Trends and Disparities in Cardiovascular Disease Burden Among Leukemia Related Deaths in the United States (1999–2020): A CDC WONDER Disproportionality Analysis

Trends and Disparities in Cardiovascular Disease Burden Among Leukemia Related Deaths in the United States (1999–2020): A CDC WONDER Disproportionality Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends and Disparities in Cardiovascular Disease Burden Among Leukemia Related Deaths in the United States (1999–2020): A CDC WONDER Disproportionality Analysis Faizan Ahmed, Tehmasp Rehman Mirza, Fenilkumar Kotadiya, Yusra Junaid, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7777208/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract BACKGROUND : The presence of cardiovascular disease (CVD) in patients with leukemia leads to worse clinical outcomes, but the disparities in this issue are still not fully examined. This research investigates differences in the CVD burden related to leukemia deaths across various demographic and geographic contexts using CDC WONDER data from 1999 to 2020. METHODOLOGY : A disproportionality analysis was conducted to calculate reporting odds ratio (ROR) of CVD burden in leukemia patients compared to all-cause deaths across age groups 15–85 years. A ROR greater than 1 indicated a higher burden of CVD in cancer patients. Average Annual Percentage Changes (AAPCs) were calculated to evaluate trends, with p-values determining significance. RESULTS : The highest ROR was found in the 15–24 age cohort (2.565), decreasing with age but rising slightly in older adults (85+: 0.56). The 55–64 age group experienced the most significant annual increase (AAPC: 2.02). Males consistently showed higher RORs compared to females, however, the most notable rise was in middle-aged females (AAPC: 1.51). Among racial groups, young Hispanics had the highest ROR (2.637), whereas NH Whites (55–64 AG) experienced the largest AAPC (1.43). Midwest had the lowest ROR but also exhibited the steepest regional increase (45–54: 1.78). Urban regions reported higher RORs than rural areas, with medical facilities displaying the highest RORs. CONCLUSION : These results highlight the importance of developing focused cardiovascular care strategies, especially for high-risk groups such as younger individuals, males, Hispanics, and those residing in urban areas. Public health initiatives should target these disparities to enhance outcomes for patients with leukemia. Cardiovascular Oncology Leukemia Mortality Odds Ratio Burden Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Cardiovascular disease (CVD) and cancer are the leading causes of death in the United States, together accounting for a significant portion of annual mortality. In 2023, heart disease was the top cause of death, responsible for 690,882 fatalities, closely followed by cancer, which claimed 598,932 lives. ​ 1 ​ The coexistence of these two diseases, both sharing common risk factors such as diabetes, hypertension, obesity, and smoking, exacerbates patient outcomes ​ 2,3 ​. For individuals with leukemia, a malignant hematologic condition, the added burden of cardiovascular morbidity can notably increase mortality risk ​ 4 . Studies suggest that the presence of CVD in cancer patients can elevate the risk of death by 2 to 6 times compared to the general population ​ 5 ​. Leukemia, as a diverse group of hematologic cancers, presents unique treatment challenges and survival outcomes, especially when complicated by cardiovascular disease. The incidence and mortality rates of leukemia and CVD, however, are not evenly distributed across the population. There are significant regional, urban, and overall disparities in these rates ​ 6 ​. These disparities are driven by factors such as socioeconomic status, healthcare access, and the availability of specialized care. This study aims to examine the intersection of regional, gender, racial, urban, place of death, and overall disparities in the burden of leukemia and cardiovascular disease, with a focus on leukemia mortality across age groups 15–85. Using data from the CDC WONDER system, we will analyze the reporting odds ratio of CVD mortality among leukemia patients and explore how these outcomes vary by region, urban vs. overall settings. By investigating these disparities, this research seeks to provide insight into the disproportionate impact of leukemia and CVD in different population groups and inform public health strategies to address the dual burden of these diseases, especially in at-risk regions and communities. METHODS STUDY SETTING AND POPULATION: Disproportionality Analysis is a statistical method commonly used in pharmacovigilance to understand the relation between specific drugs and reported adverse effects. It explores the disparity between expected and reported values. Applying a similar reasoning, we explored the contrast in burden of cardiovascular disease (CVD) in leukemia and all-cause deaths. In this study, death certificate data were retrieved from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database and examined for the years 1999 to 2020. The focus was on cardiovascular, leukemia, and all-cause mortalities in populations aged 15 and above, identified using ICD-10 codes: CVD (I00-I99) and leukemia (C91-C95). The dataset includes cause of death information from death certificates across the 50 states and the District of Columbia. Data were extracted using the Multiple Cause-of-Death Public Use files, which record all causes listed on death certificates, whether underlying or contributing. The study population was divided into four key variables: A (records with both CVD and leukemia), B (records with leukemia), C (records with CVD), and D (all mortality records). Additionally, the pre-selected age range (15+) was stratified into 10-year groups: [Young Adults: 15–24, 25–34; Middle-aged Adults: 35–44, 45–54, 55–64; Older Adults: 65–74, 75–84, and 85+]. For each age group, the CVD burden in Leukemia and all-cause mortality was evaluated, and the ratio was calculated to understand the relative impact or Reporting Odds Ratio (ROR) of CVD. For the sake of simplicity, the 10-year age groups are combined into 3 aforementioned cohorts. This study was exempt from local institutional review board approval because it used a de-identified government-issued public use dataset and adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting. DATA CALCULATION The core analytical measure in this study is the Reporting Odds Ratio (ROR), a comparative metric that assesses the relative frequency or burden of a specific outcome across two distinct populations or conditions. It is calculated by dividing the deaths of the outcome in one group by the deaths in another, providing insight into how much more or less likely the outcome is to occur in one group compared to another. In this study, ROR was used to compare the burden of cardiovascular disease (CVD) between cancer-related and all-cause-related mortalities. ROR = Burden of CVD in Cancer Mortality / Burden of CVD in All-Cause Mortality For clarity, the full stepwise derivation of the ROR calculations is described in the Supplementary Material . In addition to calculating the Reporting Odds Ratio (ROR), we also determined the corresponding confidence intervals (CIs) and standard errors (SEs) to ensure the statistical robustness of our findings. To quantify the uncertainty around the ROR estimates, we calculated the SE of the ROR using the formula for the SE of a ratio, which accounts for the variability in both the numerator and the denominator. The CIs for the ROR were then derived using the SE, applying the normal distribution to construct a 95% confidence interval. These calculations allowed us to assess the precision of the ROR estimates and determine whether observed differences were statistically significant, providing a comprehensive understanding of the disparities or trends being analyzed. DATA ABSTRACTION Each age group was further stratified by sex, race/ethnicity, urbanization, and location of death, including medical facilities (outpatient, emergency room, inpatient, death on arrival, or status unknown), home, hospice, and nursing home/long-term care facility. Race/ethnicity was classified as Non-Hispanic (NH) White, NH Black or African American, Hispanic or Latino, NH American Indian or Alaskan Native, and NH Asian or Pacific Islander. This information relies on reported data on death certificates and has been validated in previous analyses of the WONDER database.8 The National Center for Health Statistics Urban-Rural Classification Scheme was used to assess the population by urban (large metropolitan areas with populations ≥ 1 million, medium/small metropolitan areas with populations between 50,000-999,999) and rural (populations < 50,000) counties, according to the 2013 U.S. Census classification. Regions were categorized into Northeast, Midwest, South, and West, following the U.S. Census Bureau definitions. The ROR for each cohort was calculated, and trends were analyzed over the study period from 1999 to 2020. STATISTICAL ANALYSIS: To examine and quantify trends within the individual cohorts, ROR values with their standard errors from 1999 to 2020 were input into the Join Point Regression Program (Join Point V 5.2.0.0, National Cancer Institute), which calculated the average annual percent change (AAPC) with 95% confidence intervals (CIs). This method identifies significant changes in ROR over time by fitting log-linear regression models where temporal variation occurred. APCs and AAPCs were considered increasing or decreasing if the slope describing the change in mortality was significantly different from zero, as determined by 2-tailed t-tests. A p-value of < 0.05 was considered statistically significant. RESULTS OVERALL The overall burden of cardiovascular disease (CVD) in leukemia-related mortality [A/B] shows an upward trend across all Age Groups (AGs), peaking in the oldest group [15–24: 0.23, 55–64: 0.26, 85+: 0.43]. In a similar fashion, the CVD burden in all-cause deaths [C/D] also increased progressively across AGs, although it demonstrated a more pronounced rise [15–24: 0.10, 55–64: 0.50, 85+: 0.66]. As a result, the variation in increase caused the ROR in older AGs to be lower than expected, even though they had a higher burden of CVD in leukemia-related deaths [15–24: 2.17 (2.072–2.281), 55–64: 0.53 (0.525–0.542), 85+: 0.647 (0.641–0.653)] (Supplementary Table 1, Supplementary Fig. 1 , Fig. 1 ) . Middle-aged AGs have the lowest value forming a distinctive reverse J-shaped curve. Trend Analyses from 1999–2020 displayed a rise in AAPCs across all age groups with the highest increase in ROR in the 55–64 AG and 75–84 AG [55–64): 1.18 AAPC, 95% CI: 0.96–1.38, p < 0.01)] (Supplementary Table 2) . This trend can be attributed to the rising AAPC of CVD burden in leukemia mortality coupled with the declining AAPC of CVD burden in all-cause deaths [A/B (75–84): 0.57, 95% CI: 0.41 to 0.68, p < 0.01; C/D (75–84): -0.53, 95% CI: -0.56 to -0.50, p < 0.01] (Supplementary Table 2) . SEX Sex-based analysis indicated that males consistently exhibited a higher ROR across the majority of age groups throughout the study period ( Fig. 2 ) . The highest recorded ROR was found in the male demographic [Male (15–24): 2.505 (2.358–2.662); Female (15–24): 1.586 (1.467–1.715)]. The lowest ROR was observed in the female group within the older age categories [65–74: 0.531 (0.521–0.542)], while the ROR for the male group was similar [65–74: 0.557 (0.55–0.565)] (Supplementary Table 3, Supplementary Fig. 2) . The increase in ROR towards middle age groups was more pronounced for females [Female (45–54): 0.54 (0.522–0.558); Male (45–54): 0.563 (0.541–0.585)]. Trend analysis revealed that all age groups exhibited a positive AAPC, with the most significant increase recorded in young males [Male (35–44): 1.59 (0.59–2.43), p = 0.002; Female (55–64): 1.51* (0.95–1.86), p < 0.01] (Supplementary Table 2). REGION In regional stratification, the Northeast and West census regions had a greater ROR than the other regions in all AGs, with the disparity becoming less pronounced in older AGs ( Fig. 3 ) . Overall, ROR was greater in younger age groups, with the highest observed in the Western region [West (15–24): 2.565 (2.355–2.794); Northeast (15–24): 2.093 (1.97–2.223); South (15–24): 2.006 (1.851–2.174); Midwest (15–24): 1.681 (1.482–1.907)]. The Midwest region had the lowest ROR [45–54: 0.437 (0.412–0.463). (Supplementary Table 4 and Supplementary Fig. 3) . Trend based analyses revealed the steepest positive AAPC was recorded in the South [South (45–54): 1.84*, 95%CI: 1.15–2.75, p < 0.01; Midwest (45–54): 1.78*, 05% CI: 1-2.76, p < 0.01; West (55–64): 1.38*, 95% CI: 1.02–1.86, p < 0.01; Northeast (75–84): 0.65*, 95% CI: 0.18–0.94, p < 0.01]. Furthermore, contrary to other regions Northeast displayed negative trend in AGs spanning 15 to 54 [(15–24): -1.11*, 95% CI: -2.2 to -0.22, p = 0.02; (45–54): -0.87, 95% CI: -1.67 to -0.21, p = 0.015] (Supplementary Table 2) . RACE In racial stratification, Hispanics consistently exhibited a higher ROR compared to other racial groups across younger and middle age groups. While the disparity was less pronounced in older age ranges NH American Indians had a slightly higher ROR ( Fig. 4 ) . Age groups with lower averages showed a greater overall ROR, with the peak observed among Hispanics [Hispanics (15–24): 2.637 (2.419–2.874); Non-Hispanic (NH) Asians (15–24): 2.196 (1.782–2.706); NH Blacks (15–24): 2.195 (1.947–2.476); NH American Indians (15–24): 1.975 (1.163–3.354); NH Whites (15–24): 1.972 (1.838–2.116)] (Supplementary Table 5 and Supplementary Fig. 4) . The middle age groups recorded the lowest RORs, especially among NH American Indians [45–54: 0.48 (0.337–0.683)]. Trend based analyses revealed negative AAPCs dominantly in the younger AGs for Hispanics (35–44: -1.21 95% CI: -2.56-0.09, p = 0.06) and NH Black (35–44: -0.63, -0.74 (-1.87-0.28), p = 0.14) ( Supplemental Table 2) . Additionally, most AGs categorized by race exhibited a positive AAPC, with the most significant increase observed in NH White individuals [NH White (55–64): 1.43*, 95% CI: 1.09–1.64, p < 0.01; NH Black (55–64): 0.97* (0.43–1.67), p = 0.016; Hispanics (75–84): 0.92* (0.46–1.36), p = 0.02; NH Asian or Pacific Islander (65–74): 0.84*, 95% CI: 0.02–2.09, p = 0.04 (Supplementary Table 2) . Owing to suppressed data, trends for NH American Indians could not analyzed. URBANISATION In urban stratification, both Metropolitan and Nonmetropolitan cohorts exhibited comparable RORs across all age categories, particularly among the middle-aged and elder age groups ( Fig. 5 ) . The overall ROR was greater in younger demographics, peaking in Metropolitan regions [Metro (15–24): 2.223 (2.112–2.34); Non-Metro (15–24): 1.88 (1.642–2.152)]. The lowest ROR was observed in Nonmetropolitan regions [Non-Metro (45–54): 0.489 (0.459–0.522); Metro (45–54): 0.557 (0.542–0.572)]. (Supplementary Table 3, Supplementary Fig. 5) Throughout the study period, there was an upward trend in ROR for all age groups. The steepest AAPC was noted in Non-Metropolitan areas [Non-metro (55–64): 2.02*, 95% CI: 1.35–2.4, p < 0.01; Metro (55–64): 1.21* (0.9–1.45), p < 0.01] (Supplementary Table 2). PLACE OF DEATH Medical facilities had a higher ROR compared to other locations consistently in all AGs ( Fig. 6 ) . The highest ROR for each location was generally seen in younger AGs (Medical Facility (15–24): 1.473; Decadents Home (15–24): 1.199; Hospice (15–24): 0.854; Nursing Home (85+): 0.715). Other/Unknown locations had a notable ROR in the younger AGs (15–24: 4.810), alluding to possible limitations (Supplementary Table 6) . Discussion Stratification of the combined Reporting Odds Ratio (ROR) by age groups of 10 years or more indicates that the 15-24y age group possesses the highest ROR, then the 25-34y and 35-44y age groups. The ROR levels off within the 45-84y age group, followed by rising in the 85y + age group to create a reverse bell-shaped curve. An ROR > 1 among the younger groups suggests that a major contribution of cardiovascular disease (CVD) in Leukemia death is due to co-pathway CVD risk fueled by concurrent Leukemia with CVD risk being perpetuated by Leukemia and its treatment. The highest CV mortality risk in patients with Leukemia was reported in < 50 years old patients within < 2 years following diagnosis in one retrospective cohort study ​ 7 ​. Our work also demonstrates a rising trend in ROR in all age groups from 1999–2020, highlighting the necessity for focused cardio-oncological interventions in patients aged 15–34 years. In older age groups with an ROR of less than 1, deaths due to CVD and Leukemia most likely rise individually, lowering the combined odds ratio. A reverse J-shaped rise in the oldest age groups indicates vulnerability towards developing both simultaneously. Due to limitations in available data, a competing risk model could not be performed. Stratification by gender indicates that males have a greater ROR than females in the 15-24y and 25-34y groups, while other groups have similar values. Previous studies identified increased cardiac-specific mortality in older male AML patients undergoing chemotherapy, while our research emphasizes the higher CVD burden in younger male Leukemia mortality ​ 7 ​. The ROR among males has been rising in all age groups over time, while among females, the ROR has fallen in the 15-24y and 35-44y groups, remained unchanged in the 25-34y group, and risen in older age groups, especially in the oldest cohort. Stratification by race demonstrates that among younger groups, Hispanics have the highest ROR, followed by Asians, and differences become less pronounced after 35 years of age. Higher CVD mortality among Hispanics and Asians was noted in a retrospective study, and our results validate the same, noting racial disparities in younger populations. Racial trends over time (1999–2020) exhibit varied patterns. In the Hispanic group, ROR decreased between 2006–2010, rose between 2010–2016, and fell again between 2016–2020 in the youngest category. The 35-44y category presented a decrease, while older ones presented an increase. In Whites, ROR has increased in all age categories, with an increased rise among older groups. The older Black population also increases ​ 8–12 ​. The Asian population shows a general rise except for a fall in the oldest age group. Due to healthcare access inequalities experienced by Hispanic/Latin populations, specific cardio-oncological interventions are required. Regional stratification shows that the Northeast and Western regions have a greater ROR than the Midwest and Southern regions in all age groups, with the disparity more evident in younger age groups. In spite of greater overall CVD mortality in the South and Midwest, the greater ROR in the Northeast and West indicates that Leukemia and its treatment could be a greater contributor to CVD-related mortality in these areas. ROR has risen over time (1999–2020) in the Midwest and South in all age groups. The Western region has a decrease in the youngest group but an increase in others ​ 7 . The Northeast indicates a reduction in the youngest and 45-54y age groups but an increase in all the rest. Based on these patterns, the building of cardio-oncology clinics across the country is necessary, with priority in the Northeast and West. Stratification according to urban-rural residence shows an increased ROR in urban cities, especially in younger patients. In the long term (1999–2020), ROR has also gone up in metropolitan and non-metropolitan areas ​ 13 ​. Increasing cardio-oncology clinics in urban areas will help manage the growing CVD burden among Leukemia patients. Lastly, stratification by place of death reveals that among the youngest cohort, nursing homes and LTAC centers have the highest ROR, perhaps indicating chemotherapy-induced cardiotoxicity. Previous research has previously established a high frequency of cardiac complications in patients with AML treated with chemotherapy ​ 14 ​. Cardiotoxicity could play a significant role in the CVD burden in Leukemia patients, and further studies on the cardiovascular profiles of emerging and conventional chemotherapeutic agents are warranted. Our results indicate the importance of targeted cardio-oncological interventions, especially in younger men, Hispanics, urban areas, and the Northeast and Western states, to counteract the cardiovascular impact in Leukemia mortality. LIMITATIONS The retrospective methodology of this study precludes the establishment of causal linkages and limits competing risk analysis, limiting understanding of how CVD and leukemia interact in mortality. Reliance on broad cause-of-death data may result in misdiagnosis, particularly when both illnesses contribute to mortality. Individual-level characteristics such as treatment regimens, illness stage, comorbidities, and cardiotoxicity were not included, which influenced ROR interpretation. Key variables such as socioeconomic status, healthcare access, and lifestyle behaviors were not available, which influenced discrepancies. ROR variations by region and urban/rural area can be a result of unrecorded healthcare infrastructure and access to specialized care. The study time frame (1999–2020) may not fully capture the influence of newer leukemia treatments that carry different cardiovascular risks. CDC WONDER database does not report deaths < 10 leading to multiple cohorts having suppressed data. Lastly, variations in treatment protocols and healthcare practices over time and across regions may have influenced the observed trends. CONCLUSION This analysis of the CDC WONDER database (1999–2020) reveals significant demographic and geographical variations in the relative occurrence ratios (ROR) of leukemia among people with CVD. The highest ROR is typically found in younger populations (15–24 years old), whereas older age groups (55–64 and 75 + years old) have been showing an increased trend since 2018. Males, particularly those in the younger and older populations, exhibit greater RORs than females. The highest total ROR is found among Hispanic populations, particularly in younger age groups. Regionally, the Western United States has the highest ROR in younger people, whereas the Midwest has lower RORs in middle-aged groups. Urbanization patterns show slightly higher RORs in urban regions, with an increase among elderly populations. These findings highlight the importance of further research and targeted public health measures to address inequities in leukemia and CVD mortality. Declarations Data Availability Statement: All data used in this study are publicly available through the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database. The authors obtained access in accordance with the CDC’s data use guidelines. Funding Statement: This research did not receive any grants from funding agencies in the public, commercial or not-for-profit sectors. Conflict of Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. All authors have reviewed and approved the final manuscript. Ethics Approval Statement: This study used de-identified, publicly available mortality data from the CDC WONDER database. As no human subjects or identifiable data were involved, institutional review board approval was not required. Patient Consent Statement: Not applicable. Informed consent was waived because the study used de-identified, publicly available data. Permission to Reproduce Material from Other Sources: Not applicable. No third-party material was reproduced. Clinical Trial Registration: Not applicable. References Ahmad FB, Cisewski JA, Anderson RN. Mortality in the United States — Provisional Data, 2023. MMWR Morb Mortal Wkly Rep . 2024;73(31):677-681. doi:10.15585/MMWR.MM7331A1 Wilcox NS, Amit U, Reibel JB, Berlin E, Howell K, Ky B. Cardiovascular disease and cancer: shared risk factors and mechanisms. Nat Rev Cardiol . 2024;21(9):617-631. doi:10.1038/S41569-024-01017-X Armstrong GT, Oeffinger KC, Chen Y, et al. 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Analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCardiovascular disease (CVD) and cancer are the leading causes of death in the United States, together accounting for a significant portion of annual mortality. In 2023, heart disease was the top cause of death, responsible for 690,882 fatalities, closely followed by cancer, which claimed 598,932 lives. ​\u003csup\u003e1\u003c/sup\u003e​ The coexistence of these two diseases, both sharing common risk factors such as diabetes, hypertension, obesity, and smoking, exacerbates patient outcomes ​\u003csup\u003e2,3\u003c/sup\u003e​. For individuals with leukemia, a malignant hematologic condition, the added burden of cardiovascular morbidity can notably increase mortality risk ​\u003csup\u003e4\u003c/sup\u003e. Studies suggest that the presence of CVD in cancer patients can elevate the risk of death by 2 to 6 times compared to the general population ​\u003csup\u003e5\u003c/sup\u003e​.\u003c/p\u003e\u003cp\u003eLeukemia, as a diverse group of hematologic cancers, presents unique treatment challenges and survival outcomes, especially when complicated by cardiovascular disease. The incidence and mortality rates of leukemia and CVD, however, are not evenly distributed across the population. There are significant regional, urban, and overall disparities in these rates ​\u003csup\u003e6\u003c/sup\u003e​. These disparities are driven by factors such as socioeconomic status, healthcare access, and the availability of specialized care.\u003c/p\u003e\u003cp\u003eThis study aims to examine the intersection of regional, gender, racial, urban, place of death, and overall disparities in the burden of leukemia and cardiovascular disease, with a focus on leukemia mortality across age groups 15\u0026ndash;85. Using data from the CDC WONDER system, we will analyze the reporting odds ratio of CVD mortality among leukemia patients and explore how these outcomes vary by region, urban vs. overall settings. By investigating these disparities, this research seeks to provide insight into the disproportionate impact of leukemia and CVD in different population groups and inform public health strategies to address the dual burden of these diseases, especially in at-risk regions and communities.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eSTUDY SETTING AND POPULATION:\u003c/h2\u003e\u003cp\u003eDisproportionality Analysis is a statistical method commonly used in pharmacovigilance to understand the relation between specific drugs and reported adverse effects. It explores the disparity between expected and reported values. Applying a similar reasoning, we explored the contrast in burden of cardiovascular disease (CVD) in leukemia and all-cause deaths. In this study, death certificate data were retrieved from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database and examined for the years 1999 to 2020. The focus was on cardiovascular, leukemia, and all-cause mortalities in populations aged 15 and above, identified using ICD-10 codes: CVD (I00-I99) and leukemia (C91-C95). The dataset includes cause of death information from death certificates across the 50 states and the District of Columbia. Data were extracted using the Multiple Cause-of-Death Public Use files, which record all causes listed on death certificates, whether underlying or contributing. The study population was divided into four key variables: A (records with both CVD and leukemia), B (records with leukemia), C (records with CVD), and D (all mortality records). Additionally, the pre-selected age range (15+) was stratified into 10-year groups: [Young Adults: 15\u0026ndash;24, 25\u0026ndash;34; Middle-aged Adults: 35\u0026ndash;44, 45\u0026ndash;54, 55\u0026ndash;64; Older Adults: 65\u0026ndash;74, 75\u0026ndash;84, and 85+]. For each age group, the CVD burden in Leukemia and all-cause mortality was evaluated, and the ratio was calculated to understand the relative impact or Reporting Odds Ratio (ROR) of CVD. For the sake of simplicity, the 10-year age groups are combined into 3 aforementioned cohorts. This study was exempt from local institutional review board approval because it used a de-identified government-issued public use dataset and adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDATA CALCULATION\u003c/h3\u003e\n\u003cp\u003eThe core analytical measure in this study is the Reporting Odds Ratio (ROR), a comparative metric that assesses the relative frequency or burden of a specific outcome across two distinct populations or conditions. It is calculated by dividing the deaths of the outcome in one group by the deaths in another, providing insight into how much more or less likely the outcome is to occur in one group compared to another. In this study, ROR was used to compare the burden of cardiovascular disease (CVD) between cancer-related and all-cause-related mortalities.\u003c/p\u003e\u003cp\u003eROR\u0026thinsp;=\u0026thinsp;Burden of CVD in Cancer Mortality / Burden of CVD in All-Cause Mortality\u003c/p\u003e\u003cp\u003eFor clarity, the full stepwise derivation of the ROR calculations is described in the \u003cb\u003eSupplementary Material\u003c/b\u003e. In addition to calculating the Reporting Odds Ratio (ROR), we also determined the corresponding confidence intervals (CIs) and standard errors (SEs) to ensure the statistical robustness of our findings. To quantify the uncertainty around the ROR estimates, we calculated the SE of the ROR using the formula for the SE of a ratio, which accounts for the variability in both the numerator and the denominator. The CIs for the ROR were then derived using the SE, applying the normal distribution to construct a 95% confidence interval. These calculations allowed us to assess the precision of the ROR estimates and determine whether observed differences were statistically significant, providing a comprehensive understanding of the disparities or trends being analyzed.\u003c/p\u003e\n\u003ch3\u003eDATA ABSTRACTION\u003c/h3\u003e\n\u003cp\u003eEach age group was further stratified by sex, race/ethnicity, urbanization, and location of death, including medical facilities (outpatient, emergency room, inpatient, death on arrival, or status unknown), home, hospice, and nursing home/long-term care facility. Race/ethnicity was classified as Non-Hispanic (NH) White, NH Black or African American, Hispanic or Latino, NH American Indian or Alaskan Native, and NH Asian or Pacific Islander. This information relies on reported data on death certificates and has been validated in previous analyses of the WONDER database.8 The National Center for Health Statistics Urban-Rural Classification Scheme was used to assess the population by urban (large metropolitan areas with populations\u0026thinsp;\u0026ge;\u0026thinsp;1\u0026nbsp;million, medium/small metropolitan areas with populations between 50,000-999,999) and rural (populations\u0026thinsp;\u0026lt;\u0026thinsp;50,000) counties, according to the 2013 U.S. Census classification. Regions were categorized into Northeast, Midwest, South, and West, following the U.S. Census Bureau definitions. The ROR for each cohort was calculated, and trends were analyzed over the study period from 1999 to 2020.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eSTATISTICAL ANALYSIS:\u003c/h2\u003e\u003cp\u003eTo examine and quantify trends within the individual cohorts, ROR values with their standard errors from 1999 to 2020 were input into the Join Point Regression Program (Join Point V 5.2.0.0, National Cancer Institute), which calculated the average annual percent change (AAPC) with 95% confidence intervals (CIs). This method identifies significant changes in ROR over time by fitting log-linear regression models where temporal variation occurred. APCs and AAPCs were considered increasing or decreasing if the slope describing the change in mortality was significantly different from zero, as determined by 2-tailed t-tests. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eOVERALL\u003c/h2\u003e\u003cp\u003eThe overall burden of cardiovascular disease (CVD) in leukemia-related mortality [A/B] shows an upward trend across all Age Groups (AGs), peaking in the oldest group [15\u0026ndash;24: 0.23, 55\u0026ndash;64: 0.26, 85+: 0.43]. In a similar fashion, the CVD burden in all-cause deaths [C/D] also increased progressively across AGs, although it demonstrated a more pronounced rise [15\u0026ndash;24: 0.10, 55\u0026ndash;64: 0.50, 85+: 0.66]. As a result, the variation in increase caused the ROR in older AGs to be lower than expected, even though they had a higher burden of CVD in leukemia-related deaths [15\u0026ndash;24: 2.17 (2.072\u0026ndash;2.281), 55\u0026ndash;64: 0.53 (0.525\u0026ndash;0.542), 85+: 0.647 (0.641\u0026ndash;0.653)] \u003cb\u003e(Supplementary Table\u0026nbsp;1, Supplementary Fig.\u0026nbsp;1\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Middle-aged AGs have the lowest value forming a distinctive reverse J-shaped curve. Trend Analyses from 1999\u0026ndash;2020 displayed a rise in AAPCs across all age groups with the highest increase in ROR in the 55\u0026ndash;64 AG and 75\u0026ndash;84 AG [55\u0026ndash;64): 1.18 AAPC, 95% CI: 0.96\u0026ndash;1.38, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)] \u003cb\u003e(Supplementary Table\u0026nbsp;2)\u003c/b\u003e. This trend can be attributed to the rising AAPC of CVD burden in leukemia mortality coupled with the declining AAPC of CVD burden in all-cause deaths [A/B (75\u0026ndash;84): 0.57, 95% CI: 0.41 to 0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; C/D (75\u0026ndash;84): -0.53, 95% CI: -0.56 to -0.50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01] \u003cb\u003e(Supplementary Table\u0026nbsp;2)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSEX\u003c/h3\u003e\n\u003cp\u003eSex-based analysis indicated that males consistently exhibited a higher ROR across the majority of age groups throughout the study period \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The highest recorded ROR was found in the male demographic [Male (15\u0026ndash;24): 2.505 (2.358\u0026ndash;2.662); Female (15\u0026ndash;24): 1.586 (1.467\u0026ndash;1.715)]. The lowest ROR was observed in the female group within the older age categories [65\u0026ndash;74: 0.531 (0.521\u0026ndash;0.542)], while the ROR for the male group was similar [65\u0026ndash;74: 0.557 (0.55\u0026ndash;0.565)] \u003cb\u003e(Supplementary Table\u0026nbsp;3, Supplementary Fig.\u0026nbsp;2)\u003c/b\u003e. The increase in ROR towards middle age groups was more pronounced for females [Female (45\u0026ndash;54): 0.54 (0.522\u0026ndash;0.558); Male (45\u0026ndash;54): 0.563 (0.541\u0026ndash;0.585)]. Trend analysis revealed that all age groups exhibited a positive AAPC, with the most significant increase recorded in young males [Male (35\u0026ndash;44): 1.59 (0.59\u0026ndash;2.43), p\u0026thinsp;=\u0026thinsp;0.002; Female (55\u0026ndash;64): 1.51* (0.95\u0026ndash;1.86), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01] \u003cb\u003e(Supplementary Table\u0026nbsp;2).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eREGION\u003c/h3\u003e\n\u003cp\u003eIn regional stratification, the Northeast and West census regions had a greater ROR than the other regions in all AGs, with the disparity becoming less pronounced in older AGs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Overall, ROR was greater in younger age groups, with the highest observed in the Western region [West (15\u0026ndash;24): 2.565 (2.355\u0026ndash;2.794); Northeast (15\u0026ndash;24): 2.093 (1.97\u0026ndash;2.223); South (15\u0026ndash;24): 2.006 (1.851\u0026ndash;2.174); Midwest (15\u0026ndash;24): 1.681 (1.482\u0026ndash;1.907)]. The Midwest region had the lowest ROR [45\u0026ndash;54: 0.437 (0.412\u0026ndash;0.463). \u003cb\u003e(Supplementary Table\u0026nbsp;4 and Supplementary Fig.\u0026nbsp;3)\u003c/b\u003e. Trend based analyses revealed the steepest positive AAPC was recorded in the South [South (45\u0026ndash;54): 1.84*, 95%CI: 1.15\u0026ndash;2.75, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Midwest (45\u0026ndash;54): 1.78*, 05% CI: 1-2.76, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; West (55\u0026ndash;64): 1.38*, 95% CI: 1.02\u0026ndash;1.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Northeast (75\u0026ndash;84): 0.65*, 95% CI: 0.18\u0026ndash;0.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01]. Furthermore, contrary to other regions Northeast displayed negative trend in AGs spanning 15 to 54 [(15\u0026ndash;24): -1.11*, 95% CI: -2.2 to -0.22, p\u0026thinsp;=\u0026thinsp;0.02; (45\u0026ndash;54): -0.87, 95% CI: -1.67 to -0.21, p\u0026thinsp;=\u0026thinsp;0.015] \u003cb\u003e(Supplementary Table\u0026nbsp;2)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRACE\u003c/h2\u003e\u003cp\u003eIn racial stratification, Hispanics consistently exhibited a higher ROR compared to other racial groups across younger and middle age groups. While the disparity was less pronounced in older age ranges NH American Indians had a slightly higher ROR \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Age groups with lower averages showed a greater overall ROR, with the peak observed among Hispanics [Hispanics (15\u0026ndash;24): 2.637 (2.419\u0026ndash;2.874); Non-Hispanic (NH) Asians (15\u0026ndash;24): 2.196 (1.782\u0026ndash;2.706); NH Blacks (15\u0026ndash;24): 2.195 (1.947\u0026ndash;2.476); NH American Indians (15\u0026ndash;24): 1.975 (1.163\u0026ndash;3.354); NH Whites (15\u0026ndash;24): 1.972 (1.838\u0026ndash;2.116)] \u003cb\u003e(Supplementary Table\u0026nbsp;5 and Supplementary Fig.\u0026nbsp;4)\u003c/b\u003e. The middle age groups recorded the lowest RORs, especially among NH American Indians [45\u0026ndash;54: 0.48 (0.337\u0026ndash;0.683)]. Trend based analyses revealed negative AAPCs dominantly in the younger AGs for Hispanics (35\u0026ndash;44: -1.21 95% CI: -2.56-0.09, p\u0026thinsp;=\u0026thinsp;0.06) and NH Black (35\u0026ndash;44: -0.63, -0.74 (-1.87-0.28), p\u0026thinsp;=\u0026thinsp;0.14) (\u003cb\u003eSupplemental Table\u0026nbsp;2)\u003c/b\u003e. Additionally, most AGs categorized by race exhibited a positive AAPC, with the most significant increase observed in NH White individuals [NH White (55\u0026ndash;64): 1.43*, 95% CI: 1.09\u0026ndash;1.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; NH Black (55\u0026ndash;64): 0.97* (0.43\u0026ndash;1.67), p\u0026thinsp;=\u0026thinsp;0.016; Hispanics (75\u0026ndash;84): 0.92* (0.46\u0026ndash;1.36), p\u0026thinsp;=\u0026thinsp;0.02; NH Asian or Pacific Islander (65\u0026ndash;74): 0.84*, 95% CI: 0.02\u0026ndash;2.09, p\u0026thinsp;=\u0026thinsp;0.04 \u003cb\u003e(Supplementary Table\u0026nbsp;2)\u003c/b\u003e. Owing to suppressed data, trends for NH American Indians could not analyzed.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eURBANISATION\u003c/h2\u003e\u003cp\u003eIn urban stratification, both Metropolitan and Nonmetropolitan cohorts exhibited comparable RORs across all age categories, particularly among the middle-aged and elder age groups \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The overall ROR was greater in younger demographics, peaking in Metropolitan regions [Metro (15\u0026ndash;24): 2.223 (2.112\u0026ndash;2.34); Non-Metro (15\u0026ndash;24): 1.88 (1.642\u0026ndash;2.152)]. The lowest ROR was observed in Nonmetropolitan regions [Non-Metro (45\u0026ndash;54): 0.489 (0.459\u0026ndash;0.522); Metro (45\u0026ndash;54): 0.557 (0.542\u0026ndash;0.572)]. \u003cb\u003e(Supplementary Table\u0026nbsp;3, Supplementary Fig.\u0026nbsp;5)\u003c/b\u003e Throughout the study period, there was an upward trend in ROR for all age groups. The steepest AAPC was noted in Non-Metropolitan areas [Non-metro (55\u0026ndash;64): 2.02*, 95% CI: 1.35\u0026ndash;2.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Metro (55\u0026ndash;64): 1.21* (0.9\u0026ndash;1.45), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01] \u003cb\u003e(Supplementary Table\u0026nbsp;2).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003ePLACE OF DEATH\u003c/h2\u003e\u003cp\u003eMedical facilities had a higher ROR compared to other locations consistently in all AGs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The highest ROR for each location was generally seen in younger AGs (Medical Facility (15\u0026ndash;24): 1.473; Decadents Home (15\u0026ndash;24): 1.199; Hospice (15\u0026ndash;24): 0.854; Nursing Home (85+): 0.715). Other/Unknown locations had a notable ROR in the younger AGs (15\u0026ndash;24: 4.810), alluding to possible limitations \u003cb\u003e(Supplementary Table\u0026nbsp;6)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eStratification of the combined Reporting Odds Ratio (ROR) by age groups of 10 years or more indicates that the 15-24y age group possesses the highest ROR, then the 25-34y and 35-44y age groups. The ROR levels off within the 45-84y age group, followed by rising in the 85y\u0026thinsp;+\u0026thinsp;age group to create a reverse bell-shaped curve. An ROR\u0026thinsp;\u0026gt;\u0026thinsp;1 among the younger groups suggests that a major contribution of cardiovascular disease (CVD) in Leukemia death is due to co-pathway CVD risk fueled by concurrent Leukemia with CVD risk being perpetuated by Leukemia and its treatment. The highest CV mortality risk in patients with Leukemia was reported in \u0026lt;\u0026thinsp;50 years old patients within \u0026lt;\u0026thinsp;2 years following diagnosis in one retrospective cohort study ​\u003csup\u003e7\u003c/sup\u003e​. Our work also demonstrates a rising trend in ROR in all age groups from 1999\u0026ndash;2020, highlighting the necessity for focused cardio-oncological interventions in patients aged 15\u0026ndash;34 years. In older age groups with an ROR of less than 1, deaths due to CVD and Leukemia most likely rise individually, lowering the combined odds ratio. A reverse J-shaped rise in the oldest age groups indicates vulnerability towards developing both simultaneously. Due to limitations in available data, a competing risk model could not be performed.\u003c/p\u003e\u003cp\u003eStratification by gender indicates that males have a greater ROR than females in the 15-24y and 25-34y groups, while other groups have similar values. Previous studies identified increased cardiac-specific mortality in older male AML patients undergoing chemotherapy, while our research emphasizes the higher CVD burden in younger male Leukemia mortality ​\u003csup\u003e7\u003c/sup\u003e​. The ROR among males has been rising in all age groups over time, while among females, the ROR has fallen in the 15-24y and 35-44y groups, remained unchanged in the 25-34y group, and risen in older age groups, especially in the oldest cohort.\u003c/p\u003e\u003cp\u003eStratification by race demonstrates that among younger groups, Hispanics have the highest ROR, followed by Asians, and differences become less pronounced after 35 years of age. Higher CVD mortality among Hispanics and Asians was noted in a retrospective study, and our results validate the same, noting racial disparities in younger populations. Racial trends over time (1999\u0026ndash;2020) exhibit varied patterns. In the Hispanic group, ROR decreased between 2006\u0026ndash;2010, rose between 2010\u0026ndash;2016, and fell again between 2016\u0026ndash;2020 in the youngest category. The 35-44y category presented a decrease, while older ones presented an increase. In Whites, ROR has increased in all age categories, with an increased rise among older groups. The older Black population also increases ​\u003csup\u003e8\u0026ndash;12\u003c/sup\u003e​. The Asian population shows a general rise except for a fall in the oldest age group. Due to healthcare access inequalities experienced by Hispanic/Latin populations, specific cardio-oncological interventions are required.\u003c/p\u003e\u003cp\u003eRegional stratification shows that the Northeast and Western regions have a greater ROR than the Midwest and Southern regions in all age groups, with the disparity more evident in younger age groups. In spite of greater overall CVD mortality in the South and Midwest, the greater ROR in the Northeast and West indicates that Leukemia and its treatment could be a greater contributor to CVD-related mortality in these areas. ROR has risen over time (1999\u0026ndash;2020) in the Midwest and South in all age groups. The Western region has a decrease in the youngest group but an increase in others ​\u003csup\u003e7\u003c/sup\u003e. The Northeast indicates a reduction in the youngest and 45-54y age groups but an increase in all the rest. Based on these patterns, the building of cardio-oncology clinics across the country is necessary, with priority in the Northeast and West.\u003c/p\u003e\u003cp\u003eStratification according to urban-rural residence shows an increased ROR in urban cities, especially in younger patients. In the long term (1999\u0026ndash;2020), ROR has also gone up in metropolitan and non-metropolitan areas ​\u003csup\u003e13\u003c/sup\u003e​. Increasing cardio-oncology clinics in urban areas will help manage the growing CVD burden among Leukemia patients.\u003c/p\u003e\u003cp\u003eLastly, stratification by place of death reveals that among the youngest cohort, nursing homes and LTAC centers have the highest ROR, perhaps indicating chemotherapy-induced cardiotoxicity. Previous research has previously established a high frequency of cardiac complications in patients with AML treated with chemotherapy ​\u003csup\u003e14\u003c/sup\u003e​. Cardiotoxicity could play a significant role in the CVD burden in Leukemia patients, and further studies on the cardiovascular profiles of emerging and conventional chemotherapeutic agents are warranted.\u003c/p\u003e\u003cp\u003eOur results indicate the importance of targeted cardio-oncological interventions, especially in younger men, Hispanics, urban areas, and the Northeast and Western states, to counteract the cardiovascular impact in Leukemia mortality.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eLIMITATIONS\u003c/h2\u003e\u003cp\u003eThe retrospective methodology of this study precludes the establishment of causal linkages and limits competing risk analysis, limiting understanding of how CVD and leukemia interact in mortality. Reliance on broad cause-of-death data may result in misdiagnosis, particularly when both illnesses contribute to mortality. Individual-level characteristics such as treatment regimens, illness stage, comorbidities, and cardiotoxicity were not included, which influenced ROR interpretation.\u003c/p\u003e\u003cp\u003eKey variables such as socioeconomic status, healthcare access, and lifestyle behaviors were not available, which influenced discrepancies. ROR variations by region and urban/rural area can be a result of unrecorded healthcare infrastructure and access to specialized care. The study time frame (1999\u0026ndash;2020) may not fully capture the influence of newer leukemia treatments that carry different cardiovascular risks. CDC WONDER database does not report deaths\u0026thinsp;\u0026lt;\u0026thinsp;10 leading to multiple cohorts having suppressed data. Lastly, variations in treatment protocols and healthcare practices over time and across regions may have influenced the observed trends.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis analysis of the CDC WONDER database (1999\u0026ndash;2020) reveals significant demographic and geographical variations in the relative occurrence ratios (ROR) of leukemia among people with CVD. The highest ROR is typically found in younger populations (15\u0026ndash;24 years old), whereas older age groups (55\u0026ndash;64 and 75\u0026thinsp;+\u0026thinsp;years old) have been showing an increased trend since 2018. Males, particularly those in the younger and older populations, exhibit greater RORs than females. The highest total ROR is found among Hispanic populations, particularly in younger age groups. Regionally, the Western United States has the highest ROR in younger people, whereas the Midwest has lower RORs in middle-aged groups. Urbanization patterns show slightly higher RORs in urban regions, with an increase among elderly populations. These findings highlight the importance of further research and targeted public health measures to address inequities in leukemia and CVD mortality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eAll data used in this study are publicly available through the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database. The authors obtained access in accordance with the CDC\u0026rsquo;s data use guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement:\u0026nbsp;\u003c/strong\u003eThis research did not receive any grants from funding agencies in the public, commercial or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;All authors have reviewed and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval Statement:\u0026nbsp;\u003c/strong\u003eThis study used de-identified, publicly available mortality data from the CDC WONDER database. As no human subjects or identifiable data were involved, institutional review board approval was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;Informed consent was waived because the study used de-identified, publicly available data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermission to Reproduce Material from Other Sources:\u0026nbsp;\u003c/strong\u003eNot applicable. No third-party material was reproduced.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Registration:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad FB, Cisewski JA, Anderson RN. 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Social Determinants of Risk and Outcomes for Cardiovascular Disease. \u003cem\u003eCirculation\u003c/em\u003e. 2015;132(9):873-898. doi:10.1161/CIR.0000000000000228 \u003c/li\u003e\n\u003cli\u003eRodriguez F, Hastings KG, Boothroyd DB, et al. Disaggregation of Cause-Specific Cardiovascular Disease Mortality Among Hispanic Subgroups. \u003cem\u003eJAMA Cardiol\u003c/em\u003e. 2017;2(3):240-247. doi:10.1001/JAMACARDIO.2016.4653 \u003c/li\u003e\n\u003cli\u003eSingh GK, Jemal A. Socioeconomic and Racial/Ethnic Disparities in Cancer Mortality, Incidence, and Survival in the United States, 1950-2014: Over Six Decades of Changing Patterns and Widening Inequalities. \u003cem\u003eJ Environ Public Health\u003c/em\u003e. 2017;2017. doi:10.1155/2017/2819372 \u003c/li\u003e\n\u003cli\u003eLi G, Zhou Z, Yang W, et al. Long-term cardiac-specific mortality among 44,292 acute myeloid leukemia patients treated with chemotherapy: a population-based analysis. \u003cem\u003eJ Cancer\u003c/em\u003e. 2019;10(24):6161-6169. doi:10.7150/JCA.36948 \u003c/li\u003e\n\u003cli\u003eBoluda B, Solana-Altabella A, Cano I, et al. Incidence and Risk Factors for Development of Cardiac Toxicity in Adult Patients with Newly Diagnosed Acute Myeloid Leukemia. \u003cem\u003eCancers (Basel)\u003c/em\u003e. 2023;15(8):2267. doi:10.3390/CANCERS15082267/S1 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cardiovascular, Oncology, Leukemia, Mortality, Odds Ratio, Burden","lastPublishedDoi":"10.21203/rs.3.rs-7777208/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7777208/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBACKGROUND\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe presence of cardiovascular disease (CVD) in patients with leukemia leads to worse clinical outcomes, but the disparities in this issue are still not fully examined. This research investigates differences in the CVD burden related to leukemia deaths across various demographic and geographic contexts using CDC WONDER data from 1999 to 2020.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMETHODOLOGY\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eA disproportionality analysis was conducted to calculate reporting odds ratio (ROR) of CVD burden in leukemia patients compared to all-cause deaths across age groups 15–85 years. A ROR greater than 1 indicated a higher burden of CVD in cancer patients. Average Annual Percentage Changes (AAPCs) were calculated to evaluate trends, with p-values determining significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe highest ROR was found in the 15–24 age cohort (2.565), decreasing with age but rising slightly in older adults (85+: 0.56). The 55–64 age group experienced the most significant annual increase (AAPC: 2.02). Males consistently showed higher RORs compared to females, however, the most notable rise was in middle-aged females (AAPC: 1.51). Among racial groups, young Hispanics had the highest ROR (2.637), whereas NH Whites (55–64 AG) experienced the largest AAPC (1.43). Midwest had the lowest ROR but also exhibited the steepest regional increase (45–54: 1.78). Urban regions reported higher RORs than rural areas, with medical facilities displaying the highest RORs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSION\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThese results highlight the importance of developing focused cardiovascular care strategies, especially for high-risk groups such as younger individuals, males, Hispanics, and those residing in urban areas. Public health initiatives should target these disparities to enhance outcomes for patients with leukemia.\u003c/p\u003e","manuscriptTitle":"Trends and Disparities in Cardiovascular Disease Burden Among Leukemia Related Deaths in the United States (1999–2020): A CDC WONDER Disproportionality Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 16:57:34","doi":"10.21203/rs.3.rs-7777208/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b79bcf6-4a24-441d-b71f-f3fdc7672d2b","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T12:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 16:57:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7777208","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7777208","identity":"rs-7777208","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}