Open AccessPrediction of Acute COPD Exacerbation in the Swiss Multicenter COPD Cohort Study (TOPDOCS) by Clinical Parameters, Medication Use, and Immunological Biomarkers
Author(s) -
Simona Tabea Huebner,
Simona Henny,
Stéphanie Giezendanner,
Thomas Brack,
Martin Brutsche,
Prashant N. Chhajed,
Christian F. Clarenbach,
Thomas Dieterle,
Adrian Egli,
Martin Frey,
Ingmar Heijnen,
Sarosh Irani,
Noriane A. Sievi,
Robert Thurnheer,
Marten Trendelenburg,
Malcolm Kohler,
Anne Leuppi-Taegtmeyer,
Joerg D. Leuppi
Publication year - 2021
Publication title -
respiration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.264
H-Index - 81
eISSN - 1423-0356
pISSN - 0025-7931
DOI - 10.1159/000520196
Subject(s) - medicine , copd , exacerbation , biomarker , receiver operating characteristic , area under the curve , cohort , acute exacerbation of chronic obstructive pulmonary disease , cohort study , obstructive lung disease , biochemistry , chemistry
Background and Objective: Whether immunological biomarkers combined with clinical characteristics measured during an exacerbation-free period are predictive of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) frequency and severity is unknown. Method: We measured immunological biomarkers and clinical characteristics in 271 stable chronic obstructive pulmonary disease (COPD) patients (67% male, mean age 63 years) from “The Obstructive Pulmonary Disease Outcomes Cohort of Switzerland” cohort on a single occasion. One-year follow-up data were available for 178 patients. Variables independently associated with AECOPD frequency and severity were identified by multivariable regression analyses. Receiver operating characteristic analysis was used to obtain optimal cutoff levels and measure the area under the curve (AUC) in order to assess if baseline data can be used to predict future AECOPD. Results: Higher number of COPD medications (adjusted incident rate ratio [aIRR] 1.17) and platelet count (aIRR 1.03), and lower FEV1% predicted (aIRR 0.84) and IgG2 (aIRR 0.84) were independently associated with AECOPD frequency in the year before baseline. Optimal cutoff levels for experiencing frequent (>1) AECOPD were ≥3 COPD medications (AUC = 0.72), FEV1 ≤40% predicted (AUC = 0.72), and IgG2 ≤2.6 g/L (AUC = 0.64). The performance of a model using clinical and biomarker parameters to predict future, frequent AECOPD events in the same patients was fair (AUC = 0.78) but not superior to a model using only clinical parameters (AUC = 0.79). The IFN-lambda rs8099917GG-genotype was more prevalent in patients who had severe AECOPD. Conclusions: Clinical and biomarker parameters assessed at a single point in time correlated with the frequency of AECOPD events during the year before and the year after assessment. However, only clinical parameters had fair discriminatory power in identifying patients likely to experience frequent AECOPD.