National Colorectal Polyp Care
Condition: Colorectal Polyp
MeSH terms: Polyps
Study type: Observational

Summary: 
      This study has three main purposes：screening: the first purpose is to evaluate the diagnostic
      value of combintion of the life risk factors and immunochemical fecal occult blood test (FIT)
      on detection of colorectal neoplasia in Chinese population; resection: the second objective
      is to investigate the complete resection rate of colorectal adenoma and risk factors of
      incomplete resection in China; identification and classification: the third objective is to
      initially establish an artificial intelegence-assissted recognition and classification system
      of polyp based on deep learning.
    

Detailed description: 
      This study is a multi-center cross-sectional survey and diagnostic test led by the National
      Clinical Research Center for Digestive Disease (Shanghai) (Department of Gastroenterology,
      Changhai Hospital, Naval Medical University), which is conducted at about 175 digestive
      endoscopy centers nationwide in China, with the expectation of including 12,000 patients
      (10,000 screenig and 2,000 adenoma resection). The basic characteristics of patients, bowel
      preparation method and quality, and related information of colonoscopy are recorded in
      detail. According to the research purpose, the whole project can be divided into three
      sections.

        1. Screening section: All patients receive FIT test and colonoscopy, whose age, sex, family
           history, smoking history, body mass index (BMI), diabetes and other risk factors are
           collected by researchers through pad, equipped with a specially designed database and
           app. Using colonoscopy results as the gold standard, the risk prediction model for the
           Chinese population is explored, and the optimal strategy of colonoscopy practice for the
           Chinese established initially.

        2. Resection section: During the polypectomy, for all pathologically confirmed or
           NBI-predicted adenomas with size<10mm, 1-2 biopsies were randomly performed on the edge
           after resection to determine the completion rate of the polypectomy.

        3. Identification and classification section: For Patients regardless of cancer diagnosis
           or polypectomy, if there is polyp, observation of narrow band imaging (NBI) with or
           without magnification is required, with 4 white light and NBI images collected and
           reserved, respectively. If there is magnifying endoscopy, another 4 endoscopic images of
           magnification are also required. Endoscopists are invited to predict the pathology of
           polyps according to the NBI International Colorectal Endoscopic (NICE) classification
           principle and endoscopic images, and upload the pathological results and endoscopic
           images within 2-4 week after colonoscopy.
    

Intervention name(s): FIT test and colonoscopy; Polypectomy and biopsy; Classification
Intervention type(s): Diagnostic Test; Diagnostic Test; Diagnostic Test
Intervention description(s): All included patients received FIT test and then colonoscopy, with the risk factors of CRC recorded. The diagnostic performance of predicting model (based on FIT and risk factors) and colonoscopy were compared.; All included patients received polypectomy, and then biopsy is performed on the edge of resection for patients with < 10 mm adenoma (confirmed by pathology or predicted by NBI images), with the complete resection rate of polyps being calculated.; Pathology of polyps is classified by endoscopists through NICE principle and the performance of classification between endoscopists and computer is compared.
Observational model: Cohort
Time perspective: Prospective
Sampling method: Probability Sample
Study population: 
        Patients who referred to the outpatient and received colonoscopy.
      
Keywords: Colorectal neoplasia; Polypectomy; Artificial intelligence