Factors Influencing Total Delay of Breast Cancer in Northeast of China - Ren, Sihang; Zhang, Yuting; Qin, Pan; Wang, Jia (Frontiers in Oncology, 2022)
Objectives: Delay in diagnosis and treatment, called total delay, could probably result in Lower survival rates in breast cancer patients. This study aimed to investigate the factors associated with the comprehensive delay behaviors and evaluate its effect on outcomes in patients with breast cancer in Dalian, a northeast city of China. Methods: A retrospective chart review was conducted using a cancer registry dataset including 298 patients. The Kaplan-Meier survival analysis was used to identify the threshold of total delay, dividing the patients into a group with significant uncertainty and a group without substantial delay. The factors associated with the significant total delay were investigated from the potential candidates, like income level and martial status, by using Chi-squared test. The difference of the clinicopathologic characteristics between the patients grouped by the significant total delay, like tumor size and lymph node metastasis, were also investigated to find out the effect of the total delay. Results: 238 charts were used for analysis.The mean age was 57.3. The median of total delays was 3.75 months. Thirty days were identified as a threshold, more than which the total delay can lead to worse survival. Patients’ marital status ( p = 0.010 ), income levels ( p = 0.003 ), smoking status ( p = 0.031 ), initially visiting hospital level ( p = 0.005 ), self health care ( p = 0.001 ), and self-concern to initial symptom ( p ≈ 0.000 ) were identified as the independent predictors of the total delay. The metastasis ( p ≈ 0.000 ) were identified as the significant result relating to the significant total delay. Conclusions: Total delay more than 30 days predicts worse survival in breast cancer patients in Dalian. Several factors, like patients’ marital status and income levels, can be considered to be relevant to the significant total delay. We recommend that these factors can be used to predict the potential patients with the significant total delay in the clinical practice.