Prospective cohort study comparing quality of life and sexual health outcomes between women undergoing robotic, laparoscopic and open surgery for endometrial cancer
Bibliographic record
Abstract
OBJECTIVE: To evaluate patient-reported outcomes (PROs) between women treated by laparoscopic, robotic and open approaches for endometrial cancer. METHODS: Prospective cohort study comparing PRO at baseline, short- (1 and 3 weeks) and long-term (12 and 24 weeks) follow-up postoperatively. Quality of life (QOL) measures were the Functional Assessment of Cancer Therapy (FACT-G), EuroQol Five Dimensions (EQ-5D), and Brief Pain Inventory (BPI). Sexual health measures were the Female Sexual Function Index (FSFI) and the Sexual Adjustment and Body Image Scale for Gynecologic Cancer (SABIS-G). RESULTS: 468 eligible patients (laparotomy = 92, laparoscopy = 152, robotic = 224) were recruited. There were no significant differences between the laparoscopy and robotic groups for any PRO (P > 0.05). At short-term follow-up, patients who underwent minimally invasive surgery (robotic or laparoscopy) had significantly higher FACT-G (P < 0.0001) and EQ-5D (P < 0.0001) scores, with less pain (P = 0.02) and improved pain interference (P = 0.0008), than patients undergoing laparotomy. At long-term follow-up, there were sustained improvements in the FACT-G (P = 0.035) and the health state EQ-5D visual analogue scale (P = 0.022). Surgical approach had no impact on sexual health (P > 0.05); however the mean FSFI score for the entire cohort met clinical cut-offs for sexual dysfunction. CONCLUSION: Minimally invasive approaches result in improved QOL beyond the short-term postoperative period, with benefits noted up to 12 weeks after surgery. This prolonged QOL advantage provides further evidence that MIS should be the standard surgical approach for women with early stage endometrial cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".