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The global burden and associated factors of ovarian cancer in 1990–2019: findings from the Global Burden of Disease Study 2019

Abstract

Background

Ovarian cancer (OC) is a major cause of cancer-related deaths among women. The aim of this study was to estimate and report data on the current burden of ovarian cancer worldwide over the past 30 years.

Method

Based on the data provided by GBD 2019, we collected and interpreted the disease data of ovarian cancer by incidence, mortality, disability-adjusted life-years (DALYs), and used corresponding age-standardized rates as indicators. Also, we categorized the data by attributed risk factors and captured deaths due to high fasting plasma glucose, occupational exposure to asbestos and high body-mass index, respectively. All outcomes in the study were reported using mean values and corresponding 95% uncertainty intervals (95% UI).

Results

Globally, there were 294422 (260649 to 329727) incident cases in 2019, and the number of deaths and DALYs were 198412 (175357 to 217665) and 5.36 million (4.69 to 5.95). The overall burden was on the rise, with a percentage change of 107.8% (76.1 to 135.7%) for new cases, 103.8% (75.7 to 126.4%) for deaths and 96.1% (65.0 to 120.5%) for DALYs. Whereas the age-standardized rates kept stable during 1990–2019. The burden of ovarian cancer increased with age. and showed a totally different trends among SDI regions. Although high SDI region had the declining rates, the burden of ovarian cancer remained stable in high-middle and low SDI regions, and the middle and low-middle SDI areas showed increasing trends. High fasting plasma glucose was estimated to be the most important attributable risk factor for ovarian cancer deaths globally, with a percentage change of deaths of 7.9% (1.6 to 18.3%), followed by occupational exposure to asbestos and high body mass index.

Conclusions

Although the age-standardized rates of ovarian cancer didn’t significantly change at the global level, the burden still increased, especially in areas on the lower end of the SDI range. Also, the disease burden due to different attributable risk factors showed heterogeneous, and it became more severe with age.

Peer Review reports

Introduction

Ovarian cancer (OC) is a type of aggressive gynecologic malignancy disease. In 2020, the latest global cancer burden data showed that it ranked eighth among female cancer deaths, the fifth most common cause of cancer death in women in Australia, North America, and Western Europe, accounting for 5% of female oncology deaths worldwide and more than any other gynecologic cancer [1]. Ovarian cancer has an insidious onset, and the prognosis is often poor because it is usually difficult to treat with conventional therapies due to recurrence and drug resistance [2]. For example, in Europe, the average five-year survival rate was only 29% [3].

Today, in a global perspective, the number of people with the disease varies greatly from country to country. Many variabilities add to the fact that ovarian cancer is a complex disease that has emerged as major global public health concern. In order to better understand the enormous public health impact of this disease, it is necessary to identify relevant global trends through statistics and analysis.

Ovarian cancer can be attributed to multiple risk factors (e.g., a history of smoking, nulliparity, and so on) [4]. But few comprehensive reviews have been conducted on ovarian cancer risk factors in the context of global data, and some studies that showed no association were included at the same time [5]. Several studies on ovarian cancer about GBD 2017 have been published before [6,7,8]. Besides the data version need to be updated, whether a step-change in the disease burden is meaningful remains to be determined [8]. Also, one study did not address changes in disability-adjusted life years [7], and it can be seen that there was no overall grasp of age-standardized rates changes over the past 30 years [6, 7]. The same as this study, some researches show that the trend in some absolute numbers may be opposite to the trend in related ASRs during past 30 years, such as cardiovascular diseases [9], so it is necessary to discuss absolute numbers in conjunction with ASRs.

As part of GBD 2019, this study provided the information of distribution and trends in the burden of ovarian cancer globally, regionally, and in 204 countries, between 1990 and 2019. Different from previous GBD studies on ovarian cancer [6,7,8], in this study we focus not only on the details of geographic and long-term patterns of OC incidence and mortality over the past 30 years. Our objectives were to estimate the number of ovarian cancer new cases, deaths, and corresponding disability-adjusted life years (DALYs) between 1990 and 2019 based on country, age, and sociodemographic status, to explore age trends in ovarian cancer and to analyze the major risk factors that contributed to the deaths of OC.

Methods and materials

Overview

Data for this study was obtained from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019). The GBD study provides a tool to quantify the health losses from hundreds of diseases, injuries, and risk factors to improve health systems and eliminate disparities [10]. GBD is now widely used to understand the global burden of diseases. We searched the GBD database for global female ovarian cancer data from 1990 to 2019 through the GBD Results Tool of IHME (GHDx, a large database of health-related data maintained by the Institute for Health Metrics and Evaluation, http://ghdx.healthdata.org).

The codes corresponding to cancer in the GBD etiology hierarchy were derived from the ICD-9 and ICD-10 code books of the International Classification of Diseases, which is consistent with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) [11], and could be used to identify OC data. Incidence, mortality, and disability-adjusted life years and their corresponding age-standardized rates were selected as disease burden evaluation parameters, and the data obtained were subdivided according to geographic location, age groups, and attributable risk factors. The specific GBD study design and methods have been described in detail in previous literature [10, 12], and here we briefly review the methods used to assess the burden of ovarian cancer and its attributable risk factors.

Geographic units and age groups

In addition to natural geographic location, these countries and regions were divided into five regions based on different Socio-demographic indexes (SDI): high, high-middle, middle, low-middle, and low SDI regions. The SDI is a composite indicator of national and regional development status, expressed on a scale of 0 to 1, and is a measure of per capita income, average educational attainment (15 years and older), and total fertility (25 years and older) for all regions in the GBD study, and is strongly correlated with health outcomes [13, 14].

GBD provides multiple age groupings, and in this study, we focused on data on the burden of ovarian cancer in three groups: 15–49, 50–69, and ≥ 70 years.

Statistical analyses

The first step in estimating cancer burden calculations is modeling for specific mortality rates [15]. Although mortality data are available from a wide range of sources (vital registration, verbal autopsies, mortality surveillance, census, etc.), there are still instances where mortality data are not available for certain locations and time points [16, 17]. Accordingly, in GBD study, separately modeled mortality-to-incidence ratios (MIRs) was generated to maximize the availability of data obtained from cancer registries. Subsequently, the mortality estimates were used as inputs to Cause of Death Ensemble model (CODEm), which predicts single-cause mortality based on available data and causal covariates, allowing estimation of the number of deaths due to ovarian cancer by location, age, sex, and year. The specific modeling strategy has been described in detail in other literature [16].

Methods for estimating disease incidence in GBD 2019 study have been described in detail in previous study [10]. Ovarian cancer incidence data in GBD study was determined by using a literature review and studies jointly generated from a wide range of population representative data sources covering microdata, such as scientific reports from a large number of cohorts and registries, as well as macro-administrative data from health systems administrative. According to related studies, the estimation of all available data on incidence was calculated by Bayesian meta-regression software DisMod-MR 2.1 [18], and the values were estimated by dividing the mortality estimates of OC by the corresponding MIRs [15].

Disability is widely used in burden of disease analysis nowadays and refers to deviations from good or ideal health in any important area of health. Disability-adjusted life years (DALY) is a composite measure of time lost due to premature death and time spent living in less-than-optimal health, can fully analyze the population impact in of disease burden [19]. It is measured by summing the number of years of life lost (YLL) due to premature death, and the number of years of life disabled (YLD) due to nonfatal health loss [20]. In this case, YLL is estimated using each death multiplied by the standard life expectancy at each age, while YLD is estimated from the prevalence of sequelae and disability weights derived from population-based surveys [21]. For most sequelae, the same as the estimation of incidence, GBD 2019 study used the Bayesian meta-regression method DisMod MR 2.1 [18], to address some of the limitations in descriptive epidemiological data, such as missing, or inconsistent data.

Estimation of risk factors

Since 2002, the GBD has followed a comparative risk assessment (CRA) approach to quantify the attributable burden [22, 23], in which risk factors are classified into four tiers, ranging from the broadest risk category (e.g. behavioral, environmental and occupational, and metabolic) to the most detailed classification (e.g. discontinued and non-exclusive breastfeeding). 87 risks or risk clusters were provided in GBD 2019, and to ensure the persuasiveness of risk-outcomes on the relevant evidence, researchers excluded risk-outcome pairs with correlation results p-value > 0.1 from the existing studies. And ultimately 12 risk-outcome pairs in GBD 2017 were excluded from GBD 2019 after final reviews and meta-analysis [24]. This study mainly focused on the change in mortality, and related age-standardized rate by the most prominent risk factors for ovarian cancer, and included all risk factors, and top three most detailed risk factors.

Results

Burden of incidence

In 2019, the number of ovarian cancer incident cases was 294422 (260649 to 329727). The overall burden of ovarian cancer was on the rise, especially in the number of cases, with a percentage change of 107.8% (76.1 to 135.7%) compared to 1990 (Table 1, Fig. 1). But the percentage changes of global age-standardized incidence rate kept stable during the same time period. All three groups (15–49, 50–69, and 70 + age groups) showed an increasing trend in the number of cases between 1990 and 2019, with the highest cases number in 2019 in the 50–69 age group. The age group of largest percentage change in the number of incident cases was 70 + age group, were 119.9% (92.9 to 143.9%) (Table 1, Fig. 2a).

Table 1 Incident cases, Deaths, DALYs in 1990 and 2019, percentage change for ovarian cancer during 1990–2019, by age groups, global, SDI regions, world regions and countries
Fig. 1
figure 1

Map of percentage change of incident cases due to ovarian cancer, 1990–2019

Fig. 2
figure 2

Incident cases (a), Deaths (b) and DALYs (c) of three age groups in different SDI regions in 2019

The disease burden of ovarian cancer varies significantly across SDI regions. In 2019, the number of ovarian cancer incident cases was highest in the high SDI region, corresponding to value of 80454 (70504 to 91461), and lowest in the low SDI region. All regions showed an increasing trend during 1990–2019, while the high SDI region was the region with the lowest increase in morbidity burden, but the low-middle SDI region was the highest one, increased by 326.0% (158.8 to 470.5%) (Table 1) for new cases.

Similarly, the high SDI quintile had a negative change of ASIR during this period, accounting for 18.8% (-28.6 to -3.8%). In contrast, the disease burden in low-middle SDI quintile increased substantially (91.3% (17.8 to 157.1%) for ASIR) (Table 2, Fig. 3).

Table 2 Age-standardized rates of incidence, death and DALY per 100,000 population in 1990 and 2019, percentage change for ovarian cancer during 1990–2019, by global, SDI regions, world regions and countries
Fig. 3
figure 3

Map of age-standardized incidence rate due to ovarian cancer in 2019

The region with the highest number of incident cases was Western Europe in 1990, while East Asia and South Asia in 2019. And the age-standardized incidence rate of Central Europe was the highest among all world regions, reached 11.7 (10.0 to 13.7), while the rate of Central sub-Saharan Africa seemed lowest at the same time, showed 3.2 (2.1 to 5.1) (Table 2). In both regions, the highest number of incident cases was found in the 50–69 age group (Supplementary Table 1). However, from 1990 to 2019, Caribbean—the third lowest number of morbidity and mortality among all regions in 2019, showed the highest percentage increase in incident cases, with a number of 444.5% (152.5 to 582.7%). At the same time period, Western Europe turned out to be the region with no change (Table 1, Fig. 1, Supplementary Fig. 1a). From 1990 to 2019, United States of America and China were consistently the top countries with the highest number of cases (Table 1, Fig. 4), while Guatemala has seen an incredible increase in the number of cases in 30 years (1150.3% (469.1 to 1652.0%)) (Fig. 1). Focusing on age-standardized incidence rate per 100,000 people, Monaco ranked first both in the past 1990 and 2019, while Pakistan and Brunei Darussalam also climbed rapidly in recent years (Table 2, Supplementary Table 2, Fig. 3).

Fig. 4
figure 4

Ranking changes in incident cases by country, 1990–2019

Burden of deaths and DALYs

In 2019, the number of deaths for women due to ovarian cancer was 198412 (175357 to 217665), and the number of DALYs was 5.36 million (4.69 to 5.95), compared to 2.73 million (2.49 to 3.17) in 1990, and a percentage of DALYs increased by 96.1% (65.0 to 120.5%) (Table 1). Meanwhile, the percentage change of global age-standardized death rate and DALY rate were relatively flat. The age-standardized death rate due to ovarian cancer was 4.6 (4.0 to 5.0) per 100,000 in 2019 (Table 2). Of these, all three age groups were trending upward in the number of deaths and DALYs, with the highest number of deaths and DALYs in 2019 in the 50–69 age group(Table 1, Fig. 2b-c), but the largest percentage change was in the 70 + age group, with the number of 121.3% (95.7 to 140.3%) (Table 1). For DALYs, only the 15–49 age group in high SDI region showed a decrease in DALYs. And it should be noted that among all regions, the greatest increase in the percentage of DALYs was all observed in the 70 + group, with the highest number being in the low-middle SDI region (384.1% (209.8 to 546.5%)), followed by the middle SDI region (338.9% (215.1 to 431.3%)) (Supplementary Table 3).

From a global perspective, the burden of ovarian cancer reflected in DALYs and mortality was similar to that of morbidity. The high SDI region saw the highest deaths and DALYs in 2019, with the number of 56639 (50391 to 61318) and 1.23 million (1.13 to 1.32), and lowest in the low SDI area, while the high SDI region was the area that DALYs and death burden of which changed least, rising by 15.8% (6.5 to 35.4%) and 30.3% (19.1 to 47.3%). But the area with the largest deaths and DALYs number increase was low-middle SDI quintile with a percentage change of 308.6% (151.3 to 445.8%) and 282.1% (129.6 to 412.9%), respectively (Table 1). As for age-standardized rates of deaths and DALY, from 1990 to 2019, the high SDI region was in a decreasing trend, and with a significant decrease corresponding to 24.0% (-30.3 to -12.3%), and 27.5% (-33.1 to -14.2%), respectively. The same as the burden of incidence, the low-middle SDI quintile showed a striking increase (75.1% (10.1 to 134.4%) for ASDR and 75.1% (6.9 to 134.6%) for ASDALYR) (Table 2).

In 1990, Western Europe had the highest burden of both deaths and DALYs globally with 26356 (23607 to 27318) and 624896 (553975 to 645271), while in 2019, the region with the highest DALYs was South Asia (32105 (24894 to 39896)) for deaths and 982473 (748576 to 1238008) for DALYs). Central Europe had the highest ASDR (7.6, 6.6 to 8.9) while Central sub-Saharan Africa had the lowest ASDR (2.6, 1.7 to 4.1). Caribbean became the region with the highest percentage increase in both deaths and DALYs during this period, with changes of 432.7% (152.6 to 569.4%) and 388.3% (138.4 to 518.2%), respectively, while Western Europe had the flattest change in values, with little increase of 16.1% (4.9 to 30.2%) and the value of DALY showed no change. (Table 1, Table 2). High-income North America and Central sub-Saharan Africa had the highest and lowest age-standardized DALY rate, respectively. Similar to the results shown in Fig. 5 and Supplementary Fig. 2b, the values of deaths and DALYs in most of the regions showed numerically bigger with the increase of SDIs (Fig. 5, Supplementary Fig. 1b).

Fig. 5
figure 5

The correlation of ovarian cancer deaths and SDI, 1990–2019. The black line represents the average expected relation-ship between SDIs and deaths for ovarian cancer based on values from all countries from 1990 to 2019. SDI, social-demographic index

The same as the trend of cases, top three countries with the highest values of deaths and DALYs for ovarian cancer in 1990 were United States of America, China and Russian Federation, while in 2019, China, India, United States of America became the countries with the highest number, Guatemala had the highest change in the number of deaths among all over the world, United Arab Emirates had the biggest increase in DALYs as the same time (Supplementary Table 2, Fig. 6, Supplementary Fig. 2a-b). Based on an assessment conducted every five years, Monaco consistently ranked first in ASDR. As for ASDALYR, Greenland had the highest value in 1990, and then was overtaken by Monaco in 2005. During this period, the ranking changed a lot, and some countries with lower ASDALYR caught up, such as Pakistan and Brunei Darussalam, but as of 2019, the country with the highest ASDALYR was still Monaco (342.1 (248.9 to 436.0)) per 100,000 (Table 2, Supplementary Fig. 3a-b).

Fig. 6
figure 6

Ranking changes in number of deaths and DALYs by country, 1990–2019: (a) Number of DALYs; (b)Number of deaths

Burden of ovarian cancer attributable to leading risk factors

In 2019, the ASDR due to all risk factors remained essentially constant from 1990 to 2019, with the ASDALYR increasing from 12.3 (5.8 to 20.7) per 100,000 to 13.9 (5.7 to 25.3) per 100,000. During the period 1990–2000, the global ASDALYR values were relatively stable, and from 2001 a small increase occurred, and then a small decrease followed by a yearly increase from 2010 to 2019 (Supplementary Table 4).

Among the most specific risk factors attributed to all deaths of ovarian cancer globally in 1990, the top three were high fasting plasma glucose, high body-mass index, and occupational exposure to asbestos, respectively. In 2019, the same pattern of risk factors for the number of ovarian cancer deaths worldwide did not change (Supplementary Table 5–6).

In 2019, of all the risk factors for ovarian cancer death, the risk factor that led to the highest number of deaths was high fasting plasma glucose, accounting for 15736 (3023 to 36227) or age-standardized death rate of 0.4 (0.1 to 0.8) per 100000, the corresponding ASDR has shown an increase over the last 30 years (34.7% (18.6 to 51.4%)) (Supplementary Table 6, 7). Among the SDI regions, the numbers of ASDR due to high fasting plasma glucose showed different dynamics. The high SDI region has the highest ASDR but the smallest overall change of 8.9% (0.6 to 27.8%), but low-middle SDI and low SDI regions had the largest ASDR growth of 169.4% (74.6 to 268.1%) and 151.4% (55.3 to 265.3%), respectively (Table 3). In total, the ASDR for all world regions showed an upward trend over the last 30 years (Fig. 7), but Tropical Latin America showed the smallest increase (10.8% (0.1 to 23.8%)), while Caribbean showed the largest increase with 282.3% (66.1 to 388.6%) (Supplementary Table 6).

Table 3 Percentage change in number of deaths and age-standardized death rate due to leading risk factors, 1990–2019
Fig. 7
figure 7

The ovarian cancer ASDR (a) and ASDALYR (b) attributable to risk factors between 1990 to 2019 by SDI regions. ASDR, age-standardized death rate; ASDALYR, age-standardized disability-adjusted life year rate

Occupational exposure to asbestos was the second leading cause of ovarian cancer deaths globally (Supplementary Table 56), with an ASDR of 0.1 (0.1 to 0.2) per 100000, while from 1990 to 2019, value of ASDR caused by this risk factor showed a decreasing trend year by year, and as of 2019, ASDR has decreased by 24.9% (-46.7 to -7.4%). Among all SDI quintiles, only high SDI quintile showed a decreasing trend in ASDR, decreasing by 26.8% (-47.9 to -7.1%), while the changes in other areas were not statistically significant in value (Table 3, Fig. 7, Supplementary Table 6, 8). High body-mass index was the third leading cause of ovarian cancer deaths globally, with an ASDR of 0.1 (0.0 to 0.3) per 100000 (Supplementary Table 6, 9), while from 1990 to 2019, the value showed a slow upward trend with a 16.4% (2.7 to 32.0%) increase (Table 3). However, the middle and low SDI regions showed significant increasing trends, with the number of 152.9% (90.6 to 229.4%) and 208.5% (77.9 to 451.5%), while other regions showed no change (Table 3, Fig. 7).

Discussion

In this study, we estimated the distribution and trends of the global and regional burden of ovarian cancer from 1990 to 2019 using the latest GBD 2019 data, and explored the latest statistics of ovarian cancer by the major attributable risk factors.

Globally, the total number of incident cases, deaths and DALYs due to ovarian cancer increased significantly. Studies of GBD 2017 showed the same trends of incidence and mortality burden, while one of them didn’t analyze related DALY data, which is a crucial indicator of the dynamics of OC disease burden. Similar with the findings from previous study using 2017 GBD data, the number of cases, deaths and DALYs of ovarian cancer worldwide increased significantly, maintaining the trend shown in the 2017 study [6, 8], but the age-standardized rates did not change. Thus, we speculate the reasons caused this phenomenon were partly owing to the population increase as well as aging. At the same time, relatively stable ASIR could be explained as new risk factors not to introduce or the variation of exposure to risk factors in different parts of the world. Differences in access to health care in different regions of the world, and poor implementation of interventions to address ovarian cancer in some regions, could also contribute to a rise in global ovarian cancer deaths while ASDR remained unchanged. Moreover, the differentiation of OC burden varies greatly among regions. The incidence of OC in high SDI region was much more severe than in other regions, but fortunately, the value in these regions continued to decline. Worryingly, in contrast, we found a significant increase in OC morbidity and mortality in low SDI quintile, although age-standardized morbidity, mortality and DALY rates in these countries remained relatively low. High SDI regions are more severe than other regions, and East Asia has the highest burden of disease. This is associated with social and economic development, maternal number and the decrease of breastfeeding, infertility and the increase in obesity is the promoting factors of ovarian cancer [25,26,27], but fortunately, with the progress of treatment technology in recent years, and the active involvement of patients in treatment, The mortality rate of OC in these regions continued to decrease. In contrast, we found a significant increase in most developing countries. According to the data of the present study, disease burden of Caribbean showed an extraordinary growth in the last 30 years. Besides the influence of social and economic factors, genetic factors also played a big role. Studies have confirmed that breast and ovarian cancer patients who was born in the Caribbean, one in seven cases of ovarian/breast cancer was inherited [28, 29]. At the same time, young patients have a higher rate of genetic variation and the range of variation is very wide, which may be traced back to the period of European colonization and slave trade.

In this study, we found that the overall burden of ovarian cancer was heaviest in the age group 50–69, while the increase was the largest in the age group 70 + , which was similar to the conclusion of previous studies [29]. Such a result may be closely related to the emergence of aging, which is the same as the reason for the stabilization of age-standardized rates discussed above. For the two main types of epithelial ovarian cancer, patients before the age of 40 mostly belong to type I, which usually appears in the early stage and has a good prognosis. In older patients, type II epithelial neoplasms make up a large proportion, accounting for approximately 75% of it, and are usually present in advanced stages with poor prognosis [30]. At the same time, the elderly has more underlying diseases and more adverse biological factors [31], which may also be the reason for the difference in the incidence and death burden of ovarian cancer in different age groups.

At the same time, of all the risk factors, high fasting plasma glucose led to the most severe burden of ovarian cancer, and the burden changed a lot during the limited time period of this study. Therefore, this study confirms that carrying out effective policies based on local conditions and actively implementing prevention strategies for different risk factors are of great significance for the prevention and treatment of ovarian cancer.

Previous studies suggested that the high mortality and low survival rates of ovarian cancer are mainly due to the lack of screening [32], but a recent randomized controlled trial of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) [33], which has a high compliance rate among women, showed that the number of deaths among patients who had undergone annual multimodal screening (MMS), and annual transvaginal ultrasound screening (USS) was not significantly higher than those who did not, and could not be considered to have a significant reduction in mortality from ovarian cancer. This shows that future research still has a great potential to select better methods for the detection and treatment of ovarian cancer. At the same time, some previous analysis failed to take full advantage of the different types of data on incidence, mortality, disability-adjusted life years, and risk factors reported in the GBD [7].

If people consume high GI foods for a long time in daily life, they will have a higher risk of high fasting glucose. Some studies have shown that the overall insulin response increases dramatically after eating high GI foods, and insulin has been shown to be a cancer cell growth factor and cancer promoter [34], and like supplying energy to normal cells, ingested glucose can also provide energy to tumor cells, thus promoting tumor growth. Currently, diabetes is now proven to be an independent risk factor for ovarian cancer mortality [35], and age-standardized death rate of ovarian cancer worldwide due to high fasting plasma glucose was on the rise among all SDI quintiles, which may be associated with death due to diabetes comorbidity. And among them, over the past 3 decades, the age-standardized death rate of OC had the smallest rise in the high SDI region, which may be associated with the declining diabetes mortality in women in this region, with data showing a decreasing trend in female diabetes mortality in 24 of 28 EU countries as of 2019 [36]. Similarly, for Eastern Europe and Australasia, high fasting plasma glucose was not the first risk factor for ovarian cancer mortality. In contrast, high fasting plasma glucose led to the largest increase in ASDR in low SDI and low-middle SDI regions. In a nationally representative cross-sectional survey in Iran, researchers found that the prevalence of diabetes and prediabetes increased at an alarming rate among adults, with an age-standardized prevalence rate of 25.4 (18.6 to 32.1) per 100000 [37]. In addition to regional differences in the prevalence of diabetes, unequal distribution of government health resources may also contribute to this situation. In highly developed countries, up to 75% of government health care spending on diabetes is spent on hospital treatment for its complications. In developing countries, however, the structure of diabetes-related spending varies considerably, with most of the costs shifting to patients who must pay for their own treatment [38].

Occupational exposure to asbestos was the second-leading specific risk factor for deaths from ovarian cancer in 2019, contributing to 3.3% (1.5 to 5.4%) of all deaths. Current studies uniformly suggest that human mesothelial cells are highly sensitive to asbestos toxicity [39], but further scientific investigation is needed urgently to clarify the causal relationship between asbestos and ovarian cancer. Ovarian cancer due to asbestos exposure was listed as a new occupational disease in gynecology in 2017. Although asbestos has been banned in 55 countries or regions (e.g. Denmark, the USA) [40], it is still widely used today. High SDI region showed extremely high ASDR values in 2019, but the large decline in the past 3 decades may reflect the industrialization and cumulative occupational exposures of decades ago. For other quintiles with rising ASDR, which may face continued national industrialization in the future, should also introduce appropriate policies, which are not protective against cancer mortality reduction for the time being only by controlling asbestos exposure limits [41], but should ban the use of asbestos or manage the corresponding structures that already contain asbestos.

Our study indicated that high body-mass index was the third-leading specific risk factor for deaths from ovarian cancer in 2019. Numerous studies have now shown a correlation between obesity and ovarian cancer risk, and obesity is also associated with reduced survival rates specific to ovarian cancer at the same time. And in a Women's Health Initiative cohort study, low-fat dietary patterns, and physical activity showed the possibility of a negative association with ovarian cancer risk [42]. This provides an effective solution for ovarian cancer risk avoidance at the individual level.

The accuracy of the results of this study depends on the quality and quantity of GBD data. In terms of quantity, the GBD study cannot cover all regions of the world. In terms of quality, the possibility of missing information in less developed countries cannot be excluded. In addition, information bias is inevitable. Due to the limitation of information, we could not investigate further history to capture the influence of genetic factors on ovarian cancer. Also, different risk factors may have different effects on different histological subtypes of ovarian cancer, and we are currently unable to specifically distinguish between these histological subtypes, and GBD still faces some challenges in estimating the cause-specific non-lethal and lethal burden of ovarian cancer [43]. In order to develop more effective preventive measures, there is a need to analyze the severity grading and subtypes of ovarian cancer according to the etiology in the future.

Conclusion

GBD 2019 provides a more accurate source of data on ovarian cancer incidence, mortality, and DALYs, and the analysis of these data in this study revealed that the burden of ovarian cancer remains relatively heavy globally, especially in some less developed regions and older population. The findings suggest that ovarian cancer is strongly linked to women's lifestyles and occupational exposure, making it important to reduce related exposure to risk factors for both those women who already have the disease and those who want to prevent it. Currently, reducing the disease burden of ovarian cancer is still focused on primary prevention, and both governments and individuals should pay high attention to the early control of ovarian cancer, starting from both national health resource allocation and targeted prevention and treatment strategies.

Availability of data and materials

The Global Burden of Disease (GBD) Study estimates supporting the conclusions of this article is available in the Institute for Health Metrics and Evaluation (IHME) GBD Results Tool | Global Health Data Exchange, http://ghdx.healthdata.org/gbd-results-tool

Abbreviations

OC:

Ovarian cancer

GBD:

Global Burden of Disease

DALYs:

Disability-adjusted life years

ASR:

Age-standardized rate

UI:

Uncertainty interval

CI:

Confidence interval

EAPC:

Estimated annual percentage change

GHDx:

Global Health Data Exchange

SDI:

Socio-demographic index

GATHER:

Guidelines for Accurate and Transparent Health Estimates Reporting

MIRs:

Mortality-to-incidence Ratios

CODEm:

Cause of death ensemble model

YLL:

Years of life lost

YLD:

Years of life disabled

UKCTOCS:

UK Collaborative Trial of Ovarian Cancer Screening

MMS:

Multimodal screening

USS:

Ultrasound screening

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Acknowledgements

Thanks to the Institute for Health Metrics and Evaluation (IHME) and the Global Burden of Disease study collaborations.

Funding

This research funded by Medical Research Fund of Guangdong Province (ID: A2020582), Guizhou College Students' Innovation and Entrepreneurship Training Program (S202010661018), and Zunyi Medical University College Students' Innovation and Entrepreneurship Training Program (ZYDC2019029).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, Fangfang Zeng and Jun Liu; Data curation, Jun Liu; Formal analysis, Linzi Xiao and Zejian Lin; Investigation, Wanlin Li, Junrong Ma and Jun Cai; Methodology, Chen Cheng; Resources, Minqi Liao and Ruiqing Ouyang; Software, Shiwen Zhang; Supervision, Lu Liu and Donghong Wang; Validation, Xin Su, Lu Zheng and Yingjun Mu; Visualization, Shiwen Zhang; Writing – original draft, Shiwen Zhang; Writing – review & editing, Fangfang Zeng. Shiwen Zhang and Chen Cheng contributed equally to this work. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Fangfang Zeng or Jun Liu.

Ethics declarations

Ethics approval and consent to participate

There is no administrative permission required to access the raw data of this study because of public accessibility to the data. The GBD study was approved by the Institutional Review Board of the University of Washington, and current study was a secondary analysis conducted on this basis. As no individual patient data was collected, declaration of anonymity and consent to participate does not apply. We confirm that all methods in this paper were performed following the relevant guidelines and regulations.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Supplementary Information

Additional file 1: Supplementary Table 1.

Incident cases and deaths for ovarian cancer by age groups in 1990 and 2019.

Additional file 2:

Supplementary Table 2. Top 10 countries in the number of cases, deaths, DALYs and age-standardized rates for ovarian cancer, 1990-2019.

Additional file 3: Supplementary Table 3.

DALYs in 1990 and 2019 and percentage change for ovarian cancer during 1990–2019 by age groups.

Additional file 4: Supplementary Table 4.

Age-standardized death rate, DALY rate per 100 000 population for all risk factors to ovarian cancer by SDI regions during 1990–2019.

Additional file 5: Supplementary Table 5.

Leading 3 risk factors of ovarian cancer by deaths at the global and SDI level, 1990 and 2019 for females.

Additional file 6: Supplementary Table 6.

Deaths in 1990 and 2019, percent of total deaths and percentage change in age-standardized rate per 100,000 population for ovarian cancer during 1990–2019 by top three attributed risk factors.

Additional file 7: Supplementary Table 7.

Age-standardized death rate per 100 000 population for ovarian cancer due to high fasting plasma glucose by global and SDI regions during 1990–2019.

Additional file 8: Supplementary Table 8.

Age-standardized death rate per 100 000 population for ovarian cancer due to occupational exposure to asbestos by global and SDI regions during 1990–2019.

Additional file 9: Supplementary Table 9.

Age-standardized death rate per 100 000 population for ovarian cancer due to high body-mass index by global and SDI regions during 1990–2019.

Additional file 10: Supplementary Table 10.

Incident cases for ovarian cancer in three age groups by global and SDI regions during 1990–2019.

Additional file 11: Supplementary Table 11.

Age-standardized incidence rate, death rate and DALY rate per 100 000 population for ovarian cancer by global and SDI regions during 1990–2019.

Additional file 12: Supplementary Figure 1.

The correlation of ovarian cancer incident cases and SDI (a), the correlation of ovarian cancer DALYs and SDI (b), 1990-2019.

Additional file 13: Supplementary Figure 2.

Map of percentage change of deaths (a) and DALYs (b) due to ovarian cancer, 1990-2019.

Additional file 14: Supplementary Figure 3.

Map of age-standardized mortality (a) and DALY (b) rate due to ovarian cancer in 2019.

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Zhang, S., Cheng, C., Lin, Z. et al. The global burden and associated factors of ovarian cancer in 1990–2019: findings from the Global Burden of Disease Study 2019. BMC Public Health 22, 1455 (2022). https://doi.org/10.1186/s12889-022-13861-y

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Keywords

  • Ovarian cancer
  • Risk factors
  • Global burden of disease study 2019