Cancer and Pregnancy in the Post-Roe v. Wade Era: A Comprehensive Review
Bibliographic record
Abstract
Cancer during pregnancy, affecting 1 in 1000 pregnancies, is rising in incidence due to delayed childbearing and improved detection. Common types include breast cancer, melanoma and cervical cancer and Hodgkin's Lymphoma. There are several physiological changes that occur during pregnancy that make its management a challenge to clinicians. Managing it requires multidisciplinary approaches and cautious test interpretation due to overlapping symptoms. To minimize fetal radiation exposure, non-ionizing imaging is preferred, and the interpretation of tumor markers is challenging due to inflammation and pregnancy effects. In terms of treatment, chemotherapy is avoided in the first trimester but may be considered later. Immunotherapy's safety is under investigation, and surgery depends on gestational age and cancer type. Ethical and legal concerns are growing, especially with changes in U.S. abortion laws. Access to abortion for medical reasons is vital for pregnant cancer patients needing urgent treatment. Maternal outcomes may depend on the type of cancer as well as chemotherapy received but, in general, they are similar to the non-pregnant population. Fetal outcomes are usually the same as the general population with treatment exposure from the second trimester onwards. Fertility preservation may be an important component of the treatment discussion depending on the patient's wishes, age and type of treatment. This article addresses the complicated nature of a diagnosis of cancer in pregnancy, touching upon the known medical literature as well as the ethical-legal implications of such a diagnosis, whose importance has increased in the light of recent judicial developments.
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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) | 0.003 | 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 | 0.001 |
| 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".