title: Early serum galactomannan trend as a predictor of outcome of invasive aspergillosis.
abstract: The monitoring and prediction of treatment responses to invasive aspergillosis (IA) are difficult. We determined whether serum galactomannan index (GMI) trends early in the course of disease may be useful in predicting eventual clinical outcomes. For the subjects recruited into the multicenter Global Aspergillosis Study, serial GMIs were measured at baseline and at weeks 1, 2, and 4 following antifungal treatment. Clinical response and survival at 12 weeks were the outcome measures. GMI trends were analyzed by using the generalized estimation equation approach. GMI cutoffs were evaluated by using receiver-operating curve analyses incorporating pre- and posttest probabilities. Of the 202 study patients diagnosed with IA, 71 (35.1%) had a baseline GMI of ≥ 0.5. Week 1 GMI was significantly lower for the eventual responders to treatment at week 12 than for the nonresponders (GMIs of 0.62 ± 0.12 and 1.15 ± 0.22, respectively; P = 0.035). A GMI reduction of >35% between baseline and week 1 predicted a probability of a satisfactory clinical response. For IA patients with pretreatment GMIs of <0.5 (n = 131; 64.9%), GMI ought to remain low during treatment, and a rising absolute GMI to >0.5 at week 2 despite antifungal treatment heralded a poor clinical outcome. Here, every 0.1-unit increase in the GMI between baseline and week 2 increased the likelihood of an unsatisfactory clinical response by 21.6% (P = 0.018). In summary, clinical outcomes may be anticipated by charting early GMI trends during the first 2 weeks of antifungal therapy. These findings have significant implications for the management of IA.
authors.affiliation: Department of Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
authors.forename: Louis Y A
authors.initials: LY
authors.lastname: Chai
authors.forename: Bart-Jan
authors.initials: BJ
authors.lastname: Kullberg
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Johnson
authors.forename: Steven
authors.initials: S
authors.lastname: Teerenstra
authors.forename: Lay Wai
authors.initials: LW
authors.lastname: Khin
authors.forename: Alieke G
authors.initials: AG
authors.lastname: Vonk
authors.forename: Johan
authors.initials: J
authors.lastname: Maertens
authors.forename: Olivier
authors.initials: O
authors.lastname: Lortholary
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Donnelly
authors.forename: Haran T
authors.initials: HT
authors.lastname: Schlamm
authors.forename: Peter F
authors.initials: PF
authors.lastname: Troke
authors.forename: Mihai G
authors.initials: MG
authors.lastname: Netea
authors.forename: Raoul
authors.initials: R
authors.lastname: Herbrecht
mesh_terms: D015415:Biomarkers / Q000097:blood*; D016903:Drug Monitoring / Q000379:methods*; D005260:Female; D005690:Galactose / Q000031:analogs & derivatives; D006801:Humans; D055744:Invasive Pulmonary Aspergillosis / Q000175:diagnosis* / Q000188:drug therapy / Q000401:mortality; D008297:Male; D008351:Mannans / Q000097:blood*; D011379:Prognosis; D012372:ROC Curve; D044967:Serum / Q000737:chemistry*; D016019:Survival Analysis; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D008351:Mannans; C012990:galactomannan; D005690:Galactose