Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification

Patients with hematological malignancies (HM) often develop the invasive fungal disease (IFD), causing important morbidity/mortality. While treatment guidelines are available, risk stratification models for optimizing antifungal therapy strategies are few. Clinical records from 458 HM patients with...

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Main Authors: Lijin Chen, Luting Luo, Yanxin Chen, Yinzhou Wang, Jing Li, Xiaoyun Zheng, Ting Yang, Jianda Hu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Canadian Journal of Infectious Diseases and Medical Microbiology
Online Access:http://dx.doi.org/10.1155/2022/1743596
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author Lijin Chen
Luting Luo
Yanxin Chen
Yinzhou Wang
Jing Li
Xiaoyun Zheng
Ting Yang
Jianda Hu
author_facet Lijin Chen
Luting Luo
Yanxin Chen
Yinzhou Wang
Jing Li
Xiaoyun Zheng
Ting Yang
Jianda Hu
author_sort Lijin Chen
collection DOAJ
description Patients with hematological malignancies (HM) often develop the invasive fungal disease (IFD), causing important morbidity/mortality. While treatment guidelines are available, risk stratification models for optimizing antifungal therapy strategies are few. Clinical records from 458 HM patients with IFD were retrospectively analyzed. Following Chinese treatment guidelines, patients received empirical (n = 239) or diagnostic-driven therapy (n = 219). The effectiveness rate was 87.9% for the empirical and 81.7% for the diagnostic-driven therapy groups (P≥0.05). The incidence of adverse reactions was 18.4% and 16.9%, respectively (P≥0.05). All risk factors of IFD in HM patients were estimated in the univariate analyses and multivariate analyses by the chi-square test and logistic regression model. Duration ≥14 days (OR = 18.340, P=0.011), relapsed/refractory disease (OR = 11.670, P=0.005), IFD history (OR = 5.270, P=0.021), and diabetes (OR = 3.120, P=0.035) were significantly associated with IFD in the multivariate analysis. Patients with more than 3 of these factors have a significant difference in effective rates between the empirical (85.7%) and diagnostic-driven (41.6%) therapy (P=0.008). Empirical and diagnostic-driven therapy effective rates were 80.6% and 70.9% in the patients with two risk factors (P>0.05) and 85.1% and 85.4% in the patients with one risk factor (P>0.05). Thus, there was no significant difference in effectiveness in patients with one or two risk factors. The abovementioned risk stratification can guide clinical antifungal therapy. The patients with 3 or more risk factors benefit from empirical therapy.
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spelling doaj-art-8dbaa130a88249bf9ac763fc2bb4b3ec2025-08-20T03:37:54ZengWileyCanadian Journal of Infectious Diseases and Medical Microbiology1918-14932022-01-01202210.1155/2022/1743596Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk StratificationLijin Chen0Luting Luo1Yanxin Chen2Yinzhou Wang3Jing Li4Xiaoyun Zheng5Ting Yang6Jianda Hu7Department of HematologyDepartment of HematologyDepartment of HematologyThe Second Hospital of SanmingDepartment of HematologyDepartment of HematologyDepartment of HematologyDepartment of HematologyPatients with hematological malignancies (HM) often develop the invasive fungal disease (IFD), causing important morbidity/mortality. While treatment guidelines are available, risk stratification models for optimizing antifungal therapy strategies are few. Clinical records from 458 HM patients with IFD were retrospectively analyzed. Following Chinese treatment guidelines, patients received empirical (n = 239) or diagnostic-driven therapy (n = 219). The effectiveness rate was 87.9% for the empirical and 81.7% for the diagnostic-driven therapy groups (P≥0.05). The incidence of adverse reactions was 18.4% and 16.9%, respectively (P≥0.05). All risk factors of IFD in HM patients were estimated in the univariate analyses and multivariate analyses by the chi-square test and logistic regression model. Duration ≥14 days (OR = 18.340, P=0.011), relapsed/refractory disease (OR = 11.670, P=0.005), IFD history (OR = 5.270, P=0.021), and diabetes (OR = 3.120, P=0.035) were significantly associated with IFD in the multivariate analysis. Patients with more than 3 of these factors have a significant difference in effective rates between the empirical (85.7%) and diagnostic-driven (41.6%) therapy (P=0.008). Empirical and diagnostic-driven therapy effective rates were 80.6% and 70.9% in the patients with two risk factors (P>0.05) and 85.1% and 85.4% in the patients with one risk factor (P>0.05). Thus, there was no significant difference in effectiveness in patients with one or two risk factors. The abovementioned risk stratification can guide clinical antifungal therapy. The patients with 3 or more risk factors benefit from empirical therapy.http://dx.doi.org/10.1155/2022/1743596
spellingShingle Lijin Chen
Luting Luo
Yanxin Chen
Yinzhou Wang
Jing Li
Xiaoyun Zheng
Ting Yang
Jianda Hu
Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
Canadian Journal of Infectious Diseases and Medical Microbiology
title Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
title_full Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
title_fullStr Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
title_full_unstemmed Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
title_short Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification
title_sort antifungal strategy in patients with invasive fungal disease associated with hematological malignancies based on risk stratification
url http://dx.doi.org/10.1155/2022/1743596
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