Non-Invasive Prenatal Testing Leading to Detection of Asymptomatic Acute Myeloid Leukemia in a 30-Year-Old Patient: A Case Report
Bibliographic record
Abstract
The widely use of non-invasive prenatal testing (NIPT) may lead to accidental findings and the discovery of malignancy in pregnancy, often in asymptomatic patients. Diagnosis of such subclinical malignancy during pregnancy in the asymptomatic patient poses a predicament for both doctor and patient. The risks and benefits of possible treatment for both mother and child have to be weighted, and there is often limited scientific evidence available. We present a case of an abnormal NIPT result, leading to the diagnosis of acute myeloid leukemia (AML) in an asymptomatic pregnant patient. After multiple multidisciplinary meetings and an elaborate shared decision making (SDM) process, a watch and wait strategy was implemented, in contradiction with general treatment recommendations. Following this approach, it was possible to achieve a near term pregnancy before delivery of a healthy baby girl. The patient could subsequently commence treatment of her AML and is still in complete remission after a follow-up of 25 months. Our case report highlights the possibility of watch and wait strategy in selected cases and the importance of multidisciplinary collaboration and SDM, when faced with the accidental finding of AML through NIPT.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".