Altın standart test yokluğunda tanısal doğruluk ölçütlerinin Bayesci yaklaşım ile tahmini: Helicobacter Pylori verisi uygulaması

Year 2021, , 1548 - 1557, 30.12.2021

Yusuf Kemal Arslan

https://doi.org/10.17826/cumj.1003633

Abstract

Amaç: Tanı testleri, hasta ve sağlıklı bireylerin oluşturduğu heterojen bir kitlede bireyin gerçek durumunu ortaya çıkarmak amacıyla kullanılır. Bu çalışmada, altın standart test yokluğunda, Bayesci yaklaşım ile ilgilenilen tanı testine ait doğruluk ölçütlerini elde etmek ve diğer yöntemlerle karşılaştırması amaçlanmıştır.
Gereç ve Yöntem: Helicobacter Pylori tanısında; HpSA, Kültür, CLO, Histoloji ve PCR gibi farklı testler kullanılmaktadır. Bu çalışmada, Bayesci yaklaşımla parametre tahminlerinin elde edilmesinde önsel bilgileri (prevalans, duyarlılık vs.) içeren modeller oluşturulmuştur. Çalışmada bu tanı testlerinin doğruluklarının saptanmasında ortaya çıkabilen kesin olmayan altın standart yanlılığının düzeltilmesi amacıyla Bayesci yöntemler kullanılmıştır. Bu amaçla H. Pylori ile ilgili bir uzmanlık tezine ait veriler WinBUGS ve R paket programları yardımıyla analiz edilmiştir.
Bulgular: Bayesci çıkarsama yapıldığında hastalık ile ilgili prevalans bilgisi ve önsel bilgi dikkate alındığından tanı testine ait pozitif ve negatif kestirim değerlerine ait sonuçların daha güvenilir olduğu saptanmıştır. Kestirim değerlerine benzer şekilde duyarlılık ve seçicilik değerleri içinde güvenilir sonuçlar elde edilmiştir. Bayesci yaklaşım ile elde edilen güvenilir aralık önsel bilgi kullanıldığında daralmıştır.
Sonuç: Altın standardın olmadığı durumlarda prevalans gibi önsel bilgileri kullanan Bayesci yaklaşımlar klinisyenler için tanıda kolaylık sağlayacaktır.

Keywords

Bayes yaklaşımı, altın standart test, tanı testleri, Helicobacter Pylori, önsel bilgi

Bayesian estimation of diagnostic accuracy measures when there is no gold standard: a Helicobacter Pylori data application

Abstract

Purpose: Diagnostic tests are used for defining the disease status of person in a heterogeneous population which consists of healthy and diseased people. In this study, it was aimed to obtain the accuracy measures of the diagnostic test with the Bayesian approach when there was no gold standard test, and to compare it with other methods.
Materials and Methods: In the diagnosis of Helicobacter Pylori, different tests are used such as HpSA, Culture, CLO, Histology and PCR. In this study, models containing a priori information (prevalence, sensitivity, etc.) were created to obtain parameter estimations with the Bayesian approach. Bayesian methods were used to correct the imperfect gold standard bias that may occur in determining the accuracy of these diagnostic tests. For this purpose, the data of a medical thesis on H. Pylori were analyzed with the help of WinBUGS and R package programs.
Results: When Bayesian inference is made, the results of the positive and negative predictive values of the diagnostic test were found to be more reliable, since the prevalence and a priori information about the disease were taken into account. Similar to the predictive values, reliable results were obtained for sensitivity and specificity values. The credible interval obtained by using Bayesian approach is narrowed when a prior information is used.
Conclusion: In the absence of a gold standard, Bayesian approaches using a prior information such as prevalence and diagnostic test information could facilitate diagnosis for clinicians.

Keywords

Bayesian approach, gold standard, diagnostics tests, Helicobacter Pylori, prior information

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