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Updated: Mar 8, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Using cluster analysis of anxiety-depression to identify subgroups of prostate cancer patients for targeted treatment
Christopher F Sharpley1, Vicki Bitsika2, Amelia K Warren2
1Brain-Behaviour Research Group, University of New England, Armidale, New South Wales, Australia.
Background:
To explore any possible subgroupings of prostate cancer (PCa) patients based upon their combined anxiety-depression symptoms for the purposes of informing targeted treatments.
Methods:
A sample of 119 PCa patients completed the GAD7 (anxiety) and PHQ9 (depression), plus a background questionnaire, by mail survey. Data on the GAD7 and PHQ9 were used in a cluster analysis procedure to identify and define any cohesive subgroupings of patients within the sample.
Results:
Three distinct clusters of patients were identified and were found to be significantly different in the severity of their GAD7 and PHQ9 responses, and also by the profile of symptoms that they exhibited.
Conclusions:
The presence of these 3 clusters of PCa patients indicates that there is a need to extend assessment of anxiety and depression in these men beyond simple total score results. By applying the clustering profiles to samples of PCa patients, more focussed treatment might be provided to them, hopefully improving outcome efficacy.
