Serum Anti-Müllerian Hormone Levels and Risk of Premature Ovarian Insufficiency in Female Childhood Cancer Survivors: Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Female childhood cancer survivors (CCS) might have impaired ovarian reserves, especially after alkylating agents or radiotherapy. The purpose of this systematic review and network meta-analysis is to evaluate the role of serum anti-Müllerian hormone (AMH) for ovarian reserve screening and the risk of premature ovarian insufficiency (POI) according to the subtype of childhood cancer. (2) Methods: PRISMA-NMA guidelines were followed. We carried out a network meta-analysis based on a random effects model for mixed multiple treatment comparisons to rank childhood cancers effects on fertility by surface under the cumulative ranking curve (SUCRA). Studies were selected only if they had an age-matched control group. Quality assessment was performed using Newcastle-Ottawa Scale. The co-primary outcomes were mean AMH levels and the incidence of POI. (3) Results: A total of 8 studies (1303 participants) were included. Women treated for a neuroblastoma during infancy were more likely to be ranked first for impaired AMH levels (SUCRA = 65.4%), followed by mixed CCS (SUCRA = 29.6%). The greatest rates of POI were found in neuroblastoma survivors (SUCRA = 42.5%), followed by acute lymphoid leukemia (SUCRA = 26.3%) or any other neoplasia (SUCR A = 20.5%). (4) Conclusions: AMH represents a trustworthy approach for ovarian reserve screening. Direct and indirect comparisons found no differences in mean AMH levels and POI risk between subtypes of CCS and healthy controls. SUCRA analysis showed that female neuroblastoma survivors were more at risk for reduced serum AMH levels and increased risk of POI.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".