Ovarian cancer in Asia: incidence, mortality in 2022, and future projections to 2050.

This study was conducted as a systematic secondary analysis of publicly available ovarian cancer burden estimates produced by the IARC. New cases of ovarian cancer (C56) and associated deaths were extracted from the GLOBOCAN 2022 database, which employs the International Classification of Diseases, 10th Revision (ICD‑10), and provides coverage for 185 countries and territories ( https://gco.iarc.fr/) [ 1 ]. GLOBOCAN 2022 generates country-specific cancer incidence and mortality estimates using the best available data from population-based cancer registries and vital registration systems. Where high-quality national data are unavailable, estimates are derived using validated modeling approaches based on regional data, mortality-to-incidence ratios, and age-specific rates [ 13 ]. Population denominators for 2022 were obtained from the World Bank ( https://data.worldbank.org/ ). The HDI, a composite measure of life expectancy, education, and per capita income developed by the United Nations Development Programme (UNDP), was used to classify countries into four tiers: very high (≥ 0.800), high (0.700–0.799), medium (0.550–0.699), and low (< 0.550) [ 12 ]. Country-level HDI values for the 47 Asian countries included in this study are provided in Supplementary Table S1. Detailed methodologies and data sources for cancer estimates are described in previous publications [ 14 ]. Incidence reflects the estimated number of newly diagnosed ovarian cancer cases within a defined period and geographic area, typically expressed as annual counts or rates per 100,000 person-years, providing an estimate of the population’s risk and enabling regional and international comparisons. These data are systematically collected by cancer registries and synthesized by IARC using standardized modeling approaches. Mortality denotes estimated deaths attributable to ovarian cancer in a given region and period, usually reported per 100,000 person-years, and is derived from national vital statistics and IARC modeling procedures. We analyzed temporal trends in the incidence and mortality of ovarian cancer using both all-age, ASR and annual change rates, calculated using age-standard population data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD, http://ghdx.healthdata.org/gbd-results-tool ) 2023. The GBD 2023 offers an updated, comprehensive estimate of epidemiological data on 371 diseases and injuries, as well as 88 risk factors, spanning 204 countries and territories from 1990 to 2023 [ 15 , 16 ]. Additionally, trends in ovarian cancer burden were explored across 16 age groups: 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, 85–89, and 90–94 years. An APC model was applied to analyze incidence and mortality trends by age, period, and birth cohort. This framework disentangles age-related biological effects from temporal influences associated with social and technological changes and is widely used in descriptive epidemiology of chronic diseases, including cancer [ 17 ]. A log-linear Poisson regression was fitted on a Lexis diagram to estimate age, period, and cohort effects. Owing to the exact linear dependency among these components (cohort = period − age), the APC identification problem was addressed by deriving estimable functions without imposing arbitrary constraints. Analyses were conducted in R using established, publicly available methods [ 18 ]. Input data consisted of GBD 2023 estimates of ovarian cancer deaths and corresponding population data. The analysis included 16 age groups (15–19 to 90–94 years) and 21 partially overlapping 10-year birth cohorts (Supplementary Table S2). Model outputs included net drift (overall annual percentage change in mortality), local drift (age-specific temporal trends), age effects, period effects, and cohort effects, expressed as relative risks. The periods 2003–2007 and cohorts 1949–1957 were used as reference categories. Statistical significance of trends was assessed using Wald chi-squared tests. Relative risks for periods and cohorts were calculated as ratios of age-specific mortality rates relative to the reference period or cohort, with net drift incorporated. The choice of reference categories did not affect interpretation. The 88 risk factors in GBD 2023 are categorized into environmental, occupational, behavioral, and metabolic groups [ 15 , 16 . The estimation process for these risk factors follows a comparative risk assessment framework comprising six steps, as outlined in the GBD 2023 risk factor summary website ( https://www.healthdata.org/research-analysis/diseases-injuries/factsheets-overview/about-risk-factor ). We analyzed the contribution of the risk factors to ovarian cancer mortality in 2022, quantifying country-specific population-attributable fractions (PAFs). According to the GBD 2023 comparative risk assessment framework, only two risk factors—high body mass index (BMI, defined as BMI > 25 kg/m²) and asbestos exposure—are currently modelled as attributable to ovarian cancer mortality; therefore, only these factors were included in the present analysis. In addition, GBD 2023 provides risk-attributable estimates for ovarian cancer in terms of deaths and disability-adjusted life years, but not incidence. Accordingly, mortality-based PAFs were used as proxies to estimate the population-level preventable burden in this study. Projections of ovarian cancer incidence and mortality from 2022 to 2050 were obtained using the CANCER TOMORROW tool developed by the IARC ( https://gco.iarc.fr/tomorrow/en ), which is based on GLOBOCAN 2022 estimates covering 36 cancer types across 185 countries and territories [ 1 ]. The CANCER TOMORROW projections apply age-specific incidence and mortality rates observed in the baseline year of 2022 to future population estimates derived from the United Nations (UN) World Population Prospects, thereby estimating future numbers of new cases and deaths under different assumptions. The primary projection scenario assumes that national age-specific cancer rates remain constant over time (0% annual change) and that projected changes in cancer burden are driven solely by population growth and ageing. In addition, to explore the potential impact of changing epidemiological trends, hypothetical alternative scenarios assuming annual increases or decreases of ± 1%, ± 2%, and ± 3% in incidence and mortality rates were examined. These projections rely on the assumptions that baseline rates in 2022 are representative of current risk and that UN population forecasts accurately capture demographic changes between 2022 and 2050 [ 19 ]. The present study did not develop independent forecasting models, but rather synthesized and compared existing CANCER TOMORROW outputs across countries, regions, and HDI categories. Age-standardized incidence (ASIR) and mortality rates (ASMR) per 100,000 person-years were directly extracted from GLOBOCAN 2022, where they are calculated using direct standardization based on the Segi–Doll World standard population [ 20 , 21 ]. The authors did not independently recalculate standardized rates from raw age-specific data. Subgroup analyses were conducted by age group and by country. Secondary analytical steps undertaken in this study included: (1) stratification of incidence and mortality by age group (< 50 years and ≥ 50 years), with 50 years selected as the cut-point based on the observed age-specific increase in incidence and mortality and its common use as an epidemiological threshold [ 22 – 24 ]; (2) country-level comparisons of incidence and mortality patterns across HDI categories; (3) assessment of associations between HDI and age-specific ASIR and ASMR using Spearman’s correlation; and (4) synthesis of cross-HDI heterogeneity in current and future ovarian cancer burden across Asia. Statistical analyses were performed in R (v4.3.3), with significance defined as P  < 0.05.

In 2022, Asia accounted for an estimated 178.2 thousand newly diagnosed ovarian cancer cases, representing 54.9% of the global burden (Table  1 ). Ovarian cancer was among the six most frequently diagnosed malignancies in 23 of the 47 Asian countries analyzed (Fig.  1 A). The ASIR for the region was 6.2 per 100,000 women (Table  1 ; Fig.  1 B). Table 1 Incidence and mortality of ovarian cancer by continents, 2022. The data sources were obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate Region ASIR New cases Proportion ASMR Deaths Proportion Africa 5.3 25,760 7.9 4.0 18,024 8.7 Latin America and the Caribbean 5.7 24,072 7.4 3.6 15,911 7.7 Northern America 7.5 24,484 7.5 3.8 15,554 7.5 Europe 9.3 69,472 21.4 5.0 46,232 22.3 Oceania 8.1 2592 0.8 4.5 1688 0.8 Asia 6.2 178,223 54.9 3.7 109,547 52.9 World 6.7 324,603 100.0 3.9 206,956 100.0 Incidence and mortality of ovarian cancer by continents, 2022. The data sources were obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate Fig. 1 Incidence and mortality of ovarian cancer in Asia A Country-specific rankings of incidence and mortality B Country-level ASIR and ASMR of ovarian cancer. Data was obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate. ASMR, age-standardized mortality rate Incidence and mortality of ovarian cancer in Asia A Country-specific rankings of incidence and mortality B Country-level ASIR and ASMR of ovarian cancer. Data was obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate. ASMR, age-standardized mortality rate An estimated 109.5 thousand deaths from ovarian cancer occurred in Asia during the same year, comprising 52.9% of global mortality (Table  1 ). The disease ranked within the top six causes of cancer death in 30 of 47 countries (Fig.  1 A), with an ASMR of 3.7 per 100,000 (Table  1 ; Fig.  1 B). Globally, the proportion of ovarian cancer cases and deaths increases steadily with age, peaking in women aged 55–64 years, while the share among younger women (< 50 years) remains relatively low (Fig.  2 A). In contrast, Asia shows a relatively greater contribution from middle-aged groups, reflecting differences in age structure and cohort composition, with a sharp increase after age 50 (Fig.  2 A). Fig. 2 Age distribution and APC analysis of ovarian cancer incidence and mortality, 1993–2022 A Changes in the age-specific distribution of ovarian cancer new cases (left panel) and deaths (right panel) across 16 age groups from 1993 to 2022 B APC model–derived local drifts in ovarian cancer incidence (left panel) and mortality (right panel) by age group, expressed as annual percentage change (%/year) with 95% confidence intervals (CIs) C Age effects shown as fitted longitudinal age-specific incidence (left panel) and mortality (right panel) rates (per 100,000 person-years) with 95% CIs D Period effects expressed as incidence (left panel) and mortality (right panel) relative risks by period, referenced to 2003–2007 and adjusted for age and nonlinear cohort effects E Cohort effects expressed as incidence (left panel) and mortality (right panel) relative risks by birth cohort, referenced to 1949–1957 and adjusted for age and nonlinear period effects. CI, confidence interval. Data was obtained from the GBD 2023 database Age distribution and APC analysis of ovarian cancer incidence and mortality, 1993–2022 A Changes in the age-specific distribution of ovarian cancer new cases (left panel) and deaths (right panel) across 16 age groups from 1993 to 2022 B APC model–derived local drifts in ovarian cancer incidence (left panel) and mortality (right panel) by age group, expressed as annual percentage change (%/year) with 95% confidence intervals (CIs) C Age effects shown as fitted longitudinal age-specific incidence (left panel) and mortality (right panel) rates (per 100,000 person-years) with 95% CIs D Period effects expressed as incidence (left panel) and mortality (right panel) relative risks by period, referenced to 2003–2007 and adjusted for age and nonlinear cohort effects E Cohort effects expressed as incidence (left panel) and mortality (right panel) relative risks by birth cohort, referenced to 1949–1957 and adjusted for age and nonlinear period effects. CI, confidence interval. Data was obtained from the GBD 2023 database In Asia, net annual changes indicated a persistent increase in incidence across all age groups, while mortality increased modestly, with greater uncertainty at older ages (Fig.  2 B; Supplementary Table S3). In contrast, global trends showed age-dependent divergence, with declining incidence and mortality among middle-aged and older adults (Fig.  2 B; Supplementary Table S3), suggesting improvements in age-specific risks globally. Age effects showed a strong increase in both incidence and mortality with advancing age in Asia and globally. In Asia, incidence rose steadily from adolescence to late adulthood, peaking at ages 65–69, while mortality continued to increase into the oldest age groups (Fig.  2 C; Supplementary Table S4). Globally, age-specific rates were consistently higher than those observed in Asia across most age groups (Fig.  2 C; Supplementary Table S4). Period effects in Asia were largely stable before 2008, with 2003–2007 as the reference period (incidence rate ratio [IRR] = 1.00, 1.00–1.00) (Fig.  2 D; Supplementary Table S5). Thereafter, incidence increased to 1.18 (1.16–1.21) in 2018–2022 (Fig.  2 D), with a similar upward trend observed for mortality. In contrast, global period effects declined modestly after 2007 (Fig.  2 D; Supplementary Table S5). Cohort effects showed contrasting patterns between Asia and the world. In Asia, earlier birth cohorts had lower risks relative to the 1949–1957 reference cohort, (Fig.  2 E; Supplementary Table S6), whereas risks increased progressively among more recent cohorts, reaching 1.39 (1.23–1.57) for incidence in 1999–2007 (Fig.  2 E). Globally, cohort patterns followed a U-shaped distribution, with elevated risks in early and recent cohorts and lower risks in mid-20th-century cohorts (Fig.  2 E; Supplementary Table S6). The very high HDI region exhibited the highest ASIR at 7.4 per 100,000 females, whereas the low HDI region showed the lowest incidence at 4.2 per 100,000 females (Supplementary Figure S1A). No significant overall correlation was observed between HDI level and ASIR (Supplementary Figure S1B). Similarly, the ASMR was highest in very high HDI regions (4.5 per 100,000 females), followed by high HDI regions (4.3 per 100,000 females) (Supplementary Figure S1A), with no significant overall association between HDI and ASMR (Supplementary Figure S1B). Further age-stratified analysis revealed that no significant association was identified between ASIR ( r  = 0.198, P  = 0.192) or ASMR ( r = -0.209, P  = 0.167) and HDI among younger individuals. In contrast, among women aged ≥ 50 years, ASIR ( r  = 0.425, P  = 0.004) and ASMR ( r  = 0.309, P  = 0.039) were positively correlated with HDI (Fig.  3 ). Fig. 3 Age-standardized rates for incidence and mortality of ovarian cancer in Asian countries grouped by Human Development Index A Bar chart illustrating ASIR and ASMR (per 100,000) of ovarian cancer across HDI groups, stratified by age in Asia B Correlation between ASIR and ASMR (per 100,000) and HDI, stratified by age. Data was obtained from the GLOBOCAN database in 2022. HDI, Human Development Index; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate Age-standardized rates for incidence and mortality of ovarian cancer in Asian countries grouped by Human Development Index A Bar chart illustrating ASIR and ASMR (per 100,000) of ovarian cancer across HDI groups, stratified by age in Asia B Correlation between ASIR and ASMR (per 100,000) and HDI, stratified by age. Data was obtained from the GLOBOCAN database in 2022. HDI, Human Development Index; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate Among very high and high HDI countries, Brunei Darussalam exhibited the highest ASIR (13.2 per 100,000 females), followed by the Philippines (11.7 per 100,000), Georgia (10.6 per 100,000), and Singapore and Malaysia (10.3 per 100,000 each) (Table  2 , Supplementary Figure S2). Several of these nations also showed elevated ASMRs. Specifically, the Philippines had the highest mortality rate (7.5 per 100,000 females), followed by Brunei Darussalam (6.9 per 100,000), Maldives (6.5 per 100,000), Malaysia (6.5 per 100,000), and Georgia (6.4 per 100,000) (Supplementary Figure S2). Table 2 Incidence and mortality of ovarian cancer from Asia countries, 2022. The data sources were obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate. Countries are ordered by HDI values from high to low Region ASIR New cases ASMR Deaths Singapore 10.34 479 5.42 296 United Arab Emirates 5.4 105 4 61 Korea, Republic of 6.45 2799 2.55 1441 Japan 8.74 10,693 2.97 5301 Israel 7.65 492 4.85 353 Bahrain 5.11 29 4.18 21 Qatar 5.76 30 4.48 19 Saudi Arabia 3.32 426 2.37 271 Türkiye 6.88 3855 4.8 2848 Kuwait 5.51 83 4.28 55 Brunei Darussalam 13.16 33 6.92 17 Oman 3.49 50 2.69 34 Georgia 10.61 390 6.39 261 Malaysia 10.29 1838 6.49 1167 Thailand 7.4 4144 4.21 2644 Kazakhstan 7.7 931 5.08 634 China 5.68 61,060 2.64 32,646 Armenia 4.99 130 3.85 110 Sri Lanka 8.16 1299 5.41 911 Iran, Islamic Republic of 4.21 2027 2.67 1228 Maldives 8.13 17 6.52 12 Azerbaijan 5.94 390 3.85 256 Turkmenistan 4.47 142 3.37 104 Mongolia 5.68 98 4.07 69 Jordan 5.74 240 4.11 159 Korea, Democratic People Republic of 5.9 1123 4.27 807 Uzbekistan 4.78 856 3.3 562 Viet Nam 2.47 1534 1.57 1003 Lebanon 6.7 247 4.61 171 Indonesia 9.75 15,130 6.24 9673 Philippines 11.73 6453 7.46 4073 Kyrgyzstan 7.27 241 4.76 156 Bhutan 5.64 20 4.12 14 Tajikistan 1.77 77 1.46 56 Iraq 6.69 1002 5.1 693 Bangladesh 3.3 2846 2.31 1857 India 6.57 47,333 4.64 32,978 Lao People’s Democratic Republic 5.51 184 4.07 125 Myanmar 5.61 1813 3.57 1156 Nepal 4.13 643 3.04 452 Cambodia 5.58 470 4.19 335 Timor-Leste 6.59 35 5.41 25 Syrian Arab Republic 5.1 462 3.48 294 Pakistan 5.63 4987 4.19 3492 Afghanistan 4.2 512 3.49 383 Yemen 2.89 341 2.27 224 Gaza Strip and West Bank 4.22 74 3.35 53 Incidence and mortality of ovarian cancer from Asia countries, 2022. The data sources were obtained from the GLOBOCAN database in 2022. ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate. Countries are ordered by HDI values from high to low Among women younger than 50 years, the ASIR remained relatively low across countries (Supplementary Table S7, Supplementary Figure S3). In contrast, incidence increased sharply among individuals aged ≥ 50 years, particularly in higher HDI settings (Supplementary Figure S3). The highest ASIR in this age group was recorded in Georgia (46.0 per 100,000), followed by the Philippines and Brunei Darussalam (Supplementary Figure S3). A similar pattern was observed for mortality, with ASMRs highest in the Philippines (33.5 per 100,000) and Georgia (32.2 per 100,000) (Supplementary Figure S3), suggesting a positive association between HDI level and disease burden among older women. High body-mass index (BMI) emerged as the leading modifiable risk factor contributing to ovarian cancer mortality across Asia. The population-attributable fraction (PAF) of deaths due to high BMI varied substantially by country, ranging from 0.36% in Nepal to 22.3% in Kuwait, with the highest contributions observed in Middle Eastern countries, including Kuwait (22.3%), Qatar (21.3%), Jordan (20.2%), and the Syrian Arab Republic (19.2%) (Supplementary Figure S4; Supplementary Table S8). In contrast, lower PAFs were observed in South and Southeast Asian countries, including India (4.0%), China (4.9%), and Viet Nam (1.5%) (Supplementary Figure S4; Supplementary Table S8). Occupational exposure to asbestos accounted for a smaller but regionally heterogeneous fraction of deaths, ranging from 0.0003% in the Syrian Arab Republic to 7.5% in Armenia (Supplementary Figure S4; Supplementary Table S8). Overall, high BMI contributed substantially more to ovarian cancer mortality than asbestos across most Asian countries. Achieving a 15.3% reduction in new cases and a 4.8% reduction in deaths by 2050 would require a 2% annual decline in both incidence and mortality rates (Fig.  4 A; Supplementary Table S9). Under the assumption that incidence and mortality rates remain unchanged from 2022, the number of new ovarian cancer cases in Asia is projected to reach approximately 265.9 thousand, with an estimated 183.6 thousand deaths by 2050 (Supplementary Table S9).Under this constant-rate scenario, substantial heterogeneity is anticipated across HDI strata. The low-HDI group is projected to experience the most pronounced increases, with 124.1% more new cases and 137.3% more deaths by 2050 (Supplementary Table S10). In contrast, the very high-HDI group is expected to see more modest increases of 15.2% in incidence and 41.1% in mortality, assuming incidence and mortality rates remain unchanged from 2022 (Fig.  4 B; Supplementary Table S10). Fig. 4 Trends in ovarian cancer incidence and mortality counts (2022–2050) in Asia ( A) , and by Human Development Index group ( B ). The lines from 2022 represent baseline values and projections for 2025–2050 based on GLOBOCAN 2022 forecasts. The scale represents different hypothetical annual change scenarios applied to the 2022 age-specific rates, including a stable-rate scenario (0% annual change) and scenarios assuming annual increases or decreases of ± 1%, ± 2%, and ± 3%. The percentage (%) indicates the relative change in new cases or deaths by 2050, assuming no annual variation from the 2022 baseline. HDI, Human development index Trends in ovarian cancer incidence and mortality counts (2022–2050) in Asia ( A) , and by Human Development Index group ( B ). The lines from 2022 represent baseline values and projections for 2025–2050 based on GLOBOCAN 2022 forecasts. The scale represents different hypothetical annual change scenarios applied to the 2022 age-specific rates, including a stable-rate scenario (0% annual change) and scenarios assuming annual increases or decreases of ± 1%, ± 2%, and ± 3%. The percentage (%) indicates the relative change in new cases or deaths by 2050, assuming no annual variation from the 2022 baseline. HDI, Human development index

This study on ovarian cancer incidence and mortality across Asia underscores a rapidly evolving epidemiologic landscape, identifying countries and regions with disproportionately high burdens when stratified by HDI and age group. Strengthening primary prevention to reduce exposure to modifiable risk factors remains essential, supported by continued basic and translational research to clarify underlying mechanisms. At the same time, expanding secondary prevention through earlier detection and improved clinical management is critical for enhancing survival, particularly among older women who face the greatest disease burden.

Based on GLOBOCAN 2022 estimates, Asia accounted for 178.2 thousand new ovarian cancer cases (54.9% of the global total) and 109.5 thousand deaths (52.9% of global mortality) in 2022. While the overall regional age-standardized incidence (6.2 per 100,000) and mortality rates (3.7 per 100,000) were moderate, our secondary analysis highlights substantial heterogeneity across HDI categories, age groups, and countries within Asia, with important implications for prevention strategies, early detection, and health-system planning. Taken together, our findings suggest that ovarian cancer burden in Asia is shaped by the combined effects of demographic transition, socioeconomic heterogeneity, generational risk shifts, and modifiable exposures. Absolute ovarian cancer case and death counts were concentrated in the two most populous countries in Asia, China (61.1 thousand cases; 32.6 thousand deaths) and India (47.3 thousand cases; 33.0 thousand deaths), largely reflecting population size rather than the highest age-standardized incidence rates. As a result, disease control efforts in these countries are likely to have a disproportionate impact on the regional and global burden. In contrast, at the national rate level, markedly elevated ASIRs were observed in small, high-HDI countries, including Brunei Darussalam (13.2 per 100,000) and the Philippines (11.7 per 100,000), as well as among women aged ≥ 50 years in Georgia (46.0 per 100,000). Conversely, Tajikistan exhibited the lowest ASIR (4.4 per 100,000) and ASMR (5.2 per 100,000). These patterns underscore how population size and demographic structure interact with development level, shaping the absolute burden observed across HDI strata [ 25 – 28 ]. Our findings demonstrate pronounced age-, period-, and cohort-specific differences in ovarian cancer burden between Asia and the global population. Consistent with prior global analyses, ovarian cancer incidence and mortality increase steeply with age, reflecting cumulative hormonal exposure, reproductive history, and biological ageing processes [ 1 , 12 , 29 ]. However, Asia exhibited a relatively higher proportion of cases and deaths among women aged < 50 years compared with the global average, likely driven by differences in population age structure and cohort composition [ 30 ]. The persistent increase in incidence across all age groups in Asia contrasts with declining or stabilizing trends observed globally, particularly among middle-aged and older women. Similar regional divergence has been reported in previous studies, suggesting that improvements in risk-factor profiles and cancer management in high-income regions have not been uniformly achieved in Asia [ 2 , 31 ]. Differences in period effects between Asia and the global population may reflect temporal variation in diagnostic capacity, cancer registration systems, and access to specialized oncologic care. Improvements in imaging technologies, pathology services, and registry completeness in several Asian countries in recent decades may have contributed to increased detection and reporting of ovarian cancer [ 32 – 35 ], thereby influencing period-specific risk estimates. In addition, disparities in access to guideline-based surgery and systemic therapy across countries may have differentially affected mortality trends over time [ 36 , 37 ]. Changes in population-level exposure to modifiable risk factors, such as rising obesity prevalence and occupational environmental hazards [ 38 , 39 ], may have further contributed to temporal variation in ovarian cancer burden across regions. The more modest rise in mortality relative to incidence may reflect gradual improvements in access to treatment, although survival gains remain limited for ovarian cancer [ 40 ]. Strong age effects observed in both Asia and globally are consistent with established biological mechanisms, whereas the increasing cohort-specific risks among successive Asian birth cohorts point to the growing influence of lifestyle, reproductive, and metabolic risk factors accompanying socioeconomic transition, including delayed childbearing, reduced parity, and rising obesity prevalence [ 7 , 41 ]. In contrast, the U-shaped cohort pattern observed globally suggesting declining risks among mid-20th-century cohorts followed by renewed increases in more recent generations [ 42 ]. Together, these APC patterns underscore that ovarian cancer control in Asia will require strategies that address both population ageing and rising cohort-specific risks, with greater emphasis on early recognition, equitable access to care, and region-specific prevention policies. Taken together, these findings indicate that the relationship between ovarian cancer burden and socioeconomic development is complex and age-dependent, rather than linear or uniform across populations. Although the very high HDI stratum showed the highest regional ASIR (7.4 per 100,000) and ASMR (4.5 per 100,000), the associations between HDI and age-standardized rates were not uniformly significant across all strata. A positive correlation between HDI and ASIR among women aged ≥ 50 years suggests complex, non-linear relationships between development level and disease burden. Several interrelated explanations are plausible. First, detection and reporting effects likely contribute, as higher-HDI settings generally possess more comprehensive cancer registries, greater diagnostic capacity (e.g., advanced imaging, pathology), and higher case ascertainment. Second, demographic and lifestyle transitions may elevate true incidence in high-HDI countries, which typically have older population structures and a greater prevalence of risk factors such as higher body mass index, lower parity, delayed childbearing, and, in some settings, hormone replacement therapy use [ 43 , 44 ]. Third, disparities in health-system capacity and access to specialized care may also shape observed outcomes. For instance, high incidence in some high-HDI countries (e.g., the Philippines and Brunei), accompanied by high ASMRs (7.5 and 6.9 per 100,000, respectively), suggests that improvements in detection are not uniformly matched by timely, high-quality treatment [ 25 – 28 ]. These findings indicate that HDI alone is an inadequate proxy for ovarian cancer outcomes, emphasizing the need to consider diagnostic intensity, stage distribution, and access to guideline-concordant surgical and chemotherapeutic care when interpreting international differences in incidence and mortality. The spatial and age-specific heterogeneity observed across Asian countries aligns closely with established reproductive, metabolic, genetic, and health-system determinants of ovarian cancer. Although reproductive factors are not currently modelled as attributable risk factors for ovarian cancer mortality in the GBD 2023 comparative risk assessment framework, extensive epidemiological evidence supports their important role in disease etiology. Reproductive history plays a central role: nulliparity and later age at first childbirth are well-documented risk factors for ovarian cancer, and countries characterized by lower fertility rates and delayed motherhood-features typical of higher-HDI settings—tend to exhibit elevated ASIRs among older cohorts [ 45 , 46 ]. Conversely, widespread and long-term use of OC confers substantial protective effects [ 47 , 48 ]; thus, cross-national variation in OC uptake likely contributes to differences in incidence, particularly among younger women [ 49 , 50 ]. Environmental and lifestyle factors may further contribute to the observed heterogeneity in ovarian cancer incidence and mortality across Asia. Similarly, smoking—while not included as an attributable risk factor for ovarian cancer mortality in GBD 2023—has been associated with ovarian cancer risk in prior epidemiological studies, with evidence suggesting increased risks for mucinous ovarian tumors among current and former smokers [ 2 ]. Variations in smoking prevalence across Asian countries and birth cohorts may therefore partially influence generational and regional differences in incidence, particularly among older women. Dietary patterns characteristic of socioeconomic transition may also play a role. Increased consumption of processed and red meat—often accompanying urbanization and higher HDI—has been associated with systemic inflammation, insulin resistance, and hormonal dysregulation, which are biologically plausible pathways for ovarian carcinogenesis [ 51 ]. In contrast, traditional diets rich in plant-based foods and fiber may confer protective effects [ 52 ]. Marked cross-country differences in dietary profiles across Asia could thus contribute to variation in ovarian cancer risk beyond reproductive and genetic factors alone. While individual-level exposure data were not available in this ecological analysis, the convergence of rising obesity prevalence, changing dietary patterns, and persistent smoking in some subregions underscores the importance of integrating lifestyle-focused prevention strategies into national cancer control plans [ 41 , 53 ]. Under the GBD 2023 comparative risk assessment framework, risk-attributable estimates for ovarian cancer are available for deaths and disability-adjusted life years, but not for incidence; therefore, mortality-based PAFs were used to approximate the population-level preventable burden. Furthermore, only high BMI and asbestos exposure are currently modelled as attributable risk factors for ovarian cancer mortality, and thus only these factors were included in the quantitative risk attribution analysis. High BMI is a major modifiable metabolic risk factor contributing to ovarian cancer burden in Asia. Epidemiologically, population-level increases in BMI have paralleled rising ovarian cancer incidence and mortality in many Asian countries, particularly among successive birth cohorts [ 54 – 57 ], highlighting a potential generational effect. Mechanistically, elevated BMI can promote ovarian carcinogenesis through multiple interrelated pathways: chronic low-grade systemic inflammation, insulin resistance, and dysregulated levels of sex hormones such as estrogen and adipokines. These processes may enhance tumor initiation, progression, and metastasis, providing a biologically plausible link between excess adiposity and ovarian cancer mortality [ 58 – 61 ]. Furthermore, obesity often co-occurs with other metabolic abnormalities, including hyperinsulinemia and metabolic syndrome, which may synergistically exacerbate cancer risk [ 62 , 63 ]. In addition, asbestos exposure may partly explain the geographic variation in ovarian cancer incidence across Asia. Asbestos fibers have been implicated in ovarian carcinogenesis through mechanisms involving persistent inflammation, oxidative stress, and translocation of fibers to the pelvic cavity [ 64 , 65 ]. Although occupational and environmental asbestos exposure has declined in some high-income countries, it remains relevant in parts of Asia where asbestos use in construction and manufacturing has historically been widespread or remains insufficiently regulated [ 65 ]. Variability in exposure intensity, occupational safety standards, and latency periods may therefore contribute to between-country differences in ovarian cancer burden, while also introducing uncertainty in risk estimation due to limitations in exposure assessment at the population level. A family history of ovarian cancer is a well-established high-risk factor and contributes meaningfully to between-country variation. Although hereditary susceptibility and endometriosis are not included as GBD-attributable risk factors, they remain important determinants of individual-level risk reported in prior studies. Differences in the prevalence of BRCA1/2 and other hereditary mutations, as well as unequal access to genetic testing, can elevate both incidence and mortality within specific subpopulations; small nations with concentrated high-risk groups may therefore exhibit disproportionately high ASIRs [ 66 , 67 ]. Moreover, exposure-related factors such as endometriosis-which markedly increases the risk of certain histological subtypes-and the protective effect of tubal ligation may partially account for the contrasting epidemiologic patterns observed across countries [ 68 , 69 ] Finally, disparities in health-care infrastructure substantially shape mortality outcomes. Stage at diagnosis, the availability of specialized gynecologic oncology surgery, and access to evidence-based adjuvant therapies critically determine survival. High ASMRs in countries with concurrently high ASIRs, such as the Philippines (ASIR 11.7 per 100,000; ASMR 7.5 per 100,000), indicate that improved detection alone is insufficient to reduce mortality without concurrent expansion of treatment capacity [ 70 , 71 ]. If 2022 incidence and mortality rates persist, Asia’s ovarian cancer burden is projected to reach ~ 265.9 thousand cases and 183.6 thousand deaths by 2050. Low-HDI countries are expected to experience the steepest relative increases (+ 124.1% in cases; +137.3% in deaths), whereas very high-HDI countries will see more moderate growth (+ 15.2% incidence; +41.1% mortality), reflecting demographic momentum and faster population ageing in less-developed regions. Achieving a sustained 2% annual decline in incidence and mortality-and ~ 3% in medium- and low-HDI countries-is necessary to mitigate this burden. Many transitioning health systems are currently ill-equipped to meet this challenge, highlighting the risk of widening disparities [ 27 , 72 ]. Equitable access to early detection, preventive interventions, and high-quality treatment, particularly for high-risk women, is essential. Expanding care capacity, improving diagnostic and therapeutic services, and implementing coordinated risk-reduction and awareness strategies will be critical to improving outcomes and controlling ovarian cancer across Asia. Based on these results we recommend a stratified, pragmatic response: First, strengthen cancer registration and surveillance. Improving data quality in low- and middle-HDI countries is foundational-accurate incidence and mortality estimates are prerequisites for planning and evaluation. Second, targeted awareness and diagnostic pathways for women aged ≥ 45. Given that ~ 80% of cases occur in this group and incidence accelerates after 44 years, educational campaigns and primary-care diagnostic algorithms should prioritize symptomatic evaluation in midlife and older women. Third, scale up treatment capacity and referral networks. Where ASMRs remain high despite elevated ASIRs (e.g., Philippines, Brunei), investments in surgical oncology, cytoreductive surgery capacity, access to combination chemotherapy, and supportive/palliative care are needed. Fourth, primary prevention and risk reduction. High BMI emerged as the leading modifiable risk factor contributing to ovarian cancer mortality, underscoring the importance of metabolic risk factor control in shaping the future disease burden in Asia. Policies to address modifiable risks—obesity prevention, promotion of breastfeeding, and informed reproductive health policies—should be integrated into national cancer control plans, with particular emphasis on weight management and healthy lifestyle interventions to reduce mortality. Additionally, expansion of genetic counselling/testing and risk-reducing strategies for BRCA carriers could be considered in settings with identified high genetic burden. Fifth, health-system equity interventions. Within-country disparities likely underlie some paradoxes (high incidence but also high mortality). Strengthening universal access to timely, high-quality care is essential to translate early detection into survival gains. Estimates of ovarian cancer incidence and mortality should be interpreted with caution, particularly in low- and middle-HDI settings where incomplete registry coverage and variable data quality may lead to underestimation. Data sources, modeling approaches, and registry coverage vary substantially across Asian countries, contributing to heterogeneity in the estimates. Some countries rely on population-based cancer registries with complete coverage, while others use modeled estimates based on neighboring countries or partial registry data. Differences in reporting standards and diagnostic completeness across countries can also introduce systematic bias. Ovarian cancer is biologically heterogeneous, with distinct histological subtypes that differ by age, risk factors, and geographic distribution; however, subtype-specific data were not available for all countries. Therefore, the presented results reflect aggregate ovarian cancer burden and may mask important subtype-specific variations. Future projections were derived from the CANCER TOMORROW, which uses GLOBOCAN 2022 as the baseline year and does not explicitly model long-term temporal trends in incidence or mortality. As a result, potential changes driven by future risk factor modification, screening practices, or treatment advances were not captured. Nevertheless, CANCER TOMORROW provides a standardized and widely used framework for estimating future cancer burden, allowing for consistent comparisons across countries and regions. The COVID-19 pandemic has further disrupted screening and healthcare access, likely influencing incidence and mortality patterns, yet its effects are not captured in this analysis [ 73 ]. Moreover, limitations in data completeness, particularly in low-resource settings, may affect projection accuracy. These uncertainties underscore the need for enhanced cancer surveillance, standardized data collection, and international collaboration to improve comparability and precision in ovarian cancer burden estimates. To refine policy responses, future work should (1) quantify the population-attributable fractions for major modifiable risks in specific Asian regions, (2) evaluate stage-at-diagnosis distributions and treatment access to explain mortality differences, (3) assess BRCA and other high-penetrance mutation prevalence across populations, and (4) model the impact and cost-effectiveness of potential interventions (awareness campaigns, genetic testing programs, capacity-building in surgical oncology) under realistic resource constraints.

Globally, ovarian cancer ranks as the eighth most common malignancy among women, accounting for approximately 3.4% of new cancer diagnoses and 4.8% of cancer deaths in 2022 [ 1 ]. Incidence varies widely across regions, historically peaking in high-income countries of Northern Europe and North America, where rates have declined over recent decades, likely reflecting multiple factors, including increased use of oral contraceptives (OC) [ 2 ], improvements in reproductive patterns [ 3 , 4 ], and other preventive measures [ 5 ]. Conversely, rising trends have been observed in parts of Eastern Europe and Asia, particularly among women under 50 years [ 6 ]. In Asia, its burden is shaped by heterogeneous demographic, reproductive, and lifestyle factors, including population aging, declining fertility, delayed childbearing, obesity, and use of hormonal therapies [ 7 , 8 ]. These factors, combined with differences in genetic predisposition and the prevalence of hereditary mutations such as BRCA1/2, contribute to significant variation in incidence and mortality across countries [ 9 ]. Socioeconomic development, often measured by the Human Development Index (HDI), further influences disease patterns by affecting access to diagnostic resources, specialized surgical and oncologic care, and cancer registry completeness [ 10 , 11 ]. High-HDI countries may exhibit elevated age-standardized incidence due to better detection and older population structures, while low-HDI countries often face underdiagnosis and limited treatment capacity, leading to poor outcomes despite lower reported rates. Although incidence, mortality, and future projections of ovarian cancer are publicly available through the International Agency for Research on Cancer (IARC) platforms, these estimates are typically presented descriptively and examined in isolation, without a unified analytical framework that integrates age–period–cohort (APC) dynamics, socioeconomic development, and modifiable risk factors, particularly within Asia. Existing global studies often aggregate Asian countries or focus on overall trends [ 12 ], thereby obscuring substantial heterogeneity across age groups, birth cohorts, and levels of development within the region. As a result, the generational evolution of ovarian cancer risk and the contribution of preventable risk factors in Asia remain poorly characterized. To address these gaps, we conducted an integrated secondary analysis combining descriptive burden estimates, age–period–cohort modeling, HDI-stratified comparisons, and risk-factor attribution within a unified analytical framework focused on Asia. By explicitly examining generational risk patterns, age-specific associations with socioeconomic development, and the population-attributable fractions of key modifiable risk factors, this study offers insights that extend beyond the standalone presentation of IARC estimates and prior global assessments. Specifically, we aimed to (1) quantify current incidence and mortality across 47 Asian countries, (2) examine associations with HDI and age structure, (3) characterize APC effects to elucidate generational risk dynamics, and (4) project the burden through 2050 under alternative scenarios.

Supplementary Material 1: Figure S1. Incidence and mortality rates of ovarian cancer in Asian countries grouped by Human Development Index. Figure S2. Heatmap displaying the disparities in age-standardized rates of ovarian cancer incidence and mortality across Asian countries with varying Human Development Index, 2022. Figure S3. Heatmap displaying the disparities in age-standardized rates of ovarian cancer incidence and mortality across Asian countries with varying Human Development Index, stratified by age, 2022. Figure S4. Age-standardized deaths of ovarian cancer attributed to risk factors by Asian countries in 2022. Table S1. Human Development Index values for Asian countries, 2022. Table S2. The lexis diagram of GBD data for the APC model. Table S3. Net annual changes of ovarian cancer incidence and mortality rates in Asia and globally. Table S4. Age-specific ovarian cancer incidence and mortality rates in Asia and globally, 2022. Table S5. Period-specific rate ratios for ovarian cancer incidence and mortality in Asia and globally, 1993–2022. Table S6. Cohort-specific rate ratios for ovarian cancer incidence and mortality in Asia and globally, 1899–2007. Table S7. Incidence and mortality of ovarian cancer from Asia countries by age, 2022. Table S8. Population-attributable fractions (PAFs) of modeled risk factors for ovarian cancer mortality, 2022. Table S9. Projected number of ovarian cancer incidence and mortality from 2022 to 2050 in Asia. Table S10. Projected number of ovarian cancer incidence and mortality from 2022 to 2050 among different HDI regions. Supplementary Material 1: Figure S1. Incidence and mortality rates of ovarian cancer in Asian countries grouped by Human Development Index. Figure S2. Heatmap displaying the disparities in age-standardized rates of ovarian cancer incidence and mortality across Asian countries with varying Human Development Index, 2022. Figure S3. Heatmap displaying the disparities in age-standardized rates of ovarian cancer incidence and mortality across Asian countries with varying Human Development Index, stratified by age, 2022. Figure S4. Age-standardized deaths of ovarian cancer attributed to risk factors by Asian countries in 2022. Table S1. Human Development Index values for Asian countries, 2022. Table S2. The lexis diagram of GBD data for the APC model. Table S3. Net annual changes of ovarian cancer incidence and mortality rates in Asia and globally. Table S4. Age-specific ovarian cancer incidence and mortality rates in Asia and globally, 2022. Table S5. Period-specific rate ratios for ovarian cancer incidence and mortality in Asia and globally, 1993–2022. Table S6. Cohort-specific rate ratios for ovarian cancer incidence and mortality in Asia and globally, 1899–2007. Table S7. Incidence and mortality of ovarian cancer from Asia countries by age, 2022. Table S8. Population-attributable fractions (PAFs) of modeled risk factors for ovarian cancer mortality, 2022. Table S9. Projected number of ovarian cancer incidence and mortality from 2022 to 2050 in Asia. Table S10. Projected number of ovarian cancer incidence and mortality from 2022 to 2050 among different HDI regions.