Highly Differentiated Follicular Carcinoma of Ovarian Origin: A Systematic Review of the Literature
Bibliographic record
Abstract
(1) Background: Highly differentiated follicular carcinoma of ovarian origin (HDFCO) is an extremely uncommon neoplasm, associated with struma ovarii. There are scarce cases reported in the literature and, subsequently, no reliable conclusions on its pathophysiology, treatment, and prognosis can be drawn. The goal of this study is to enrich the literature on the topic by adding our own experience with a case, and simultaneously accumulate all cases published up to date. (2) Methods: The present review was performed in accordance with the guidelines for systematic reviews and meta-analyses (PRISMA). PubMed (1966-2022), Scopus (2004-2022), and Clinicaltrials.gov databases were screened for relevant articles published up to July 2022. (3) Results: Twenty patients with HDFCO were identified. The included patients were aged 47.15 years (range 24-74). The predominant origin was ovarian (60%) and extraperitoneal spread was confirmed in 15% of the cases. Surgical treatment varied from conservative to radical (35.3% vs. 41.2%, respectively) and the administration of supplementary therapy and thyroidectomy was not universal. Combined thyroidectomy/radioactive iodine therapy was applied in just 62.5% of the reported cases. There was one patient who demonstrated disease recurrence and lives with the disease. No disease related morbidity was reported. (4) Conclusions: HDFCO represents a low-grade malignant tumor, whose rarity does not allow for reliable conclusions. Standard treatment including complete surgical excision and supplementary treatment seems to offer a favorable prognosis in selected cases.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".