Cheharazi M, Shamsipour M, Norouzi M, Jafari F, Ramazan Ali F. A New Method for Correcting Verification Bias in Diagnostic Accuracy Studies Using A Bayesian Approach. irje 2012; 8 (2) :20-28
URL:
http://irje.tums.ac.ir/article-1-5-en.html
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Abstract: (12826 Views)
Background & Objectives: One of the problems of diagnostic accuracy studies is
verification bias. It occurs when standard test performed only for
non-representative subsample of study subjects that diagnostic test done for
them. In this study we extend a Bayesian method to correct this bias.
Methods: Patients
that have had at least twice repeated failures in cycles IVF ICSI were included
in this model. Patients were screened by using an ultrasonography and those
with polyps recommended for hysteroscopy. A logistic regression with binomial
outcome fit to predict the missing values (false and true negative),
sensitivity and specificity. Bayesian methods was applied with informative
prior on polyp prevalence. False and true negatives were estimated in Bayesian
framework.
Results: A
total of 238 patients were screened and 47 had polyps. Those with polyps are
strongly recommended to undergo hysteroscopy, 47/47 decided to have a
hysteroscopy and 37/47 were confirmed to have polyps. None of the 191 patients
with no polyps in ultrasonography had hysteroscopy. The false negative was
obtained 14 and true negative 177, so sensitivity and specificity was estimated
easily after estimating missing data. Sensitivity and specificity were equal to
74% and 94% respectively.
Conclusion: Bayesian analyses with
informative prior seem to be powerful tools in simulation experimental
Type of Study:
Research |
Subject:
General Received: 2011/07/31 | Accepted: 2012/01/28 | Published: 2013/08/18
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