Evaluating the use of PCR for diagnosing invasive aspergillosis - Buchheidt, Dieter; Reinwald, Mark; Hofmann, Wolf-Karsten; Boch, Tobias; Spiess, Birgit (Expert review of molecular diagnostics, 2017)
Introduction: Aspergillus species, primarily Aspergillus fumigatus, are still the most emerging fungal pathogens. Within recent years, novel molecular methods have been developed to improve the diagnosis of life-threatening invasive aspergillosis in high risk patients. Especially patients with malignant hematological diseases undergoing intensive chemotherapy are at risk and mortality rates are exceptionally high, in part due to difficulties and delays in establishing a microbiologic diagnosis. Early diagnosis and treatment are crucial for an adequate therapeutical management, but, however, are hardly achieved in the clinical setting because most of the current conventional diagnostic tools either lack specificity or acceptable sensitivity at the critical early phase of the infection.Areas covered: To review the clinical value, advantages and problems as well as drawbacks of molecular approaches, especially polymerase chain reaction (PCR)-based assays to detect genomic DNA of Aspergillus species in clinical samples of immunocompromised, especially hematological patients at high risk for IA, a comprehensive review of the literature was performed and expert opinion was expressed.Expert commentary: The results of numerous attempts to diagnose invasive aspergillosis by PCR-based detection of fungal genome in clinical samples highlight the potential of the PCR technique to improve early diagnosis of invasive aspergillosis in patients with hematological malignancies during intensive antineoplastic treatment, combined with imaging surveillance and serologic diagnostic tools. Further comparative validation of reliable assays in prospective multicenter studies is mandatory and urgently needed in order to establish a harmonization and standardization, so that ‘gold standard assays’ may be incorporated into diagnostic and therapeutic algorithms that improve the prognosis of patients with life-threatening infections caused by Aspergillus species.
Gesehen am 04.04.2018