Global Virus Network, Middle East Region, Shiraz, Iran.
R&D Department, PIHO, Shiraz, Iran.
BMC Med Res Methodol. 2023 Jan 30;23(1):30. doi: 10.1186/s12874-023-01841-8.
Diagnostic tests are important in clinical medicine. To determine the test performance indices - test sensitivity, specificity, likelihood ratio, predictive values, etc. - the test results should be compared against a gold-standard test. Herein, a technique is presented through which the aforementioned indices can be computed merely based on the shape of the probability distribution of the test results, presuming an educated guess.
We present the application of the technique to the probability distribution of hepatitis B surface antigen measured in a group of people in Shiraz, southern Iran. We assumed that the distribution had two latent subpopulations - one for those without the disease, and another for those with the disease. We used a nonlinear curve fitting technique to figure out the parameters of these two latent populations based on which we calculated the performance indices.
The model could explain > 99% of the variance observed. The results were in good agreement with those obtained from other studies.
We concluded that if we have an appropriate educated guess about the distributions of test results in the population with and without the disease, we may harvest the test performance indices merely based on the probability distribution of the test value without need for a gold standard. The method is particularly suitable for conditions where there is no gold standard or the gold standard is not readily available.
诊断测试在临床医学中很重要。为了确定测试性能指标——测试敏感度、特异性、似然比、预测值等——应该将测试结果与金标准测试进行比较。在此，我们提出了一种技术，仅根据测试结果概率分布的形状（假设是有根据的猜测），就可以计算出上述指标。
我们将该技术应用于伊朗南部设拉子一组人群中乙肝表面抗原的概率分布。我们假设该分布有两个潜在的亚群——一个是没有疾病的人群，另一个是有疾病的人群。我们使用非线性曲线拟合技术，根据这两个潜在群体的参数来计算性能指标。
该模型可以解释观察到的>99%的方差。结果与其他研究的结果一致。
我们得出结论，如果我们对有和没有疾病的人群中的测试结果分布有适当的有根据的猜测，我们可以仅根据测试值的概率分布来获得测试性能指标，而不需要金标准。该方法特别适用于没有金标准或金标准不易获得的情况。
