Predicting prostate cancer-specific outcome after radical prostatectomy among men with very high-risk cT3b/4 PCa: a multi-institutional outcome study of 266 patients

BACKGROUND The value of radical prostatectomy (RP) as an approach for very high-risk prostate cancer (PCa) patients is controversial. To examine the risk of 10-year cancer-specific mortality (CSM) and other-cause mortality (OCM) according to clinical and pathological characteristics of very high-risk cT3b/4 PCa patients treated with RP as the primary treatment option. METHODS In a multi-institutional cohort, 266 patients with very high-risk cT3b/4 PCa treated with RP were identified. All patients underwent RP and pelvic lymph-node dissection. Competing-risk analyses assessed 10-year CSM and OCM before and after stratification for age and Charlson comorbidity index (CCI). RESULTS Overall, 34 (13%) patients died from PCa and 73 (28%) from OCM. Ten-year CSM and OCM rates ranged from 5.6% to 12.9% and from 10% to 38%, respectively. OCM was the leading cause of death in all subgroups. Age and comorbidities were the main determinants of OCM. In healthy men, CSM rate did not differ among age groups (10-year CSM rate for ⩽64, 65-69 and ⩾70 years: 16.2%, 11.5% and 17.1%, respectively). Men with a CCI ⩾1 showed a very low risk of CSM irrespective of age (10-year CSM: 5.6-6.1%), whereas the 10-year OCM rates increased with age up to 38% in men ⩾70 years. CONCLUSION Very high-risk cT3b/4 PCa represents a heterogeneous group. We revealed overall low CSM rates despite the highly unfavorable clinical disease. For healthy men, CSM was independent of age, supporting RP even for older men. Conversely, less healthy patients had the highest risk of dying from OCM while sharing very low risk of CSM, indicating that this group might not benefit from an aggressive surgical treatment. Outcome after RP as the primary treatment option in cT3b/4 PCa patients is related to age and comorbidity status.

Stratification of high-risk prostate cancer into prognostic categories: a European multi-institutional study

BACKGROUND High-risk prostate cancer (PCa) is an extremely heterogeneous disease. A clear definition of prognostic subgroups is mandatory. OBJECTIVE To develop a pretreatment prognostic model for PCa-specific survival (PCSS) in high-risk PCa based on combinations of unfavorable risk factors. DESIGN, SETTING, AND PARTICIPANTS We conducted a retrospective multicenter cohort study including 1360 consecutive patients with high-risk PCa treated at eight European high-volume centers. INTERVENTION Retropubic radical prostatectomy with pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Two Cox multivariable regression models were constructed to predict PCSS as a function of dichotomization of clinical stage (< cT3 vs cT3-4), Gleason score (GS) (2-7 vs 8-10), and prostate-specific antigen (PSA; ≤ 20 ng/ml vs > 20 ng/ml). The first "extended" model includes all seven possible combinations; the second "simplified" model includes three subgroups: a good prognosis subgroup (one single high-risk factor); an intermediate prognosis subgroup (PSA >20 ng/ml and stage cT3-4); and a poor prognosis subgroup (GS 8-10 in combination with at least one other high-risk factor). The predictive accuracy of the models was summarized and compared. Survival estimates and clinical and pathologic outcomes were compared between the three subgroups. RESULTS AND LIMITATIONS The simplified model yielded an R(2) of 33% with a 5-yr area under the curve (AUC) of 0.70 with no significant loss of predictive accuracy compared with the extended model (R(2): 34%; AUC: 0.71). The 5- and 10-yr PCSS rates were 98.7% and 95.4%, 96.5% and 88.3%, 88.8% and 79.7%, for the good, intermediate, and poor prognosis subgroups, respectively (p = 0.0003). Overall survival, clinical progression-free survival, and histopathologic outcomes significantly worsened in a stepwise fashion from the good to the poor prognosis subgroups. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS This study presents an intuitive and easy-to-use stratification of high-risk PCa into three prognostic subgroups. The model is useful for counseling and decision making in the pretreatment setting.

Structural and Institutional Determinants of Influence Reputation: A Comparison of Collaborative and Adversarial Policy Networks in Decision Making and Implementation

The central assumption in the literature on collaborative networks and policy networks is that political outcomes are affected by a variety of state and nonstate actors. Some of these actors are more powerful than others and can therefore have a considerable effect on decision making. In this article, we seek to provide a structural and institutional explanation for these power differentials in policy networks and support the explanation with empirical evidence. We use a dyadic measure of influence reputation as a proxy for power, and posit that influence reputation over the political outcome is related to vertical integration into the political system by means of formal decision-making authority, and to horizontal integration by means of being well embedded into the policy network. Hence, we argue that actors are perceived as influential because of two complementary factors: (a) their institutional roles and (b) their structural positions in the policy network. Based on temporal and cross-sectional exponential random graph models, we compare five cases about climate, telecommunications, flood prevention, and toxic chemicals politics in Switzerland and Germany. The five networks cover national and local networks at different stages of the policy cycle. The results confirm that institutional and structural drivers seem to have a crucial impact on how an actor is perceived in decision making and implementation and, therefore, their ability to significantly shape outputs and service delivery.