Disease Burden and Attributable Risk Factors of Ovarian Cancer From 1990 to 2017: Findings From the Global Burden of Disease Study 2017

Zhou, Zhangjian; Wang, Xuan; Ren, Xueting; Zhou, Linghui; Wang, Nan; Kang, Huafeng

doi:10.3389/fpubh.2021.619581

Cited by 23 publications

(25 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inflammation can mediate and stimulate the production of tumor-promoting compounds, including cytokines, especially interleukin (IL) 6 and 8 and chemokines, as well as reactive oxygen species (ROS), tumor necrosis factor (TNF)-α and IL-1β, and lipid hydroperoxides ( Browning et al, 2018 ). These compounds can contribute to cell proliferation, malignant transformation, and cancer development ( Savant et al, 2018 , Zhou et al, 2021 , Crusz and Balkwill, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Etiopathogenesis of ovarian cancer. An inflamm-aging entity?

Sánchez‐Prieto

Sánchez-Borrego²,

Lubián-López³

et al. 2022

Gynecologic Oncology Reports

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Etiopathogenesis of ovarian cancer. An inflamm-aging entity?

Sánchez‐Prieto

Sánchez-Borrego²,

Lubián-López³

et al. 2022

Gynecologic Oncology Reports

View full text Add to dashboard Cite

“…Ovarian cancer (OC) accounts for 3.4% and 4.7% of new cancers and cancer-related deaths in women worldwide, with 313,959 new cases and 207,252 cancer-related deaths in 2020, respectively [ 1 ]. Globally, OC incidence, related deaths and disability-adjusted life-years doubled between 1990 and 2020 [ 1 , 2 , 3 ]. The overall mortality attributed to OC exceeds that of any other gynecological cancer [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…Globally, OC incidence, related deaths and disability-adjusted life-years doubled between 1990 and 2020 [ 1 , 2 , 3 ]. The overall mortality attributed to OC exceeds that of any other gynecological cancer [ 1 , 2 , 3 ]. This deadliest amongst all genital cancers will develop in 1.1–1.5% of women during their lifespan [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…The overall mortality attributed to OC exceeds that of any other gynecological cancer [ 1 , 2 , 3 ]. This deadliest amongst all genital cancers will develop in 1.1–1.5% of women during their lifespan [ 1 , 2 , 3 ]. The high mortality rates result from usually advanced stages at diagnosis (70% of OC are diagnosed in FIGO stage III/IV), the high biological aggressiveness of the most common histological subtype (high-grade serous OC (HGSOC) accounting for 75% of all ovarian malignancies) and the lack of effective screening strategies [ 2 , 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…This deadliest amongst all genital cancers will develop in 1.1–1.5% of women during their lifespan [ 1 , 2 , 3 ]. The high mortality rates result from usually advanced stages at diagnosis (70% of OC are diagnosed in FIGO stage III/IV), the high biological aggressiveness of the most common histological subtype (high-grade serous OC (HGSOC) accounting for 75% of all ovarian malignancies) and the lack of effective screening strategies [ 2 , 3 , 4 , 5 ]. Early diagnosis of OC is critical because the 5-year recurrence rates of OC in FIGO stage I are only 20% and the 10-year overall survival rates between 62% and 78% [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study

Watrowski

Obermayr

Wallisch

et al. 2022

Cancers

View full text Add to dashboard Cite

Ovarian cancer (OC) is the most lethal genital malignancy in women. We aimed to develop and validate new proteomic-based models for non-invasive diagnosis of OC. We also compared them to the modified Risk of Ovarian Malignancy Algorithm (ROMA-50), the Copenhagen Index (CPH-I) and our earlier Proteomic Model 2017. Biomarkers were assessed using bead-based multiplex technology (Luminex®) in 356 women (250 with malignant and 106 with benign ovarian tumors) from five European centers. The training cohort included 279 women from three centers, and the validation cohort 77 women from two other centers. Of six previously studied serum proteins (CA125, HE4, osteopontin [OPN], prolactin, leptin, and macrophage migration inhibitory factor [MIF]), four contributed significantly to the Proteomic Model 2021 (CA125, OPN, prolactin, MIF), while leptin and HE4 were omitted by the algorithm. The Proteomic Model 2021 revealed a c-index of 0.98 (95% CI 0.96, 0.99) in the training cohort; however, in the validation cohort it only achieved a c-index of 0.82 (95% CI 0.72, 0.91). Adding patient age to the Proteomic Model 2021 constituted the Combined Model 2021, with a c-index of 0.99 (95% CI 0.97, 1) in the training cohort and a c-index of 0.86 (95% CI 0.78, 0.95) in the validation cohort. The Full Combined Model 2021 (all six proteins with age) yielded a c-index of 0.98 (95% CI 0.97, 0.99) in the training cohort and a c-index of 0.89 (95% CI 0.81, 0.97) in the validation cohort. The validation of our previous Proteomic Model 2017, as well as the ROMA-50 and CPH-I revealed a c-index of 0.9 (95% CI 0.82, 0.97), 0.54 (95% CI 0.38, 0.69) and 0.92 (95% CI 0.85, 0.98), respectively. In postmenopausal women, the three newly developed models all achieved a specificity of 1.00, a positive predictive value (PPV) of 1.00, and a sensitivity of >0.9. Performance in women under 50 years of age (c-index below 0.6) or with normal CA125 (c-index close to 0.5) was poor. CA125 and OPN had the best discriminating power as single markers. In summary, the CPH-I, the two combined 2021 Models, and the Proteomic Model 2017 showed satisfactory diagnostic accuracies, with no clear superiority of either model. Notably, although combining values of only four proteins with age, the Combined Model 2021 performed comparably to the Full Combined Model 2021. The models confirmed their exceptional diagnostic performance in women aged ≥50. All models outperformed the ROMA-50.

show abstract

The global, regional and national epidemiology, incidence, mortality, and burden of ovarian cancer

Mazidimoradi

Momenimovahed

Allahqoli

et al. 2022

Health Science Reports

View full text Add to dashboard Cite

Background Ovarian cancer has the highest mortality rate among gynecological malignancies and is associated with poor prognosis. Since the accurate assessment of the global burden along with the trend of cancers contributes to the development of policies, this study aimed to explain the incidence, mortality, and burden of ovarian cancer using the global burden of disease (GBD) 2019 study. Methods Epidemiological data have been collected from the study of the GBD 2019. Data were extracted globally for 204 countries and groups based on a socio‐demographic index (SDI), WHO regions, continents, World Bank regions, and 22 GBD regions. Results In 2019, a total of 294,422 new cases of ovarian cancer were reported. The highest age‐standardized incidence rate (ASIR) was reported in areas with higher SDI, World high‐income countries, continental Europe, and then America. In GBD regions, the highest age‐standardized incidence is in Central Europe. In 2019, a total of 198,412 deaths due to ovarian cancer were reported. The highest ASR death is related to countries with high SDI and the World Bank high‐income countries. In 2019, adjusted years of life with disabilities (DALYs) due to ovarian cancer were reported to be 5,359,737, of which 5,205,660 were related to lost years of life (YLLs), and 154,077 were related to years of life with disabilities (YLDs). Conclusions In 2019, the highest age‐standardized incidence of ovarian cancer, ASR death, and DALYs ASR belong to the high SDI countries. Designing interventions based on risk factors as well as providing preventive approaches to reduce the risk of this cancer, improving the treatment of ovarian cancer, and using appropriate and invasive treatments are recommended.

show abstract

Disease Burden and Attributable Risk Factors of Ovarian Cancer From 1990 to 2017: Findings From the Global Burden of Disease Study 2017

Cited by 23 publications

References 41 publications

Etiopathogenesis of ovarian cancer. An inflamm-aging entity?

Etiopathogenesis of ovarian cancer. An inflamm-aging entity?

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study

The global, regional and national epidemiology, incidence, mortality, and burden of ovarian cancer

Contact Info

Product

Resources

About