共 115 条
Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart?
被引:58
作者:

Kastrinos, Fay
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机构:
Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, New York, NY USA
Columbia Univ, Div Digest & Liver Dis, Med Ctr, New York, NY USA
Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, 630 West 168th St 318, New York, NY 10032 USA Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, New York, NY USA

Kupfer, Sonia S.
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h-index: 0
机构:
Univ Chicago, Sect Gastroenterol Hepatol & Nutr, Chicago, IL USA Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, New York, NY USA

Gupta, Samir
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h-index: 0
机构:
Univ Calif San Diego, Dept Internal Med, Div Gastroenterol, La Jolla, CA USA
Vet Affairs San Diego Healthcare Syst, San Diego, CA USA Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, New York, NY USA
机构:
[1] Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, New York, NY USA
[2] Columbia Univ, Div Digest & Liver Dis, Med Ctr, New York, NY USA
[3] Univ Chicago, Sect Gastroenterol Hepatol & Nutr, Chicago, IL USA
[4] Univ Calif San Diego, Dept Internal Med, Div Gastroenterol, La Jolla, CA USA
[5] Vet Affairs San Diego Healthcare Syst, San Diego, CA USA
[6] Columbia Univ, Herbert Irving Comprehens Canc Ctr, Med Ctr, 630 West 168th St 318, New York, NY 10032 USA
关键词:
Precision Colorectal Cancer Screening;
Colorectal Cancer Risk Prediction Models;
Polygenic Risk Scores;
Colorectal Cancer Risk Assessment;
FECAL IMMUNOCHEMICAL TEST;
SOCIETY TASK-FORCE;
FAMILY-HISTORY;
ADVANCED NEOPLASIA;
AFRICAN-AMERICANS;
SCORING SYSTEM;
PREDICTION MODEL;
COLONOSCOPY;
VALIDATION;
DERIVATION;
D O I:
10.1053/j.gastro.2023.02.021
中图分类号:
R57 [消化系及腹部疾病];
学科分类号:
摘要:
Current colorectal cancer (CRC) screening recommenda-tions take a "one-size -fits-all" approach using age as the major criterion to initiate screening. Precision screening that incorporates factors beyond age to risk stratify in-dividuals could improve on current approaches and opti-mally use available resources with benefits for patients, providers, and health care systems. Prediction models could identify high-risk groups who would benefit from more intensive screening, while low-risk groups could be recom-mended less intensive screening incorporating noninvasive screening modalities. In addition to age, prediction models incorporate well-established risk factors such as genetics (eg, family CRC history, germline, and polygenic risk scores), lifestyle (eg, smoking, alcohol, diet, and physical inactivity), sex, and race and ethnicity among others. Although several risk prediction models have been validated, few have been systematically studied for risk-adapted population CRC screening. In order to envisage clinical implementation of precision screening in the future, it will be critical to develop reliable and accurate prediction models that apply to all individuals in a population; prospectively study risk -adapted CRC screening on the population level; garner acceptance from patients and providers; and assess feasi-bility, resources, cost, and cost-effectiveness of these new paradigms. This review evaluates the current state of risk prediction modeling and provides a roadmap for future implementation of precision CRC screening.
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页码:812 / 827
页数:16
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