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Objectives: To explore socio-behavioral, clinical, and imaging findings associated with antepartum intimate partner violence (IPV) and aid in risk stratification of at-risk individuals. Methods: We analyzed electronic medical records during indexed pregnancies for 108 pregnant patients who self-reported antepartum IPV (cases) and 106 age-matched pregnant patients who did not self-report antepartum IPV (controls). Sociodemographic, clinical, and radiology data were analyzed via chi-squared and Fisher's exact tests with p < 0.05 as the threshold for significance. Stepwise logistic regression was applied to derive a risk prediction model. Results: The proportion of cases reporting emotional IPV (76% vs. 52%) and/or physical IPV (45% vs. 31%) during pregnancy significantly increased from prior to pregnancy. Cases were significantly more likely to report prepregnancy substance use (odds ratio [OR] = 2.60; 95% confidence interval [CI]: 1.13–5.98), sexually transmitted infections (OR = 3.48; 95%CI: 1.64–7.37), abortion (OR = 3.17; 95%CI: 1.79, 5.59), and preterm birth (OR = 5.97; 95%CI: 1.69–21.15). During pregnancy, cases were more likely to report unstable housing (OR = 5.26; 95%CI: 2.67–10.36), multigravidity (OR = 2.83; 95%CI: 1.44–5.58), multiparity (OR = 3.75; 95%CI: 1.72–8.20), anxiety (OR = 3.35; 95%CI: 1.85–6.08), depression (OR = 5.58; 95%CI: 3.07–10.16), substance use (OR = 2.92; 95%CI: 1.28–6.65), urinary tract infection (UTI) (OR = 3.26; 95%CI: 1.14–9.32), intrauterine growth restriction (OR = 10.71; 95%CI: 1.35–85.25), and cesarean delivery (OR = 2.25; 95%CI: 1.26–4.02). Cases had significantly more OBGYN abnormalities on imaging and canceled more radiological studies (OR = 5.31). Logistic regression found housing status, sexually transmitted infection history, preterm delivery history, abortion history, depression, and antepartum UTI predictive of antepartum IPV. The risk prediction model achieved good calibration with an area under the curve of 0.79. Conclusions: This study identifies significant disparities among patients experiencing antepartum IPV, and our proposed risk prediction model can inform risk assessment in this setting. [ABSTRACT FROM AUTHOR]

Background: We examined associations of CD44, CD24 and ALDH1A1 breast stem cell markers with mammographic breast density (MBD), a well-established breast cancer (BCa) risk factor. Methods: We included 218 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on BCa risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was done on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as percent of positively stained cells for each marker out of the total cell count. MBD was assessed with computer-assisted techniques. Generalised linear regression was used to examine the associations of each marker with square root-transformed percent density (PD), absolute dense and non-dense areas (NDA), adjusted for BCa risk factors. Results: Stromal CD44 and ALDH1A1 expression was positively associated with PD (≥ 10% vs. <10% β = 0.56, 95% confidence interval [CI] [0.06; 1.07] and β = 0.81 [0.27; 1.34], respectively) and inversely associated with NDA (β per 10% increase = −0.17 [−0.34; −0.01] and β for ≥10% vs. <10% = −1.17 [−2.07; −0.28], respectively). Epithelial CD24 expression was inversely associated with PD (β per 10% increase = −0.14 [−0.28; −0.01]. Stromal and epithelial CD24 expression was positively associated with NDA (β per 10% increase = 0.35 [0.2 × 10−2; 0.70] and β per 10% increase = 0.34 [0.11; 0.57], respectively). Conclusion: Expression of stem cell markers is associated with MBD. [ABSTRACT FROM AUTHOR]

We aimed to examine the association between the use of metformin and other anti‐diabetic medications and breast cancer incidence within two large prospective cohort studies. We followed 185,181 women who participated in the Nurses' Health Study (NHS; 1994–2016) and the NHSII (1995–2017), with baseline corresponding to the date metformin was approved for type 2 diabetes (T2D) treatment in the US Information on T2D diagnosis, anti‐diabetes medications, and other covariates was self‐reported at baseline and repeatedly assessed by follow‐up questionnaires every 2 years. Breast cancer cases were self‐reported and confirmed by medical record review. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between medication use and breast cancer were estimated using Cox proportional hazards regression models, adjusting for breast cancer risk factors. During 3,324,881 person‐years of follow‐up, we ascertained 9,192 incident invasive breast cancer cases, of which 451 were among women with T2D. Compared with women without T2D (n = 169,263), neither metformin use (HR = 0.97; 95% CI = 0.81–1.15) nor other anti‐diabetic medications use (HR = 1.11; 95% CI = 0.90–1.36) associated with significantly lower breast cancer incidence. Among women with T2D (n = 15,918), compared with metformin never users, metformin ever use was not significantly inversely associated with breast cancer (HR = 0.92; 95% CI = 0.74–1.15). Although we observed that past use of metformin was inversely associated with breast cancer in the T2D population (HR = 0.67; 95% CI = 0.48–0.94), current use (HR = 1.01; 95% CI = 0.80–1.27) and longer duration of metformin use were not associated with breast cancer (each 2‐year interval: HR = 1.01; 95% CI = 0.95–1.07). Overall, metformin use was not associated with the risk of developing breast cancer among the overall cohort population or among women with T2D. [ABSTRACT FROM AUTHOR]

Purpose: Physical activity is associated with lower breast cancer risk, especially in postmenopausal women. Associations in premenopausal women are less well established. Methods: We evaluated recreational physical activity and breast cancer risk in the Nurses' Health Study (NHS) and NHSII (187,278 women; n = 12,785 breast cancers; follow-up: NHS = 1986–2016, NHSII = 1989–2017) by menopausal status and estrogen (ER) and progesterone (PR) receptor status. Physical activity was evaluated as updated cumulative average of metabolic equivalent of task (MET)-h/week. Cox proportional hazards models were used to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI). Results: Recreational physical activity was inversely associated with breast cancer risk in pre- and postmenopausal women. Higher activity levels were associated with lower risk of ER+/PR + breast cancer in both pre- and postmenopausal women (e.g., total recreational activity, ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83, 95%CI = (0.70–0.99), postmenopausal HR = 0.86 (0.78–0.95); pheterogeneity = 0.97). Results were attenuated with adjustment for current body mass index (BMI) among postmenopausal, but not premenopausal, women (e.g., ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83 (0.69–0.98); postmenopausal HR = 0.95 (0.85–1.05); pheterogeneity = 0.99). In analyses of moderate-vigorous activity and breast cancer risk, no heterogeneity by menopausal status was observed (phet ≥ 0.53; e.g., ≥ 27 vs < 3 MET-h/week, ER+/PR+, premenopausal HR = 0.88 (0.69–1.11); postmenopausal HR = 0.71 (0.58–0.88). No associations were observed for ER−/PR− disease. Conclusions: Recreational physical activity was associated with lower breast cancer risk in both pre- and postmenopausal women, supporting recreational physical activity as an accessible, modifiable exposure associated with reduced breast cancer risk regardless of menopausal status. [ABSTRACT FROM AUTHOR]

Background: Early menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear. Methods: We profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses' Health Studies (NHS) to investigate whether early menarche (age < 12) is associated with tumor molecular and prognostic features in women with breast cancer. Multivariable linear regression and pathway analyses using competitive gene set enrichment analysis were conducted in both tumor and adjacent-normal tissue and externally validated in TCGA (N = 116). Subgroup analyses stratified on ER-status based on the tumor were also performed. PAM50 signatures were used for tumor molecular subtyping and to generate proliferation and risk of recurrence scores. We created a gene expression score using LASSO regression to capture early menarche based on 28 genes from FDR-significant pathways in breast tumor tissue in NHS and tested its association with 10-year disease-free survival in both NHS (N = 836) and METABRIC (N = 952). Results: Early menarche was significantly associated with 369 individual genes in adjacent-normal tissues implicated in extracellular matrix, cell adhesion, and invasion (FDR ≤ 0.1). Early menarche was associated with upregulation of cancer hallmark pathways (18 significant pathways in tumor, 23 in tumor-adjacent normal, FDR ≤ 0.1) related to proliferation (e.g. Myc, PI3K/AKT/mTOR, cell cycle), oxidative stress (e.g. oxidative phosphorylation, unfolded protein response), and inflammation (e.g. pro-inflammatory cytokines IFN α and IFN γ ). Replication in TCGA confirmed these trends. Early menarche was associated with significantly higher PAM50 proliferation scores (β = 0.082 [0.02–0.14]), odds of aggressive molecular tumor subtypes (basal-like, OR = 1.84 [1.18–2.85] and HER2-enriched, OR = 2.32 [1.46–3.69]), and PAM50 risk of recurrence score (β = 4.81 [1.71–7.92]). Our NHS-derived early menarche gene expression signature was significantly associated with worse 10-year disease-free survival in METABRIC (N = 952, HR = 1.58 [1.10–2.25]). Conclusions: Early menarche is associated with more aggressive molecular tumor characteristics and its gene expression signature within tumors is associated with worse 10-year disease-free survival among women with breast cancer. As the age of onset of menarche continues to decline, understanding its relationship to breast tumor characteristics and prognosis may lead to novel secondary prevention strategies. [ABSTRACT FROM AUTHOR]

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = − 0.98 standard deviations; 95% CI: − 1.11, − 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation. [ABSTRACT FROM AUTHOR]

Background: We investigated the associations of reproductive factors known to influence breast cancer risk with the expression of breast stem cell markers CD44, CD24, and ALDH1A1 in benign breast biopsy samples. Methods: We included 439 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on reproductive and other breast cancer risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was performed on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as % of cells that stained positive for a specific marker out of the total cell count. Generalized linear regression was used to examine the associations of reproductive factors with a log-transformed expression of each marker (in epithelium and stroma), adjusted for other breast cancer risk factors. Results: In multivariate analysis, the time between menarche and age at first birth was inversely associated with CD44 in epithelium (β per 5 years = -0.38, 95% CI -0.69; -0.06). Age at first birth and the time between menarche and age at first birth were inversely associated with ALDH1A1 (stroma: β per 5 years = -0.43, 95% CI -0.76; -0.10 and β = -0.47, 95% CI -0.79; -0.15, respectively; epithelium: β = -0.15, 95% CI -0.30; -0.01 and β = -0.17, 95% CI -0.30; -0.03, respectively). Time since last pregnancy was inversely associated with stromal ALDH1A1 (β per 5 years = -0.55, 95% CI -0.98; -0.11). No associations were found for CD24. The observed associations were similar in premenopausal women. In postmenopausal women, lifetime duration of breastfeeding was inversely associated with stromal ALDH1A1 expression (β for ≥24 vs. 0 to <1 months = -2.24, 95% CI 3.96; -0.51, p-trend = 0.01). Conclusion: Early-life reproductive factors may influence CD44 and ALDH1A1 expression in benign breast tissue. [ABSTRACT FROM AUTHOR]

Context Black women have a higher prevalence of hypertension as compared to White women. Differences in dietary sodium intake have been implicated as a contributing factor for the disparities in hypertension. Objective Our objective was to understand whether young Black women would have higher systolic blood pressure (SBP) than White women even on controlled sodium diets and to determine whether SBP differences were due to differences in dietary sodium intake and/or aldosterone regulation. Design The analyses included 525 hypertensive and normotensive women (ages 18-71) from the International Hypertensive Pathotype consortium, who were maintained on liberal sodium (LIB; >200 mEq sodium/day) and restricted sodium (RES; 10 mEq sodium/day) diets. Results Multivariate regression analyses (adjusted for age, race, study site, body mass index) found that Black women (ages 18-50) had significantly higher SBP than White women on both sodium diets: +8.7 ± 2.7 mmHg (P -value =.002) on a LIB diet and +8.5 ± 2.5 mmHg (P -value =.001) on a RES diet. Even among 18- to 35-year-olds—who were normotensive and nonobese—Black women had higher SBP: +7.9 ± 2.4 mmHg (P -value =.001) on a LIB diet and +7.6 ± 2.7 mmHg (P -value =.005) on a RES diet. Younger Black women also had higher plasma aldosterone concentration to plasma renin activity ratio (ARR) on both LIB and RES diets as well as a higher sodium-modulated aldosterone suppression-stimulation index—an indicator of aldosterone dysregulation. In younger Black women—but not in White women—there was a significant association between SBP and ARR on both LIB and RES diets. Conclusion Young Black women had increased SBP and ARR as compared to White women on LIB and RES diets, which offers insights into the possible mechanisms for the increased hypertension and cardiovascular disease risk in an at-risk and understudied population. [ABSTRACT FROM AUTHOR]

Background: We examined associations between dog ownership, morning dog walking and its timing and duration, and depression risk in female nurses, exploring effect modification by chronotype. We hypothesized that dog ownership and morning walking with the dog are associated with lower odds of depression, and that the latter is particularly beneficial for evening chronotypes by helping them to synchronize their biological clock with the solar system. Methods: 26,169 depression-free US women aged 53–72 from the Nurses' Health Study 2 (NHS2) were prospectively followed from 2017–2019. We used age- and multivariable-adjusted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for depression according to dog ownership, and morning dog walking, duration, and timing. Results: Overall, there was no association between owning a dog (ORvs_no_pets = 1.12, 95%CI = 0.91–1.37), morning dog walking (ORvs_not = 0.87, 95%CI = 0.64–1.18), or the duration (OR>30min vs. ≤15mins = 0.68, 95%CI = 0.35–1.29) or timing of morning dog walks (ORafter9am vs. before7am = 1.06, 95%CI = 0.54–2.05) and depression. Chronotype of dog owners appeared to modify these associations. Compared to women of the same chronotype but without pets, dog owners with evening chronotypes had a significantly increased odds of depression (OR = 1.60, 95%CI = 1.12–2.29), whereas morning chronotypes did not (OR = 0.94, 95%CI = 0.71–1.23). Further, our data suggested that evening chronotypes benefited more from walking their dog themselves in the morning (OR = 0.75, 95%CI = 0.46–1.23, Pintx = 0.064;) than morning chronotypes. Conclusions: Overall, dog ownership was not associated with depression risk though it was increased among evening chronotypes. Walking their dog in the morning might help evening chronotypes to lower their odds of depression, though more data are needed to confirm this finding. [ABSTRACT FROM AUTHOR]

Introduction: The Health-Related Quality of Life (HRQoL) often declines among cancer survivors due to many factors. Some cancer patients who smoke before the cancer diagnosis continue this harmful habit, potentially contributing to a more significant decline in their HRQoL. Therefore, this study investigates the association between smoking status and HRQoL in cancer survivors. Methods: We conducted a cross-sectional study utilizing self-reported cancer history from 39,578 participants of the Behavioral Risk Factor Surveillance System (BRFSS) database, leveraging 2016 and 2020 year questionaries. A multidimensional composite outcome was created to assess HRQoL, integrating four distinct dimensions - general health, mental health, physical health, and activity limitations. After accounting for the complex survey design, logistic regression models were used to analyze the association between smoking status and poor HRQoL, adjusting for demographic, socioeconomic, and health-related confounders. Results: Our study found that, after adjusting for potential confounders, current smokers exhibited a significantly poorer HRQoL than never smokers (OR 1.65, 95%CI 1.40-1.93). Furthermore, former smokers showed a poorer HRQoL than never smokers; however, this association was not as strong as current smokers (OR 1.22, 95%CI 1.09-1.38). Conclusion: Our findings highlight the adverse association of smoking with poor HRQoL in cancer survivors, underscoring the importance of healthcare professionals prioritizing smoking cessation and providing tailored interventions to support this goal. [ABSTRACT FROM AUTHOR]

We evaluated the validity and reproducibility of a semiquantitative food frequency questionnaire (FFQ) for measuring intakes of 149 foods and 25 food groups among 736 participants of the Women's Lifestyle Validation Study (WLVS, 2010–2012) and 649 participants of the Men's Lifestyle Validation Study (MLVS, 2011–2013). Validity of the FFQ compared with two 7-day dietary records measured 6 months apart and the reproducibility between 2 FFQs administered 1 year apart (FFQ1 and FFQ2) were assessed using Spearman correlations and intraclass correlation coefficients. The average 1-year reproducibility of FFQ-measured foods was 0.64 in both the WLVS and MLVS. Reproducibility of the food groups (mean = 0.71 among women and 0.72 among men) was generally higher than that for individual foods. Among women, the average validity correlation for individual foods was 0.59 when comparing FFQ2 with the 7-day dietary records. Among men, the corresponding average validity correlation was 0.61. Compared with individual foods, food groups had slightly higher validity correlations in both women (range, 0.45–0.92; mean = 0.61) and men (range, 0.46–0.88; mean = 0.65). This study reaffirms that the FFQ performs well in measuring most foods and food groups and provides data to adjust for measurement errors in epidemiologic studies of foods and food groups. [ABSTRACT FROM AUTHOR]

Background To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models. Methods We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668). The Nurses' Health Study development cohort (n = 48 102) regression coefficients were applied to the validation cohorts. We compared our model's performance with breast cancer risk assessment tool (Gail) and International Breast Cancer Intervention Study (IBIS) models by computing breast cancer risk estimates and C statistics. Results When predicting 10-year breast cancer risk, our model's C index was 0.569 in BWHS, 0.572 in WHI-ES, and 0.576 in MEC. The Gail model's C statistic was 0.554 in BWHS, 0.564 in WHI-ES, and 0.551 in MEC; IBIS's C statistic was 0.547 in BWHS, 0.552 in WHI-ES, and 0.562 in MEC. The Gail model underpredicted breast cancer risk in WHI-ES; IBIS underpredicted breast cancer risk in WHI-ES and in MEC but overpredicted breast cancer risk in BWHS. Our model calibrated well. Our model's C index for predicting 10-year nonbreast cancer death was 0.760 in WHI-ES and 0.763 in MEC. Conclusions Our competing-risk model performs as well as existing breast cancer prediction models in diverse cohorts and predicts nonbreast cancer death. We are developing a website to disseminate our model. [ABSTRACT FROM AUTHOR]

BACKGROUND: It remains unclear whether in utero and childhood exposure to air pollution affects pubertal development, particularly age of menarche in girls. OBJECTIVE: The aim of this study was to determine whether residential ambient particulate matter (PM) exposure in utero and during childhood is associated with age of menarche. METHODS: We studied 5,201 girls in the Growing Up Today Study 2 (2004-present) who were 10-17 y of age at enrollment (47.7% premenarchal; 52.3% postmenarchal). Exposure to three size fractions of PM [fine PM with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM with aerodynamic diameters between 2.5 μm and 10 μm (PM2.5-10), and PM with aerodynamic diameter 10 μm (PM10)] was assigned based on maternal residential address, updated every 2 y, using nationwide spatiotemporal models. We estimated average PM exposure in utero, and time-varying windows: annual average exposure in the prior 1 and 2 y and cumulative average from birth. Age of menarche was self-reported on three surveys administered in 2004, 2006, and 2008. We calculated hazard ratios (HR) for menarche for an interquartile range (IQR) increase in PM exposure using Cox proportional hazard models adjusting for potential confounders. RESULTS: Girls attained menarche at 12.3 y of age on average. In the adjusted model, higher residential exposure to ambient PM2.5 during all time windows was associated with earlier age of menarche. The HRs of menarche for each IQR (4 μg/m³) increase in exposure to PM2.5 during the in utero period, 1 y prior to menarche, and throughout childhood were 1.03 [95% confidence interval (CI): 1.00, 1.06], 1.06 (95% CI: 1.02, 1.10) and 1.06 (95% CI: 1.02, 1.10), respectively. Effect estimates for PM10 exposure were similar, albeit attenuated, for all time windows. PM2.5-10 exposure was not associated with age of menarche. DISCUSSION: Among a large, nationwide, prospective cohort of U.S. girls, higher exposure to PM2.5 and PM10 in utero and throughout childhood was associated with an earlier age of menarche. Our results suggest that PM2.5 and PM10 may have endocrine-disrupting properties that could lead to altered timing of menarche. [ABSTRACT FROM AUTHOR]

The Kaplan–Meier estimator is ubiquitously used to estimate survival probabilities for time-to-event data. It is nonparametric, and thus does not require specification of a survival distribution, but it does assume that the risk set at any time t consists of independent observations. This assumption does not hold for data from paired organ systems such as occur in ophthalmology (eyes) or otolaryngology (ears), or for other types of clustered data. In this article, we estimate marginal survival probabilities in the setting of clustered data, and provide confidence limits for these estimates with intra-cluster correlation accounted for by an interval-censored version of the Clayton–Oakes model. We develop a goodness-of-fit test for general bivariate interval-censored data and apply it to the proposed interval-censored version of the Clayton–Oakes model. We also propose a likelihood ratio test for the comparison of survival distributions between two groups in the setting of clustered data under the assumption of a constant between-group hazard ratio. This methodology can be used both for balanced and unbalanced cluster sizes, and also when the cluster size is informative. We compare our test to the ordinary log rank test and the Lin-Wei (LW) test based on the marginal Cox proportional Hazards model with robust standard errors obtained from the sandwich estimator. Simulation results indicate that the ordinary log rank test over-inflates type I error, while the proposed unconditional likelihood ratio test has appropriate type I error and higher power than the LW test. The method is demonstrated in real examples from the Sorbinil Retinopathy Trial, and the Age-Related Macular Degeneration Study. Raw data from these two trials are provided. [ABSTRACT FROM AUTHOR]

Background and objectives: Crossover designs are frequently used to assess treatments for patients with Parkinson’s disease. Typically, two-period two-treatment trials include a washout period between the 2 periods and assume that the washout period is sufficiently long to eliminate carryover effects. A complementary strategy might be to jointly model carryover and treatment effects, though this has rarely been done in Parkinson’s disease crossover studies. The primary objective of this research is to demonstrate a modeling approach that assesses treatment and carryover effects in one unified mixed model analysis and to examine how it performs in a simulation study and a real data analysis example, as compared to other data analytic approaches used in Parkinson’s disease crossover studies. Methods: We examined how three different methods of analysis (standard crossover t-test, mixed model with a carryover term included in model statement, and mixed model with no carryover term) performed in a simulation study and illustrated the methods in a real data example in Parkinson’s disease. Results: The simulation study based on the presence of a carryover effect indicated that mixed models with a carryover term and an unstructured correlation matrix provided unbiased estimates of treatment effect and appropriate type I error. The methods are illustrated in a real data example involving Parkinson’s disease. Our literature review revealed that a majority of crossover studies included a washout period but did not assess whether the washout was sufficiently long to eliminate the possibility of carryover. Discussion: We recommend using a mixed model with a carryover term and an unstructured correlation matrix to obtain unbiased estimates of treatment effect. [ABSTRACT FROM AUTHOR]

Inadequate sleep is a global health concern. Sleep is multidimensional and complex; new multi-ingredient agents are needed. This study assessed the comparative effects of two multi-ingredient supplements on sleep relative to placebo. Adults (N = 620) seeking better sleep were randomly assigned to receive one of three study products. Sleep A (contained lower (0.35 mg THC and higher levels of botanicals (75 mg each hops oil and valerian oil), Sleep B (contained higher THC (0.85 mg) and lower botanicals (20 mg each hops oil and valerian oil) or placebo) for 4 weeks. Sleep disturbance was assessed at baseline and weekly using NIH's Patient-Reported Outcomes Measurement Information System (PROMIS™) Sleep Disturbance SF 8A survey. Anxiety, stress, pain, and well-being were assessed using validated measures at baseline and weekly. A linear mixed-effects regression model was used to assess the change in health outcome score between active product groups and the placebo. There was a significant difference in sleep disturbance, anxiety, stress, and well-being between Sleep A and placebo. There was no significant difference in any health parameter between Sleep B and placebo. Side effects were mild or moderate. There were no significant differences in the frequency of side effects between the study groups. A botanical blend containing a low concentration of THC improved sleep disturbance, anxiety, stress, and well-being in healthy individuals that reported better sleep as a primary health concern. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to examine the relationship between alcohol consumption and hip osteoarthritis in women. Alcohol has been associated with both adverse and beneficial health effects generally; however, the relationship between alcohol consumption and hip osteoarthritis has been minimally studied. Methods: Among women in the Nurses' Health Study cohort in the US, alcohol consumption was assessed every 4 years, starting in 1980. Intake was computed as cumulative averages and simple updates with latency periods of 0–4 through 20–24 years. We followed 83,383 women without diagnosed osteoarthritis in 1988 to June 2012. We identified 1,796 cases of total hip replacement due to hip osteoarthritis defined by self‐report of osteoarthritis with hip replacement. Results: Alcohol consumption was positively associated with hip osteoarthritis risk. Compared with nondrinkers, multivariable hazard ratios (HRs) and 95% confidence intervals (95% CIs) were HR 1.04 (95% CI 0.90, 1.19) for drinkers of >0 to <5 grams/day, HR 1.12 (95% CI 0.94, 1.33) for 5 to <10 grams/day, HR 1.31 (95% CI 1.10, 1.56) for 10 to <20 grams/day, and HR 1.34 (95% CI 1.09, 1.64) for ≥20 grams/day (P for trend < 0.0001). This association held in latency analyses of up to 16–20 years, and for alcohol consumption between 35–40 years of age. Independent of other alcoholic beverages, the multivariable HRs (per 10 grams of alcohol) were similar for individual types of alcohol intake (wine, liquor, and beer; P = 0.57 for heterogeneity among alcohol types). Conclusion: Higher alcohol consumption was associated with greater incidence of total hip replacement due to hip osteoarthritis in a dose‐dependent manner in women. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to evaluate the role of low‐carbohydrate diets after breast cancer diagnosis in relation to breast cancer–specific and all‐cause mortality. Methods: For 9621 women with stage I–III breast cancer from two ongoing cohort studies, the Nurses' Health Study and Nurses' Health Study II, overall low‐carbohydrate, animal‐rich low‐carbohydrate, and plant‐rich low‐carbohydrate diet scores were calculated by using food frequency questionnaires collected after breast cancer diagnosis. Results: Participants were followed up for a median 12.4 years after breast cancer diagnosis. We documented 1269 deaths due to breast cancer and 3850 all‐cause deaths. With the use of Cox proportional hazards regression and after controlling for potential confounding variables, we observed a significantly lower risk of overall mortality among women with breast cancer who had greater adherence to overall low‐carbohydrate diets (hazard ratio for quintile 5 vs. quintile 1 [HRQ5vsQ1], 0.82; 95% CI, 0.74–0.91; ptrend =.0001) and plant‐rich low‐carbohydrate diets (HRQ5vsQ1, 0.73; 95% CI, 0.66–0.82; ptrend <.0001) after breast cancer diagnosis but not animal‐rich low‐carbohydrate diets (HRQ5vsQ1, 0.93; 95% CI, 0.84–1.04; ptrend =.23). However, greater adherence to overall, animal‐rich, or plant‐rich low‐carbohydrate diets was not significantly associated with a lower risk of breast cancer–specific mortality. Conclusions: This study showed that greater adherence to low‐carbohydrate diets, especially plant‐rich low‐carbohydrate diets, was associated with better overall survival but not breast cancer–specific survival among women with stage I–III breast cancer. Greater adherence to low‐carbohydrate diets, especially plant‐rich low‐carbohydrate diets, was associated with better overall survival but not breast cancer–specific survival among women with stage I–III breast cancer. [ABSTRACT FROM AUTHOR]

Background: Olive oil consumption may reduce breast cancer risk, but it is unclear whether olive oil is beneficial for breast cancer prevention in populations outside of Mediterranean regions, namely in the U.S., where the average consumption of olive oil is low compared with Mediterranean populations. We examined whether olive oil intake was associated with breast cancer risk in two prospective cohorts of U.S. women. Methods: We used multivariable-adjusted time-varying Cox proportional hazards models to estimate hazard ratios (HR) and 95% confidence interval (CI) for breast cancer among 71,330 (Nurses' Health Study, 1990–2016) and 93,295 women (Nurses' Health Study II, 1991–2017) who were free of cancer at baseline. Diet was assessed by a validated semi-quantitative food frequency questionnaire every 4 years. Results: During 3,744,068 person-years of follow-up, 9,638 women developed invasive breast cancer. The multivariable-adjusted HR (95% CI) for breast cancer among women who had the highest consumption of olive oil (>1/2 tablespoon/d or >7 g/d) compared with those who never or rarely consumed olive oil, was 1.01 (0.93, 1.09). Higher olive oil consumption was not associated with any subtype of breast cancer. Conclusion: We did not observe an association between higher olive oil intake and breast cancer risk in two large prospective cohorts of U.S. women, whose average olive oil consumption was low. Prospective studies are needed to confirm these findings and to further investigate whether different varieties of olive oil (e.g., virgin and extra virgin olive oil) may play a role in breast cancer risk. [ABSTRACT FROM AUTHOR]

Background: Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential 'outlier' evaluators are needed to improve data quality during data collection stage. Methods: In this paper, we propose a two-stage algorithm to detect 'outlier' evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators' effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect 'outlier' evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential 'outlier' audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses' Health Study II. Results: Our simulation study shows that our method not only can detect true 'outlier' evaluators, but also is less likely to falsely reject true 'normal' evaluators. Conclusions: Our two-stage 'outlier' detection algorithm is a flexible approach that can effectively detect 'outlier' evaluators, and thus data quality can be improved during data collection stage. [ABSTRACT FROM AUTHOR]

Participant‐level meta‐analysis across multiple studies increases the sample size for pooled analyses, thereby improving precision in effect estimates and enabling subgroup analyses. For analyses involving biomarker measurements as an exposure of interest, investigators must first calibrate the data to address measurement variability arising from usage of different laboratories and/or assays. In practice, the calibration process involves reassaying a random subset of biospecimens from each study at a central laboratory and fitting models that relate the study‐specific "local" and central laboratory measurements. Previous work in this area treats the calibration process from the perspective of measurement error techniques and imputes the estimated central laboratory value among individuals with only a local laboratory measurement. In this work, we propose a repeated measures method to calibrate biomarker measurements pooled from multiple studies with study‐specific calibration subsets. We account for correlation between measurements made on the same person and between measurements made at the same laboratory. We demonstrate that the repeated measures approach provides valid inference, and compare it to existing calibration approaches grounded in measurement error techniques in an example describing the association between circulating vitamin D and stroke. [ABSTRACT FROM AUTHOR]

Screening mammography aims to identify breast cancer early and secondarily measures breast density to classify women at higher or lower than average risk for future breast cancer in the general population. Despite the strong association of individual mammography features to breast cancer risk, the statistical literature on mammogram imaging data is limited. While functional principal component analysis (FPCA) has been studied in the literature for extracting image‐based features, it is conducted independently of the time‐to‐event response variable. With the consideration of building a prognostic model for precision prevention, we present a set of flexible methods, supervised FPCA (sFPCA) and functional partial least squares (FPLS), to extract image‐based features associated with the failure time while accommodating the added complication from right censoring. Throughout the article, we hope to demonstrate that one method is favored over the other under different clinical setups. The proposed methods are applied to the motivating data set from the Joanne Knight Breast Health cohort at Siteman Cancer Center. Our approaches not only obtain the best prediction performance compared to the benchmark model, but also reveal different risk patterns within the mammograms. [ABSTRACT FROM AUTHOR]

The area under the true ROC curve (AUC) is routinely used to determine how strongly a given model discriminates between the levels of a binary outcome. Standard inference with the AUC requires that outcomes be independent of each other. To overcome this limitation, a method was developed for the estimation of the variance of the AUC in the setting of two-level hierarchical data using probit-transformed prediction scores generated from generalized estimating equation models, thereby allowing for the application of inferential methods. This manuscript presents an extension of this approach so that inference for the AUC may be performed in a three-level hierarchical data setting (e.g., eyes nested within persons and persons nested within families). A method that accounts for the effect of tied prediction scores on inference is also described. The performance of 95% confidence intervals around the AUC was assessed through the simulation of three-level clustered data in multiple settings, including ones with tied data and variable cluster sizes. Across all settings, the actual 95% confidence interval coverage varied from 0.943 to 0.958, and the ratio of the theoretical variance to the empirical variance of the AUC varied from 0.920 to 1.013. The results are better than those from existing methods. Two examples of applying the proposed methodology are presented. [ABSTRACT FROM AUTHOR]

Glaucoma is a progressive optic neuropathy and a leading cause of irreversible blindness worldwide. Primary open-angle glaucoma is the most common form, and yet the etiology of this multifactorial disease is poorly understood. We aimed to identify plasma metabolites associated with the risk of developing POAG in a case-control study (599 cases and 599 matched controls) nested within the Nurses' Health Studies, and Health Professionals' Follow-Up Study. Plasma metabolites were measured with LC-MS/MS at the Broad Institute (Cambridge, MA, USA); 369 metabolites from 18 metabolite classes passed quality control analyses. For comparison, in a cross-sectional study in the UK Biobank, 168 metabolites were measured in plasma samples from 2,238 prevalent glaucoma cases and 44,723 controls using NMR spectroscopy (Nightingale, Finland; version 2020). Here we show higher levels of diglycerides and triglycerides are adversely associated with glaucoma in all four cohorts, suggesting that they play an important role in glaucoma pathogenesis. Primary open-angle glaucoma is a leading cause of blindness. Here, the authors report higher plasma levels of diglycerides and triglycerides in samples collected prior to diagnosis, particularly in cases presenting with vision loss near fixation. [ABSTRACT FROM AUTHOR]

Delirium is an acute confusional state and a common postoperative morbidity. Prevalent in older adults, delirium occurs at other ages but it is unclear whether the pathophysiology and biomarkers for the condition are independent of age. We quantified expression of 273 plasma proteins involved in inflammation and cardiovascular or neurologic conditions in 34 middle-aged and 42 older patients before and one day after elective spine surgery. Delirium was identified by the 3D-CAM and comprehensive chart review. Protein expression was measure by Proximity Extension Assay and results were analyzed by logistic regression, gene set enrichment, and protein–protein interactions. Twenty-two patients developed delirium postoperatively (14 older; 8 middle-aged) and 89 proteins in pre- or 1-day postoperative plasma were associated with delirium. A few proteins (IL-8, LTBR, TNF-R2 postoperatively; IL-8, IL-6, LIF, ASGR1 by pre- to postoperative change) and 12 networks were common to delirium in both age groups. However, there were marked differences in the delirium proteome by age; older patients had many more delirium-associated proteins and pathways than middle-aged subjects even though both had the same clinical syndrome. Therefore, there are age-dependent similarities and differences in the plasma proteomic signature of postoperative delirium, which may signify age differences in pathogenesis of the syndrome. [ABSTRACT FROM AUTHOR]

Background Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors. Methods We developed endometrial cancer risk prediction models using data on postmenopausal White women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in 3 cohorts: Nurses' Health Study (NHS), NHS II, and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Results Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% confidence interval [CI] = 0.62 to 0.67) to 0.69 (95% CI = 0.66 to 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in area under the receiver operating characteristic curves in NHS; PLCO = 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall expected-to-observed ratio [E/O]   =   1.09, 95% CI = 0.98 to 1.22) and PLCO (overall E/O   =   1.04, 95% CI = 0.95 to 1.13) but poorly calibrated in NHS (overall E/O   =   0.55, 95% CI = 0.51 to 0.59). Conclusions Using data from the largest, most heterogeneous study population to date (to our knowledge), prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations. [ABSTRACT FROM AUTHOR]

Purpose: We compared a simple breast cancer risk prediction model, BRISK (which includes mammographic density, polygenic risk and clinical factors), against a similar model with more risk factors (simplified Rosner) and against two commonly used clinical models (Gail and IBIS). Methods: Using nested case–control data from the Nurses' Health Study, we compared the models' association, discrimination and calibration. Classification performance was compared between Gail and BRISK for 5-year risks and between IBIS and BRISK for remaining lifetime risk. Results: The odds ratio per standard deviation was 1.43 (95% CI 1.32, 1.55) for BRISK 5-year risk, 1.07 (95% CI 0.99, 1.14) for Gail 5-year risk, 1.72 (95% CI 1.59, 1.87) for simplified Rosner 10-year risk, 1.51 (95% CI 1.41, 1.62) for BRISK remaining lifetime risk and 1.26 (95% CI 1.16, 1.36) for IBIS remaining lifetime risk. The area under the receiver operating characteristic curve (AUC) was improved for BRISK over Gail for 5-year risk (AUC = 0.636 versus 0.511, P < 0.0001) and for BRISK over IBIS for remaining lifetime risk (AUC = 0.647 versus 0.571, P < 0.0001). BRISK was well calibrated for the estimation of both 5-year risk (expected/observed [E/O] = 1.03; 95% CI 0.73, 1.46) and remaining lifetime risk (E/O = 1.01; 95% CI 0.86, 1.17). The Gail 5-year risk (E/O = 0.85; 95% CI 0.58, 1.24) and IBIS remaining lifetime risk (E/O = 0.73; 95% CI 0.60, 0.87) were not well calibrated, with both under-estimating risk. BRISK improves classification of risk compared to Gail 5-year risk (NRI = 0.31; standard error [SE] = 0.031) and IBIS remaining lifetime risk (NRI = 0.287; SE = 0.035). Conclusion: BRISK performs better than two commonly used clinical risk models and no worse compared to a similar model with more risk factors. [ABSTRACT FROM AUTHOR]

With mammography being the primary breast cancer screening strategy, it is essential to make full use of the mammogram imaging data to better identify women who are at higher and lower than average risk. Our primary goal in this study is to extract mammogram-based features that augment the well-established breast cancer risk factors to improve prediction accuracy. In this article, we propose a supervised functional principal component analysis (sFPCA) over triangulations method for extracting features that are ordered by the magnitude of association with the failure time outcome. The proposed method accommodates the irregular boundary issue posed by the breast area within the mammogram imaging data with flexible bivariate splines over triangulations. We also provide an eigenvalue decomposition algorithm that is computationally efficient. Compared to the conventional unsupervised FPCA method, the proposed method results in a lower Brier Score and higher area under the ROC curve (AUC) in simulation studies. We apply our method to data from the Joanne Knight Breast Health Cohort at Siteman Cancer Center. Our approach not only obtains the best prediction performance comparing to unsupervised FPCA and benchmark models but also reveals important risk patterns within the mammogram images. This demonstrates the importance of utilizing additional supervised image-based features to clarify breast cancer risk. [ABSTRACT FROM AUTHOR]

Background Physical activity is generally associated with better outcomes following diagnosis; however, few studies have evaluated change in pre- to postdiagnosis activity and repeated measures of activity by intensity and type. Methods We evaluated physical activity and survival following a breast cancer diagnosis in the Nurses' Health Study and Nurses' Health Study II (n = 9308 women, n = 1973 deaths). Physical activity was evaluated as updated cumulative average of metabolic equivalent of task (MET)-h/wk (assigned per activity based on duration and intensity) and change in pre- to postdiagnosis activity. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results Higher postdiagnosis activity was inversely associated with breast cancer–specific mortality in categories from ≥9 MET-h/wk (vs <3 MET h/wk, HR≥9 to <18 = 0.74 [95% CI = 0.55 to 0.99]; HR≥27 = 0.69 [95% CI = 0.50 to 0.95]; P trend = .04) and all-cause mortality from ≥3 MET-h/wk (HR≥3 to <9 = 0.73 [95% CI = 0.61 to 0.88]; HR≥27 = 0.51 [95% CI = 0.41 to 0.63]; P trend < .001). Associations were predominantly observed for estrogen receptor–positive tumors and in postmenopausal women. Walking was associated with lower risk of all-cause mortality (≥9 vs <3 MET-h/wk, HR= 0.69 [95% CI = 0.57 to 0.84]) as was strength training. Relative to stable activity pre- to postdiagnosis (±3 MET-h/wk), increases from ≥3 to 9 MET-h/wk were associated with lower all-cause mortality risk (P trend < .001). Results were robust to adjustment for prediagnosis physical activity. Conclusions Physical activity was associated with lower risk of death following diagnosis. Increased pre- to postdiagnosis activity corresponding to at least 1-3 h/wk of walking was associated with lower risk of death. These results provide further impetus for women to increase their activity after a breast cancer diagnosis, though reverse causation cannot be fully excluded. [ABSTRACT FROM AUTHOR]

Background: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women's breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women's individualized BC risk and life expectancy. Methods: Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses' Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women's Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. Results: Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784–0.796) in NHS and 0.768 (0.757–0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538–0.641) in NHS and 0.573 (0.536–0.611) in BWHS. Conclusions: We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening. [ABSTRACT FROM AUTHOR]

Published studies report inconsistent associations of polyunsaturated fatty acid (PUFA) intake with non-Hodgkin lymphoma (NHL) risk. We conducted a nested case-control study in Nurses' Health Study and Health Professionals Follow-Up Study participants to evaluate a hypothesis of inverse association of pre-diagnosis red blood cell (RBC) membrane PUFA levels with risk of NHL endpoints. We confirmed 583 NHL cases and matched 583 controls by cohort/sex, age, race and blood draw date/time. We estimated odds ratios (OR) and 95% confidence intervals (CI) for risk of NHL endpoints using logistic regression. RBC PUFA levels were not associated with all NHL risk; cis 20:2n-6 was associated with follicular lymphoma risk (OR [95% CI] per one standard deviation increase: 1.35 [1.03–1.77]), and the omega-6/omega-3 PUFA ratio was associated with diffuse large B-cell lymphoma risk (2.33 [1.23–4.43]). Overall, PUFA did not demonstrate a role in NHL etiology; the two unexpected positive associations lack clear biologic explanations. [ABSTRACT FROM AUTHOR]

Background: We investigated the associations of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) with breast cancer risk by the status of COX-2 protein expression. Methods: This study included 421 cases and 3,166 controls from a nested case–control study within the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) cohorts. Information on medication use was first collected in 1980 (NHS) and 1989 (NHSII) and was updated biennially. Medication use was defined as none, past or current; average cumulative dose and frequency were calculated for all past or current users using data collected from all biannual questionnaires preceding the reference date. Immunochemistry for COX-2 expression was performed using commercial antibody (Cayman Chemical and Thermo Fisher Scientific). We used polychotomous logistic regression to quantify associations of aspirin and NSAIDs with the risk of COX2+ and COX2− breast cancer tumors, while adjusting for known breast cancer risk factors. All tests of statistical significance were two-sided. Results: In multivariate analysis, we found no differences in associations of the aspirin exposures and NSAIDs with breast cancer risk by COX2 expression status. In stratified analyses by COX2 status, significant associations of these medications with breast cancer risk were observed for dosage of aspirin among current users in COX2- tumors (OR for > 5 tablets per week vs. none 1.71, 95% CI 1.01–2.88, p-trend 0.04). Regular aspirin use was marginally associated with the risk of COX2- tumors (p-trend = 0.06). Conclusions: Our findings suggested no differences in associations of aspirin and other NSAIDs with COX2+ and COX2− tumors. [ABSTRACT FROM AUTHOR]

Background Insulin resistance and hyperinsulinemia play important roles in the progression of multiple chronic disease and conditions. Diet modulates insulin response; however, evidence is limited regarding whether diets with higher insulinemic potential increase the risk of invasive breast cancer. Objectives We aimed to prospectively evaluate the association between a food-based empirical dietary index for hyperinsulinemia (EDIH) and the incidence of invasive breast cancer. Methods We prospectively followed 76,686 women from the Nurses' Health Study (NHS; 1984–2016) and 93,287 women from the Nurses' Health Study II (NHSII; 1991–2017). Diet was assessed by food-frequency questionnaires every 4 y. The insulinemic potential of diet was evaluated using the previously established EDIH based on circulating C-peptide concentrations. Higher scores indicate higher insulinemic potential of the diet. Covariates included reproductive, hormonal, and anthropometric factors (height and BMI at age 18 y); race; socioeconomic status; total alcohol intake; total caloric intake; and physical activity. Results During 4,216,106 person-years of follow-up, we documented 10,602 breast cancer cases (6689 NHS, 3913 NHSII). In the pooled multivariable-adjusted analyses, women in the highest, compared with the lowest, EDIH quintile (Q) were at higher breast cancer risk (HRQ5 vs. Q1 = 1.15; 95% CI: 1.07, 1.24; P -trend < 0.01). Although heterogeneity by estrogen receptor (ER) status was nonsignificant, the strongest association between EDIH and breast cancer was observed for ER-negative tumors (HRQ5 vs. Q1 = 1.21; 95% CI: 1.00, 1.46; P -trend = 0.02). Among tumor molecular subtypes, the strongest associations were observed for human epidermal growth factor receptor 2 (HER2)–enriched tumors (HRQ5 vs. Q1 = 1.62; 95% CI: 1.01, 2.61; P -trend = 0.02). Conclusions A dietary pattern contributing to hyperinsulinemia and insulin resistance was associated with greater breast cancer risk, especially ER-negative and HER2-enriched tumors. Our findings suggest that dietary modifications to reduce insulinemic potential may reduce the risk of breast cancer. [ABSTRACT FROM AUTHOR]

Background: Obesity is a risk factor for multiple myeloma (MM), yet results of prior studies have been mixed regarding the importance of early and/or later adult obesity; other measures of body composition have been less well studied.Methods: We evaluated associations of early adult (ages 18-21) and usual adult body mass index (BMI), waist circumference, and predicted fat mass with MM by pooling data from six U.S. prospective cohort studies comprising 544,016 individuals and 2756 incident diagnoses over 20-37 years of follow-up. We used Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations, adjusted for age and other risk factors.Results: Each 5 kg/m2 increase in usual adult BMI was associated with a 10% increased risk of MM (HR: 1.10; 95% CI: 1.05-1.15). Positive associations were also noted for early adult BMI (HR per 5 kg/m2: 1.14; 95% CI: 1.04-1.25), height (HR per 10 cm: 1.28; 95% CI: 1.20-1.37), waist circumference (HR per 15 cm: 1.09; 95% CI: 1.00-1.19), and predicted fat mass (HR per 5 kg: 1.06; 95% CI: 1.01-1.11).Conclusions: These findings highlight the importance of avoidance of overweight/obesity and excess adiposity throughout adulthood as a potential MM risk-reduction strategy. [ABSTRACT FROM AUTHOR]

Background: Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear.Methods: In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis.Results: Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01).Conclusions: Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer. [ABSTRACT FROM AUTHOR]

Background: Pediatric intra-cranial germ cell tumors (iGCTs) occur at an incidence of 0.6–1.2 cases/million/year in Western countries. The incidence is reported up to 5 times higher in Japan. It is unknown whether this increased incidence is due to genetic predisposition or environment. Methods: The incidence of iGCTs in children ages 0–19 years was evaluated from December 1st, 1996-December 1st, 2016 in stable Japanese immigrant populations living abroad and compared to current native Japanese registry data. The incidence of medullobblastoma was used as a control to account for assumptions in the data. Sites were identified based on historical and population data of known large scale emigration from Japan during a period of industrialization from 1868–1912 which resulted in large, stable Japanese immigrant populations abroad. These three representative sites included Lima, Peru, San Paolo, Brazil, and Vancouver, Canada. Data was collected from registry and hospital-based resources within each region. Results: A review of the Brain Tumor Registry of Japan from 1984–2004 revealed an incidence of 2.5 cases/million/year, lower than previously reported, and a lower incidence of medulloblastoma at 1.2 cases/million/year. Data from Vancouver, Canada, Lima, Peru, and San Paolo, Brazil included a total population of 731,174 Japanese persons. The ratio of all medulloblastoma to iGCT cases in Japan was identified as 1:2 while the ratio was 2:1, 6.5:1, and 5:1, respectively, in the other three locations. The data suggests increased incidence in native Japan may not translate to higher incidence in immigrant Japanese populations abroad and a clear genetic component was not found in our data set. Conclusions: A more precise and comprehensive study is needed to determine the cause of this difference in incidence. This study also emphasizes the importance of national and state registries and is a call to collaborate on state and country level epidemiology studies. [ABSTRACT FROM AUTHOR]

Background Many studies have linked intakes of fat and of specific fatty acids during pregnancy with preeclampsia; however, information on the association of intake before pregnancy with hypertensive disorders of pregnancy (HDP) is scant. Objectives We evaluated the associations of intakes of major and specific types of fat before pregnancy with the risks of HDP, including preeclampsia and gestational hypertension (GHTN). Methods We followed 11,535 women without chronic disease participating in the Nurses' Health Study II from 1991 and 2009. Pre-pregnancy dietary fat was assessed by an FFQ. Intakes of total fat, saturated fat, trans fatty acid (TFA), MUFAs, PUFAs, and fat subtypes (omega-3 and omega-6) were categorized into quintiles of intake. HDP were self-reported. The RRs (95% CIs) of HDP were estimated by log-binomial generalized estimating equation regression models, with an exchangeable correlation matrix to account for repeated pregnancies while adjusting for potential confounders. Results During 19 years of follow-up, there were 495 cases of preeclampsia (2.9%) and 561 (3.3%) cases of GHTN in 16,892 singleton pregnancies. The mean age at pregnancy was 34.6 years (SD, 3.9 years). Among major fat types, only pre-pregnancy TFA was related to a higher risk of HDP (RR, 1.32; 95% CI: 1.05–1.66), and only for preeclampsia (RR, 1.50; 95% CI: 1.07–2.10) but not for GHTN (RR, 1.21; 95% CI: 0.87–1.70). Among specific types of PUFAs, intake of arachidonic acid was positively related with GHTN (RR, 1.43; 95% CI: 1.00–2.04) but not preeclampsia (RR, 1.08; 95% CI: 0.75–1.57). In analyses restricted to pregnancies 1 year after the diet assessment, women with the highest intake of long-chain omega-3 fatty acids had a 31% lower risk of HDP (95% CI: 3%–51%), which was driven by preeclampsia (RR, 0.55; 95% CI: 0.33–0.92). Conclusions Pre-pregnancy intakes of total fat, saturated fat, and MUFA were unrelated to HDP, whereas TFA was positively related to HDP. These findings highlight the importance of ongoing efforts to eliminate TFA from the global food supply. [ABSTRACT FROM AUTHOR]

In low- and middle-income countries (LMIC), measurement of symphysis fundal height (SFH) is often the only available method of estimating gestational age (GA) in pregnancy. This systematic review aims to summarize methods of SFH measurement and assess the accuracy of SFH for the purpose of GA estimation. We searched PubMed, EMBASE, Cochrane, Web of Science, POPLINE, and WHO Global Health Libraries from January 1980 through November 2021. For SFH accuracy, we pooled the variance of the mean difference between GA confirmed by ultrasound versus SFH. Of 1,003 studies identified, 37 studies were included. Nineteen different SFH measurement techniques and 13 SFH-to-GA conversion methods were identified. In pooled analysis of five studies (n = 5838 pregnancies), 71% (95% CI: 66–77%) of pregnancies dated by SFH were within ±14 days of ultrasound confirmed dating. Using the 1 cm SFH = 1wk assumption, SFH underestimated GA compared with ultrasound-confirmed GA (mean bias: -14.0 days) with poor accuracy (95% limits of agreement [LOA]: ±42.8 days; n = 3 studies, 2447 pregnancies). Statistical modeling of three serial SFH measurements performed better, but accuracy was still poor (95% LOA ±33 days; n = 4 studies, 4391 pregnancies). In conclusion, there is wide variation in SFH measurement and SFH-to-GA conversion techniques. SFH is inaccurate for estimating GA and should not be used for GA dating. Increasing access to quality ultrasonography early in pregnancy should be prioritized to improve gestational age assessment in LMIC. [ABSTRACT FROM AUTHOR]

Adiposity has been associated with several health conditions as well as timing of menopause. Prior epidemiologic studies on the association of adiposity and anti-Müllerian hormone (AMH) have been inconsistent. We evaluated the relations of anthropometric measures with AMH at two time periods in a subset of premenopausal participants in the Nurses' Health Study II. This prospective study included 795 women who provided a premenopausal sample in 1996–1999 and in 2010–2012. Current weight and height, and weight at age 18 were assessed in 1989 and weight again in 1996–1999. Waist and hip circumference were measured and reported in 1993. In linear regression models adjusted for smoking, reproductive events, and other factors, AMH was inversely related to BMI at age 18 (P =.03) and in 1996–1999 (P <.0001). Higher waist circumference was related to lower AMH levels in 1996–1999 (p =.0009). BMI in 1996–1999 was inversely associated with AMH levels in 2010–2012 (P =.005). Weight gain between age 18 and 1996–1999 was strongly inversely associated with AMH levels in 1996–1999 (P <.0001) and in 2010–2012 (P <.0001). Our results indicate that adiposity and weight gain are associated with lower AMH levels, suggesting an adverse impact on ovarian function. [ABSTRACT FROM AUTHOR]

Background Due to the increasing disease burden, strategies to predict and prevent heart failure (HF) are urgently needed. Objective We aimed to investigate whether the Alternative Healthy Eating Index (AHEI) and the clinically abbreviated Prime Diet Quality Score (PDQS) are associated with the risk of overall HF, HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF). Methods Our study included 44,525 men from the Health Professionals Follow-up Study (HPFS) who were free from cardiovascular disease and cancer at baseline. The AHEI and PDQS were computed based on dietary data repeatedly measured using semiquantitative FFQs. HF, HFpEF, and HFrEF were adjudicated based on review of medical records through 2008. Associations of diet quality with incident HF were estimated with multivariate-adjusted Cox proportional hazards models. Results During 929,911 person-years of follow-up, 803 HF cases were documented, including 184 with HFpEF and 181 with HFrEF among those with ejection fraction (EF) data. Adjusting for potential confounders, we did not observe a significant association between the AHEI and overall HF (HR per SD: 0.96; 95% CI: 0.89, 1.04; P -trend = 0.57) or between the PDQS and overall HF (HR per SD: 0.98; 95% CI: 0.91, 1.06; P -trend = 0.82). Both dietary indices were not significantly associated with HFpEF. However, a higher AHEI was associated with lower risk of HFrEF upon comparison of the extreme quintiles (HR per SD: 0.81; 95% CI: 0.69, 0.96; P -trend = 0.02). Every SD increment in the PDQS was associated with 20% lower risk of HFrEF (HR per SD: 0.80; 95% CI: 0.68, 0.95; P -quadratic = 0.03). Conclusions A healthy overall diet was associated with lower risk of HFrEF, and associations were similar with the AHEI and PDQS. We did not observe a significant association between dietary indices and either overall HF or HFpEF. [ABSTRACT FROM AUTHOR]

In 2022, more than 100 000 non‐Hodgkin lymphoma (NHL) diagnoses are expected, yet few risk factors are confirmed. In this study, data from six US‐based cohorts (568 717 individuals) were used to examine body size and risk of NHL. Over more than 20 years of follow‐up, 11 263 NHLs were identified. Hazard ratios (HRs) and 95% confidence intervals (CI) estimated associations with NHLs for adult body mass index (BMI), height, weight change, waist circumference and predicted fat mass. Adult height was broadly associated with NHL, but most strongly with B‐cell NHLs among non‐White participants (e.g. HRBLACK = 2.06, 95% CI: 1.62–2.62). However, the strongest association among the anthropometric traits examined was for young adult BMI and risk of diffuse large B‐cell lymphoma (DLBCL), particularly those who maintained a higher BMI into later adulthood. Individuals with BMI over 30 kg/m2 throughout adulthood had more than double the DLBCL risk (HR = 2.67, 95% CI: 1.71–4.17) compared to BMI 18.5–22.9 kg/m2. Other anthropometric traits were not associated with NHL after controlling for BMI. These results suggest that sustained high BMI is a major driver of DLBCL risk. If confirmed, we estimate that up to 23.5% of all DLBCLs (and 11.1% of all NHLs) may be prevented with avoidance of young adult obesity. [ABSTRACT FROM AUTHOR]

Background: Epidemiological studies have demonstrated a favorable association of whole grain intake with coronary heart disease (CHD) risk, although whether such an inverse association holds true for individual whole grain foods that have various nutritional profiles has not been examined.Methods: We followed 74,244 women from Nurses' Health Study since 1986, 91,430 women from Nurses' Health Study II since 1991, and 39,455 men from the Health Professionals Follow-Up Study since 1984, who did not have a history of cardiovascular disease or cancer at baseline. Intake of seven individual whole grain foods was repeatedly assessed using a validated semi-quantitative food frequency questionnaire every 2-4 years since baseline. CHD diagnoses were ascertained through review of medical records or death certificates.Results: We documented 9461 CHD cases during an average of 25.8 years' follow-up. In the multivariable-adjusted model, the pooled hazard ratio (HR) (95% CI) of CHD risk corresponding to each one serving/day consumption of total whole grains was 0.93 (0.90-0.95; p trend <0.0001). Higher consumption of most individual whole grain foods was associated with significantly lower risk of CHD. Comparing participants consuming ≥1 serving/day with those consuming < 1 serving/month, the multivariable-adjusted pooled HRs (95% CIs) of CHD were 0.83 (0.78-0.89) for whole grain cold breakfast cereal, 0.92 (0.86-0.99) for dark bread, and 1.08 (0.96-1.22) for popcorn. For other whole grain foods with lower overall intake levels, comparing intake level of ≥2 servings/week with < 1 serving/month, the pooled hazard ratios (95% CIs) were 0.79 (0.74-0.84) for oatmeal, 0.79 (0.71-0.87) for brown rice, 0.84 (0.78-0.90) for added bran, and 0.87 (0.77-0.99) for wheat germ. Cubic spline regression suggested non-linear associations for certain whole grain foods: the risk reduction plateaued approximately over 2 servings/day for total whole grains, 0.5 serving/day for both cold breakfast cereal and dark bread, 0.5 serving/week for oatmeal, 1 serving/week for brown rice, and 2 serving/week for added bran (p for non-linearity <0.01 for all associations).Conclusions: These data suggest that higher consumption of total whole grains, as well as individual whole grain foods except popcorn, were significantly associated with lower CHD risk. The inverse associations may plateau at various intake levels for total whole grain and individual whole grain foods. This study provides further evidence in support of increasing whole grain intake for the prevention of CHD in US populations. [ABSTRACT FROM AUTHOR]