ArticleTranslational andrology and urology2021
Nomogram predicting survival to assist decision-making of radical prostatectomy in patients with metastatic prostate cancer.
Article in Translational andrology and urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
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- A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study.Frontiers in public health · 2022Trial
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRadical prostatectomy (RP) has heterogeneous effects on survival of patients with metastatic prostate cancer (mPCa). A reliable model to predict risk of cancer-specific mortality (CSM) and the potential benefit derived from RP is needed.
methodsPatients diagnosed with mPCa were identified using the Surveillance, Epidemiology, and End Results database (2004-2015) and categorized in RP versus nonlocal treatment (NLT). Based on the Fine and Gray competing risks model in 8,463 NLT patients, a nomogram was created to predict CSM in mPCa patients. Decision tree analysis was then utilized for patient stratification. The effect of RP was evaluated among 3 different subgroups.
resultsA total of 8,863 patients were identified for analysis. Four hundred (4.5%) patients received RP. The 5-year cumulative incidence of CSM was 52.4% for the entire patients. Based on nomogram scores, patients were sorted into three risk groups using decision tree analysis. In the low- and intermediate-risk group, RP was found to be significantly correlated with a 21.7% risk reduction of 5-year CSM, and 25.0% risk reduction of 5-year CSM, respectively, whereas RP was not associated with CSM in high-risk group (hazard ratio =0.748, 95% confidence interval 0.485-1.150; P=0.190).
conclusionsWe developed a novel nomogram and corresponding patient stratification predicting CSM in mPCa patients. A newly identified patient subgroup with low-, and intermediate-risk of CSM might benefit more from RP. These results should be further validated and improved by ongoing prospective trials.
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