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. 2016 Jun 10;11(6):e0157269.
doi: 10.1371/journal.pone.0157269. eCollection 2016.

Development of a Novel Scoring System for Predicting the Risk of Colorectal Neoplasia: A Retrospective Study

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Development of a Novel Scoring System for Predicting the Risk of Colorectal Neoplasia: A Retrospective Study

Tomohiko Ohno et al. PLoS One. .

Abstract

Objective: The purpose of this study was to develop a novel scoring system to screen subjects who have a high risk for colorectal neoplasia.

Study design and setting: We retrospectively analyzed 1061 subjects undergoing total colonoscopy (TCS) for the first time at Gihoku Kosei Hospital. The characteristics and habits of the subjects were analyzed using a multivariate logistic regression analysis. The risk score was established according to each odds ratio of the individual risk factors, and the correlations between the sum of the risk scores and the prevalence of colorectal neoplasia for each individual were evaluated.

Results: Age 45-59 (risk score: 2 points) and ≥60 (3 points), male gender (1 point), and habitual alcohol consumption ≥21g daily (1 point) were extracted as the significant risk factors for colorectal neoplasia. When the risk groups were determined by summing up these risk scores, the prevalence rates of colorectal neoplasia were 8.8% for the low risk group (0-2 points), 30.5% for the low-moderate risk group (3 points), 39.1% for the high-moderate risk group (4 points), and 57.6% for the high risk group (5 points). In comparison with the low risk group, the odds ratio of the low-moderate risk, the high-moderate risk, and the high risk groups were 4.6, 6.7, and 14.1 folds, respectively.

Conclusion: Our scoring system, which linearly correlates with the prevalence rate of colorectal neoplasia, may be an effective tool for screening the subjects who have a high risk for colorectal neoplasia. These subjects, therefore, should be recommended to undergo TCS.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Multivariate predictors of colorectal neoplasia analyzed using a multiple logistic regression analysis.
The plot shows the odds ratios (black squares), and 95% CIs (horizontal lines). P-values show the interaction between the prevalence of colorectal neoplasia and any subgroup variable. a. Significant risk factor of colorectal neoplasia by the Pearson χ2 test (P < 0.001). b. Significant risk factor of colorectal neoplasia by the Pearson χ2 test (P < 0.01).

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