Age, Tumor Metastasis, Surgical Treatment Contribute to Cardiovascular Mortality in Patients With Ovarian Cancer

The researchers identified age, tumor metastasis, and surgical treatment as key independent prognostic factors for cardiovascular mortality in patients with ovarian cancer, highlighting the need for individualized treatment and surveillance strategies.

Age, tumor metastasis, and surgical treatment are independent prognostic factors for cardiovascular mortality (CVM) in patients with ovarian cancer (OC), according to a study published in the Journal of Ovarian Research.1

Due to the lack of cancer-specific symptoms and effective screening tools, OC is typically diagnosed at an advanced stage, with high recurrence and mortality rates.2 More specifically, in 2020, there were about 313,959 new OC cases and 207,252 deaths (death rate, 66.01%).3

Simultaneously, the number of deaths caused by cardiovascular diseases gradually increased worldwide as past studies found that CVM increased by 2.1% over 10 years from 2007.4 Several past studies also showed that CVM risk is significantly higher in patients with cancer, with CVM risk varying dramatically between malignancies.1 For example, patients with endometrial cancer and colorectal cancer have 8.8- and 11.7-fold higher risks of CVM than the general population, respectively.5,6

However, no prediction of CVM risk in patients with OC has been retrieved.1 Because of this, the researchers conducted a study to identify independent risk factors of CVM in patients with OC to help guide individualized treatment and surveillance strategies.

Human heart animation | Image Credit: Siarhei -

Human heart animation | Image Credit: Siarhei -

The researchers used the Surveillance, Epidemiology, and End Results (SEER) database to create their study population. Eligible patients were those diagnosed clinically and/or histologically with OC; they also had available data on potential influencing variables, namely race, age, year of diagnosis, survival months, summary stage, chemotherapy recode, histological type, and surgical treatment.

The researchers determined the impact of prognosis-related independent risk factors through a univariate Cox analysis. Based on the identified risk factors, they developed a nomogram, “a visually friendly risk statistical prediction model that can provide better survival risk prediction for clinical patients.”

To assess the nomogram's predictive efficiency, the researchers used the receiver operating characteristic (ROC) curve and the area under the curve (AUC) values. Lastly, Harrell’s concordance index (C-index) was used to evaluate the model's ability to discriminate between observed and predicted outcomes; a higher C-index value indicated a better effect of different variables on survival outcomes.

The study population consisted of 88,653 patients with OC, the majority of whom were White (83.39%). The main age groups diagnosed with OC were those between 45 and 59 years (32.96%) and those between 60 and 74 years (34.44%). Additionally, most patients received surgical treatment (86.50%), including palliative surgery (49.12%) and cytoreductive surgery (36.39%); similarly, most patients (67.61%) received systemic therapy.

Of the study population, 52,139 died, 2282 of whom (4.38%) died from various cardiovascular diseases, namely atherosclerosis (1.1%), hypertension without heart disease (3.86%), cerebrovascular diseases (19.37%), or heart disease (69.50%). Therefore, heart disease remains the leading cause of CVM in patients with OC.

Through the univariate Cox analysis, the researchers found 7 variables significantly associated with overall survival (OS) time in patients with OC: race, age at diagnosis, chemotherapy, surgical method, histological type, time of diagnosis, and distant metastasis.

In particular, the univariate analysis showed that CVM was 16 times (HR, 16.34; 95% CI, 11.35-23.51; P < .001) and 33 times (HR, 33.81; 95% CI, 23.49-48.68; P < .001) higher when the age at diagnosis was 60 to 74 years or 75 years or older, respectively. It also found that a patient's OS significantly improved if their tumor did not develop distant metastasis (HR, 0.13; 95% CI, 0.13-0.14; P < .001).

After identifying the 7 risk factors, the researchers developed a nomogram to predict 12-, 36-, and 60-month OS in patients with OC. Their evaluation of the nomogram’s overall performance resulted in a C-index of 0.759 (95% CI, 0.757-0.761), indicating its sufficient discriminative power for prediction. Similarly, the researchers found that the AUC values of the ROC curve at 12, 36, and 60 months under the training model were 0.823 (95% CI, 0.789-0.858), 0.812 (95% CI, 0.785-0.839), and 0.831 (95% CI, 0.805-0.856), respectively; this means that the model has good discrimination ability.

Using the nomogram, the researchers observed the impact of the 7 independent risk factors on OS in patients with OC. The results showed that more than half of patients with OC suffer from CVM when they are over 60 years old (HR, 21.07; 95% CI, 5.21-85.30). Also, it showed that CVM risk in patients with OC who undergo chemotherapy is significantly lower (HR, 0.48; 95% CI, 0.44-0.52; P < .001). Lastly, the nomogram determined that those who received surgery were at a lower CVM risk. Overall, older age, distant metastasis, and a lack of surgical treatment are key factors in patients’ poor prognosis.

The researchers acknowledged their limitations, one being the exclusion of numerous important variables, like specific chemotherapy regimens, the presence of other malignant tumors, and income level; other variables not analyzed included education, marital status, secondary cytoreductive surgery, drinking, and smoking. They noted that these variables are highly likely to impact CVM risk, indicating the need for further research.

“This is likely to indicate that the risk of CVM in patients with OC is underestimated, and we need to conduct more in-depth population studies,” the authors concluded.


  1. Hu ZL, Yuan YX, Xia MY, et al. Cardiovascular mortality risk in patients with ovarian cancer: a population-based study. J Ovarian Res. 2024;17:88. doi:10.1186/s13048-024-01413-4
  2. Webb PM, Jordan SJ. Epidemiology of epithelial ovarian cancer. Best Pract Res Clin Obstet Gynaecol. 2017;41:3-14. doi:10.1016/j.bpobgyn.2016.08.006
  3. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209-249. doi:10.3322/caac.21660
  4. James SLG, Abate D, Abate KH, et al. Global, regional, and national incidence, prevalence, andyears lived with disability for 354 diseases and injuries for 195 countries and Territories, 1990-2017: a systematic analysis for the global burden of disease study 2017. Lancet. 2018;392(10159):1789-1858. doi:10.1016/s0140‑6736(18)32279‑7
  5. Felix AS, Bower JK, Pfeiffer RM, Raman SV, Cohn DE, Sherman ME. High cardiovascular disease mortality after endometrial cancer diagnosis: results from the Surveillance, Epidemiology, and End Results (SEER) Database. Int J Cancer. 2017;140(3):555-564. doi:10.1002/ijc.30470
  6. Gaitanidis A, Spathakis M, Tsalikidis C, Alevizakos M, Tsaroucha A, Pitiakoudis M. Risk factors for cardiovascular mortality in patients with colorectal cancer: a population-based study. Int J Clin Oncol. 2019;24(5):501-507. doi:10.1007/s10147-018-01382-x
Related Videos
dr mohamad mohty
dr ryan jacobs
Video 2 - 3 KOLs are featured in, "Assessing Limitations, Costs, Mobility and Cognition in Progressive Multiple Sclerosis"
Video 1 - 3 KOLs are featured in, "Multiple Sclerosis: Impact, Types, Pathophysiology, and Progression"
Justin Oldham, MD, MS, an expert on IPF
Justin Oldham, MD, MS, an expert on IPF
Chesahna Kindred, MD, MBA, FAAD, board-certified dermatologist, Kindred Hair & Skin Cente
A panel of experts on Alzheimer's disease
A panel of experts on Alzheimer's disease
Related Content
CH LogoCenter for Biosimilars Logo