The Surgical Learning Curve for Prostate Cancer Control After Radical Prostatectomy

作者: A. J. Vickers , F. J. Bianco , A. M. Serio , J. A. Eastham , D. Schrag

DOI: 10.1093/JNCI/DJM060

关键词:

摘要: Background The learning curve for surgery — i.e., improvement in surgical outcomes with increasing surgeon experience remains primarily a theoretical concept; actual curves based on outcome data are rarely presented. We analyzed the prostate cancer recurrence after radical prostatectomy. Methods study cohort included 7765 patients who were treated prostatectomy by one of 72 surgeons at four major US academic medical centers between 1987 and 2003. For each patient, was coded as total number prostatectomies performed before patient ’ s operation. Multivariable survival – time regression models used to evaluate association recurrence, defined serum prostatespecific antigen (PSA) more than 0.4 ng/mL followed subsequent higher PSA level (i.e., bio che mical ), adjustment established clinical tumor characteristics. All P values two-sided. Results steep did not start plateau until had completed approximately 250 prior operations. predicted probabilities 5 years 17.9% (95% confidence interval [CI] = 12.1% 25.6%) 10 operations 10.7% CI 7.1% 15.9%) (difference 7.2%, 95% 4.6% 10.1%; <.001). This finding robust sensitivity analysis; particular, results unaffected if we restricted sample 1995, when stage migration related advent screening appeared largely complete. Conclusions As surgeon’s increases, control improves, presumably because improved technique. Further research is needed examine specific techniques experienced that associated outcomes.

参考文章(22)
Michael W. Kattan, Thomas M. Wheeler, Peter T. Scardino, Postoperative Nomogram for Disease Recurrence After Radical Prostatectomy for Prostate Cancer Journal of Clinical Oncology. ,vol. 17, pp. 1499- 1499 ,(1999) , 10.1200/JCO.1999.17.5.1499
Eric W. Lee, L. J. Wei, David A. Amato, Sue Leurgans, Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations Survival Analysis: State of the Art. pp. 237- 247 ,(1992) , 10.1007/978-94-015-7983-4_14
Joseph Lipscomb, Transcending the Volume–Outcome Relationship in Cancer Care Journal of the National Cancer Institute. ,vol. 98, pp. 151- 154 ,(2006) , 10.1093/JNCI/DJJ055
Colin B. Begg, Elyn R. Riedel, Peter B. Bach, Michael W. Kattan, Deborah Schrag, Joan L. Warren, Peter T. Scardino, Variations in Morbidity after Radical Prostatectomy The New England Journal of Medicine. ,vol. 346, pp. 1138- 1144 ,(2002) , 10.1056/NEJMSA011788
Tom Treasure, The learning curve BMJ. ,vol. 329, pp. 424.1- 424 ,(2004) , 10.1136/BMJ.38176.444745.63
Deborah Schrag, Katherine S. Panageas, Elyn Riedel, Laura D. Cramer, Jose G. Guillem, Peter B. Bach, Colin B. Begg, Hospital and Surgeon Procedure Volume as Predictors of Outcome Following Rectal Cancer Resection Annals of Surgery. ,vol. 236, pp. 583- 592 ,(2002) , 10.1097/00000658-200211000-00008
Phillip L. Ross, Claudia Gerigk, Mithat Gonen, Ofer Yossepowitch, Ilias Cagiannos, Pramod C. Sogani, Peter T. Scardino, Michael W. Kattan, Comparisons of nomograms and urologists' predictions in prostate cancer. Seminars in Urologic Oncology. ,vol. 20, pp. 82- 88 ,(2002) , 10.1053/SURO.2002.32490
Nancy J.O. Birkmeyer, John D. Birkmeyer, Strategies for Improving Surgical Quality — Should Payers Reward Excellence or Effort? The New England Journal of Medicine. ,vol. 354, pp. 864- 870 ,(2006) , 10.1056/NEJMSB053364
Matthew E. Nielsen, Misop Han, Leslie Mangold, Elizabeth Humphreys, Patrick C. Walsh, Alan W. Partin, Stephen J. Freedland, Black Race Does Not Independently Predict Adverse Outcome Following Radical Retropubic Prostatectomy at a Tertiary Referral Center The Journal of Urology. ,vol. 176, pp. 515- 519 ,(2006) , 10.1016/J.JURO.2006.03.100