Health-related quality of life in robotic versus open radical prostatectomy
Bibliographic record
Abstract
INTRODUCTION: It is unclear whether health-related quality of life (HRQoL) outcomes are superior in robot-assisted radical prostatectomy (RARP) compared to open prostatectomy (ORP). METHODS: We retrospectively analyzed records from men who received ORP or RARP at our institution between January 2009 and December 2012. Patients completed a demographics questionnaire and the Patient-Oriented Prostate Utility Scale (PORPUS), a validated disease-specific HRQoL instrument prior to surgery and every 3 months up to 15 months after surgery. RESULTS: In total, 974 men met the inclusion criteria (643 ORP and 331 RARP patients). At baseline, RARP patients were significantly younger (p < 0.001), had lower body mass index (BMI) (p < 0.001), lower preoperative prostate-specific antigen (PSA) (p < 0.001), fewer comorbidities (p < 0.004), and higher baseline PORPUS scores (p = 0.024). On follow-up, unadjusted PORPUS scores were significantly higher in the RARP group at each point. On multivariable analysis adjusting for age, ORP versus RARP procedure, Gleason score, BMI, first PSA, comorbidity, ethnicity, and baseline PORPUS scores, PORPUS score was higher for the RARP group at 3 months (p = 0.038) and 9 months (p = 0.037), but not at 6, 12, and 15 months (p = 0.014). No difference met pre-defined thresholds of clinical significant. CONCLUSIONS: Though unadjusted HRQoL outcomes appeared improved with RARP compared to ORP differences, adjusted differences were seen at only 2 of 5 postoperative time points, and did not meet pre-defined thresholds of clinical significance. Further randomized trials are needed to assess whether one treatment option provides consistently better HRQoL outcomes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".