Stomach Cancer Prediction Model (SCoPM): An approach to risk stratification in a diverse U.S. population

Population-based screening for gastric cancer (GC) in low prevalence nations is not recommended. The objective of this study was to develop a risk-prediction model to identify high-risk patients who could potentially benefit from targeted screening in a racial/ethnically diverse regional US populati...

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Veröffentlicht in:	PloS one 2024-05, Vol.19 (5), p.e0303153-e0303153
Hauptverfasser:	Wu, Bechien U, Dong, Elizabeth Y, Chen, Qiaoling, Luong, Tiffany Q, Lustigova, Eva, Jeon, Christie Y, Chen, Wansu
Format:	Artikel
Sprache:	eng
Schlagworte:	Age Aged Aged, 80 and over Alcohol Anemia Biology and Life Sciences California - epidemiology Cancer Datasets Diagnosis Early Detection of Cancer Evaluation Female Gastric cancer Genetics Health services Hemoglobin Humans Incidence Male Medicine and Health Sciences Middle Aged Mortality Patients People and places Physical Sciences Population Prediction models Regression analysis Regression models Research and Analysis Methods Retrospective Studies Risk Assessment - methods Risk Factors Risk groups Service areas Stomach cancer Stomach Neoplasms - diagnosis Stomach Neoplasms - epidemiology Training Ulcers United States United States - epidemiology
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Zusammenfassung:	Population-based screening for gastric cancer (GC) in low prevalence nations is not recommended. The objective of this study was to develop a risk-prediction model to identify high-risk patients who could potentially benefit from targeted screening in a racial/ethnically diverse regional US population. We performed a retrospective cohort study from Kaiser Permanente Southern California from January 2008-June 2018 among individuals age ≥50 years. Patients with prior GC or follow-up
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0303153