Key result
This paper documents a research protocol for a case-control study involving 74,800 individuals to refine and validate a web-based cancer risk assessment tool in rural China.
Why the study?
Can a two-stage and web-based cancer risk assessment tool accurately identify individuals at elevated risk for leading cancers in rural China?
Case-Control (n=74,800)
Can a two-stage and web-based cancer risk assessment tool accurately identify individuals at elevated risk for leading cancers in rural China?
This protocol outlines a large-scale case-control study to validate a web-based cancer risk assessment tool for use by village doctors in rural China.
This validation protocol for a rural China cancer risk tool leaves clinical utility unproven; extends risk assessment research but should not change practice.
The big gap between efficacy of population level prevention and expectations due to heterogeneity and complexity of cancer etiologic factors calls for selective yet personalized interventions based on effective risk assessment. This paper documents our research protocol aimed at refining and validating a two-stage and web-based cancer risk assessment tool, from a tentative one in use by an ongoing project, capable of identifying individuals at elevated risk for one or more types of the 80% leading cancers in rural China with adequate sensitivity and specificity and featuring low cost, easy application and cultural and technical sensitivity for farmers and village doctors. The protocol adopted a modified population-based case control design using 72, 000 non-patients as controls, 2, 200 cancer patients as cases, and another 600 patients as cases for external validation. Factors taken into account comprised 8 domains including diet and nutrition, risk behaviors, family history, precancerous diseases, related medical procedures, exposure to environment hazards, mood and feelings, physical activities and anthropologic and biologic factors. Modeling stresses explored various methodologies like empirical analysis, logistic regression, neuro-network analysis, decision theory and both internal and external validation using concordance statistics, predictive values, etc..
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Shen et al. (2015) conducted a case-control in Cancer (n=74,800). Two-stage and web-based cancer risk assessment tool was evaluated on Sensitivity and specificity of identifying individuals at elevated risk for leading cancers. This paper documents a research protocol for a case-control study involving 74,800 individuals to refine and validate a web-based cancer risk assessment tool in rural China.
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