Population-based Analyses Research Articles

Health Disparities and Inequities in the Utilization of Proton Therapy for Prostate Cancer

Our study sought to review and summarize the reported health disparities and inequities in the utilization of proton beam therapy (PBT) for prostate cancer. We queried the PubMed search engine through 12/2023 for original publications examining disparate utilization of PBT for prostate cancer. The query terms included the following: prostate cancer AND proton AND (disparities OR IMRT OR race OR insurance OR socioeconomic OR inequities)”. Studies were included if they involved United States patients, examined PBT in prostate cancer, and addressed health inequities. From this query, 22 studies met the inclusion criteria, comprising 13 population-based analyses, 5 single-institutional analyses, 3 cost/modeling investigations, and 1 survey-based study. The analyses revealed that in addition to age-related and insurance-related disparities, race and socioeconomic status played significant roles in the receipt of PBT. The likelihood of receiving PBT was lower for non-White patients in population-based and single-institution analyses. Socioeconomic metrics, such as higher median income and higher education level, portended an increased likelihood of receiving PBT. Conclusively, substantial age-based, racial, socioeconomic/insurance-related, and facility-associated disparities and inequities existed for PBT utilization in prostate cancer. The identification of these disparities provides a framework to better address these as the utility of PBT continues to expand across the US and globally.

Abstract 4139144: "Comparative Analysis of Inpatient Outcomes: Decompensated Systolic Heart Failure (HFrEF) with and without Iron Deficiency Anemia, Propensity-Matched Nationwide Study (2017-2021)."

Background: Iron deficiency anemia (IDA) affects approximately one-third of patients with systolic heart failure, yet comprehensive population-based analyses of its impact on in-hospital outcomes remain limited. This study seeks to examine how IDA influences in-hospital outcomes among individuals with decompensated systolic congestive heart failure (HFrEF). Methods: Using data from the National Inpatient Sample (NIS) database spanning from 2017 to 2021, this study identified patients hospitalized for decompensated systolic congestive heart failure (HFrEF) with a secondary diagnosis of IDA using ICD-10 codes such as I5020-23 and D500, D501, D508, D509. Propensity score matching (PSM) was then employed to create cohorts without and with IDA at a 1:3 ratio. Multivariate regression analyses were conducted to evaluate various outcomes, including in-hospital mortality, cardiogenic shock (CS), acute myocardial injury (AMI), cardiac arrest, ventricular tachycardia (VT), ventricular fibrillation (VF), length of stay (LOS), and total hospitalization charges. Furthermore, the utilization rate of mechanical ventilation and circulatory support, including intra-aortic balloon pump and extracorporeal membrane oxygenation, was evaluated in both cohorts. Results: Among 253,034 HFrEF hospitalizations, 16,200 (6.4%) had a secondary diagnosis of IDA. After PSM, multivariate regression analyses revealed no significant differences in the odds of cardiogenic shock (10% vs. 10%, p=0.86), in-hospital mortality (2.6% vs. 2.8%, p=0.71), and LOS (7.19 vs. 7.27 days) between the two groups. Additionally, the likelihood of cardiac arrest, ventricular arrhythmias, AMI, and utilization of mechanical ventilation and circulatory support did not reach statistical significance. However, patients with IDA and HFrEF had higher hospitalization charges ($85,516 vs. $93,000). Conclusion: HFrEF patients, with or without IDA, had similar odds of cardiogenic shock, in-hospital mortality, mechanical circulatory support utilization, as well as LOS. However, IDA with HFrEF correlated with higher hospitalization charges.

Partial reduction of interleukin-33 signaling improves senescence and renal injury in diabetic nephropathy.

Diabetic nephropathy (DN) is a frequent and costly complication of diabetes with limited understandings of mechanisms and therapies. Emerging evidence points to the important roles of interleukin-33 (IL-33) in acute kidney injury, yet its contribution to DN is still unclear. We here found a ubiquitous increase of IL-33 and its receptor (ST2) in murine models and patients with DN. Surprisingly, both IL-33 and ST2 knockdown aggravated renal lesions in DN, while overexpression of IL-33 also exacerbated the condition. Further population-based analyses revealed a positive correlation of IL-33 expression with renal dysfunction in DN patients. Individuals with high IL-33expression-related polygenic risk score had a higher DN risk. These findings confirmed the harmful effects of IL-33 on DN. Conversely, endogenous and exogenous partial reduction of IL-33 signaling conferred renoprotective effects in vivo and in vitro. Mechanistically, IL-33 induced senescence by regulating cell cycle factors in HK-2 cells, and accordingly senescence led to renal cell damage through the secretion of senescence-related secretory phenotype (SASP) including IL-33 and prostaglandins. Together, elevated IL-33 accelerates cellular senescence to drive DN possibly by SASP production, while a partial blockage improves renal injury and senescence. Our findings pinpoint a possible and new avenue for DN interventions.

Characteristics and Rates of Preterm Births During the COVID-19 Pandemic in Germany

Population-based analyses provided divergent data on the changes in preterm birth rates during the COVID-19 pandemic, and there is a gap of knowledge on the variations in birth characteristics. To study changes in perinatal care, causes of preterm delivery, and very preterm (VPT; defined as <32 weeks' gestation) birth rates before and during the COVID-19 pandemic. This population-level cohort study used data from the quality assurance registry, which covers all births in Hesse, Germany. Deliveries during the COVID-19 pandemic (2020) were compared with the corresponding grouped prepandemic time intervals (2017 to 2019). Analyses were executed between August 2023 and July 2024. Analyses were directed to study differences in preterm births before and during 3 pandemic phases: first (March 14 to May 15, 2020) and second (October 19 to December 31, 2020) lockdowns and a period of less-vigorous restrictions between them (May 16 to October 18, 2020). Outcomes of interest were variations in preterm birth rates in the context of baseline characteristics and causes of preterm births during vs before the first year of the COVID-19 pandemic. From the total cohort of 184 827 births from 2017 to 2020, 719 stillbirths occurred and 184 108 infants were liveborn. Compared with the prepandemic period, medical care characteristics did not differ during the COVID-19 period. The odds of VPT births were lower during the pandemic period (odds ratio [OR], 0.87; 95% CI, 0.79-0.95) compared with the prepandemic period, with the greatest reduction observed during the second lockdown period (OR, 0.69; 95% CI, 0.55-0.84). Reduction in VPT births was attributed to fewer births in pregnancies among individuals with a history of serious disease (OR, 0.64; 95% CI, 0.50-0.83), pathologic cardiotocography (OR, 0.66; 95% CI, 0.53-0.82), and intrauterine infection (OR, 0.82; 95% CI, 0.72-0.92) while incidences of history of preterm birth, multiple pregnancies, serious or severe psychological distress, and preeclampsia, eclampsia, or hemolysis, elevated liver enzymes, and low platelet count syndrome as cause for preterm delivery remained unchanged. In this population-based cohort study on the COVID-19 pandemic and preterm birth rates, the duration of exposure to mitigation measures during pregnancy was associated with accelerated reductions in preterm births. The findings of lower rates of baseline risks and causes of preterm deliveries support efforts to intensify health care prevention programs during pregnancy to reduce the preterm birth burden. These findings of this study put particular focus on hygiene measures to reduce the rate of deliveries for intrauterine infection and highlight the potential of expanding strategies to the different risks and causes of preterm delivery.

Phylogenetic insights into the genetic legacies of Hungarian-speaking communities in the Carpathian Basin

This study focuses on exploring the uniparental genetic lineages of Hungarian-speaking minorities residing in rural villages of Baranja (Croatia) and the Zobor region (Slovakia). We aimed to identify ancestral lineages by examining genetic markers distributed across the entire mitogenome and on the Y-chromosome. This allowed us to discern disparities in regional genetic structures within these communities. By integrating our newly acquired genetic data from a total of 168 participants with pre-existing Eurasian and ancient DNA datasets, our goal was to enrich the understanding of the genetic history trajectories of Carpathian Basin populations. Our findings suggest that while population-based analyses may not be sufficiently robust to detect fine-scale uniparental genetic patterns with the sample sizes at hand, phylogenetic analysis of well-characterized Y-chromosomal Short Tandem Repeat (STR) data and entire mitogenome sequences did uncover multiple lineage ties to far-flung regions and eras. While the predominant portions of both paternal and maternal DNA align with the East-Central European spectrum, rarer subhaplogroups and lineages have unveiled ancient ties to both prehistoric and historic populations spanning Europe and Eastern Eurasia. This research augments the expansive field of phylogenetics, offering critical perspectives on the genetic constitution and heritage of the communities in East-Central Europe.

The impact of the SARS-CoV2 pandemic on the prescription of thyroid medication in Austria – A nationwide population-based registry analysis

BackgroundCase reports indicate a clinical connection between SARS-CoV-2 and thyroid dysfunctions. However, evidence from large population-based registry analyses is sparse, especially in Europe, where iodine deficiency is common. This study aimed to analyze the impact of the COVID-19 pandemic on healthcare provision for thyroid diseases in Austria. MethodsWe performed a retrospective, population-based registry analysis of the Austrian health insurance fund database, covering more than 9 million inhabitants. Data from all patients with prescriptions of thyroid-specific drugs and/or inpatient thyroid-related diagnoses from 2017 to 2019 (pre-pandemic years) were compared to 2020 and 2021 (pandemic years; characterized by high numbers of SARS-CoV2 infections and population-wide vaccination strategy). The incidence rates of thyroid medication prescriptions for hypothyroidism and hyperthyroidism were calculated for every year to evaluate the impact of the pandemic. ResultsThe incidence rate for total thyroid medication prescription was 539.07/100,000 individuals (534.23–543.93 95%CI) in 2018 and declined during the pandemic (2020: 387.19/100,000 (383.12–391.29 95%CI); 2021: 336.90/100,000 (333.11–340.73 95%CI)). Similarly, the incidence rate for levothyroxine prescription was higher pre-pandemic (2018: 465.46/100,000 (460.97–469.98 95%CI) and declined during the pandemic (2020: 348.14/100,000 (344.28–352.03 95%CI); 2021: 300.30/100,000 (296.7–303.91 95%CI). The incidence rates of thiamazole prescriptions (2018: 10.24/100,000 (9.58–10.93 95%CI); 2020: 8.62/100,000 (8.03–9.26 95%CI); 2021: 11.17/100,000 (10.49–11.89 95%CI) were stable. ConclusionsThese findings suggest no clinically significant impact of SARS-CoV2 and/or vaccination on thyroid function at a population level.

Association between glaucoma and stroke: A bidirectional mendelian randomization study

PurposeObservational studies have reported positive associations between glaucoma and stroke; however, controversial results exist. Importantly, the nature of the relationship remains unknown since previous studies were not designed to test causality. Therefore, we aimed to investigate the possible causal relationships between glaucoma and stroke. MethodsOur two-sample Mendelian randomization (MR) encompassed multi-ethnic large-scale genome-wide association studies with more than 20000 cases and 260000 controls for glaucoma, and more than 80000 cases and 630000 controls for stroke. Individual effect estimates for each SNP were combined using the inverse-variance weighted (IVW) method. To avoid potential pleiotropic effects, we adjusted the main results by excluding genetic variants associated with metabolic factors. The weighted median and MR-Egger methods were also used for the sensitivity analysis. ResultsOur MR analysis revealed that glaucoma and its subtypes, including primary open-angle glaucoma and primary angle-closure glaucoma, exhibited no causal role in relation to any stroke (AS), any ischemic stroke (AIS), large-artery atherosclerotic stroke (LAS), small-vessel stroke (SVS), or cardioembolic stroke (CES) across MR analyses (all P ​> ​0.05). The null associations remained robust even after adjusting for metabolic-related traits and were consistent in both the European and Asian populations. Furthermore, reverse MR analyses also did not indicate any significant causal effects of AS, AIS, LAS, or CES on glaucoma risk. ConclusionsEvidence from our series of causal inference approaches using large-scale population-based MR analyses did not support causal effects between glaucoma and stroke. These findings suggest that the relationship of glaucoma management and stroke risk prevention should be carefully evaluated in future studies. In turn, stroke diagnosis should not be simply applied to glaucoma risk prediction.

Exploration and demonstration of explainable machine learning models in prosthetic rehabilitation-based gait analysis.

Quantitative gait analysis is important for understanding the non-typical walking patterns associated with mobility impairments. Conventional linear statistical methods and machine learning (ML) models are commonly used to assess gait performance and related changes in the gait parameters. Nonetheless, explainable machine learning provides an alternative technique for distinguishing the significant and influential gait changes stemming from a given intervention. The goal of this work was to demonstrate the use of explainable ML models in gait analysis for prosthetic rehabilitation in both population- and sample-based interpretability analyses. Models were developed to classify amputee gait with two types of prosthetic knee joints. Sagittal plane gait patterns of 21 individuals with unilateral transfemoral amputations were video-recorded and 19 spatiotemporal and kinematic gait parameters were extracted and included in the models. Four ML models-logistic regression, support vector machine, random forest, and LightGBM-were assessed and tested for accuracy and precision. The Shapley Additive exPlanations (SHAP) framework was applied to examine global and local interpretability. Random Forest yielded the highest classification accuracy (98.3%). The SHAP framework quantified the level of influence of each gait parameter in the models where knee flexion-related parameters were found the most influential factors in yielding the outcomes of the models. The sample-based explainable ML provided additional insights over the population-based analyses, including an understanding of the effect of the knee type on the walking style of a specific sample, and whether or not it agreed with global interpretations. It was concluded that explainable ML models can be powerful tools for the assessment of gait-related clinical interventions, revealing important parameters that may be overlooked using conventional statistical methods.

Individual Survival Distributions Generated by Multi-Task Logistic Regression Yield a New Perspective on Molecular and Clinical Prognostic Factors in Gastric Adenocarcinoma.

Recent advances in our understanding of gastric cancer biology have prompted a shift towards more personalized therapy. However, results are based on population-based survival analyses, which evaluate the average survival effects of entire treatment groups or single prognostic variables. This study uses a personalized survival modelling approach called individual survival distributions (ISDs) with the multi-task logistic regression (MTLR) model to provide novel insight into personalized survival in gastric adenocarcinoma. We performed a pooled analysis using 1043 patients from a previously characterized database annotated with molecular subtypes from the Cancer Genome Atlas, Asian Cancer Research Group, and tumour microenvironment (TME) score. The MTLR model achieved a 5-fold cross-validated concordance index of 72.1 ± 3.3%. This model found that the TME score and chemotherapy had similar survival effects over the entire study time. The TME score provided the greatest survival benefit beyond a 5-year follow-up. Stage III and Stage IV disease contributed the greatest negative effect on survival. The MTLR model weights were significantly correlated with the Cox model coefficients (Pearson coefficient = 0.86, p < 0.0001). We illustrate how ISDs can accurately predict the survival time for each patient, which is especially relevant in cases of molecular subtype heterogeneity. This study provides evidence that the TME score is principally associated with long-term survival in gastric adenocarcinoma. Additional external validation and investigation into the clinical utility of this ISD model in gastric cancer is an area of future research.

Five years of Hospital at Home adoption in Catalonia: impact, challenges, and proposals for quality assurance

BackgroundHospital at home (HaH) was increasingly implemented in Catalonia (7.7 M citizens, Spain) achieving regional adoption within the 2011-2015 Health Plan. This study aimed to assess population-wide HaH outcomes over five years (2015-2019) in a consolidated regional program and provide context-independent recommendations for continuous quality improvement of the service.MethodsA mixed-methods approach was adopted, combining population-based retrospective analyses of registry information with qualitative research. HaH (admission avoidance modality) was compared with a conventional hospitalization group using propensity score matching techniques. We evaluated the 12-month period before the admission, the hospitalization, and use of healthcare resources at 30 days after discharge. A panel of experts discussed the results and provided recommendations for monitoring HaH services.ResultsThe adoption of HaH steadily increased from 5,185 episodes/year in 2015 to 8,086 episodes/year in 2019 (total episodes 31,901; mean age 73 (SD 17) years; 79% high-risk patients. Mortality rates were similar between HaH and conventional hospitalization within the episode [76 (0.31%) vs. 112 (0.45%)] and at 30-days after discharge [973(3.94%) vs. 1112(3.24%)]. Likewise, the rates of hospital re-admissions at 30 days after discharge were also similar between groups: 2,00 (8.08%) vs. 1,63 (6.58%)] or ER visits [4,11 (16.62%) vs. 3,97 (16.03%). The 27 hospitals assessed showed high variability in patients’ age, multimorbidity, severity of episodes, recurrences, and length of stay of HaH episodes. Recommendations aiming at enhancing service delivery were produced.ConclusionsBesides confirming safety and value generation of HaH for selected patients, we found that this service is delivered in a case-mix of different scenarios, encouraging hospital-profiled monitoring of the service.

Population-based high-dimensional analyses identify multiple intrinsic characters for cancer vaccines against lung squamous cell carcinoma.

In lung squamous cell carcinoma (LUSC), current cancer vaccines show promising effects, despite a lack of benefit for a large number of patients. We first identified the tumor antigens into shared and private antigens, and determined the population by clustering analysis in public datasets. For vaccine development, The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were collected. WGCNA method was furthermore applied to construct a consensus gene co-expression network based on TCGA and CPTAC datasets. The main analyses in bulk sequencing included survival, clinical features, tumor microenvironment (TME), and pathways enrichment. In addition, single-cell RNA (scRNA) analysis of cancer epithelium dissected consensus subtype. We identified the ideal population for cancer vaccines, and candidate neoantigens including AOC1, COL5A2, LGI2, and POSTN. According to subtype analysis, Lung squamous 1 (LSQ1) type exhibited a higher tumor mutational load (TMB) and copy number but no immune infiltration, whereas lung squamous 2 (LSQ2) tumors had a higher global methylation level and more fibroblasts but had less stemness. Meanwhile, trajectory analysis further revealed that the evolution of TME influenced prognosis. We emphasized specific pathways or targets with the potential for combination immunotherapy by consensus network and single-cell RNA analyses. Anti-androgen therapy has been validated in vitro experiments of LUSC as proof of concept. In conclusion,LSQ1 was linked to immune exclusion and might be utilized for vaccination, while LSQ2 was linked to immune dysfunction and could be used for programmed cell death protein 1 (PD1) blocking therapy.

The Retail Food Environment Index and its association with dietary patterns, body mass index, and socioeconomic position: A multilevel assessment in Mexico.

In Mexico, 75% of the population are affected by overweight or obesity, and the availability and affordability of high-calorie-dense foods and beverages are high. This study tested the association between the retail food environment index (RFEI), dietary patterns, body mass index (BMI), and socioeconomic position (SEP) in Mexico. Cross-sectional diet, health, and sociodemographic population-based secondary data analyses were conducted. The RFEI was calculated by dividing the total number of fast-food outlets and convenience stores by the total number of supermarkets and fruit and vegetable stores per census tract area. Associations between BMI, dietary patterns, SEP and the RFEI were tested using multilevel linear regression, including interactions of the RFEI with SEP, gender, and age. Living in neighbourhoods with a higher RFEI was associated with a 0.01kg/m2 higher BMI (β = 0.01, 95%CI: 0.0005, 0.02, p = 0.04), equivalent to a mean 0.046 weight gain for a 1.60m tall person per 10% higher RFEI. Unhealthy dietary patterns were more likely in neighbourhoods with a higher RFEI (β = 0.100, 95%CI: 0.03, 0.12, p = 0.001). Multilevel linear regression showed that lower SEP households had a higher RFEI compared to higher SEP households (β = 0.020, 95% CI: -0.006 to 0.04, p = 0.10). Generalised structural equation models revealed a graded relationship between RFEI and SEP, showing that lower SEP households were exposed to a higher RFEI (β = 0.060, 95% CI: 0.05 to 0.07, p < 0.001.) The study identified significant associations between higher proportions of fast-food outlets and convenience stores, higher BMI, and unhealthy dietary patterns. It was particularly evident that low-income populations are more likely to be exposed to obesogenic food environments.

Characterization of Comparative Clinical Outcomes and Molecular Features of Black Patients with Acute Promyelocytic Leukemia (APL) Reveals Similar Survival and Distinct Genomic Profiles

Introduction: Although APL, a subtype of acute myeloid leukemia (AML), is an aggressive disease, its treatment was revolutionized with combination all- trans retinoic acid (ATRA) and arsenic trioxide (ATO), making APL a highly curable malignancy. Molecularly, APL is characterized by t(15;17) resulting in PML:: RARA gene fusion as disease-initiating event and by several recurrent gene mutations (eg, FLT3) identified in previous studies. In AML, prior studies have established inferior overall survival (OS) of Black versus White AML patients (pts) in both population-based analyses and clinical trials, found a negative prognostic impact of higher social deprivation (SDI), and characterized differences in frequencies and impact of disease-associated gene mutations. Herein, we compared OS of Black and White APL pts and evaluated genomic landscape of Black pts, which has not been comprehensively assessed to date. Methods: For nationwide population analysis, 2 sets of cancer registries were included in the Surveillance Epidemiology End Results (SEER) Program of the National Cancer Institute to identify 829 adults diagnosed with de novo APL (confirmed by cytogenetic and/or molecular findings) in 1995-2019. To assess survival in the setting of clinical trials, we analyzed 249 pts treated on historic frontline Cancer and Leukemia Group B (CALGB)/Alliance for Clinical Trials in Oncology (Alliance) trials with or without inclusion of ATRA (CALGB 9191, 1992-1995; CALGB 9710, 1999-2005). For Alliance pts, neighborhood SDI was assigned based on pt-reported residence zip code and classified as low (1-25, n=33) or high deprivation (26-100, n=95). OS was analyzed separately for pts diagnosed before and after 2012 to account for treatment advances with ATRA/ATO. To assess molecular features, we performed integrated genomic profiling (paired tumor/normal whole-exome and transcriptome sequencing) on 31 Black APL Alliance pts (9/31 completed, with complete results to be presented at the Annual Meeting). Results: On a population level using SEER data, 3-year (3y) OS significantly improved from 65% for cases diagnosed in 1995-2012 to 75% in those diagnosed after 2012 (p=&amp;lt;0.001), concordant with ATRA/ATO use. Notably, OS of Black and White pts did not differ significantly before or after 2012. This held true in race-specific findings for median household income, Yost index and urban/rural status; none of which significantly associated with OS. Older age was the only parameter associated with OS (3y rates, 1995-2012: &amp;lt;40y, 79%; 40-59y, 71%; ≥60y, 44%; and 2012-2019: &amp;lt;40y, 92%; 40-59y, 80%; ≥60y, 56%). Again, OS of Black and White pts did not differ within age groups. Likewise, OS of Black and White APL pts treated in a relatively controlled setting of clinical trials was not significantly different. As in population-based findings, OS improved over time and with ATRA addition (3y OS rates, 1992-1995, 66%; 1999-2005, 85%), and older age was a strong negative OS predictor (p&amp;lt;0.001). When comparing OS of pts treated on clinical trials with population-based OS, trial pts had a longer 3y OS (84% vs 64%, p&amp;lt;0.001). Notably, pts with SDI &amp;gt;25 (n=95) had a worse OS than pts with SDI &amp;lt;25 (n=33, p=0.03). On a molecular level, preliminary results of whole-exome sequencing (finalized for 9/31 Black pts) showed frequent mutations in FLT3 (5/9 pts), a known APL-associated event, but also revealed several recurrent gene mutations not reported in prior APL sequencing efforts, which were almost exclusively based on White pts, including mutations in DPP6, GOLA6L, NLGN2 and SP8 (found in ≥2 pts). Intriguingly, CALR mutations were found in 3/9 pts. Mutations in FLT3 and CALR were mutually exclusive and found in 8/9 pts, with the remaining pt harboring a SORBS2 mutation. Conclusions: In contrast to most cancer types, including AML, there was no OS disparity with respect to race in APL pts, both in population-based analyses and in the setting of historic clinical trials. Older age and residence with high SDI (&amp;gt;25) were negative OS predictors. Molecularly, our pilot data reveal existence of ancestry-associated differences in driver mutations, suggesting that FLT3 and CALR mutations represent necessary proliferative signals in addition to PML:: RARA-driven differentiation arrest. Support: U10CA180821, U10CA180882, U24CA196171; Clinicaltrials.gov IDs: NCT00048958, NCT00899223, NCT00900224; https://acknowledgments.alliancefound.org

Patient-Associated Survival Modulators in Adolescent and Young Adult (AYA) Patients (Pts) with Acute Myeloid Leukemia (AML)

Background: AML is a highly aggressive hematologic malignancy, but the AYA pts [aged 18-39 years (y)] have improved survival, with ~50% of pts achieving long-term cure. Pt outcomes are known to be affected by disease-related factors including cytogenetic findings and gene mutations, which were established in large genomic studies. In addition, pt-related factors, such as self-reported race and socioeconomic contributors have been found to affect survival in population-based studies. Whereas population-based studies are performed on large pt cohorts to establish meaningful conclusions, they usually lack details with respect to additional pt-related factors, including complete comorbidities, insurance status as well as information on disease presentation, such as time from the first provider contact to confirmation of AML diagnosis (time to diagnosis) and treatment, which might also influence pt survival. Rationale and Methods: Thus, we set out to establish recent survival rates of AML AYA pts at the population level using pts reported to one of 12 Surveillance Epidemiology End Results (SEER) Program registries of the National Cancer Institute [n=1119; median age, 30 y,1992-2014; n=239; median age, 29 y, 2015-2020], and analyze possible factors influencing survival. In parallel, we performed an in-depth analysis of treatment response and survival, including time to diagnosis, and additional pt-associated variables pertinent to AYA pts (employment status, housing, insurance, comorbidities, distance to treatment center, research study enrollment, biobanking) based on retrospectively collected data of AYA AML pts cared for at a major US Comprehensive Cancer Center (CCC) in 2015-2020 (n=96, median age, 31 y), for whom detailed clinical information was available. Results: Generally, overall survival (OS) of AYA AML pts significantly improved over time, with a marked improvement of 3-y OS rates from 47% in pts diagnosed prior to 2009, to 63% in pts diagnosed in 2010-2014 and 69% in pts diagnosed in 2015-2020. Analysis of possible associations between demographic parameters and risk of death among AYA AML pts reported to SEER Program registries did not show any statistically significant impact of sex, age, county-level median household income or metro/rural status. The only factor affecting OS of AYA AML pts was race. Specifically, Black AML pts had a higher risk of death compared with that of White AML pts [HR 2.13 (95% CI 1.03 - 4.39)], with 3-y OS rates of 47% and 80% ( P=.04), respectively. Survival disparities did not improve over time. CCC AYA AML pts had similar OS rates to those seen in the population-based analyses, with a 3-y OS rate of 70%. Ninety-three percent of pts achieved a complete remission, and 31% of pts relapsed. Analyses of CCC AML pts allowed for preliminary assessment of additional parameters. Ninety-one percent of pts (77/85) received a diagnosis in ≤2 weeks after first provider contact. Although pt numbers were small, there was a trend for a longer diagnosis time in Black pts, 27% (3/11) of whom were diagnosed &amp;gt;2 weeks after first presentation, compared with only 8% (5/61; P=.10) of White pts. Interestingly, analysis of possible additional outcome modulators in CCC AYA pts suggested that presence of other medical conditions at diagnosis associated with lower relapse rates (16% vs 34%, P=.04), and unemployment tended to associate with higher relapse rates (34% vs 17%, P=.06). In addition, of pts approached for biobanking, fewer Black pts consented to sample collection than White pts (60% vs 87%, P=.06). Conclusion: Survival of AYA pts with AML significantly improved over time, likely driven by availability of allogeneic stem cell transplantation and improved supportive care. Black race still represents the most important negative survival prognosticator, without marked signs of improvement. An exploratory analyses of additional pt-associated variables suggested less recognized factors that may impact survival, such as trends for longer time to diagnosis and reduced participation in biobanking protocols in Black pts compared with White pts, and a higher relapse rate in pts who are unemployed. Although these differences were not yet statistically significant , we are currently in the process of increasing the sample size to further evaluate these potentially important trends. Support: American Cancer Society, Leukemia Lymphoma Society

Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses

Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses. We identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case-control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses. We identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case-control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51-0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07-1.13), 1.16 (1.09-1.24), and 1.09 (1.05-1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design. This large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer. Swedish Research Council, Cancerfonden, Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 111 Project and MAS cancer.

Incidence, Characteristics, and Outcomes of Robin Sequence: A Population-Based Analysis in the United States.

While the literature is replete of clinical studies reporting on the Robin sequence (RS), population-based analyses are scarce with significant variability within the literature in terms of reported incidence, demographic parameters, and outcomes. The authors have conducted a 20-year population-based analysis to guide clinical practice. A birth cohort was created from the available datasets in the Healthcare Cost and Utilization Project-Kids' Inpatient Database (HCUP-KID; 2000-2019). Robin sequence patients were identified and further stratified by syndromic status. Incidence, demographic parameters, and outcomes including mortality and tracheostomy rates were computed. A subset analysis comparing the isolated and syndromic cohorts was conducted. Data was analyzed through a χ 2 or t test. The incidence of RS was 5.15:10,000 (95% CI: 4.99-5.31) from a birth cohort of 7.5 million. Overall, 63.3% of the cohort was isolated RS and 36.7% had syndromic RS. Robin sequence patients had a significantly higher rate of cardiac (25.9%) and neurological (8.6%) anomalies compared with the general birth cohort and were most commonly managed in urban teaching hospitals ( P <0.0001). The pooled mortality and tracheostomy rates were 6.6% and 3.6%, respectively. Syndromic status was associated with a longer length of hospital stay (27.8 versus 13.6d), tracheostomy rate (6.2% versus 2.1%), and mortality (14.1% versus 2.2%) compared with isolated RS ( P <0.0001). The true incidence of RS is likely higher than previously reported estimates. Isolated RS patients have a low associated mortality and tracheostomy rate and are typically managed in urban teaching hospitals. Syndromic status confers a higher mortality rate, tracheostomy rate, and length of stay compared with nonsyndromic counterparts.

Skin Cancer and Hydrochlorothiazide: Novel Population-Based Analyses Considering Personal Risk Factors Including Race/Ethnicity.

Hydrochlorothiazide, a common antihypertensive, has photosensitive properties, potentially increasing skin cancer risk. We evaluated melanoma and nonmelanoma skin cancer among hydrochlorothiazide users with 3 different cohorts as each allows assessment of different potential cofounders/effect modifiers, including race/ethnicity. We built 3 cohorts using IBM MarketScan Research Databases: Commercial and Encounters (>3.5 million individuals, 2010-2018), a subcohort with health risk assessment respondents (415, 330), and Medicaid (509, 767, 2011-2017). Adults (aged 18+ years) entered the respective cohort with a first-filled prescription (cohort entry) for hydrochlorothiazide (the exposure of interest) or angiotensin-converting enzyme (ACE) inhibitors (the active comparator), with ≥12 months of continuous enrollment with medical/pharmacy coverage at baseline. We excluded those who used hydrochlorothiazide/ACE inhibitor (including fixed-dose combination products) 12 months before cohort entry and those with prior skin cancer, HIV, or organ transplant. We compared the risk for hydrochlorothiazide versus ACE inhibitor using multivariate proportional hazards regression. Baseline characteristics were similar, aside from more Black individuals among hydrochlorothiazide users (43.3% [95% CI, 43.0%-43.6%]) than ACE inhibitor users (28.1% [95% CI, 27.9%-28.3%]). The hazard ratio (95% CI) for nonmelanoma skin cancer related to hydrochlorothiazide (versus ACE inhibitor) was 0.96 (0.91-1.00) in the Commercial cohort, 1.01 (0.77-1.32) for the health risk assessment subcohort, and 1.33 (0.77-2.29) for Medicaid. For melanoma, the respective hazard ratios were 1.07 (0.95-1.20), 0.85 (0.43-1.67), and 0.93 (0.51-1.67), respectively. Our evaluation using 3 different approaches, including adjustment for race/ethnicity, did not establish a clear difference between hydrochlorothiazide and ACE inhibitor in terms of skin cancer risk.

An analytical framework for decoding cell type-specific genetic variation of gene regulation

A deeper understanding of genetic regulation and functional mechanisms underlying genetic associations with complex traits and diseases is impeded by cellular heterogeneity and linkage disequilibrium. To address these limits, we introduce Huatuo, a framework to decode genetic variation of gene regulation at cell type and single-nucleotide resolutions by integrating deep-learning-based variant predictions with population-based association analyses. We apply Huatuo to generate a comprehensive cell type-specific genetic variation landscape across human tissues and further evaluate their potential roles in complex diseases and traits. Finally, we show that Huatuo’s inferences permit prioritizations of driver cell types associated with complex traits and diseases and allow for systematic insights into the mechanisms of phenotype-causal genetic variation.

Exome Sequencing Implicates DGKZ , ESRRA , and GXYLT1 for Modulating Granuloma Formation in Crohn Disease.

Non-caseating granulomas may indicate a more aggressive phenotype of Crohn disease (CD). Genetic associations of granulomatous CD (GCD) may help elucidate disease pathogenesis. Whole-exome sequencing was performed on peripheral blood-derived DNA from 17 pediatric patients with GCD and 19 with non-GCD (NGCD), and from an independent validation cohort of 44 GCD and 19 NGCD cases. PLINK (a tool set for whole-genome association and population-based linkage analyses) analysis was used to identify single nucleotide polymorphisms (SNPs) differentiating between groups, and subgroup allele frequencies were also compared to a public genomic database (gnomAD). The Combined Annotation Dependent Depletion scoring tool was used to predict deleteriousness of SNPs. Human leukocyte antigen (HLA) haplotype findings were compared to a control group (n = 8496). PLINK-based analysis between GCD and NGCD groups did not find consistently significant hits. gnomAD control comparisons, however, showed consistent subgroup associations with DGKZ , ESRRA , and GXYLT1 , genes that have been implicated in mammalian granulomatous inflammation. Our findings may guide future research and precision medicine.

Post Antenatal Late Preterm Steroids trial: interrupted time series analysis of respiratory outcomes in twin and pregestational diabetes

The Antenatal Late Preterm Steroids trial found that corticosteroid administration decreased respiratory complications by 20% among late preterm singleton deliveries. After the Antenatal Late Preterm Steroids trial, corticosteroid administration increased by 76% among twin pregnancies and 113% among singleton pregnancies complicated by pregestational diabetes mellitus compared with expected rates based on the pre-Antenatal Late Preterm Steroids trial trend. However, the effect of corticosteroids on twin pregnancies and pregnancies complicated by pregestational diabetes mellitus is not well studied, as the Antenatal Late Preterm Steroids trial excluded twin pregnancies and pregnancies complicated by pregestational diabetes mellitus. This study aimed to examine the change in the incidence rate of immediate assisted ventilation use and ventilation use for more than 6 hours among 2 populations after the dissemination of the Antenatal Late Preterm Steroids trial at the population level. This study was a retrospective analysis of publicly available US birth certificate data. The study period was from August 1, 2014, to April 30, 2018. The dissemination period of the Antenatal Late Preterm Steroids trial was from February 2016 to October 2016. Population-based interrupted time series analyses were performed for 2 target populations: (1) twin pregnancies not complicated by pregestational diabetes mellitus and (2) singleton pregnancies complicated by pregestational diabetes mellitus. For both target populations, analyses were limited to individuals who delivered nonanomalous live neonates between 34 0/7 and 36 6/7 weeks of gestation (vaginal or cesarean delivery). As a sensitivity analysis, a total of 23 placebo tests were conducted before (5 tests) and after (18 tests) the dissemination period. For the analysis of late preterm twin deliveries, 191,374 individuals without pregestational diabetes mellitus were identified. For the analysis of late preterm singleton pregnancy with pregestational diabetes mellitus, 21,395 individuals were identified. After the dissemination period, the incidence rate of immediate assisted ventilation use for late preterm twin deliveries was significantly lower than the expected value based on the pre-Antenatal Late Preterm Steroids trial trend (11.6% observed vs 13.0% expected; adjusted incidence rate ratio, 0.87; 95% confidence interval, 0.78-0.97). The incidence rate of ventilation use for more than 6 hours among late preterm twin deliveries did not change significantly after the dissemination of the Antenatal Late Preterm Steroids trial. A significant increase in the incidence rate of immediate assisted ventilation use and ventilation use for more than 6 hours was found among singleton pregnancies with pregestational diabetes mellitus. However, the results of placebo tests suggested that the increase in incidence was not necessarily due to the dissemination period of the Antenatal Late Preterm Steroids trial. The dissemination of the Antenatal Late Preterm Steroids trial was associated with decreased incidence of immediate assisted ventilation use, but no change in ventilation use for more than 6 hours, among late preterm twin deliveries in the United States. In contrast, the incidence of neonatal respiratory outcomes among singleton deliveries with pregestational diabetes mellitus did not decrease after the dissemination of the Antenatal Late Preterm Steroids trial.