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Female survivors of childhood cancer are at risk for primary ovarian insufficiency (POI), defined as the cessation of gonadal function before the age of 40 years. We aimed to develop and validate models to predict age-specific POI risk among long-term survivors of childhood cancer. To develop models to predict age-specific POI risk for the ages of 21–40 years, we used data from the Childhood Cancer Survivor Study (CCSS). Female survivors aged 18 years or older at their latest follow-up, with self-reported menstrual history information and free of subsequent malignant neoplasms within 5 years of diagnosis, were included. We evaluated models that used algorithms based on statistical or machine learning to consider all predictors, including cancer treatments. Cross-validated prediction performance metrics (eg, area under the receiver operating characteristic curve [AUROC]) were compared to select the best-performing models. For external validation of the models, we used data from 5-year survivors in the St Jude Lifetime Cohort (SJLIFE) with ovarian status clinically ascertained using hormone measurements (menopause defined by follicle stimulating hormone >30 mIU/mL and oestradiol <17 pg/mL) and medical chart or questionnaire review. We also evaluated an SJLIFE-based polygenic risk score for POI among 1985 CCSS survivors with genotype data available. 7891 female CCSS survivors (922 with POI) were included in the development of the POI risk prediction model, and 1349 female SJLIFE survivors (101 with POI) were included in the validation study. Median follow-up from cancer diagnosis was 23·7 years (IQR 18·3–30·0) in CCSS and 15·1 years (10·4–22·9) in SJLIFE. Between the ages of 21 and 40 years, POI prevalence increased from 7·9% (95% CI 7·3–8·5) to 18·6% (17·3–20·0) in CCSS and 7·3% (5·8–8·9) to 14·9% (11·6–19·1) in SJLIFE. Age-specific logistic regression models considering ovarian radiation dosimetry or prescribed pelvic and abdominal radiation dose, along with individual chemotherapy predictors, performed well in CCSS. In the SJLIFE validation, the prescribed radiation dose model performed well (AUROC 0·88–0·95), as did a simpler model that considered any exposures to pelvic or abdominal radiotherapy or alkylators (0·82–0·90). Addition of the polygenic risk predictor significantly improved the average positive predictive value (from 0·76 [95% CI 0·63–0·89] to 0·87 [0·80–0·94]; p=0·029) among CCSS survivors treated with ovarian radiation and chemotherapy. POI risk prediction models using treatment information showed robust prediction performance in adult survivors of childhood cancer. Canadian Institutes of Health Research, US National Cancer Institute. [ABSTRACT FROM AUTHOR]

Background: Treatment outcomes among survivors of cancer diagnosed during adolescence and early young adulthood have not been characterised independently of survivors of cancers diagnosed during childhood. We aimed to describe chronic health conditions and all-cause and cause-specific mortality among survivors of early-adolescent and young adult cancer.Methods: The Childhood Cancer Survivor Study (CCSS) is a retrospective cohort study with longitudinal follow-up of 5-year survivors diagnosed with cancer before the age of 21 years at 27 academic institutions in the USA and Canada between 1970 and 1999. We evaluated outcomes among survivors of early-adolescent and young adult cancer (aged 15-20 years at diagnosis) and survivors diagnosed at age younger than 15 years (matched on primary cancer diagnosis, including leukaemia, lymphoma, CNS tumours, neuroblastoma, Wilms tumour, soft-tissue sarcomas, and bone cancer) by comparing both groups to siblings of the same age. Mortality was ascertained with the National Death Index. Chronic health conditions were classified with the Common Terminology Criteria for Adverse Events. Standardised mortality ratios (SMRs) were estimated with age-specific, sex-specific, and calendar year-specific US rates. Cox proportional hazard models estimated hazard ratios (HRs) for chronic health conditions and 95% CIs.Findings: Among 5804 early-adolescent and young adult survivors (median age 42 years, IQR 34-50) the SMR compared to the general population for all-cause mortality was 5·9 (95% CI 5·5-6·2) and among 5804 childhood cancer survivors (median age 34 years; 27-42), it was 6·2 (5·8-6·6). Early-adolescent and young adult survivors had lower SMRs for death from health-related causes (ie, conditions that exclude recurrence or progression of the primary cancer and external causes, but include the late effects of cancer therapy) than did childhood cancer survivors (SMR 4·8 [95% CI 4·4-5·1] vs 6·8 [6·2-7·4]), which was primarily evident more than 20 years after cancer diagnosis. Early-adolescent and young adult cancer survivors and childhood cancer survivors were both at greater risk of developing severe and disabling, life-threatening, or fatal (grade 3-5) health conditions than siblings of the same age (HR 4·2 [95% CI 3·7-4·8] for early adolescent and young adult cancer survivors and 5·6 [4·9-6·3] for childhood cancer survivors), and at increased risk of developing grade 3-5 cardiac (4·3 [3·5-5·4] and 5·6 [4·5-7·1]), endocrine (3·9 [2·9-5·1] and 6·4 [5·1-8·0]), and musculoskeletal conditions (6·5 [3·9-11·1] and 8·0 [4·6-14·0]) when compared with siblings of the same age, although all these risks were lower for early-adolescent and young adult survivors than for childhood cancer survivors.Interpretation: Early-adolescent and young adult cancer survivors had higher risks of mortality and severe and life threatening chronic health conditions than the general population. However, early-adolescent and young adult cancer survivors had lower non-recurrent, health-related SMRs and relative risks of developing grade 3-5 chronic health conditions than childhood cancer survivors, by comparison with siblings of the same age, which were most notable more than 20 years after their original cancer. These results highlight the need for long-term screening of both childhood and early-adolescent and young adult cancer survivors.Funding: National Cancer Institute and American Lebanese-Syrian Associated Charities. [ABSTRACT FROM AUTHOR]

Background: Cancer treatment can cause gonadal impairment. Acute ovarian failure is defined as the permanent loss of ovarian function within 5 years of cancer diagnosis. We aimed to develop and validate risk prediction tools to provide accurate clinical guidance for paediatric patients with cancer.Methods: In this cohort study, prediction models of acute ovarian failure risk were developed using eligible female US and Canadian participants in the Childhood Cancer Survivor Study (CCSS) cohort and validated in the St Jude Lifetime Cohort (SJLIFE) Study. 5-year survivors from the CCSS cohort were included if they were at least 18 years old at their most recent follow-up and had complete treatment exposure and adequate menstrual history (including age at menarche, current menstrual status, age at last menstruation, and menopausal aetiology) information available. Participants in the SJLIFE cohort were at least 10-year survivors. Participants were excluded from the prediction analysis if they had an ovarian hormone deficiency, had missing exposure information, or had indeterminate ovarian status. The outcome of acute ovarian failure was defined as permanent loss of ovarian function within 5 years of cancer diagnosis or no menarche after cancer treatment by the age of 18 years. Logistic regression, random forest, and support vector machines were used as candidate methods to develop the risk prediction models in the CCSS cohort. Prediction performance was evaluated internally (in the CCSS cohort) and externally (in the SJLIFE cohort) using the areas under the receiver operating characteristic curve (AUC) and the precision-recall curve (average precision [AP; average positive predictive value]).Findings: Data from the CCSS cohort were collected for participants followed up between Nov 3, 1992, and Nov 25, 2016, and from the SJLIFE cohort for participants followed up between Oct 17, 2007, and April 16, 2012. Of 11 336 female CCSS participants, 5886 (51·9%) met all inclusion criteria for analysis. 1644 participants were identified from the SJLIFE cohort, of whom 875 (53·2%) were eligible for analysis. 353 (6·0%) of analysed CCSS participants and 50 (5·7%) of analysed SJLIFE participants had acute ovarian failure. The overall median follow-up for the CCSS cohort was 23·9 years (IQR 20·4-27·9), and for SJLIFE it was 23·9 years (19·0-30·0). The three candidate methods (logistic regression, random forest, and support vector machines) yielded similar results, and a prescribed dose model with abdominal and pelvic radiation doses and an ovarian dose model with ovarian radiation dosimetry using logistic regression were selected. Common predictors in both models were history of haematopoietic stem-cell transplantation, cumulative alkylating drug dose, and an interaction between age at cancer diagnosis and haematopoietic stem-cell transplant. External validation of the model in the SJLIFE cohort produced an estimated AUC of 0·94 (95% CI 0·90-0·98) and AP of 0·68 (95% CI 0·53-0·81) for the ovarian dose model, and AUC of 0·96 (0·94-0·97) and AP of 0·46 (0·34-0·61) for the prescribed dose model. Based on these models, an online risk calculator has been developed for clinical use.Interpretation: Both acute ovarian failure risk prediction models performed well. The ovarian dose model is preferred if ovarian radiation dosimetry is available. The models, along with the online risk calculator, could help clinical discussions regarding the need for fertility preservation interventions in girls and young women newly diagnosed with cancer.Funding: Canadian Institutes of Health Research, Women and Children's Health Research Institute, National Cancer Institute, and American Lebanese Syrian Associated Charities. [ABSTRACT FROM AUTHOR]