Who should undergo gastroscopy: a smartphone-based noninvasive auxiliary screening system (Preprint)
BACKGROUND Gastroscopy is conducive to the early diagnosis of gastric cancer. It remains a key issue to screen premalignant patients who need gastroscopy in the clinic. Current screening strategies, including serum testing-based screening, are limited by high cost or invasive sampling, making them difficult to apply to large-scale natural populations. Therefore, a cost-effective and noninvasive auxiliary screening method that is suitable for large-scale application is urgently needed. OBJECTIVE The aim of this study was to construct a smartphone-based noninvasive auxiliary screening system suitable for screening patients with precancerous lesions of gastric cancer. Based on the auxiliary screening system, we expect to apply the concept of mobile health (mHealth) to establish a system to assist in screening natural populations at risk of gastric cancer and in need of gastroscopy. METHODS We developed the screening system by applying a naive Bayes classification algorithm based on collected questionnaires and gastritis medical records. We then established an affiliated app for application testing. The system was validated in three communities and we assessed the performance by comparison with other methods. RESULTS We constructed a “BIANQUE” screening system. First, we collected 841 questionnaires and 75,624 medical records. Second, we selected 9 risk factors in 20 factors. Third, we developed a screening system that achieved an AUC of 0.78 (95% CI [0.71,0.86]), comparable to blood testing-based screening methods (AUC=0.76). Fourth, we carried out a community validation. The odds ratio (OR) of different degrees of risk and gastric precancerous lesions was 2.85. CONCLUSIONS We have established an auxiliary screening system to help predict who needs gastroscopy. This system can achieve noninvasive and cost-effective testing with comparable performance to current invasive screening strategies. Thus, we speculate that this system could be easily applied on large-scale natural populations. CLINICALTRIAL Chinese clinical trial registry ChiCTR2100044006 http://www.chictr.org.cn/