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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.

Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). Methods: This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates. Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10–9.02), depression (6.32; 95% CI: 3.18–9.47), fatigue (7.93; 95% CI: 5.11–10.80), sleep (6.07; 95% CI: 3.43–8.70), pain (5.16; 95% CI: 2.11–8.22), and cognitive function (–6.89; 95% CI: –10.00 to –3.79) in the third month. Conclusions: Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.

PurposeTo investigate racial/ethnic-related disparities by insurance status in “forgoing needed medical care in the last year due to finances” in childhood cancer survivors.MethodsOur study included 3310 non-Hispanic/Latinx White, 562 non-Hispanic/Latinx Black, and 92 Hispanic/Latinx survivors from the St. Jude Lifetime Cohort Study. Logistic regression analyses, guided by Andersen’s Healthcare Utilization Model, were adjusted for “predisposing” (survey age, sex, childhood cancer diagnosis and treatment, and treatment era) and “need” (perceived health status) factors. Additional adjustment for household income/education and chronic health conditions was considered.ResultsRisk of forgoing care was highest among non-Hispanic/Latinx Blacks and lowest among Hispanics/Latinxs for each insurance status. Among privately insured survivors, relative to non-Hispanic/Latinx Whites, non-Hispanic/Latinx Blacks were more likely to forgo care (adjusted OR: 1.82, 95% CI: 1.30–2.54): this disparity remained despite additional adjustment for household income/education (adjusted OR: 1.43, 95% CI: 1.01–2.01). In contrast, publicly insured survivors, regardless of race/ethnicity, had similar risk of forgoing care as privately insured non-Hispanic/Latinx Whites. All uninsured survivors had high risk of forgoing care. Additional chronic health condition adjustment did not alter these results.ConclusionsProvision of public insurance to all childhood cancer survivors may diminish racial/ethnic disparities in forgoing care that exist among the privately insured and reduce the risk of forgoing care among uninsured survivors to that of privately insured non-Hispanic/Latinx Whites.Implications for Cancer SurvivorsUnder public insurance, childhood cancer survivors had low risk of forgoing care, at the similar level to privately insured non-Hispanic/Latinx Whites, regardless of race/ethnicity.

Background: Female childhood cancer survivors (CCSs) carry a risk of therapy-related gonadal dysfunction. Alkylating agents (AA) are well-established risk factors, yet inter-individual variability in ovarian function is observed. Polymorphisms in CYP450 enzymes may explain this variability in AA-induced ovarian damage. We aimed to evaluate associations between previously identified genetic polymorphisms in CYP450 enzymes and AA-related ovarian function among adult CCSs. Methods: Anti-Müllerian hormone (AMH) levels served as a proxy for ovarian function in a discovery cohort of adult female CCSs, from the pan-European PanCareLIFE cohort (n = 743; age (years): median 25.8, interquartile range (IQR) 22.1–30.6). Using two additive genetic models in linear and logistic regression, nine genetic variants in three CYP450 enzymes were analyzed in relation to cyclophosphamide equivalent dose (CED) score and their impact on AMH levels. The main model evaluated the effect of the variant on AMH and the interaction model evaluated the modifying effect of the variant on the impact of CED score on log-transformed AMH levels. Results were validated, and meta-analysis performed, using the USA-based St. Jude Lifetime Cohort (n = 391; age (years): median 31.3, IQR 26.6–37.4). Results: CYP3A4*3 was significantly associated with AMH levels in the discovery and replication cohort. Meta-analysis revealed a significant main deleterious effect (Beta (95% CI): −0.706 (−1.11–−0.298), p-value = 7 × 10−4) of CYP3A4*3 (rs4986910) on log-transformed AMH levels. CYP2B6*2 (rs8192709) showed a significant protective interaction effect (Beta (95% CI): 0.527 (0.126–0.928), p-value = 0.01) on log-transformed AMH levels in CCSs receiving more than 8000 mg/m2 CED. Conclusions: Female CCSs CYP3A4*3 carriers had significantly lower AMH levels, and CYP2B6*2 may have a protective effect on AMH levels. Identification of risk-contributing variants may improve individualized counselling regarding the treatment-related risk of infertility and fertility preservation options.

Abstract Disclosure: T. Yoshida: None. J. Baedke: None. F. Wang: None. W. Moon: None. Y. Sapkota: None. J. Miguel Martínez: None. T.E. Merchant: None. C.L. Wilson: None. K.K. Ness: None. M.M. Hudson: None. Y. Yasui: None. A. Delaney: None. Background: Survivors of childhood cancer are at elevated risk for short adult height (SAH) due to cancer and/or its treatment. In the general population, height is a highly polygenic trait; heritability is estimated to be 70-80%. However, the contribution of genetic factors to SAH among childhood cancer survivors is unknown. In addition, the contribution of chemotherapy agents to risk of SAH among survivors has not been established. We assessed: 1) prevalence of SAH; 2) contribution of genetic factors; and 3) impact of cancer therapy including chemotherapy, on SAH in a large cohort of childhood cancer survivors. Methods: Participants included 4461 childhood cancer survivors aged ≥18 years (female 47.5%, mean age 33.2 years old) with measured height information. SAH was defined as height <3rd percentile for age and sex based on the Centers for Disease Control growth charts. Cancer and treatment history were extracted from medical records. We calculated multi-ancestry height polygenic score (PGS) using the latest methodology developed from 5.4 million individuals of diverse ancestries with more than 1 million variants, where lower score associates with shorter height. With a random sample of 75% of survivors, we fit a multivariable logistic regression model for SAH with the PGS, chemotherapy exposures/doses, corticosteroid exposures/doses, and established risk factors for SAH (e.g., age at cancer diagnosis, radiotherapy exposure) as covariates (main model). The remaining 25% of survivors served for validation of the main model and for the calculation of the population attributable fractions (PAF) of the PGS and cancer treatments. Results: The prevalence of SAH was 8.9% among all survivors (9.3% in males; 8.5% in females) and differed widely by primary cancer diagnosis. SAH was associated with lower PGS [odds ratio (OR) 0.47, 95% confidence interval (CI) 0.40-0.55 for a one standard deviation increase], alkylating agent exposure of >12000 mg/m2 (OR 2.19, 95% CI 1.41-3.38, vs. non-exposure), and spinal radiotherapy (OR 3.65, 95% CI 2.23-6.00, vs. non-exposure). Radiotherapy exposure to the hypothalamic-pituitary region and younger age at cancer diagnosis was also associated with SAH in a dose-response manner. The area under the ROC curve of the main model in the validation dataset was 0.80 (95% CI 0.74-0.87), suggesting good predictive ability for SAH by the model. The PAF of SAH calculated from the multiplicative logistic regression model of SAH was 85.7% for cancer treatments and 30.2% and 60.2% for having PGS below the median and the 90th percentile, respectively. Conclusions: Cancer treatments are the primary contributor to SAH risk among survivors with a PAF of 85.7%. Exposure to high-dose alkylating agents contributes to this along with radiotherapy. Inherited genetic factors also affect SAH among survivors but to a much lesser degree than cancer treatments. Presentation: 6/3/2024