Cardiovascular mortality risk in patients with ovarian cancer: a population-based study.

OBJECTIVES: Ovarian cancer (OC) can occur at different ages and is affected by a variety of factors. In order to evaluate the risk of cardiovascular mortality in patients with ovarian cancer, we included influencing factors including age, histological type, surgical method, chemotherapy, whether distant metastasis, race and developed a nomogram to evaluate the ability to predict occurrence. At present, we have not found any correlation studies on cardiovascular death events in patients with ovarian cancer. This study was designed to provide targeted measures for effective prevention of cardiovascular death in patients with ovarian cancer. METHODS: Kaplan-Meier analysis and multivariable Cox proportional model were performed to evaluate the effectiveness of cardiovascular diseases on overall survival (OS) and ovarian cancer-specific survival (OCSS). We compared multiple groups including clinical, demographic, therapeutic characteristics and histological types. Cox risk regression analysis, Kaplan-Meier survival curves, and propensity score matching were employed for analyzing the data. RESULTS: A total of 88,653 ovarian cancer patients were collected, of which 2,282 (2.57%) patients died due to cardiovascular-related diseases. Age, chemotherapy and whether satisfactory cytoreduction surgery is still the most important factors affecting the prognosis of ovarian cancer patients, while different histological types, diagnosis time, and race also have a certain impact on the prognosis. The newly developed nomogram model showed excellent predictive performance, with a C-index of 0.759 (95%CI: 0.757-0.761) for the group. Elderly patients with ovarian cancer are still a high-risk group for cardiovascular death [HR: 21.07 (95%CI: 5.21-85.30), p < 0.001]. The calibration curve showed good agreement from predicted survival probabilities to actual observations. CONCLUSION: This study found that age, histology, surgery, race, chemotherapy, and tumor metastasis are independent prognostic factors for cardiovascular death in patients with ovarian cancer. The nomogram-based model can accurately predict the OS of ovarian cancer patients. It is expected to inform clinical decision-making and help develop targeted treatment strategies for this population.

Reexamining the Causes and Effects of Cholesterol Deposition in the Brains of Patients with Alzheimer's Disease.

Alzheimer's disease (AD) is a degenerative disease of the central nervous system. Numerous studies have shown that imbalances in cholesterol homeostasis in the brains of AD patients precede the onset of clinical symptoms. In addition, cholesterol deposition has been observed in the brains of AD patients even though peripheral cholesterol does not enter the brain through the blood‒brain barrier (BBB). Studies have demonstrated that cholesterol metabolism in the brain is associated with many pathological conditions, such as amyloid beta (Aß) production, Tau protein phosphorylation, oxidative stress, and inflammation. In 2022, some scholars put forward a new hypothesis of AD: the disease involves lipid invasion and its exacerbation of the abnormal metabolism of cholesterol in the brain. In this review, by discussing the latest research progress, the causes and effects of cholesterol retention in the brains of AD patients are analyzed and discussed. Additionally, the possible mechanism through which AD may be improved by targeting cholesterol is described. Finally, we propose that improving the impairments in cholesterol removal observed in the brains of AD patients, instead of further reducing the already impaired cholesterol synthesis in the brain, may be the key to preventing cholesterol deposition and improving the corresponding pathological symptoms.