Development and Validation of an Esophageal Squamous Cell Carcinoma Risk Prediction Model for Rural Chinese: Multicenter Cohort Study

Abstract

BackgroundThere are rare prediction models for esophageal squamous cell carcinoma (ESCC) for rural Chinese population. We aimed to develop and validate a prediction model for ESCC based on a cohort study for the population.MethodsData of 115,686 participants were collected from esophageal cancer (EC) early diagnosis and treatment of cancer program as derivation cohort while data of 54,750 participants were collected as validation cohort. Risk factors considered included age, sex, smoking status, alcohol drinking status, body mass index (BMI), tea drinking status, marital status, annual household income, source of drinking water, education level, and diet habit. Cox proportional hazards model was used to develop ESCC prediction model at 5 years. Calibration ability, discrimination ability, and decision curve analysis were analyzed in both derivation and validation cohort. A score model was developed based on prediction model.ResultsOne hundred eighty-six cases were diagnosed during 556,949.40 person-years follow-up in the derivation cohort while 120 cases from 277,302.70 in the validation cohort. Prediction model included the following variables: age, sex, alcohol drinking status, BMI, tea drinking status, and fresh fruit. The model had good discrimination and calibration performance: R2, D statistic, and Harrell’s C statistic of prediction model were 43.56%, 1.70, and 0.798 in derivation cohort and 45.19%, 1.62, and 0.787 in validation cohort. The calibration analysis showed good coherence between predicted probabilities and observed probabilities while decision curve analysis showed clinical usefulness. The score model was as follows: age (3 for 45–49 years old; 4 for 50–54 years old; 7 for 55–59 years old; 9 for 60–64 years; 10 for 65–69 years), sex (5 for men), BMI (1 for ≤25), alcohol drinking status (2 for alcohol drinkers), tea drinking status (2 for tea drinkers), and fresh fruit (2 for never) and showed good discrimination ability with area under the curve and its 95% confidence interval of 0.792 (0.761,0.822) in the deviation cohort and 0.773 (0.736,0.811) in the validation cohort. The calibration analysis showed great coherence between predicted probabilities and observed probabilities.ConclusionsWe developed and validated an ESCC prediction model using cohort study with good discrimination and calibration capability which can be used for EC screening for rural Chinese population.

Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review

“…Major deficiencies in the analysis domain relate to number of participants with the outcome and evaluation of model performance. The relatively recommended prediction model for subjects with high risk of ESCC were Chen's model ( 25 ) and Han's model ( 26 ), and the model by Kunzmann was recommended for identifying individuals at risk for EAC ( 18 ).…”

“…We used the recently published tool PROBAST to assess the risk of bias and applicability of the included prediction model studies and then evaluated their methodological characteristics and performance. Risk prediction models by Chen ( 25 ), Han ( 26 ), and Kunzmann ( 18 ) were recommended based on the relatively standardized measurement of predictors and outcome, large sample size, complete evaluation, and good result of model performance. The results of this study will provide a reference for the further development, validation, and application of risk prediction models in the target subjects for endoscopic screening.…”

Prediction of esophageal cancer risk based on genetic variants and environmental risk factors in Chinese population

“…Previous risk prediction models for EC were mostly based on non-genetic factors [14,[43][44][45][46][47], and easy-toobtain variables were included in a standardized manner without any extra costs. However, for such a complex etiological disease, the actual predictive efficacy of environmental factors alone has not been completely established.…”

Performance of Prediction Models for Esophageal Squamous Cell Carcinoma in General Population: A Systematic Review and External Validation Study

“…SDA might be the more appropriate outcome for screening because the primary purpose of both population-based screening and opportunistic screening in hospitals is to detect precancerous lesions and early-stage cancers. In general, the logistic models of cross-sectional design (15)(16)(17)(18)(19) were diagnostic and more suitable for prescreening before endoscopic screening, and the Cox proportional hazards models of cohort design (23)(24)(25) were prognostic and more suitable for predicting long-term risk. The event rate of the prediction models varied depending on the outcome and study design.…”

“…The outcome of logistic models (15)(16)(17)(18)(19)(20)(21)(22) was defined as the endoscopic diagnosis at baseline and 2 of the models, Liu et al (2022) (15) and Chen et al (2021) (19), also included cases with ESCC diagnosed within 1 and 3 years of follow-up, respectively. The outcome of Cox proportional hazards models (23)(24)(25) was defined as new cases with ESCC during follow-up in participants without any tumors and severe dysplasia at baseline. Esophageal cancer was coded as C15 according to the International Classification of Diseases, 10th Revision.…”