Oncological outcome after radical prostatectomy: Marital status does not make a difference

Nomograms Predict Survival Advantages of Gleason Score 3+4 Over 4+3 for Prostate Cancer: A SEER-Based Study

Background: Different proportions of Gleason pattern 3 and Gleason pattern 4 lead to various prognosis of prostate cancer with Gleason score 7. The objective of this study was to compare the survival outcomes of Gleason score 3+4 and 4+3 based on data from the Surveillance, Epidemiology, and End Results cancer registry database, and to investigate independent prognosis-associated factors and develop nomograms for predicting survival in Gleason score 7 prostate cancer patients.

Methods: A retrospective study was conducted on 69,116 cases diagnosed as prostate adenocarcinoma with Gleason score 7 between 2004 and 2009. Prognosis-associated factors were evaluated using univariate and multivariate Cox regression analysis, and a 1:1 ratio paired cohort by propensity score matching with the statistical software IBM SPSS, to evaluate prognostic differences between Gleason score 3+4 and 4+3. The primary cohort was randomly divided into training set (n = 48,384) and validation set (n = 20,732). Based on the independent factors of prognosis, nomograms for prognosis were established by the training group and validated by the validation group using R version 3.5.0.

Results: After propensity score matching, Cox regression analysis showed that Gleason 4+3 had an increased mortality risk both for overall survival (HR: 1.235, 95% CI: 1.179–1.294, P < 0.001) and cancer-specific survival (HR: 1.606, 95% CI: 1.468–1.762, P < 0.001). Nomograms for overall survival and cancer-specific survival were established with C-index 0.786 and 0.842, respectively. The calibration plot indicated an optimal agreement between the actual observation and nomogram prediction for overall survival and cancer-specific survival probability at 5 or 10 year.

Conclusions: Prostate cancer with Gleason score 4+3 had worse overall survival and cancer-specific survival than Gleason score 3+4. Nomograms were formulated to predict 5-year and 10-year OS and CSS in patients with prostate cancer of Gleason score 7.

Marital status independently predicts prostate cancer survival in men who underwent radical prostatectomy: An analysis of 95,846 individuals

Marital status is an independent prognostic factor for survival in several types of cancer, but has not been fully studied in prostate cancer (PCa). A total of 95,846 men diagnosed with PCa were treated with radical prostatectomy (RP) between 2004 and 2009 within 18 Surveillance, Epidemiology and End Results registries. Survival curves were generated using Kaplan-Meier estimates and differences in survival were assessed using the log-rank test. Cox regression models were used to assess the impact of marital status on survival outcomes. The results demonstrated that the 8-year cancer-cause specific survival (CSS) rate of married men was higher than unmarried individuals. Further analyses revealed that divorced/separated men had a higher proportion of high Gleason scores (GS) PCa at diagnosis [hazard ratio (HR), 1.12; P=0.007] and those patients had the worst survival outcomes independent of age, ethnicity, grade, stage and sequence number [HR, 1.61; 95% confidence interval (CI), 1.34-1.93]. Interestingly, it was observed that CSS among divorced/separated men decreased as the GS increased (GS≤6: HR, 2.5; GS=7: HR, 1.71; GS≥8: HR, 1.50; all P<0.05). Apart from that, no significant differences in CSS were observed in those who had never been married (HR, 1.20) or were widowed (HR, 1.13) relative to the married group. The results of the present study support the hypothesis that marital status is an independent prognostic factor among men with PCa who underwent RP. It was demonstrated that the mortality rates of divorced or separated men with PCa were significantly greater compared with the other groups. A further understanding of the potential associations among marital status, psychosocial factors and survival outcomes may help in developing novel, more effective methods of treating different groups of patients with PCa.

Predicting prostate cancer progression: protocol for a retrospective cohort study to identify prognostic factors for prostate cancer outcomes using routine primary care data

INTRODUCTION

Prostate cancer is the most common cancer in men in the UK, with nearly 40 000 diagnosed in 2014; and it is the second most common cause of male cancer-related mortality. The clinical conundrum is that most men live with prostate cancer rather than die from it, while existing treatments have significant associated morbidity. Recent studies have shown very low mortality rates (1% after a median of 10-year follow-up) and no treatment-related reductions in mortality, in men with localised prostate cancer. This study will identify prognostic factors associated with prostate cancer progression to help differentiate aggressive from more indolent tumours in men with localised disease at diagnosis, and so inform the decision to adopt conservative (active surveillance) or radical (surgery or radiotherapy) management strategies.

METHODS AND ANALYSIS

The Clinical Practice Research Datalink (CPRD) contains 57 318 men who were diagnosed with prostate cancer between 1 January 1987 and 31 December 2016. These men will be linked to the Office for National Statistics (ONS) and the National Cancer Registration and Analysis Service registry databases for mortality, TNM stage, Gleason grade and treatment data. Men with a diagnosis date prior to 1 January 1987 and men with lymph node or distant metastases at diagnosis will be excluded. A priori determined prognostic factors potentially associated with prostate cancer mortality, the end point of cancer progression, will be measured at baseline, and the participants followed through to development of cancer progression, death or the end of the follow-up period (31 December 2016). Cox proportional hazards regression will be used to estimate crude and mutually adjusted HRs. Mortality risk will be predicted using flexible parametric survival models that can accurately fit the shape of the hazard function.

ETHICS AND DISSEMINATION

This study protocol has approval from the Independent Scientific Advisory Committee for the UK Medicines and Healthcare products Regulatory Agency Database Research (protocol 17_041). The findings will be presented in peer-reviewed journals and local CPRD researcher meetings.