Diagnostic yield of third eye retroscope on adenoma detection during colonoscopy:A systematic review and meta-analysis

AIM: To determine the diagnostic yield of the "third eye retroscope",on adenoma detection rate during screening colonoscopy.METHODS: The "third eye retroscope" when used with standard colonoscopy provides an additional retrograde view to visualize lesions on the proximal aspects of folds and flexures.We searched MEDLINE(Pub Med and Ovid),SCOPUS(including MEDLINE and EMBASE databases),Cochrane Database of Systemic Reviews,Google Scholar,and CINAHL Plus databases to identify studies that evaluated diagnostic yield of "third eye retroscope" during screening colonoscopy.Der Simonian Laird random effects model was used to generate the overall effect for each outcome.We evaluated statistical heterogeneity among the studies by using the Cochran Q statistic and quantified by I2 statistics.RESULTS: Four distinct studies with a total of 920 patients,mean age 59.83(95%CI: 56.77-62.83) years,were included in the review.The additional adenoma detection rate(AADR) defined as the number of additional adenomas identified due to "third eye retroscope" device in comparison to standard colonoscopy alone was 19.9%(95%CI: 7.3-43.9).AADR for right and left colon were 13.9%(95%CI: 9.4-20) and 10.7(95%CI: 1.9-42),respectively.AADR for polyps ≥ 6 mm and ≥ 10 mm were 24.6%(95%CI: 16.6-34.9) and 24.2%(95%CI: 12.9-40.8),respectively.The additional polyp detection rate defined as the number of additional polyps identified due to "third eye retroscope" device in comparison to standard colonoscopy alone was 19.8%(95%CI: 7.9-41.8).There were no complications reported with use of "third eye retroscope" device.CONCLUSION: The "third eye retroscope" device when used with standard colonoscopy is safe and detects 19.9% additional adenomas,compared to standard colonoscopy alone.

Additive Rate Model With Auxiliary Covariates

In this paper, we consider an inference method for recurrent event data in which the primary exposure covariate is assessed only in a validation set, while as an auxiliary covariate for the main exposure is available for the full cohort. Additive rate model is considered. The existing estimating equations in the absence of primary exposure are corrected by taking use of the validation data and auxiliary information, which yield consistent and asymptotically normal estimators of the regression parameters. The estimated baseline mean process is shown to converge weakly to a zero-mean Gaussian process. Extensive simulations are conducted to evaluate finite sample performance.

A Semiparametric Additive Rates Model for Clustered Recurrent Event Data

Recurrent event data often arises in biomedical studies, and individuals within a cluster might not be independent. We propose a semiparametric additive rates model for clustered recurrent event data, wherein the covariates are assumed to add to the unspecified baseline rate. For the inference on the model parameters, estimating equation approaches are developed, and both large and finite sample properties of the proposed estimators are established.