We aimed to assess the rate and predictive factors of bloodstream infection (BSI) due to multidrug-resistant (MDR) Pseudomonas aeruginosa in neutropenic cancer patients. We performed a multicenter, retrospective cohort study including oncohematological neutropenic patients with BSI due to P. aeruginosa conducted across 34 centers in 12 countries from January 2006 to May 2018. A mixed logistic regression model was used to estimate a model to predict the multidrug resistance of the causative pathogens. Of a total of 1,217 episodes of BSI due to P. aeruginosa, 309 episodes (25.4%) were caused by MDR strains. The rate of multidrug resistance increased significantly over the study period (P 0.033). Predictors of MDR P. aeruginosa BSI were prior therapy with piperacillin-tazobactam (odds ratio [OR], 3.48; 95% confidence interval [CI], 2.29 to 5.30), prior antipseudomonal carbapenem use (OR, 2.53; 95% CI, 1.65 to 3.87), fluoroquinolone prophylaxis (OR, 2.99; 95% CI, 1.92 to 4.64), underlying hematological disease (OR, 2.09; 95% CI, 1.26 to 3.44), and the presence of a urinary catheter (OR, 2.54; 95% CI, 1.65 to 3.91), whereas older age (OR, 0.98; 95% CI, 0.97 to 0.99) was found to be protective. Our prediction model achieves good discrimination and calibration, thereby identifying neutropenic patients at higher risk of BSI due to MDR P. aeruginosa. The application of this model using a web-based calculator may be a simple strategy to identify high-risk patients who may benefit from the early administration of broad-spectrum antibiotic coverage against MDR strains according to the local susceptibility patterns, thus avoiding the use of broad-spectrum antibiotics in patients at a low risk of resistance development.

Clinical Predictive Model of Multidrug Resistance in Neutropenic Cancer Patients with Bloodstream Infection Due to Pseudomonas aeruginosa

M. Peghin;
2020-01-01

Abstract

We aimed to assess the rate and predictive factors of bloodstream infection (BSI) due to multidrug-resistant (MDR) Pseudomonas aeruginosa in neutropenic cancer patients. We performed a multicenter, retrospective cohort study including oncohematological neutropenic patients with BSI due to P. aeruginosa conducted across 34 centers in 12 countries from January 2006 to May 2018. A mixed logistic regression model was used to estimate a model to predict the multidrug resistance of the causative pathogens. Of a total of 1,217 episodes of BSI due to P. aeruginosa, 309 episodes (25.4%) were caused by MDR strains. The rate of multidrug resistance increased significantly over the study period (P 0.033). Predictors of MDR P. aeruginosa BSI were prior therapy with piperacillin-tazobactam (odds ratio [OR], 3.48; 95% confidence interval [CI], 2.29 to 5.30), prior antipseudomonal carbapenem use (OR, 2.53; 95% CI, 1.65 to 3.87), fluoroquinolone prophylaxis (OR, 2.99; 95% CI, 1.92 to 4.64), underlying hematological disease (OR, 2.09; 95% CI, 1.26 to 3.44), and the presence of a urinary catheter (OR, 2.54; 95% CI, 1.65 to 3.91), whereas older age (OR, 0.98; 95% CI, 0.97 to 0.99) was found to be protective. Our prediction model achieves good discrimination and calibration, thereby identifying neutropenic patients at higher risk of BSI due to MDR P. aeruginosa. The application of this model using a web-based calculator may be a simple strategy to identify high-risk patients who may benefit from the early administration of broad-spectrum antibiotic coverage against MDR strains according to the local susceptibility patterns, thus avoiding the use of broad-spectrum antibiotics in patients at a low risk of resistance development.
2020
2020
multidrug resistant, Pseudomonas aeruginosa, bacteremia, bloodstream infection, neutropenia, cancer, risk factors, predictive model
Gudiol, C.; Albasanz-Puig, A.; Laporte-Amarg??s, J.; Pallar??s, N.; Mussetti, A.; Ruiz-Camps, I.; Puerta-Alcalde, P.; Abdala, E.; Oltolini, C.; Akova, M.; Montejo, M.; Mikulska, M.; Mart??n-D??vila, P.; Herrera, F.; Gasch, O.; Drgona, L.; Paz Morales, H.; Brunel, A. -S.; Garc??a, E.; Isler, B.; Kern, W. V.; Morales, I.; Maestro-de la Calle, G.; Montero, M.; Kanj, S. S.; Sipahi, O. R.; Calik, S.; M??rquez-G??mez, I.; Marin, J. I.; Gomes, M. Z. R.; Hemmatti, P.; Araos, R.; Peghin, M.; del Pozo, J. L.; Y????ez, L.; Tilley, R.; Manzur, A.; Novo, A.; Carratal??, J.; Cuervo, Guillermo; Escrihuela-Vidal, Francesc; Tubau, Fe; Teb??, Cristian; Rodr??guez Arias, Marisol; Aguilar-Company, Juan; Larrosa, Nieves; Cardozo, Celia; Garcia-Vidal, Carolina; Karim-Yaqub, Ibrahim; Greco, Raffaella; Cichero, Paola; Merve Ayaz, Caglayan; C??spedes, Roberto; L??pez-Soria, Leire; Magnasco, Laura; Fort??n, Jes??s; Torres, Diego; Bot??, Anna; Espasa, Mateu; Hold Montaguti, Mia; Bochud, Pierre-Yves; Manuel, Oriol; Tabares Carrasco, Salvador; Serrano L??pez, Josefina; Bertz, Hartmut; Rieg, Siegbert; de Cueto, Marina; Rodr??guez-Ba??o, Jes??s; Lizasoain, Manuel; Mar??a Aguado, Jos??; Pablo Horcajada, Juan; El Zein, Saeed; Jabbour, Jean-Francois; Uyan-Onal, Ayse; Nazli-Zeka, Arzu; Palop, Bego??a; Clemencia Correa, Lina; Aparecida da Silva Machado, Amanda; Pedro Silva Tonh??, Jo??o; Maschmeyer, Georg; Munita, Jose; Bassetti, Matteo; Castaldo, Nadia; Sangro del Alc??zar, Paloma
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2140673
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