Micropapillary pattern in serous borderline ovarian tumor and the risk of extraovarian localization of low-grade serous carcinoma (‘invasive implants’): A systematic review and meta-analysis
Bibliographic record
Abstract
In serous borderline ovarian tumor (SBOT), a micropapillary (MP) pattern has been considered analogous to intraepithelial low-grade serous carcinoma (LGSC). On this account, it is reasonable to hypothesize that MP-SBOT is more likely to be associated with extraovarian LGSC localizations (also referred to as 'invasive implants') compared to conventional SBOT. The aim of this study was to investigate the potential association between a MP pattern and invasive implants in SBOT. Three electronic databases were searched from 2000 (year of publication of histological criteria for MP-SBOT) to 2023 for all studies assessing the presence of invasive implants in conventional SBOT vs MP-SBOT. Exclusion criteria were sample size <20, overlapping patient data, reviews. The association between MP pattern and invasive implants was assessed by using odds ratio (OR), with a significant p-value<0.05. Seven studies with 1,766 SBOT were included, out of which 205 (11.5%) were MP-SBOT, 462 (26%) had implants and 62 (3.5%) had invasive implants. A MP pattern was significantly associated with the presence of invasive implants (OR=7.33, 95% CI 3.61-14.86) (p<0.001), with low heterogeneity among studies (I 2 =28%). In conclusion, a MP pattern in SBOT is significantly associated with extraovarian LGSC localization, supporting that it represents intraepithelial LGSC.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".