Divergent Mortality Trends in Hematologic Malignancies and Diffuse Non–Hodgkin Lymphoma Across the United States: A CDC WONDER Database Analysis from 1999 to 2023

Divergent Mortality Trends in Hematologic Malignancies and Diffuse Non–Hodgkin Lymphoma Across the United States: A CDC WONDER Database Analysis from 1999 to 2023 | 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 Divergent Mortality Trends in Hematologic Malignancies and Diffuse Non–Hodgkin Lymphoma Across the United States: A CDC WONDER Database Analysis from 1999 to 2023 Junping Li, Shiyu Xiong, Feng Xiong, Feng Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8312078/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: While overall hematologic and lymphoid malignancy (HLM) mortality has declined in the US, significant disparities persist across subtypes and demographic groups. This study characterizes 24-year trends in HLM and diffuse non-Hodgkin lymphoma (DNHL) mortality, quantifying inequities through advanced segmentation modeling. Methods: Using CDC WONDER mortality data (1999–2023), we performed Joinpoint regression analyses to calculate annual percent changes (APC) and average annual percent changes (AAPC) in age-adjusted mortality rates (AAMR). Stratification by sex, race/ethnicity, age, region, and urbanicity identified high-risk populations. Results • Divergent national trends: HLM mortality decreased (AAPC = -1.74%; 95% CI: -1.80 to -1.68) despite +1.74% absolute death increase. DNHL mortality surged (AAPC = +2.64%; 95% CI: 1.19 to 4.11) with +177.59% death rise. • Critical disparities: Age: Young adults (25–34y) showed HLM mortality reversal post-2020 (APC +1.17%, P ≥0.05) vs steep DNHL rise in ≥85y (AAPC= +4.41%；95% CI:1.75 to 7.14). Race: Hispanic and NH-Other populations experienced 107–128% HLM death increases alongside 3.41–3.90% DNHL AAPC rises. Geography: DNHL mortality doubled in Western states (e.g., California: 2008–2011 APC = +15.37%; 95% CI: -2.12 to 35.99) while HLM declines lagged in Southern regions. l Novel inflection points: Nationwide DNHL mortality shifted from decline (1999–2008 APC = -3.83%; 95% CI: -4.92 to -2.73) to sharp increase (2008–2011 APC = +16.79%; 95% CI: 3.97 to 31.18). Urban areas demonstrated accelerated HLM declines post-2012 (APC = -2.14%; 95% CI: -2.34 to -1.94). Conclusion: Substantial gains in HLM mortality mask worsening disparities, particularly among racial minorities and older adults. The alarming rise in DNHL mortality—characterized by distinct inflection points and geographic hotspots—signals an urgent need for targeted interventions. Hematologic Malignancies Diffuse Non-Hodgkin Lymphoma Mortality trends Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Hematologic and lymphoid malignancies (HLM) constitute a substantial burden of cancer-related morbidity and mortality in the United States 1 , 2 . While therapeutic advances have yielded improved outcomes for many patients 3 , recent epidemiological patterns reveal divergent trajectories across specific malignancy subtypes and demographic subgroups 4 . In particular, diffuse non-Hodgkin lymphoma (DNHL), an aggressive lymphoid cancer subtypes, displays distinct epidemiological characteristics meriting deeper scrutiny 5 – 7 . The CDC WONDER mortality database provides a comprehensive national platform for examining long-term cancer mortality trends across diverse demographic and geographic strata. Although previous studies have documented overall declines in mortality for multiple myeloma, acute myeloid leukemia, and non-Hodgkin lymphoma mortality 8 – 10 , few have specifically contrasted trends between HLM collectively and DNHL specifically. Moreover, comprehensive assessments of disparities by sex, race, ethnicity, age, region, and urbanicity over an extended period remain limited. This investigation leverages Joinpoint regression analysis 11 , 12 , to delineate mortality trends for HLM and DNHL from 1999 to 2023, identifying significant temporal shifts and quantifying average annual percent changes (AAPC) in age-adjusted mortality rates (AAMR). Analyses are stratified by key demographic and geographic variables to uncover disparities and pinpoint high-risk populations. We assess whether improvements in HLM outcomes are equitably distributed and probe the marked rise in DNHL mortality, particularly evident among racial and ethnic minorities, older adults, and specific geographic regions. These insights are critical for informing public health planning, resource allocation, and targeted interventions aimed at reducing disparities and mitigating the escalating burden of specific Hematologic and Lymphoid Malignancies in vulnerable populations. Methods Data Source and Study Population Mortality data spanning 1999–2023 were sourced from the Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database 13 . CDC WONDER compiles national mortality data derived from death certificates filed across all 50 U.S. states and the District of Columbia. The study encompassed all deaths where hematologic and lymphoid malignancies (HLM) and diffuse non-Hodgkin lymphoma (DNHL) were designated as the underlying cause of death, based on the International Classification of Diseases, Tenth Revision (ICD-10) codes C81–C96 for HLM and C83.9 for DNHL. Variables and Stratification AAMR per 100,000 standard population was computed using the direct method with the 2000 U.S. standard population. Stratification was performed by sex (male and female), race and ethnicity (Non-Hispanic White, Non-Hispanic Black, Hispanic, and Non-Hispanic Other), age group (25–34, 35–44, 45–54, 55–64, 65–74, 75–84, and 85 + years), census region (Northeast, Midwest, South, and West), and urbanization level (metropolitan and nonmetropolitan areas as defined by the National Center for Health Statistics). This classification was derived from information available in the CDC Wonder database 14 . Statistical Analysis Joinpoint regression analysis was conducted using the National Cancer Institute’s Joinpoint Regression Program (Version 5.0.2) to pinpoint significant temporal shifts in mortality trends 15 . Beginning with zero Joinpoints, the Monte Carlo permutation test determined the optimal number of significant change points. Annual percent change (APC) for each identified segment and average annual percent change (AAPC) for the entire period (1999–2023) were calculated 16 , along with their 95% confidence intervals (CI). Statistical significance was defined as p < 0.05. Trends were classified as increasing or decreasing if the APC/AAPC was significantly from zero. Poisson regression models accounted for potential overdispersion in the mortality data. Ethical Considerations Utilizing publicly accessible, de-identified aggregate data from CDC WONDER, this study was exempt from institutional review board approval. Results Divergent National Trends in HLM and DNHL Mortality, United States 1999–2023 Between 1999 and 2023, U.S. mortality trends for HLM and DNHL diverged sharply. While HLM deaths saw a modest increase from 55,080 to 56,039 (+ 1.74%), the AAMR declined significantly from 31.09 to 20.29 per 100,000 (AAPC = -1.74%; 95% CI: -1.80 to -1.68) (Table 1). In stark contrast, DNHL deaths escalated dramatically from 2,628 to 7,295 (+ 177.59%), accompanied by a rising AAMR from 1.48 to 2.62 (AAPC = 2.64%; 95% CI: 1.19 to 4.11) (Table 2). Synthesizing data from Tables 1 & 2 reveals notable disparities: Sex : HLM mortality decreased more markedly among females (AAPC = -1.99%) than males (-1.65%). Conversely, DNHL mortality increased more rapidly in males (AAPC = 2.56%) compared to females (2.44%). Region : HLM mortality declined in the Northeast (AAPC = -2.06%) and Midwest (-1.70%) but increased in the South and West. DNHL mortality rose across all regions, most precipitously in the West (+ 223.33% deaths) and Northeast (AAPC = 3.01%). Race/Ethnicity : HLM deaths increased among Hispanic (+ 107.61%) and Non-Hispanic (NH) Other (+ 128.37%) populations. Mirroring this, DNHL mortality surged most rapidly in these same groups (AAPC = 3.90% and 3.41%, respectively). Age : The largest declines in HLM mortality occurred in younger age groups (e.g., 45–54 years: AAPC = -3.11%), while DNHL increases were most pronounced in the oldest group (≥ 85 years: AAPC = 4.41%). Urbanicity : Metropolitan areas witnessed significant increases in DNHL mortality (AAPC = 2.56%), a trend not observed in nonmetropolitan areas. Sex-Specific Patterns in HLM Mortality and DNHL mortality, United States 1999–2023 Joinpoint regression analyses delineated sex-specific differences (1999–2023). HLM Mortality (Fig. 1 A): Mortality declined significantly for both sexes, with a steeper reduction among females (APC = -1.99%; 95% CI: -2.07 to -1.91) than males (APC = -1.65%; 95% CI: -1.72 to -1.59). DNHL mortality (Fig. 1 B): The overall population exhibited an initial decline (1999–2008: APC = -3.83%; 95% CI: -4.92 to -2.73), followed by a sharp increase (2008–2011: APC = + 16.79%; 95% CI: 3.97 to 31.18), and a sustained rise (2011–2023: APC = 4.35%; 95% CI: 3.83 to 4.88). Females experienced a more pronounced initial decline (1999–2008: APC = -5.22%; 95% CI: -6.57 to -3.85) followed by significant increases (2008–2011: APC = 17.39%; 95% CI: 0.60 to 36.97; 2011–2023: APC = 4.96%; 95% CI: 4.28 to 5.65). Males demonstrated greater complexity: an initial decline (1999–2008: APC = -3.22%; 95% CI: -3.81 to -2.63), a sharp increase (2008–2011: APC = 17.35%; 95% CI: 10.56 to 24.55), and subsequent phased increases culminating in a significant rise from 2017–2023 (APC = 2.42%; 95% CI: 1.74 to 3.10). Regional Variation in HLM Mortality and DNHL mortality, United States 1999–2023 Joinpoint regression analyses revealed distinct regional patterns for HLM mortality and DNHL mortality across U.S. census regions (1999–2023). HLM mortality (Fig. 2 A): Mortality declined significantly in all regions. The Northeast exhibited a biphasic pattern: an initial decrease (1999–2017: APC = -1.74%; 95% CI: -1.85 to -1.62) followed by a steeper decline (2017–2023: APC = -3.03%; 95% CI: -3.65 to -2.40). The Midwest, South, and West showed consistent monotonic declines with APCs of -1.70% (95% CI: -1.77 to -1.62), -1.64% (95% CI: -1.71 to -1.57), and − 1.73% (95% CI: -1.82 to -1.65), respectively. DNHL mortality (Fig. 2 B): Mortality increased substantially nationwide, but with region-specific multiphase patterns. The Northeast, Midwest, and West shared a trajectory: initial decline (1999–2008), sharp upturn (2008–2011: APCs 16.43–21.35%), and sustained increase (2011–2023: APCs 3.65–4.53%). The South differed slightly, showing a significant decrease (1999–2006: APC = -5.20%;95% CI: -8.21 to -2.09) followed by a pronounced continuous rise (2006–2023: APC = 5.67%; 95% CI: 4.99 to 6.36). Racial and Ethnic Disparities in HLM Mortality and DNHL mortality, United States 1999–2023 Joinpoint regression analyses highlighted divergent trends across racial and ethnic groups (1999–2023). HLM Mortality (Fig. 3 A): Consistent declines were observed across all groups: Non-Hispanic White (APC = -1.66%; 95% CI: -1.72 to -1.60), Hispanic (APC = -1.44%; 95% CI: -1.59 to -1.28), Non-Hispanic Black (APC = -1.54%; 95% CI: -1.65 to -1.44). Non-Hispanic Other exhibited a biphasic decline with acceleration after 2018 (APC = -3.19%; 95% CI: -4.62 to -1.74). DNHL mortality (Fig. 3 B): Complex multiphase increases characterized all populations. Non-Hispanic White transitioned from initial decline (1999–2008: APC = -3.71%; 95% CI: -4.83 to -2.57) to sharp increase (2008–2011: APC = 16.29%; 95% CI: 2.92 to 31.40) and sustained rise (2011–2023: APC = 4.45%; 95% CI: 3.89 to 5.01). Similar patterns emerged among Non-Hispanic Black, Hispanic, and Other racial groups, each showing significant upward trends in recent periods (2010–2023 APCs ranging 4.38%–5.33%). Age-Specific Divergence in HLM Mortality and DNHL mortality, 1999–2023 Joinpoint regression analyses from 1999 to 2023 uncovered contrasting age-specific patterns for HLM mortality and DNHL mortality. HLM mortality (Fig. 4 A): Significant declines characterized most age cohorts, with the steepest reductions in middle-aged groups: ages 55–64 experienced an APC of -4.27% (1999–2004), followed by -2.69% until 2023; ages 35–44 showed a persistent decline (APC = -2.88%). However, a concerning reversal emerged among young adults (25–34 years), shifting from a significant decrease (APC = -4.27%, 2009–2020) to a non-significant increase (APC = 1.17%) post-2020. DNHL mortality (Fig. 4 B): Mortality rose substantially, particularly among older populations: ages 75–84 increased sharply (APC = 11.81%, 2007–2012), then stabilized at 4.76% until 2023; ages ≥ 85 + exhibited significant increases from 2010 onwards (APC = 7.09%). Middle-aged groups also transitioned to rising mortality; for example, ages 45–54 shifted from decline (APC = -6.40%, 1999–2005) to sustained increase (APC = 3.64%, 2005–2023). Notably, young adults (25–34 years) demonstrated a steady rise in DNHL mortality (APC = 1.29%) throughout the period, temporally coinciding with the recent HLM mortality reversal in this same age group. Urban–Rural Disparities in HLM Mortality and DNHL mortality, United States 1999–2020 Joinpoint regression analyses (1999–2020) revealed contrasting trends by urbanization level. HLM Mortality (Fig. 5 A): Mortality declined across all areas but with distinct patterns. Metropolitan areas showed a triphasic trend with accelerated decline from 2012 to 2020 (APC = -2.14%; 95% CI: -2.34 to -1.94). Nonmetropolitan areas demonstrated a consistent monotonic decrease (APC = -1.56%; 95% CI: -1.65 to -1.48). DNHL mortality (Fig. 5 B): Both settings displayed similar triphasic patterns: initial decline (metropolitan: APC = -3.78%, 95% CI: -5.14 to -2.40; nonmetropolitan: APC = -3.72%, 95% CI: -5.27 to -2.16), sharp increase around 2008–2011 (metropolitan: APC = 16.54%, 95% CI: 0.9134.59; nonmetropolitan: APC = 15.10%, 95% CI: -2.82 to 36.32), and sustained significant rise from 2011 to 2020 (metropolitan: APC = 4.75%, 95% CI: 3.71 to 5.79; nonmetropolitan: APC = 4.50%, 95% CI: 3.26 to 5.76). Metropolitan areas experienced marginally more pronounced increases in the most recent period. Geographic Disparities in HLM and DNHL Mortality, United States 1999–2020 Significant interstate variations in age-adjusted mortality rates (AAMR) were observed for both hematologic malignancies (HLM) and diffuse non-Hodgkin lymphoma (DNHL) (Tables S1&S2). The Average Annual Percent Change (AAPC) for HLM ranged from − 1.05% (95% CI: -1.32 to -0.78) in Oklahoma to -2.56% (95% CI: -3.20 to -1.92) in New Jersey. For DNHL, AAPC varied from − 0.25% (95% CI: -2.98 to 2.43) in Iowa to -4.44% (95% CI: -2.44 to 6.48) in Kentucky. Spatial analysis indicated consistent mortality burdens across tumor types (Fig. 6 A, B). Among HLM-related mortalities, California, Florida, and Texas recorded the highest death counts, with DNHL’s top-ranked states aligning with this pattern. For HLM, the most pronounced nationwide declines in AAMR occurred in New Jersey (-2.56% AAPC), New York, and District of Columbia. In New Jersey, the AAMR exhibited a notable late-phase acceleration (2020–2023 APC: -5.15%; 95% CI: -10.05 to -0.01) after a period of steady reduction (1999–2020 APC: -2.19%; 95% CI: -2.43 to -1.94) (Figure S1 ). However, DNHL showed upward AAMR trends, with Kentucky, Massachusetts, and California experiencing the steepest increases. Notably, California’s AAMR followed a triphasic pattern: a neutral early phase (1999–2008 APC: -0.28%; 95% CI: -2.11 to 1.59), a transient surge (2008–2011 APC: 15.37%; 95% CI: -2.12 to 35.99), a sustained rise (2011–2023 APC: 4.67%; 95% CI: 3.91 to 5.44) (Figure S2). Discussion This comprehensive analysis of U.S. HLM and DNHL mortality trends from 1999 to 2023 identifies persistent and emerging disparities across demographic, geographic, and urban–rural strata. Although overall HLM mortality has decreased–aligning with advancements in therapeutic and supportive care–our results highlight that these improvements have not been distributed equitably. In contrast, DNHL incidence and mortality have increased substantially, especially among historically marginalized populations and older adults, which signals an urgent public health concern. The observed decline in HLM mortality aligns with prior research documenting improved survival for leukemias, lymphomas, and multiple myeloma 8 – 10 , a trend plausibly linked to innovations like targeted therapies, immunotherapies, and hematopoietic stem cell transplantation 17 – 20 . Nonetheless, substantial heterogeneity in mortality reductions across racial, ethnic, and geographic lines indicates systemic inequities in accessing to these advancements 21 , 22 . For example, the more pronounced mortality declined among Non-Hispanic White individuals, relative to slower progress among Hispanic and Non-Hispanic Black populations, may stem from disparities in timely diagnosis, treatment quality, and healthcare access. Furthermore, the reversed mortality trend among young adults (25–34 years) warrants scrutiny, as it could signal emerging risk factors or delays in care within this age group. By stark contrast, the sharp increase in DNHL incidence and mortality represents a divergent and alarming trajectory. The multiphasic surge–an initial decline followed by a steep upward shift after 2008–201–might stem from changes in diagnostic practices, disease classification, or genuine increases in mortality due to environmental, immunological, or viral factors 23 – 26 . Notably, the exceptionally high increase among older adults (APC = 7.09% in ages ≥ 85+) emphasizes age-related vulnerability and potentially cumulative carcinogenic exposures 27 , 28 . Moreover, the significant rise among racial and ethnic minorities, including Hispanic and Non-Hispanic Other populations, underscores the influence of social determinants of health, such as socioeconomic status, environmental justice issues disparities, and differential access to preventive care. Geographic and urban–rural disparities further highlight the uneven burden of these malignancies. The slower decline in HLM mortality and faster rise in DNHL in the South and West may be influenced by regional differences in healthcare infrastructure, screening programs, and provider density. In contrast, more favorable trends in the Northeast and Midwest might reflect earlier adoption of advanced treatments and stricter public health policies. Similarly, the reduced improvements in nonmetropolitan areas (compared to metropolitan regions) emphasize the urgency of addressing rural health disparities, including limited access to specialty care and diagnostic delays. The identified sex-specific differences—steeper HLM mortality declines among females and sharper DNHL increases among males—may arise from biological, behavioral, or environmental factors that affect each sex differently 29 , 30 . Areas for further investigation include hormonal influences, occupational exposures, and health-seeking behaviors. Study Limitations Several limitations merit consideration. First, reliance on death certificate data may introduce misclassification bias in cause-of-death reporting. Second, the Joinpoint model’s assumption linearity between change points could oversimplifying intricate underlying patterns. Third, DNHL mortality analyses relied on mortality proxies rather than population-based registry data, which may limit interpretability. Finally, unmeasured confounders such as socioeconomic status, comorbidities, and treatment patterns were not incorporated into in this ecological analysis. Public Health Implications These findings advocate for targeted public health strategies to mitigate the growing DNHL burden and persistent inequities in HLM outcomes. Priorities should include enhancing early detection, expanding access to specialized care in underserved regions, and implementing culturally tailored prevention programs. Future research should investigate the biologic and social mechanisms driving these disparities, including the roles of genomics, environmental exposures, and health care policy. Conclusion While progress has been made in reducing HLM mortality at the national level, significant disparities remain across populations. The rapid rise in DNHL mortality and mortality demands concerted clinical and public health action to mitigate its impact, particularly among vulnerable subgroups. Abbreviations HLM Hematologic and Lymphoid Malignancy DNHL Diffuse Non-Hodgkin Lymphoma APC Annual Percent Changes AAPC Average Annual Percent Changes AAMR Age-Adjusted Mortality Rates NS Not Significant NH Non-Hispanic CDC WONDER Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research ICD-10 International Classification of Diseases, Tenth Revision CI Confidence Intervals Declarations Ethics approval and consent to participate All data used in this study were de-identified and publicly available. Consent for publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study are available in the CDC WONDER database, https:// wonder. cdc. gov. Competing interests The authors declare no competing interests. Funding Nanchang Science and Technology Bureau, General Project of Medical and Health Science and Technology Support (2022-KJZC-028). Authors’ contributions Jumping Li: Conceptualization, Methodology, Formal Analysis, Writing: original draft and editing. Shiyu Xiong: Writing: original draft, review and editing. Feng Xiong: Writing: original draft and editing. Feng Qiu: Validation, Conceptualization, Supervision, and editing. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the Centers for Disease Control and Prevention for providing the database. The authors would like to thank Dr. Anmin Liu (University of Salford) for his suggestions on manuscript revision. References Bray F, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229–63. Teras LR, et al. 2016 US lymphoid malignancy statistics by World Health Organization subtypes. CA Cancer J Clin. 2016;66:443–59. Thanarajasingam G, et al. 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Oncogenic Mutations and Tumor Microenvironment Alterations of Older Patients With Diffuse Large B-Cell Lymphoma. Front Immunol. 2022;13:842439. Iosselevitch I, Tabibian-Keissar H, Barshack I, Mehr R. Gastric DLBCL clonal evolution as function of patient age. Front Immunol. 2022;13:957170. Wu Y-T, et al. Sex differences in mortality: results from a population-based study of 12 longitudinal cohorts. Can Med Assoc J. 2021;193:E361–70. Zhao E, Crimmins EM. Mortality and morbidity in ageing men: Biology, Lifestyle and Environment. Rev Endocr Metab Disord. 2022;23:1285–304. Tables Tables 1 to 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8312078","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":570273028,"identity":"e1384960-bff9-4e38-9caf-95fa726f6f05","order_by":0,"name":"Junping Li","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Junping","middleName":"","lastName":"Li","suffix":""},{"id":570273029,"identity":"90fa2b8e-f5a8-4e28-bc71-b31b3cb472ab","order_by":1,"name":"Shiyu Xiong","email":"","orcid":"","institution":"Nanchang 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10:14:49","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":88361,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/8ccf44c9e5b5c300901ede4c.html"},{"id":99777682,"identity":"eaa667e1-aa36-4f69-b1c6-833da562b04b","added_by":"auto","created_at":"2026-01-08 10:14:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":239561,"visible":true,"origin":"","legend":"\u003cp\u003e(A) AAMR per 100,000 population in HLM; both and stratified by sex, 1999–2023. (B) AAMR per 100,000 population in DNHL; both and stratified by sex, 1999–2023. AAMR, Age-Adjusted Mortality Rate;*, P\u0026lt;0.05, isstatistically significant.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/6db6293bab95bcc85a43986d.png"},{"id":99777683,"identity":"2052772c-dbcf-4e27-b0a4-161e6c868762","added_by":"auto","created_at":"2026-01-08 10:14:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":345275,"visible":true,"origin":"","legend":"\u003cp\u003e(A) AAMR per 100,000 population in HLM; stratified by census region, 1999–2023. (B) AAMR per 100,000 population in DNHL; stratified by census region, 1999–2023. AAMR, Age-Adjusted Mortality Rate; *, P\u0026lt;0.05, is statistically significant.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/b0d26dd68dca1c117e599728.png"},{"id":99777685,"identity":"df117195-9987-4018-b11c-f0f39cce0d3d","added_by":"auto","created_at":"2026-01-08 10:14:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":322400,"visible":true,"origin":"","legend":"\u003cp\u003e(A) AAMR per 100,000 population in HLM; stratified by race, 1999–2023. (B) AAMR per 100,000 population in DNHL; stratified by race, 1999–2023. AAMR, Age-Adjusted Mortality Rate; NH, Non-Hispanic;*, P\u0026lt;0.05, isstatistically significant.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/0f19ec0f902ee9893aae8b64.png"},{"id":99798275,"identity":"357ddf6f-7f5a-44e9-9259-77841ffd7960","added_by":"auto","created_at":"2026-01-08 13:47:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":301577,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Crude mortality rate per 100,000 people in HLM; stratified by age groups, 1999–2023. (B) Crude mortality rate per 100,000 people in DNHL; stratified by age groups, 1999–2023. *, P\u0026lt;0.05, is statistically significant.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/2512d9f89ee071db989ab0a3.png"},{"id":99777691,"identity":"eb5049bf-5f66-4f8e-bf22-083ada8e3545","added_by":"auto","created_at":"2026-01-08 10:14:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":274999,"visible":true,"origin":"","legend":"\u003cp\u003e(A) AAMR per 100,000 population in HLM; stratified by metropolitan/nonmetropolitan, 1999–2020. (B) AAMR per 100,000 population in DNHL; stratified by metropolitan/nonmetropolitan, 1999–2020. AAMR, Age-Adjusted Mortality Rate; *, P\u0026lt;0.05, is statistically significant.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/f9677435d00a3ba5c8037d26.png"},{"id":99799234,"identity":"7a517041-a668-42cd-be5f-24a87d0ec177","added_by":"auto","created_at":"2026-01-08 13:49:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":419092,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Deaths and AAMR per 100,000 population in HLM; stratified by states, 1999–2023. (B) Deaths and AAMR per 100,000 population in DNHL; stratified by states, 1999–2023. AAMR, Age-Adjusted Mortality Rate; NA, is not statistically significant.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/2755ab9c5c6c74f4bca16a1c.png"},{"id":103602037,"identity":"40354da1-abdd-4f1e-bb69-a6d790742eee","added_by":"auto","created_at":"2026-02-27 14:11:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2575492,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/a12edeb2-2069-42e9-b758-66f4b5a98e31.pdf"},{"id":99798546,"identity":"70c1a568-8a81-482a-b6f0-48bfda5f84d4","added_by":"auto","created_at":"2026-01-08 13:48:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1319631,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/74d583d91922d4ef34c353b3.docx"},{"id":99798659,"identity":"c49a3cd2-1045-4366-a409-1e2de7c86339","added_by":"auto","created_at":"2026-01-08 13:48:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25048,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8312078/v1/3f454bd7653bee0f256876b1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Divergent Mortality Trends in Hematologic Malignancies and Diffuse Non–Hodgkin Lymphoma Across the United States: A CDC WONDER Database Analysis from 1999 to 2023","fulltext":[{"header":"Background","content":"\u003cp\u003eHematologic and lymphoid malignancies (HLM) constitute a substantial burden of cancer-related morbidity and mortality in the United States\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. While therapeutic advances have yielded improved outcomes for many patients\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, recent epidemiological patterns reveal divergent trajectories across specific malignancy subtypes and demographic subgroups\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In particular, diffuse non-Hodgkin lymphoma (DNHL), an aggressive lymphoid cancer subtypes, displays distinct epidemiological characteristics meriting deeper scrutiny\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe CDC WONDER mortality database provides a comprehensive national platform for examining long-term cancer mortality trends across diverse demographic and geographic strata. Although previous studies have documented overall declines in mortality for multiple myeloma, acute myeloid leukemia, and non-Hodgkin lymphoma mortality\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, few have specifically contrasted trends between HLM collectively and DNHL specifically. Moreover, comprehensive assessments of disparities by sex, race, ethnicity, age, region, and urbanicity over an extended period remain limited.\u003c/p\u003e \u003cp\u003eThis investigation leverages Joinpoint regression analysis\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, to delineate mortality trends for HLM and DNHL from 1999 to 2023, identifying significant temporal shifts and quantifying average annual percent changes (AAPC) in age-adjusted mortality rates (AAMR). Analyses are stratified by key demographic and geographic variables to uncover disparities and pinpoint high-risk populations. We assess whether improvements in HLM outcomes are equitably distributed and probe the marked rise in DNHL mortality, particularly evident among racial and ethnic minorities, older adults, and specific geographic regions. These insights are critical for informing public health planning, resource allocation, and targeted interventions aimed at reducing disparities and mitigating the escalating burden of specific Hematologic and Lymphoid Malignancies in vulnerable populations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Study Population\u003c/h2\u003e \u003cp\u003eMortality data spanning 1999\u0026ndash;2023 were sourced from the Centers for Disease Control and Prevention\u0026rsquo;s Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. CDC WONDER compiles national mortality data derived from death certificates filed across all 50 U.S. states and the District of Columbia. The study encompassed all deaths where hematologic and lymphoid malignancies (HLM) and diffuse non-Hodgkin lymphoma (DNHL) were designated as the underlying cause of death, based on the International Classification of Diseases, Tenth Revision (ICD-10) codes C81\u0026ndash;C96 for HLM and C83.9 for DNHL.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariables and Stratification\u003c/h3\u003e\n\u003cp\u003eAAMR per 100,000 standard population was computed using the direct method with the 2000 U.S. standard population. Stratification was performed by sex (male and female), race and ethnicity (Non-Hispanic White, Non-Hispanic Black, Hispanic, and Non-Hispanic Other), age group (25\u0026ndash;34, 35\u0026ndash;44, 45\u0026ndash;54, 55\u0026ndash;64, 65\u0026ndash;74, 75\u0026ndash;84, and 85\u0026thinsp;+\u0026thinsp;years), census region (Northeast, Midwest, South, and West), and urbanization level (metropolitan and nonmetropolitan areas as defined by the National Center for Health Statistics). This classification was derived from information available in the CDC Wonder database\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eJoinpoint regression analysis was conducted using the National Cancer Institute\u0026rsquo;s Joinpoint Regression Program (Version 5.0.2) to pinpoint significant temporal shifts in mortality trends\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Beginning with zero Joinpoints, the Monte Carlo permutation test determined the optimal number of significant change points. Annual percent change (APC) for each identified segment and average annual percent change (AAPC) for the entire period (1999\u0026ndash;2023) were calculated\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, along with their 95% confidence intervals (CI). Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eTrends were classified as increasing or decreasing if the APC/AAPC was significantly from zero. Poisson regression models accounted for potential overdispersion in the mortality data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eUtilizing publicly accessible, de-identified aggregate data from CDC WONDER, this study was exempt from institutional review board approval.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDivergent National Trends in HLM and DNHL Mortality, United States 1999\u0026ndash;2023\u003c/h2\u003e \u003cp\u003eBetween 1999 and 2023, U.S. mortality trends for HLM and DNHL diverged sharply. While HLM deaths saw a modest increase from 55,080 to 56,039 (+\u0026thinsp;1.74%), the AAMR declined significantly from 31.09 to 20.29 per 100,000 (AAPC = -1.74%; 95% CI: -1.80 to -1.68) (Table\u0026nbsp;1). In stark contrast, DNHL deaths escalated dramatically from 2,628 to 7,295 (+\u0026thinsp;177.59%), accompanied by a rising AAMR from 1.48 to 2.62 (AAPC\u0026thinsp;=\u0026thinsp;2.64%; 95% CI: 1.19 to 4.11) (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eSynthesizing data from Tables\u0026nbsp;1 \u0026amp; 2 reveals notable disparities:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSex\u003c/b\u003e: HLM mortality decreased more markedly among females (AAPC = -1.99%) than males (-1.65%). Conversely, DNHL mortality increased more rapidly in males (AAPC\u0026thinsp;=\u0026thinsp;2.56%) compared to females (2.44%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRegion\u003c/b\u003e: HLM mortality declined in the Northeast (AAPC = -2.06%) and Midwest (-1.70%) but increased in the South and West. DNHL mortality rose across all regions, most precipitously in the West (+\u0026thinsp;223.33% deaths) and Northeast (AAPC\u0026thinsp;=\u0026thinsp;3.01%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRace/Ethnicity\u003c/b\u003e: HLM deaths increased among Hispanic (+\u0026thinsp;107.61%) and Non-Hispanic (NH) Other (+\u0026thinsp;128.37%) populations. Mirroring this, DNHL mortality surged most rapidly in these same groups (AAPC\u0026thinsp;=\u0026thinsp;3.90% and 3.41%, respectively).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAge\u003c/b\u003e: The largest declines in HLM mortality occurred in younger age groups (e.g., 45\u0026ndash;54 years: AAPC = -3.11%), while DNHL increases were most pronounced in the oldest group (\u0026ge;\u0026thinsp;85 years: AAPC\u0026thinsp;=\u0026thinsp;4.41%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eUrbanicity\u003c/b\u003e: Metropolitan areas witnessed significant increases in DNHL mortality (AAPC\u0026thinsp;=\u0026thinsp;2.56%), a trend not observed in nonmetropolitan areas.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSex-Specific Patterns in HLM Mortality and DNHL mortality, United States 1999–2023\u003c/h3\u003e\n\u003cp\u003eJoinpoint regression analyses delineated sex-specific differences (1999\u0026ndash;2023).\u003c/p\u003e \u003cp\u003eHLM Mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA): Mortality declined significantly for both sexes, with a steeper reduction among females (APC = -1.99%; 95% CI: -2.07 to -1.91) than males (APC = -1.65%; 95% CI: -1.72 to -1.59).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNHL mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB): The overall population exhibited an initial decline (1999\u0026ndash;2008: APC = -3.83%; 95% CI: -4.92 to -2.73), followed by a sharp increase (2008\u0026ndash;2011: APC\u0026thinsp;=\u0026thinsp;+\u0026thinsp;16.79%; 95% CI: 3.97 to 31.18), and a sustained rise (2011\u0026ndash;2023: APC\u0026thinsp;=\u0026thinsp;4.35%; 95% CI: 3.83 to 4.88). Females experienced a more pronounced initial decline (1999\u0026ndash;2008: APC = -5.22%; 95% CI: -6.57 to -3.85) followed by significant increases (2008\u0026ndash;2011: APC\u0026thinsp;=\u0026thinsp;17.39%; 95% CI: 0.60 to 36.97; 2011\u0026ndash;2023: APC\u0026thinsp;=\u0026thinsp;4.96%; 95% CI: 4.28 to 5.65). Males demonstrated greater complexity: an initial decline (1999\u0026ndash;2008: APC = -3.22%; 95% CI: -3.81 to -2.63), a sharp increase (2008\u0026ndash;2011: APC\u0026thinsp;=\u0026thinsp;17.35%; 95% CI: 10.56 to 24.55), and subsequent phased increases culminating in a significant rise from 2017\u0026ndash;2023 (APC\u0026thinsp;=\u0026thinsp;2.42%; 95% CI: 1.74 to 3.10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eRegional Variation in HLM Mortality and DNHL mortality, United States 1999–2023\u003c/h3\u003e\n\u003cp\u003eJoinpoint regression analyses revealed distinct regional patterns for HLM mortality and DNHL mortality across U.S. census regions (1999\u0026ndash;2023).\u003c/p\u003e \u003cp\u003eHLM mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eA): Mortality declined significantly in all regions. The Northeast exhibited a biphasic pattern: an initial decrease (1999\u0026ndash;2017: APC = -1.74%; 95% CI: -1.85 to -1.62) followed by a steeper decline (2017\u0026ndash;2023: APC = -3.03%; 95% CI: -3.65 to -2.40). The Midwest, South, and West showed consistent monotonic declines with APCs of -1.70% (95% CI: -1.77 to -1.62), -1.64% (95% CI: -1.71 to -1.57), and \u0026minus;\u0026thinsp;1.73% (95% CI: -1.82 to -1.65), respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNHL mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eB): Mortality increased substantially nationwide, but with region-specific multiphase patterns. The Northeast, Midwest, and West shared a trajectory: initial decline (1999\u0026ndash;2008), sharp upturn (2008\u0026ndash;2011: APCs 16.43\u0026ndash;21.35%), and sustained increase (2011\u0026ndash;2023: APCs 3.65\u0026ndash;4.53%). The South differed slightly, showing a significant decrease (1999\u0026ndash;2006: APC = -5.20%;95% CI: -8.21 to -2.09) followed by a pronounced continuous rise (2006\u0026ndash;2023: APC\u0026thinsp;=\u0026thinsp;5.67%; 95% CI: 4.99 to 6.36).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRacial and Ethnic Disparities in HLM Mortality and DNHL mortality, United States 1999\u0026ndash;2023\u003c/h2\u003e \u003cp\u003eJoinpoint regression analyses highlighted divergent trends across racial and ethnic groups (1999\u0026ndash;2023).\u003c/p\u003e \u003cp\u003eHLM Mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA): Consistent declines were observed across all groups: Non-Hispanic White (APC = -1.66%; 95% CI: -1.72 to -1.60), Hispanic (APC = -1.44%; 95% CI: -1.59 to -1.28), Non-Hispanic Black (APC = -1.54%; 95% CI: -1.65 to -1.44). Non-Hispanic Other exhibited a biphasic decline with acceleration after 2018 (APC = -3.19%; 95% CI: -4.62 to -1.74).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNHL mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eB): Complex multiphase increases characterized all populations. Non-Hispanic White transitioned from initial decline (1999\u0026ndash;2008: APC = -3.71%; 95% CI: -4.83 to -2.57) to sharp increase (2008\u0026ndash;2011: APC\u0026thinsp;=\u0026thinsp;16.29%; 95% CI: 2.92 to 31.40) and sustained rise (2011\u0026ndash;2023: APC\u0026thinsp;=\u0026thinsp;4.45%; 95% CI: 3.89 to 5.01). Similar patterns emerged among Non-Hispanic Black, Hispanic, and Other racial groups, each showing significant upward trends in recent periods (2010\u0026ndash;2023 APCs ranging 4.38%\u0026ndash;5.33%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAge-Specific Divergence in HLM Mortality and DNHL mortality, 1999\u0026ndash;2023\u003c/h2\u003e \u003cp\u003eJoinpoint regression analyses from 1999 to 2023 uncovered contrasting age-specific patterns for HLM mortality and DNHL mortality.\u003c/p\u003e \u003cp\u003eHLM mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eA): Significant declines characterized most age cohorts, with the steepest reductions in middle-aged groups: ages 55\u0026ndash;64 experienced an APC of -4.27% (1999\u0026ndash;2004), followed by -2.69% until 2023; ages 35\u0026ndash;44 showed a persistent decline (APC = -2.88%). However, a concerning reversal emerged among young adults (25\u0026ndash;34 years), shifting from a significant decrease (APC = -4.27%, 2009\u0026ndash;2020) to a non-significant increase (APC\u0026thinsp;=\u0026thinsp;1.17%) post-2020.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNHL mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eB): Mortality rose substantially, particularly among older populations: ages 75\u0026ndash;84 increased sharply (APC\u0026thinsp;=\u0026thinsp;11.81%, 2007\u0026ndash;2012), then stabilized at 4.76% until 2023; ages\u0026thinsp;\u0026ge;\u0026thinsp;85\u0026thinsp;+\u0026thinsp;exhibited significant increases from 2010 onwards (APC\u0026thinsp;=\u0026thinsp;7.09%). Middle-aged groups also transitioned to rising mortality; for example, ages 45\u0026ndash;54 shifted from decline (APC = -6.40%, 1999\u0026ndash;2005) to sustained increase (APC\u0026thinsp;=\u0026thinsp;3.64%, 2005\u0026ndash;2023). Notably, young adults (25\u0026ndash;34 years) demonstrated a steady rise in DNHL mortality (APC\u0026thinsp;=\u0026thinsp;1.29%) throughout the period, temporally coinciding with the recent HLM mortality reversal in this same age group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eUrban\u0026ndash;Rural Disparities in HLM Mortality and DNHL mortality, United States 1999\u0026ndash;2020\u003c/h2\u003e \u003cp\u003eJoinpoint regression analyses (1999\u0026ndash;2020) revealed contrasting trends by urbanization level.\u003c/p\u003e \u003cp\u003eHLM Mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eA): Mortality declined across all areas but with distinct patterns. Metropolitan areas showed a triphasic trend with accelerated decline from 2012 to 2020 (APC = -2.14%; 95% CI: -2.34 to -1.94). Nonmetropolitan areas demonstrated a consistent monotonic decrease (APC = -1.56%; 95% CI: -1.65 to -1.48).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNHL mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eB): Both settings displayed similar triphasic patterns: initial decline (metropolitan: APC = -3.78%, 95% CI: -5.14 to -2.40; nonmetropolitan: APC = -3.72%, 95% CI: -5.27 to -2.16), sharp increase around 2008\u0026ndash;2011 (metropolitan: APC\u0026thinsp;=\u0026thinsp;16.54%, 95% CI: 0.9134.59; nonmetropolitan: APC\u0026thinsp;=\u0026thinsp;15.10%, 95% CI: -2.82 to 36.32), and sustained significant rise from 2011 to 2020 (metropolitan: APC\u0026thinsp;=\u0026thinsp;4.75%, 95% CI: 3.71 to 5.79; nonmetropolitan: APC\u0026thinsp;=\u0026thinsp;4.50%, 95% CI: 3.26 to 5.76). Metropolitan areas experienced marginally more pronounced increases in the most recent period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGeographic Disparities in HLM and DNHL Mortality, United States 1999\u0026ndash;2020\u003c/h2\u003e \u003cp\u003eSignificant interstate variations in age-adjusted mortality rates (AAMR) were observed for both hematologic malignancies (HLM) and diffuse non-Hodgkin lymphoma (DNHL) (Tables S1\u0026amp;S2). The Average Annual Percent Change (AAPC) for HLM ranged from \u0026minus;\u0026thinsp;1.05% (95% CI: -1.32 to -0.78) in Oklahoma to -2.56% (95% CI: -3.20 to -1.92) in New Jersey. For DNHL, AAPC varied from \u0026minus;\u0026thinsp;0.25% (95% CI: -2.98 to 2.43) in Iowa to -4.44% (95% CI: -2.44 to 6.48) in Kentucky.\u003c/p\u003e \u003cp\u003eSpatial analysis indicated consistent mortality burdens across tumor types (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B). Among HLM-related mortalities, California, Florida, and Texas recorded the highest death counts, with DNHL\u0026rsquo;s top-ranked states aligning with this pattern. For HLM, the most pronounced nationwide declines in AAMR occurred in New Jersey (-2.56% AAPC), New York, and District of Columbia. In New Jersey, the AAMR exhibited a notable late-phase acceleration (2020\u0026ndash;2023 APC: -5.15%; 95% CI: -10.05 to -0.01) after a period of steady reduction (1999\u0026ndash;2020 APC: -2.19%; 95% CI: -2.43 to -1.94) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, DNHL showed upward AAMR trends, with Kentucky, Massachusetts, and California experiencing the steepest increases. Notably, California\u0026rsquo;s AAMR followed a triphasic pattern: a neutral early phase (1999\u0026ndash;2008 APC: -0.28%; 95% CI: -2.11 to 1.59), a transient surge (2008\u0026ndash;2011 APC: 15.37%; 95% CI: -2.12 to 35.99), a sustained rise (2011\u0026ndash;2023 APC: 4.67%; 95% CI: 3.91 to 5.44) (Figure S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis comprehensive analysis of U.S. HLM and DNHL mortality trends from 1999 to 2023 identifies persistent and emerging disparities across demographic, geographic, and urban\u0026ndash;rural strata. Although overall HLM mortality has decreased\u0026ndash;aligning with advancements in therapeutic and supportive care\u0026ndash;our results highlight that these improvements have not been distributed equitably. In contrast, DNHL incidence and mortality have increased substantially, especially among historically marginalized populations and older adults, which signals an urgent public health concern.\u003c/p\u003e \u003cp\u003eThe observed decline in HLM mortality aligns with prior research documenting improved survival for leukemias, lymphomas, and multiple myeloma\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, a trend plausibly linked to innovations like targeted therapies, immunotherapies, and hematopoietic stem cell transplantation\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Nonetheless, substantial heterogeneity in mortality reductions across racial, ethnic, and geographic lines indicates systemic inequities in accessing to these advancements\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. For example, the more pronounced mortality declined among Non-Hispanic White individuals, relative to slower progress among Hispanic and Non-Hispanic Black populations, may stem from disparities in timely diagnosis, treatment quality, and healthcare access. Furthermore, the reversed mortality trend among young adults (25\u0026ndash;34 years) warrants scrutiny, as it could signal emerging risk factors or delays in care within this age group.\u003c/p\u003e \u003cp\u003eBy stark contrast, the sharp increase in DNHL incidence and mortality represents a divergent and alarming trajectory. The multiphasic surge\u0026ndash;an initial decline followed by a steep upward shift after 2008\u0026ndash;201\u0026ndash;might stem from changes in diagnostic practices, disease classification, or genuine increases in mortality due to environmental, immunological, or viral factors\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Notably, the exceptionally high increase among older adults (APC\u0026thinsp;=\u0026thinsp;7.09% in ages\u0026thinsp;\u0026ge;\u0026thinsp;85+) emphasizes age-related vulnerability and potentially cumulative carcinogenic exposures\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Moreover, the significant rise among racial and ethnic minorities, including Hispanic and Non-Hispanic Other populations, underscores the influence of social determinants of health, such as socioeconomic status, environmental justice issues disparities, and differential access to preventive care.\u003c/p\u003e \u003cp\u003eGeographic and urban\u0026ndash;rural disparities further highlight the uneven burden of these malignancies. The slower decline in HLM mortality and faster rise in DNHL in the South and West may be influenced by regional differences in healthcare infrastructure, screening programs, and provider density. In contrast, more favorable trends in the Northeast and Midwest might reflect earlier adoption of advanced treatments and stricter public health policies. Similarly, the reduced improvements in nonmetropolitan areas (compared to metropolitan regions) emphasize the urgency of addressing rural health disparities, including limited access to specialty care and diagnostic delays.\u003c/p\u003e \u003cp\u003eThe identified sex-specific differences\u0026mdash;steeper HLM mortality declines among females and sharper DNHL increases among males\u0026mdash;may arise from biological, behavioral, or environmental factors that affect each sex differently\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Areas for further investigation include hormonal influences, occupational exposures, and health-seeking behaviors.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitations\u003c/h2\u003e \u003cp\u003eSeveral limitations merit consideration. First, reliance on death certificate data may introduce misclassification bias in cause-of-death reporting. Second, the Joinpoint model\u0026rsquo;s assumption linearity between change points could oversimplifying intricate underlying patterns. Third, DNHL mortality analyses relied on mortality proxies rather than population-based registry data, which may limit interpretability. Finally, unmeasured confounders such as socioeconomic status, comorbidities, and treatment patterns were not incorporated into in this ecological analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePublic Health Implications\u003c/h2\u003e \u003cp\u003eThese findings advocate for targeted public health strategies to mitigate the growing DNHL burden and persistent inequities in HLM outcomes. Priorities should include enhancing early detection, expanding access to specialized care in underserved regions, and implementing culturally tailored prevention programs. Future research should investigate the biologic and social mechanisms driving these disparities, including the roles of genomics, environmental exposures, and health care policy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhile progress has been made in reducing HLM mortality at the national level, significant disparities remain across populations. The rapid rise in DNHL mortality and mortality demands concerted clinical and public health action to mitigate its impact, particularly among vulnerable subgroups.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHLM \u003cstrong\u003eHematologic and Lymphoid Malignancy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNHL Diffuse Non-Hodgkin Lymphoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAPC Annual Percent Changes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAAPC Average Annual Percent Changes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAAMR Age-Adjusted Mortality Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNS Not Significant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNH Non-Hispanic\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCDC WONDER Centers for Disease Control and Prevention\u0026rsquo;s Wide-ranging Online Data for Epidemiologic Research\u003c/p\u003e\n\u003cp\u003eICD-10 International Classification of Diseases, Tenth Revision\u003c/p\u003e\n\u003cp\u003eCI Confidence Intervals\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used in this study were de-identified and publicly available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available in the CDC WONDER database, https:// wonder. cdc. gov.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNanchang Science and Technology Bureau, General Project of Medical and Health Science and Technology Support (2022-KJZC-028).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJumping Li: Conceptualization, Methodology, Formal Analysis, Writing: original draft and editing. Shiyu Xiong: Writing: original draft, review and editing. Feng Xiong: Writing: original draft and editing. Feng Qiu: Validation, Conceptualization, Supervision, and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Centers for Disease Control and Prevention for providing the database. The authors would like to thank Dr. Anmin Liu (University of Salford) for his suggestions on manuscript revision.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeras LR, et al. 2016 US lymphoid malignancy statistics by World Health Organization subtypes. 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Personal tumor antigens in blood malignancies: genomics-directed identification and targeting. J Clin Invest. 2020;130:1595\u0026ndash;607.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhatnagar B, Eisfeld A-K. Racial and ethnic survival disparities in patients with haematological malignancies in the USA: time to stop ignoring the numbers. Lancet Haematol. 2021;8:e947\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasey M, et al. Are Pivotal Clinical Trials for Drugs Approved for Leukemias and Multiple Myeloma Representative of the Population at Risk? J Clin Oncol Off J Am Soc Clin Oncol. 2022;40:3719\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFalini B, Martino G, Lazzi S. A comparison of the International Consensus and 5th World Health Organization classifications of mature B-cell lymphomas. Leukemia. 2023;37:18\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKimani S, et al. 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Front Immunol. 2022;13:842439.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIosselevitch I, Tabibian-Keissar H, Barshack I, Mehr R. Gastric DLBCL clonal evolution as function of patient age. Front Immunol. 2022;13:957170.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y-T, et al. Sex differences in mortality: results from a population-based study of 12 longitudinal cohorts. Can Med Assoc J. 2021;193:E361\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao E, Crimmins EM. Mortality and morbidity in ageing men: Biology, Lifestyle and Environment. Rev Endocr Metab Disord. 2022;23:1285\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 2 are available in the Supplementary Files section.\u003c/p\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":"Hematologic Malignancies, Diffuse Non-Hodgkin Lymphoma, Mortality trends","lastPublishedDoi":"10.21203/rs.3.rs-8312078/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8312078/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eWhile overall hematologic and lymphoid malignancy (HLM) mortality has declined in the US, significant disparities persist across subtypes and demographic groups. This study characterizes 24-year trends in HLM and diffuse non-Hodgkin lymphoma (DNHL) mortality, quantifying inequities through advanced segmentation modeling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eUsing CDC WONDER mortality data (1999–2023), we performed Joinpoint regression analyses to calculate annual percent changes (APC) and average annual percent changes (AAPC) in age-adjusted mortality rates (AAMR). Stratification by sex, race/ethnicity, age, region, and urbanicity identified high-risk populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e• \u003cstrong\u003eDivergent national trends:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHLM mortality decreased (AAPC = -1.74%; 95% CI: -1.80 to -1.68) despite +1.74% absolute death increase.\u003c/p\u003e\n\u003cp\u003eDNHL mortality surged (AAPC = +2.64%; 95% CI: 1.19 to 4.11) with +177.59% death rise.\u003c/p\u003e\n\u003cp\u003e• \u003cstrong\u003eCritical disparities:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAge: Young adults (25–34y) showed HLM mortality reversal post-2020 (APC +1.17%, P ≥0.05) vs steep DNHL rise in ≥85y (AAPC= +4.41%；95% CI:1.75 to 7.14).\u003c/p\u003e\n\u003cp\u003eRace: Hispanic and NH-Other populations experienced 107–128% HLM death increases alongside 3.41–3.90% DNHL AAPC rises.\u003c/p\u003e\n\u003cp\u003eGeography: DNHL mortality doubled in Western states (e.g., California: 2008–2011 APC = +15.37%; 95% CI: -2.12 to 35.99) while HLM declines lagged in Southern regions.\u003c/p\u003e\n\u003cp\u003el \u003cstrong\u003eNovel inflection points:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNationwide DNHL mortality shifted from decline (1999–2008 APC = -3.83%; 95% CI: -4.92 to -2.73) to sharp increase (2008–2011 APC = +16.79%; 95% CI: 3.97 to 31.18).\u003c/p\u003e\n\u003cp\u003eUrban areas demonstrated accelerated HLM declines post-2012 (APC = -2.14%; 95% CI: -2.34 to -1.94).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Substantial gains in HLM mortality mask worsening disparities, particularly among racial minorities and older adults. The alarming rise in DNHL mortality—characterized by distinct inflection points and geographic hotspots—signals an urgent need for targeted interventions.\u003c/p\u003e","manuscriptTitle":"Divergent Mortality Trends in Hematologic Malignancies and Diffuse Non–Hodgkin Lymphoma Across the United States: A CDC WONDER Database Analysis from 1999 to 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 10:14:37","doi":"10.21203/rs.3.rs-8312078/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":"87ef5f44-96c6-44d9-a396-deaadda898c6","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T14:10:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-08 10:14:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8312078","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8312078","identity":"rs-8312078","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}