Desmoid-Type Fibromatosis and Pregnancy
Bibliographic record
Abstract
In Brief Background: Many women who present with desmoid-type fibromatosis (DF) have had a recent pregnancy. Long-term data about disease behavior during and after pregnancy are lacking. Objective: To investigate the possible relationship between DF and pregnancy. Patients and Methods: A cohort of women with DF and pregnancy was identified from 4 sarcoma centers. Four groups were identified: diagnosis during pregnancy (A); diagnosis after delivery (B); DF clinically evident during pregnancy (C); and DF resected before pregnancy (D). Progression/regression rates, recurrence rates after resection, and obstetric outcomes were analyzed. Results: Ninety-two women were included. Forty-four women (48%) had pregnancy-related DF (A + B), whereas 48 (52%) had a history of DF before conception (C + D). Initial treatment was resection in 52%, medical therapy in 4%, and watchful waiting in 43%. Postsurgical relapse rate in A + B was 13%, although progression during watchful waiting was 63%. Relapse/progression in C + D was 42%. After pregnancy, 46% underwent treatment of DF, whereas 54% were managed with watchful waiting. Eventually, only 17% experienced further progression after treatment. Spontaneous regression occurred in 14%. After further pregnancies, only 27% progressed. The only related obstetric event was a cesarean delivery. Conclusions: Pregnancy-related DF has good outcomes. Progression risk during pregnancy is high, but it can be safely managed. DF does not increase obstetric risk, and it should not be a contraindication to future pregnancy. The relation between desmoid-type fibromatosis and pregnancy is analyzed in a large international series. Pregnancy-related fibromatosis showed good outcomes, and conservative nonsurgical management was also feasible. Although disease progression was frequent during and after pregnancy, it could be safely managed in referral centers. No obstetric risks were described.
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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 | 0.003 |
| 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) | 0.002 | 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".