MP64-03 CONTEMPORARY POPULATION-BASED ANALYSIS OF BONE MINERAL DENSITY TESTING IN MEN INITIATING ANDROGEN DEPRIVATION THERAPY FOR PROSTATE CANCER
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: Robotically assisted radical prostatectomy (RARP) has become the most common surgical treatment option for clinically localized prostate cancer in the United States.Controversy continues to exist over the benefits of a robotic approach versus open radical retropubic prostatectomy (RRP).Previous studies have failed to show a difference in oncologic or functional outcomes.Short term quality of life studies have also failed to show a significant difference between the two options.We report data on 15 years of follow up using standardized quality of life questionnaires.METHODS: Survey data was obtained from patients who underwent treatment for clinically localized prostate cancer from August 2002 to December 2005.Patients were matched 2:1 for surgical year, age, preoperative PSA, clinical stage and biopsy Gleason grade.Patients were asked to fill out and return 3 standardized questionnaires sent as a package: SF-12, EORTC QLQ-30 and EPIC-26 SF.Four additional questions were also added to our survey regarding the use of erectile therapies and surgical treatments for erectile dysfunction and urinary incontinence.RESULTS: 452 patients completed and returned the survey.This included 156 patients treated with RARP, matched to 296 patients treated by RRP.Response rate was 70%.There were no significant differences in clinicopathologic characteristics between both groups.In review of all three questionnaires, a significant difference was only noted in the number of pads/diapers required in the past 4 weeks (p[0.04).The overall rate of patients reporting surgical treatments for incontinence (9/452, 2.1%) and erectile dysfunction (3/452, 0.7%) were very low with no significant difference between RARP and RRP.CONCLUSIONS: There continues to exist few differences in quality of life measures between RARP and RRP at long term follow up.Key components of the survey involving sexual function and continence showed no significant difference at 15 years follow up.This represents one of the longest follow up periods to date comparing these treatment modalities.All additional variables regarding multiple facets of quality of life measures showed no long term differences between both subgroups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".