Application of summary receiver operating characteristics (sROC) analysis to diagnostic clinical testing.

Summary receiver operating characteristics (sROC) analysis is a recently developed statistical technique that can be applied to meta-analysis of diagnostic tests. This technique can overcome some of the limitations associated with pooling the sensitivities and specificities of published studies. The sROC curve is initially constructed by plotting the sensitivity (true positivity) and false positivity (1 - specificity) of each study. After mathematical manipulation of the true and false positivities, linear regression is performed to calculate the slope and y-intercept. These coefficients are then entered into the sROC equation to generate the sROC curve. There are three commonly used methods to assess the accuracy of the test: the exact area under the curve (AUC) for the sROC function, the homogeneous AUC, and the index Q*. Statistical formulas can compare these values from different diagnostic tests. With the introduction of sROC software and better understanding of this method, the application of sROC analysis should continue to increase.

[1]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[2]  J. Hanley,et al.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.

[3]  B Littenberg,et al.  A Meta-analytic Method for Summarizing Diagnostic Test Performances , 1993, Medical decision making : an international journal of the Society for Medical Decision Making.

[4]  L E Moses,et al.  Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. , 1993, Statistics in medicine.

[5]  Frederick Mosteller,et al.  Guidelines for Meta-analyses Evaluating Diagnostic Tests , 1994, Annals of Internal Medicine.

[6]  A. Zanetti,et al.  Mother-to-infant transmission of hepatitis C virus , 1995, The Lancet.

[7]  P Glasziou,et al.  Meta-analytic methods for diagnostic test accuracy. , 1995, Journal of clinical epidemiology.

[8]  M. Chang.  Mother‐to‐infant transmission of hepatitis C virus , 1995 .

[9]  N. Terrin,et al.  Meta-analysis of diagnostic tests for acute sinusitis. , 2000, Journal of clinical epidemiology.

[10]  C. Langlotz,et al.  Accuracy of CT angiography versus pulmonary angiography in the diagnosis of acute pulmonary embolism: evaluation of the literature with summary ROC curve analysis. , 2000, Academic radiology.

[11]  S. Walter,et al.  Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data , 2002, Statistics in medicine.

[12]  D. Hamer,et al.  Diagnostic accuracy of stool assays for inflammatory bacterial gastroenteritis in developed and resource-poor countries. , 2003, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[13]  L. Shaw,et al.  Comparison of risk stratification with pharmacologic and exercise stress myocardial perfusion imaging: A meta-analysis , 2004, Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.

[14]  J. Fine,et al.  Meta-Analysis: Methods for Diagnosing Intravascular DeviceRelated Bloodstream Infection , 2005, Annals of Internal Medicine.

[15]  S D Walter,et al.  The partial area under the summary ROC curve , 2005, Statistics in medicine.

[16]  John Ioannidis,et al.  Meta-Analysis: Test Performance of Ultrasonography for Giant-Cell Arteritis , 2005, Annals of Internal Medicine.

[17]  T. Fukui,et al.  Ventilation-perfusion scanning and helical CT in suspected pulmonary embolism: meta-analysis of diagnostic performance. , 2005, Radiology.

[18]  J. Deeks,et al.  A methodological review of how heterogeneity has been examined in systematic reviews of diagnostic test accuracy. , 2005, Health technology assessment.

[19]  G. Casazza,et al.  Accuracy of Ultrasonography, Spiral CT, Magnetic Resonance, and Alpha-Fetoprotein in Diagnosing Hepatocellular Carcinoma: A Systematic Review , 2006, The American Journal of Gastroenterology.

[20]  Javier Zamora,et al.  Meta-DiSc : a software for meta-analysis of test accuracy data , 2015 .

[21]  A. Darzi,et al.  Magnetic resonance colonography vs computed tomography colonography for the diagnosis of colorectal cancer: an indirect comparison , 2007, Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland.

[22]  A. Rosman,et al.  Meta-analysis comparing CT colonography, air contrast barium enema, and colonoscopy. , 2007, The American journal of medicine.