| Literature DB >> 25578934 |
Insang Hwang, Donghoon Lim, Young Beom Jeong, Seung Chol Park, Jun Hwa Noh, Dong Deuk Kwon, Taek Won Kang1.
Abstract
Only 54% of prostate cancer cases in Korea are localized compared with 82% of cases in the US. Furthermore, half of Korean patients are upgraded after radical prostatectomy (41.6%-50.6%). We investigated the risk factors for upgrading and/or upstaging of low-risk prostate cancer after radical prostatectomy. We retrospectively reviewed the medical records of 1159 patients who underwent radical prostatectomy at five hospitals in Honam Province. Preoperative data on standard clinicopathological parameters were collected. The radical prostatectomy specimens were graded and staged and we defined a "worsening prognosis" as a Gleason score ≥ 7 or upstaging to ≥ pT3. Multivariate logistic regression models were used to assess factors associated with postoperative pathological upstaging. Among the 1159 patients, 324 were classified into the clinically low-risk group, and 154 (47.5%) patients were either upgraded or upstaged. The multivariable analysis revealed that the preoperative serum prostate-specific antigen level (odds ratio [OR], 1.131; 95% confidence interval [CI], 1.007-1.271; P= 0.037), percent positive biopsy core (OR: 1.018; 95% CI: 1.002-1.035; P= 0.032), and small prostate volume (≤30 ml) (OR: 2.280; 95% CI: 1.351-3.848; P= 0.002) were predictive of a worsening prognosis. Overall, 47.5% of patients with low-risk disease were upstaged postoperatively. The current risk stratification criteria may be too relaxed for our study cohort.Entities:
Mesh:
Substances:
Year: 2015 PMID: 25578934 PMCID: PMC4577596 DOI: 10.4103/1008-682X.143751
Source DB: PubMed Journal: Asian J Androl ISSN: 1008-682X Impact factor: 3.285
Baseline characteristics of the patient population
Comparison of GS upgrading, upstaging and worsening prognosis
Univariate and multivariable analysis for predicting of GS upgrading
Univariate and multivariable analysis for predicting pathological upstaging
Univariate and multivariable analysis for predicting a worsening prognosis