首页|Prediction model using readily available clinical data for colorectal cancer in a chinese population
Prediction model using readily available clinical data for colorectal cancer in a chinese population
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NSTL
Elsevier
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。 ? 2022
Clinical decision rulesColonoscopyColorectal cancerPublic Health Surveillance
NSTL
Elsevier
