Administrative Datasets Research Articles

Sex-specific clinical outcomes and healthcare resource utilization in the 5 years following hospitalization for heart failure

Abstract Background Heart failure (HF) a leading cause of hospitalization, and sex differences in care have been described. Purpose We assessed sex-specific clinical outcomes and healthcare resource utilization following hospitalization for HF. Methods This was an exploratory analysis of patients hospitalized for HF across 10 Canadian hospitals enrolled in the Patient-Centred Care Transitions in HF pragmatic cluster-randomized trial. Primary outcome was all-cause mortality. Secondary outcomes included all-cause readmissions, HF readmissions, emergency department (ED) visits, and healthcare resource utilization. Outcomes were obtained via linkages with administrative datasets. Results The 4441 patients (50.7% female) had high event rates. At 5 years of follow-up, 63.6% male and 65.5% of male and female patients, respectively, had died (p=0.19); 85.4% and 84.4% of male and female patients, respectively, were readmitted with no sex differences in mean [SD] all-cause readmissions (males, 2.8 [7.8] and females, 3.0 [8.4], p=0.54) or HF readmissions (males, 0.9 [3.6] and females, 0.9 [4.5], p=0.80) per person. The mean (SD) annual total healthcare costs per patient was $80334 (116762) for males and $81010 (112625) for females, with no sex difference (p=0.90); however, there were sex differences in cost breakdown: males incurred greater costs from specialist, hemodialysis, and day surgical care, and females incurred greater costs from home visits and long-term care. Conclusions Males and females were at similarly high risk of mortality and readmissions, and had similar total healthcare costs following hospitalized for HF. Notwithstanding similar risks, males received relatively more specialist and invasive care, and females received relatively more supportive care.

Assessing the alignment of obstructive hypertrophic cardiomyopathy pharmacological treatments with ESC guidelines in Germany

Abstract Introduction The European Society of Cardiology (ESC) recently updated treatment guidelines for hypertrophic cardiomyopathy (HCM). Purpose The aim of this study was to describe the treatment of obstructive HCM in Germany and assess alignment with the 2014 and 2023 ESC guidelines. Methods Adults with HCM were identified using a nationally representative administrative claims dataset (WIG2 Benchmark database) from several German Statutory Health Insurances between 2012 and 2018. Obstructive HCM was identified as any obstructive HCM diagnosis (ICD-10: I42.1) or any HCM diagnosis (I42.2, I42.9) with septal reduction therapy. The index date was defined as the date where the patient met all eligibility criteria for HCM. Minimum follow-up time was set to one year. Patients had at least 1 year of baseline data prior to the index HCM diagnosis and were followed up for at least 1 year after the diagnosis (or until death within 1 year). Patients with phenocopies were excluded. ESC guideline-directed pharmacological treatments for HCM included beta-blockers (BB), calcium channel blockers (CCB), disopyramide, and/or mavacamten (approved by EMA June 2023). While the 2014 ESC Guidelines on Diagnosis and Management of HCM were applicable during the study, recommendations pertaining to the use of non-vasodilating BBs and non-dihydropyridine (DHP) CCBs did not change in the 2023 ESC Guidelines for the Management of Cardiomyopathies; thus, this study applies to both. Results Out of 6793 patients with HCM analysed in the period 2012-2018, 1,141 had obstructive HCM. The average follow-up was 5 years. Patients were mostly male (62%) with a mean age of 60 years. Hypertension, hyperlipidaemia, coronary artery disease, heart failure, and atrial fibrillation were among the most common comorbidities; the mean Charlson Comorbidity Index score was 2.3. At index, 46% of patients were on BB monotherapy, 23% were on CCB monotherapy, <1% were on a combination of BBs or a combination of CCBs, 9% were on a combination of BBs and CCBs, and as many as 22% received no HCM treatment. Patients experienced 1615 unique treatment combinations throughout the study across all lines of therapy (Table 1). The most common treatments were bisoprolol (24%), metoprolol (19%), amlodipine (12%), and verapamil (12%). The use of propranolol was negligible (1%). 43% of pharmacological treatments were not in line with ESC guidelines. The most common reason for not aligning was using DHP-CCBs or vasodilating BBs. Conclusion This study shows that 57% of obstructive HCM treatments received by patients during the study were aligned with recommendations from the 2023 ESC guidelines on cardiomyopathies. Research is needed to investigate barriers and enablers to implementing the guideline including awareness of recommended treatments, as well as the management of comorbidities.

Cardiovascular disease risk in people with diabetes in the era of universal diabetes screening

Abstract Background/Introduction Traditionally, most people with diabetes have been considered at high cardiovascular disease (CVD) risk and CVD preventive treatment has been recommended for almost all patients after diagnosis. However, guidelines are increasingly recommending a more stratified approach to preventive treatment informed by predicted CVD risk. In the early 2000’s, New Zealand initiated the world-first national diabetes screening programme, as a component of a national CVD risk assessment programme, and by 2016, approximately 90% of eligible New Zealand adults had been screened. We hypothesised that in the era of universal diabetes screening, many recently diagnosed patients will be at low CVD risk and that contemporary CVD risk prediction equations would be required to accurately assess their risk. Purpose We aimed to develop sex-specific 5-year CVD risk prediction models in people with diabetes in New Zealand using a contemporary natural-population based cohort, and to characterise the distribution of CVD risk. Methods De-identified individual-level linkage of multiple health administrative datasets was undertaken to establish a cohort of almost all adults with diabetes in the northern region of New Zealand (one-third of the national population), without CVD or heart failure, and aged 30–74 years on January 1, 2014, with follow-up linkage to hospitalisations and mortality until December 31, 2018. Sex-specific models were developed to estimate the 5-year risk of CVD hospitalisation or death, with 15 pre-defined predictors, including sociodemographic variables, diabetes-related and renal function measures. Results 64,645 participants (median age: 57 years [IQR: 49–65]) were included in the final cohort, of whom 4,992 had first CVD events during 301,272 person-years follow-up. Models calibrated well in both women and men (Figure 1). Overall, increasing age; high deprivation level; smoking-related hospitalisations or use of smoking cessation medications; history of atrial fibrillation; high levels of haemoglobin A1c, total cholesterol to HDL cholesterol ratio, and albumin-to-creatinine ratio; use of blood pressure-lowering medications and insulin were associated with elevated CVD risk. Median 5-year CVD risks were 4.9% (IQR: 2.9%–8.1%) in women and 7.7% (4.8%–12.0%) in men. There was a wide range of predicted 5-year CVD risk, with 51% of women and 27% of men having a predicted risk below 5%, and 6% of women and 16% of men having a risk of 15% or above (Figure 2). Conclusions This study demonstrated marked heterogeneity in predicted CVD risk in people with diabetes in an era of universal diabetes screening. As diabetes screening is increasingly undertaken as part of a routine CVD risk assessment, these findings will have important clinical implications for accurately targeting new but expensive CVD preventive medications to the highest risk patients.

Real-world analysis exploring the association between anti-hypertensive therapy with perindopril-based single-pill combinations (SPC) and cardiovascular outcomes and all-cause mortality in Italy

Abstract Background/Introduction A combination of blood pressure (BP)-lowering medications is recommended by guidelines as an effective strategy to obtain rapid and optimal BP control in hypertensive patients. However, the prescription of multiple BP-lowering medications increases the pill burden, potentially reducing medication adherence. Guidelines also recommend using single pill combinations(SPCs) containing ≥2 anti-hypertensive medications as a practical approach to simplify treatment schedules and possibly improve adherence. Yet, real-world evidence on the association between SPC or free combination of BP-lowering medications and hyperthensive patient outcome remains limited. Purpose We compared the association of SPC versus free-pill combination(free) on cardiovascular outcomes and all-cause mortality in hypertensive patients treated with perindopril(PER)-based therapies in real clinical practice in Italy. Methods A retrospective analysis was conducted using administrative databases covering 6.7 million health-assisted Italian residents. Among adults with hospitalization discharge diagnosis or exemption code for hypertension between 2010 and 2021, the study included patients prescribed with a combination of PER with amlodipine(AML) and/or indapamide(IND), either as SPC or free or mixed (SPC plus separate pill) combinations. Results The analysis included 24,476 hypertensive subjects receiving a PER-based therapy, 22,663 (93%) of them using SPC, 1458 (6%) free and 355 (1.4%) mixed. The last cohort was not included in the analysis due to the small sample size (N=355). The patients in the free cohort were significantly older than those in the SPC cohort (69.5±12.3 vs. 64.3±12.2 years, p<0.001), showed a higher number of pre-existing comorbidities (0.5±0.8 vs. 0.4±0.7, p<0.001), and received a larger number of different medications (pill burden: 1.2±1.7 vs. 0.7±1.3, p<0.001). To minimize selection bias, the groups were balanced with propensity score and inverse probability weighting (IPW), adjusting for baseline covariates, including comorbidity profile and pill burden. The IPW-adjusted Kaplan-Meier plots and Cox’s proportional hazard model (Table 1) revealed that, compared with SPC users, patients on free regimens had a significantly increased risk of all-cause mortality (36%, p<0.001), all cardiovascular events (45%, p<0.001), ischemic heart disease (29%, p<0.05), cerebrovascular events (84%, p<0.001), and occurrence of the composite outcome cardiovascular events/all-cause mortality (40%, p<0.001). Conclusions This real-world data from a large Italian administrative dataset suggested that PER-based anti-hypertensive therapy with SPC results in significant clinical benefits in terms of lowered risk of cardiovascular/cerebrovascular events and all-cause mortality. Reducing pill burden and simplifying therapeutic schedules is of crucial importance to maximize the potential benefits derived from the prescription of anti-hypertensive treatment.

Pathways to Eviction

Abstract Over the past several years, socio-legal researchers have focused attention on the phenomenon of eviction, particularly in low-income communities and communities of color. One major aspect of the eviction phenomenon has been largely overlooked: how and why certain eviction filings result in forced, legally compelled tenant moves and others do not. Through coding of the legal documents associated with eviction filings and multi-level regression analysis, this article advances the analysis of evictions in two crucial ways. First, it identifies and describes the frequency of the distinct legal procedural pathways that result in forced tenant moves once an eviction case has been filed. Second, it identifies the case, tenancy, neighborhood, and property correlates of forced tenant moves and of distinct procedural pathways to forced tenant moves. The article demonstrates that move-out agreements are the primary procedural pathway by which tenants are forcibly moved, yet they have been largely overlooked in previous eviction research because they are not easily analyzable in administrative datasets. The regression analyses advance the growing work examining the role of landlord characteristics in shaping tenants’ housing stability and break new ground in identifying the characteristics of the different pathways through which tenants are forced out of their homes following eviction filing.

Application of Duty of Candour legislation in post-colonoscopy colorectal cancer: a prospective cohort study.

Background & Study Aims The study investigates the application of Duty of Candour (DoC) legislation in the context of post-colonoscopy colorectal cancers (PCCRCs). DoC mandates transparent disclosure of notifiable safety incidents to patients in the English National Health Service, including those leading to severe or moderate harm. This study aims to analyse the application of DoC in PCCRCs, improve understanding of the legislation and identify challenges in its implementation. Patients & Methods A national audit of PCCRCs was conducted between September 2021 to May 2022. PCCRCs were identified using linked administrative datasets and root-cause analyses were performed using a structured template. 1,724 PCCRCs were included. 'Avoidability' and harm categorised into specific levels, with guidance provided to improve consistency in judgments. Results 16% of PCCRCs resulted in major harm or death, of which 27%(75) were at least probably avoidable. Hospitals deemed DoC discharge necessary in only 53% of these cases. When including moderate harm, 11% of all PCCRCs would trigger DoC discharge, yet this was deemed necessary in only 41% of these cases. Conclusions There is inconsistent application of DoC in PCCRC cases. Challenges include determining 'avoidability' and harm, particularly when there is a delay in diagnosis. Clearer guidance and definitions of harm are needed to improve adherence to regulations.

Help-Seeking Behaviors of Young People with Problematic Sexualized Behaviors

ABSTRACT A substantial proportion of all reported child sexual abuse is perpetrated by other young people, though it is challenging to accurately depict its prevalence. Even less is known about the help-seeking behaviors of young people. Understanding how they seek help for their own problematic sexualized behavior is crucial to better inform therapeutic interventions and early intervention opportunities. This study used an administrative dataset of contacts (N = 901) received by Kids Helpline over nine years. Given the paucity of research on this topic, our approach to draw upon the contacts made to Kids Helpline by young people concerned about their own sexualized interests or behaviors is innovative and exploratory. Descriptive analyses were conducted to examine the characteristics of each contact as well as the demographics of the young people making contact. The present study examined the characteristics of 695 males and 206 females (aged 10 to 25) seeking help for their own problematic sexualized behaviors. Young people who contacted Kids Helpline for problematic sexualized behavior reported the following specific concerns: sexual behaviors (40.50%) and pornography use (38.20%). A quarter of contacts (25.86%) raised multiple concerns. Results suggest that intervention should be provided early and in an age-graded way. Several implications for theory and practice are discussed.

Patterns of Migration Following Dementia Diagnosis

Diseases have historically prompted individual relocations to mitigate the risk of disease acquisition or improve access to care. As dementia prevalence increases, comprehending the migration patterns of affected individuals is vital for public policy. To quantify the association of dementia diagnosis with migration patterns by examining the proportion of individuals with dementia who relocate, the timing of their moves relative to diagnosis, and the nature of their new living arrangements, whether in institutional settings or different households. This cohort study leveraged a comprehensive dataset of national Medicare claims and assessments spanning from 2012 to 2020, including Medicare Beneficiary Summary File and nursing home administrative datasets. The study focused on beneficiaries who received diagnoses in 2016 of dementia, myocardial infarction, chronic obstructive pulmonary disease, or colon cancer. Analyses were performed from March 2023 to August 2024. The primary outcome was migration, defined as change in county or state. The analysis distinguished between migrations with and without a nursing home stay. By tracking patients' residential county for 4 years before and after diagnosis, a difference-in-differences approach was used to contrast migration tendencies associated with dementia against the other 3 conditions. The sample included 1 626 127 Medicare beneficiaries (mean [SD] age, 80.1 [8.0] years; 922 194 women [56.7%]) who received diagnoses of the 4 conditions in 2016. In total, 818 862 had a new dementia diagnosis (age, 82.0 [7.8] years; 492 146 women [60.1%]). Comparing between the prediagnosis and postdiagnosis months, the proportion migrating to a different county increased by 8.5 percentage points (95% CI, 7.6-9.4 percentage points) for individuals with dementia and between 4.2 to 5.8 percentage points among those with myocardial infarction, chronic obstructive pulmonary disease, or colon cancer. The difference-in-difference estimates indicated a 3.9 percentage point (95% CI, 3.7-4.0 percentage points) increase in intercounty migration and a 1.9 percentage point (95% CI, 1.8-2.0 percentage points) increase in interstate migration for patients with dementia, effectively doubling the likelihood of migration compared with the other conditions. Of the excess migrations resulting from dementia diagnosis, 55% occurred in community settings, and 45% occurred in institutional settings. In this retrospective cohort study of Medicare fee-for-service beneficiaries, dementia was associated with a marked increase in migration rates over other major illnesses. This finding underscores the need to understand the factors associated with these distinct migration behaviors.

Design of a Location-Based Case-Control Study of Built Environment Risk Factors for Pedestrian Fatalities in the U.S.

The location-based case-control design is a useful approach for studies where the exposures of interest are aspects of the environment around the location of a health event such as a pedestrian fatality. In this design locations are the unit of analysis and an enumerated cohort of locations are followed through time for the health events of interest and a case-control study of locations is nested within the cohort. Locations where events occurred (case-locations) are compared to matched locations where these events did not occur (control-locations). We describe the application of this design to the issue of pedestrian fatalities using a cohort of 9,612,698 intersections, 17,737,728 road segments, and 222,318 entrance/exit ramp segments that existed in 2017 across all 384 U.S. Metropolitan Statistical Areas. This cohort of locations was followed up from Jan 1, 2017 to Dec 31, 2018 for pedestrian fatalities using the National Highway Traffic Safety Administration Fatality Analysis Reporting System. In total, 10,587 fatalities were identified as having occurred on cohort locations and 21,174 matched control locations were selected using incidence density sampling. Geographic information systems, spatially linked administrative data sets and virtual neighborhood audits via Google Street View are underway to characterize study locations.

Prediction of the Remaining Useful Life of Lithium-Ion Battery Using Multilayer Perceptron

Cogitating the reliability of the supply and ensuring continuous delivery of power to the loads, especially in the growing demand for Lithium-Ion batteries in electric vehicle applications, prediction of the remaining useful life of Lithium-Ion batteries is crucial for the timely replacement. For prediction of non-linear and chaotic relationship, experience-based approach, physics-based approach and data driven approach are used among which data driven approach is a model free, accurate and reliable approach. Therefore, a driven approach in predicting remaining useful life can be implemented in the battery management system. This research uses a multilayer perceptron to predict the remaining useful life of the battery. The NASA Ames Prognostics Center of Excellence (PCoE) battery dataset is used to test the proposed methodology. The use of multilayer perceptron for remaining life prediction seems promising despite the significant number of jump points, gaps in data and a small quantity of experimental data in the National Aeronautics and Space Administration (NASA) dataset. The predicted result was obtained with 8.52 % mean absolute error and 9.59 % root mean square error. When compared with the predicted results of different literatures, proposed multilayer perceptron with sliding window approach outperforms most of the existing approach. Incorporation of optimization techniques and hybrid algorithm in proposed approach can further enhance the accuracy of the model.

Exploring the potential cost-effectiveness of a new computerised decision support tool for identifying fetal compromise during monitored term labours: an early health economic model

BackgroundAround 60% of term labours in the UK are continuously monitored using cardiotocography (CTG) to guide clinical labour management. Interpreting the CTG trace is challenging, leading to some babies suffering adverse outcomes and others unnecessary expedited deliveries. A new data driven computerised tool combining multiple clinical risk factors with CTG data (attentive CTG) was developed to help identify term babies at risk of severe compromise during labour. This paper presents an early health economic model exploring its potential cost-effectiveness.MethodsThe model compared attentive CTG and usual care with usual care alone and simulated clinical events, healthcare costs, and infant quality-adjusted life years over 18 years. It was populated using data from a cohort of term pregnancies, the literature, and administrative datasets. Attentive CTG effectiveness was projected through improved monitoring sensitivity/specificity and potential reductions in numbers of severely compromised infants. Scenario analyses explored the impact of including litigation costs.ResultsNationally, attentive CTG could potentially avoid 10,000 unnecessary alerts in labour and 2400 emergency C-section deliveries through improved specificity. A reduction of 21 intrapartum stillbirths amongst severely compromised infants was also predicted with improved sensitivity. Attentive CTG could potentially lead to cost savings and health gains with a probability of being cost-effective at £25,000 per QALY ranging from 70 to 95%. Potential exists for further cost savings if litigation costs are included.ConclusionsAttentive CTG could offer a cost-effective use of healthcare resources. Prospective patient-level studies are needed to formally evaluate its effectiveness and economic impact in routine clinical practice.

Validity and timeliness of cancer diagnosis data collected during a prospective cohort study and reported by the English and Welsh cancer registries: a retrospective, comparative analysis

Cancer places a high burden on society and health-care systems. Cancer research requires high-quality data, which is resource-intensive to obtain. Using administrative datasets such as cancer registries could improve the efficiency of cancer studies if data were valid and timely. We aimed to compare the validity and timeliness of diagnostic cancer data on-site during the SYMPLIFY study to that obtained from the cancer registries of England and Wales. Cancer data were collected from 5461 participants across 44 hospital sites during a prospective observational study in England and Wales, SYMPLIFY (ISRCTN10226380). Linked cancer data were obtained from Digital Health and Care Wales (DHCW), the Welsh Cancer Intelligence and Surveillance Unit (WCISU), and the English National Cancer Registration Dataset (NCRD) and Rapid Cancer Registration Dataset (RCRD), regularly between April, 2022, and September, 2023. The primary objectives of the study were to evaluate the validity (via assessment of the proportion of completed data fields and concordance with SYMPLIFY sites), and timeliness of the data in all datasets, for all cancers diagnosed within 9 months of study enrolment. Data fields investigated were cancer site via International Classification of Disease, 10th Revision (ICD-10) code; cancer morphology via International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) morphology histology code and broad morphological grouping; overall stage; and TNM classification. For data collected between April, 2022, and September, 2023, completeness at the last data cut available for each dataset ranged from 84% to 100% for ICD-O-3 morphology, from 43% to 100% for overall stage, and from 74% to 83% for TNM stage. The concordance between SYMPLIFY data and NCRD was 96% (95% CI 92-98) for ICD-10, 60% (53-66) for ICD-O-3 morphology, 83% (78-88) for ICD-O-3 broad morphology groupings, 73% (67-78) for stage, and 51% (44-59) for TNM; and with WCISU was 89% (95% CI 81-94) for ICD-10, 63% (53-73) for ICD-O-3 morphology, 80% (70-87) for ICD-O-3 broad morphology groupings, 83% (74-90) for overall stage, and 49% (38-61) for TNM stage. Concordance between SYMPLIFY and RCRD was 95% (95% CI 92-98) for ICD-10, 67% (60-74) for ICD-O-3 morphology, 85% (79-90) for ICD-O-3 broad morphology groupings, and 73% (65-80) for overall stage; and between SYMPLIFY and DHCW was 96% (91-99) for ICD-10, 74% (64-83) for ICD-O-3 morphology, 84% (75-91) for ICD-O-3 broad morphology groupings, and 87% (74-95) for stage. The SYMPLIFY dataset reached completion at 12 months post-enrolment in November, 2022, compared with 13 months for NCRD in December, 2023. RCRD and DHCW reached completion at 13 months and 15 months post-enrolment, in December, 2022, and February, 2023, respectively. We report similar completeness of data fields, concordance, and timeliness between on-site and centrally collected cancer outcomes data. Our findings suggest that central registry data can help alleviate the resource burden in clinical trials and improve cancer research. Cancer registries might need additional resources to provide data for registry-based trials at scale. GRAIL Bio UK.

Cohort profile: Understanding the influence of early life environments and health and social service system contacts over time and across generations through the Western Australian Aboriginal Child Health Survey (WAACHS) Linked Data Study

PurposeDespite the volume of accumulating knowledge from prospective Aboriginal cohort studies, longitudinal data describing developmental trajectories in health and well-being is limited. The linkage of child and carer cohorts from...

Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand

BackgroundIn the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aimed to apply ML methods on extensive national-level health and social administrative datasets to assess the utility of these for predicting future diabetes complications, including by ethnicity.MethodsFive ML models were used to predict CVD events among all people with known diabetes in the population of New Zealand, utilizing nationwide individual-level administrative data.ResultsThe Xgboost ML model had the best predictive power for predicting CVD events three years into the future among the population with diabetes (N = 145,600). The optimization procedure also found limited improvement in prediction by ethnicity (using area under the receiver operating curve, [AUC]). The results indicated no trade-off between model predictive performance and equity gap of prediction by ethnicity (that is improving model prediction and reducing performance gaps by ethnicity can be achieved simultaneously). The list of variables of importance was different among different models/ethnic groups, for example: age, deprivation (neighborhood-level), having had a hospitalization event, and the number of years living with diabetes.Discussion and conclusionsWe provide further evidence that ML with administrative health data can be used for meaningful future prediction of health outcomes. As such, it could be utilized to inform health planning and healthcare resource allocation for diabetes management and the prevention of CVD events. Our results may suggest limited scope for developing prediction models by ethnic group and that the major ways to reduce inequitable health outcomes is probably via improved delivery of prevention and management to those groups with diabetes at highest need.

Ischemic events are infrequent in patients with ovarian hyperstimulation syndrome

BackgroundCase reports describe arterial thrombosis including ischemic stroke associated with severe ovarian hyperstimulation syndrome (OHSS), but the prevalence of major ischemic events during or shortly after OHSS is unknown. MethodsUsing publicly available administrative datasets in the United States between 2015 and 2020, we conducted two separate cross-sectional studies of patients with OHSS. We included all patients with OHSS. Our study outcome was any hospitalization for acute ischemic stroke, acute myocardial infarction, cerebral venous sinus thrombosis, pulmonary embolism, or acute deep venous thrombosis during the index hospitalization or within 90 days of OHSS diagnosis. Results and conclusionsWe found very few major ischemic events in patients with OHSS.

Abstract B006: Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada

Abstract Background: Despite the comparably comprehensive healthcare system in Canada, health inequities are widespread, and this holds true for breast cancer patients in Ontario. It is thus essential to learn if socio-demographic disparities continue after diagnosis of breast cancer, and if these contribute to higher mortality rates in the lower income quintile groups. Methods: We conducted a real-word population-based study using a provincial health administrative dataset from Ontario, Canada. We included patients diagnosed with HER2-negative breast cancer, treated with surgery and adjuvant chemotherapy, between 2009 to 2017. We used log-rank test and Kaplan Meier curves to compare overall survival (OS) between breast cancer populations among income quintile groups, and Cox regression to evaluate risk factors, using hazard ratio (HR) and 95% confidence intervals (CI). Results: We analysed 10,634 women diagnosed with stage I-III breast cancer. At diagnosis, in the Q1 group, there were 248 (15.8%) women with stage I, 997 (63.7%) with stage II, and 320 (20.45%) with stage III. In the Q5 group, there were 568 (22.15%), with stage I, 1,532 (59.75%) with stage II and 464 (18%) with stage III. Comparison between those in the lowest versus highest income quintile groups, and lymph node (LN) status at diagnosis, showed that in Q1, 534 (34%) women had LN 0 and 897 (57.3%) had LN+. In Q5, there were 954 (37.2%) women with LN 0 and 1,379 (53.8%) with LN+. Similarly, comparing tumor size (TS) at diagnosis, we found that in Q1, there were 463 (32.2%) women with TS≤ 2 cm and 974 (67.8%) with TS > 2 cm. In Q5, 915 (39%) women had TS≤ 2 cm and 1,426 (61%) had TS > 2 cm. In the Q1 group, there were 325 (20.7%) patients who received non- anthracycline and 1,240 (79.3%) treated with anthracycline-taxane chemotherapy. In Q5, there were 673 (26.2%) women treated with non-anthracycline and 1,891 (73.8%) who received anthracycline-taxane chemotherapy. The OS analysis based on the household income group compared to Q5 showed a substantial difference in the Q1 (HR 1.52, 1.2–1.9, p = 0.0002) and Q2 (HR 1.34, 1.1–1.7, p = 0.006) groups. In Cox regression models, Q5 group and endocrine receptor (ER) positive were significantly associated with reduced mortality risk. There was a significant correlation between increased risk of death and the following: receipt of non- anthracycline chemotherapy, TS > 2 cm, LN+ and grade 3 histology. Conclusion: Our study found an uneven distribution of breast cancer patients between the lowest and highest income quintile groups. Women with HER2-negative breast cancer who were part of the lower income quintile groups, thereby likely with a socioeconomic disadvantage, had the lowest OS. At diagnosis, these women were more likely to have more advanced breast cancer staging, including larger tumors, LN+, and receive anthracycline-based chemotherapy as compared to those with higher household income. Further research is warranted to identify the key social determinants that are systematically associated with disparities in equitable access to care. Citation Format: Danilo Giffoni M. M. Mata, Rossanna C. Pezo, Kelvin K.W. Chan, Ines Menjak, Andrea Eisen, Maureen Trudeau. Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B006.

Affirmative Action for Black, Indigenous and Quilombola Students at a Brazilian University

Multiculturalism and cultural diversity permeate various sectors of society, including higher education. The educational policies implemented in this sphere appear to promote social and educational equality. The aim of this study was to examine this subject by analysing the affirmative action policy implemented in a Brazilian university. It sought to understand whether this policy has contributed to the access and completion of undergraduate programmes of black and mixed-race, indigenous and quilombola students. The analysis was conducted based on data relating to the access and dropout of students who enrolled in the university through the quota and reservation systems. Data were collected from university administrative datasets and a questionnaire administered to undergraduate course coordinators and students who had benefited from the policy in question and dropped out of university. The findings reveal, on the one hand, an increase in the intake of black and mixed-race, indigenous and quilombola students. On the other hand, a high dropout rate was observed among these students, which may raise the possibility that the policy in question is not completely successful.

A hybrid‐ensemble model for software defect prediction for balanced and imbalanced datasets using AI‐based techniques with feature preservation: SMERKP‐XGB

AbstractMaintaining software quality is a significant challenge as the complexity of software is increasing with the rise of the software industry. Software defects are a primary concern in complex modules, and predicting them in the early stages of the software development life cycle (SDLC) is difficult. Previous techniques to address this issue have not been very promising. We have proposed “A hybrid ensemble model for software defect prediction using AI‐based techniques with feature preservation” to overcome this problem. We have used the National Aeronautics and Space Administration (NASA) dataset from the PROMISE repository for testing and validation. By applying exploratory data analysis (EDA), feature engineering, scaling, and standardization, we found that the dataset is imbalanced, which can negatively affect the model's performance. To address this, we have used the Synthetic Minority Oversampling (SMOTE) technique and the edited nearest neighbor (ENN) (SMOTE‐ENN). We have also used recursive feature elimination cross‐validation (RFE‐CV) with a pipeline to prevent data leaking in CV and kernel‐based principal component analysis (K‐PCA) to minimize dimensionality and selectively relevant features. The reduced dimensional data is then given to the eXtreme Gradient Boosting (XGBoost) for classification, resulting in the hybrid‐ensemble (SMERKP‐XGB) model. The proposed SMERKP‐XGB model is better than previously developed models in terms of accuracy (CM1: 97.53%, PC1: 92.05%, and PC2: 97.45%, KC1:95.65%), and area under the receiver operating characteristic curve values (CM1:96.30%, PC1:98.30%, and PC2:99.30%: KC1: 93.54) and other evaluation criteria mentioned in the literature.

The biodemography of human aging (Gompertz-Makeham law) applied to surgical mortality modelling: a retrospective national cohort study.

The Gompertz-Makeham law describes a characteristic pattern of mortality in human populations where death rate is near constant between age 18 and 30 years (Makeham's Law) and rises exponentially thereafter (Gompertz Law). This pattern has not been described in surgical populations, but if true, would have important implications for understanding surgical risk and design and interpretation of surgical risk models. The aim of this study was to determine if the Gompertz-Makeham law applies to perioperative mortality risk and the conditions under which it may apply. We examined the relationship between age and 1-month postoperative all-cause mortality risk in a 10-year New Zealand administrative dataset comprising of 5,615,100 surgical procedures from 2007 to 2016. The dataset includes patient and surgical factors including procedures, American Society of Anesthesiologist's physical status score (ASA-PS), diagnoses and other relevant details. Semi-logarithmic graphs of mortality risk and age were plotted. Linear regression models were fitted, with regression line slope and Pearson's correlation coefficient calculated. The primary outcome occurred in 114,782 (2.0%) of 5,615,100 included participants. The Gompertz-Makeham law seems to apply to the national surgical population as a whole (slope = 0.0241, R2 = 0.971). The law applies in all subgroups studied including sex, ASA-PS, surgical acuity, surgical severity category, cancer status and ethnicity (slopes 0.0066 to 0.0307, R2 0.771 to 0.990). Important interactions were found between age, mortality risk and three high risk groups (cancer diagnosis, ASA-PS 4-5 and high surgical severity). The Gompertz-Makeham law seems to apply in a national cohort of surgical patients. The inflection point for increased 1-month risk is apparent at age 30 years. A strict exponential rise in mortality risk occurs thereafter. This finding improves our understanding of surgical risk and suggests a concept-driven approach to improve modelling of age and important interactions in future surgical risk models.

Variational Bayes machine learning for risk adjustment of general outcome indicators with examples in urology

Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally oversimplified and not equipped to disentangle complex factors influencing outcomes that are out of a healthcare professional’s control. We present VIRGO, a novel variational Bayes model trained on routinely collected, large administrative datasets to risk-adjust outcome QIs. VIRGO uses detailed demographics, diagnosis, and procedure codes to provide individualized risk adjustment and explanations on patient factors affecting outcomes. VIRGO achieves state-of-the-art on external datasets and features capabilities of uncertainty expression, explainable features, and counterfactual analysis capabilities. VIRGO facilitates risk adjustment by explaining how patient factors led to adverse outcomes and expresses the uncertainty of each prediction, allowing healthcare professionals to not only explore patient factors with unexplained variance that are associated with worse outcomes but also reflect on the quality of their clinical practice.