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Updated: May 11, 2026

Detection of Invasive Pulmonary Aspergillosis in Haematological Malignancy Patients by using Lateral-flow Technology
Published on: March 22, 2012
Age difference of patients with and without invasive aspergillosis: a systematic review and meta-analysis
Elena Shekhova1, Fabián Salazar2, Alessandra Da Silva Dantas3
1Medical Research Council Centre for Medical Mycology, Geoffrey Pope Building, University of Exeter, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK. shekhova.elena@yandex.com.
Background:
Invasive Aspergillosis (IA) is a life-threatening fungal disease with significant mortality rates. Timely diagnosis and treatment greatly enhance patient outcomes. This study aimed to explore the association between patient age and the development of IA, as well as the potential implications for risk stratification strategies.
Methods:
We searched National Center for Biotechnology Information (NCBI) databases for publications until October 2023 containing age characteristics of patients with and without IA. A random-effects model with the application of inverse-variance weighting was used to pool reported estimates from each study, and meta-regression and subgroup analyses were utilized to assess sources of heterogeneity.
Results:
A systematic review was conducted, resulting in the inclusion of 55 retrospective observational studies with a total of 13,983 patients. Meta-analysis revealed that, on average, patients with IA were approximately two and a half years older (95% Confidence Interval [CI] 1.84-3.31 years; I2 = 26.1%) than those without the disease (p < 0.0001). No significant moderators could explain the observed heterogeneity in age difference. However, subgroup analysis revealed that age differences were more pronounced within particular patient groups compared to others. For example, patients with and without IA who had primary severe lung infections exhibited a greater difference in mean age than other patient cohorts.
Conclusions:
Further research, such as individual patient data meta-analysis, is necessary to better understand the potential relationship between increasing age and the likelihood of IA. Improved risk stratification strategies based on patient age could potentially enhance the early detection and treatment of IA, ultimately improving patient outcomes.
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