Clinicopathological Characteristics and Prognostic Factors in Ovarian Metastases from Right- and Left-Sided Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Secondary tumors of the ovary (STOs) account for 10-25% of all ovarian malignancies, including metastases from primary gynecological tumors. Colorectal cancer (CRC) has been recognized as one of the most common causes of STOs in Western countries. Despite it being well-known that CRC originating from the right versus left side of the colon/rectum differ substantially, there is a paucity of information regarding the effect of the primary tumor sidedness on the clinicopathological characteristics of STOs. METHODS: This retrospective, observational chart review study included patients with histologically confirmed STOs of CRC origin diagnosed between January 2000 and December 2019. The clinicopathological characteristics of STOs originating from left-sided and right-sided CRC were compared. Univariable and multivariable analyses employing elastic net Cox proportional hazard models were used to evaluate potential prognostic factors. Further, the role of imaging methods in STOs diagnostics was evaluated. RESULTS: Fifty-one patients with STOs of colorectal origin were identified. The primary tumor originated in the right and left colon/rectum in 39% and 61% of the cases, respectively. STOs originating from right-sided primary tumors were more frequently bilateral, associated with peritoneal carcinomatosis, had the ovarian surface affected by the tumor, and contained a mucinous component. The independent prognostic factors for overall survival in the whole cohort included: the presence of macroscopic residual disease after cytoreductive surgery, menopausal status, the application of systemic therapy, and the application of targeted therapy. In 54% of cases, the imaging methods failed to determine the laterality of the STOs correctly as compared to pathological reports and/or intraoperative findings. CONCLUSION: STOs originating from left-sided and right-sided CRC show distinct clinicopathological characteristics. Moreover, different metastatic pathways might be employed according to the primary tumor sidedness. Considering the discrepancies between radiological assessment and histopathological findings regarding the laterality of STOs, bilateral adnexectomy should be advised whenever feasible.
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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 | 0.001 | 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) | 0.001 | 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 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".