Global epidemiology of ovarian cancer: patterns, trends, and risk factors

Ovarian cancer was the eighth most frequently diagnosed cancer among women in 2022. The global age-standardized incidence rate of ovarian cancer decreased from 7.22/100,000 to 6.71/100,000 from 1990 to 2021. However, incidence trends varied across countries. Declining ovarian cancer incidence rates were reported in high-income countries, such as the United States, Austria, the Netherlands, and Norway, while there were increasing incidence rates in Africa and parts of Asia, including Japan and India. The global age-standardized mortality rate of ovarian cancer decreased from 4.73/100,000 to 4.06/100,000 between 1999 and 2021 with varying trends among countries. Moreover, the age-standardized 5-year net ovarian cancer survival rate in most countries remained < 50%. Several specific factors related to ovarian cancer risk have been identified, including reproductive factors, use of oral contraceptives, anti-inflammatory diets, endometriosis, pelvic inflammatory disease, obesity, diabetes, and occupational asbestos exposure. No screening or prevention strategy has been proven effective in downstaging or reducing mortality from ovarian cancer in an average-risk population without a family cancer history or pathogenic variants. Indeed, risk-reducing salpingo-oophorectomy remains the gold standard for lowering the risk of ovarian cancer in high-risk individuals with hereditary mutations. This review provides a comprehensive overview of the epidemiology, risk factors, screening, and prevention of ovarian cancer, aiming to offer a global perspective on public health strategies for addressing the disease.

Ovarian cancer; epidemiology; risk factors; trend; prevention; screening

Ovarian cancer ranks as the eighth most frequently diagnosed cancer and the eighth leading cause of cancer-related deaths in women worldwide. An estimated 324,603 women were diag- nosed with ovarian cancer in 2022 and 206,956 died of the disease according to GLOBOCAN 2022 1. The global number of ovarian cancer cases and deaths is projected to increase by 46.9% and 62.7%, respectively, reaching 476,912 cases and 336,637 deaths by 2050 2. Although there have been advances in ovarian cancer screening, detection, and treatment meth- ods over the past several decades, particularly targeted ther - apy and immunotherapy 3, ovarian cancer remains largely incurable with a 5-year net survival < 50% in most countries4. The substantial disease burden underscores the public health significance given the persistent challenges in treating ovar - ian cancer. A structured search of PubMed, Web of Science, and EMBASE (January 1990–May 2025) was performed using terms related to ovarian cancer epidemiology, risk factors, screening, and prevention. Peer-reviewed original studies, pooled analyses, meta-analyses, and large population-based investigations were included, while non-English publica- tions, case reports, conference abstracts, and studies lacking methodologic detail were excluded. Additional sources were identified through manual reference screening. This review presents the most recent and comprehensive evidence on the epidemiology, risk factors, screening, and prevention of ovar- ian cancer with the aim of enhancing global understanding and informing public health strategies to reduce the burden of disease. *These authors contributed equally to this work. Correspondence to: Bin Li and Hongmei Zeng E-mail: [email protected] and [email protected] ORCID ID: https://orcid.org/0000-0001-8660-6457 and https://orcid. org/0000-0003-3999-3081 Received October 9, 2025; accepted December 24, 2025; published online March 24, 2026. Available at www.cancerbiomed.org ©2026 The Authors. Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). 2 Li et al. Global epidemiology of ovarian cancer Pathologic classification of ovarian cancer Ovarian cancer encompasses a heterogeneous group that orig- inates from epithelial and non-epithelial cells, resulting in two major subtypes (epithelial and non-epithelial ovarian cancer). Each subtype is characterized by distinct origins, pathologic features, epidemiologic patterns, and risk factors. Epithelial ovarian cancer is the most common form, accounting for 90%–95% of all ovarian cancers 5,6. Epithelial cancer is classified histologically into serous (52%), endome- trioid (10%), mucinous (6%), clear cell (6%), and unspecified subtypes (approximately 25%) 7. Low-grade serous carcino- mas are thought to originate from fallopian tube epithelium (endosalpingiosis) or serous ovarian borderline tumors, whereas endometrioid and clear cell carcinomas originate from endometrial tissue (endometriosis) 8. Most mucinous carcinomas are believed to derive from transitional epithelium at the tuboperitoneal junction9. Epithelial ovarian cancer can be further grouped as type I or II ovarian cancer according to clinicopathologic and molecular characteristics9. Type I epithelial ovarian cancers are generally low-grade and indolent, genetically stable, large, unilateral, cystic tumors that are confined to the ovary and are believed to develop from extraovarian benign lesions. Type II epithelial ovarian cancers typically present in an advanced stage and are high-grade bilateral types with aggressive behavior and lethal survival. Type II epithelial ovarian cancers are thought to orig- inate as fallopian tube fimbriae carcinomas that spread to the ovaries and/or peritoneum9,10. Non-epithelial ovarian cancer consists of sex cord-stromal tumors (e.g., granulosa cell tumors and thecomas) and germ cell tumors (e.g., teratomas and dysgerminomas). These subtypes are relatively rare and occur more frequently in younger women. The endometrioid subtype of localized and regional epi- thelial ovarian cancer exhibits the most favorable prognosis, followed by low-grade serous and mucinous ovarian cancer. Ovarian carcinosarcoma is associated with the poorest prog- nosis with a 5-year survival rate < 50%. However, distant-stage ovarian cancer, which accounts for the majority of diagnoses, presents a comparatively worse prognosis. Within these clas- sifications, low-grade serous, endometrioid, and high-grade serous ovarian cancer have the best prognosis, followed by clear cell and mucinous subtypes. Ovarian carcinosarcoma has the worst histology of ovarian cancer6. Descriptive epidemiology and time trend of the cancer burden The global annual incident cases of ovarian cancer reached 324,603 in 2022 according to GLOBOCAN 1; the geographic incidence variation differed worldwide. The highest age-ad- justed incidence rates for ovarian cancer were in Eastern Europe at 11.0/100,000, followed by Northern Europe (9.1/100,000), Southern Europe (8.4/100,000), and South-East Asia (8.1/100,000). The lowest age-adjusted incidence rates for ovarian cancer were in Middle Africa (4.3/100,000), Southern Africa (4.9/100,000), and the Caribbean (4.9/100,000). Detailed data for each region are shown in Table 1. Countries with a very high human development index (HDI) had the highest age-adjusted incidence rates for ovar - ian cancer (8.2/100,000). Low HDI countries had the lowest incidence rate for ovarian cancer (4.9/100,000). The global age-standardized incidence rate for ovarian cancer declined from 7.22/100,000 to 6.71/100,000 from 1990 to 2021 with an estimated annual percentage change of −0.38 [95% con- fidence interval (CI), −0.43 to −0.32] 1,11. Detailed data from 2005–2016 revealed a decreased incidence rate for ovarian cancer in Australia, the USA, Denmark, Sweden, Germany, France, Colombia, and Norway, which was due, at least in part, to the increased use of oral contraceptive pills and the decreased administration of menopausal estrogen-only hor - mone therapy 7,12. In contrast, the incidence rates for ovar - ian cancer in Eastern Europe and some regions of Asia have been increasing, particularly in Belarus, Japan, Thailand, and India 12,13. Of note, the lower use of oral contraceptive pills and lower parity might partially explain the increas- ing rates 14. Statistics in China showed the age-standardized incidence rates for ovarian cancer were relatively stable from 2011–2018 15. The global new deaths from ovarian cancer have reached 206,956 according to GLOBOCAN 2022. Regionally, the high- est age-adjusted mortality rates for ovarian cancer were also in Eastern Europe (6.1/100,000), followed by South-East Asia (5.1/100,000), and Northern Europe (4.8/100,000). Eastern Asia had the lowest age-adjusted mortality rate for ovarian cancer (2.7/100,000). Countries with a medium HDI had the highest age-adjusted mortality rate for ovarian cancer (4.5/100,000), while the high HDI countries had the lowest mortality rate (3.3/100,000). The global age-standardized mortality rate for ovarian cancer declined from 1999–2021 by an estimated annual percentage change of −0.62 (95% CI, −0.68 to −0.57) 11. The mortality rate of ovarian cancer in the USA declined between 1976 and 2015 by 33.0%7. However, the mortality rate for ovarian cancer in China showed an upward trend with an average annual percentage change of 4.4% from 2000–201815. The age-standardized 5-year net ovarian cancer survival rate in most countries was still < 50% for women diagnosed from 2010–2014 according to the CONCORD-3 4. Survival rates for ovarian cancer ranged from 40.0%–49.0% in Canada, the USA, China, Japan, Korea, Singapore, Austria, Finland, France, Germany, Iceland, Norway, Portugal, Sweden, Switzerland, and Australia. Survival rates for ovar - ian cancer were < 30% in Chile and < 20% in India. The Cancer Biol Med Vol xx, No x Month 2026 3 survival trend for ovarian cancer has remained relatively flat between 1995-1999 and 2010-2014 4,16. Improvements in 5-year survival for ovarian cancer were reported across 17 countries, including the USA, Japan, Korea, Bulgaria, the Czech Republic, Denmark, France, Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Spain, Switzerland, the UK, and Australia. The most remarkable improvement in survival for ovarian cancer was observed in Japan with an increase of 11.1%; detailed data are shown in Figure 1 . The updated age-standardized 5-year relative survival rate for ovarian cancer in China between 2019 and 2021 was 39.6%; the rate was stable from 2008–2021 17. The 5-year rel- ative ovarian cancer survival rate in the US increased from 44.6% to 52.8% between 2000 and 2017 with an average absolute increase of 0.4% according to the SEER database of 21 registries 18. Table 1 Age-standardized ovarian cancer incidence and mortality rates in 2022 World Incidence Mortality Number ASR Crude rate Cumulative risk Number ASR Crude rate Cumulative risk Region Northern America 24,484 7.5 13.0 0.83 15,554 3.8 8.3 0.44 Central America 6175 6.0 6.6 0.64 4033 3.9 4.3 0.44 South America 16,447 5.6 7.4 0.62 10,866 3.5 4.9 0.41 Eastern Africa 7690 5.3 3.3 0.60 5518 4.2 2.3 0.50 Middle Africa 2458 4.3 2.6 0.45 1794 3.5 1.9 0.39 Northern Africa 7145 6.0 5.6 0.66 4687 4.0 3.7 0.48 Southern Africa 1677 4.9 4.8 0.55 1424 4.2 4.1 0.47 Western Africa 6790 5.1 3.2 0.54 4601 3.8 2.2 0.43 Caribbean 1450 4.9 6.5 0.53 1012 3.2 4.5 0.36 Eastern Asia 75,773 6.0 9.5 0.64 40,264 2.7 5.1 0.32 South-East Asia 32,113 8.1 9.4 0.85 20,514 5.1 6.0 0.58 South Central Asia 61,931 6.1 6.2 0.67 42,839 4.3 4.3 0.51 Western Asia 8406 6.1 6.1 0.66 5930 4.3 4.3 0.51 Eastern Europe 29,416 11.0 19.0 1.2 19,165 6.1 12.4 0.73 Northern Europe 9787 9.1 18.1 1.0 6586 4.8 12.2 0.56 Southern Europe 13,265 8.4 17.1 0.93 8398 4.1 10.8 0.48 Western Europe 17,004 7.1 17.0 0.81 12,083 4.1 12.1 0.48 Australia-New Zealand 2177 8.0 14.0 0.89 1384 4.0 8.9 0.46 Melanesia 359 7.5 6.4 0.77 262 5.8 4.6 0.64 Micronesia 22 7.3 7.9 0.91 19 6.4 6.9 0.83 Polynesia 34 9.0 10.0 1.1 23 6.0 6.7 0.76 HDI level Very high HDI country 120,904 8.2 14.6 0.91 77,625 4.3 9.4 0.51 High HDI country 113,283 6.0 8.3 0.65 66,974 3.3 4.9 0.38 Medium HDI country 70,820 6.4 6.4 0.70 48,669 4.5 4.4 0.53 Low HDI country 19,477 4.9 3.2 0.53 13,590 3.7 2.3 0.43 ASR, age-adjusted rate, per 100,000 person-years; HDI, human development index. 4 Li et al. Global epidemiology of ovarian cancer Disability-adjusted life years and years lived with disability Table 2 illustrates the disability-adjusted life years (DALYs) and years lived with disability (YLDs) for ovarian can- cer19. The global DALYs count reached 5,160,000/100,000 in 2021. The European region had the highest DALYs count (1,260,000/100,000), followed by South-East Asia (1,130,000/100,000) and the Western Pacific region (1,120,000/100,000). The Eastern Mediterranean region had the lowest DALYs count (320,000/100,000). The global DALYs for ovarian cancer increased from 1990 to 2021 (Figure 2A). The global YLDs count rose to 155,650/100,000 in 2021. The regional distribution of ovarian cancer YLDs was compa- rable to DALYs. The European region had the highest YLDs count (38,100/100,000), followed by the Western Pacific region (37,280/100,000) and South-East Asia (33,320/100,000). The Eastern Mediterranean region had the lowest YLDs count (8300/100,000). The global YLDs trend for ovarian cancer also exhibited a similar increase from 1990–2021 (Figure 2B). The age-specific DALYs counts in 2021 are shown in Figure 3A. The DALYs counts increased with advancing age at the time of diagnosis. Women > 70 years of age had the highest DALYs count (1,130,000/100,000). The age-specific YLDs counts in 2021 are shown in Figure 3B. The YLDs increased with advancing age at the time of diagnosis. However, it is worth noting that both DALYs and YLDs counts declined in women who were diagnosed between 60 and 69 years of age, which may be attributed to the use of oral contraceptives 12. Risk factors for ovarian cancer Several factors have been shown to be associated with the risk of ovarian cancer, including reproductive, behavioral, dietary, metabolic, medical, genetic, and environmental factors (Table 3, Figure 4). The risk estimates presented in Table  3 were extracted from published meta-analyses or pooled studies, each of which used a multivariable-adjusted analytical frame- work as reported by the original authors. Because effect mod- ifiers and confidence intervals were not uniformly available across studies, these values should be interpreted as summa- rized associations rather than harmonized effect sizes derived from a single analytical model. Reproductive factors Studies have shown that childbirth has a protective effect on epithelial ovarian cancer and the effect is subtype-depend- ent. The risk of ovarian cancer decreased by 6% [relative risk (RR), 0.94; 95% CI, 0.92–0.96] with each additional birth among women who have had children in a prospective study involving 1.1 million UK women with the greatest reduction Kore a Singapor e Sw eden Norw ay FranceFinlan d USATurk ey Japan Por tugalChin a Austria Sw itzerlandGermanyIcelan d AustraliaCanada Italy Thailand SpainBrazil Netherlands DenmarkKuwait New ZealandCzech R epublicRussi a PolandBulgariaColombia UK Irelan d ChileIndi a Country Age-standardized 5-year net survival (%) 0 10 20 30 40 50 2000–2004 2005–2009 2010–2014 Figure 1 Age-standardized 5-year net ovarian cancer survival in different countries from 2000 to 2014. This figure illustrates the geographic and temporal variations in ovarian cancer survival across select countries. A key box above the graph explains the colored lines representing different time periods. The x-axis shows the countries sorted from highest-to-lowest average survival rate. The y-axis shows the age-stand - ardized 5-year net survival rate expressed as a percentage (%). Cancer Biol Med Vol xx, No x Month 2026 5 in the risk of clear cell carcinoma (RR, 0.75; 95% CI, 0.65– 0.85)20. However, in a Finnish cohort study involving 87,929 multiparous women, multiparity (> 5 births) did not provide additional protection against ovarian cancer 37. In summary, these findings indicated that while the number of pregnan- cies is negatively correlated with the risk of ovarian cancer, this protective effect does not follow a linear dose-response relationship with the number of pregnancies. In fact, evidence suggests that most of this protective effect is attributable to the first three pregnancies38. The current mainstream view is that the cessation of ovula- tion during pregnancy and breastfeeding inhibits the division and proliferation of ovarian epithelial cells, thereby reduc- ing the chance of initiating or promoting carcinogenesis 39. A pooled analysis of 13 case-control studies from the Ovarian Cancer Association Consortium showed that breastfeeding can reduce the risk of invasive ovarian cancer by 24% with the greatest reduction observed in high-grade serous ovar - ian cancer. The duration of breastfeeding can further reduce the risk of ovarian cancer39. The risk of ovarian cancer can be reduced by approximately 10% for every 12 months of breast- feeding (RR, 0.89; 95% CI, 0.84–0.94)20. Dietary and metabolic factors Inflammation is a normal physiologic process but long-term, persistent chronic inflammation may promote carcinogenesis by damaging important cell components, activating tumor- promoting signaling pathways, promoting abnormal prolifer- ation, and inhibiting apoptosis40. Pro-inflammatory diets have Table 2 Ovarian cancer DALYs and YLDs in the global burden of disease study 2021 Location DALYs per 100,000 YLDs per 100,000 Value Lower bound Upper bound Value Lower bound Upper bound Africa 357,474.21 266,133.78 427,989.60 8,835.35 5,890.77 12,014.81 South-East Asia 1,132,285.22 966,868.25 1,372,584.52 33,318.56 23,436.52 44,561.70 Americas 944,236.63 889,096.85 990,123.33 28,354.09 20,965.35 36,478.54 Europe 1,263,327.45 1,177,992.02 1,332,170.16 38,099.13 28,070.04 48,972.54 Eastern Mediterranean 315,571.69 235,103.98 406,673.99 8,378.60 5,684.23 11,920.54 Western Pacific 1,120,217.11 896,904.74 1,364,393.88 37,279.62 25,724.54 51,643.26 Global 5,163,256.30 5,608,304.11 4,692,422.55 155,645.72 201,143.40 113,442.62 DALY, disability-adjusted life years; YLD, years lived with disability. 1990 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5 5.2 5.4 5.6 60 80 100 120 140 160 180 200 1995 2000 2005 Year AB 2010 2015 2020 1990 1995 2000 2005 Year 2010 2015 2020 Number of disability-adjusted life years (millions) Number of years lived with disability (thousands) Figure 2 Global trends in disability-adjusted life years (DALYs) and years lived with disability (YLDs) due to ovarian cancer (1990–2021). This figure presents the global disease burden of ovarian cancer over three decades, as measured by DALYs (A) and YLDs (B). The global trends in DALYs and YLDs from ovarian cancer showed an increasing trend from 1990 to 2021. 6 Li et al. Global epidemiology of ovarian cancer 1,200 1,000 800 600 400 200 0 35 30 25 20 5 15 10 0 <2020–2425–2930–3435–3940–4445–4950–5455–5960–6465–69 70+ <2020–2425–2930–3435–3940–4445–4950–5455–5960–6465–69 70+ Age at diagnosis Age at diagnosis Number of disability-adjusted life years (thousands) Number of years lived with disability (thousands) AB Figure 3 Age-specific disability-adjusted life years (DALYs) and years lived with disability (YLDs) for ovarian cancer in 2021. This figure depicts the distribution of the ovarian cancer disease burden across different age groups in 2021. The x-axis represents the age groups at the time of diagnosis. The y-axis represents the DALYs (A) or YLDs counts (B). Table 3 Factors associated with the risk of ovarian cancer Factors RR, OR, HR, SMR and 95% CI Reference Reproductive factor Childbirth Each of the first three pregnancies in ovarian cancer risk [RR, 0.94; 95% CI, 0.92–0.96] Each of the first three pregnancies in clear cell ovarian cancer risk [RR, 0.75; 95% CI, 0.65–0.85] 20 Breastfeeding Every 12 months of breastfeeding [RR, 0.89; 95% CI, 0.84–0.94] Dietary factors Vegetable intake Green leafy vegetables [RR, 0.91; 95% CI, 0.85–0.98] Allium vegetables [RR, 0.79; 95% CI, 0.64–0.96] 21 Fiber intake Fiber [RR, 0.89; 95% CI, 0.81–0.98] Fat intake Total fat [RR, 1.10; 95% CI, 1.02–1.18] Saturated fat [RR, 1.11; 95% CI, 1.01–1.22] Saturated fatty acid [RR, 1.19; 95% CI, 1.04–1.36] Cholesterol [RR, 1.13; 95% CI, 1.04–1.22] Tea intake Green tea [RR, 0.61; 95% CI, 0.49–0.76] 22 Pro-inflammatory diets Higher DII scores [OR, 1.42; 95% CI. 1.19–1.65] Each increase in DII point [OR, 1.10; 95% CI, 1.06–1.14] 23 Metabolic factors High BMI Serous borderline ovarian tumor [OR, 1.24; 95% CI, 1.18–1.30] Endometrioid ovarian cancer [OR, 1.17; 95% CI, 1.11–1.23] Mucinous ovarian cancer [OR, 1.19; 95% CI, 1.06–1.32] 24 Diabetes Diabetes [RR, 1.32; 95% CI, 1.14–1.52] 25 Cancer Biol Med Vol xx, No x Month 2026 7 been shown to be a risk factor for ovarian cancer in multiple case-control studies41,42. Indeed, there was a positive correla- tion between dietary inflammatory potential, as measured by the dietary inflammatory index (DII), and the incidence of ovarian cancer in a meta-analysis of six studies. Individuals with higher DII scores had a 42% increased risk for ovarian cancer [odds ratio (OR), 1.42; 95% CI, 1.19–1.65] 23. A mul- ticenter case-control study from Italy involving 1031 ovarian cancer cases and 2411 non-ovarian-cancer cases suggested that a diabetes risk reduction diet reduces the risk of ovarian can- cer43. A meta-analysis of 97 cohort studies showed that green vegetable, fiber, and green tea intake reduced the risk of ovarian cancer, while total fat, saturated fat, saturated fatty acids, cho- lesterol, and retinol intake significantly increased the risk21,22. Several studies have shown that overweight and obesity increase the likelihood of developing ovarian cancer 44,45. Cancer cells often exhibit altered metabolic pathways with increased fatty acid oxidation, glycolysis, and glutaminolysis, which contribute to ovarian cancer growth 46. Research indi- cates that overweight or obesity can increase the risk of can- cer through multiple pathways, including hyperinsulinemia/ insulin resistance and abnormalities in the insulin-like growth factor-I (IGF-I) system and signaling, the biosynthesis and action pathways of sex hormones, subclinical chronic low- grade inflammation, and oxidative stress47. A Mendelian study suggested a causal link between obesity and aggressive epi- thelial ovarian cancer with body mass index (BMI) differen- tially associated with histologic subtypes of ovarian cancer 48. A pooled analysis of 15 case-control studies in the Ovarian Cancer Association Consortium, including 13,548 cases and 17,913 controls, suggested that high BMI increases the risk of serous borderline ovarian tumor (OR, 1.24; 95% CI, 1.18– 1.30), invasive endometrioid ovarian cancer (OR, 1.17; 95% CI, 1.11–1.23), and invasive mucinous ovarian cancer (OR, 1.19; 95% CI, 1.06–1.32) but not high-grade invasive serous cancer24. Factors RR, OR, HR, SMR and 95% CI Reference Behavioral factor Prolonged sitting time 10–19 h/week sitting [HR, 1.25; 95% CI, 1.04–1.51] ≥ 20 h/week sitting [HR, 1.40; 95% CI, 1.14–1.71] 26 Psychosocial stress HR, 1.71; 95% CI, 1.16–2.52 27 Medical factors Oral contraceptives Ever vs. never [OR, 0.73; 95% CI, 0.70–0.76] Each 5 years of use decreased risk by 20% (95% CI, 18–23%) 28 Hormone replacement therapy Serous ovarian cancer [RR, 1.53; 95% CI, 1.40–1.66] Endometrioid ovarian cancer [RR, 1.42; 95% CI, 1.20–1.67] 29 Endometriosis Clear cell ovarian cancer [OR, 3.05; 95% CI, 2.43–3.84] Endometrioid ovarian cancer [OR, 2.04; 95% CI, 1.67–2.48] 30 Pelvic inflammatory disease Borderline ovarian tumor [OR, 1.50; 95% CI, 1.08–2.08] 31 Serous borderline ovarian tumor [OR, 1.76; 95% CI, 1.36–2.29] 32 Salpingectomy Unilateral or bilateral salpingectomy [HR, 0.65; 95% CI, 0.52–0.81] Unilateral salpingectomy [HR, 0.71; 95% CI, 0.56–0.91] Bilateral salpingectomy [HR, 0.35; 95% CI, 0.17–0.73] 33 Genetic factors BRCA mutations BRCA1 carriers (by 70 years of age): 59% (95% CI, 43–76%) BRCA2 carriers (by 70 years of age): 16.5% (95% CI, 7.5–34%) 34 Lynch syndrome Lifetime risk of 6.7% (95% CI, 5.3–9.1%) 35 Environmental factors Occupational asbestos exposure Standardized mortality ratio, 1.77; 95% CI, 1.3–72.28 36 RR, relative risk; 95% CI, 95% confidence interval; HR, hazard ratio; DII, dietary inflammatory index; OR, odds ratio. The risk factors listed above were associated with overall ovarian cancer when no specific histologic type was specified. Table 3 Continued 8 Li et al. Global epidemiology of ovarian cancer Diabetes may also increase the risk of ovarian cancer. Cancer cells rely on aerobic Warburg metabolism to meet the energy needs. Cancer cells also synthesize fatty acids, proteins, and nucleotides. Therefore, cancer cells continuously require an increased supply of glucose and diabetes-related hyperglyce- mia may fuel this demand47. A meta-analysis of 9 case-control and 27 cohort studies suggested that patients with diabetes had a relatively increased risk of ovarian cancer (RR, 1.32; 95% CI, 1.14–1.52)25 and the association between diabetes and ovarian cancer is more significant in Asian populations49. Lifestyle and psychological factors Prolonged sitting time may increase the risk of ovarian can- cer50. In a cohort study involving 173,688 participants, women who sat for 10–19 h/week [hazard ratio (HR), 1.25; 95% CI, 1.04–1.51] and women who sat for ≥ 20 h/week (HR, 1.40; 95% CI, 1.14–1.71) had an increased risk compared to women who sat for < 5 h/week26. Another meta-analysis involving 26 studies showed that women who engaged in regular recrea- tional physical activity had a 30%–60% lower risk of ovarian cancer51. Chronic stress is linked to increased ovarian cancer risk. Stress can lead to increased concentrations of adrenaline and norepinephrine, activate β-adrenergic signaling, then partici- pate in the regulation of various cellular processes involved in the occurrence and development of cancer, such as promoting tumor angiogenesis, inducing DNA damage, inhibiting DNA repair, and reducing tumor cell apoptosis 52. In a study that included 115,694 participants with > 21 years of follow-up, women who experienced ≥ 3 distress-related psychosocial fac- tors had a > 70% increased risk of ovarian cancer compared Environmental Asbestos exposure Childbirth Breast feeding Sedentariness Stress Vegetable, fiber, and tea intake Fat intake Overweight Obese Risk factor Protective factor DiabetesOral contraceptives Endometriosis PID HRT Salpingectomy BRCA mutation Lynch syndrome Reproductive Behavioral Dietary Metabolic Medical Genetic Factors associated with risk of ovarian cancer Figure 4 Summary of risk factors for ovarian cancer. This schematic summarizes and categorizes a spectrum of factors linked to ovarian cancer risk, distinguishing between factors that increase risk and factors that confer protection. The factors are organized into seven intercon- nected categories for systematic understanding, including genetic, reproductive, behavioral, dietary, metabolic, medical, and environmental factors. Cancer Biol Med Vol xx, No x Month 2026 9 to women who had < 3 distress-related psychosocial factors (HR, 1.71; 95% CI, 1.16–2.52). Notably, when post-traumatic stress disorder was included, the association between distress- related factors and ovarian cancer was strengthened27. Medical history Oral contraceptives have long been known to reduce the inci- dence of ovarian cancer by inhibiting the ovulation process. Ovulation causes repeated microtrauma to the ovarian epithe- lial surface, which increases the risk of malignant transforma- tion. This process may explain why oral contraceptives reduce the risk of ovarian cancer 45, especially in women with endo- metriosis53. A Meta-analysis involving 23,257 women with ovarian cancer and 87,303 women without ovarian cancer from 45 studies in 21 countries showed that oral contracep- tives can prevent ovarian cancer in the long term (RR, 0.73; 95% CI, 0.70–0.76); the duration of oral contraceptive usage and the reduction in risk displayed a dose-response relation- ship28. However, the protective effect of oral contraceptives may decrease with age or after discontinuation. Hormone replacement therapy (HRT), which has been widely used to treat menopausal symptoms in women, is associated with an increased risk of ovarian cancer. The main HRT regimens include estrogen alone [estrogen replace- ment therapy (ERT)] or an estrogen and progestin combi- nation [estrogen-progestin replacement therapy (EPRT)]. The relationship between HRT and the risk of ovarian can- cer has not been consistent across studies. A meta-analysis of 52 epidemiologic studies conducted since 1970 showed that for every 1000 women who received hormone therapy for 5 years starting at approximately 50 years of age, 1 additional ovarian cancer patient would be diagnosed. The increase was most pronounced for serous (RR, 1.53; 95% CI, 1.40–1.66) and endometrioid ovarian cancer (RR, 1.42; 95% CI, 1.20–1.67) 29. Studies have shown a significant correlation between the use of ERT and the incidence of ovarian cancer, while the use of EPRT alone did not increase the risk 54. This finding may be explained by the fact that most ovarian tumors are estrogen receptor-positive and progesterone may counteract the pro- liferative effect of estrogen by promoting ovarian cell apop- tosis45. A meta-analysis of 21 cohort studies showed that the use of HRT increased the risk of ovarian cancer. However, when the research time frame was limited to the past decade, the associated risk was minimal, indicating that the impact of HRT on the incidence of ovarian cancer is not durable55. Endometriosis is a recognized risk for ovarian cancer that shares overlapping genetic susceptibility with endometrioid and clear cell subtypes 56. A large international case-control study including 13,226 controls and 7911 invasive ovarian can- cer cases showed that endometriosis was most strongly asso- ciated with clear cell carcinoma (OR, 3.05; 95% CI, 2.43–3.84) and endometrioid carcinoma (OR, 2.04; 95% CI, 1.67–2.48)30. In like manner, a cohort study involving 450,906 women (78,476 with endometriosis and 372,430 without) showed that women with endometriosis had a higher risk of type I ovarian cancer than women without endometriosis, especially patients with deep infiltrating endometriosis or ovarian endometriotic cysts53. Inflammation has been linked to ovarian cancer. In a popu- lation-based case-control study including 554 Danish women with invasive ovarian cancer, pelvic inflammatory disease (PID) was associated with increased risk of borderline ovarian tumor (OR, 1.50; 95% CI, 1.08–2.08)31. A Swedish case-control study, including 4782 cases and 45,167 controls also reported an elevated risk of serous borderline ovarian tumor among women with a history of PID (OR, 1.76; 95% CI, 1.36–2.29)32. Current evidence suggests that high-grade serous ovar - ian cancer originates from the distal fallopian tube epithe- lium, forming serous tubal intraepithelial carcinoma that can shed and implant on the ovarian surface 57. Women who underwent unilateral or bilateral salpingectomy in a popula- tion-based cohort study spanning from 1973–2009 in Sweden (n = 34,433) had a significantly lower risk of ovarian cancer compared to women who had not undergone unilateral or bilateral salpingectomy [n = 5,449,119] (HR, 0.65; 95% CI, 0.52–0.81). The reduction in ovarian cancer risk was greater with bilateral salpingectomy than with unilateral33. Given the long study period, potential variations in diagnostic criteria, surgical practices, and classification systems should be consid- ered. For example, changes in Swedish surgical coding after 1997 prevented distinction between unilateral and bilateral salpingectomy, which limited stratified analyses. Nevertheless, because meaningful risk reduction typically emerges >10 years after salpingectomy, the extended follow-up and large sample size still lend substantial strength to these findings. Evidence linking hysterectomy to the risk of ovarian cancer remains inconsistent. Several studies have found no significant associa- tion between hysterectomy for benign gynecologic conditions and ovarian cancer incidence58,59, whereas other studies have reported a modest reduction in risk60. Genetic factors Hereditary breast-ovarian cancer syndrome is a major genetic predisposition to ovarian cancer. Hereditary breast-ovarian cancer syndrome results primarily from pathogenic variants (mutations) in the BRCA1 or BRCA2 genes, which have key roles in DNA damage repair61. BRCA1 and BRCA2 gene muta- tions are associated with a high lifetime risk of ovarian cancer. It is estimated that by 70 years of age, the average cumulative risk of ovarian cancer for BRCA1 mutation carriers is 41% and 15% for BRCA2 mutation carriers62. Lynch syndrome also contributes to hereditary ovarian cancer. Lynch syndrome is an autosomal dominant disorder caused by germline pathogenic variants in DNA mismatch 10 Li et al. Global epidemiology of ovarian cancer repair (MMR) genes. Women with a family history of Lynch syndrome have a 6.7% lifetime risk of ovarian cancer 35. The increased risk of ovarian cancer in Lynch syndrome is not histology-specific. In contrast, high-grade serous carcinoma is nearly the only histologic type of hereditary ovarian can- cer in hereditary breast-ovarian cancer syndrome with BRCA mutations, suggesting that hereditary breast-ovarian cancer may have a different nature from ovarian cancer in Lynch syndrome63. Environmental and occupational exposures Some occupational and environmental exposures may increase ovarian cancer risk. A meta-analysis of 18 cohort studies involving women with occupational asbestos expo- sure showed that asbestos exposure was associated with an increased risk of ovarian cancer (standardized mortality ratio, 1.77; 95% CI, 1.37–2.28) 36. Talc, which is structurally similar to asbestos, was among the first environmental risk factors identified for ovarian cancer. Earlier studies suggested that talc use increases the risk of ovarian tumors, especially serous subtypes 64. However, recent evidence remains incon- sistent. Case-control studies often report a weak positive association, whereas cohort studies consistently showed null results, with the discrepancy likely due to recall bias or resid- ual confounding65-67. Racial and ethnic disparities Ovarian cancer risk and outcomes differ across racial and ethnic groups and are influenced by underlying social deter - minants, such as socioeconomic status (SES) and access to healthcare. Data from the US Centers for Disease Control and Prevention indicated that ovarian cancer rates are the highest among non-Hispanic American Indian, native Alaskan, and non-Hispanic White women, while the rates are low among Hispanic, non-Hispanic Asian and Pacific Islander, and non-Hispanic Black women. The higher rates among non-Hispanic White women may be due to the higher incidence of hereditary breast and ovarian cancer mutations in the Ashkenazi Jewish population 68. SES can influence the risk and prognosis of ovarian cancer through multiple pathways. Women from lower-SES backgrounds are more likely to experience adverse lifestyle and meta- bolic factors, such as obesity and chronic inflammation, and to have lower utilization of preventive healthcare services, all of which may increase ovarian cancer risk 69. Limited access to gynecologic care, delay in diagnosis, and decreased adherence to guideline- recommended treatment have also been associated with a higher likelihood of presenting with advanced-stage ovarian cancer and poorer survival outcomes70. Furthermore, a meta-analysis demonstrated marked disparities in treatment adherence and mortality across racial and socioeconomic groups. Black patients had a 25% lower rate of adherence to ovarian cancer treatment (RR, 0.75; 95% CI, 0.66–0.84) and an 18% higher risk of mortality (RR, 1.18; 95% CI, 1.11–1.26) compared to White patients. Patients in the lowest SES category had a 15% lower adherence rate compared to patients in the highest SES group (RR, 0.85; 95% CI, 0.77–0.94) and individuals with fewer hospital visits showed a 30% lower adherence rate compared to patients with more frequent healthcare contact (RR, 0.70; 95% CI, 0.58–0.85) 71. Screening of ovarian cancer In ovarian cancer screening women are divided into average- and high-risk populations. Women with a family history of cancer or carrying BRCA1, BRCA2, or other pathogenic var - iants have an increased ≥ 10% lifetime risk of ovarian cancer compared to women with an average risk72,73. Because patients with early-stage ovarian cancer frequently lack symptoms, screening and early detection remain challenging. Clinical trials, such as SCSOCS (82,487 participants with a mean follow-up of 9.2 years) and PLCO (78,216 partici- pants with a mean follow-up of 12.4 years), demonstrated that screening strategies using serum CA-125 combined with transvaginal ultrasound did not result in downstaging or a reduction in ovarian cancer mortality for women at average risk74. The UKCTOCS trial, which involved 202,638 partici- pants with a median follow-up of 16.3 years, reported that a multimodal screening strategy consisting of longitudinal serum CA-125 levels interpreted by the risk of ovarian cancer algorithm (ROCA) calculation combined with transvaginal ultrasound findings, down-staged ovarian cancer but did not reduce ovarian cancer mortality75. Therefore, screening is not recommended for average-risk individuals according to the international guidelines from the National Comprehensive Cancer Network, the European Society of Medical Oncology, and the Society of Gynaecological Oncology and Ovarian Cancer Alliance76,77. A GOG trial involving 3692 high-risk women with a strong family history of BRCA1/2 pathogenic variants and a median follow-up of 6 years showed that ROCA-based multimodal screening every 3 months had better sensitivity and high spec- ificity for early-stage ovarian cancer 23. The UKFOCSS trial recruited 4348 high-risk women (≥ 10% lifetime risk) and per- formed ROCA-based multimodal screening every 4 months. This strategy resulted in downstaging of ovarian cancer after a median follow-up of 4.8 years. However, the impact on mor - tality could not be evaluated 42. A serum CA-125 level and transvaginal ultrasound screening findings remain an option with uncertain benefit for high-risk women who wish to delay or decline risk-reducing surgery76,77. Cancer Biol Med Vol xx, No x Month 2026 11 Artificial intelligence (AI)-enabled screening has recently emerged as a potential approach for early detection of ovarian cancer. Research involving 10,992 individuals (1 internal val- idation set of 3007 individuals and 2 external validation sets of 7985 individuals) from China used an AI model to inter - pret laboratory tests, achieved an area under the receiver-op- erating characteristic curve (AUC) of 0.949 in the internal validation set and an AUC of 0.88 in the external validation sets78. Another deep learning model using 17,119 ultrasound images from 3652 patients across 20 centers in 8 countries also reported promising diagnostic accuracy in detecting ovarian cancer79. The integration of AI into ovarian cancer screening offers a promising approach for improving early detection by uncovering complex, non-linear relationships within mul- ti-modal datasets that may elude traditional analysis. However, this potential is limited by significant challenges, including the “black-box” nature of many algorithms, which can obscure the reasoning underlying decisions. Rigorous external val- idation and prospective clinical trials are also necessary to demonstrate a tangible impact on patient outcomes, such as down-staging or reduced ovarian cancer mortality. Several novel biomarkers and screening strategies are under investigation, including DNA methylation biomark- ers80, circulating tumor (ct) DNA 81, glycosylated CA-125 82, and other candidate biomarkers, such as Osteopontin, Human Epididymis Protein 4, and so on 83. Targeted cell-free DNA methylation analysis had sensitivities for ovarian cancer of 83.1% (95% CI, 72.2–90.3%) across all stages and 50% (95% CI, 23.7–76.3%) in stage I based on the Circulating Cell-free Genome Atlas (CCGA) study84. Whether these new methods can achieve down-staging or reduce ovarian cancer mortality requires further investigation. Prevention of ovarian cancer Although ovarian cancer screening has limited efficacy, both non-surgical and surgical options are available to reduce ovar- ian cancer risk. Non-surgical prevention is primarily achieved through use of oral contraceptives 12. Oral contraceptive use is associated with a 40%–50% reduction in lifetime ovarian cancer risk among women at average risk 85. Women carrying BRCA1 or BRCA2 mutations are also advised to consider oral contracep- tive use for prevention86. A longer duration of oral contracep- tive use provides greater protection for average- and high-risk populations, although the potential risk of thrombosis should be considered 87,88. The levonorgestrel intrauterine device (LNG-IUD) has also been shown to reduce ovarian cancer risk in women at average risk for ovarian cancer89,90. Risk-reducing salpingo-oophorectomy (RRSO) can reduce ovarian cancer risk by 80%–97% in BRCA carriers and reduce the mortality rate. Therefore, for high-risk individuals who have completed childbearing, bilateral RRSO is recommended for pre-menopausal women with a ≥ 4% lifetime risk of ovar - ian cancer and post-menopausal women with a ≥ 5% life- time risk of ovarian cancer 72,91. BRCA1 mutation carriers are advised to undergo RRSO between 35 and 40 years of age, BRCA2 carriers between 40 and 45 years of age, and RAD51C, RAD51D, PALB2, and BRIP1 carriers ≥ 45 years of age 92. The timing of RRSO may be individualized based on family history and personal choices86. HRT is recommended for pre-meno- pausal women following RRSO if they do not have a personal history of breast cancer93,94. Risk-reducing salpingectomy with or without delayed oopho- rectomy (RRSDO) represents an alternative for premenopausal women who wish to retain ovarian function72,86. The multicenter non-randomized controlled TUBA study recruited 577 women with a BRCA1/2 pathogenic variant from the Netherlands and showed that women undergoing RRSDO reported a bet- ter menopause-related quality of life than women who under- went RRSO95. The USWISP study used a similar design in 190 women and reported that the RRSO group exhibited worsen- ing menopausal symptoms and greater decision regret 96. The long-term safety and prophylactic effect of RRSDO are under evaluation. The ongoing TUBA-WISP II trial aims to determine whether delayed oophorectomy after salpingectomy is non-in- ferior to immediate RRSO in reducing tubo-ovarian cancer risk. However, follow-up remains too short for conclusions 97. To date, RRSO remains the gold standard for risk reduction98. RRSO should not be undertaken for ovarian cancer pre- vention in women at average risk. Opportunistic bilateral salpingectomy (OBS) may be offered at the time of benign gynecologic surgery, after childbearing, and following coun- selling on benefits and risks with informed consent72,91. Endometriosis management should also be considered with respect to endometriosis-associated ovarian cancer. Medical or surgical treatment should be individualized according to age, reproductive plans, and disease characteristics99. Therapeutic landscape Although each subtype of ovarian cancer has various clin- ical features, molecular characteristics, and different prog- noses, the subtypes share a similar principle of treatment. Complete cytoreduction (R0 resection) remains the corner - stone of ovarian cancer treatment across disease stages and settings, including primary, interval, and secondary cytore- ductive surgery 100,101. Platinum-based combination chemo- therapy remains the standard first-line regimen for most histologic subtypes of ovarian cancer. The introduction of targeted therapy has transformed management paradigms. Bevacizumab, a monoclonal antibody targeting VEGF , is rec- ommended in combination with cytotoxic chemotherapy for stage II–IV disease, followed by maintenance therapy (ICON7 12 Li et al. Global epidemiology of ovarian cancer and GOG-218)102,103. However, neither trial showed a signifi- cant overall survival benefit in the entire population. Further analysis in ICON-7 demonstrated that the high-risk subgroup, defined by stage IV ovarian cancer, inoperable stage III dis- ease, or sub-optimally debulked (> 1 cm) stage III disease, received a significant overall survival benefit from bevaci- zumab administration with an HR of 0.78 (0.63–0.97). The analysis suggested that residual tumor burden, presumably producing VEGF , is necessary to enable bevacizumab to exert an effect on the tumor microenvironment. Poly (ADP-ribose) polymerase (PARP) inhibitors repre- sent a major therapeutic advance. Maintenance therapy with olaparib or niraparib, with or without bevacizumab, sub- stantially prolongs progression-free and overall survival in patients with germline BRCA1/2 mutations or homologous recombination deficiency (HRD) 104-106. In contrast, benefits in non-BRCA and HRD-proficient patients remain limited.

from immunotherapy trials have been largely disap- pointing107, which can be attributed to tumor heterogeneity as well as inherent or acquired immunotherapy resistance associated with the tumor microenvironment. However, recent combination regimens have shown promise. The DUO-O trial demonstrated that non-BRCA-mutated patients receiving chemotherapy, bevacizumab, durvalumab, and olaparib achieved a median progression-free survival (PFS) of 24.2 months (HR, 0.63 vs. control) 108. The KEYLYNK-001 trial reported an improved PFS (22.2 months; HR, 0.71) with chemotherapy plus pembrolizumab followed by olaparib maintenance109. Further biomarker development is required to enable more personalized therapeutic strategies.

and future perspectives The interpretation of global epidemiology is subject to heter - ogeneity in the methodologies and quality of the underlying cancer registries. Although the incidence of ovarian cancer has declined in some high-income countries, an upward trend persists in other countries. Globally, mortality has decreased, but despite advances in targeted therapy and other modali- ties, improvements in overall survival remain limited. Further exploration of underlying mechanisms is warranted. Modifying lifestyle and reproductive factors offers a feasible approach to reduce ovarian cancer risk. Women should be educated on the impact of reproductive decisions, physical activity, and diet on their future cancer risk. RRSO remains the most effective pre- ventive measure for high-risk women. Public health policies should focus on promoting awareness, managing modifiable risk factors, and facilitating access to preventive surgery. Future epidemiologic research should explore novel deter - minants to refine the understanding of ovarian cancer eti- ology. Large-scale multicenter cohort studies are needed to evaluate emerging factors, such as metabolomic signatures, gut microbiota composition, and chronic inflammatory states. The next frontier lies in the development of improved early detection strategies, in which AI and molecular biomarkers are potentially poised to play a role. Acknowledgments We thank the epidemiologists, researchers, and clinicians for their efforts to help ovarian cancer patients. Grant support This study was supported by Beijing Natural Science Foundation (Grant No. Z240004). Conflict of interest statement No potential conflicts of interest are disclosed. Author contributions Conceived and designed the analysis: Hongmei Zeng, Bin Li. Collected the data: Ruyuan Li, Anqi Zhao, Meicen Liu. Contributed data or analysis tools: Ruyuan Li, Lingeng Lu, Hongmei Zeng. Performed the analysis: Ruyuan Li. Wrote the paper: Ruyuan Li, Anqi Zhao.

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