County-level socio-environmental factors and obesity prevalence in the United States

AIMS

To investigate high-risk sociodemographic and environmental determinants of health (SEDH) potentially associated with adult obesity in counties in the United States using machine-learning techniques.

MATERIALS AND METHODS

We performed a cross-sectional analysis of county-level adult obesity prevalence (body mass index ≥30 kg/m2) in the United States using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used in a classification and regression trees (CART) model to identify county-level clusters. The CART model was validated using a 'hold-out' set of counties and variable importance was evaluated using Random Forest.

RESULTS

Overall, we analysed 2752 counties in the United States, identifying a national median (interquartile range) obesity prevalence of 34.1% (30.2%, 37.7%). The CART method identified 11 clusters with a 60.8% relative increase in prevalence across the spectrum. Additionally, seven key SEDH variables were identified by CART to guide the categorization of clusters, including Physically Inactive (%), Diabetes (%), Severe Housing Problems (%), Food Insecurity (%), Uninsured (%), Population over 65 years (%) and Non-Hispanic Black (%).

CONCLUSION

There is significant county-level geographical variation in obesity prevalence in the United States, which can in part be explained by complex SEDH factors. The use of machine-learning techniques to analyse these factors can provide valuable insights into the importance of these upstream determinants of obesity and, therefore, aid in the development of geo-specific strategic interventions and optimize resource allocation to help battle the obesity pandemic.

Cardiac MRI feature-tracking-derived torsion mechanics in systolic and diastolic dysfunction in systemic light-chain cardiac amyloidosis

AIM

To describe the myocardial torsion mechanics in cardiac amyloidosis (CA), and evaluate the correlations between left ventricle (LV) torsion mechanics and conventional parameters using cardiac magnetic resonance imaging feature tracking (CMR-FT).

MATERIALS AND METHODS

One hundred and thirty-nine patients with light-chain CA (AL-CA) were divided into three groups: group 1 with preserved systolic function (LV ejection fraction [LVEF] ≥50%, n=55), group 2 with mildly reduced systolic function (40% ≤ LVEF <50%, n=51), and group 3 with reduced systolic function (LVEF <40%, n=33), and compared with age- and gender-matched healthy controls (n=26). All patients underwent cine imaging and late gadolinium-enhancement (LGE). Cine images were analysed offline using CMR-FT to estimate torsion parameters.

RESULTS

Global torsion, base-mid torsion, and peak diastolic torsion rate (diasTR) were significantly impaired in patients with preserved systolic function (p<0.05 for all), whereas mid-apex torsion and peak systolic torsion rate (sysTR) were preserved (p>0.05 for both) compared with healthy controls. In patients with mildly reduced systolic function, global torsion and base-mid torsion were lower compared to those with preserved systolic function (p<0.05 for both), while mid-apex torsion, sysTR, and diasTR were preserved (p>0.05 for all). In patients with reduced systolic function, only sysTR was significantly worse compared with mildly reduced systolic function (p<0.05). At multivariable analysis, right ventricle (RV) end-systolic volume RVESV index and NYHA class were independently related to global torsion, whereas LVEF was independently related to sysTR. RV ejection fraction (RVEF) was independently related to diasTR. LV global torsion performed well (AUC 0.71; 95% confidence interval [CI]: 0.61, 0.77) in discriminating transmural from non-transmural LGE in AL-CA patients.

CONCLUSION

LV torsion mechanics derived by CMR-FT could help to monitor LV systolic and diastolic function in AL-CA patients and function as a new imaging marker for LV dysfunction and LGE transmurality.

County-Level Socio-Environmental Factors Associated With Stroke Mortality in the United States: A Cross-Sectional Study

We used machine learning methods to explore sociodemographic and environmental determinants of health (SEDH) associated with county-level stroke mortality in the USA. We conducted a cross-sectional analysis of individuals aged ≥15 years who died from all stroke subtypes between 2016 and 2020. We analyzed 54 county-level SEDH possibly associated with age-adjusted stroke mortality rates/100,000 people. Classification and Regression Tree (CART) was used to identify specific county-level clusters associated with stroke mortality. Variable importance was assessed using Random Forest analysis. A total of 501,391 decedents from 2397 counties were included. CART identified 10 clusters, with 77.5% relative increase in stroke mortality rates across the spectrum (28.5 vs 50.7 per 100,000 persons). CART identified 8 SEDH to guide the classification of the county clusters. Including, annual Median Household Income ($), live births with Low Birthweight (%), current adult Smokers (%), adults reporting Severe Housing Problems (%), adequate Access to Exercise (%), adults reporting Physical Inactivity (%), adults with diagnosed Diabetes (%), and adults reporting Excessive Drinking (%). In conclusion, SEDH exposures have a complex relationship with stroke. Machine learning approaches can help deconstruct this relationship and demonstrate associations that allow improved understanding of the socio-environmental drivers of stroke and development of targeted interventions.

Predictive effect of net water uptake on futile recanalisation in patients with acute large-vessel occlusion stroke

AIM

To determine whether net water uptake (NWU) based on automated software evaluation could predict futile recanalisation in patients with acute anterior circulation large-vessel occlusion (LVO).

MATERIALS AND METHODS

Patients with acute anterior circulation LVO undergoing mechanical thrombectomy in Jinling Hospital were evaluated retrospectively. NWU and other baseline data were evaluated by performing univariate and multivariate analyses. The primary endpoint was 90-day modified Rankin scale score ≥3. A nomogram to predict poor clinical outcomes was developed based on multivariate logistic regression analysis.

RESULTS

Overall, 135 patients who underwent thrombectomy with a TICI grade ≥2b were enrolled. In multivariate logistic regression analysis, the following factors were identified as independent predictors of futile recanalisation: age (odds ratio [OR]: 1.055, 95 % confidence interval [CI]: 1.004-1.110, p=0.035), female (OR: 0.289, 95 % CI: 0.098-0.850, p=0.024), hypertension (OR: 3.182, 95 % CI: 1.160-8.728, p=0.025), high blood glucose level (OR: 1.36, 95 % CI: 1.087-1.701, p=0.007), admission National Institutes of Health Stroke Scale score (OR: 1.082, 95 % CI: 1.003-1.168, p=0.043), and NWU (OR: 1.312, 95 % CI: 1.038-1.659, p=0.023).

CONCLUSIONS

NWU based on Alberta Stroke Program Early Computed Tomography (CT) Score (ASPECTS) could be used to predict the occurrence of futile recanalisation in patients with acute anterior circulation LVO ischaemic stroke.

Causal relationship between cigarette smoking behaviors and the risk of hernias: a Mendelian randomization study

PURPOSE

As the global population continues to age, there is a noticeable yearly rise in the incidence of hernias. Simultaneously, smoking, a widespread addictive behavior and a significant contributor to mortality, has evolved into a pervasive public health concern. Existing literature has already established a connection between smoking and an increased risk of postoperative recurrence and postoperative infections following hernia surgery. However, there remains a dearth of research exploring the association between smoking and hernia morbidity. In this study, our objective is to systematically evaluate the causal relationship between cigarette smoking behaviors and hernia morbidity using a Mendelian randomization (MR) approach.

METHODS

Hernia-related data were sourced from the FinnGen Biobank database, while cigarette smoking behavior data were gathered from the GWAS and Sequencing Consortium of Alcohol and Nicotine Use. To assess the causal relationship, we employed five methods: the weighted median, the weighted mode the inverse variance weighted (IVW), MR-Egger, and the simple mode. Sensitivity analysis was conducted, incorporating Cochran's Q test, the MR-Egger intercept test, leave-one-out analysis, and funnel plot. The presentation of the causal relationship is expressed as an odds ratio (OR) along with their corresponding 95% confidence intervals (CI).

RESULTS

Employing the IVW method as the reference standard, we found that smoking intensity is associated with an increased risk of diaphragmatic hernia (OR = 1.21, 95% CI 1.00-1.46, P = 0.047). These consistent findings were further corroborated by the weighted median and weighted mode methods (OR = 1.26, 95% CI 1.03-1.54, P = 0.026; OR = 1.25, 95% CI 1.02-1.52, P = 0.045). Conversely, when applying the IVW method, we identified no statistically significant causal relationship between smoking age, smoking initiation status, smoking cessation status, and the incidence of hernia.

CONCLUSIONS

Our MR study has uncovered genetic evidence linking smoking intensity and the occurrence of diaphragmatic hernia. The risk of developing diaphragmatic hernia rises in tandem with the intensity of smoking. This emphasizes the crucial role of regularly advising patients to cease smoking in clinical settings.

Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion

BACKGROUND

The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies.

METHODS

Using 2011-2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women's timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics.

RESULTS

Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06-1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04-1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80-1.26]).

CONCLUSIONS

Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

Accounting for Medicaid expansion and regional policy and programs to advance equity in cancer prevention in the United States

BACKGROUND

Many studies compare state-level outcomes to estimate changes attributable to Medicaid expansion. However, it is imperative to conduct more granular, demographic-level analyses to inform current efforts on cancer prevention among low-income adults. Therefore, the authors compared the volume of patients with cancer and disease stage at diagnosis in Ohio, which expanded its Medicaid coverage in 2014, with those in Georgia, a nonexpansion state, by cancer site and health insurance status.

METHODS

The authors used state cancer registries from 2010 to 2017 to identify adults younger than 64 years who had incident female breast cancer, cervical cancer, or colorectal cancer. Multivariable Poisson regression was conducted by cancer type, health insurance, and state to examine the risk of late-stage disease, adjusting for individual-level and area-level covariates. A difference-in-differences framework was then used to estimate the differences in risks of late-stage diagnosis in Ohio versus Georgia.

RESULTS

In Ohio, the largest increase in all three cancer types was observed in the Medicaid group after Medicaid expansion. In addition, significantly reduced risks of late-stage disease were observed among patients with breast cancer on Medicaid in Ohio by approximately 7% and among patients with colorectal cancer on Medicaid in Ohio and Georgia after expansion by approximately 6%. Notably, the authors observed significantly reduced risks of late-stage diagnosis among all patients with colorectal cancer in Georgia after expansion.

CONCLUSIONS

More early stage cancers in the Medicaid-insured and/or uninsured groups after expansion suggest that the reduced cancer burden in these vulnerable population subgroups may be attributed to Medicaid expansion. Heterogeneous risks of late-stage disease by cancer type highlight the need for comprehensive evaluation frameworks, including local cancer prevention efforts and federal health policy reforms.

PLAIN LANGUAGE SUMMARY

This study looked at how Medicaid expansion affected cancer diagnosis and treatment in two states, Ohio and Georgia. The researchers found that, after Ohio expanded their Medicaid program, there were more patients with cancer among low-income adults on Medicaid. The study also found that, among people on Medicaid, there were lower rates of advanced cancer at the time of diagnosis for breast cancer and colon cancer in Ohio and for colon cancer in Georgia. These findings suggest that Medicaid expansion may be effective in reducing the cancer burden among low-income adults.

Alzheimer`s disease mortality in the United States: Cross-sectional analysis of county-level socio-environmental factors

BACKGROUND

Geographical disparities in mortality among Alzheimer`s disease (AD) patients have been reported and complex sociodemographic and environmental determinants of health (SEDH) may be contributing to this variation. Therefore, we aimed to explore high-risk SEDH factors possibly associated with all-cause mortality in AD across US counties using machine learning (ML) methods.

METHODS

We performed a cross-sectional analysis of individuals ≥65 years with any underlying cause of death but with AD in the multiple causes of death certificate (ICD-10,G30) between 2016 and 2020. Outcomes were defined as age-adjusted all-cause mortality rates (per 100,000 people). We analyzed 50 county-level SEDH and Classification and Regression Trees (CART) was used to identify specific county-level clusters. Random Forest, another ML technique, evaluated variable importance. CART`s performance was validated using a "hold-out" set of counties.

RESULTS

Overall, 714,568 individuals with AD died due to any cause across 2,409 counties during 2016-2020. CART identified 9 county clusters associated with an 80.1% relative increase of mortality across the spectrum. Furthermore, 7 SEDH variables were identified by CART to drive the categorization of clusters, including High School Completion (%), annual Particulate Matter 2.5 Level in Air, live births with Low Birthweight (%), Population under 18 years (%), annual Median Household Income in US dollars ($), population with Food Insecurity (%), and houses with Severe Housing Cost Burden (%).

CONCLUSION

ML can aid in the assimilation of intricate SEDH exposures associated with mortality among older population with AD, providing opportunities for optimized interventions and resource allocation to reduce mortality among this population.

Understanding Disparities in Receipt of Complex Gastrointestinal Cancer Surgery at a Small Geographic Scale

OBJECTIVE

To define neighborhood-level disparities in the receipt of complex cancer surgery.

BACKGROUND

Little is known about the geographic variation of receipt of surgery among patients with complex gastrointestinal (GI) cancers, especially at a small geographic scale.

METHODS

This study included individuals diagnosed with 5 invasive, nonmetastatic, complex GI cancers (esophagus, stomach, pancreas, bile ducts, liver) from the Ohio Cancer Incidence Surveillance System during 2009 and 2018. To preserve patient privacy, we combined US census tracts into the smallest geographic areas that included a minimum number of surgery cases (n=11) using the Max-p-regions method and called these new areas "MaxTracts." Age-adjusted surgery rates were calculated for MaxTracts, and the Hot Spot analysis identified clusters of high and low surgery rates. US Census and CDC PLACES were used to compare neighborhood characteristics between the high- and low-surgery clusters.

RESULTS

This study included 33,091 individuals with complex GI cancers located in 1006 MaxTracts throughout Ohio. The proportion in each MaxTract receiving surgery ranged from 20.7% to 92.3% with a median (interquartile range) of 48.9% (42.4-56.3). Low-surgery clusters were mostly in urban cores and the Appalachian region, whereas high-surgery clusters were mostly in suburbs. Low-surgery clusters differed from high-surgery clusters in several ways, including higher rates of poverty (23% vs. 12%), fewer married households (40% vs. 50%), and more tobacco use (25% vs. 19%; all P <0.01).

CONCLUSIONS

This improved understanding of neighborhood-level variation in receipt of potentially curative surgery will guide future outreach and community-based interventions to reduce treatment disparities. Similar methods can be used to target other treatment phases and other cancers.

Individual-level home values and cancer mortality in a statewide registry

BACKGROUND

Prior work assessing disparities in cancer outcomes has relied on regional socioeconomic metrics. These metrics average data across many individuals, resulting in a loss of granularity and confounding with other regional factors.

METHODS

Using patients' addresses at the time of diagnosis from the Ohio Cancer Incidence Surveillance System, we retrieved individual home price estimates from an online real estate marketplace. This individual-level estimate was compared with the Area Deprivation Index (ADI) at the census block group level. Multivariable Cox proportional hazards models were used to determine the relationship between home price estimates and all-cause and cancer-specific mortality.

RESULTS

A total of 667 277 patients in Ohio Cancer Incidence Surveillance System were linked to individual home prices across 16 cancers. Increasing home prices, adjusted for age, stage at diagnosis, and ADI, were associated with a decrease in the hazard of all-cause and cancer-specific mortality (hazard ratio [HR] = 0.92, 95% confidence interval [CI] = 0.92 to 0.93, and HR = 0.95, 95% CI = 0.94 to 0.95, respectively). Following a cancer diagnosis, individuals with home prices 2 standard deviations above the mean had an estimated 10-year survival probability (7.8%, 95% CI = 7.2% to 8.3%) higher than those with home prices 2 standard deviations below the mean. The association between home price and mortality was substantially more prominent for patients living in less deprived census block groups (Pinteraction < .001) than for those living in more deprived census block groups.

CONCLUSION

Higher individual home prices were associated with improved all-cause and cancer-specific mortality, even after accounting for regional measures of deprivation.

Patterns of Diagnostic Evaluation and Determinants of Treatment in Older Patients With Non-transfusion Dependent Myelodysplastic Syndromes

BACKGROUND

Older patients with myelodysplastic syndromes (MDS), particularly those with no or one cytopenia and no transfusion dependence, typically have an indolent course. Approximately, half of these receive the recommended diagnostic evaluation (DE) for MDS. We explored factors determining DE in these patients and its impact on subsequent treatment and outcomes.

PATIENTS AND METHODS

We used 2011-2014 Medicare data to identify patients ≥66 years of age diagnosed with MDS. We used Classification and Regression Tree (CART) analysis to identify combinations of factors associated with DE and its impact on subsequent treatment. Variables examined included demographics, comorbidities, nursing home status, and investigative procedures performed. We conducted a logistic regression analysis to identify correlates associated with receipt of DE and treatment.

RESULTS

Of 16 851 patients with MDS, 51% underwent DE. patients with MDS with no cytopenia (n = 3908) had the lowest uptake of DE (34.7%). Compared to patients with no cytopenia, those with any cytopenia had nearly 3 times higher odds of receiving DE [adjusted odds ratio (AOR), 2.81: 95% CI, 2.60-3.04] and the odds were higher for men than for women [AOR, 1.39: 95%CI, 1.30-1.48] and for Non-Hispanic Whites [vs. everyone else (AOR, 1.17: 95% CI, 1.06-1.29)]. The CART showed DE as the principal discriminating node, followed by the presence of any cytopenia for receiving MDS treatment. The lowest percentage of treatment was observed in patients without DE, at 14.6%.

CONCLUSION

In this select older patients with MDS, we identified disparities in accurate diagnosis by demographic and clinical factors. Receipt of DE influenced subsequent treatment but not survival.

Geographical Patterns and Risk Factor Association of Cardio-Oncology Mortality in the United States

Cardio-oncology mortality (COM) is a complex issue that is compounded by multiple factors that transcend a depth of socioeconomic, demographic, and environmental exposures. Although metrics and indexes of vulnerability have been associated with COM, advanced methods are required to account for the intricate intertwining of associations. This cross-sectional study utilized a novel approach that combined machine learning and epidemiology to identify high-risk sociodemographic and environmental factors linked to COM in United States counties. The study consisted of 987,009 decedents from 2,717 counties, and the Classification and Regression Trees model identified 9 county socio-environmental clusters that were closely associated with COM, with a 64.1% relative increase across the spectrum. The most important variables that emerged from this study were teen birth, pre-1960 housing (lead paint indicator), area deprivation index, median household income, number of hospitals, and exposure to particulate matter air pollution. In conclusion, this study provides novel insights into the socio-environmental drivers of COM and highlights the importance of utilizing machine learning approaches to identify high-risk populations and inform targeted interventions for reducing disparities in COM.

Thermodynamics, statistical mechanics and the vanishing pore width limit of confined fluids

Temperature, particle number and volume are the independent variables of the Helmholtz free energy for a bulk fluid. For a fluid confined in a slit pore between two walls, they are usually complemented by the surface area. However, an alternative choice is possible with the volume replaced by the pore width. Although the formulations with such two sets of independent variables are different, we show they are equivalent and present their relations. Corresponding general statistical-mechanics results are also presented. When the pore width becomes very small, the system behaves rather like a two-dimensional (2D) fluid and one can wonder if thermodynamics still holds. We find it remains valid even in the limit of vanishing pore width and show how to treat the divergences in the normal pressure and the chemical potential so that the corresponding 2D results can be obtained. Thus, we show that the Gibbs surface thermodynamics is perfectly capable of describing small systems.

Understanding Factors Leading to Surgical Attrition for "Resectable" Gastric Cancer

OBJECTIVES

We used a novel combined analysis to evaluate various factors associated with failure to surgical resection in non-metastatic gastric cancer.

METHODS

We identified factors associated with the receipt of surgery in publicly available clinical trial data for gastric cancer and in the National Cancer Database (NCDB) for patients with stages I-III gastric adenocarcinoma. Next, we evaluated variable importance in predicting the receipt of surgery in the NCDB.

RESULTS

In published clinical trial data, 10% of patients in surgery-first arms did not undergo surgery, mostly due to disease progression and 15% of patients in neoadjuvant therapy arms failed to reach surgery. Effects related to neoadjuvant administration explained the increased attrition (5%). In the NCDB, 61.7% of patients underwent definitive surgery. In a subset of NCDB patients resembling those enrolled in clinical trials (younger, healthier, and privately insured patients treated at high-volume and academic centers) the rate of surgery was 79.2%. Decreased likelihood of surgery was associated with advanced age (OR 0.97, p < 0.01), Charlson-Deyo score of 2+ (OR 0.90, p < 0.01), T4 tumors (OR 0.39, p < 0.01), N+ disease (OR 0.84, p < 0.01), low socioeconomic status (OR 0.86, p = 0.01), uninsured or on Medicaid (OR 0.58 and 0.69, respectively, p < 0.01), low facility volume (OR 0.64, p < 0.01), and non-academic cancer programs (OR 0.79, p < 0.01).

CONCLUSION

Review of clinical trials shows attrition due to unavoidable tumor and treatment factors (~ 15%). The NCDB indicates non-medical patient and provider characteristics (i.e., age, insurance status, facility volume) associated with attrition. This combined analysis highlights specific opportunities for improving potentially curative surgery rates.

Nanoscale thermodynamics needs the concept of a disjoining chemical potential

Disjoining pressure was discovered by Derjaguin in 1930's, which describes the difference between the pressure of a strongly confined fluid and the corresponding one in a bulk phase. It has been revealed recently that the disjoining pressure is at the origin of distinct differential and integral surface tensions for strongly confined fluids. Here we show how the twin concept, disjoining chemical potential, arises in a reminiscent way although it comes out eighty years later. This twin concept advances our understanding of nanoscale thermodynamics. Ensemble-dependence (or environment-dependence) is one hallmark of thermodynamics of small systems. We show that integral surface tension is ensemble-dependent while differential surface tension is not. Moreover, two generalized Gibbs-Duhem equations involving integral surface tensions are derived, as well as two additional adsorption equations relating surface tensions to adsorption-induced strains. All the results obtained in this work further evidence that an approach alternative of Hill's nanothermodynamics is possible, by extending Gibbs surface thermodynamics instead of resorting to Hill's replica trick. Moreover, we find a compression-expansion hysteresis without any underlying phase transition.

Ibrutinib Is Associated With Increased Cardiovascular Events and Major Bleeding in Older CLL Patients

Background

Early ibrutinib trials showed an association between ibrutinib use and risk of bleeding and atrial fibrillation (AF) in younger chronic lymphocytic leukemia (CLL) patients. Little is known about these adverse events in older CLL patients and whether increased AF rates are associated with increased stroke risk.

Objectives

To compare the incidence of stroke, AF, myocardial infarction, and bleeding in CLL patients treated with ibrutinib with those who were treated without ibrutinib in a linked SEER-Medicare database.

Methods

The incidence rate of each adverse event for treated and untreated patients was calculated. Among those treated, inverse probability weighted Cox proportional hazards regression models were used to calculate HRs and 95% CIs for the association between ibrutinib treatment and each adverse event.

Results

Among 4,958 CLL patients, 50% were treated without ibrutinib and 6% received ibrutinib. The median age at first treatment was 77 (IQR: 73-83) years. Compared with those treated without ibrutinib, those treated with ibrutinib had a 1.91-fold increased risk of stroke (95% CI: 1.06-3.45), 3.65-fold increased risk of AF (95% CI: 2.42-5.49), a 4.92-fold increased risk of bleeding (95% CI: 3.46-7.01) and a 7.49-fold increased risk of major bleeding (95% CI: 4.32-12.99).

Conclusions

In patients a decade older than those in the initial clinical trials, treatment with ibrutinib was associated with an increased risk of stroke, AF, and bleeding. The risk of major bleeding is higher than previously reported and underscores the importance of surveillance registries to identify new safety signals.

Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach

Disparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the "phenotypes", or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. This study applied the classification and regression tree (CART) to identify county phenotypes of PCVM and geographic information systems to examine the distributions of identified phenotypes. Random forest analysis was applied to evaluate the relative importance of risk factors associated with PCVM. The CART analysis identified seven county phenotypes of PCVM, where high-risk phenotypes were characterized by having greater percentages of people with lower income, higher physical inactivity, and higher food insecurity. These high-risk phenotypes were mostly concentrated in the Black Belt of the American South and the Appalachian region. The random forest analysis identified additional important risk factors associated with PCVM, including broadband access, smoking, receipt of Supplemental Nutrition Assistance Program benefits, and educational attainment. Our study demonstrates the use of machine learning approaches in characterizing community-level phenotypes of PCVM. Interventions to reduce PCVM should be tailored according to these phenotypes in corresponding geographic areas.

Treatment patterns and survival of low and intermediate-risk prostate cancer in end-stage kidney disease: A retrospective population cohort study

BACKGROUND

In accordance with guidelines, observation with or without active surveillance for low-risk prostate cancer increased in recent years in the general population. We compared treatment patterns and mortality for low- and intermediate-risk prostate cancer and mortality rates among end-stage kidney disease (ESKD) and non-ESKD patients.

METHODS

This is a retrospective population-based observational cohort study of Surveillance, Epidemiology, and End Results-Medicare data of men aged 66 years and older with localized prostate cancer (2004-2015). ESKD status was determined using Medicare billing codes. Multivariable logistic regression models and Cox-proportional hazards models were used to study definitive treatment patterns and mortality, respectively.

RESULTS

For low-risk prostate cancer, dialysis patients (N = 83) had lower but not statistically significant odds (OR, 0.74; 95% CI: 0.48-1.16) of receiving definitive treatment than non-ESKD patients (N = 24,935). For those with intermediate-risk prostate cancer, dialysis patients (N = 254) had lower odds to receive definitive treatment (OR, 0.54; 95% CI: 0.42-0.72) than non-ESKD patients (N = 60,883). From 2004-2010 to 2011-2015, for patients with low-risk prostate cancer, while the receipt of definitive treatment for non-ESKD patients trended down from 72% to 48%, it trended up for dialysis patients from 55% to 65%. Kidney transplant patients (N = 33 for low-risk and N = 91 for intermediate-risk) had lower rates of definitive treatment for low-risk and similar rates of treatment for intermediate-risk prostate cancer compared to non-ESKD patients.

CONCLUSIONS

The disparity in definitive treatment rates for low-risk prostate cancer among dialysis patients exists despite their high mortality, compared to the general population.

Describing and assessing a new method of approximating categorical individual-level income using community-level income from the census (weighting by income probabilities)

OBJECTIVE

To assess a new approach (weighting by "income probabilities [IP]") that uses US Census data from the patients' communities to approximate individual-level income, an important but often missing variable in health services research.

DATA SOURCES

Community (census tract level) income data came from the 2017 5-year American Community Survey (ACS). The patient data included those diagnosed with cancer in 2017 in Ohio (n = 65,759). The reference population was the 2017 5-year ACS Public Use Microdata Sample (n = 564,357 generalizing to 11,288,350 Ohioans).

STUDY DESIGN/METHODS

We applied the traditional approach of income approximation using median census tract income along with two IP based approaches to estimate the proportions in the patient data with incomes of 0%-149%, 150%-299%, 300%-499%, and 500%+ of the federal poverty level (FPL) ("class-relevant income grouping") or 0%-138%, 139%-249%, 250%-399%, and 400%+ FPL ("policy-relevant income grouping"). These estimated income distributions were then compared with the known income distributions of the reference population.

DATA COLLECTION/EXTRACTION METHODS

The patient data came from Ohio's cancer registry. The other data were publicly available.

PRINCIPAL FINDINGS

Both IP based approaches consistently outperformed the traditional approach overall and in subgroup analyses, as measured by the weighted average absolute percentage point differences between the proportions of each of the income categories of the reference population and the estimated proportions generated by the income approximation approaches ("average percent difference," or APD). The smallest APD for an IP based method, 0.5%, was seen in non-Hispanic White females in the class-relevant income grouping (compared with 16.5% for the conventional method), while the largest APD, 7.1%, was seen in non-Hispanic Black females in the policy-relevant income grouping (compared with 18.0% for the conventional method).

CONCLUSIONS

Weighting by IP substantially outperformed the conventional approach of estimating the distribution of incomes in patient data.

[A case of sclerocornea combined with open-angle glaucoma]

A patient complained of progressive visual acuity decline in the left eye for 3 years was admitted. The appearance of the patient was bilateral microcornea. After ocular ultrasonography, ultrasound biomicroscopy, etc, the patient was diagnosed as sclerocornea of the left eye with open-angle glaucoma. Trabeculectomy of the left eye was performed after drug treatment failed, and there were no surgical complications. The intraocular pressure of the left eye was normal and the anterior chamber was well formed 6 months after surgery.

Post-Affordable Care Act Improvements in Cancer Stage Among Ohio Medicaid Beneficiaries Resulted From an Increase in Stable Coverage

BACKGROUND

The mechanisms underlying improvements in early-stage cancer at diagnosis following Medicaid expansion remain unknown. We hypothesized that Medicaid expansion allowed for low-income adults to enroll in Medicaid before cancer diagnosis, thus increasing the number of stably-enrolled relative to those who enroll in Medicaid only after diagnosis (emergently-enrolled).

METHODS

Using data from the 2011-2017 Ohio Cancer Incidence Surveillance System and Medicaid enrollment files, we identified individuals diagnosed with incident invasive breast (n=4850), cervical (n=1023), and colorectal (n=3363) cancer. We conducted causal mediation analysis to estimate the direct effect of pre- (vs. post-) expansion on being diagnosed with early-stage (-vs. regional-stage and distant-stage) disease, and indirect (mediation) effect through being in the stably- (vs. emergently-) enrolled group, controlling for individual-level and area-level characteristics.

RESULTS

The percentage of stably-enrolled patients increased from 63.3% to 73.9% post-expansion, while that of the emergently-enrolled decreased from 36.7% to 26.1%. The percentage of patients with early-stage diagnosis remained 1.3-2.9 times higher among the stably-than the emergently-enrolled group, both pre-expansion and post-expansion. Results from the causal mediation analysis showed that there was an indirect effect of Medicaid expansion through being in the stably- (vs. emergently-) enrolled group [risk ratios with 95% confidence interval: 1.018 (1.010-1.027) for breast cancer, 1.115 (1.064-1.167) for cervical cancer, and 1.090 (1.062-1.118) for colorectal cancer.

CONCLUSION

We provide the first evidence that post-expansion improvements in cancer stage were caused by an increased reliance on Medicaid as a source of stable insurance coverage.

Variation in and Factors Associated With US County-Level Cancer Mortality, 2008-2019

IMPORTANCE

The association between cancer mortality and risk factors may vary by geography. However, conventional methodological approaches rarely account for this variation.

OBJECTIVE

To identify geographic variations in the association between risk factors and cancer mortality.

DESIGN, SETTING, AND PARTICIPANTS

This geospatial cross-sectional study used county-level data from the National Center for Health Statistics for individuals who died of cancer from 2008 to 2019. Risk factor data were obtained from County Health Rankings & Roadmaps, Health Resources and Services Administration, and Centers for Disease Control and Prevention. Analyses were conducted from October 2021 to July 2022.

MAIN OUTCOMES AND MEASURES

Conventional random forest models were applied nationwide and by US region, and the geographical random forest model (accounting for local variation of association) was applied to assess associations between a wide range of risk factors and cancer mortality.

RESULTS

The study included 7 179 201 individuals (median age, 70-74 years; 3 409 508 women [47.5%]) who died from cancer in 3108 contiguous US counties during 2008 to 2019. The mean (SD) county-level cancer mortality rate was 177.0 (26.4) deaths per 100 000 people. On the basis of the variable importance measure, the random forest models identified multiple risk factors associated with cancer mortality, including smoking, receipt of Supplemental Nutrition Assistance Program (SNAP) benefits, and obesity. The geographical random forest model further identified risk factors that varied at the county level. For example, receipt of SNAP benefits was a high-importance factor in the Appalachian region, North and South Dakota, and Northern California; smoking was of high importance in Kentucky and Tennessee; and female-headed households were high-importance factors in North and South Dakota. Geographic areas with certain high-importance risk factors did not consistently have a corresponding high prevalence of the same risk factors.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, the associations between cancer mortality and risk factors varied by geography in a way that did not correspond strictly to risk factor prevalence. The degree to which other place-specific characteristics, observed and unobserved, modify risk factor effects should be further explored, and this work suggests that risk factor importance may be a preferable paradigm for selecting cancer control interventions compared with risk factor prevalence.

Medicaid Expansion Associated With Reduction in Geospatial Breast Cancer Stage at Diagnosis Disparities

CONTEXT

Prior studies demonstrate that Medicaid expansion has been associated with earlier-stage breast cancer diagnosis among women with low income, likely through increased access to cancer screening services. However, how this policy change has impacted geospatial disparities in breast cancer stage at diagnosis is unclear.

OBJECTIVE

To examine whether there were reductions in geospatial disparities in advanced stage breast cancer at diagnosis in Ohio after Medicaid expansion.

DESIGN

The study included 33 537 women aged 40 to 64 years diagnosed with invasive breast cancer from the Ohio Cancer Incidence Surveillance System between 2010 and 2017. The space-time scan statistic was used to detect clusters of advanced stage at diagnosis before and after Medicaid expansion. Block group variables from the Census were used to describe the contextual characteristics of detected clusters.

RESULTS

The percentage of local stage diagnosis among women with breast cancer increased from 60.2% in the pre-expansion period (2010-2013) to 62.6% in the post-expansion period (2014-2017), while the uninsured rate among those women decreased from 13.7% to 7.5% during the same period. Two statistically significant ( P < .05) and 6 nonsignificant spatial clusters ( P > .05) of advanced stage breast cancer cases were found in the pre-expansion period, while none were found in the post-expansion period. These clusters were in the 4 largest metropolitan areas in Ohio, and individuals inside the clusters were more likely to be disadvantaged along numerous socioeconomic factors.

CONCLUSIONS

Medicaid expansion has played an important role in reducing geospatial disparities in breast cancer stage at diagnosis, likely through the reduction of advanced stage disease among women living in socioeconomically disadvantaged communities.

Factors affecting timely breast cancer treatment among black women in a high-risk urban community: a qualitative study

BACKGROUND

Black women diagnosed with breast cancer in the U.S. tend to experience significantly longer waits to begin treatment than do their white counterparts, and such treatment delay has been associated with poorer survival. We sought to identify the factors driving or mitigating treatment delay among Black women in an urban community where treatment delay is common.

METHODS

Applying the SaTScan method to data from Ohio's state cancer registry, we identified the community within Cuyahoga County, Ohio (home to Cleveland) with the highest degree of breast cancer treatment delay from 2010 through 2015. We then recruited breast cancer survivors living in the target community, their family caregivers, and professionals serving breast cancer patients in this community. Participants completed semi-structured interviews focused on identifying barriers to and facilitators of timely breast cancer treatment initiation after diagnosis.

RESULTS

Factors reported to impact timely treatment fell into three primary themes: informational, intrapersonal, and logistical. Informational barriers included erroneous beliefs and lack of information about processes of care; intrapersonal barriers centered on mistrust, fear, and denial; while logistical barriers involved transportation and financial access, as well as patients' own caregiving obligations. An informational facilitator was the provision of objective and understandable disease information, and a common intrapersonal facilitator was faith. Logistical facilitators included financial counseling and mechanisms to assist with Medicaid enrollment. Crosscutting these themes, and mentioned frequently, was the centrality of both patient navigators and support networks (formal and, especially, informal) as critical lifelines for overcoming barriers and leveraging facilitating factors.

CONCLUSIONS

The present study describes the numerous hurdles to timely breast cancer treatment faced by Black women in a high-risk urban community. These hurdles, as well as corresponding facilitators, can be classified as informational, intrapersonal, and logistical. Observing similar results on a larger scale could inform the design of interventions and policies to reduce race-based disparities in processes of cancer care.

The identification of treatment-resistant depression patients in electronic health records, a retrospective cohort study in China

Introduction

Previous Electronic Health Records (EHR) based studies adopted various definitions in identifying Treatment-Resistant Depression (TRD) patients. There is a lack of similar attempts among Chinese population which limits the understanding of TRD in China.

Objectives

Assess TRD identification using EHR from a major psychiatric hospital in China.

Methods

This study utilized a retrospective Major Depressive Disorder (MDD) cohort of patients who newly initiated pharmaceutical treatment (2010-2018); follow-up was ended upon 1-year or treatment discontinuation (≥120d without treatment). TRD was first identified based on common clinical definition of two prior regimen failures (change of regimen) with 4-week as regimen adequacy threshold (Def1). Alternative adequacy thresholds of 2-week and 6-week were applied. Based on Def1 (4-week), at least 3 distinctive regimens were additionally required in TRD identification (Def2). Further, a data-driven definition (Def3) based on drug count as having ≥3 antidepressants or ≥1 antipsychotic within 1 year was considered (Cepeda et al., 2018).

Results

From 12257 MDD patients included in the cohort, Def1 identified 633 (5.2%) TRD cases, whereas regimen adequacy thresholds of 2-week and 6-week identified 1772 (14.5%) and 61 (0.5%) cases, respectively. Further, Def2 identified 261 (2.4%) TRD cases. Finally, Def3 yielded 2449 (20.0%) TRD cases, including 1966 exclusive cases that were not identified by Def1.

Conclusions

This study showed different definitions for TRD identification had considerable impact on the number of patients identified among Chinese population, obscuring the comparability among EHR-based TRD studies. As first step, we found the criteria of regimen adequacy as major contributor to the observed variability in China.

Disclosure

No significant relationships.

An informatics infrastructure to catalyze cancer control research and practice

PURPOSE

A disconnect often exists between those with the expertise to manage and analyze complex, multi-source data sets, and the clinical, social services, advocacy, and public health professionals who can pose the most relevant questions and best apply the answers. We describe development and implementation of a cancer informatics infrastructure aimed at broadening the usability of community cancer data to inform cancer control research and practice; and we share lessons learned.

METHODS

We built a multi-level database known as The Ohio Cancer Assessment and Surveillance Engine (OH-CASE) to link data from Ohio's cancer registry with community data from the U.S. Census and other sources. Space-and place-based characteristics were assigned to individuals according to residential address. Stakeholder input informed development of an interface for generating queries based on geographic, demographic, and disease inputs and for outputting results aggregated at the state, county, municipality, or zip code levels.

RESULTS

OH-CASE contains data on 791,786 cancer cases diagnosed from 1/1/2006 to 12/31/2018 across 88 Ohio counties containing 1215 municipalities and 1197 zip codes. Stakeholder feedback from cancer center community outreach teams, advocacy organizations, public health, and researchers suggests a broad range of uses of such multi-level data resources accessible via a user interface.

CONCLUSION

OH-CASE represents a prototype of a transportable model for curating and synthesizing data to understand cancer burden across communities. Beyond supporting collaborative research, this infrastructure can serve the clinical, social services, public health, and advocacy communities by enabling targeting of outreach, funding, and interventions to narrow cancer disparities.

Sub-micrometer focusing setup for high-pressure crystallography at the Extreme Conditions beamline at PETRA III

Scientific tasks aimed at decoding and characterizing complex systems and processes at high pressures set new challenges for modern X-ray diffraction instrumentation in terms of X-ray flux, focal spot size and sample positioning. Presented here are new developments at the Extreme Conditions beamline (P02.2, PETRA III, DESY, Germany) that enable considerable improvements in data collection at very high pressures and small scattering volumes. In particular, the focusing of the X-ray beam to the sub-micrometer level is described, and control of the aberrations of the focusing compound refractive lenses is made possible with the implementation of a correcting phase plate. This device provides a significant enhancement of the signal-to-noise ratio by conditioning the beam shape profile at the focal spot. A new sample alignment system with a small sphere of confusion enables single-crystal data collection from grains of micrometer to sub-micrometer dimensions subjected to pressures as high as 200 GPa. The combination of the technical development of the optical path and the sample alignment system contributes to research and gives benefits on various levels, including rapid and accurate diffraction mapping of samples with sub-micrometer resolution at multimegabar pressures.

[Analysis of HIV-1 genetic subtype and pretreatment drug resistance among men who have sex with men infected with HIV-1 from 19 cities of 6 provinces in China]

Objective: To investigate the distribution of HIV-1 genetic subtypes and pretreatment drug resistance (PDR) among men who have sex with men (MSM) from 19 cities of 6 provinces in China. Methods: From April to November 2019, 574 plasma samples of ART-naive HIV-1 infected MSM were collected from 19 cities in Hebei, Shandong, Jiangsu, Zhejiang, Fujian, and Guangdong provinces, total ribonucleic acid (RNA) was extracted and amplified the HIV-1 pol gene region by nested polymerase chain reaction (PCR) after reverse transcription. Then sequences were used to construct a phylogenetic tree to determine genetic subtypes and submitted to the Stanford drug resistance database for drug resistance analysis. Results: A total of 479 samples were successfully amplified by PCR. The HIV-1 genetic subtypes included CRF01_AE, CRF07_BC, B, CRF55_01B, CRF59_01B, CRF65_cpx, CRF103_01B, CRF67_01B, CRF68_01B and unrecognized subtype, which accounted for 43.4%, 36.3%, 6.3%, 5.9%, 0.8%, 0.8%, 0.4%, 0.4%, 0.2% and 5.5%, respectively. The distribution of genetic subtypes among provinces is statistically different (χ²=44.141, P<0.001). The overall PDR rate was 4.6% (22/479), the drug resistance rate of non-nucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 3.5% (17/479), 0.8% (4/479) and 0.2% (1/479), respectively. The PDR rate of recent infections was significantly higher than that of long-term infections (χ²=4.634, P=0.031). Conclusions: The HIV-1 genetic subtypes among MSM infected with HIV-1 from 19 cities of 6 provinces in China are diverse, and the distribution of subtypes is different among provinces. The overall PDR rate is low, while the PDR rate of recent infections was significantly higher than that of long-term infections, suggesting the surveillance of PDR in recent infections should be strengthened.

Is Medicaid Expansion Narrowing Gaps in Surgical Disparities for Low-Income Breast Cancer Patients?

BACKGROUND

The objective of this study is to understand the effect of Medicaid expansion under the Affordable Care Act (ACA) on patterns of surgical care among low-income breast cancer patients. Emerging literature suggests cancer patients in Medicaid expansion states are presenting with earlier stages of disease. However, less is known regarding the implications of Medicaid expansion on patterns of surgical care in low-income women.

PATIENTS AND METHODS

We compared nonmetastatic 30-64-year-old uninsured or Medicaid-insured Ohio breast cancer patients diagnosed 4 years before and 4 years after the state's 2014 Medicaid expansion (study group); the control group was the privately insured. Time-to-surgery (TTS) was defined as days from diagnosis to surgery. Demographic and treatment variables before and after expansion were examined in multivariate analysis.

RESULTS

There was a 10.4% point increase in breast conservation therapy (BCT) in the study group (pre-ACA 26.3%, post-ACA 36.7%; p < 0.01) compared with a 5.8% point increase in the control group (pre-ACA 36.0%, post-ACA 41.8%; p < 0.01). Disparities in reconstruction narrowed between the study (pre-ACA 21.4%, post-ACA 34.5%; p < 0.01) and the control (37.0% pre-ACA, 44.1% post-ACA group p < 0.01) groups. There was no statistically significant change in mean TTS in the study group (pre-ACA 42.1 days, post-ACA 43.1 days p = 0.18) but there was an increase in TTS in the control group (pre-ACA 35.0 days, post ACA 37.0 days; p < 0.01).

CONCLUSIONS

Medicaid expansion appears to have narrowed disparities in the utilization of BCT and reconstruction in low-income women. However, there was no improvement in surgical delay.

Abstract P3-12-30: Impact of medicaid expansion on breast cancer stage at diagnosis: Exploring the mechanisms at play

Background: Prior studies have shown significant improvements in earlier breast cancer stage at diagnosis following Medicaid expansion. However, the mechanisms behind this finding have not been explored. The timing of Medicaid enrollment among cancer patients has been shown to be associated with cancer stage at diagnosis, with significantly higher percentages of women with late-stage breast cancer enrolling in Medicaid shortly before or after cancer diagnosis (hereafter referred to as the Peri-dx group), compared to those continuously enrolled in Medicaid at least 4 months prior to cancer diagnosis (Pre-dx group). Hence, we conducted a causal mediation study based on a logistic regression model to determine whether the observed improvements in breast cancer stage at diagnosis from Pre- to Post-expansion can be attributed to a decreasing percentage of women in the Peri-dx group, and a corresponding increase in the Pre-dx group. Methods: We used the linked Ohio Cancer Incidence Surveillance System and Medicaid data, and identified women in Ohio age younger than 66 years, diagnosed with incident invasive breast cancer during the period May 2011-December 2017, and enrolled in Medicaid at the time of cancer diagnosis (n=5,880, excluding those with unstaged/unknown-stage cancer). We defined the years 2011-2013 and 2014-2017 as the Pre- and Post-expansion periods, and Month 0 as the month of cancer diagnosis. We identified women enrolled in Medicaid in the -3 to +3-month window in the Peri-dx group, and those continuously enrolled in Medicaid at least 4 months prior to cancer diagnosis in the Pre-dx group. We conducted a causal mediation analysis to estimate the direct, indirect, and total effect of Medicaid expansion on being diagnosed with local-stage disease versus late- (regional- and distant-) stage disease, with the mediator variable being a patient in the Pre-dx group (versus in the Peri-dx group), adjusting for patient- and area-level covariates. Results: The median age of our study population was 53 years; 75.0% were non-Hispanic White. The percent of breast cancer patients diagnosed with late-stage disease was 43.5% and 53.4% in the Pre- and Peri-dx groups, respectively. We observed a clear shift in the distribution of breast cancer patients from the Peri- to the Pre-dx group over time, with an increase in the percentage of women in the Pre-dx group (from 55.2% to 74.2% from the Pre- to Post-Expansion period), and a corresponding decrease in the Peri-dx group (from 44.8% to 25.8%). Findings from our causal mediation analysis, based on a risk difference scale, showed that while the direct effect of Medicaid expansion on being diagnosed with local-stage disease was not significant (coefficient: 0.037, (p=0.297)), both the indirect and total effects were highly significant (0.049 (p &lt; 0.001), and 0.086 (p=0.015)). Conclusion: Our results indicate that the improvements in breast cancer stage at diagnosis from Pre- to Post-Expansion can be attributed to a decrease in the Peri-dx group, and a corresponding increase in the Pre-dx group, which improves access to screening, increases the likelihood of breast cancer patients being engaged with Medicaid providers, and reduces delays in enrollment logistics prior to treatment initiation.

Citation Format: Siran M. Koroukian, Weichuan Dong, Jeffrey Albert, Uriel Kim, Johnie Rose, Cynthia Owusu, Kristine Zanotti, Gregory Cooper, Jennifer Tsui. Impact of medicaid expansion on breast cancer stage at diagnosis: Exploring the mechanisms at play [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-30.

Phenotype Discovery and Geographic Disparities of Late-Stage Breast Cancer Diagnosis across U.S. Counties: A Machine Learning Approach

BACKGROUND

Disparities in the stage at diagnosis for breast cancer have been independently associated with various contextual characteristics. Understanding which combinations of these characteristics indicate highest risk, and where they are located, is critical to targeting interventions and improving outcomes for patients with breast cancer.

METHODS

The study included women diagnosed with invasive breast cancer between 2009 and 2018 from 680 U.S. counties participating in the Surveillance, Epidemiology, and End Results program. We used a machine learning approach called Classification and Regression Tree (CART) to identify county "phenotypes," combinations of characteristics that predict the percentage of patients with breast cancer presenting with late-stage disease. We then mapped the phenotypes and compared their geographic distributions. These findings were further validated using an alternate machine learning approach called random forest.

RESULTS

We discovered seven phenotypes of late-stage breast cancer. Common to most phenotypes associated with high risk of late-stage diagnosis were high uninsured rate, low mammography use, high area deprivation, rurality, and high poverty. Geographically, these phenotypes were most prevalent in southern and western states, while phenotypes associated with lower percentages of late-stage diagnosis were most prevalent in the northeastern states and select metropolitan areas.

CONCLUSIONS

The use of machine learning methods of CART and random forest together with geographic methods offers a promising avenue for future disparities research.

IMPACT

Local interventions to reduce late-stage breast cancer diagnosis, such as community education and outreach programs, can use machine learning and geographic modeling approaches to tailor strategies for early detection and resource allocation.

[G-protein coupled receptor Smo positively regulates proliferation and migration of adult neural stem cells in vitro]

OBJECTIVE

To investigate the role of G-protein coupled receptor Smoothened (Smo) in regulating proliferation and migration of adult neural stem cells (ANSCs) and explore the underlying mechanism.

METHODS

Cultured ANSCs were treated with purmorphamine (PM, an agonist of Smo) or cyclopamine (CPM, an inhibitor of Smo), and the changes in cell proliferation migration abilities were assessed using cell counting kit-8 (CCK8) assay and wound healing assay, respectively. The mRNA expressions of membrane receptor Patched 1 (Ptch1), Smo, glioma-associated oncogene homolog 1 (Gli1), axon guidance cue slit1 (Slit1) and brain-derived neurotrophic factor (BDNF) in the treated cells were detected using real-time quantitative PCR (RT-PCR).

RESULTS

PM significantly promoted the proliferation (P < 0.01) and migration of ANSCs (P < 0.01), and up-regulated the mRNA expressions of Ptch1, Smo, Gli1, Slit1 and BDNF. Treatment with CPM significantly inhibited the proliferation and migration of ANSCs.

CONCLUSION

Modulating Smo activity can positively regulate the proliferation and migration of ANSCs possibly by regulating the expressions of BDNF and Slit1.

[Clinical and molecular pathological features of uterine inflammatory myofibroblastic tumor]

Objective: To evaluate the clinical and molecular pathologic features of uterine inflammatory myofibroblastic tumor (UIMT). Methods: Six UIMT cases collected at Department of Pathology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University from 2019 to 2020. They were analyzed for their general characteristics and clinicopathologic features. ALK rearrangements were detected by fluorescence in situ hybridization. Results: The age of the six patients ranged from 14 to 65 years, the tumors ranged in size from 2.5 to 6.0 cm. The masses were intramural or submucosal in location. Most of them (4/6) were white with yellow foci, and two (2/6) were white with tan foci. Other features noted included a soft or firm appearance. The fasciitis-like pattern of UIMT had myxoid stroma around the spindle cells and inflammatory cells. The ganglion-like pattern showed either fascicular or storiform architecture with diffuse growth. Nuclear atypia was mild or moderate. Mitoses ranged from 2 to 4 per 10 high-power fields. Five tumors were ALK-positive with granular cytoplasmic staining by immunohistochemistry. ALK rearrangements were detected in five cases but was absent in one case. Conclusions: UIMT is an intermediate grade soft tissue tumor, a minority may present with extrauterine spread and/or recurrence. The tumors are composed of spindled cells. The main differentials include smooth muscle tumors and endometrial stromal tumors and their morphology may overlap with that of UIMT. Immunohistochemical positivity for ALK or FISH testing for ALK rearrangements can help in the diagnosis.

Choosing unwisely: Low-value care in older adults with a diagnosis of myelodysplastic syndrome

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Background: In tandem with the Choosing Wisely initiative, ASCO’s Cost of Care Task Force has proposed a list of low-value (LV) procedures and therapies that may be of limited benefit to patients. Myelodysplastic syndrome (MDS) is the most common myeloid malignancy in the US. A complete diagnostic evaluation (CDE) of MDS requires a bone marrow biopsy, fluorescence in situ hybridization and chromosomal analysis. As a potential LV procedure, we evaluated receipt of CDE in MDS patients with isolated or no cytopenias and no transfusion dependence. Methods: Using national 2011-2014 Medicare data, we identified fee-for-service Medicare patients 66 years of age or older with an MDS diagnosis, one or no cytopenias, and no blood transfusions in the 16 weeks before or after an MDS diagnosis (n = 16,779). We examined the following variables that may have provided a clinical context to (or not to) pursue CDE – demographics (age, race, sex); number of Elixhauser comorbid conditions ( < 5 vs >5); nursing home status, prior history of lymphoma, myeloma, MGUS and other cancers; chronic kidney disease (CKD); colonoscopy; and therapies received including erythropoiesis stimulating agents (ESAs), hypomethylating agents (HMAs) or lenalidomide. We conducted Classification and Regression Tree (CART) analysis, a machine learning approach to identify combinations of factors in patients with little clinical justification for CDE, and Cox proportional hazards regression analysis to compare survival outcomes between those with or without CDE. Results: Over half of our study population (51%) received CDE. Of those, 46.6% were 80 years of age or older, 4.8% were nursing home residents; and 33.6% had 5 or more chronic conditions. Results from CART analysis showed that among patients with an isolated cytopenia (e.g., isolated anemia), 46.0% of patients >80 years (n = 860), and 57.7% (n = 1,156) of those in the 66-79 age group underwent CDE in the absence of CKD, colonoscopy, HMA, or ESA. Among those with no cytopenia (n = 3890), 866 patients received CDE in the absence of HMA, ESA, or history of lymphoma or progression to leukemia. In adjusted analyses, no survival benefit was associated with receipt of CDE (p = 0.24). Conclusions: A substantial number of patients with an MDS diagnosis, isolated or no cytopenias, and no transfusion dependence received a CDE in the absence of other diagnoses, procedures, or therapies that may have explained the clinical decision to perform CDE. These procedures entail costs, pain and anxiety, but do not appear to yield useful information to guide clinical management, as evidenced by the comparable survival outcomes between patients who did and did not undergo CDE. To promote patient-centered care, careful patient selection that reduces unnecessary CDE in MDS patients should be a priority in clinical decision-making.

Towards reducing cancer burden within the Medicaid program: Impact of Medicaid expansion on cancer stage at diagnosis

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Background: Studies to date have shown post-Medicaid expansion (M-exp) decreases in the percentage of cancer patients who are uninsured and improvements in cancer stage at diagnosis in states that expanded Medicaid as part of the Affordable Care Act. However, most studies have examined impact of M-exp on stage outcomes at the population level, or among Medicaid and uninsured, rather than solely in the Medicaid population. Using cancer registry data from a non M-exp state (Georgia (GA)) and two M-exp states (Ohio (OH) and New Jersey (NJ)), we compared changes in cancer stage in patients on Medicaid, accounting for individual- and contextual-level characteristics at the Zip Code Tabulation Area (ZCTA) level. Methods: We used GA, OH, and NJ cancer registry data for individuals 20-64 years of age and diagnosed with incident invasive female breast (BC), cervical (CC), and colorectal cancer (CRC). Data spanned from 2010-2017 for GA and OH, and from 2011-2016 for NJ (for BC and CRC only), with 2014 marking the year in which Medicaid was expanded in OH and NJ. We retrieved demographic data (age, race/ethnicity, sex for CRC, insurance status, and cancer stage from the cancer registries), and obtained ZCTA-level data from the American Community Survey (e.g., income, education, and female-headed households). We defined late-stage diagnosis as regional- or distant- stage. We conducted multivariable logistic regression models by state and cancer site to examine changes in late-stage cancer diagnosis pre- and post-M-exp, accounting for individual- and ZCTA-level covariates. Results: The number of patients with incident cancer who were on Medicaid increased by 41.7% (n = 1757 to 2490), 59.6% (327 to 522), and 76.4% (953 to 1681) for BC, CC, and CRC cancers, respectively, in Ohio; by 92.4% (433 to 833) for BC and by over 100% for CRC (232 to 496) in NJ; but by 12.7% (662 to 746) among CRC patients in GA, where the number of BC and CC patients on Medicaid remained relatively stable. Adjusting for individual and contextual-level factors, the adjusted risk ratio (ARR and (95% Confidence Interval)) for late-stage disease was lowest for BC patients in OH (0.93 (0.87, 0.99)) and for CRC patients in GA (0.94 (0.89, 0.99)). The ARR for BC and CRC in NJ were not statistically significant, though they trended towards improvement. Similarly, changes in late-stage for CC were not statistically significant in OH or in GA. Conclusions: The increased number of cancer patients in Medicaid and the reductions in late-stage diagnosis observed may potentially translate into reduced, or at least stabilized, cancer-related morbidity and mortality burden among Medicaid beneficiaries over time. However, reductions in late-stage diagnosis were not consistent across cancer sites or states, possibly due to differences in population demographics, health behaviors, healthcare seeking patterns, and state-level cancer prevention efforts.

Drug utilization of paliperidone in adolescent schizophrenia patients: A retrospective cohort study in China

Introduction

In China, the indications of paliperidone extended in schizophrenia adolescents (12-17 years) was approved by National Medical Products Administration (NMPA) in 2017. But, the utilization of paliperidone in this group needs to be further investigated.

Objectives

To assess paliperidone utilization in schizophrenia adolescents.

Methods

The study employed the electronic medical records (EMRs) database from a psychiatry specialized hospital (PH) and a general hospital (GH), respectively. General information, including birth date, gender, visit date, diagnosis (inpatient and outpatient) with ICD-10 coding, drug characterize, prescription date and dosage, was de-identified and standardized for analysis. Schizophrenia adolescents (ICD-10: F20.x) received at least one prescription of paliperidone between 2018 and 2019 were included in this study. Index date was defined as the date of first identified paliperidone prescription. The patients were followed up until the end of 2019 with the last record, or upon reaching 18 years. The database was analyzed based on days of supply, administration frequency, and daily dose.

Results

Overall, 112 and 117 eligible patients were included in the present study from PH and GH, respectively. The median drug supply was 179.0 days and 44.0 days, respectively, during which median number of prescriptions patients received was 6.0 and 3.0. Paliperidone was mostly initiated alone (57.1% and 88.9%) with frequency of once daily (97.3% and 88.9%), and the median of average daily dose during follow-up was 5.7 mg/day and 6.0 mg/day, respectively.

Conclusions

The duration of paliperidone usage was very different in two hospitals, but the dosages in both hospitals were generally agreed with prescribing information.

Dosage of antipsychotics in China routine practice

Introduction

The antipsychotic dosage of Chinese schizophrenia patients has rarely been studied, although nonstandard dosage has impact on prognosis.

Objectives

To describe the dosage of antipsychotics in China routine practice.

Methods

This was a retrospective cohort study using de-identified data from a Chinese mental health hospital. The included patients were adults (≥18 years) with at least one diagnosis of schizophrenia (ICD-10: F20) and one prescription of any antipsychotic between 2014 and 2019. Date of first identified antipsychotic prescription was defined as index date, patients were followed up until last prescription of antipsychotics, end of 2019, or discontinuation (>60 days without antipsychotic prescription), whichever was earliest. Dosage was summarized using defined daily dose (DDD), calculated by cumulative average daily dose (CAD) with a unit of DDDs/day, i.e., total DDDs of all antipsychotics in follow-up period divided by total days of follow-up. CAD was categorized into low (<0.5 DDDs/day), moderate (0.5-1.5 DDDs/day), and high (>1.5 DDDs/day) groups.

Results

13554 patients were included with an average follow-up of 269.9 days. Median CAD was 0.8 DDDs/day (IQR=0.5-1.3), patients with hospitalization during follow-up and used multiple antipsychotics at the same time had larger median CAD, 1.0 DDDs/day and 1.2 DDDs/days, respectively. There were 3245 (23.9%), 7627 (56.3%), and 2682 (19.8%) patients in low, moderate, and high groups, respectively. The median CAD of high dosage group was 2.5 DDDs/day (IQR=1.9-10.5).

Conclusions

CAD of most Chinese schizophrenia patients was low or moderate. Association between CAD and hospitalization and multiple concurrent antipsychotics merit further research.

Abstract SS1-09: Medicaid expansion associated with earlier stage and improved reconstruction rates in low income breast cancer patients

Introduction: Substantial delays in time to initiation of treatment (TTT) following diagnosis of breast cancer (BC) can inflict a toll on quality of life and can decrease cancer-specific survival. Among low-income, non-elderly Ohio women having newly-diagnosed breast cancer with local or regional spread, we examined TTT and other measures where income-related disparities have been documented, comparing 2011-2013 (pre-Medicaid-expansion) vs. 2014-2016 (post-expansion). Our primary hypothesis was that TTT would decrease following 2014 Medicaid expansion.Methods: Using data from the Northeast Ohio Cancer Assessment and Surveillance Engine (NEO-CASE), a multilevel data infrastructure linking Ohio cancer registry data with community data, we identified 30-64 year-old women with new diagnosis of invasive, non-metastatic BC who were uninsured or on Medicaid when diagnosed. TTT was defined as days from diagnosis to first BC treatment with any modality. We excluded women with TTT=0 (likely coding error). The main exposure was pre- or post-Medicaid expansion period defined as 2011-2013 or 2014-2016, respectively. We examined additional key demographic and treatment variables before and after expansion and in multivariate analysis of TTT. We used a previously-described probability-weighting approach based on neighborhood median income to approximate excluding women with incomes above 138% of Federal Poverty Level. As a control analysis, we compared pre- and post-expansion TTT among privately insured women, probability weighted to select for higher income individuals.Results: Our study population included 1177 and 1143 women diagnosed with BC pre- and post-expansion, respectively. Demographic characteristics were similar, though mean age increased by 1.2 years (p&lt;0.01) post-expansion. Mean TTT increased by 2 days post-expansion, from 41.1 to 43.1 (p=0.18). The control analysis showed a similar small post-expansion increase. Though no significant change in TTT was observed, the percent uninsured in the low-income group fell by more than half (from 32.9% to 14.1%; p&lt;0.01), and the percent of women diagnosed with regional stage disease decreased from 38.1% to 30.9% (p&lt;0.01). The percent of women undergoing reconstructive surgery increased from 12.1% to 16.7% (p&lt;0.01) from the pre- to the post-Medicaid expansion period, a change not observed in the privately-insured control group. Cox proportional hazards regression models controlling for the effect on TTT of covariates shown in the table revealed an adjusted hazard rate (AHR) of 0.950 (95% CI 0.855 to 1.056) associated with Medicaid expansion. Stage-stratified Cox models showed a similar lack of effect among women with local and regional disease. Discussion: TTT increased by 2 days post-expansion; however, this increase was neither statistically significant nor clinically meaningful. Despite the lack of improvements in TTT, we note the dramatic drop in the percent uninsured among BC patients post-expansion, as well as a marked decrease in the percent of women diagnosed with regional-stage disease, and an increase in BC patients undergoing reconstruction. Taken together, these trends show an overall positive impact of Medicaid expansion on BC process of care and outcome measures.

Pre-expansionPost-expansionpN11771143Mean TTT in days (SD)41.1 (37.1)43.1 (33.7)0.18Mean age at diagnosis (SD)51.6 (8.39)52.8 (8.14)&lt;0.01Non-Hispanic African American (%)269 (22.9)225 (19.7)0.07Married/Partnered (%)408 (34.7)417 (36.5)0.38Uninsured (%)387 (32.9)161 (14.1)&lt;0.01Non-metropolitan census tract (%)285 (24.2)232 (20.3)0.03Area Deprivation Index 9 or 10: most deprived (%)274 (23.3)238 (20.8)0.17Regional disease (%)448 (38.1)353 (30.9)&lt;0.01Reconstructive surgery (%)143 (12.1)191 (16.7)&lt;0.01Breast conserving surgery (%)509 (43.2)590 (51.6)&lt;0.01

Citation Format: Johnie Rose, Weichuan Dong, Uriel Kim, Samilia Obeng-Gyasi, Siran Koroukian. Medicaid expansion associated with earlier stage and improved reconstruction rates in low income breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SS1-09.