Practice Guidelines for the Management of Patients with BlastomycosisGuidelines for the treatment of blastomycosis are presented; these guidelines are the consensus opinion of an expert panel representing the National Institute of Allergy and Infectious Diseases Mycoses Study Group and the Infectious Diseases Society of America. The clinical spectrum of blastomycosis is varied, including asymptomatic infection, acute or chronic pneumonia, and extrapulmonary disease. Most patients with blastomycosis will require therapy. Spontaneous cures may occur in some immunocompetent individuals with acute pulmonary blastomycosis. Thus, in a case of disease limited to the lungs, cure may have occurred before the diagnosis is made and without treatment; such a patient should be followed up closely for evidence of disease progression or dissemination. In contrast, all patients who are immunocompromised, have progressive pulmonary disease, or have extrapulmonary disease must be treated. Treatment options include amphotericin B, ketoconazole, itraconazole, and fluconazole. Amphotericin B is the treatment of choice for patients who are immunocompromised, have life-threatening or central nervous system (CNS) disease, or for whom azole treatment has failed. In addition, amphotericin B is the only drug approved for treating blastomycosis in pregnant women. The azoles are an equally effective and less toxic alternative to amphotericin B for treating immunocompetent patients with mild to moderate pulmonary or extrapulmonary disease, excluding CNS disease. Although there are no comparative trials, itraconazole appears more efficacious than either ketoconazole or fluconazole. Thus, itraconazole is the initial treatment of choice for nonlife-threatening non-CNS blastomycosis.
Advances in statistical methodology for the evaluation of diagnostic and laboratory testsG. Douglas Campbell|Statistics in Medicine|1994 The ROC plot is a useful tool in the evaluation of the performance of medical tests for separating two populations. For a two-state decision rule based on such a test, the ROC plot is the graph of all observed (1-specificity, sensitivity) pairs. Each point on this empirical plot can be represented by a 2 x 2 contingency table. The non-parametric statistics of Mann-Whitney and Kolmogorov-Smirnov can be immediately identified on this plot. Local non-parametric confidence interval procedures related to the theoretical ROC curve are briefly reviewed. For continuous data, two new simultaneous confidence regions associated with the ROC curve are presented, one based on Kolmogorov-Smirnov confidence bands for distribution functions and the other based on bootstrapping. Two different tests on the same patients can be compared on the ROC scale. For continuous data, one important problem concerns the comparison of two ROC plots (as would arise from two correlated diagnostic tests on each patient) using a sup norm (this metric can detect differences that the ROC area cannot). The distribution of a statistic based on this norm is studied, using the bootstrap. A biomedical example illustrates the methodologies.