Abstract
Introduction: Preoperative determination of pathologic outcomes in patients with high-risk prostate cancer is challenging because of limitations of existing nomograms. We aimed to assess whether certain preoperative clinical and pathologic characteristics correlate with pathologic outcome in high-risk prostate cancer patients who underwent robot-assisted laparoscopic radical prostatectomy (RALP). Methods: A retrospective evaluation of patients with high-risk disease (prostate-specific antigen [PSA] ≥10ng/dL with high volume disease or Gleason score ≥8) who underwent RALP between December 2004 and September 2008 was conducted. Patients were grouped based on favorable pathology, including organ-confined disease and negative surgical margins (group 1), and unfavorable pathology, including positive surgical margins and extracapsular extension (group 2). Preoperative PSA levels, transrectal ultrasonography findings, and biopsy reports were compared to final pathology data. Results: Of 69 high-risk patients, 37 (54%) had favorable postoperative pathology (group 1) and 32 (46%) had unfavorable pathology (group 2). Mean PSA was 10.0ng/dL (range, 4.1-20.3) (group 1) and 13.8ng/dL (range, 3.1-39.9) (group 2). Mean PSA density was 0.28 (group 1) and 0.41 (group 2). Mean positive biopsy core was 33% (group 1) and 44% (group 2). Differences in PSA levels, PSA density, and percentage of positive cores were statistically significant (p<0.05) between the groups. Bilateral disease and high-grade prostatic intraepithelial neoplasia were not statistically significant (p>0.05). Discussion: Lower PSA level and PSA density, as well as fewer positive biopsy cores, were associated with favorable postoperative pathology. Continued surveillance of these patients will serve to determine whether these findings will assist in predicting which high-risk prostate cancer patients may likely benefit from RALP.
| Original language | English |
|---|---|
| Pages (from-to) | 403-407 |
| Number of pages | 5 |
| Journal | Journal of Endourology |
| Volume | 24 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Mar 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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