Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model–based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.Objective To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model—a well-established risk prediction model based on a predominantly White population—across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.Design, Setting, and Participants In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.Exposures The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.Outcomes Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).Results Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity–specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).Conclusions The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits

Genetic risk factors for body mass index and obesity in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) Study

Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups. As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated the association between thirteen GWAS-identified SNPs and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated beta coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI. By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians. Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations

The temporal reliability of serum estrogens, progesterone, gonadotropins, SHBG and urinary estrogen and progesterone metabolites in premenopausal women

BACKGROUND: There is little existing research to guide researchers in estimating the minimum number of measurement occasions required to obtain reliable estimates of serum estrogens, progesterone, gonadotropins, sex hormone-binding globulin (SHBG), and urinary estrogen and progesterone metabolites in premenopausal women. METHODS: Using data from a longitudinal study of 34 women with a mean age of 42.3 years (SD = 2.6), we calculated the minimum number of measurement occasions required to obtain reliable estimates of 12 analytes (8 in blood, 4 in urine). Five samples were obtained over 1 year: at baseline, and after 1, 3, 6, and 12 months. We also calculated the percent of true variance accounted for by a single measurement and intraclass correlation coefficients (ICC) between measurement occasions. RESULTS: Only 2 of the 12 analytes we examined, SHBG and estrone sulfate (E(1)S), could be adequately estimated by a single measurement using a minimum reliability standard of having the potential to account for 64% of true variance. Other analytes required from 2 to 12 occasions to account for 81% of the true variance, and 2 to 5 occasions to account for 64% of true variance. ICCs ranged from 0.33 for estradiol (E(2)) to 0.88 for SHBG. Percent of true variance accounted for by single measurements ranged from 29% for luteinizing hormone (LH) to 92% for SHBG. CONCLUSIONS: Experimental designs that take the natural variability of these analytes into account by obtaining measurements on a sufficient number of occasions will be rewarded with increased power and accuracy

Association Between Menopausal Estrogen-Only Therapy and Ovarian Carcinoma Risk

OBJECTIVE: To describe the association between postmenopausal estrogen-only therapy use and risk of ovarian carcinoma, specifically with regard to disease histotype and duration and timing of use. METHODS: We conducted a pooled analysis of 906 women with ovarian carcinoma and 1,220 women in a control group; all 2,126 women included reported having had a hysterectomy. Ten population-based case-control studies participating in the Ovarian Cancer Association Consortium, an international consortium whose goal is to combine data from many studies with similar methods so reliable assessments of risk factors can be determined, were included. Self-reported questionnaire data from each study were harmonized and conditional logistic regression was used to examine estrogen-only therapy's histotype-specific and duration and recency of use associations. RESULTS: Forty-three and a half percent of the women in the control group reported previous use of estrogen-only therapy. Compared with them, current or recent estrogen-only therapy use was associated with an increased risk for the serous (51.4%, odds ratio [OR] 1.63, 95% confidence interval [CI] 1.27-2.09) and endometrioid (48.6%, OR 2.00, 95% CI 1.17-3.41) histotypes. In addition, statistically significant trends in risk according to duration of use were seen among current or recent postmenopausal estrogen-only therapy users for both ovarian carcinoma histotypes (Ptrend<.001 for serous and endometrioid). Compared with women in the control group, current or recent users for 10 years or more had increased risks of serous ovarian carcinoma (36.8%, OR 1.73, 95% CI 1.26-2.38) and endometrioid ovarian carcinoma (34.9%, OR 4.03, 95% CI 1.91-8.49). CONCLUSION: We found evidence of an increased risk of serous and endometrioid ovarian carcinoma associated with postmenopausal estrogen-only therapy use, particularly of long duration. These findings emphasize that risk may be associated with extended estrogen-only therapy use

Estrogen Receptor Beta rs1271572 Polymorphism and Invasive Ovarian Carcinoma Risk: Pooled Analysis within the Ovarian Cancer Association Consortium

The association of ovarian carcinoma risk with the polymorphism rs1271572 in the estrogen receptor beta (ESR2) gene was examined in 4946 women with primary invasive ovarian carcinoma and 6582 controls in a pooled analysis of ten case-control studies within the Ovarian Cancer Association Consortium (OCAC). All participants were non-Hispanic white women. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression adjusted for site and age. Women with the TT genotype were at increased risk of ovarian carcinoma compared to carriers of the G allele (OR = 1.10; 95%; CI: 1.01-1.21; p = 0.04); the OR was 1.09 (CI: 0.99-1.20; p = 0.07) after excluding data from the center (Hawaii) that nominated this SNP for OCAC genotyping A stronger association of rs1271572 TT versus GT/GG with risk was observed among women aged <= 50 years versus older women (OR = 1.35; CI: 1.12-1.62; p = 0.002; p for interaction = 0.02) that remained statistically significant after excluding Hawaii data (OR = 1.34; CI: 1.11-1.61; p = 0.009). No heterogeneity of the association was observed by study, menopausal status, gravidity, parity, use of contraceptive or menopausal hormones, tumor histological type, or stage at diagnosis. This pooled analysis suggests that rs1271572 might influence the risk of ovarian cancer, in particular among younger women

Vitamin D receptor rs2228570 polymorphism and invasive ovarian carcinoma risk: Pooled analysis in five studies within the Ovarian Cancer Association Consortium

The association of invasive ovarian carcinoma risk with the functional polymorphism rs2228570 (aka rs10735810; FokI polymorphism) in the vitamin D receptor (VDR) gene was examined in 1820 white non-Hispanic cases and 3479 controls in a pooled analysis of five population-based case-control studies within the Ovarian Cancer Association Consortium. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression. Carriers of the rare T allele were at increased risk of ovarian carcinoma compared to women with the CC genotype in all studies combined; each copy of the T allele was associated with a modest 9% increased risk (OR=1.09; 95% CI:1.01–1.19; p=0.04). No significant heterogeneity among studies was observed (p=0.37) and, after excluding the dataset from the Hawaii study, the risk association for rs2228570 among replication studies was unchanged (OR=1.09; 95% CI: 1.00–1.19; p=0.06). A stronger association of rs2228570 with risk was observed among younger women (aged < 50 years versus 50 years or older) (p=0.04). In all studies combined, the increased risk per copy of the T allele among younger women was 24% (OR=1.24; 95% CI: 1.04–1.47; p=0.02). This association remained statistically significant after excluding the Hawaii data (OR= 1.20; 95% CI: 1.01–1.43; p=0.04). No heterogeneity of the association was observed by stage (p= 0.46), tumor histology (p=0.98), or time between diagnosis and interview (p=0.94). This pooled analysis provides further evidence that the VDR rs2228570 polymorphism might influence ovarian cancer susceptibility

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity and Hormone-Related Risk Factors

BACKGROUND: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. RESULTS: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)). CONCLUSIONS: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT