Clinical challenges of glioma and pregnancy: a systematic review
Bibliographic record
Abstract
INTRODUCTION: This review aims to summarize challenges in clinical management of concomitant gliomas and pregnancy and provides suggestions for this management based on current literature. METHODS: PubMed and Embase databases were systematically searched for studies on glioma and pregnancy. Observational studies and articles describing expert opinions on clinical management were included. The strength of evidence was categorized as arguments from observational studies, consensus in expert opinions, or single expert opinions. Risk of bias was assessed by the Newcastle-Ottawa Scale (NOS). RESULTS: 27 studies were selected, including 316 patients with newly diagnosed (n = 202) and known (n = 114) gliomas during pregnancy. The median sample size was 6 (range 1-65, interquartile range 1-9). Few recommendations originated from observational studies; the remaining arguments originated from consensus in expert opinions. CONCLUSION: Findings from observational studies of adequate quality include (1) There is no known effect of pregnancy on survival in low-grade glioma patients; (2) Pregnancy can provoke clinical deterioration and tumor growth on MRI; (3) In stable women at term, there is no benefit of cesarean section over vaginal delivery, with respect to adverse events in mother or child. Unanswered questions include when pregnancy should be discouraged, what best monitoring schedule is for both mother and fetus, and if and how chemo- and radiation therapy can be safely administered during pregnancy. A multicenter individual patient level meta-analysis collecting granular information on clinical management and related outcomes is needed to provide scientific evidence for clinical decision-making in pregnant glioma patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".