Identifying Factors Contributing to Delayed Diagnosis of Ovarian Cancer: A Comprehensive Analysis.

Abstract

Background: Ovarian cancer (OC) remains the deadliest gynecologic malignancy worldwide due to delayed diagnosis, recurrence, and drug resistance. This study aimed to identify key factors affecting delayed diagnosis in OC patients.

Methods: A retrospective analysis was conducted on OC patients treated at Taihe Hospital, Hubei University of Medicine from June 2023 to September 2023. Patients were categorized based on a three-months cut-off point for delayed diagnosis. Collected data included demographics, tumor incidence, and disease cognition. The analysis of variance and the chi-squared test was used for comparison between groups.

Results: The significant differences were found in age, residence, education level, family income, family history of tumor, histology, FIGO stage, and tumor location between groups (P<0.05). Multifactorial logistic regression analysis identified education level [odds ratio (OR) = 0.606; 95% confidence interval (CI): 0.440, 0.833; P = 0.002], family history of tumor (OR = 0.462; 95% CI: 0.214, 0.997; P = 0.049), emotional barriers (OR = 1.332; 95% CI: 1.081, 1.642; P = 0.007), and practical barriers (OR = 2.964; 95% CI: 2.195, 4.004; P < 0.001) as risk factors for delayed diagnosis of OC.

Conclusion: Patient cognition is crucial in OC diagnosis delay. Enhancing public awareness and understanding of OC is essential to eliminate fear and improve early diagnosis.