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Published on: March 22, 2012
Diagnostic-driven antifungal therapy in neutropenic patients using the D-index and serial serum galactomannan testing
Marcia Garnica1, Aline Sinhorelo1, Laura Madeira1
1Universidade Federal do Rio de Janeiro (UFRJ), Hospital Universitário, Departmento de Medicina Interna, Rio de Janeiro, RJ, Brazil.
Introduction:
Invasive mold disease is an important complication of patients with hematologic malignancies, and is associated with high mortality. A diagnostic-driven approach has been an alternative to the classical empiric antifungal therapy. In the present study we tested an algorithm that incorporated risk stratification using the D-index, serial serum galactomannan and computed tomographic-scan to guide the decision to start antifungal therapy in neutropenic patients.
Patients And Methods:
Between May 2010 and August 2012, patients with acute leukemia in induction remission were prospectively monitored from day 1 of chemotherapy until discharge or death with the D-index and galactomannan. Patients were stratified in low, intermediate and high risk according to the D-index and an extensive workup for invasive mold disease was performed in case of positive galactomannan (≥0.5), persistent fever, or the appearance of clinical manifestations suggestive of invasive mold disease.
Results:
Among 29 patients, 6 (21%), 11 (38%), and 12 (41%) were classified as high, intermediate, and low risk, respectively. Workup for invasive mold disease was undertaken in 67%, 73% and 58% (p=0.77) of patients in each risk category, respectively, and antifungal therapy was given to 67%, 54.5%, and 17% (p=0.07). Proven or probable invasive mold disease was diagnosed in 67%, 45.5%, and in none (p=0.007) of high, intermediate, and low risk patients, respectively. All patients survived.
Conclusion:
A risk stratification using D-index was a useful instrument to be incorporated in invasive mold disease diagnostic approach, resulting in a more comprehensive antifungal treatment strategy, and to guide an earlier start of treatment in afebrile patients under very high risk.
Insights
A diagnostic algorithm using the D-index and galactomannan successfully identified patients at high risk for invasive mold disease, enabling earlier antifungal treatment and improving outcomes in neutropenic patients with hematologic malignancies.
Area of Science:
- Hematology
- Infectious Diseases
- Medical Mycology
Background:
- Invasive mold disease (IMD) is a serious complication in patients with hematologic malignancies, associated with high mortality.
- A diagnostic-driven approach offers an alternative to empirical antifungal therapy.
- This study evaluated an algorithm integrating risk stratification (D-index), serum galactomannan, and CT scans to guide antifungal treatment decisions.
Purpose of the Study:
- To assess the utility of a diagnostic algorithm incorporating the D-index for risk stratification in neutropenic patients.
- To guide the initiation of antifungal therapy based on risk assessment and diagnostic markers.
- To improve the management of invasive mold disease in patients undergoing chemotherapy for acute leukemia.
Main Methods:
- Prospective monitoring of acute leukemia patients undergoing induction remission chemotherapy.
- Stratification into low, intermediate, and high-risk groups using the D-index.
- Workup for IMD triggered by positive galactomannan (≥0.5), persistent fever, or suggestive clinical signs.
Main Results:
- Proven or probable IMD was diagnosed in 67% of high-risk, 45.5% of intermediate-risk, and 0% of low-risk patients (p=0.007).
- Antifungal therapy was initiated in 67% of high-risk, 54.5% of intermediate-risk, and 17% of low-risk patients (p=0.07).
- All patients in the study survived, regardless of risk stratification.
Conclusions:
- Risk stratification using the D-index is valuable for diagnosing invasive mold disease.
- The D-index aids in developing a comprehensive antifungal treatment strategy.
- This approach facilitates earlier antifungal treatment initiation, particularly in afebrile, high-risk patients.

