Immune markers measured before treatment predict outcome of intensive phase tuberculosis therapy
| Autor: | N M Carroll, P. D. van Helden, Martin Kidd, F. Salker, Nulda Beyers, G F Black, Pauline T. Lukey, Ken Duncan, Gerhard Walzl, S Brahmbhatt |
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| Rok vydání: | 2006 |
| Předmět: |
Adult
Male Tuberculosis Lymphocyte Immunology Antitubercular Agents Leukocyte Count White blood cell Immunopathology Clinical Studies medicine Humans Immunology and Allergy Tuberculosis Pulmonary medicine.diagnostic_test business.industry Monocyte Sputum Middle Aged Prognosis medicine.disease Clinical trial Treatment Outcome medicine.anatomical_structure Cytokines Female medicine.symptom Epidemiologic Methods Chest radiograph business Biomarkers |
| Zdroj: | Clinical and Experimental Immunology. 146:243-252 |
| ISSN: | 1365-2249 0009-9104 |
| DOI: | 10.1111/j.1365-2249.2006.03211.x |
| Popis: | SummaryThe development of a statistical model based on simple immunological markers which could predict the response to tuberculosis treatment would facilitate clinical trials of new anti-tuberculosis drugs. We have examined the ability of immunological biomarkers, measured at diagnosis and after 4 weeks of treatment, to predict sputum smear status at week 8. Eighteen tuberculosis patients with positive Ziehl–Nielsen (ZN)-stained sputum smears 8 weeks after initiation of treatment (slow response) were matched for age, gender, sputum smear grade and extent of disease on chest radiograph to 18 patients with negative sputum smears at week 8 (fast response). In addition to total white blood cell (WBC) counts and absolute lymphocyte, monocyte and neutrophil numbers, concentrations of six serum markers were measured by enzyme-linked immunosorbent assay (ELISA) in all patients (soluble interleukin-2 receptor alpha (sIL-2Rα), granzyme B, soluble tumour necrosis factor alpha receptors 1 and 2 (sTNF-R1 and -2), nitrotyrosine and interferon-gamma (IFN-γ). At diagnosis, 4 biomarkers (sTNF-R1, total WBC, absolute monocyte and absolute neutrophil numbers) were significantly higher in slow response patients. At week 4, total WBC count and absolute monocyte and neutrophil numbers remained significantly higher in slow responders. Discriminant analysis of the diagnosis and week 4 data provided models for classification of slow response patients with 67% and 83% predictive accuracy. We suggest that treatment response phenotypes can be determined before the start of treatment. Reliable predictive models would allow targeted interventions for patients at risk for slow treatment response to standard tuberculosis therapy. |
| Databáze: | OpenAIRE |
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