Geographic Influence Upon Noninfectious Diseases Accounting for Fever of Unknown Origin: A Systematic Review and Meta-Analysis

BACKGROUND: Diagnostic outcomes for fever of unknown origin (FUO) remain with notable numbers of undiagnosed cases. A recent systemic review and meta-analysis of studies reported geographic variation in FUO-related infectious diseases. Whether geography influences types of FUO noninfectious diagnoses deserves examination. METHODS: We systematically searched Medline (PubMed), Embase, Scopus, and Web of Science databases using medical subject headings published from January 1, 1997 to March 31, 2021. Prospective clinical studies investigating participants meeting adult FUO defining criteria were selected if they assessed final diagnoses. Meta-analyses were based on the random-effects model according to World Health Organization (WHO) geographical regions. RESULTS: Nineteen studies with significant heterogeneity were analyzed, totaling 2667 participants. Noninfectious inflammatory disorders had a pooled estimate at 20.0% (95% confidence interval [CI], 17.0%–23.0%). Undiagnosed illness had a pooled estimate of 20.0% (95% CI, 14.0%–26.0%). The pooled estimate for cancer was 15.0% (95% CI, 12.0%–18.0%). Miscellaneous conditions had a pooled estimate of 6.0% (95% CI, 4.0%–8.0%). Noninfectious inflammatory disorders and miscellaneous conditions were most prevalent in the Western Pacific region with a 27.0% pooled estimate (95% CI, 20.0%–34.0%) and 9.0% (95% CI, 7.0%–11.0%), respectively. The highest pooled estimated for cancer was in the Eastern Mediterranean region at 25.0% (95% CI, 18.0%–32.0%). Adult-onset Still’s disease (114 [58.5%]), systemic lupus (52 [26.7%]), and giant-cell arteritis (40 [68.9%]) predominated among the noninfectious inflammatory group. Lymphoma (164 [70.1%]) was the most common diagnosis in the cancer group. CONCLUSIONS: In this systematic review and meta-analysis, noninfectious disease diagnostic outcomes varied among WHO-defined geographies. Evaluations for FUO should include local variations in disease prevalence.