Overall and progression-free survival in endometrial carcinoma: A single-center retrospective study of patients treated between 2000-2018
Bibliographic record
Abstract
BACKGROUND: Investigating survival in endometrial cancer (EC) is crucial to determine the effectiveness of overall management as it will reflect on the level of care provided among this population. OBJECTIVE: The study was conducted to analyze the overall survival (OS) and progression-free survival (PFS) in treated endometrial carcinoma and to determine the associated predictors. DESIGN: Retrospective SETTING: Department of obstetrics and gynecology in university tertiary hospital PATIENTS AND METHODS: Baseline demographic and clinical data, tumor characteristics and perioperative and outcome data were collected from consecutive patients treated for EC between 2000 and 2018. Kaplan-Meier method and multivariate Cox regression were used to analyze factors and predictors of OS and PFS. MAIN OUTCOME MEASURES: OS, PFS and prognostic factors SAMPLE SIZE: 200 RESULT: Endometrioid type was the most common type accounting for 78.5% of the cases, followed by papillary serous carcinoma (18.5%). At diagnosis, 21.5% were stage III, and 12.0% were stage IV. Invasiveness features showed involvement of the myometrium (96.5%), lymph vessels (36.5%), cervix stroma (18.5%), lower segment (22.0%), and parametrium (7.0%). The majority of patients had open surgery (80.0%), while 11.5% and 7.0% had laparoscopy and robotic surgery, respectively. Staging and debulking were performed in 89.0% of patients, and 12.5% of patients had residual disease of more than 2 cm. The mean OS and PFS were 104.4 (95% CI=91.8–117.0) months and 96.8 (95% CI=83.9–109.7) months, respectively. The 5-year OS and PFS were 62.5% and 46.9%, respectively. The majority of the factors we assessed were significantly associated with OS or PFS. However, reduced OS was independently associated age ≥60 years (hazard ratio [HR]=1.99, P =.010), papillary serous carcinoma (HR=2.35, P =.021), and residual disease (HR=3.84, P =.007); whereas PFS was predicted by age ≥60 years (HR=1.87, P =.014) and residual disease (HR=3.22, P =.040). CONCLUSION: There is a need for a national strategy to tackle the growing burden of EC, by identifying the locally-specific incidence, delayed diagnosis and survival outcome. LIMITATIONS: This was a single-center study conducted at a tertiary center, which may question the generalizability of the findings, as the sample may be biased by overrepresentation with patients who were diagnosed at an advanced stage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".