Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities
Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction.
Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals'preferences for health states given similar treatments and clinical risks.
Methods: Using latent class mixture model (LCA), we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states) and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups.
Results: The sample (N=244) included men with prostate cancer (n=188) and men at-risk for disease (n=56). The sample was predominantly white (77%), with mean age of 60 years (SD+/- 9.5).
Most (85.9%) were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC), substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of <.001.
The three identified clusters were named high-traders (n=31), low-traders (n=116), and no-traders (n=97). High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment.
Low-traders were less likely to trade survival time and accepted risks of treatment. No-traders were likely to make no trade-offs in any direction favouring the status quo.
There was significant difference among the clusters in the importance of sexual activity (Pearson's chi2=16.55, P=0.002; Goodman and Kruskal tau = 0.039, P<0.001). In multinomial logistic regression, the level of importance assigned to sexual activity remained an independent predictor of class membership.
Age and prostate cancer at-risk status were not significant factors in the multinomial model.
Conclusions: Most existing utility work is undertaken focusing on how people choose on average. Distinct clusters of prostate cancer treatment utilities in our sample point to the need for further understanding of subgroups and need for tailored assessment and interventions.
Author: Salimah MeghaniChristopher LeeAlexandra HanlonDeborah Bruner
Credits/Source: BMC Medical Informatics and Decision Making 2009, 9:47
Published on: 2009-11-27
Copyright by the authors listed above - made available via BioMedCentral (Open Access). Please
make sure to read our disclaimer prior to contacting 7thSpace Interactive. To contact our editors, visit our online helpdesk. If you wish submit your own press release, click here.
Social Bookmarking
RETWEET This! | Digg this! | Post to del.icio.us | Post to Furl | Add to Netscape | Add to Yahoo! | Rojo
|
|
