Intelligent Remote Intervention for High-risk Breast Cancer Populations

Breast cancer is one of the world's major public health problems. According to the report of the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO), breast cancer has replaced lung cancer as the world's number one cancer in 2020, posing a serious threat to women's lives and health. Breast nodules are benign lumps or masses that form in the breast tissue. Breast nodules may increase the risk of breast cancer to a certain extent, and enhancing early health management of breast nodules is an effective measure to diagnose and prevent breast cancer. This project aims to construct an intelligent breast cancer intelligent health management system using remote intervention technology. The system includes modules of intelligent breast health information management, breast disease risk assessment and breast stratified intervention, aiming to break through the bottleneck of breast cancer prevention and treatment. The goal of this clinical trial is to compare the effects of modern remote health intervention regime with traditional in-person intervention strategies in high-risk breast cancer groups that with BI-RADS 3 or higher nodules. The main questions it aims to answer are: * Can the remote health intervention be more effective in slowing down the progression of breast nodules than the traditional in-person intervention? * Can the remote health intervention be more effective in minimizing the deterioration of the disease and reducing the risk of death in patients than the traditional in-person intervention? * Can the knowledge, belief and behavioral change of breast nodule population improve after receiving remote health intervention compared with traditional health management model? Research content: The screened and qualified subjects were randomly divided into experimental group and control group, and different health management programs were adopted, the experimental group adopted the remote intervention health management mode, and the control group adopted the health management mode recommended by the conventional guidelines, to the end of the follow-up, and statistical analysis was performed to compare the effects of the two health management modes. 1\) To analyze the effectiveness of the remote intervention health management model in slowing down the malignant progression of breast nodules relative to the traditional model, and to analyze the differences in the rates of nodal lesion progression, nodal malignancy, and nodal improvement as well as the time spent on health management. (2) To analyze the effectiveness of the tele-intervention health management model relative to the traditional model in reducing the risk of progression and death of patients with potential breast cancer after detection of the intelligent health management model, and to analyze the differences in the risk of death of the patients, the risk of progression of the lesions and the survival time. (3) To analyze the degree of change in knowledge, beliefs, and behaviors of breast nodule populations after different health management intervention modes of tele-intervention health management mode relative to the traditional mode. Study Population: Female medical examiners who participated in physical examinations and had TI-RADS category 3 or higher breast nodules on breast color Doppler ultrasound at the health management centers of five large tertiary hospitals nationwide during the trial period. The study was a clinical trial study with qualitative variables as the main efficacy outcome indicators, and the subjects were randomized into a test group, a control group, and an equally parallel 1:1 design for both groups. Each group required 1,000 cases, and taking into account a 20% dropout rate, 1,250 cases were recruited in each group, totaling 2,500 cases in both groups. Statistical analysis The study was a clinical trial study with qualitative variables as the primary outcome indicators of efficacy, with an equally parallel 1:1 design for both groups. The researchers considered that the smart health management program (trial group) had to be at least 5% better than the conventional health management program (control group) to be clinically meaningful. An equal (1:1) superiority design scheme was used, setting α = 0.025 (unilateral), β = 0.20 (unilateral), Δ = 5%, and estimating the sample size n. Based on the design of this clinical pilot study, combined with the primary efficacy outcome metrics, the estimation yielded a need for 500 cases in each group, and considering a 20% shedding rate, 625 cases were recruited in each group, for a total of 1,250 cases in both groups. Unless otherwise stated, all statistical tests were performed using a two-sided test with a test level of α = 0.05 (one-sided test α = 0.025). The study was a clinical trial study with qualitative variables as the main efficacy outcome indicators, and the effect of the new regimen had to be at least 5% better than that of the control drug to be clinically meaningful, so it was set at α = 0.025 (one-sided) and β = 0.20 (one-sided). Hypotheses for the test of superiority H0: the efficiency of the test group is less than or equal to the control group, π\_T-π\_C≤0 H1: The efficiency of the test group is greater than that of the control group, π\_T-π\_C\>0 α = 0.025, the superiority cut-off value is 0. Calculate the difference between the effective rate of the experimental group and the control group, and calculate the 95% CI of the difference, if the lower limit of the 95% CI is greater than 0, the efficacy of the experimental group is considered to be better than that of the control group, and the expected goal of the study is achieved.