Neoadjuvant Chemotherapy in Pregnant Patients with Cervical Cancer: A Monocentric Retrospective Study
Bibliographic record
Abstract
BACKGROUND: To date, little and discordant data still exists on the management of cervical cancer (CC) during pregnancy. In this paper, we report our experience of the treatment of these patients analyzing the oncologic, obstetric, and neonatal outcomes. METHODS: Between January 2010 and December 2021, 13 patients were diagnosed with CC during pregnancy. All patients underwent platinum-based neoadjuvant chemotherapy (NACT) and 11/13 patients underwent a cesarean radical hysterectomy (CRH). RESULTS: All 13 patients were diagnosed with squamous-cell carcinoma, FIGO-2018 stage between IB2-IIIC1. The majority of patients had a partial (61.5%) or complete (15.4%) response to NACT. Most patients had a regular course of pregnancy and the obstetric complications observed were gestational diabetes mellitus in 23.1% and IUGR in 15.4% of cases. CRH was performed in the absence of major complications. Only 2 patients (15.4%) had disease recurrence and only 1 patient (7.7%) died of disease. All children are currently healthy. At birth, we observed mainly prematurity-related complications (38.5% respiratory distress syndrome and 7.7% neonatal jaundice) and only a case of congenital malformation (hypospadias). In our pediatric population, we reported a case of malignancy (acute myeloid leukemia). CONCLUSION: NACT seems to be safe and efficacious in controlling tumor burden during pregnancy. CRH following NACT appears to be feasible, avoiding repeated surgery and treatment delays. This approach is also reasonably safe from a maternal, obstetric, and neonatal point of view.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".