Acute Ovarian Failure in the Childhood Cancer Survivor Study
Bibliographic record
Abstract
CONTEXT: Defined as the loss of ovarian function within 5 yr of diagnosis, acute ovarian failure (AOF) is known to develop in a subset of survivors of pediatric and adolescent cancers. Its precise incidence is unknown, and data concerning its risk factors are limited. OBJECTIVE: Our objective was to determine the incidence of and patient/treatment factors associated with AOF in a large cohort of pediatric cancer survivors. DESIGN AND SETTING: We conducted a retrospective cohort, multicenter study. PATIENTS: Female participants from the Childhood Cancer Survivor Study who were greater than 18 yr of age were considered for inclusion. We excluded survivors who received cranial irradiation at doses of more than 3000 cGy, those with hypothalamic/pituitary tumors, and survivors who underwent bilateral oophorectomy. Survivors who reported never menstruating or who had ceased having menses within 5 yr after their cancer diagnosis were considered to have AOF. MAIN OUTCOME: We assessed incidence and risk factors for AOF. RESULTS: Of a total of 3390 eligible survivors, 215 cases (6.3%) developed AOF. Survivors with AOF were older at diagnosis and more likely to have been diagnosed with Hodgkin's lymphoma or to have received abdominal or pelvic radiotherapy than survivors without AOF. Among survivors with AOF, 116 (54%) had received at least 1000-cGy ovarian irradiation. In a multivariable logistic regression model, increasing doses of ovarian irradiation, exposure to procarbazine, and exposure to cyclophosphamide at ages 13-20 yr were independent risk factors for AOF. CONCLUSIONS: AOF develops in a small subset of survivors, especially those treated with at least 1000-cGy ovarian radiation. These results will facilitate patient counseling and selection of candidates for newer fertility preservation techniques.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".