Cardiovascular Mortality in Ovarian Cancer Patients: An Analysis of Patient Characteristics Using the SEER Database.

Background and Objectives: Cardiovascular disease (CVD) is a major contributor to the high mortality rate among individuals with ovarian cancer. Nevertheless, there is limited understanding regarding the specific patient attributes that might impact the risk of CVD in this group. Materials and Methods: A retrospective cohort study was performed using the SEER database to analyze primary ovarian cancer cases from 2000 to 2019. Multivariable logistic regression analysis was employed to identify patient characteristics linked to cardiovascular mortality. Results: The cohort included 41,930 cases of patients who were alive, 54,829 cases of cancer-related deaths, 3003 cases of cardiovascular-related deaths, and 10,238 cases with other causes of death. Poorly differentiated cancer cells and distant metastasis were associated with a higher risk of cardiovascular mortality. Logistic regression analysis identified age, year of diagnosis, race, laterality, and staging as significant risk factors for cardiovascular cause of death. The risk of cardiovascular cause of death was lower in patients aged 31-60 and higher in those aged over 60 years old, and the risk also increased with a later year of diagnosis. Patients who were not white were at a higher risk of cardiovascular cause of death. Additionally, bilateral ovarian cancer and distant staging disease were linked to elevated risks of cardiovascular cause of death. Conclusion: Cardiovascular mortality is a significant concern in ovarian cancer patients, and several patient characteristics are associated with an increased risk. Our study suggests that targeted interventions to improve cardiovascular health in high-risk patients, such as those with comorbidities or an advanced stage at diagnosis, may improve survival in this population.

Association between polycystic ovary syndrome and the risk of malignant gynecologic cancers (ovarian, endometrial, and cervical): A population-based study from the U.S.A. National Inpatient Sample 2016-2019.

OBJECTIVE: This study aimed to systematically examine the relationship between polycystic ovary syndrome and ovarian, endometrial, and cervical cancers using the National Inpatient Sample (NIS) database. METHODS: We utilized the International Classification of Diseases (ICD-10) system to identify relevant codes from the NIS database (2016-2019). Univariate and multivariable regression analyses (adjusted age, race, hospital region, hospital teaching status, income Zip score, smoking, alcohol use, and hormonal replacement therapy) were conducted to evaluate association between PCOS and gynecologic cancers. Results were summarized as odds ratio (OR) with 95% confidence intervals (CI). RESULTS: Overall, 15,024,965 patients were analyzed, of whom 56,183 and 14,968,782 patients were diagnosed with and without PCOS, respectively. Among the patients diagnosed with gynecologic cancers (n = 91,599), there were 286 with PCOS and 91,313 without PCOS. Univariate analysis revealed that PCOS was significantly associated with higher risk of endometrial cancer (OR = 1.39, 95 % CI [1.18-1.63], p < 0.0001), but lower risk of ovarian cancer (OR = 0.55, 95 % CI [0.45-0.67], p < 0.0001) and cervical cancer (OR = 0.68, 95 % CI [0.51-0.91], p = 0.009). In contrast, after Bonferroni correction, multivariable analysis depicted that PCOS remained significantly associated with higher risk of endometrial cancer (OR = 3.90, 95 % CI [4.32-4.59], p < 0.0001). There was no significant correlation between PCOS and risk of ovarian cancer (OR = 1.09, 95 % CI [0.89-1.34], p = 0.409) and cervical cancer (OR = 0.83, 95 % CI [0.62-1.11], p = 0.218). CONCLUSION: This first-ever NIS analysis showed that patients with PCOS exhibited unique gynecologic cancer risk profiles, with higher risk for endometrial cancer, and no significant risk for ovarian or cervical cancers.

Association between Endometriosis and the Risk of Ovarian, Endometrial, Cervical, and Breast Cancer: A Population-Based Study from the U.S. National Inpatient Sample 2016-2019.

OBJECTIVE: We investigated the potential relationship between endometriosis and risk of ovarian, endometrial, cervical, and breast cancers using the National Inpatient Sample (NIS) database. METHODS: We utilized the International Classification of Diseases (ICD-10) system to identify relevant codes from the NIS database (2016-2019). Univariate and multivariate regression analyses (adjusted for age, race, hospital region, hospital teaching status, income Zip score, smoking, alcohol use, and hormonal replacement therapy) were conducted to evaluate the association between endometriosis and gynecologic cancers and summarized as odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: In the examined dataset, there were 1164 and 225,323 gynecologic cancer patients with and without endometriosis, respectively. Univariate analysis showed endometriosis was significantly associated with a higher risk of ovarian (OR = 3.42, 95% CI: 3.05-3.84, p < 0.001) and endometrial (OR = 3.35, 95% CI: 2.97-3.79, p < 0.001) cancers. There was no significant association between endometriosis and cervical cancer (OR = 1.05, 95% CI: 0.85-1.28, p = 0.663). Interestingly, endometriosis was significantly associated with a low risk of breast cancer (OR = 0.12, 95% CI: 0.10-0.17, p < 0.001). Multivariate analysis after Bonferroni correction (p < 0.006) showed that endometriosis was significantly associated with a high risk of ovarian (adjusted OR = 3.34, 95% CI: 2.97-3.75, p < 0.001) and endometrial (adjusted OR = 3.61, 95% CI: 3.12-4.08, p < 0.001) cancers. Conversely, there was no significant association between endometriosis and cervical cancer (OR = 0.80, 95% CI: 0.65-0.99, p = 0.036). CONCLUSIONS: Patients with endometriosis exhibited unique gynecologic cancer risk profiles, with higher risks for ovarian and endometrial cancers, and no significant risk for cervical cancer. The observed connection between endometriosis and a reduced risk of breast cancer remains a perplexing phenomenon, which cannot be put into context to date.