Explore the vast range of titles available.

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.

Survivors of childhood cancer are at risk of subsequent neoplasms (SNs) associated with exposure to radiotherapy and chemotherapy, as well as with genetic predisposition. We aimed to estimate the relative contributions of these risk factors to the total SN burden in survivor populations. We analysed data from two retrospectively constructed cohorts with ongoing recruitment and prospective follow-up: the St Jude Lifetime Cohort (SJLIFE; 4401 participants; NCT00760656) and the Childhood Cancer Survivor Study (CCSS; 7943 participants; NCT01120353). We used multivariable piecewise-exponential models to calculate attributable fractions to assess the contributions of radiotherapy and chemotherapy exposures, genetic predisposition (comparing the top two tertiles with the lowest tertile of polygenic risk scores [PRSs] where the tertile is from external general population corresponding to SN outcome) and lifestyle factors (physical activity, smoking, alcohol consumption, obesity, and diet) to incident of the first occurrences of SNs as the primary outcome. The study was conducted between Jan 1, 2024, and Sept 30, 2024. Of the 12 344 survivors eligible for analysis, median attained age was 33·0 years (IQR 24·1–42·1) in SJLIFE and 36·0 years (29·5–43·6) in CCSS; 6127 (49·6%) were men and 6217 (50·4%) were women. Most patients were White (10 907 [88·4%]). The median follow-up from primary cancer diagnosis was 24·2 years (IQR 11·7–35·4) in SJLIFE (from Sept 13, 2007 to April 20, 2020) and 28·0 years (8·9–37·2) in CCSS (from Jan 1, 1975 to Dec 31, 2023). Cancer treatments and genetic risk jointly contributed to a substantial proportion of incident SN cases with attributable fractions ranging from 30% (95% CI 6–49; sarcoma) to 92% (89–94; meningioma). Higher exposure levels of radiotherapy contributed most, particularly in older (≥35 years; SJLIFE proportion of SNs 44·7% [95% CI 41·9–47·5]) compared with younger (<35 years; 40·0% [37·1–43·3]) follow-up age periods. Elevated genetic risk based on the PRSs accounted for a notable proportion, ranging from 1% (95% CI 0–7; meningioma) to 52% (39–62; thyroid cancer), surpassing contributions of chemotherapies, ranging from 3% (1–6; SMNs) to 35% (19–49; sarcoma). Lifestyle factors contributed negligibly. Cancer treatments and genetic predisposition are primary contributors to the risk of SNs in childhood cancer survivors, and lifestyle factors seem to have a minimal effect. These results highlight the crucial need to consider both treatment history and genetic factors in developing effective risk assessment and surveillance strategies for this vulnerable population. US National Institutes of Health and the American Lebanese Syrian Associated Charities.

Childhood cancer survivors, particularly those who received chest radiotherapy, are at high risk for developing subsequent breast cancer. Minimizing long-term toxicity risks associated with additional radiotherapy and chemotherapy is a priority, but therapeutic tradeoffs have not been comprehensively characterized and their impact on survival is unknown. In this study, 431 female childhood cancer survivors with subsequent breast cancer from a multicenter retrospective cohort study were evaluated. Compared with one-to-one matched females with first primary breast cancer, survivors are as likely to be prescribed guideline-concordant treatment (N = 344 pairs; survivors: 94%, controls: 93%), but more frequently undergo mastectomy (survivors: 81%, controls: 60%) and are less likely to be treated with anthracyclines (survivors: 47%, controls: 66%) or radiotherapy (survivors: 18%, controls: 61%). Despite this, survivors have nearly 3.5-fold (95% CI = 2.17-5.57) greater mortality risk. Here, we show survivors with subsequent breast cancer face excess mortality despite therapeutic tradeoffs and require specialized treatment guidelines. Children receiving chest radiotherapy for childhood cancer have a higher risk of developing breast cancer later in life. Here, using the data from the Childhood Cancer Survivor Study, the authors investigate the treatment and survival outcomes of breast cancer patients who previously survived childhood cancer finding them to receive altered treatment and having increased mortality.

Objectives: To quantify the Black/Hispanic disparity in COVID-19 mortality in the United States (US). Methods: COVID-19 deaths in all US counties nationwide were analyzed to estimate COVID-19 mortality rate ratios by county-level proportions of Black/Hispanic residents, using mixed-effects Poisson regression. Excess COVID-19 mortality counts, relative to predicted under a counterfactual scenario of no racial/ethnic disparity gradient, were estimated. Results: County-level COVID-19 mortality rates increased monotonically with county-level proportions of Black and Hispanic residents, up to 5.4-fold (≥43% Black) and 11.6-fold (≥55% Hispanic) higher compared to counties with <5% Black and <15% Hispanic residents, respectively, controlling for county-level poverty, age, and urbanization level. Had this disparity gradient not existed, the US COVID-19 death count would have been 92.1% lower (177,672 fewer deaths), making the rate comparable to other high-income countries with substantially lower COVID-19 death counts. Conclusion: During the first 8 months of the SARS-CoV-2 pandemic, the US experienced the highest number of COVID-19 deaths. This COVID-19 mortality burden is strongly associated with county-level racial/ethnic diversity, explaining most US COVID-19 deaths.

[This corrects the article DOI: 10.3389/ijph.2021.1604004.].

Single-nucleotide polymorphisms (SNPs) contributing to interactions between regulatory elements that modulate gene transcription may explain some of the uncharacterized variation for complex traits. We explored this hypothesis among 856 adult survivors of pediatric cancer exposed to curative treatments that adversely affect bone mineral density (BMD). To restrict our search to interactions among SNPs in regulatory elements, our analysis considered 75523 SNPs mapped to putative promoter or enhancer regions. In anticipation that power to detect higher order epistasis would be low using an exhaustive search and a Bonferroni-corrected threshold for genome-wide significance (e.g., P < 5.6 × 10−14), a novel non-exhaustive statistical algorithm was implemented to detect chromosome-wide three-way regulatory interactions. We used a permutation-based evaluation statistic to identify candidate SNP interactions with stronger associations with BMD than expected. Of the six regulatory 3-SNP interactions identified as candidate interactions (P < 3.5 × 10−11) among cancer survivors exposed to treatments, five were replicated in an independent cohort of survivors (N = 1428) as modifiers of treatment effects on BMD (P < 0.05). Analyses with publicly available bioinformatics data revealed that SNPs contributing to replicated interactions were enriched for gene expressions (P = 3.6 × 10−4) and enhancer states (P < 0.05) in cells relevant for bone biology. For each replicated interaction, implicated SNPs were within or directly adjacent to 100-kb windows of genomic regions that plausibly physically interact in lymphoblastoid cells. Our study demonstrates the utility of a hypothesis-driven approach in revealing epistasis associated with complex traits.

Carriers of cancer predisposing variants are at an increased risk of developing subsequent malignant neoplasms among those who have survived childhood cancer. We aimed to investigate whether cancer predisposing variants contribute to the risk of subsequent malignant neoplasm-related late mortality (5 years or more after diagnosis). In this analysis, data were included from two retrospective cohort studies, St Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), with prospective follow-up of patients who were alive for at least 5 years after diagnosis with childhood cancer (ie, long-term childhood cancer survivors) with corresponding germline whole genome or whole exome sequencing data. Cancer predisposing variants affecting 60 genes associated with well-established autosomal-dominant cancer-predisposition syndromes were characterised. Subsequent malignant neoplasms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 with modifications. Cause-specific late mortality was based on linkage with the US National Death Index and systematic cohort follow up. Fine-Gray subdistribution hazard models were used to estimate subsequent malignant neoplasm-related late mortality starting from the first biospecimen collection, treating non-subsequent malignant neoplasm-related deaths as a competing risk, adjusting for genetic ancestry, sex, age at diagnosis, and cancer treatment exposures. SJLIFE (NCT00760656) and CCSS (NCT01120353) are registered with ClinicalTrials.gov. 12 469 (6172 male and 6297 female) participants were included, 4402 from the SJLIFE cohort (median follow-up time since collection of the first biospecimen 7·4 years [IQR 3·1–9·4]) and 8067 from the CCSS cohort (median follow-up time since collection of the first biospecimen 12·6 years [2·2–16·6]). 641 (5·1%) of 12 469 participants carried cancer predisposing variants (294 [6·7%] in the SJLIFE cohort and 347 [4·3%] in the CCSS cohort), which were significantly associated with an increased severity of subsequent malignant neoplasms (CTCAE grade ≥4 vs grade <4: odds ratio 2·15, 95% CI 1·18–4·19, p=0·0085). 263 (2·1%) subsequent malignant neoplasm-related deaths (44 [1·0%] in the SJLIFE cohort; and 219 [2·7%] in the CCSS cohort) and 426 (3·4%) other-cause deaths (103 [2·3%] in SJLIFE; and 323 [4·0%] in CCSS) occurred. Cumulative subsequent malignant neoplasm-related mortality at 10 years after the first biospecimen collection in carriers of cancer predisposing variants was 3·7% (95% CI 1·2–8·5) in SJLIFE and 6·9% (4·1–10·7) in CCSS versus 1·5% (1·0–2·1) in SJLIFE and 2·1% (1·7–2·5) in CCSS in non-carriers. Carrying a cancer predisposing variant was associated with an increased risk of subsequent malignant neoplasm-related mortality (SJLIFE: subdistribution hazard ratio 3·40 [95% CI 1·37–8·43]; p=0·0082; CCSS: 3·58 [2·27–5·63]; p<0·0001). Identifying participants at increased risk of subsequent malignant neoplasms via genetic counselling and clinical genetic testing for cancer predisposing variants and implementing early personalised cancer surveillance and prevention strategies might reduce the substantial subsequent malignant neoplasm-related mortality burden. American Lebanese Syrian Associated Charities and US National Institutes of Health.