Trends and outcome from radical therapy for primary non-metastatic prostate cancer in a UK population.

BACKGROUND: Increasing proportions of men diagnosed with prostate cancer in the UK are presenting with non-metastatic disease. We investigated how treatment trends in this demographic have changed. PATIENT AND METHODS: Non-metastatic cancers diagnosed from 2000-2010 in the UK Anglian Cancer network stratified by age and risk group were analysed [n = 10,365]. Radiotherapy [RT] and prostatectomy [RP] cancer specific survival [CSS] were further compared [n = 4755]. RESULTS: Over the decade we observed a fall in uptake of primary androgen deprivation therapy but a rise in conservative management [CM] and radical therapy [p<0.0001]. CM in particular has become the primary management for low-risk disease by the decade end [p<0.0001]. In high-risk disease however both RP and RT uptake increased significantly but in an age dependent manner [p<0.0001]. Principally, increased RP in younger men and increased RT in men ≥ 70y. In multivariate analysis of radically treated men both high-risk disease [HR 8.0 [2.9-22.2], p<0.0001] and use of RT [HR 1.9 [1.0-3.3], p = 0.024] were significant predictors of a poorer CSM. In age-stratified analysis however, the trend to benefit of RP over RT was seen only in younger men [≤ 60 years] with high-risk disease [p = 0.07]. The numbers needed to treat by RP instead of RT to save one cancer death was 19 for this group but 67 for the overall cohort. CONCLUSION: This study has identified significant shifts in non-metastatic prostate cancer management over the last decade. Low-risk disease is now primarily managed by CM while high-risk disease is increasingly treated radically. Treatment of high-risk younger men by RP is supported by evidence of better CSM but this benefit is not evident in older men

Improving Clinical Risk Stratification at Diagnosis in Primary Prostate Cancer: A Prognostic Modelling Study.

INTRODUCTION: 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. CONCLUSIONS: 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.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pmed.100206

The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.

Purpose: To validate a new 5-tier prognostic classification system to better discriminate cancer specific mortality in men diagnosed with primary non-metastatic prostate cancer. Patients and Methods: We applied a recently described 5 strata model (Cambridge Prognostic Groups-CPG) in 2 international cohorts and tested prognostic performance against the current standard 3 strata classification of low, intermediate or high-risk disease. Diagnostic clinico-pathological data of men from Prostate Cancer Data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality. Results: The PCBaSe cohort included 72,337 men, of whom 7,162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk-regression confirming significant intergroup distinction (p<0.0001). The CPGs were significantly better at stratified prediction of PCM compared to the current 3-tier system (C-Index 0.81 vs. 0.77, p<0.0001). This superiority was maintained for every age group division (p<0.0001). Also in the ethnically different Singapore cohort of 2,550 men with 142 prostate cancer deaths, the CPG model outperformed the 3 strata categories (C-Index 0.79 vs. 0.76, p<0.0001). The model also retained superior prognostic discrimination in treatment sub-groups - Radical prostatectomy (n=20,586): C-Index 0.77 vs. 074, radiotherapy (n=11,872): C-Index 0.73 vs. 0.68, and conservative management (n=14,950): C-Index 0.74 vs. 0.73. The CPG groups that sub-divided the old intermediate (CPG2 vs. CPG3) and high-risk categories (CPG4 vs.CPG5) significantly discriminated PCM outcomes after radical therapy or conservative management (p<0.0001). Conclusion: This validation study of nearly 75,000 men, confirms that the CPG 5-tiered prognostic model has superior discrimination in predicting prostate cancer death over the 3-tier model across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes We therefore propose adoption of the CPG model as a simple to use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer

Evolution and oncological outcomes of a contemporary radical prostatectomy practice in a UK regional tertiary referral centre

Objective To investigate the clinical and pathological trends over a ten-year period for robotic-assisted laparoscopic prostatectomy (RALP) in a UK regional tertiary referral centre. Patients and Methods 1500 consecutive patients underwent RALP between October 2005 and January 2015. Prospective data was collected on clinic-pathological details at presentation as well as surgical outcomes and compared over time. Results The median(range) age of patients throughout the period was 62(35-78) years. The proportion of pre-operative high-grade cases (Gleason sum 8-10) rose from 4.6% in 2005-2008 to 18.2% in 2013-2015 (p<0.0001). In the same periods the proportion of clinical stage T3 cases operated on rose from 2.4% to 11.4% (p<0.0001). Median PSA at diagnosis did not alter significantly. Overall 11.6% of men in 2005-2008 were classified pre-operatively as high-risk by NICE criteria, compared to 33.6% in 2013-2015 (p<0.0001). The corresponding proportions for low-risk cases were 48.6% and 17.3% respectively. Final surgical pathology demonstrated an increase in tumour stage, Gleason grade and nodal status across time. The proportion of pT3 cases rose from 43.2% in 2005-2008 to 55.5% in 2013-15 (p=0.0007), Gleason grade 9-10 tumours increased from 1.8% to 9.1% (p=0.0002) and positive nodal status increased from 1.6% to 12.9% (p<0.0001) between the same periods. Despite this, positive surgical margin rates showed a downward trend in all pT groups across the different eras (p=0.72). Conclusion This study suggests that the patient profile for RALP in our unit is changing, with increasing proportions of higher-stage and more advanced disease being referred and operated on. Surgical margin outcomes however have remained good.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1111/bju.1351

Family History of Prostate Cancer and Survival Outcomes in the UK Genetic Prostate Cancer Study.

BACKGROUND: A family history (FH) of prostate cancer (PrCa) is associated with an increased likelihood of PrCa diagnosis. Conflicting evidence exists regarding familial PrCa and clinical outcomes among PrCa patients, including all-cause mortality/overall survival (OS), PrCa-specific survival (PCSS), aggressive histology, and stage at diagnosis. OBJECTIVE: To determine how the number, degree, and age of a PrCa patient's affected relatives are associated with OS and PCSS of those already diagnosed with PrCa. DESIGN, SETTING, AND PARTICIPANTS: The UK Genetic Prostate Cancer Study is a longitudinal, multi-institutional, observational study collecting baseline and follow-up clinical data since 1992. We examined OS and PCSS in 16340 men by degree and number of relatives with prostate and genetically related cancers (breast, ovarian, and colorectal). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was all-cause mortality among PrCa patients. The risk of death with respect to FH was assessed by calculating hazard ratios from Cox proportional hazard regression models, adjusting for relevant factors. RESULTS AND LIMITATIONS: A stronger FH was inversely associated with the risk of all-cause and PrCa-specific mortality. This association was greater in those with an increasing number (p-trend < 0.001) and increasing closeness (p-trend < 0.001) of the diagnosed relatives. Patients with at least one first-degree relative were at a lower risk of all-cause mortality than those with no FH (hazard ratio = 0.82 [95% confidence interval 0.75-0.89]). The population is largely of European ancestry, and this may cause an issue with representation and generalisation. Data are missing on epidemiological risk factors for death such as smoking and on comorbidities. Recall of family members' diagnoses may affect the classification of FH in unconfirmed cases. CONCLUSIONS: Based on the investigation of the type and timing of relatives' cancers, it is likely that reductions in mortality are due almost completely to a greater awareness of the disease. This study provides information for clinicians guiding patients and their relatives based on their familial risk. It shows the importance of screening and awareness programmes, which are likely to improve survival among men with an FH. PATIENT SUMMARY: We were interested in how a family history of prostate cancer affects survival in prostate cancer patients. We studied 16340 patients, categorised them according to the strength of their family history, and found that the stronger their family history, the better they did in terms of overall survival. We looked at the type and timing of patients' diagnoses compared with those of their relatives and found that this effect is likely to be explained by awareness, which indicates the importance of screening and awareness programmes

Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival.

BACKGROUND: Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE: To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS: We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS: We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS: This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY: By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa

CanRisk-Prostate: A Comprehensive, Externally Validated Risk Model for the Prediction of Future Prostate Cancer.

PURPOSE: Prostate cancer (PCa) is highly heritable. No validated PCa risk model currently exists. We therefore sought to develop a genetic risk model that can provide personalized predicted PCa risks on the basis of known moderate- to high-risk pathogenic variants, low-risk common genetic variants, and explicit cancer family history, and to externally validate the model in an independent prospective cohort. MATERIALS AND METHODS: We developed a risk model using a kin-cohort comprising individuals from 16,633 PCa families ascertained in the United Kingdom from 1993 to 2017 from the UK Genetic Prostate Cancer Study, and complex segregation analysis adjusting for ascertainment. The model was externally validated in 170,850 unaffected men (7,624 incident PCas) recruited from 2006 to 2010 to the independent UK Biobank prospective cohort study. RESULTS: The most parsimonious model included the effects of pathogenic variants in BRCA2, HOXB13, and BRCA1, and a polygenic score on the basis of 268 common low-risk variants. Residual familial risk was modeled by a hypothetical recessively inherited variant and a polygenic component whose standard deviation decreased log-linearly with age. The model predicted familial risks that were consistent with those reported in previous observational studies. In the validation cohort, the model discriminated well between unaffected men and men with incident PCas within 5 years (C-index, 0.790; 95% CI, 0.783 to 0.797) and 10 years (C-index, 0.772; 95% CI, 0.768 to 0.777). The 50% of men with highest predicted risks captured 86.3% of PCa cases within 10 years. CONCLUSION: To our knowledge, this is the first validated risk model offering personalized PCa risks. The model will assist in counseling men concerned about their risk and can facilitate future risk-stratified population screening approaches