Pregnancy after Hematopoietic Cell Transplantation: A Report from the Late Effects Working Committee of the Center for International Blood and Marrow Transplant Research (CIBMTR)
Bibliographic record
Abstract
Preservation of fertility after hematopoietic cell transplantation (HCT) can have a significant influence on the quality of life of transplant survivors. We describe 178 pregnancies in HCT recipients that were reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) between 2002 and 2007. There were 83 pregnancies in female HCT recipients and 95 pregnancies in female partners of male HCT recipients. Indications for transplantation included hematologic and other malignancies (N = 99) and nonmalignant disorders (N = 79, of which 75 patients had severe aplastic anemia). The cohort included recipients of autologous HCT (20 women, 13 men), myeloablative (MA) allogeneic HCT (12 women, 50 men), and nonmyeloablative allogeneic HCT (2 women, 2 men). Age at HCT was <20 years for 50% of women and 19% of men. Conditioning regimens included total body irradiation (TBI) in 16% of women and 19% of men; doses were MA in 10% of women and in 16% of men. Live births were reported in 86% of pregnancies in partners of male transplant patients and 85% of pregnancies in female transplant patients, with most pregnancies occurring 5 to 10 years after HCT. We conclude that some HCT recipients can retain fertility, including patients who have received TBI and/or MA conditioning. Young patients undergoing HCT should be counseled both before and after HCT about potential loss of fertility, methods for preserving fertility, and planning for future pregnancy. Fertility and outcomes of pregnancy after HCT need prospective evaluation in large transplant cohorts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".