Introduction

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm originating from hematopoietic stem cells, often presenting with symptoms such as fatigue, low-grade fever, and unintentional weight loss.1 The molecular hallmark of CML is the Philadelphia chromosome, resulting from the reciprocal translocation t(9;22)(q34;q11.2). This translocation generates the BCR-ABL1 fusion gene, which encodes a constitutively active tyrosine kinase that drives leukemogenesis.2,3 CML has an annual incidence of approximately 2 cases per 100,000 population, corresponding to an estimated 9600 new cases in the United States in 2024.4 The advent of tyrosine kinase inhibitors (TKIs), such as imatinib, nilotinib, and dasatinib, has dramatically improved outcomes and transformed CML into a manageable chronic condition for many patients.5 However, this therapeutic success has been accompanied by emerging challenges, including TKI resistance, cardiovascular toxicities, and the escalating economic burden of lifelong therapy, particularly in resource-limited settings.6 For elderly patients (≥65 years), these challenges are further compounded. This population frequently presents with comorbidities, which may increase susceptibility to TKI-associated toxicities and complicate treatment regimens.7 Crucially, existing clinical guidelines lack specific recommendations tailored to the physiological and pharmacological particularities of the elderly, highlighting a significant gap in evidence-based care.

Globally, population aging is accelerating, leading to a projected increase in the number of older adults living with CML. Previous GBD-based studies8–11 have provided valuable insights into the global and national burden of CML. However, these analyses have primarily focused on the general population without specifically addressing the elderly subgroup or systematically evaluating age-specific patterns in the context of global population aging. The availability of updated GBD 2021 data offers an opportunity to address this gap. Therefore, this study aims to provide a comprehensive assessment of the CML burden in adults aged ≥65 years.

Using data from the GBD 2021 study, we systematically evaluated the burden of CML among adults aged ≥65 years from 1990 to 2021 across 204 countries and territories. We examined age-standardized rates of prevalence, mortality, and disability-adjusted life years (DALYs), quantified temporal trends using the average annual percentage change (AAPC), and stratified all analyses by age, sex, geographical region, and sociodemographic index (SDI) to identify disparities and inform targeted public health strategies.

Materials and Methods Data Source and Study Population

This study is a secondary analysis of publicly available, de-identified data from the GBD 2021 study, obtained via the Global Health Data Exchange query tool. The GBD 2021 provides a comprehensive and comparable assessment of the burden of 369 diseases and injuries and 87 risk factors across 204 countries and territories, stratified into 21 regions, from 1990 to 2021.12,13

Our study population comprised all individuals aged 65 years and older diagnosed with CML. This cutoff was selected because the median age at diagnosis of CML is approximately 65 years, and the incidence increases significantly with advancing age, making this age group the predominant demographic affected by the disease.14 CML cases were identified based on physician diagnosis, supported by cancer registry data, hospital discharge records, and mortality reports, in accordance with the GBD case definition. For the present analysis, we extracted the following annual estimates for the population aged ≥65 years from the GBD 2021 dataset: 1) prevalence counts and age-standardized prevalence rates, 2) mortality counts and age-standardized mortality rates, 3) DALY counts and age-standardized DALY rates, and 4) DALYs attributable to specific risk factors.

Estimation Framework and Key Metrics

The GBD study employs a standardized, iterative analytical framework to produce internally consistent estimates. Key steps and metrics relevant to our analysis are summarized below.

Prevalence and mortality estimation: A Bayesian meta-regression tool, DisMod-MR 2.1, was used as the core modeling platform to synthesize data from 1527 site-years of input. These data were derived from scientific literature, survey microdata, and insurance claims to estimate non-fatal (prevalence) and fatal (mortality) outcomes for CML, accounting for disease complications.15,16 Spatiotemporal Gaussian process regression was applied to smooth estimates across geography and time, and to generate estimates for locations with sparse or missing data.17,18 All estimates are reported with 95% uncertainty intervals, representing the 25th and 975th values of 1000 posterior distribution draws.19 Wider intervals indicate greater uncertainty due to limited data or model heterogeneity.20

Calculation of DALYs: DALYs quantify the total health loss from a disease, calculated as the sum of years of life lost due to premature mortality and years lived with disability. Years of life lost were calculated by multiplying the number of deaths at each age by a standard life expectancy at that age of death, based on the theoretical minimum risk life expectancy from the GBD study.21 Years lived with disability were estimated by multiplying the prevalence of sequelae (health states) associated with CML by their respective disability weights, which reflect the severity of health loss on a scale from 0 (perfect health) to 1 (equivalent to death). To isolate the contribution of CML, years lived with disability were adjusted for comorbidities using microsimulation methods.22

Attributable DALYs represent the portion of total DALYs that can be ascribed to specific risk factors. Changes in exposure to a risk factor directly influence the magnitude of its attributable burden.23,24

Stratification and SDI

All burden estimates (prevalence, mortality, and DALYs) were analyzed by seven age subgroups (65–69, 70–74, 75–79, 80–84, 85–89, 90–94, and ≥95 years), sex (male and female), and geographical location (global, 21 GBD regions, and 204 countries/territories).

To assess socioeconomic disparities, we utilized the GBD’s SDI. The SDI is a composite measure of a location’s lag-distributed income per capita, average years of education in the population aged 15 and older, and the total fertility rate under the age of 25. It ranges from 0 (lowest development) to 1 (highest development). Countries and territories were classified into five quintiles for comparative analysis: low, low-middle, middle, high-middle, and high SDI.25

Statistical Analysis and Trend Assessment

The primary metrics reported were age-standardized rates per 100,000 population. Age-standardization was performed using the GBD 2021 world standard population to facilitate comparisons across populations with different age structures and over time. Temporal trends from 1990 to 2021 were quantified using the AAPC and its 95% confidence interval, derived from joinpoint regression analysis (Joinpoint Regression Program, Version 5.0.2). The AAPC summarizes the average trend over the entire period; a negative AAPC indicates a declining trend, while a positive AAPC indicates an increasing trend. A trend was considered statistically significant if its 95% confidence interval did not include zero.26

Descriptive analyses and data visualization were performed using R software (version 4.3.3) and GraphPad Prism version 9.0 (GraphPad Software, San Diego, CA, USA). All analyses were conducted in accordance with the Guidelines for Accurate and Transparent Health Estimates Reporting.

Ethics Statement

According to Article 32, Items 1 and 2 of the Measures for Ethical Review of Life Science and Medical Research Involving Human Subjects (February 18, 2023, China), ethical review and approval are exempted for research that utilizes publicly available, de-identified data without direct intervention or interaction with human subjects. Therefore, no separate ethical approval was required for this study. Individual informed consent was not applicable as the data were anonymized and aggregated prior to analysis.

Results Global Burden and Trends (1990–2021)

We first analyzed the overall trends in the burden of CML among adults aged ≥65 years globally from 1990 to 2021, including changes in case counts, age-standardized prevalence, mortality, and DALY rates. From 1990 to 2021, the absolute number of prevalent CML cases among individuals aged ≥65 years globally increased by 36.84%. Consequently, the proportion of elderly patients among all CML cases rose from 33.5% in 1990 to 40.5% in 2021 (Figure 1A). Despite this increase in case numbers, the age-standardized prevalence rate declined substantially (Table 1 and Figure 2A). The proportion of CML-related mortality among the elderly increased to 56% by 2021 (Figure 1B). However, the age-standardized mortality rate showed a more pronounced decline (Supplementary Table S1 and Figure 2B). Similarly, the proportion of all-cause DALYs attributable to CML in this age group also increased over the study period (Figure 1C). Despite the increasing proportion, the age-standardized DALY rate declined markedly (Supplementary Table S1 and Figure 2C). Therefore, while the absolute number of elderly individuals living with CML has risen significantly over the past three decades, the age-standardized rates of prevalence, mortality, and DALYs have shown substantial annual declines globally, indicating improved disease management and survival.

Table 1 Age-Standardized Prevalence and AAPC of CML in Individuals Aged ≥65 years at Global, Sex-, Age-, and SDI-Specific Levels, 1990–2021

Figure 1 Burden of CML in adults aged ≥65 years among all CML patients, 1990–2021. (A) Proportion of CML patients aged ≥65 years among all CML patients, 1990–2021. (B) Proportion of mortality in adults aged ≥65 years among all CML‑related deaths, 1990–2021. (C) Proportion of DALYs attributable to CML in adults aged ≥65 years among all CML‑related DALYs, 1990–2021.

Abbreviations: CML, chronic myeloid leukemia; DALYs, disability-adjusted life years.

Figure 2 AAPC in age‑standardized prevalence, mortality, and DALYs for CML patients aged ≥65 years and for all CML patients, by SDI level, 1990–2021. Positive AAPC values indicate increasing trends; negative values indicate decreasing trends. (A) Age-standardized prevalence rate; (B) Age-standardized mortality rate; (C) Age-standardized DALY rate.

Abbreviations: CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Stratified Analysis by Sex, Age, and SDI

To identify disparities and differential progress, we analyzed and compared the trends in CML burden from 1990 to 2021 among elderly adults, stratified by sex, age subgroups, and sociodemographic development levels.

Sex-specific trends: From 1990 to 2021, the age-standardized prevalence declined more rapidly in men than in women, although the absolute number of cases increased for both sexes (Table 1). The declines in age-standardized mortality and DALYs were comparable between sexes (Supplementary Table S1). However, men consistently bore a higher absolute disease burden than women across all SDI levels (Supplementary Table S1, Figures 3 and 4).

Figure 3 Trends in age‑standardized mortality and DALYs of CML in adults aged ≥65 years, by global and SDI levels and sex, 1990–2021.

Abbreviations: CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Figure 4 AAPC in age‑standardized mortality and DALYs of CML in adults aged ≥65 years, by SDI level and sex, 1990–2021. Positive AAPC values indicate increasing trends; negative values indicate decreasing trends.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Age-specific trends: The most substantial declines in age-standardized DALYs were observed in the younger elderly subgroups: 65–79 years (Supplementary Table S1), while in 2021, the highest mortality and DALY rates shifted to the oldest age groups (90–94 and ≥95 years) (Figure 5).

Figure 5 AAPC in age‑standardized prevalence, mortality, and DALYs of CML in adults aged ≥65 years, by sex and age group, 1990–2021. Positive AAPC values indicate increasing trends; negative values indicate decreasing trends. Age groups are: 65–69, 70–74, 75–79, 80–84, 85–89, 90–94, and ≥95 years.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years.

SDI-specific trends: Significant disparities were observed across the SDI spectrum. Figure 6 illustrates the temporal trends in age-standardized prevalence, mortality, and DALYs across SDI quintiles from 1990 to 2021, showing consistent declines in all SDI groups but with steeper slopes in higher SDI regions. Figure 7 compares the age-standardized rates between 1990 and 2021 across SDI quintiles, demonstrating that higher SDI regions achieved greater absolute reductions over the 31-year period. In 2021, the highest age-standardized prevalence was observed in high-SDI countries, while low-SDI countries had the lowest (Table 1 and Figure 8A). The most rapid declines in mortality and DALYs occurred in high-SDI countries (Supplementary Table S1). In contrast, low-middle-SDI countries experienced the slowest declines and had the highest age-standardized DALY rate in 2021 (Supplementary Table S1; Figure 8B and C).

Figure 6 Trends in age‑standardized prevalence, mortality, and DALYs for CML patients aged ≥65 years and for all CML patients, by global and SDI levels, 1990–2021. Rates are expressed per 100,000 population.

Abbreviations: CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Figure 7 Comparision of age‑standardized prevalence, mortality, and DALYs between 1990 and 2021 for CML patients aged ≥65 years and for all CML patients, by global and SDI levels, 1990–2021. Rates are expressed as percentages.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Figure 8 Age‑standardized prevalence, mortality, and DALY rates of CML in adults aged ≥65 years, plotted against SDI in 2021. (A) Age-standardized prevalence rate; (B) Age-standardized mortality rate; (C) Age-standardized DALY rate. Each point represents a country or territory. The SDI is a composite measure of income per capita, education, and fertility rate, ranging from 0 (lowest development) to 1 (highest development).

Abbreviations: CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; SDI, sociodemographic index.

Thus, the burden was consistently higher in men than in women. Reductions in DALYs were most pronounced in the 65–79 year age group. Higher SDI quintiles were associated with both the most rapid declines in mortality and DALYs, and, in 2021, the lowest DALY rates.

Regional Patterns in 2021 and Trends (1990–2021)

We then examined the geographical distribution of the CML burden in the elderly population in 2021 and evaluated regional trends over the study period, identifying areas of high burden and variable progress. In 2021, the highest age-standardized prevalence rates were concentrated in High-income North America and Western Europe (Table 2). In contrast, the highest age-standardized DALY rates were identified in Oceania, the Caribbean, and North Africa and the Middle East (Supplementary Table S2).

Table 2 Age-Standardized Prevalence and AAPC of CML in Individuals Aged ≥65 years Across 21 GBD Regions, 1990–2021

From 1990 to 2021, most regions exhibited declining trends. Australasia recorded the most significant reduction in age-standardized DALYs (Supplementary Table S2). A few regions, including Andean Latin America, East Asia, Eastern Europe, and North Africa and the Middle East, showed stable or slightly increasing prevalence trends (Figure 9 and Table 2). Sex-stratified analysis at the regional level showed higher burden in males but similar declining trends for both sexes (Figure 10 and Supplementary Table S3).

Figure 9 AAPC in age‑standardized prevalence, mortality, and DALYs of CML in adults aged ≥65 years, by GBD region, 1990–2021. Positive AAPC values indicate increasing trends; negative values indicate decreasing trends.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; GBD, Global Burden of Disease.

Figure 10 AAPC in age‑standardized mortality and DALYs of CML in adults aged ≥65 years, by GBD region and sex, 1990–2021. Positive AAPC values indicate increasing trends; negative values indicate decreasing trends.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; GBD, Global Burden of Disease.

National-Level Variation

Next, we evaluated the heterogeneity in the trends of CML burden among the elderly at the national level, identifying countries with the most and least progress. The results revealed considerable heterogeneity at the country level (Supplementary Table S4 and Figures 11–13). The largest increase in age-standardized prevalence, mortality, and DALYs was observed in American Samoa, while the most substantial decreases were seen in Ireland and Singapore. Countries like Sierra Leone and Liberia showed minimal change in age-standardized mortality and DALYs over the 31 years.

Figure 11 Geographic distribution of the AAPC in global DALYs due to CML among adults aged ≥65 years, 1990–2021. Colors represent the magnitude of AAPC: blue indicates decreasing trends, red indicates increasing trends. The maps depict trends within the GBD analytical framework and do not imply any judgment on national boundaries.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALYs, disability-adjusted life years; GBD, Global Burden of Disease.

Figure 12 Geographic distribution of the AAPC in global mortality due to CML among adults aged ≥65 years, 1990–2021. Colors represent the magnitude of AAPC: blue indicates decreasing trends, red indicates increasing trends. The maps depict trends within the GBD analytical framework and do not imply any judgment on national boundaries.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; GBD, Global Burden of Disease.

Figure 13 Geographic distribution of the AAPC in global prevalence of CML among adults aged ≥65 years, 1990–2021. Colors represent the magnitude of AAPC: blue indicates decreasing trends, red indicates increasing trends. The maps depict trends within the GBD analytical framework and do not imply any judgment on national boundaries.

Abbreviations: AAPC, average annual percentage change; CML, chronic myeloid leukemia; GBD, Global Burden of Disease.

Attributable Burden of Risk Factors

Finally, we quantified the contribution of key modifiable risk factors to the DALY burden of CML in the elderly population from 1990 to 2021 and assessed trends in their attributable burden. The four primary risk factors contributing to CML-related DALYs in the elderly globally in 2021 were smoking, high body-mass index, occupational exposure to benzene, and occupational exposure to formaldehyde (Supplementary Table S5). From 1990 to 2021, the attributable burden from these factors declined, with the most rapid reduction observed for smoking (Supplementary Table S5). The decline in smoking-attributable burden was most pronounced in high-SDI countries, whereas countries with lower SDI showed less progress (Supplementary Table S5).

Discussion Key Findings and Overall Interpretation

From 1990 to 2021, the global landscape of CML in the elderly (≥65 years) has undergone a significant transformation. While the absolute number of prevalent cases increased, the age-standardized rates of prevalence, mortality, and DALYs demonstrated consistent and substantial annual declines. This divergence indicates a dual trend: a rising number of older adults living with CML due to extended survival, alongside a marked improvement in disease-specific outcomes. These improvements are unequivocally linked to the global dissemination and adoption of TKIs, which have fundamentally altered the natural history of CML.5 The increasing proportion of elderly patients within the total CML population underscores a critical demographic shift, demanding focused attention on the unique clinical needs and comorbidities of this growing cohort.7

Disparities by Development Status and Geography

Our analysis reveals profound and persistent inequalities in the CML burden across the development spectrum, as measured by the SDI. Although high-SDI regions (eg, High-income North America, Western Europe) exhibited the highest age-standardized prevalence in 2021, likely reflecting superior diagnostic capacity and longer life expectancy, they also achieved the most dramatic reductions in mortality and DALYs. Conversely, the highest DALY burdens were concentrated in regions such as Oceania, the Caribbean, and North Africa/Middle East, with low-middle SDI countries experiencing the slowest pace of improvement. This pattern aligns with previous global burden studies and highlights SDI as a pivotal determinant of timely diagnosis, sustained treatment access, and quality of care.9,27 From a clinical and policy standpoint, these disparities indicate that the survival benefits of TKIs have not been equitably realized worldwide. In resource-limited settings, barriers to timely diagnosis, drug availability, and treatment monitoring remain critical obstacles. Addressing these gaps requires not only drug donation programs but also investments in healthcare workforce training to ensure that elderly CML patients everywhere can benefit from modern therapy.

Sex and Age-Specific Patterns

Gender disparities were evident, with men consistently bearing a higher age-standardized burden than women across all metrics and SDI levels. While the reasons are multifactorial and may include biological differences, lifestyle factors, and possibly variations in healthcare-seeking behavior,28 this finding has important clinical implications. Clinically, targeted outreach and education efforts may be warranted to ensure timely diagnosis and treatment engagement in male elderly populations, who may present with more advanced disease or face barriers to care.

Furthermore, the most pronounced improvements in DALYs were observed in the “younger” elderly subgroups (65–79 years), suggesting that the therapeutic benefits of TKIs may be most effectively realized in patients diagnosed at earlier stages of older age.29 Meanwhile, the shift of the highest mortality and DALY rates to the oldest age groups (≥90 years) in 2021 points to the growing challenge of managing CML in the context of extreme aging and accumulated comorbidities.30 This age-related shift has important clinical implications: very elderly patients (eg, ≥85 years) often have multiple comorbidities, reduced physiological reserve, and increased susceptibility to treatment-related toxicities. For this subgroup, treatment goals may need to be individualized, balancing disease control with quality of life, and potentially considering lower-intensity approaches or modified TKI dosing regimens. These clinical considerations underscore the need for geriatric-informed care models that can accommodate the unique needs of the oldest patients.

The Role of Modifiable Risk Factors

Among the modifiable risk factors assessed, smoking remained the predominant contributor to CML-related DALYs among the elderly in 2021. Despite a significant global decline in its attributable burden, which was most pronounced in high-SDI countries, this persistent association underscores tobacco control as a sustained and critical public health intervention for cancer prevention.31 From a clinical perspective, smoking cessation should be an integral component of CML management in elderly patients, as continued smoking may increase the risk of cardiovascular complications that can be exacerbated by TKI therapy. The attributable burdens of high body-mass index and occupational exposures to benzene and formaldehyde, although substantially lower, nonetheless identify additional, actionable targets for preventive strategies. Notably, benzene is a well-established leukemogen,32 and formaldehyde is classified as a Group 1 human carcinogen,33 which reinforces the importance of upholding stringent occupational safety standards even as their population-level attribution diminishes. The attenuated decline in smoking-attributable burden observed in lower-SDI regions highlights an urgent need for intensified, equitable, and culturally adapted global tobacco control initiatives.

Implications for Clinical Practice and Health Policy

The evolving epidemiology of CML in the elderly necessitates a multifaceted response across clinical and policy domains. First, age-adapted treatment strategies should be prioritized. Elderly patients often exhibit altered pharmacokinetics and increased susceptibility to TKI-related toxicities, particularly cardiovascular adverse events such as hypertension, arrhythmias, and arterial thrombotic events.29,34 Therefore, baseline cardiovascular risk assessment and regular monitoring during TKI therapy are essential in this population.35 Second, the integration of geriatric assessment into routine CML care may help identify frail patients who could benefit from modified treatment approaches, including lower initial TKI doses or closer monitoring for drug interactions due to polypharmacy.29,36,37 Third, there is a pressing need for the development and integration of evidence-based, age-specific clinical guidelines. Such guidelines should address the unique challenges in this population, including polypharmacy, comorbidity management, and the monitoring of TKI-related toxicities, to optimize treatment safety and efficacy.7,38 Fourth, healthcare systems globally, and particularly in rapidly aging societies and lower-resource settings, must enhance their preparedness. This involves planning for the longitudinal care of a growing cohort of elderly CML survivors, which includes long-term surveillance for treatment sequelae, management of age-related functional decline, and interventions to support overall quality of life. Finally, achieving equitable outcomes requires targeted, equity-oriented strategies at both international and national levels. Policies must prioritize strengthening diagnostic infrastructure and securing sustainable financing mechanisms to ensure reliable access to TKIs and optimal supportive care, especially in regions bearing the highest persistent burden of the disease.

Strengths and Limitations

The primary strength of this study lies in its comprehensive use of the GBD 2021 data, providing a standardized and comparable assessment of the CML burden across 204 countries and territories over three decades. However, several limitations must be acknowledged. First, the estimates are model-based extrapolations from regions with available epidemiological data, and their accuracy is contingent upon the quality and completeness of the underlying input data. Disparities in health information systems and reporting mechanisms across countries, particularly in low-resource and conflict settings, may introduce bias. Second, there is an inherent time lag in global burden of disease data, and our modeling approach, while rigorous, is influenced by model selection and parameter settings. Third, our analysis lacks granular clinical data (eg, specific TKI treatment lines, molecular response rates) and detailed metrics on healthcare access, which limits our ability to establish mechanistic links between observed trends and specific clinical or policy drivers. Finally, the challenges in diagnosing CML in the elderly, coupled with variations in healthcare systems and practices, may differentially impact burden estimates across nations. Therefore, our findings should be interpreted within the context of these constraints and validated by future high-quality, real-world studies.

Conclusion

In summary, our analysis demonstrates significant declines in CML-related mortality and DALYs among adults aged ≥65 years from 1990 to 2021, consistent with recent global trends in hematologic malignancies showing improved outcomes in high-income settings alongside persistent disparities. However, these gains remain unequally distributed: women and higher-SDI regions exhibited lower mortality and DALY rates, while substantial burdens persist among men and in lower-SDI settings. These disparities transform the observed trends from a mere clinical success story into a measurable indicator of progress—or lack thereof—toward health equity. Notably, compared with many other hematologic malignancies affecting older adults, where mortality reductions have been less pronounced despite therapeutic advances, CML exemplifies how molecularly targeted therapy can fundamentally alter disease trajectory in aging populations. This contrast underscores both the transformative efficacy of TKIs and the urgent imperative to extend these benefits equitably. Smoking remains a predominant modifiable risk factor demanding sustained public health attention. Moving forward, addressing the dual challenges of equity and aging requires dismantling structural barriers to diagnosis and treatment in underserved regions, while developing integrated, person-centered care models for the growing elderly CML population. Ultimately, ensuring that increased life expectancy translates into improved quality of life for all elderly patients with CML—irrespective of gender, geography, or socioeconomic context—must remain the paramount goal.

Abbreviations

AAPC, average annual percentage change; CML, chronic myeloid leukemia; DALY, disability-adjusted life year; GBD, Global Burden of Disease; SDI, sociodemographic index; TKI, tyrosine kinase inhibitor.

Data Sharing Statement

The datasets supporting the findings of this study are publicly available from the Global Health Data Exchange query tool of the Global Burden of Disease Study 2021: https://ghdx.healthdata.org/gbd-results-tool.

Ethics Approval and Informed Consent

According to Article 32, Items 1 and 2 of the Measures for Ethical Review of Life Science and Medical Research Involving Human Subjects (February 18, 2023, China), ethical review and approval are exempted for research that utilizes publicly available, de-identified data without direct intervention or interaction with human subjects. Therefore, no separate ethical approval was required for this study. Individual informed consent was not applicable as the data were anonymized and aggregated prior to analysis.

Acknowledgments

We gratefully acknowledge the invaluable contributions of the numerous collaborators involved in the Global Burden of Disease Study 2021.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was supported by the Bingtuan Talent Program [Grant No. CZ001248] and The Second Batch of Tianchi Talent Introduction Program of the Autonomous Region.

Disclosure

The authors report no conflicts of interest in this work.

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