Introduction
Malignant melanoma (MM) is a type of aggressive tumor that arises from melanocytes. While it represents a relatively minor percentage of typical skin tumors, it has become the most lethal variant of skin cancer because of its considerable invasive and metastatic capabilities, responsible for more than 90% of fatalities associated with skin cancer and posing a serious risk to human health and life. 1 , 2 According to the International Agency for Research on Cancer (IARC) GLOBOCAN 2022 data, Asia accounts for 7.5% of global cutaneous melanoma cases, with 25,003 out of 331,722 new cases reported globally. In terms of mortality, Asia represents 22.4% of global melanoma deaths, equating to 13,147 out of 58,667 deaths worldwide, a proportion significantly higher than its incidence share. Regarding the five-year prevalence, Asia accounts for 6.5%, with 82,382 cases out of 1,262,756 globally. These data indicate that although the age-standardized incidence rate of melanoma in Asia is considerably lower than in Western populations—approximately 0.41 to 0.5 per 100,000 in Asia compared to 20 to 30 per 100,000 in Europe and North America—the region’s large population base results in a substantial absolute number of cases. Furthermore, Asian countries exhibit the highest mortality-to-incidence (M:I) ratios, reflecting disparities in early detection and access to healthcare. This disparity underscores Asia’s strategic importance in global MM prevention and control. 3 , 4 Previous studies have either provided a generalized description of Asia as a whole or focused exclusively on individual developed countries, lacking systematic quantification of the MM burden across diverse regions and sociodemographic backgrounds within Asia, as well as accurate predictions of its long-term future trends. 5 , 6 This gap in understanding has resulted in the allocation of health resources and the formulation of prevention strategies in Asian countries being devoid of robust, localized data support. In addition, the changing prognosis of melanoma at the population level may be influenced by the evolution of molecular stratification patterns, advancements in biomarker development, the growth of precision oncology, and the introduction of modern systemic therapies. This broader clinical and biological context elucidates why, in certain populations, the incidence of melanoma continues to rise while mortality rates have stabilized or declined. 7 Therefore, epidemiological studies involving patients across Asia are essential.
The Global Burden of Disease Study (GBD) offers a robust framework for comprehensively assessing temporal trends of diseases at both global and regional levels. Leveraging the most recent information from the 2023 GBD report, this research thoroughly assesses the prevalence of MM in Asia. It examines the distribution patterns across diverse genders, age groups, risk factors, and nations with varying levels of the Socio-demographic Index (SDI), in addition to developing mathematical models to forecast future trends extending to 2050. The research findings are anticipated to elucidate the true burden of MM in Asia, identify high-risk populations and key drivers, and provide forward-looking, evidence-based support for cancer prevention and control planning, clinical resource allocation, and public health policy formulation in the region over the next three decades.
Method
Study Population and Data Collection
The 2023 GBD study provides extensive epidemiological data encompassing 204 countries and territories, covering 371 diseases and injuries. The data sources include surveys, censuses, vital registration systems, demographic surveillance, and other health-related datasets. Standardized statistical modeling methods are utilized to correct potential biases, with specific data accessible through the online platform ( https://vizhub.healthdata.org/gbd-results ). The GBD Study estimates MM burden across 204 countries and territories, including all major Asian countries and regions. Specifically, GBD provides national-level estimates for China, India, Japan, South Korea, and individual Southeast Asian countries (Indonesia, Thailand, Vietnam, Philippines, Malaysia, etc). For China and India, GBD also provides subnational estimates at the provincial/state level. The integrated modeling framework DisMod-MR 2.1 is employed to standardize and harmonize data from various sources of differing quality, ensuring the reliability and comparability of estimates. The GBD data received approval from the Institutional Review Board of the University of Washington School of Medicine. 8 This study constitutes a secondary analysis of GBD data and does not involve individual subject information, thus negating the need for additional ethical approval or informed consent.
Statistical Analysis
In this study, we selected the annual number of incident cases, prevalent cases, disability-adjusted life years (DALYs), and their corresponding age-standardized rates (ASR) per 100,000 population from 48 Asian countries as the primary indicators to assess the disease burden of primary malignant tumors. The ASR specifically encompasses the age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized disability-adjusted life year rate (ASDR). All estimates are presented with a 95% uncertainty interval (UI). 9
In order to evaluate the changes over time in the disease burden of MM between 1990 and 2021, this research calculated the estimated annual percentage change (EAPC). An EAPC value exceeding 0 signifies a rising trend in ASR, whereas a value below 0 points to a declining trend. When the 95% confidence interval (CI) encompasses 0, the trend is regarded as stable, indicating that there is no notable temporal change. 10
The Age-Period-Cohort (APC) model serves as an advanced analytical framework that surpasses conventional methods used in studies related to health and socioeconomic development. Rooted in the Poisson distribution, this model improves upon typical descriptive analyses by breaking down the variables of interest into three separate elements: age, period, and cohort. This breakdown allows for an in-depth exploration of long-term disease progression patterns over time. The age effect clarifies how the likelihood of a particular outcome varies with increasing age, thus highlighting the influence of demographic shifts on that outcome. Period effects indicate changes in disease occurrence and DALY rates among different populations, shaped by factors related to human activity, such as improvements in diagnostic technology, screening processes, and early detection measures. The cohort effect relates to the distinctions in traits among individuals born within the same year. Generally, the APC model can be expressed with the formula: Y = log(M) = µ + α(age)i + β(period)j + γ(cohort)k + ε. Additionally, we evaluated the statistical significance of the annual percentage change trends using a Wald chi-square test. 11–13
The Bayesian Age-Period-Cohort (BAPC) model is a widely utilized framework for analyzing and predicting health events or disease burden over time. This method establishes prior distributions and integrates observed data with likelihood functions for inference, effectively addressing uncertainty in estimation while thoroughly considering age, period, and cohort factors. Consequently, it is extensively applied in epidemiological research, disease burden assessment, and the analysis of social health trends. In this study, we employed the BAPC package to forecast the ASIR, ASPR, and ASDR of MM from 2024 to 2050. 12 Projections were specifically developed for East Asians, who exhibited the most comprehensive underlying data series and the steepest, most consistent increase in incidence, thereby providing the clearest signal for forward modeling.
Data analysis and visualization were conducted using R software (version 4.5.1), with a statistical significance threshold established at P < 0.05.
Results
The Burden of MM in the Asian Population Aged 15 and Older (1990–2023)
Based on the GBD data from 1990 to 2023, the burden of MM in Asia among individuals aged 15 years and older has exhibited distinct spatial and temporal shifts. Between 1990 and 2023, the absolute numbers of incidence, deaths, and DALYs increased significantly, particularly in East Asia, Southeast Asia, and certain regions of Central Asia. Figures 1 (Columns 1 to 4) corresponding to DALYs, deaths, incidence, and prevalence illustrate a geographic transition of high-burden areas from high-income regions toward rapidly developing economies. Figure 1 Geographic distribution of MM burden in Asia, 1990–2023. Maps show age-standardized rates per 100,000 population for: ( A ) DALYs, ( B ) deaths, ( C ) incidence, and ( D ) prevalence. The images A, B, C and D are thematic choropleth maps of Asia, each with north at the top, showing different health metrics by ASR (per 100,000). Image A depicts DALYs, with tick values 20, 40, 60; darker shades indicate higher ASR, prevalent in northern Asia, while southern regions are lighter. Image B shows deaths, with tick values 0.5, 1.0, 1.5, 2.0; higher ASR is concentrated in the north. Image C illustrates incidence, with tick values 2, 4, 6; northern and far eastern areas have higher ASR. Image D represents prevalence, with tick values 10, 20, 30, 40, 50; northern and far eastern regions show higher ASR, whereas southern and southeastern areas are lighter. Four choropleth maps of Asia show malignant melanoma ASR per 100,000 for DALYs, deaths, incidence, prevalence. Abbreviations : ASIR, age-standardized incidence rate; ASDR, age-standardized death rate; ASPR, age-standardized prevalence rate; DALYs, disability-adjusted life years; ASR, Age-Standardized Rate; EAPC, Estimated Annual Percentage Change.
Age-standardized rates exhibited divergence: high-SDI regions, such as Japan and South Korea, have stabilized or declined in incidence rates, accompanied by reductions in mortality and DALY rates, indicative of effective prevention and treatment strategies. In contrast, middle- and low-SDI regions have witnessed substantial increases in incidence rates, suggesting a genuine rise in disease risk that transcends demographic changes. East Asia, particularly China, has emerged as the fastest-growing hotspot, with absolute burdens in 2023 ranking among the highest in Asia. The burden of MM has increased most rapidly in East Asia, which has emerged as the fastest-growing hotspot on the continent. Country-level estimates within East Asia (see Supplementary Table S1 ) indicate that this regional trend is predominantly driven by mainland China, which accounted for approximately 72% of all incident melanoma cases in the region in 2023. While age-standardized incidence rates have risen across China, Japan, and South Korea from 1990 to 2023, the absolute number of cases has increased most steeply in China. In contrast, neighboring countries with high SDI have exhibited more favorable trajectories in terms of mortality and DALY. The maps visually underscore the eastward and southward expansion of high DALY and mortality burdens, alongside the widening zones of incidence and prevalence throughout East and Central Asia.
Quantitatively, the absolute number of incident cases in Asia increased from approximately 8,000 in 1990 to over 28,000 in 2023. East Asia accounted for the majority of this increase, with incident cases rising from 4,657 to 16,593, deaths from 2,835 to 5,823, and DALYs from 98,386 to 157,595. In contrast, the growth of absolute cases in other sub-regions was more modest, underscoring the eastward concentration of the burden. All reported EAPC trends had 95% UIs excluding zero, indicating statistically significant changes over time ( Supplementary Table S1 ).
Temporal and Spatial Variations in the Burden of MM in Asia (1990–2023)
Temporal and Spatial Variations in the Burden of Malignant Melanoma in Asia (1990–2023) Figure 2 illustrates the distinct burden of MM among Asia’s population aged 15 years and older across four metrics: DALYs ( Figure 2A ), deaths ( Figure 2B ), incidence ( Figure 2C ), and prevalence ( Figure 2D ). The absolute numbers for all indicators have risen substantially, with age-standardized rates showing regional divergence. DALYs ( Figure 2A ) stabilized in rate after 2010; however, absolute counts surged to nearly 300,000 in 2023, predominantly driven by East Asia. Similarly, deaths ( Figure 2B ) increased from fewer than 15,000 to approximately 25,000, while the age-standardized mortality rate declined. The incidence ( Figure 2C ) exhibits rising rates in East and Southeast Asia post-2010, contrasting with a peak and subsequent decline in Central Asia after 1990. Prevalence ( Figure 2D ) grew nearly fourfold to 200,000 cases, with increasing age-standardized rates in East and Southeast Asia indicating both higher incidence and prolonged survival. In summary, Asia’s burden of MM reflects rapid absolute growth, divergent trends in standardized rates, and regional variations influenced by aging, ultraviolet exposure, and uneven advancements in healthcare, as clearly depicted in Figure 2 . Figure 2 Trends in MM by age group and region, 1990–2023. Stacked area charts display the contribution of five sub-regions (East Asia, South Asia, North Africa and Middle East, Southeast Asia, and Central Asia) to the total burden. The left column shows age-standardized rates (ASR) per 100,000 population, and the right column shows the absolute number of cases or events. ( A ) DALYs; ( B ) Deaths; ( C ) Incidence; ( D ) Prevalence. The image contains four stacked area charts labeled A to D, each with two graphs showing trends from 1990 to 2023. Each panel includes an age-standardized rate per 100,000 (ASR) and an absolute number chart. Panel A shows Disability-Adjusted Life Years (DALYs), with ASR declining slightly while absolute numbers rise to nearly 300,000 by 2023, driven by East Asia. Panel B depicts deaths, with ASR decreasing but numbers increasing to about 25,000. Panel C illustrates incidence, with rising rates in East and Southeast Asia, peaking post-2010. Panel D shows prevalence, growing nearly fourfold to 200,000 cases. Regions are color-coded: Central Asia, North Africa and Middle East, East Asia, Southeast Asia and South Asia. The charts highlight regional contributions, with East Asia showing significant growth across all metrics. The panels collectively illustrate the burden of malignant melanoma, with incidence and prevalence rising alongside deaths and DALYs. Stacked area charts show trends in malignant melanoma by region from 1990 to 2023 across four metrics. Abbreviations : ASIR, Age-standardized Incidence Rate; ASPR, Age-standardized Prevalence Rate; ASDR, Age-standardized DALY Rate; ASMR, Age-standardized Mortality Rate; DALYs, Disability-adjusted Life Years.
Age-Structured Transition of MM Burden Across Asia
Figures 3 and 4 collectively illustrate the age-structured transition of MM in Asia. Throughout all sub-regions, the burden has shifted from the 45–64 age group in 1990 to individuals aged 65 and older by 2023, with East Asia exhibiting the most pronounced aging trends ( Figure 3 ). In East Asia, the contribution of the 75+ age group to prevalence, mortality, and DALYs has increased most steeply. Age-specific trends over time ( Figure 4 ) indicate a progressive rightward shift rather than a uniform increase across all age groups. From 1990 to 2023, incident cases in East Asia have risen nearly fourfold, compared to approximately twofold in Southeast Asia, reflecting both the aging population and increasing incidence rates. Figure 3 Age-specific distribution of MM burden across Asian sub-regions, 1990 and 2023. Stacked bars show the contribution of each age group to total prevalent, incidence, death cases and DALYs. ( A ) DALYs; ( B ) Deaths; ( C ) Incidence; ( D ) Prevalence. Four panels labeled A, B, C and D display MM burden across five Asian subregions. Each panel covers one metric: A shows disability-adjusted life years, B shows deaths, C shows incidence and D shows prevalence. Within each panel, the left block represents 1990 and the right block represents 2023. The vertical axis lists five subregions: North Africa and Middle East, Southeast Asia, Central Asia, South Asia and East Asia. The horizontal axis spans percentage from 0 to 100, showing each age group′s share of total burden. The legend maps gradient intensity to age groups ranging from 25-29 years through 95 plus years, where higher intensity indicates greater percentage contribution. In 1990, middle age bands around 45 to 64 years dominate across most subregions. By 2023, older age bands from 65 years and above show notably higher shares, particularly in East Asia across panels A, B and D. Central Asia and South Asia show comparatively smaller shifts between the two years. Age-specific MM burden in Asia: 1990 & 2023 heatmaps for DALYs, deaths, incidence, prevalence. Abbreviations : ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; ASDR, age-standardized DALY rate; DALYs, disability-adjusted Life Years. Figure 4 Temporal shift in age composition of MM burden in East Asia, 1990–2023. Lines indicate the ASPR, ASIR, ASMR and ASR of DALYs contributed by different age groups. ( A ) DALYs; ( B ) Deaths; ( C ) Incidence; ( D ) Prevalence. The image features eight mixed bar and line graphs labeled A, B, C and D, each with two graphs, showing multiple myeloma burden by age in Asia. Age groups range from 0-4 to 95+ years on the horizontal axis. The left vertical axis displays counts (DALYs, deaths, incidence, prevalence), while the right shows rates per 100,000 population. Graph A focuses on DALYs, Graph B on deaths, Graph C on incidence and Graph D on prevalence. Bars represent different regions like East Asia and Central Asia, with a legend for regions. Lines with shaded bands indicate uncertainty intervals. Trends show increased burden with age, especially in older groups. East Asia has the highest rates in most metrics, with notable peaks in the 75+ age group and steep increases. The graphs highlight regional differences, with East Asia generally showing higher values than other regions. Eight mixed bar and line graphs showing multiple myeloma burden by age group in Asia. Abbreviations : ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; DALYs, disability-adjusted life years; ASR, Age-Standardized Rate.
Age-Period-Cohort Analysis of MM Burden in East Asia (1990–2023)
Figure 5 presents the APC analysis of MM burden in East Asia, the region with the highest MM burden in Asia, by deconstructing temporal trends into period, cohort, and age effects. Figure 5A (DALYs), Figure 5B (deaths), Figure 5C (incidence), and Figure 5D (prevalence) reveal distinct epidemiological dynamics. The period effects (top row) indicate a consistent increase in the burden of MM across successive calendar periods. Age-standardized incidence rose by approximately 0.04 to 0.05 per 100,000 per year, which corresponds to a near doubling of the baseline rate from 1990 to 2023. This increase reflects both a genuine rise in incidence and enhanced detection capabilities over time. The cohort effects (middle row) illustrate a significant generational increase in risk. Compared to individuals born around 1920, those born in the early 1960s exhibit a relative risk of approximately 1.5 for developing MM, while later birth cohorts (1970s-1980s) show relative risks of 2.0 or higher. This trend indicates a clear cohort-driven escalation in lifetime risk, likely attributable to cumulative ultraviolet exposure, Westernized lifestyles, and patterns of sun exposure in early life. Notably, there is no evidence of a plateau in the most recent birth cohorts, suggesting that incidence will continue to rise without enhanced primary prevention measures. The age effects (bottom row) align with expected biological patterns, showing rates that rise sharply after age 50, peaking in the over 85-year age group, particularly for prevalence, which reflects the cumulative nature of the disease over the life course. The age effects (bottom rows) illustrate the biological progression of MM, with rates climbing steeply after middle age (50–64 years) and peaking in the oldest groups (85+ years). This pattern is most pronounced in prevalence ( Figure 5D ), where cumulative incidence over a lifetime is evident. The APC analysis underscores that East Asia’s high MM burden is driven by a combination of increasing period-specific risk, greater susceptibility in younger cohorts, and the demographic effect of an aging population. Figure 5 APC analysis of MM burden in East Asia, 1990–2023. Top row: period effects showing calendar-time trends in age-standardized rates. Middle row: cohort effects expressed as relative risk by birth year. Bottom row: age effects showing rate increase with advancing age. Each column corresponds to: ( A ) DALYs, ( B ) deaths, ( C ) incidence, ( D ) prevalence. Period and cohort effects indicate a steady rise in burden, particularly among recent birth cohorts, while age effects peak in the over 85-year group. Four graphs labeled A, B, C and D depict MM burden in East Asia from 1990 to 2023, showing period, cohort and age effects. The top row graphs plot calendar years against age-standardized rates per 100,000, revealing an upward trend across age groups. The middle row graphs plot birth year cohorts against relative risk, with recent cohorts showing increased risk, especially post-1960. The bottom row graphs plot age groups against rates per 100,000, with rates peaking in the 85+ age group. Panel A shows DALYs, panel B deaths, panel C incidence and panel D prevalence, with the most pronounced age effect in prevalence. Period and cohort effects rise across all panels. Legends map lines to specific age groups or cohorts. Multi-line graphs showing APC analysis of MM burden across DALYs, deaths, incidence and prevalence in East Asia. Abbreviations : ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; DALYs, disability-adjusted life years; ASR, Age-Standardized Rate; APC, Age-Period-Cohort analysis.
Projected East Asian Trends of MM Burden (2024–2050)
Based on the BAPC modeling results for East Asia (2024–2050), Figure 6A – D present projections for the age-standardized burden of MM across four key metrics: DALYs ( Figure 6A ), deaths ( Figure 6B ), incidence ( Figure 6C ), and prevalence ( Figure 6D ). The projections reveal distinct and interrelated patterns. The age-standardized incidence rate ( Figure 6C ) is anticipated to rise from 0.85 per 100,000 in 2024 to 1.45 in 2050, while the prevalence ( Figure 6D ) is expected to increase correspondingly from 5.46 to 9.29. In contrast, the age-standardized mortality rate ( Figure 6B ) is projected to remain relatively stable at approximately 0.39–0.40 throughout the forecast period. The age-standardized DALY rate ( Figure 6A ) indicates a modest decline in the central estimate. All four panels demonstrate a notable widening of the 95% uncertainty intervals as projections extend toward 2050, highlighting the inherent uncertainty associated with long-term forecasting. These trends indicate that, although the risk of developing and living with MM is anticipated to rise in East Asia, the population-level mortality rate may remain stable This stability could reflect advancements in treatment that offset the increasing incidence. The growing predictive uncertainty illustrated in Figures 6A – D emphasizes the sensitivity of these projections to potential future changes in risk exposure, healthcare interventions, and demographic factors. Figure 6 BAPC projections of MM burden in East Asian, 2024–2050. Panels show age-standardized: ( A ) DALY rate, ( B ) mortality rate, ( C ) incidence rate, ( D ) prevalence rate. Central line indicates projected trend; shaded area represents 95%UI, which widens with time. Projections are illustrative scenario envelopes: incidence and prevalence are expected to rise, mortality remains stable, and DALY rates show a modest decline. These forecasts reflect extrapolation of historical trends and are subject to future changes in risk exposure and health system capacity. Image A: Line graph with X axis ′Period′ (1990-2050) and Y axis ′Age std. rate per 100000′ (-10 to 20). Historical data near 10 from 1990 to 2000, declining to 8 by 2020. Post-2024, a solid line trends downward to 2050, with increasing uncertainty bands. Image B: Line graph with X axis ′Period′ (1990-2050) and Y axis ′Age std. rate per 100000′ (-0.5 to 1.5). Historical data near 0.5 in 1990s, declining to 0.4 by 2020. Post-2024, solid line remains near 0.4 to 2050, with widening uncertainty bands. Image C: Line graph with X axis ′Period′ (1990-2050) and Y axis ′Age std. rate per 100000′ (-2 to 6). Historical data rises from 0.5 in 1990 to 1.0 by 2020. Post-2024, solid line rises to 1.5 by 2050, with widening uncertainty bands. Image D: Line graph with X axis ′Period′ (1990-2050) and Y axis ′Age std. rate per 100000′ (-10 to 30). Historical data rises from 1 in 1990 to 6 by 2020. Post-2024, solid line rises to 9 by 2050, with widening uncertainty bands. A set of four line graphs showing projected age standardized burden rates over time. Abbreviations : ASR, Age-Standardized Rate, DALYs, Disability-Adjusted Life Years, UI, uncertainty interval, BAPC, Bayesian Age-Period-Cohort.
Discussion
This study reveals that between 1990 and 2023, the burden of MM among Asia’s population aged 15 and older has demonstrated a complex pattern. This pattern is characterized by a sustained increase in incidence, a gradual decline in age-standardized mortality, and a significant shift toward an older and geographically concentrated distribution of the disease. 14–16 Our analysis indicates that population aging is a significant and likely contributor to the growing burden of MM. This is alongside factors such as changes in UV exposure, lifestyle modifications, advancements in diagnostic capacity, and improved access to treatment. However, a formal decomposition analysis is necessary to quantify the relative contributions of each factor, which exceeds the scope of this ecological study. More critically, the geographic epicenter of this disease burden is experiencing a significant transition: historically high-income regions, such as Japan and South Korea, exhibit relatively stable or declining age-standardized rates. In contrast, the fastest-growing “hotspots” have shifted to middle- and low-SDI regions undergoing rapid socioeconomic transformation, particularly in East Asia. This eastward shift primarily reflects a transition in absolute case numbers, predominantly driven by mainland China, which contributed approximately 72% of East Asia’s incident cases in 2023, rather than a uniform rise in risk across all East Asian population. 17 , 18 This shift is closely associated with increased exposure to ultraviolet radiation, changes in lifestyle, and disparities in the advancements of diagnostic and treatment capabilities. These trends are consistent with previous national and regional analyses, including the rising incidence in China and broader patterns observed in East Asia 17 which supports the credibility of our GBD-based estimates. Several converging mechanisms underlie this transition. First, cumulative UV exposure is increasing not primarily due to changes in stratospheric ozone, but rather as a result of behavioral shifts: the rapid growth of outdoor leisure activities, skiing, beach tourism, and occupational exposure in construction and agriculture across Asia. Although indoor tanning is less prevalent than in the West, it is increasingly being marketed in urban centers in East Asia. Second, the westernization of lifestyle - characterized by greater recreational sun exposure, changing clothing norms, and an urban outdoor culture - has altered exposure patterns, particularly among younger cohorts, which is consistent with the rising cohort effects observed in our APC analysis. Third, improved diagnostic capacity and heightened health-seeking behavior have led to an increased detection of thin and in situ lesions that would have previously remained undocumented, thereby contributing to an element of “diagnostic drift” in the rising incidence.
Asia’s trajectory reflects broader global patterns. Recent global analyses indicate that melanoma incidence is increasing most rapidly in historically low-burden populations, including Hispanic, Asian, and other non-White groups, which often present with more advanced disease at diagnosis. This trend is not limited to Asia; even in resource-constrained and conflict-affected regions outside the high-income Western core, hospital-based series are now documenting significant melanoma caseloads with late-stage presentations. For instance, a retrospective analysis conducted from 2022 to 2025 at Syria’s national cancer center reported a median diagnosis age of 57 years, with a considerable proportion of cases already at advanced stages. This underscores how gaps in diagnostics and health systems exacerbate the apparent burden in lower-SDI populations. 19 In comparison to Australia, Europe, and North America—where the high baseline incidence of skin cancer has been somewhat mitigated by decreasing mortality rates due to organized screening programs and broad access to immunotherapy- Asia is still in an earlier phase of this public health challenge. The incidence of skin cancer is increasing, while significant reductions in mortality are only just beginning to manifest in high-SDI subregions. This indicates that the insights gained from Western primary prevention initiatives, national skin cancer registries, and structured treatment pathways remain highly pertinent. However, these strategies must be adapted to accommodate Asia’s unique tumor biology and the constraints of its healthcare systems.
The burden of MM exhibits a distinct nonlinear relationship with socioeconomic development. This relationship highlights the dual impact of advancement: while the incidence of MM has increased due to heightened risk exposure and improved detection capabilities, mortality rates have concurrently declined in several high-SDI settings. Innovations in molecular diagnostics, targeted therapies (such as BRAF/MEK inhibitors), and immune checkpoint inhibitors have significantly transformed the management of melanoma in high-income contexts. 7 However, as this study focuses on an ecological analysis of modeled data, we cannot attribute the observed declines in mortality to any specific therapeutic modality. These advancements represent plausible contributors that require validation through country-level treatment utilization studies. 15 , 16 The anticipated ongoing rise in age-standardized incidence rates, in contrast to stable or slightly decreasing mortality rates, highlights this evolving dynamic. This divergence constitutes a fundamental aspect of the shifting burden of MM in Asia and underscores a crucial focus for future public health initiatives: addressing the increasing incidence while maintaining control over mortality. 15 , 20
However, this study has several limitations. First, the estimates rely on modeled GBD data, which may underrepresent the true burden of cancer in regions with inadequate cancer registration. 2 Second, the analyses do not differentiate between melanoma subtypes, which could obscure significant etiological and prognostic variations. 5 Third, long-term projections rely on the extrapolation of past trends and are inherently subject to significant uncertainty, as evidenced by the widening of predictive intervals. The accuracy of these projections may be influenced by future developments in prevention, screening, therapy, or environmental factors. 21 Fourth, BAPC projections assume continuity of historical trends and cannot anticipate disruptive future interventions, such as new national screening programs or breakthrough prevention policies. Consequently, they should be interpreted as upper- and lower-bound planning scenarios rather than precise forecasts. Furthermore, as an ecological analysis of modeled data, this study can identify population-level associations but cannot establish causal relationships between specific risk factors or treatments and observed outcomes. To validate these findings, country-level studies with individual patient data are necessary.
In summary, MM has emerged as a significant and growing public health challenge in Asia, driven by the dual forces of an aging population and rapid socioeconomic development. The region is now characterized by a distinctive epidemiological transition: age-standardized incidence rates are steadily climbing, particularly in East Asian economies that are undergoing transformation, while age-standardized mortality rates have begun to stabilize or decline in certain contexts. This pattern reflects both increasing risk exposure and advances in clinical management. Such dynamics underscore the urgent need for a dual-track public health response tailored to Asia’s diverse and evolving disease landscape.
First, prioritizing and scaling primary prevention is essential, particularly in high-growth regions such as East and Southeast Asia. A comprehensive, population-wide sun-safety education program—targeting both occupational and recreational ultraviolet (UV) exposure—should serve as the cornerstone of these prevention efforts. This program should promote consistent sunscreen use, protective clothing, and the avoidance of peak sun hours, while also addressing cultural norms that may favor intentional tanning. 22 Such initiatives must be culturally adapted, sustained through multimedia campaigns, and integrated into school curricula and workplace health programs. 23 Environmental and policy measures, such as the provision of shade in public spaces and the regulation of artificial UV sources (eg, tanning beds), can further reinforce these behaviors. 24 Without effective primary prevention, the underlying risk of MM will continue to rise, undermining long‑term control.
Second, health systems must ensure equitable access to early detection, advanced diagnostics, and effective treatment. Despite improvements in prevention, a residual burden of MM will persist, necessitating robust secondary and tertiary prevention strategies. In high-income Asian countries, enhancing structured screening for high-risk groups—such as individuals with fair skin, numerous nevi, or a family history of skin cancer—can facilitate earlier diagnosis. 25 In middle- and low-income settings, where diagnostic infrastructure may be limited, task-shifting (training primary care providers in dermoscopy) and tele-dermatology can help bridge gaps in specialist access. 26 Crucially, advances in molecular diagnostics and targeted therapies, such as BRAF/MEK inhibitors and immune checkpoint inhibitors, provide substantial survival benefits in high-income settings. However, these agents remain financially prohibitive for the majority of patients in low- and middle-SDI regions. Therefore, a pragmatic, tiered approach is essential. In accordance with the WHO Global Cancer Control Framework, resource-limited settings should prioritize: (i) task-shifting and teledermatology to enhance early detection; (ii) ensuring universal access to surgical excision and, where feasible, sentinel lymph node assessment; and (iii) providing chemotherapy and palliative care as recommended in the WHO Essential Medicines List, serving as the backbone of systemic treatment. Access to high-cost targeted and immune therapies can be gradually expanded through regional pooled procurement, public–private pricing agreements, and referral to designated tertiary centers. 27 , 28 Recent advancements in immune-related risk stratification, tumor immune heterogeneity, and personalized treatment offer a more comprehensive framework for understanding the potential differences in outcomes. However, in the absence of country-specific data regarding immunotherapy coverage and individual treatment patterns, 29 , 30 it is inappropriate to directly attribute regional mortality trends to any specific treatment modality. Disparities in treatment access threaten to widen outcome gaps, as the rising incidence of MM in under-served populations could outpace the survival gains achieved in well-resourced areas.
Achieving this balance—curbing incidence through prevention while improving outcomes through equitable care—requires sustained investment and cross-sector collaboration. Effective, real-time surveillance systems are necessary to monitor trends in burden, risk factors, and the coverage of interventions. Resource allocation should be informed by local epidemiological data and customized to regional priorities, such as primary prevention in high-incidence areas and the enhancement of diagnostic capacity in underserved regions. 31 , 32 Furthermore, regional networks for data sharing, training, and research can accelerate the adoption of best practices and foster innovation in prevention and care delivery. 28
Ultimately, reversing the rising trajectory of MM in Asia will depend on the capacity of health systems to simultaneously address the upstream drivers of risk while ensuring that advancements in diagnosis and therapy benefit all populations. A comprehensive, equity-focused strategy that combines prevention, early detection, and treatment is essential to mitigate the future human and economic burden of malignant melanoma across the continent.
Conclusion
This study highlights that malignant melanoma poses a significant and escalating public health challenge in Asia, characterized by a rising incidence in rapidly developing East Asia and stabilizing or declining mortality in higher-SDI regions. The geographic epicenter has shifted from high-income to lower-resource regions, in the context of population aging, increasing UV exposure, and uneven access to diagnostics and treatment. Immediate action should prioritize sun-safety education among outdoor workers and school-aged populations, alongside targeted early detection for high-risk groups (those over 50 years of age and with a high nevus burden) utilizing primary care and teledermatology, particularly in China and urbanizing Southeast Asia. Lower-resource regions should initially focus on establishing basic diagnostic and surgical capacities before advancing to more complex therapies. These phased efforts aim to narrow the mortality-to-incidence gap by 2050, acknowledging that long-term projections remain scenario envelopes with increasing uncertainty. Progress should be tracked through pragmatic, registry-based indicators, specifically the proportion of cases diagnosed at advanced stages and the mortality-to-incidence ratio, to ensure that incidence control is accompanied by equitable survival gains.
Acknowledgments
We acknowledge the BioRender ( https://www.biorender.com/ ) for their illustration services.
Data Sharing Statement
Data resources from the GBD study 2023 could be accessed online through the Global Health Data Exchange (GHDx) query tool ( http://ghdx.healthdata.org/gbd-results-tool ).
Ethics Statements
According to Article 32 of the Ethical Review Measures for Life Science and Medical Research Involving Human Beings of the People’s Republic of China, the data used in this study will not cause any form of harm to human beings, nor will it touch sensitive personal privacy or trade secrets, so the ethical review can be exempted. In addition, the database used in this study was publicly available and legally available.
Disclosure
The authors declare no competing interests in this work.
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