Association between diabetes mellitus and subsequent ovarian cancer in women
Bibliographic record
Abstract
Epidemiologic studies have suggested that diabetes mellitus (DM) might be associated with risk of ovarian cancer; however, the results have been inconsistent. The aim of this study was to determine the relationship between DM and the incidence of ovarian cancer on the basis of cohort studies.Relevant studies from PubMed, Embase, and the Cochrane Library until September 2016 were collected. The summary risk ratio (RR) was used as the effect measure in a random effects model. Sensitivity analysis, subgroup analysis, and calculation of publication bias were conducted.Thirteen articles including 14 cohorts comprising a total of 3708, 313 women and reporting 5534 cases of ovarian cancer were included. The summary RR suggested that patients with DM had a higher risk of ovarian cancer than patients without DM (RR: 1.19; 95% confidence interval: 1.06-1.34; P = .004), and no evidence of publication bias was found. The subgroup analysis indicated a higher incidence of ovarian cancer in patients with DM in studies published after 2010, studies not conducted in Europe or the United States, studies that did not adjust for body mass index or smoking status, and studies with lower Newcastle-Ottawa Scale scores.The present findings indicated that DM is a risk factor for ovarian cancer, and future large-scale epidemiologic studies should be performed to evaluate this relation in specific populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".