Over 80% of the nearly 1 million men diagnosed with prostate cancer annually worldwide present with localised or locally advanced non-metastatic disease. Risk stratification is the cornerstone for clinical decision making and treatment selection for these men. The most widely applied stratification systems use presenting prostate-specific antigen (PSA) concentration, biopsy Gleason grade, and clinical stage to classify patients as low, intermediate, or high risk. There is, however, significant heterogeneity in outcomes within these standard groupings. The International Society of Urological Pathology (ISUP) has recently adopted a prognosis-based pathological classification that has yet to be included within a risk stratification system. Here we developed and tested a new stratification system based on the number of individual risk factors and incorporating the new ISUP prognostic score.
Methods and Findings
Diagnostic clinicopathological data from 10,139 men with non-metastatic prostate cancer were available for this study from the Public Health England National Cancer Registration Service Eastern Office. This cohort was divided into a training set (n = 6,026; 1,557 total deaths, with 462 from prostate cancer) and a testing set (n = 4,113; 1,053 total deaths, with 327 from prostate cancer). The median follow-up was 6.9 y, and the primary outcome measure was prostate-cancer-specific mortality (PCSM). An external validation cohort (n = 1,706) was also used. Patients were first categorised as low, intermediate, or high risk using the current three-stratum stratification system endorsed by the National Institute for Health and Care Excellence (NICE) guidelines. The variables used to define the groups (PSA concentration, Gleason grading, and clinical stage) were then used to sub-stratify within each risk category by testing the individual and then combined number of risk factors. In addition, we incorporated the new ISUP prognostic score as a discriminator. Using this approach, a new five-stratum risk stratification system was produced, and its prognostic power was compared against the current system, with PCSM as the outcome. The results were analysed using a Cox hazards model, the log-rank test, Kaplan-Meier curves, competing-risks regression, and concordance indices. In the training set, the new risk stratification system identified distinct subgroups with different risks of PCSM in pair-wise comparison (p < 0.0001). Specifically, the new classification identified a very low-risk group (Group 1), a subgroup of intermediate-risk cancers with a low PCSM risk (Group 2, hazard ratio [HR] 1.62 [95% CI 0.96–2.75]), and a subgroup of intermediate-risk cancers with an increased PCSM risk (Group 3, HR 3.35 [95% CI 2.04–5.49]) (p < 0.0001). High-risk cancers were also sub-classified by the new system into subgroups with lower and higher PCSM risk: Group 4 (HR 5.03 [95% CI 3.25–7.80]) and Group 5 (HR 17.28 [95% CI 11.2–26.67]) (p < 0.0001), respectively. These results were recapitulated in the testing set and remained robust after inclusion of competing risks. In comparison to the current risk stratification system, the new system demonstrated improved prognostic performance, with a concordance index of 0.75 (95% CI 0.72–0.77) versus 0.69 (95% CI 0.66–0.71) (p < 0.0001). In an external cohort, the new system achieved a concordance index of 0.79 (95% CI 0.75–0.84) for predicting PCSM versus 0.66 (95% CI 0.63–0.69) (p < 0.0001) for the current NICE risk stratification system. The main limitations of the study were that it was registry based and that follow-up was relatively short.
A novel and simple five-stratum risk stratification system outperforms the standard three-stratum risk stratification system in predicting the risk of PCSM at diagnosis in men with primary non-metastatic prostate cancer, even when accounting for competing risks. This model also allows delineation of new clinically relevant subgroups of men who might potentially receive more appropriate therapy for their disease. Future research will seek to validate our results in external datasets and will explore the value of including additional variables in the system in order in improve prognostic performance.
Vincent Gnanapragasam and colleagues test the performance of a new 5-category risk stratification scheme for primary prostate cancer, using data from large cohorts of men with localised or locally-advanced disease.
Why Was This Study Done?
Prostate cancer incidence is rising worldwide, and, with improved detection, increasing proportions of men are presenting with non-metastatic disease (over 80%). Amongst these men, the disease is heterogeneous, and different management options are possible.
Risk stratification is the primary method of deciding which treatment is appropriate for an individual. However, the current method of risk stratification is based on historical data and was not originally validated against prostate cancer mortality as an outcome. Moreover, no current risk stratification system has been developed first in an unscreened population, which represents the vast majority of men presenting with prostate cancer worldwide.
Current risk models therefore require improvement to be more relevant for the management of prostate cancer in patients. In this study, we sought to improve clinical risk stratification by refining the attributes that make up the current risk stratification system and incorporating the latest pathological grading system for prostate cancer from the International Society of Urological Pathology.
What Did the Researchers Do and Find?
We studied a large dataset from a cohort of UK patients. Data from 10,139 men were available, and the cohort was split into a training group and a testing group for analysis.
Clinico-pathological characteristics at diagnosis (including clinical stage, biopsy grade, and prostate-specific antigen [PSA] concentration) were used first to categorise patients according to the standard three-stratum risk stratification system (from the UK NICE guidelines). These same three individual characteristics were then used to sub-stratify within each risk group. In addition, we incorporated the new pathological prognostic grading system (score 1–5) recently adopted by the International Society of Urological Pathology.
We found that the new risk model (with five subgroups) was significantly better at identifying patient populations with very different outcomes in terms of prostate-cancer-specific mortality. The model performance held true even when other competing risks of death were included. Most importantly, the model demonstrated improved prognostic power in comparison to the NICE stratification system, both in our primary cohort and in a separate external validation cohort.
What Do These Findings Mean?
To our knowledge, this study is the first to test the standard three-stratum risk stratification system in an unscreened first diagnosis population and to measure this system’s ability to predict prostate-cancer-specific mortality. We show that this model has a poor concordance for predicting mortality outcome at the point of diagnosis and is probably of little value in this context.
Our new model performs much better and not only improves prediction of mortality but also provides better distinction of patient subgroups to inform clinical decision making. Moreover, the cohorts used for our study are more representative of real-world practice, where screening for prostate cancer is uncommon.
These findings do need further validation in independent external cohorts, and our study is limited by its reliance on cancer registry records and relatively short follow-up.
Nevertheless, the large sample size and the consistency of our findings in external validation suggest that these findings are robust and ready for clinical use. The new model does not require any additional variables other than those routinely collected at diagnosis in any clinic setting worldwide and will therefore be simple to adopt internationally.