Add like
Add dislike
Add to saved papers

Using cluster analysis of anxiety-depression to identify subgroups of prostate cancer patients for targeted treatment planning.

Psycho-oncology 2017 November
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.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app