Risk of Premature Menopause After Treatment for Hodgkin’s Lymphoma
Bibliographic record
Abstract
BACKGROUND: Modern treatment of Hodgkin's lymphoma (HL) has transformed its prognosis but causes late effects, including premature menopause. Cohort studies of premature menopause risks after treatment have been relatively small, and knowledge about these risks is limited. METHODS: Nonsurgical menopause risk was analyzed in 2127 women treated for HL in England and Wales at ages younger than 36 years from 1960 through 2004 and followed to 2003 through 2012. Risks were estimated using Cox regression, modified Poisson regression, and competing risks. All statistical tests were two-sided. RESULTS: During follow-up, 605 patients underwent nonsurgical menopause before age 40 years. Risk of premature menopause increased more than 20-fold after ovarian radiotherapy, alkylating chemotherapy other than dacarbazine, or BEAM (bis-chloroethylnitrosourea [BCNU], etoposide, cytarabine, melphalan) chemotherapy for stem cell transplantation, but was not statistically significantly raised after adriamycin, bleomycin, vinblastine, dacarbazine (ABVD). Menopause generally occurred sooner after ovarian radiotherapy (62.5% within five years of ≥5 Gy treatment) and BEAM (50.9% within five years) than after alkylating chemotherapy (24.2% within five years of ≥6 cycles), and after treatment at older than at younger ages. Cumulative risk of menopause by age 40 years was 81.3% after greater than or equal to 5Gy ovarian radiotherapy, 75.3% after BEAM, 49.1% after greater than or equal to 6 cycles alkylating chemotherapy, 1.4% after ABVD, and 3.0% after solely supradiaphragmatic radiotherapy. Tables of individualized risk information for patients by future period, treatment type, dose and age are provided. CONCLUSIONS: Patients treated with HL need to plan intended pregnancies using personalized information on their risk of menopause by different future time points.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".