Antifungal Strategy in Patients with Invasive Fungal Disease Associated with Hematological Malignancies Based on Risk Stratification.
Lijin ChenLuting LuoYanxin ChenYinzhou WangJing LiXiaoyun ZhengTing YangJian-da HuPublished in: The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale (2022)
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.