Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.
Greenberg, David C
Lee, Lui S
Huang, Hong H
Public Library of Science (PLoS)
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Thurtle, D., Greenberg, D. C., Lee, L. S., Huang, H. H., Pharoah, P., & Gnanapragasam, V. (2019). Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.. PLoS medicine, 16 (3), e1002758. https://doi.org/10.1371/journal.pmed.1002758
Abstract Background Prognostic stratification is the cornerstone of management in non-metastatic prostate cancer (PCa). However, existing prognostic models are inadequate – often using treatment outcomes rather than survival, stratifying by broad heterogeneous groups and using heavily treated cohorts. To address this unmet need, we developed an individualised prognostic model which contextualizes PCa-specific mortality (PCSM) against other cause mortality, and estimates the impact of treatment on survival. Methods and findings Using records from the UK National Cancer Registration and Analysis Service, data were collated for 10,089 men diagnosed with non-metastatic PCa between 2000 and 2010 in Eastern England. Median follow-up was 9.8 years with 3,829 deaths (1,202 PCa-specific). 19.8%, 14.1%, 34.6% and 31.5% of men underwent conservative management, prostatectomy, radiotherapy and androgen deprivation monotherapy respectively. 2,546 men diagnosed in Singapore over a similar time period represented an external validation cohort. Data were randomly split 70:30 into model development and validation cohorts. 15-year PCSM and non-prostate cancer mortality (NPCM) were explored using separate multivariable Cox models within a competing risks framework. Fractional polynomials were utilised to fit continuous variables and baseline hazards. Model accuracy was assessed by discrimination and calibration using Harrell’s C-index and chi-squared goodness-of-fit respectively within both validation cohorts. A multivariable model estimating individualised 10 and 15-year survival outcomes was constructed combining age, PSA, histological grade, biopsy core involvement, stage, and primary treatment which were each independent prognostic factors for PCSM and age and comorbidity which were prognostic for NPCM. The model demonstrated good discrimination with C-index of 0.83 (95%CI: 0.80-0.85) and 0.86 (95%CI: 0.83-0.89) for 15-year PCSM in the UK and Singapore validation cohorts respectively, outperforming currently endorsed international risk-stratification criteria (p<0.001). Discrimination was maintained for overall mortality with C-index 0.75 (95%CI: 0.74-0.77) and 0.77 (95%CI: 0.74-0.79). The model was well-calibrated with no significant difference between predicted and observed PCa-specific (p=0.19) or overall deaths (p=0.43). Conclusions ‘PREDICT: Prostate’ is the first individualised multivariable PCa prognostic model built from baseline diagnostic information and the first to model potential treatment benefits on overall survival. Prognostic power is high despite using only routinely collected clinico-pathological information.
Humans, Prostatic Neoplasms, Prognosis, Registries, Multivariate Analysis, Risk Factors, Cohort Studies, Follow-Up Studies, Reproducibility of Results, Predictive Value of Tests, Models, Theoretical, Aged, Middle Aged, Male, United Kingdom
The Urology Foundation
Urology Foundation (unknown)
Urology Foundation (unknown)
Urology Foundation (David Thurtle)
External DOI: https://doi.org/10.1371/journal.pmed.1002758
This record's URL: https://www.repository.cam.ac.uk/handle/1810/289639