TP53 as a Diagnostic Aid in the Distinction of Ovarian Mucinous Borderline Tumors From Mucinous Carcinoma
Bibliographic record
Abstract
Ovarian mucinous borderline tumors (MBTs) are clinically managed as benign neoplasms while the management of ovarian mucinous carcinomas (MC) is dependent on tumor stage. Despite the standardization of sampling of ovarian mucinous neoplasms, limited interobserver reproducibility between MBT and MC persists. Based on our recent finding that abnormal TP53 expression is associated with unfavorable outcome in MBT, we hypothesized that TP53 status might improve the reproducible distinction of MBT from MC. A virtual slide set of 85 consecutive ovarian mucinous neoplasms received at a single institution, with each case represented by 3 full sections, were reviewed by 3 pathologists in 2 iterations. The initial assessment was based solely on morphologic review, while the second iteration was performed with knowledge of TP53 status. The reproducibility of a trinary categorization (MBT, MBT with intraepithelial carcinoma [IEC], MC) significantly improved from a κ of 0.60 based on the initial morphologic assessment to a κ of 0.76 (t-test, P =0.0042) after consideration of TP53 immunohistochemistry (IHC) results. Six out of 85 patients died of disease, and in 2 of them, at least 1 pathologist assessed MBT with IEC and not MC even after integration of TP53 IHC. With the integration of TP53 IHC, substantial interobserver agreement for MBT and MC can be reached, particularly in cases with an uncertain degree of confluent growth. TP53 IHC can also be used to highlight and support the presence of IEC in MBT, however, discordances remained in 2 cases with adverse outcome.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".