[Meta-analysis of prognosis of ovarian preserving in young patients with early endometrial cancer].
Bibliographic record
Abstract
OBJECTIVE: To discuss the effect of preserving ovaries on the prognosis of young early endometrial cancer patients. METHODS: Searched English and Chinese databases by computors, including Cochrane library, Embase, PubMed, Web of Science, China National Knowledge Internet (CNKI), data base of Wanfang, China Science and Technology Journal (CSTJ) , and also relevant journals and magazines by hand. Retrieval time from January 1996 to March 2016. In accordance with the inclusion criteria, two independent investigators screened the studies and extracted the relevant data respectively. Then evaluated the quality of included studies. Finally, conducted the meta-analysis with RevMan 5.3 software from cochrane collaboration network, in which heterogeneity test of enrolled studies firstly was completed and combined analysis with effect models according to the heterogeneity secondary. In the light of the result, effect of remaining ovaries on the prognosis (5-year recurrence rate and 5-year overall survival rate) of young early endometrial cancer patients was determined. RESULTS: Ten trials were included. All of them were cohort studies, a total of 5 299 patients, in which 916 patients' ovaries were remained. Quality assessment of all 10 studies were based on Newcastle-Ottawa Scale (NOS) scale. All of the studies enrolled were of high quality with a score of ≥7. After quality assessment,all studies illustrated the higher the quality. Meta-analysis showed that there was no statistically significant difference between who had ovarian preservation and without preservation in terms of 5-year overall survival rate [96.00% (863/899) vs 96.51% (3 736/3 871); RR=1.00, 95%CI: 0.99-1.02, P=0.792] and the 5-year recurrence rate [2.58% (7/271) vs 4.43% (51/1 150); RR=1.01, 95%CI: 0.46-2.22, P=0.986]. CONCLUSION: Ovarian preservation in young early stage patients of endometrial cancer could not effect the 5-year overall survival rateand the 5-year recurrence rate.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.041 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".