Browsing by Author "Davies, Kalatu R."

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    An Alternative Approach for Estimating the Accuracy of Colposcopy in Detecting Cervical Precancer
    (Public Library of Science, 2015) Davies, Kalatu R.; Cantor, Scott B.; Cox, Dennis D.; Follen, Michele
    Introduction: Since colposcopy helps to detect cervical cancer in its precancerous stages, as new strategies and technologies are developed for the clinical management of cervical neoplasia, precisely determining the accuracy of colposcopy is important for characterizing its continued role. Our objective was to employ a more precise methodology to estimate of the accuracy of colposcopy to better reflect clinical practice. Study design: For each patient, we compared the worst histology result among colposcopically positive sites to the worst histology result among all sites biopsied, thereby more accurately determining the number of patients that would have been underdiagnosed by colposcopy than previously estimated. Materials and Methods: We utilized data from a clinical trial in which 850 diagnostic patients had been enrolled. Seven hundred and ninety-eight of the 850 patients had been examined by colposcopy, and biopsy samples were taken at colposcopically normal and abnormal sites. Our endpoints of interest were the percentages of patients underdiagnosed, and sensitivity and specificity of colposcopy. Results: With the threshold of low-grade squamous intraepithelial lesions for positive colposcopy and histology diagnoses, the sensitivity of colposcopy decreased from our previous assessment of 87.0% to 74.0%, while specificity remained the same. The drop in sensitivity was the result of histologically positive sites that were diagnosed as negative by colposcopy. Thus, 28.4% of the 798 patients in this diagnostic group would have had their condition underdiagnosed by colposcopy in the clinic. Conclusions: In utilizing biopsies at multiple sites of the cervix, we present a more precise methodology for determining the accuracy of colposcopy. The true accuracy of colposcopy is lower than previously estimated. Nevertheless, our results reinforce previous conclusions that colposcopy has an important role in the diagnosis of cervical precancer.
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    Inverse decision theory with medical applications
    (2005) Davies, Kalatu R.; Cox, Dennis D.
    Medical decision makers would like to use decision theory to determine optimal treatment strategies for patients, but it can be very difficult to specify loss functions in the medical setting, especially when trying to assign monetary value to health outcomes. These issues led to the development of an alternative approach, called Inverse Decision Theory (IDT), in which given a probability model and a specific decision rule, we determine the set of losses for which that decision rule is optimal. This thesis presents the evolution of the IDT method and its applications to medical treatment decision rules. There are two ways in which we can use the IDT method. Under the first approach, we operate under the assumption that the decision rule of interest is optimal, and use the prior information that we have to make inferences on the losses. The second approach involves the use of the prior information to derive an optimal region and determine if the losses in this region are reasonable based on our prior information. We illustrate the use of IDT by applying it to the current standard of care (SOC) for the detection and treatment of cervical neoplasias. First, we model the diagnostic and treatment process as a Bayesian sequential decision procedure. Then, we determine the Bayes risk expression for all decision rules and compare the Bayes risk expression for the current SOC decision rule to the Bayes risk expressions of all other decision rules, forming linear inequality constraints on a region under which the current SOC is optimal. The current standard of care has been in use for many years, but we find another decision rule to be optimal. We question whether the current standard of care is the optimal decision rule and will continue to examine these implications and the practicality of implementing this new decision rule. The IDT method provides us with a mathematical technique for dealing with the challenges in formally quantifying patient experiences and outcomes. We believe that it will be applicable to many other disease conditions and become a valuable tool for determining optimal medical treatment standards of care.