Incidence of metastatic tumors to ovary (Krukenberg) versus primary ovarian neoplasms associated with colorectal cancer surgery
Bibliographic record
Abstract
Background An ovarian mass in the setting of colorectal cancer (CRC) can be concerning due to the uncertainty of it being metastatic disease or primary ovarian neoplasm, leading to different referral and treatment options. Our objective was to determine the incidence of ovarian metastasis compared to primary ovarian pathology in women diagnosed with CRC. Methods Women aged 18 years or older, diagnosed with CRC in 2014 were included. 806 records were screened for findings of an ovarian mass until 2023. Pathology was determined via resection, biopsy, or imaging with follow-up. Results Forty women (5.0 %) had an ovarian mass; 11 at index surgery and 29 on follow-up. Median age at CRC diagnosis was 62.7 years. The incidence of Krukenberg tumour (KT) was 3.2 % accounting for 65 % of ovarian masses. Approximately 20 % presented with synchronous KTs (n = 5) and 53.8 % had synchronous peritoneal carcinomatosis (n = 14). On follow-up, KTs were found in 72.4 % of the patients (n = 21). The Overall Survival (OS) in the KT group was 7.8 % with median survival of 30.4 months. The median time to developing KTs was 20.8 months with 2-year disease-free survival of 19.2 %. Synchronous KT presentation was the only factor associated with worse OS on univariate and multivariate analysis (HR 7.23, 95 % CI 1.57–33.28, P < 0.05). Conclusion The risk of developing KT in women with CRC is 3.2 %, of which most (72.4 %) present with metachronous disease within 2 years of CRC diagnosis. Initial evaluation by a gastrointestinal tumor group is warranted. Synopsis In this multicenter study involving 806 women diagnosed with colorectal cancer, most ovarian masses that were detected during or following surgery are colorectal metastases and not primary ovarian pathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".