Understanding of prognosis in non-metastatic prostate cancer: a randomised comparative study of clinician estimates measured against the PREDICT Prostate model.
BAUS ePoster online library. Thurtle D. 06/24/19; 259547; P5-3
Mr. David Thurtle
Mr. David Thurtle
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Decision-making around treatment for non-metastatic prostate cancer (PCa) is notoriously complex. In this study we assessed clinicians' understanding of prognosis in PCa. Responses were compared to estimates from the multivariable prognostic model PREDICT Prostate, derived from UK survival data and validated in 3 PCa cohorts (including >80,000 men). We then reviewed the model's potential impact on treatment recommendations.

Materials and methods
Study materials were managed using Qualtrics research software (Utah, USA). PCa specialists' participation was primarily requested through professional mailing lists. Respondents were randomised to group A or B and presented with opposing hypothetical vignettes: 6 with clinical diagnostic information only and 6 with these plus PREDICT Prostate estimates. Comparisons were made between groups for clinician-estimated and model-predicted 15-year survival outcomes.


190 responses were received, 121(63.7%) and 32(16.8%) respondents were urologists and oncologists respectively. Only 19.3% reported using any survival model in their current routine practice.
Clinician estimates of 15-year PCa-mortality (PCM) exceeded PREDICT Prostate estimates in 92% of the case vignettes. Mean clinician estimates were 1.9-fold greater than PREDICT. Perceptions of overall survival benefit from radical treatment were over-optimistic in every vignette, with mean clinician estimates 5.4-fold greater than PREDICT estimates. Concomitantly viewing PREDICT Prostate estimates led to reduced likelihood of recommending radical treatment in 9/12 vignettes, with reductions most evident in intermediate-risk cases.


Our study suggests clinicians overestimate PCa-related mortality and the survival benefits of radical treatment. PREDICT Prostate provides individualised and contextualised prognostic information to help inform treatment decisions, and may reduce overtreatment.
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