Models predicting survival to guide treatment decision-making in newly diagnosed primary non-metastatic prostate cancer: a systematic review.
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Thurtle, D., Rossi, S., Berry, B., Pharoah, P., & Gnanapragasam, V. (2019). Models predicting survival to guide treatment decision-making in newly diagnosed primary non-metastatic prostate cancer: a systematic review.. BMJ open, 9 (6), e029149. https://doi.org/10.1136/bmjopen-2019-029149
Objectives Men diagnosed with non-metastatic prostate cancer require standardised and robust long-term prognostic information to help them decide on management. Most currently-used tools utilise short-term and surrogate outcomes. We explored the evidence base in the literature on available pre-treatment, prognostic models built around long-term survival, and assess the accuracy, generalisability and clinical availability of these models. Design Systematic literature review,pre-specified and registered on PROSPERO (CRD42018086394). Data sources MEDLINE, Embase and The Cochrane Library were searched from January 2000 through February 2018, using previously-tested search terms. Eligibility criteria Inclusion required a multi-variable model prognostic model for non-metastatic prostate cancer, using long-term survival data(defined as ≥5 years), which was not treatment-specific and usable at the point of diagnosis. Data extraction and synthesis Title, abstract and full-text screening were sequentially performed by 3 reviewers. Data extraction was performed for items in the CHARMS checklist. Individual studies were assessed using the new Prediction model Risk Of Bias ASsessment Tool (PROBAST). Results Database searches yielded 6,581 studies after deduplication. Twelve studies were included in the final review. Nine were model development studies using data from over 231,888 men. However, only 6/9 studies included any conservatively managed cases and only 3/9 included treatment as a predictor variable. Every included study had at least one parameter for which there was high risk of bias, with failure to report accuracy, and inadequate reporting of missing data common failings. Three external validation studies were included, reporting 2 available models: The UCSF CAPRA score and the Cambridge Prognostic Groups. Neither included treatment effect, and both had potential flaws in design, but represent the most robust and usable prognostic models currently available. Conclusion Few long-term prognostic models exist to inform decision-making at diagnosis of non-metastatic prostate cancer. Improved models are required to inform management and avoid under- and over-treatment of non-metastatic prostate cancer.
Humans, Prostatic Neoplasms, Neoplasm Staging, Prognosis, Risk Assessment, Survival Analysis, Decision Making, Health Services Misuse, Disease Management, Male
The Urology Foundation - Research Scholarships
Urology Foundation (unknown)
Urology Foundation (unknown)
Urology Foundation (David Thurtle)
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External DOI: https://doi.org/10.1136/bmjopen-2019-029149
This record's URL: https://www.repository.cam.ac.uk/handle/1810/293525
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