Incidence of different histologic subtype of ovarian cancer in China: a population-based cancer registry study.

This analysis employed data from the Cancer Incidence in Five Continents, Volume XII (CI5-XII) database between 2013 and 2017. CI5-XII is the most authoritative compendium of real-world data in the field of oncology epidemiology, first published in 1966 (Volume I) and updated every 5 years by the International Agency for Research on Cancer (IARC) and the International Association of Cancer Registries (IACR) ( https://ci5.iarc.who.int/ci5-xii/ ). CI5-XII has been updated to Volume XII with global cancer incidence data from 2013 to 2017, and it contains data from 460 population-based cancer registries in 65 countries [ 21 ]. Data on ovarian cancer incidence of different histological subtypes from Chinese registries in CI5-XII were employed. Exclusion criteria comprised: (1) those under 20 years old; (2) the person-year at risk is 0 in one of the four subtypes at the province level; and (3) the number of cases is 0 in one of the four subtypes at the province level. Ovarian cancer and its histological subtypes were determined by the third edition of the International Classification of Diseases for Oncology (ICD-O-3) codes: overall ovarian cancer (C56), serous carcinoma (8441, 8460–8463, 9014), mucinous carcinoma (8470–8490, 9015), endometrioid carcinoma (8380–8383, 8560, 8570), clear cell carcinoma (8310–8313, 9110), adenocarcinoma, NOS (8140–8147, 8170–8190, 8211–8231, 8260, 8384, 8440, 8576), other specified carcinoma, unspecified carcinoma (8010–8035), sex cord-stromal tumor (8590–8671), germ cell tumor (8240–8245, 9060–9102), other morphology, and unspecified morphology (8000–8005). This analysis was exempt from ethical approval and informed consent due to the utilize of publicly available anonymized data extracted from the CI5-XII database. For the histological subtypes of ovarian cancer, five subtype classifications were applied for analysis: SC, MC, EC, CCC, and others. Other categories included unidentified subtypes of ovarian cancer, such as adenocarcinoma, NOS, other specified carcinoma, unspecified carcinoma, sex cord-stromal tumor, germ cell tumor, and other morphology, and unspecified morphology. The 34 provincial administrative regions of China are divided into six major administrative regions according to geographical distribution: Northeast (e.g., Liaoning), North China (e.g., Hebei), Northwest (e.g., Shaanxi), East China (e.g., Jiangsu), Central South (e.g., Guangdong), and Southwest (e.g., Sichuan). However, the CI5-XII database only records data from 20 common provincial administrative regions. Furthermore, these provinces were ranked based on the Gross Domestic Product (GDP) levels announced by the National Bureau of Statistics of China in 2015 ( https://www.stats.gov.cn/sj/ndsj/2016/indexch.htm ), and were divided into three economic level groups according to the tertiles of their GDP levels (Supplement Table 1): low (e.g., Qinghai), medium (e.g., Hubei), and high (e.g., Beijing). The composition ratio of each histological subtype was visualized using stacked bar graphs. The proportions of different subtypes under different provinces, major administrative regions, and economic level groupings were also visualized using stacked bar charts. The age-standardized incidence rates (ASR) per 100,000 people of ovarian cancer and its histologic subtypes under different provinces, administrative regions, and economic level subgroups were calculated (based on the 5-year age group), and the ASR under different provinces were visualized through heat maps. ASR was calculated according to the formula [ 22 ]: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{ASR}={\textstyle\sum_i}\;d_i\;w_i/y_i$$\end{document} , where i is the age group, d i is the number of cases in age group i, y i is the number of person-years at risk in age group i, and w i is the number of individuals in age group i in the world standard population. Furthermore, the crude incidence rates of ovarian cancer and its histological subtypes in different age groups were calculated and visualized by grouped line graphs. The crude rate per 100,000 per year was calculated using the following formula [ 22 ]: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{crude}\;\mathrm{rate}\;=10^5\left({\textstyle\sum_i}di\right)/\left({\textstyle\sum_i}\;y_i\right)$$\end{document} . Statistical analysis and visualization were accomplished using R 4.5.0 software (R Foundation for Statistical Computing, Vienna, Austria): The “readr” package is used for reading data; the “dplyr” package is used for data cleaning; the “ggplot2”, “geojsonio”, “sf”, “lwgeom”, and “ggrepel” packages are used for creating heatmaps and processing geographic location information.

The CI5-XII database recorded 33,780 ovarian cancer populations in China. After applying exclusion criteria to 936 cases, the remaining 32,817 cases were deemed eligible for analysis (Fig.  1 ). The proportions of ovarian cancer histological subtypes in China and its six major administrative regions (Fig.  2 A), different provinces (Fig.  2 B), and different economic level groups (Fig.  2 C) are listed in Fig.  2 . In China, SC was the main histological subtype of ovarian cancer, accounting for 23.59%, followed by MC (5.21%), CCC (4.02%), and EC (3.76%). Among the six major administrative regions, SC and CCC were most prevalent in the Northeast and North China, MC in the Northeast and Central South, and EC in the North China and Central South. For different provinces of China, SC was most prevalent in Beijing and lowest in Henan. The highest CCC prevalence was recorded in Beijing, with the lowest in Inner Mongolia. Jilin exhibited the highest prevalence of MC, while Jiangsu showed the lowest rate. EC was most frequent in Guangdong and rarest in Sichuan. Among different economic level groups, the distribution of histological subtypes varies among different economic level groups. SC, CCC, and EC occur more frequently in the high economic level group, while the occurrence of MC does not change significantly among different economic level groups. Fig. 1 Flow chart for the study population Flow chart for the study population Fig. 2 The proportions of ovarian cancer histological subtypes in China. A six major administrative regions; ( B ) different provinces of China; ( C ) different economic level groups The proportions of ovarian cancer histological subtypes in China. A six major administrative regions; ( B ) different provinces of China; ( C ) different economic level groups Table  1 lists the number and ASR of ovarian cancer and its histological subtypes in China and its six major administrative regions between 2013 and 2017. Among these 32,817 ovarian cancer cases in China, SC accounted for 7,742 (23.59%), MC for 1,709 (5.21%) cases, EC for 1,233 (3.76%) cases, CCC for 1,319 (4.02%) cases, and other unidentified subtypes for 20,814 (64.42%) cases. Among the unidentified subtypes of ovarian cancer, there were 6,873 (20.94%) cases of adenocarcinoma (NOS), 1,603 (4.88%) cases of other specified carcinoma, 1,611 (4.91%) cases of unspecified carcinoma, 285 (0.87%) cases of sex cord-stromal tumor, 932 (2.84%) cases of germ cell tumor, and 9,510 (28.98%) cases of other subtypes. The corresponding ASR was 5.31 (95%CI: 5.26–5.37) per 100,000 people for overall ovarian cancer, 1.27 (95%CI: 1.24–1.29) for SC, 0.30 (95%CI: 0.28–0.31) for MC, 0.21 (95%CI: 0.20–0.22) for EC, 0.22 (95%CI: 0.21–0.23) for CCC, and 0.47 (95%CI: 0.47–0.48) for other subtypes. For the six major administrative regions, the ASR of MC [0.41 (95%CI: 0.34–0.48) per 100,000 people] was highest in the Northeast, while the ASRs of EC [0.29 (95%CI: 0.25–0.33) per 100,000 people], CCC [0.44 (95%CI: 0.39–0.49) per 100,000 people], and SC [1.87 (95%CI: 1.77–1.97) per 100,000 people] were highest in the North China. The ASRs for unidentified subtype ovarian cancer in six major administrative regions are listed in Supplement Table 2. Table 1 The number and ASR of ovarian cancer and its histological subtypes in China and its six major administrative regions Regions Ovary SC MC EC CCC Other subtypes ASR (95%CI) Case ASR (95%CI) Case ASR (95%CI) Case ASR (95%CI) Case ASR (95%CI) Case ASR (95%CI) Case China 5.31 (5.26, 5.37) 32,817 1.27 (1.24, 1.29) 7742 0.30 (0.28, 0.31) 1709 0.21 (0.20, 0.22) 1233 0.22 (0.21, 0.23) 1319 0.47 (0.47, 0.48) 20,814 North China 6.13 (5.95, 6.31) 4598 1.87 (1.77, 1.97) 1387 0.28 (0.24, 0.32) 191 0.29 (0.25, 0.33) 209 0.44 (0.39, 0.49) 321 0.47 (0.45, 0.48) 2332 East China 4.92 (4.84, 5.00) 16,138 1.15 (1.11, 1.18) 3727 0.25 (0.23, 0.27) 760 0.17 (0.15, 0.18) 536 0.19 (0.17, 0.20) 594 0.45 (0.44, 0.46) 9801 Central South 5.59 (5.47, 5.71) 8052 1.12 (1.07, 1.18) 1594 0.37 (0.34, 0.41) 516 0.27 (0.24, 0.30) 386 0.17 (0.15, 0.19) 243 0.52 (0.51, 0.54) 4884 Northeast 5.67 (5.43, 5.92) 2220 1.79 (1.65, 1.92) 688 0.41 (0.34, 0.48) 148 0.21 (0.16, 0.26) 77 0.29 (0.24, 0.35) 114 0.42 (0.40, 0.45) 1064 Southwest 5.57 (5.30, 5.85) 1631 1.11 (0.99, 1.24) 321 0.30 (0.24, 0.37) 86 0.07 (0.04, 0.11) 23 0.14 (0.10, 0.18) 41 0.56 (0.53, 0.60) 1024 Northwest 7.21 (6.12, 8.31) 178 1.09 (0.64, 1.55) 25 0.31 (0.09, 0.53) 8 0.07 (-0.03, 0.17) 2 0.21 (0.04, 0.39) 6 0.79 (0.65, 0.92) 127 SC serous carcinoma, MC mucinous carcinoma, EC endometrioid carcinoma, CCC clear cell carcinoma, ASR age-standardized incidence rates, CI confidence interval The number and ASR of ovarian cancer and its histological subtypes in China and its six major administrative regions SC serous carcinoma, MC mucinous carcinoma, EC endometrioid carcinoma, CCC clear cell carcinoma, ASR age-standardized incidence rates, CI confidence interval The number and ASR of histological subtypes in different economic level groups are presented in Table  2 . The ASR for overall ovarian cancer was 5.26 (95%CI: 5.19–5.33) per 100,000 people in the high economic level group, 5.48 (95%CI: 5.35–5.61) in the medium economic level group, and 5.52 (95%CI: 5.28–5.76) in the low economic level group. Among the histological subtypes, the ASRs for SC [1.29 (95%CI: 1.25–1.32) per 100,000 people], CCC [0.24 (95%CI: 0.23–0.26) per 100,000 people], and EC [0.23 (95%CI: 0.22–0.25) per 100,000 people] were highest in the high economic level group. The number and ASR for unidentified subtype ovarian cancer in different economic level groups are demonstrated in Supplement Table 3. Table 2 The number and ASR of histological subtypes in different economic level groups in China Economic level Ovary SC MC EC CCC Other subtypes ASR Case ASR Case ASR Case ASR Case ASR Case ASR Case China 5.31 (5.26, 5.37) 32,817 1.27 (1.24, 1.29) 7742 0.30 (0.28, 0.31) 1709 0.21 (0.20, 0.22) 1233 0.22 (0.21, 0.23) 1319 0.47 (0.47, 0.48) 20,814 High 5.26 (5.19, 5.33) 23,979 1.29 (1.25, 1.32) 5833 0.29 (0.27, 0.30) 1202 0.23 (0.22, 0.25) 1013 0.24 (0.23, 0.26) 1071 0.46 (0.45, 0.47) 13,825 Medium 5.48 (5.35, 5.61) 6759 1.20 (1.14, 1.26) 1457 0.33 (0.30, 0.37) 391 0.13 (0.11, 0.15) 159 0.15 (0.13, 0.17) 185 0.52 (0.51, 0.54) 4194 Low 5.52 (5.28, 5.76) 2079 1.20 (1.09, 1.31) 452 0.32 (0.26, 0.38) 116 0.17 (0.12, 0.21) 61 0.16 (0.12, 0.21) 63 0.52 (0.50, 0.55) 1213 SC serous carcinoma, MC mucinous carcinoma, EC endometrioid carcinoma, CCC clear cell carcinoma, ASR age-standardized incidence rates The number and ASR of histological subtypes in different economic level groups in China SC serous carcinoma, MC mucinous carcinoma, EC endometrioid carcinoma, CCC clear cell carcinoma, ASR age-standardized incidence rates The number and ASR of histological subtypes in different provinces are summarized in Supplement Table 4 and visualized in Fig.  3 . Higher ASR of overall ovarian cancer was observed in Beijing [7.27 (95%CI: 6.98–7.57) per 100,000 people], Qinghai [7.21 (95%CI: 6.12–8.31) per 100,000 people], and Chongqing [6.95 (95%CI: 6.38–7.52) per 100,000 people] (Fig.  3 A). Beijing [2.82 (95%CI: 2.63-3.00) per 100,000 people] exhibited the highest ASR for SC, followed by Liaoning [1.83 (95%CI: 1.66-2.00) per 100,000 people] and Chongqing [1.75 (95%CI: 1.46–2.04) per 100,000 people] (Fig.  3 B). Jilin [0.48 (95%CI: 0.32–0.64) per 100,000 people], Guangdong [0.48 (95%CI: 0.43–0.54) per 100,000 people], and Liaoning [0.40 (95%CI: 0.32–0.49) per 100,000 people] showed a higher ASR for MC (Fig.  3 C). Higher ASR of EC was shown in Guangdong [0.44 (95%CI: 0.39–0.50) per 100,000 people], Beijing [0.43 (95%CI: 0.35–0.50) per 100,000 people], and Heilongjiang [0.36 (95%CI: 0.17–0.55) per 100,000 people] (Fig.  3 D). Beijing [0.84 (95%CI: 0.74–0.94) per 100,000 people] and Shanghai [0.53 (95%CI: 0.47–0.59) per 100,000 people] presented a higher ASR of CCC (Fig.  3 E). For other unidentified subtypes of ovarian cancer, higher ASR was found in Qinghai [0.79 (95%CI: 0.65–0.92) per 100,000 people], Hubei [0.65 (95%CI: 0.62–0.68) per 100,000 people], and Chongqing [0.63 (95%CI: 0.56–0.69) per 100,000 people] (Fig.  3 F). The detailed ASRs for the unidentified subtypes of ovarian cancer in different provinces are presented in Supplement Table 5. Fig. 3 The ASR distribution of histological subtypes of ovarian cancer in different provinces in China. A distribution of overall ovarian cancer; ( B ) distribution of SC; ( C ) distribution of MC; ( D ) distribution of EC; ( E ) distribution of CCC; ( F ) distribution of other subtypes. SC, serous carcinoma; MC, mucinous carcinoma; EC, endometrioid carcinoma; CCC, clear cell carcinoma; ASR, age-standardized incidence rates The ASR distribution of histological subtypes of ovarian cancer in different provinces in China. A distribution of overall ovarian cancer; ( B ) distribution of SC; ( C ) distribution of MC; ( D ) distribution of EC; ( E ) distribution of CCC; ( F ) distribution of other subtypes. SC, serous carcinoma; MC, mucinous carcinoma; EC, endometrioid carcinoma; CCC, clear cell carcinoma; ASR, age-standardized incidence rates The crude incidence rates of ovarian cancer and its histological subtypes in China and its different economic level groups are listed in Fig.  4 . The crude incidence rates of overall ovarian cancer in China and its different economic level groups showed a larger change trend, first increasing and then decreasing with age, with the downward trend occurring roughly at the age of 60. However, the crude incidence rates of overall ovarian cancer worldwide exhibited an increasing trend with age. Changes in crude incidence rates for SC were similar to those of overall ovarian cancer, while changes in crude incidence rates for CCC, EC, MC, and other subtypes were not distinct. Fig. 4 The crude incidence rates of ovarian cancer and its histological subtypes in China and its different economic level groups. A the crude incidence rates in the high economic level group; ( B ) the crude incidence rates in the medium economic level group; ( C ) the crude incidence rates in the low economic level group; ( D ) the crude incidence rates in China; ( E ) the crude incidence rates in global. SC, serous carcinoma; MC, mucinous carcinoma; EC, endometrioid carcinoma; CCC, clear cell carcinoma The crude incidence rates of ovarian cancer and its histological subtypes in China and its different economic level groups. A the crude incidence rates in the high economic level group; ( B ) the crude incidence rates in the medium economic level group; ( C ) the crude incidence rates in the low economic level group; ( D ) the crude incidence rates in China; ( E ) the crude incidence rates in global. SC, serous carcinoma; MC, mucinous carcinoma; EC, endometrioid carcinoma; CCC, clear cell carcinoma

Ovarian cancer is the eighth most common cancer in women worldwide. This analysis provided evidence of the incidence of ovarian cancer and its histological subtypes in China. Our findings revealed that SC (23.59%) was the main histological subtype of ovarian cancer in China, followed by MC (5.21%) and CCC (4.02%). The distribution of different histologic subtypes varied over different geographic regions in China. SC and CCC occurred most in the Northeast and North China, MC in the Northeast and Central South, and EC in the North China and Central South. Furthermore, the distribution of histological subtypes also varied across economic level regions, with higher frequencies of SC, CCC, and EC in the high economic level group. Ovarian cancer is highly heterogeneous, with over 90% being epithelial cancers and only a small portion derived from stromal cells [ 7 ]. Common histologic subtypes such as SC, MC, CCC, and EC are derived from epithelial cancers. SC, representing 42.97% of global ovarian cancer cases, stands as the predominant form of epithelial carcinoma [ 23 ]. Our findings revealed that SC was also the most common histologic subtype of ovarian cancer in China, accounting for 23.59% of all cases. Many of the factors that influence the development of different subtypes of ovarian cancer overlap, such as parity, full-term pregnancy, and oral contraceptive pill, but there are still differences between subtypes [ 7 , 24 ]. Family history of ovarian cancer is an important risk factor for high-grade SC, while smoking increases the risk of aggressive and borderline MC [ 7 , 12 ]. Endometriosis and older age at menopause increase the risk of CCC and EC, while tubal sterilization decreases the risk of these subtypes [ 7 , 24 ]. Our results indicated that there were differences in the distribution of histological subtypes in different regions of China: SC and CCC occurred most in the Northeast and North China, MC in the Northeast and Central South, and EC in the North China and Central South. This regional distribution difference may be related to climate, environment, and diet. There are distinct differences in climate, environment, and diet among the six major administrative regions in China. Previous studies indicated that a significant correlation was observed between prolonged exposure to high ambient temperatures and gynecologic cancers (including ovarian cancer) [ 25 ]. A prospective study revealed that environmental temperature affects the state of the ovaries and that higher temperatures may accelerate ovarian aging [ 26 ]. Furthermore, diet has also been reported to be linked to ovarian cancer risk and survival [ 27 – 29 ]. Ovarian cancer risk showed negative correlations with black tea consumption and calcium intake, while demonstrating positive correlations with skimmed/low-fat milk and lactose consumption [ 27 ]. Lifestyle factors such as BMI, physical activity, sedentary behavior, and tobacco and alcohol consumption also influence the risk of ovarian cancer [ 7 ]. However, there remains a lack of understanding and evidence regarding the impact of climate, environment, and diet on the development of ovarian cancer across different histological subtypes. Future research may need to explore the influence of these factors on different histological subtypes of ovarian cancer. The distribution of different subtypes of ovarian cancer also varies in regions with different economic levels in China. Our findings indicated that the ASRs for SC, MC, and EC were highest in the high economic level group. Previous studies have reported a complex relationship between socioeconomic development level and ovarian cancer risk: higher levels of socioeconomic development are linked to higher ASR, but in some areas, there is a tendency for ASR to decrease when the level of socioeconomic development exceeds a certain value [ 30 ]. Furthermore, our results revealed that the crude incidence rates of overall ovarian cancer and SC subtypes in China increased with age, but showed a decreasing trend at age 60 years. The crude incidence rates of CCC, EC, MC, and other subtypes do not change distinctly with age. Research on the global trend of ovarian cancer incidence also presented that the incidence of SC increases steadily with age, reaching its peak between the ages of 70 and 74 [ 31 ]. This suggests that the decline in ovarian cancer incidence after age 60 in China may be caused by competitive mortality or reporting differences, rather than an actual biological decline. This requires subsequent research for further confirmation. In addition, preventive tubal resection and screening for susceptibility genes are important measures for the prevention and early detection of SC subtypes [ 7 ]. Approximately 15% to 20% of women diagnosed with epithelial ovarian cancer have genetic susceptibility, among which BRCA1 and BRCA2 mutations are the most common [ 32 ]. BRCA1 and BRCA2 mutations have been identified as risk factors for high-grade SC [ 33 ]. The lifetime risk of ovarian cancer in BRCA1 mutation patients is 40%-60%, while the lifetime risk in BRCA2 mutation patients is 11%-27% [ 34 ]. This study is the first to analyze the incidence of ovarian cancer in different regions and age groups in China based on different histological subtypes, which provides a reference for formulating more targeted screening and prevention strategies. Furthermore, this analysis is based on the latest CI5 data (data from 20 provincial administrative regions in China, 147 survey sites), which has a wider coverage than the previous data, and the data were subjected to strict quality control. Nevertheless, several limitations need to be declared. First, some provinces, especially less economically developed areas, still lack data due to the data quality requirements of the CI5 database. Second, regional differences in pathology practice and documentation quality may introduce classification bias, thereby compromising the accuracy of findings. Third, there are differences in pathological characteristics and prognosis between high-grade and low-grade SCs, this study was unable to further distinguish between high-grade and low-grade SCs due to the lack of classification information in the database. More detailed incidence data need to be collected in the future. Fourth, 64.42% of the patients included in the analysis remained unspecified in terms of histologic subtype, and the results may be biased and should be interpreted with caution.

This exploratory analysis assessed the incidence distribution of the histologic subtype of ovarian cancer in China. SC was the main histological subtype of ovarian cancer in China, followed by MC and CCC. For regional distribution, SC and CCC occurred most in the Northeast and North China, MC in the Northeast and Central South, and EC in the North China and Central South. The distribution of histological subtypes also varied across economic level regions, with higher frequencies of SC, CCC, and EC in the high economic level group. However, the accuracy of these exploratory findings depends on the completeness and consistency of data from various cancer registry systems.

Ovarian cancer, which encompasses malignant tumors originating from ovarian epithelial cells, mesenchymal cells, or germ cells, is one of the most fatal gynecological malignancies worldwide [ 1 ]. Global statistics indicate that ovarian cancer resulted in an estimated 206,839 deaths and 324,398 newly diagnosed cases annually in 2022 [ 2 ]. Asymptomatic early stages and nonspecific symptoms (e.g., bloating, pelvic pain) lead to late diagnosis in 70% ovarian cancer patients, severely impacting survival [ 3 ]. In recent years, the standardized incidence and mortality rates of ovarian cancer in Chinese women have shown a significant upward trend [ 4 – 6 ]. The incidence and mortality rates of ovarian cancer in China in 2019 were 79.19% and 58.93% higher than in 1990, respectively [ 5 ]. Furthermore, the burden of ovarian cancer in China may continue to grow at a higher rate than the global level in the future [ 5 , 6 ]. Histologically, 90% of ovarian cancers are epithelial tumors, including serous carcinoma (SC), mucinous carcinoma (MC), endometrioid carcinoma (EC), and clear cell carcinoma (CCC) subtypes [ 7 ]. Different histologic subtypes of ovarian cancer have unique origins and molecular genetic mechanisms [ 8 – 10 ] and exhibit different clinicopathologic features [ 11 ]. Moreover, there are distinct differences in risk factors related to different histologic subtypes, with reproductive-related factors strongly correlated with EC and CCC, while smoking is correlated with an increased risk of MC, and obesity may be more associated with EC [ 12 – 14 ]. For prognosis, the survival of SC and EC subtypes may be higher in stage III/IV ovarian cancer individuals, whereas survival is poorer in MC and CCC patients [ 15 – 17 ]. Additionally, high-grade and low-grade SCs also differ in morphological and genetic characteristics, pathogenesis, and clinical behaviors [ 18 , 19 ]. High-grade SC is the most common subtype, which is clinically aggressive and usually fatal, but is sensitive to chemotherapy [ 18 ]. Ovarian cancers of different histological subtypes not only exhibit distinct pathological characteristics but also vary in treatment availability and accessibility [ 20 ]. This makes histological subtype a significant factor influencing diagnostic and therapeutic decisions for ovarian cancer. Therefore, it is necessary to estimate the disease burden of ovarian cancer according to different histologic subtypes. For the vast geographic area of China, there are large differences in relevant risk factors and the current status of cancer prevention and control in different regions, and evidence of ovarian cancer incidence in different regions based on histologic subtypes is still lacking. Furthermore, some studies have revealed that the incidence of ovarian cancer in Chinese women peaks near menopause [ 5 ], but the trend of age-dependent changes in the incidence of different subtypes is also unclear in Chinese women. Thus, this analysis intends to examine the regional differences in the incidence rates of different histologic subtypes of ovarian cancer, as well as the changes in the incidence in different age groups based on the database data of a large sample, to provide a reference for the screening, prevention, and control of the disease in the Chinese population.

Supplementary Material 1. Supplementary Material 1.