Prediction model using readily available clinical data for colorectal cancer in a chinese population

Am J Med Sci. 2022 Jul;364(1):59-65. doi: 10.1016/j.amjms.2022.01.011. Epub 2022 Feb 2.

Abstract

Background: In China, health screening has become common, although colonoscopy is not always available or acceptable. We sought to develop a prediction model of colorectal cancer (CRC) for health screening population based on readily available clinical data to reduce labor and economic costs.

Methods: We conducted a cross-sectional study based on a health screening population in Karamay Central Hospital. By collecting clinical data and basic information from participants, we identified independent risk factors and established a prediction model of CRC. Internal and external validation, calibration plot, and decision curve analysis were employed to test discriminating ability, calibration ability, and clinical practicability.

Results: Independent risk factors of CRC, which were readily available in primary public health institutions, included high-density lipoprotein cholesterol, male sex, total cholesterol, advanced age, and hemoglobin. These factors were successfully incorporated into the prediction model (AUC 0.740, 95% CI 0.713-0.767). The model demonstrated a high degree of discrimination and calibration, in addition to a high degree of clinical practicability in high-risk people.

Conclusions: The prediction model exhibits good discrimination and calibration and is pragmatic for CRC screening in rural areas and primary public health institutions.

Keywords: Clinical decision rules; Colonoscopy; Colorectal cancer; Public Health Surveillance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cholesterol
  • Colonoscopy*
  • Colorectal Neoplasms* / diagnosis
  • Colorectal Neoplasms* / epidemiology
  • Cross-Sectional Studies
  • Early Detection of Cancer
  • Humans
  • Male

Substances

  • Cholesterol