patients have been classified on prognostic characteristics using standard risk assessment procedures (e.g.. Cox’ regression). This requires long term follow-up, differentiates patients only on attributes relevant to survival, and assumes that patients are sampled from a common population. Other approaches involve the use of clustering algorithms to classify patients into categories based on multiple clinical attributes. We illustrate the use of a multivariate statistical procedure to directly characterize patients on multiple clinical characteristics. The procedure is designed to analyze discrete response data with parameters representing individual differences within groups. Its use is illustrated for patients with Stage I melanoma in determining how age is related to treatment response in different patient groups.
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