Impact of gender and mutational differences in hormone receptor expressing non-small cell lung cancer.

Background: The incidence of lung cancer in the US has been decreasing but a bigger decline has been observed in men despite similar declines in tobacco use between men and women. Multiple theories have been proposed, including exposure to exogenous estrogens. Our study seeks to understand the relationship between hormone receptors (HR), gender, and the genomic landscape of non-small lung cancer (NSCLC). Methods: 3,256 NSCLC tumor samples submitted for molecular profiling between 2013-2018 were retrospectively identified and assessed for HR expression. Hormone receptor (HR+) was defined as ≥ 1% nuclear staining of estrogen receptor-alpha (ER-a) or progesterone receptor (PR) by immunohistochemistry. DNA sequencing by NGS included cases sequenced by the Illumina MiSeq hot spot 47 gene panel (n=2753) and Illumina NextSeq 592 gene panel (n=503). An adjusted p-value (q-value) <0.05 was determined significant. Results: HR+ was identified in 18.3% of NSCLC. HR+ occurred more commonly in women compared to men (19.6% vs 11.4%, p <0.0001, q <0.0001). EGFR mutations occurred more commonly in HR+ NSCLC than HR- NSCLC (20.2% vs. 14.6%, p = 0.002, q=0.007). Overall, men with EGFR mutations were affected by HR status with a higher prevalence in HR+ NSCLC while such differences were not seen in women. However, in women ages ≤45, there was a trend towards greater prevalence HR+ NSCLC (25.25% vs. 11.32%, q= 0.0942) and 10/25 (40.0%) of HR+ cases in young women were found to be EGFR mutated. KRAS mutations and ALK+ IHC expression occurred more in HR+ NSCLC whereas TP53 mutations occurred more in HR- NSCLC. Conclusions: Women were more likely to have HR+ NSCLC than men and EGFR and KRAS mutations occurred more commonly in HR+ NSCLC. Additional studies with more strict inclusion criteria for HR+ are warranted to see if there is benefit to targeting HR in these subgroups.

Florida-California Cancer Research, Education and Engagement (CaRE2) Health Equity Center: Structure, Innovations, and Initial Outcomes.

INTRODUCTION: The Florida-California Cancer Research, Education, and Engagement (CaRE2) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE2 triad partnership. METHODS: CaRE2 serves diverse populations in Florida and California using a "molecule to the community and back" model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. RESULTS: Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE2-related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. CONCLUSION: The CaRE2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.

Human Papillomavirus and Rising Oropharyngeal Cancer Incidence in the United States.

PURPOSE: Recent increases in incidence and survival of oropharyngeal cancers in the United States have been attributed to human papillomavirus (HPV) infection, but empirical evidence is lacking. PATIENTS AND METHODS: HPV status was determined for all 271 oropharyngeal cancers (1984-2004) collected by the three population-based cancer registries in the Surveillance, Epidemiology, and End Results (SEER) Residual Tissue Repositories Program by using polymerase chain reaction and genotyping (Inno-LiPA), HPV16 viral load, and HPV16 mRNA expression. Trends in HPV prevalence across four calendar periods were estimated by using logistic regression. Observed HPV prevalence was reweighted to all oropharyngeal cancers within the cancer registries to account for nonrandom selection and to calculate incidence trends. Survival of HPV-positive and HPV-negative patients was compared by using Kaplan-Meier and multivariable Cox regression analyses. RESULTS: HPV prevalence in oropharyngeal cancers significantly increased over calendar time regardless of HPV detection assay (P trend < .05). For example, HPV prevalence by Inno-LiPA increased from 16.3% during 1984 to 1989 to 71.7% during 2000 to 2004. Median survival was significantly longer for HPV-positive than for HPV-negative patients (131 v 20 months; log-rank P < .001; adjusted hazard ratio, 0.31; 95% CI, 0.21 to 0.46). Survival significantly increased across calendar periods for HPV-positive (P = .003) but not for HPV-negative patients (P = .18). Population-level incidence of HPV-positive oropharyngeal cancers increased by 225% (95% CI, 208% to 242%) from 1988 to 2004 (from 0.8 per 100,000 to 2.6 per 100,000), and incidence for HPV-negative cancers declined by 50% (95% CI, 47% to 53%; from 2.0 per 100,000 to 1.0 per 100,000). If recent incidence trends continue, the annual number of HPV-positive oropharyngeal cancers is expected to surpass the annual number of cervical cancers by the year 2020. CONCLUSION: Increases in the population-level incidence and survival of oropharyngeal cancers in the United States since 1984 are caused by HPV infection.

Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization.

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10-9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10-4-5.79 × 10-14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10-4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10-4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10-4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3- B cells, CD5+IgD- cells, IgM- cells, IgD-IgM- cells, and CD4-CD8- PBMCs (p = 4.9 × 10-4-8.6 × 10-4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27- cells (p = 9.3 × 10-4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3-, MCP-2-, and IL20-dependent pathways.

A pleiotropic variant in DNAJB4 is associated with multiple myeloma risk.

Pleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome-wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5 × 10-8 ) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4-rs34517439-A and an increased risk of developing MM (OR = 1.22, 95%CI 1.13-1.32, P = 4.81 × 10-7 ). rs34517439-A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA-binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4-rs34517439 as a potentially novel MM risk locus.

Alcohol and tobacco use and risk of multiple myeloma: A case-control study.

Multiple myeloma (MM) is the second most common hematological cancer and causes significant mortality and morbidity. Knowledge regarding modifiable risk factors for MM remains limited. This analysis of an Australian population-based case-control family study investigates whether smoking or alcohol consumption is associated with risk of MM and related diseases. Incident cases (n = 789) of MM were recruited via cancer registries in Victoria and New South Wales. Controls (n = 1,113) were either family members of cases (n = 696) or controls recruited for a similarly designed study of renal cancers (n = 417). Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional multivariable logistic regression. Heavy intake (>20 g ethanol/day) of alcohol had a lower risk of MM compared with nondrinkers (OR = 0.68, 95% CI: 0.50-0.93), and there was an inverse dose-response relationship for average daily alcohol intake (OR per 10 g ethanol per day = 0.92, 95% CI: 0.86-0.99); there was no evidence of an interaction with sex. There was no evidence of an association with MM risk for smoking-related exposures (p > 0.18). The associations between smoking and alcohol with MM are similar to those with non-Hodgkin lymphoma. Further research into potential underlying mechanisms is warranted.

Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?

BACKGROUND: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. METHODS: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. RESULTS: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P < 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. CONCLUSIONS: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. IMPACT: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

B-Cell NHL Subtype Risk Associated with Autoimmune Conditions and PRS.

BACKGROUND: A previous International Lymphoma Epidemiology (InterLymph) Consortium evaluation of joint associations between five immune gene variants and autoimmune conditions reported interactions between B-cell response-mediated autoimmune conditions and the rs1800629 genotype on risk of B-cell non-Hodgkin lymphoma (NHL) subtypes. Here, we extend that evaluation using NHL subtype-specific polygenic risk scores (PRS) constructed from loci identified in genome-wide association studies of three common B-cell NHL subtypes. METHODS: In a pooled analysis of NHL cases and controls of Caucasian descent from 14 participating InterLymph studies, we evaluated joint associations between B-cell-mediated autoimmune conditions and tertile (T) of PRS for risk of diffuse large B-cell lymphoma (DLBCL; n = 1,914), follicular lymphoma (n = 1,733), and marginal zone lymphoma (MZL; n = 407), using unconditional logistic regression. RESULTS: We demonstrated a positive association of DLBCL PRS with DLBCL risk [T2 vs. T1: OR = 1.24; 95% confidence interval (CI), 1.08-1.43; T3 vs. T1: OR = 1.81; 95% CI, 1.59-2.07; P-trend (Ptrend) < 0.0001]. DLBCL risk also increased with increasing PRS tertile among those with an autoimmune condition, being highest for those with a B-cell-mediated autoimmune condition and a T3 PRS [OR = 6.46 vs. no autoimmune condition and a T1 PRS, Ptrend < 0.0001, P-interaction (Pinteraction) = 0.49]. Follicular lymphoma and MZL risk demonstrated no evidence of joint associations or significant Pinteraction. CONCLUSIONS: Our results suggest that PRS constructed from currently known subtype-specific loci may not necessarily capture biological pathways shared with autoimmune conditions. IMPACT: Targeted genetic (PRS) screening among population subsets with autoimmune conditions may offer opportunities for identifying those at highest risk for (and early detection from) DLBCL.

Longitudinal SARS-CoV-2 mRNA Vaccine-Induced Humoral Immune Responses in Patients with Cancer.

Longitudinal studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine-induced immune responses in patients with cancer are needed to optimize clinical care. In a prospective cohort study of 366 (291 vaccinated) patients, we measured antibody levels [anti-spike (IgG-(S-RBD) and anti-nucleocapsid immunoglobulin] at three time points. Antibody level trajectories and frequency of breakthrough infections were evaluated by tumor type and timing of treatment relative to vaccination. IgG-(S-RBD) at peak response (median = 42 days after dose 2) was higher (P = 0.002) and remained higher after 4 to 6 months (P = 0.003) in patients receiving mRNA-1273 compared with BNT162b2. Patients with solid tumors attained higher peak levels (P = 0.001) and sustained levels after 4 to 6 months (P < 0.001) compared with those with hematologic malignancies. B-cell targeted treatment reduced peak (P = 0.001) and sustained antibody responses (P = 0.003). Solid tumor patients receiving immune checkpoint inhibitors before vaccination had lower sustained antibody levels than those who received treatment after vaccination (P = 0.043). Two (0.69%) vaccinated and one (1.9%) unvaccinated patient had severe COVID-19 illness during follow-up. Our study shows variation in sustained antibody responses across cancer populations receiving various therapeutic modalities, with important implications for vaccine booster timing and patient selection. SIGNIFICANCE: Long-term studies of immunogenicity of SARS-CoV-2 vaccines in patients with cancer are needed to inform evidence-based guidelines for booster vaccinations and to tailor sequence and timing of vaccinations to elicit improved humoral responses.

Lymphoma-Associated Biomarkers Are Increased in Current Smokers in Twin Pairs Discordant for Smoking.

Smoking is associated with a moderate increased risk of Hodgkin and follicular lymphoma. To understand why, we examined lymphoma-related biomarker levels among 134 smoking and non-smoking twins (67 pairs) ascertained from the Finnish Twin Cohort. Previously collected frozen serum samples were tested for cotinine to validate self-reported smoking history. In total, 27 immune biomarkers were assayed using the Luminex Multiplex platform (R & D Systems). Current and non-current smokers were defined by a serum cotinine concentration of >3.08 ng/mL and ≤3.08 ng/mL, respectively. Associations between biomarkers and smoking were assessed using linear mixed models to estimate beta coefficients and standard errors, adjusting for age, sex and twin pair as a random effect. There were 55 never smokers, 43 current smokers and 36 former smokers. CCL17/TARC, sgp130, haptoglobin, B-cell activating factor (BAFF) and monocyte chemoattractant protein-1 (MCP1) were significantly (p < 0.05) associated with current smoking and correlated with increasing cotinine concentrations (Ptrend < 0.05). The strongest association was observed for CCL17/TARC (Ptrend = 0.0001). Immune biomarker levels were similar in former and never smokers. Current smoking is associated with increased levels of lymphoma-associated biomarkers, suggesting a possible mechanism for the link between smoking and risk of these two B-cell lymphomas.

Genome-wide homozygosity and risk of four non-Hodgkin lymphoma subtypes.

AIM: Recessive genetic variation is thought to play a role in non-Hodgkin lymphoma (NHL) etiology. Runs of homozygosity (ROH), defined based on long, continuous segments of homozygous SNPs, can be used to estimate both measured and unmeasured recessive genetic variation. We sought to examine genome-wide homozygosity and NHL risk. METHODS: We used data from eight genome-wide association studies of four common NHL subtypes: 3061 chronic lymphocytic leukemia (CLL), 3814 diffuse large B-cell lymphoma (DLBCL), 2784 follicular lymphoma (FL), and 808 marginal zone lymphoma (MZL) cases, as well as 9374 controls. We examined the effect of homozygous variation on risk by: (1) estimating the fraction of the autosome containing runs of homozygosity (FROH); (2) calculating an inbreeding coefficient derived from the correlation among uniting gametes (F3); and (3) examining specific autosomal regions containing ROH. For each, we calculated beta coefficients and standard errors using logistic regression and combined estimates across studies using random-effects meta-analysis. RESULTS: We discovered positive associations between FROH and CLL (ß = 21.1, SE = 4.41, P = 1.6 × 10-6) and FL (ß = 11.4, SE = 5.82, P = 0.02) but not DLBCL (P = 1.0) or MZL (P = 0.91). For F3, we observed an association with CLL (ß = 27.5, SE = 6.51, P = 2.4 × 10-5). We did not find evidence of associations with specific ROH, suggesting that the associations observed with FROH and F3 for CLL and FL risk were not driven by a single region of homozygosity. CONCLUSION: Our findings support the role of recessive genetic variation in the etiology of CLL and FL; additional research is needed to identify the specific loci associated with NHL risk.

Mode of Delivery, Birth Characteristics, and Early-Onset Non-Hodgkin Lymphoma in a Population-Based Case-Control Study.

BACKGROUND: The etiology of non-Hodgkin lymphoma (NHL) in children and in adolescents and young adults (AYA) is not well understood. METHODS: We evaluated potential associations between mode of delivery, birth characteristics, and NHL risk in a population-based case-control study, which included 3,064 cases of NHL [490 with Burkitt lymphoma, 981 with diffuse large B-cell lymphoma (DLBCL), and 978 with T-cell NHL) diagnosed at the age of 0 to 37 years in California during 1988 to 2015 and 153,200 controls frequency matched on year of birth. Odds ratios (OR) and 95% confidence intervals (CI) were estimated from an unconditional multivariable logistic regression model that included year of birth and birth characteristics. RESULTS: Individuals born via cesarean section had a decreased risk of pediatric Burkitt lymphoma (age 0-14 years; OR = 0.71, 95% CI: 0.51-0.99) and pediatric T-cell NHL (OR = 0.73, 95% CI: 0.55-0.97) compared with those born vaginally. Having a birth order of second (OR = 0.73, 95% CI: 0.57-0.93) or third or higher (OR = 0.76, 95% CI: 0.58-0.99) was associated with a lower risk of pediatric T-cell NHL compared with first-borns. AYA (age 15-37 years) with a heavier birthweight had an elevated risk of DLBCL (OR for each kg = 1.16, 95% CI: 1.00-1.35). Associations between other birth characteristics, including plurality, maternal age, maternal education, and NHL risk, also exhibited variations across subgroups based on age of diagnosis and histologic subtype. CONCLUSIONS: These findings support a role of mode of delivery and birth characteristics in the etiology of early-onset NHL. IMPACT: This study underscores the etiologic heterogeneity of early-onset NHL.

An integrated risk and epidemiological model to estimate risk-stratified COVID-19 outcomes for Los Angeles County: March 1, 2020-March 1, 2021.

The objective of this study was to use available data on the prevalence of COVID-19 risk factors in subpopulations and epidemic dynamics at the population level to estimate probabilities of severe illness and the case and infection fatality rates (CFR and IFR) stratified across subgroups representing all combinations of the risk factors age, comorbidities, obesity, and smoking status. We focus on the first year of the epidemic in Los Angeles County (LAC) (March 1, 2020-March 1, 2021), spanning three epidemic waves. A relative risk modeling approach was developed to estimate conditional effects from available marginal data. A dynamic stochastic epidemic model was developed to produce time-varying population estimates of epidemic parameters including the transmission and infection observation rate. The epidemic and risk models were integrated to produce estimates of subpopulation-stratified probabilities of disease progression and CFR and IFR for LAC. The probabilities of disease progression and CFR and IFR were found to vary as extensively between age groups as within age categories combined with the presence of absence of other risk factors, suggesting that it is inappropriate to summarize epidemiological parameters for age categories alone, let alone the entire population. The fine-grained subpopulation-stratified estimates of COVID-19 outcomes produced in this study are useful in understanding disparities in the effect of the epidemic on different groups in LAC, and can inform analyses of targeted subpopulation-level policy interventions.

Genetically Raised Circulating Bilirubin Levels and Risk of Ten Cancers: A Mendelian Randomization Study.

Bilirubin, an endogenous antioxidant, may play a protective role in cancer development. We applied two-sample Mendelian randomization to investigate whether genetically raised bilirubin levels are causally associated with the risk of ten cancers (pancreas, kidney, endometrium, ovary, breast, prostate, lung, Hodgkin's lymphoma, melanoma, and neuroblastoma). The number of cases and their matched controls of European descent ranged from 122,977 and 105,974 for breast cancer to 1200 and 6417 for Hodgkin's lymphoma, respectively. A total of 115 single-nucleotide polymorphisms (SNPs) associated (p < 5 × 10-8) with circulating total bilirubin, extracted from a genome-wide association study in the UK Biobank, were used as instrumental variables. One SNP (rs6431625) in the promoter region of the uridine-diphosphoglucuronate glucuronosyltransferase1A1 (UGT1A1) gene explained 16.9% and the remaining 114 SNPs (non-UGT1A1 SNPs) explained 3.1% of phenotypic variance in circulating bilirubin levels. A one-standarddeviation increment in circulating bilirubin (≈ 4.4 µmol/L), predicted by non-UGT1A1 SNPs, was inversely associated with risk of squamous cell lung cancer and Hodgkin's lymphoma (odds ratio (OR) 0.85, 95% confidence interval (CI) 0.73-0.99, P 0.04 and OR 0.64, 95% CI 0.42-0.99, p 0.04, respectively), which was confirmed after removing potential pleiotropic SNPs. In contrast, a positive association was observed with the risk of breast cancer after removing potential pleiotropic SNPs (OR 1.12, 95% CI 1.04-1.20, p 0.002). There was little evidence for robust associations with the other seven cancers investigated. Genetically raised bilirubin levels were inversely associated with risk of squamous cell lung cancer as well as Hodgkin's lymphoma and positively associated with risk of breast cancer. Further studies are required to investigate the utility of bilirubin as a low-cost clinical marker to improve risk prediction for certain cancers.

Estimation of COVID-19 risk-stratified epidemiological parameters and policy implications for Los Angeles County through an integrated risk and stochastic epidemiological model.

Background: Health disparities have emerged with the COVID-19 epidemic because the risk of exposure to infection and the prevalence of risk factors for severe outcomes given infection vary within and between populations. However, estimated epidemic quantities such as rates of severe illness and death, the case fatality rate (CFR), and infection fatality rate (IFR), are often expressed in terms of aggregated population-level estimates due to the lack of epidemiological data at the refined subpopulation level. For public health policy makers to better address the pandemic, stratified estimates are necessary to investigate the potential outcomes of policy scenarios targeting specific subpopulations. Methods: We develop a framework for using available data on the prevalence of COVID-19 risk factors (age, comorbidities, BMI, smoking status) in subpopulations, and epidemic dynamics at the population level and stratified by age, to estimate subpopulation-stratified probabilities of severe illness and the CFR (as deaths over observed infections) and IFR (as deaths over estimated total infections) across risk profiles representing all combinations of risk factors including age, comorbidities, obesity class, and smoking status. A dynamic epidemic model is integrated with a relative risk model to produce time-varying subpopulation-stratified estimates. The integrated model is used to analyze dynamic outcomes and parameters by population and subpopulation, and to simulate alternate policy scenarios that protect specific at-risk subpopulations or modify the population-wide transmission rate. The model is calibrated to data from the Los Angeles County population during the period March 1 - October 15 2020. Findings: We estimate a rate of 0.23 (95% CI: 0.13,0.33) of infections observed before April 15, which increased over the epidemic course to 0.41 (0.11,0.69). Overall population-average IFR( t ) estimates for LAC peaked at 0.77% (0.38%,1.15%) on May 15 and decreased to 0.55% (0.24%,0.90%) by October 15. The population-average IFR( t ) stratified by age group varied extensively across subprofiles representing each combination of the additional risk factors considered (comorbidities, BMI, smoking). We found median IFRs ranging from 0.009%-0.04% in the youngest age group (0-19), from 0.1%-1.8% for those aged 20-44, 0.36%-4.3% for those aged 45-64, and 1.02%-5.42% for those aged 65+. In the group aged 65+ for which the rate of unobserved infections is likely much lower, we find median CFRs in the range 4.4%-23.45%. The initial societal lockdown period avoided overwhelming healthcare capacity and greatly reduced the observed death count. In comparative scenario analysis, alternative policies in which the population-wide transmission rate is reduced to a moderate and sustainable level of non-pharmaceutical interventions (NPIs) would not have been sufficient to avoid overwhelming healthcare capacity, and additionally would have exceeded the observed death count. Combining the moderate NPI policy with stringent protection of the at-risk subpopulation of individuals 65+ would have resulted in a death count similar to observed levels, but hospital counts would have approached capacity limits. Interpretation: The risk of severe illness and death of COVID-19 varies tremendously across subpopulations and over time, suggesting that it is inappropriate to summarize epidemiological parameters for the entire population and epidemic time period. This includes variation not only across age groups, but also within age categories combined with other risk factors analyzed in this study (comorbidities, obesity status, smoking). In the policy analysis accounting for differences in IFR across risk groups in comparing the control of infections and protection of higher risk groups, we find that the strict initial lockdown period in LAC was effective because it both reduced overall transmission and protected individuals at greater risk, resulting in preventing both healthcare overload and deaths. While similar numbers of deaths as observed in LAC could have been achieved with a more moderate NPI policy combined with greater protection of individuals 65+, this would have come at the expense of overwhelming the healthcare system. In anticipation of a continued rise in cases in LAC this winter, policy makers need to consider the trade offs of various policy options on the numbers of the overall population that may become infected, severely ill, and that die when considering policies targeted at subpopulations at greatest risk of transmitting infection and at greatest risk for developing severe outcomes.

Dietary glycemic index, glycemic load, and lung cancer risk: A case-control study in Los Angeles County.

BACKGROUND: Although there is some evidence of positive associations between both the glycemic index (GI) and glycemic load (GL) with cancer risk, the relationships with lung cancer risk remain largely unexplored. We evaluated the associations between GI and GL with lung cancer. METHODS: The analyses were performed using data from a population-based case-control study recruited between 1999 and 2004 in Los Angeles County. Dietary factors were collected from 593 incident lung cancer cases and 1026 controls using a modified food frequency questionnaire. GI and GL were estimated using a food composition table. Adjusted odds ratios (ORs) and 95 % confidence intervals (CI) were estimated using unconditional logistic regression adjusting for potential confounders. RESULTS: Dietary GI was positively associated with lung cancer (OR for upper vs. lower tertile = 1.62; 95 % CI: 1.17, 2.25). For histologic subtypes, positive associations were observed between GI and adenocarcinoma (OR for upper vs. lower tertile = 1.82; 95 % CI: 1.22, 2.70) and small cell carcinoma (OR for upper vs. lower tertile = 2.68; 95 % CI: 1.25, 5.74). No clear association between GL and lung cancer was observed. CONCLUSION: These findings suggest that high dietary GI was associated with increased lung cancer risk, and the positive associations were observed for both lung adenocarcinoma and small cell lung carcinoma. Replication in an independent dataset is merited for a broader interpretation of our results.