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Effect of Clinical Parameters on Risk of Death from Cancer after Radical Prostatectomy in Men with Localized and Locally Advanced Prostate Cancer
SIMPLE SUMMARY: Since prostate cancer-related deaths hold the third most common cause worldwide in men, it is important to acknowledge clinical predictors leading to such high cancer-related mortality rates. The study aimed to assess these predictors and to identify patient groups with increased ris...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032251/ https://www.ncbi.nlm.nih.gov/pubmed/35454938 http://dx.doi.org/10.3390/cancers14082032 |
Sumario: | SIMPLE SUMMARY: Since prostate cancer-related deaths hold the third most common cause worldwide in men, it is important to acknowledge clinical predictors leading to such high cancer-related mortality rates. The study aimed to assess these predictors and to identify patient groups with increased risk of cancer-specific mortality. This retrospective cohort study included patients who underwent radical prostatectomy due to localized and locally advanced prostate cancer. We analyzed cancer-specific and other-cause mortality rates regarding the most important factors, such as Grade Group, pathological stage, patient’s age, and various combinations of these factors. The presented long-term mortality plots can be useful in daily practice and help clinicians identify patient cohorts with the most aggressive prostate cancer, who could benefit from more intensive or novel multimodal treatment strategies. ABSTRACT: Background: The study aimed to assess predictors and to identify patients at increased risk of prostate-cancer-specific mortality (CSM) after radical prostatectomy (RP). Methods: A total of 2421 men with localized and locally advanced PCa who underwent RP in 2001–2017 were included in the study. CSM predictors were assessed using multivariate competing risk analysis. Death from other causes was considered a competing event. Cumulative CSM and other-cause mortality (OCM) were calculated in various combinations of predictors. Results: During the median 8 years (interquartile range 4.4–11.7) follow-up, 56 (2.3%) of registered deaths were due to PCa. Cumulative 10 years CSM and OCM was 3.6% (95% CI 2.7–4.7) and 15.9% (95% CI 14.2–17.9), respectively. The strongest predictors of CSM were Grade Group 5 (GG5) (hazard ratio (HR) 19.9, p < 0.0001), lymph node invasion (HR 3.4, p = 0.001), stage pT3b-4 (HR 3.1, p = 0.009), and age (HR 1.1, p = 0.0007). In groups created regarding age, stage, and GG, cumulative 10 years CSM ranged from 0.4–84.9%, whereas OCM varied from 0–43.2%. Conclusions: CSM after RP is related to GGs, pathological stage, age, and combinations of these factors, whereas other-cause mortality is only associated with age. Created CSM and OCM plots can help clinicians identify patients with the most aggressive PCa who could benefit from more intensive or novel multimodal treatment strategies. |
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