Should surgeon specific factors be incorporated in prediction modeling? <ul><li>Andrew J. Vickers </li></ul><ul><li>Associ...
Does a patient ’s chance of cure depend on the surgeon? <ul><li>Oncologic surgery is highly skilled </li></ul><ul><li>It i...
Complications after radical prostatectomy Volume -------------- Outcome Low Medium High Very High Postoperative complicati...
 
The learning curve for open radical prostatectomy
Organ confined Non-organ confined
 
Patient characteristics laparoscopic learning curve Prior cases (surgeon experience) before incident case < 50 50-99 100-2...
Principal analysis <ul><li>After adjustment for stage, grade, PSA,  highly significant relationship between surgeon experi...
Open RP Laparoscopic RP
What about variation of functional outcomes? <ul><li>1,333 patients treated with radical prostatectomy at MSKCC 1999 - 200...
 
 
Surgeon experience affects predictiveness Locally advanced disease Gleason 8 Gleason 7 PSA AUC 0.750 for patients treated ...
Surgeon specific factors and prediction modelling <ul><li>Already a problem! </li></ul><ul><li>Kattan nomogram based on pa...
Application of models created in academic centers <ul><li>An issue of  calibration  not  discrimination </li></ul><ul><li>...
CAPRA vs. Stephenson
 
Prediction models and surgeon specific factors <ul><li>So…. </li></ul><ul><li>Should surgeon be a variable in prediction m...
Nomogram including surgeon experience
Nomogram including surgeon experience: AUC 0.812 vs. 0.811
Radical prostatectomy outcomes collaboration
Inclusion of surgeon factors in prediction models <ul><li>My best guess?: </li></ul><ul><ul><li>High vs. low volume surgeo...
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NY Prostate Cancer Conference - A. Vickers - Session 7: Should surgeon specific factors be incorporated in prediction modeling?

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Transcript of "NY Prostate Cancer Conference - A. Vickers - Session 7: Should surgeon specific factors be incorporated in prediction modeling?"

  1. 1. Should surgeon specific factors be incorporated in prediction modeling? <ul><li>Andrew J. Vickers </li></ul><ul><li>Associate Attending Research Methodologist </li></ul><ul><li>Memorial Sloan-Kettering Cancer Center </li></ul>
  2. 2. Does a patient ’s chance of cure depend on the surgeon? <ul><li>Oncologic surgery is highly skilled </li></ul><ul><li>It is plausible that the outcome of surgery depends on the surgeon </li></ul><ul><ul><li>More experienced surgeons better than less experienced surgeons? </li></ul></ul><ul><ul><li>Some surgeons better than others with equivalent levels of experience? </li></ul></ul>
  3. 3. Complications after radical prostatectomy Volume -------------- Outcome Low Medium High Very High Postoperative complications 32% 31% 30% 26% Urinary complications 28% 26% 27% 20%
  4. 5. The learning curve for open radical prostatectomy
  5. 6. Organ confined Non-organ confined
  6. 8. Patient characteristics laparoscopic learning curve Prior cases (surgeon experience) before incident case < 50 50-99 100-249 250-1000 p n 793 611 946 2352 PSA (ng / ml) 6.9 (5.0, 10.0) 6.8 (5.0, 9.8) 7 (5.1, 10.3) 5.9 (4.3, 8.5) 0.11 Age at RP 64 (59, 68) 64 (59, 68) 63 (58, 68) 61 (56, 66) 0.036 Path. Gleason 0.4 ≤ 6 365 (46%) 255 (42%) 439 (46%) 1024 (44%) 7 375 (47%) 311 (51%) 423 (45%) 1180 (50%) ≥ 8 53 (7%) 45 (7%) 84 (9%) 148 (6%) Non-organ confined 247 (31%) 205 (34%) 304 (32%) 612 (26%) 0.3
  7. 9. Principal analysis <ul><li>After adjustment for stage, grade, PSA, highly significant relationship between surgeon experience & cancer recurrence (p=0.005) </li></ul><ul><li>Risk of recurrence at five years: </li></ul><ul><ul><li>17% for surgeon with 10 prior cases </li></ul></ul><ul><ul><li>9% for surgeon with 750 prior cases </li></ul></ul><ul><li>Absolute risk difference of 8.0% NNT 13 </li></ul>
  8. 10. Open RP Laparoscopic RP
  9. 11. What about variation of functional outcomes? <ul><li>1,333 patients treated with radical prostatectomy at MSKCC 1999 - 2007 </li></ul><ul><li>Evaluated for urinary and erectile function one year after surgery </li></ul><ul><ul><ul><li>Urinary function: no pads </li></ul></ul></ul><ul><ul><ul><li>Erectile function: full erections sufficient for sexual activity </li></ul></ul></ul>
  10. 14. Surgeon experience affects predictiveness Locally advanced disease Gleason 8 Gleason 7 PSA AUC 0.750 for patients treated by surgeons with <50 cases 0.849 for patients treated by surgeons with >500 cases
  11. 15. Surgeon specific factors and prediction modelling <ul><li>Already a problem! </li></ul><ul><li>Kattan nomogram based on patients treated by a leading surgeon at a major academic center </li></ul>
  12. 16. Application of models created in academic centers <ul><li>An issue of calibration not discrimination </li></ul><ul><li>Patients with organ confined disease will do better no matter who they see </li></ul><ul><li>Absolute risk of recurrence varies ten fold by experience: </li></ul><ul><ul><li>Inexperienced surgeon: ~15% risk </li></ul></ul><ul><ul><li>Experienced surgeon: ~1% risk </li></ul></ul>
  13. 17. CAPRA vs. Stephenson
  14. 19. Prediction models and surgeon specific factors <ul><li>So…. </li></ul><ul><li>Should surgeon be a variable in prediction models? </li></ul>
  15. 20. Nomogram including surgeon experience
  16. 21. Nomogram including surgeon experience: AUC 0.812 vs. 0.811
  17. 22. Radical prostatectomy outcomes collaboration
  18. 23. Inclusion of surgeon factors in prediction models <ul><li>My best guess?: </li></ul><ul><ul><li>High vs. low volume surgeon </li></ul></ul><ul><li>Will it help prediction? </li></ul><ul><ul><li>I don’t know </li></ul></ul><ul><li>Will it help education? </li></ul><ul><ul><li>Certainly! </li></ul></ul>

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