OBJECTIVE: Recent studies have shown an improvement in prostate cancer diagnosis with the use of 3.0-Tesla magnetic resonance imaging.
We retrospectively assessed the ability of this imaging technique to predict side-specific extracapsular extension of prostate cancer.
METHODS: From October 2007 to August 2011, prostatectomy was carried out in 396 patients after preoperative 3.0-Tesla magnetic resonance imaging. Among these, 132 (primary sample) and 134 patients (validation sample) underwent 12-core prostate biopsy at the National Cancer Center Hospital of Tokyo, Japan, and at other institutions, respectively. In the primary dataset, univariate and multivariate analyses were carried out to predict side-specific extracapsular extension using variables determined preoperatively, including 3.0-Tesla magnetic resonance imaging findings (T2-weighted and diffusion-weighted imaging). A prediction model was then constructed and applied to the validation study sample.
RESULTS: Multivariate analysis identified four significant independent predictors (P < 0.05), including a biopsy Gleason score of ≥8, positive 3.0-Tesla diffusion-weighted magnetic resonance imaging findings, ≥2 positive biopsy cores on each side and a maximum percentage of positive cores ≥31% on each side. The negative predictive value was 93.9% in the combination model with these four predictors, meanwhile the positive predictive value was 33.8%. Good reproducibility of these four significant predictors and the combination model was observed in the validation study sample.
CONCLUSIONS: The side-specific extracapsular extension prediction by the biopsy Gleason score and factors associated with tumor location, including a positive 3.0-Tesla diffusion-weighted magnetic resonance imaging finding, have a high negative predictive value, but a low positive predictive value.
Written by:
Hara T, Nakanishi H, Nakagawa T, Komiyama M, Kawahara T, Manabe T, Miyake M, Arai E, Kanai Y, Fujimoto H. Are you the author?
Urology Division, National Cancer Center Hospital, Tokyo, Japan.
Reference: Int J Urol. 2013 Jan 29. Epub ahead of print.
doi: 10.1111/iju.12091
PubMed Abstract
PMID: 23360237
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