Clinical and translational gastroenterology · 2025
Nomogram Prediction for Gastric Cancer Development.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lim Joo Hyun, Han Areum, Cho Soo-Jeong, Hahn Seokyung, Kim Sang Gyun
Аннотация
INTRODUCTION: Helicobacter pylori ( Hp ) and gastric atrophy represent significant risk factors for gastric cancer (GC). Nevertheless, to date, no nomogram has been developed to predict GC based on the specific combination of risk factors present in individual cases.
METHODS: A retrospective cohort study was conducted using health screening data collected between 2003 and 2018. Subjects with positive results for anti- Hp antibody were enrolled. Individuals were classified into 4 groups: low-B (low titer without atrophy), high-B (high titer without atrophy), high-C (high titer with atrophy), and low-C (low titer with atrophy). Nomogram prediction models were developed for overall GCs as well as intestinal and diffuse cancers, with each type considered a competing event, by using both Cox proportional and subdistribution hazard models. Prediction performance was evaluated using the concordance index (c-index) and the area under the curve through 10-fold cross-validation.
RESULTS: During a median follow-up period of 5.7 years, 231 new GC cases developed among the total cohort of 28,311 subjects, including 159 intestinal type, 68 diffuse type, and 4 cases of unknown type. Multivariable analyses indicated that age, body mass index, family history, smoking, and classification into the high-C or low-C group were significant predictors of GC. The nomograms for intestinal type, diffuse type, and total GC demonstrated area under the curve values of 0.82, 0.62, and 0.75, respectively, and c-indices of 0.85, 0.54, and 0.76, respectively.
DISCUSSION: The nomograms for GC prediction would be useful in identifying high-risk individuals, particularly for intestinal type. This would facilitate the implementation of personalized eradication and intensive screening strategies to target those at higher risk for GC.
METHODS: A retrospective cohort study was conducted using health screening data collected between 2003 and 2018. Subjects with positive results for anti- Hp antibody were enrolled. Individuals were classified into 4 groups: low-B (low titer without atrophy), high-B (high titer without atrophy), high-C (high titer with atrophy), and low-C (low titer with atrophy). Nomogram prediction models were developed for overall GCs as well as intestinal and diffuse cancers, with each type considered a competing event, by using both Cox proportional and subdistribution hazard models. Prediction performance was evaluated using the concordance index (c-index) and the area under the curve through 10-fold cross-validation.
RESULTS: During a median follow-up period of 5.7 years, 231 new GC cases developed among the total cohort of 28,311 subjects, including 159 intestinal type, 68 diffuse type, and 4 cases of unknown type. Multivariable analyses indicated that age, body mass index, family history, smoking, and classification into the high-C or low-C group were significant predictors of GC. The nomograms for intestinal type, diffuse type, and total GC demonstrated area under the curve values of 0.82, 0.62, and 0.75, respectively, and c-indices of 0.85, 0.54, and 0.76, respectively.
DISCUSSION: The nomograms for GC prediction would be useful in identifying high-risk individuals, particularly for intestinal type. This would facilitate the implementation of personalized eradication and intensive screening strategies to target those at higher risk for GC.