Defining Invasive Fungal Infection Risk in Hematological Malignancies: A New Tool for Clinical Practice
Benedetta Rambaldi1, Domenico Russo1 and Livio Pagano2
Corresponding
author: Benedetta Rambaldi. Cattedra di Ematologia, Unità di Malattie
del Sangue e Trapianto di Midollo Osseo, Dipartimento di Scienze
Cliniche e Sperimentali, Università di Brescia e ASST Spedali Civili,
Brescia, Italy. E-mail: detta.rambaldi@hotmail.it
Published: January 1, 2017
Received: November 16, 2016
Accepted: December 11, 2016
Mediterr J Hematol Infect Dis 2017, 9(1): e2017012 DOI 10.4084/MJHID.2017.012
This article is available on PDF format at:
Received: November 16, 2016
Accepted: December 11, 2016
Mediterr J Hematol Infect Dis 2017, 9(1): e2017012 DOI 10.4084/MJHID.2017.012
This article is available on PDF format at:
| This is an Open Access article distributed
under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dear Editor,
Invasive
fungal infections (IFIs) represent an important cause of morbidity and
mortality in patients affected by hematological malignancies (HMs),
particularly those with an immunocompromised status.[1,2]
In this setting, IFIs still represents a major clinical problem also
for the high costs related to the antifungal prophylaxis and treatment.[3,4]
When considering the high clinical heterogeneity of these patients, the
risk of IFIs may be remarkably different. Accordingly, if such a risk
is not appropriately evaluated, the possibility of an overtreatment in
some or an undertreatment in other patients is very likely.
Pagano et al., on behalf of SEIFEM (Sorveglianza Epidemiologica Infezioni Fungine nelle Emopatie Maligne) group, recently published a systematic review of the literature on the risk and incidence of IFIs in the setting of HMs with the aim to consider the main predisposing factors and to suggest practical strategies for prevention and treatment of IFIs.[5] In this review, specific IFI predisposing factors are summarized for each disease class. Depending on the risk of developing IFIs, patients are then divided into three groups: high, intermediate, low-risk group. Briefly, patients with acute myeloid leukemia (AML) or treated with an allogeneic hematopoietic stem cell transplantation (HSCT) have per se an increased risk of IFI. Moreover, some conditions predispose a high risk of IFI, independently of the underlying disease, like neutropenia, relapse/refractory disease, previous history of IFI, salvage therapy and a high dose of steroids.
To facilitate the reading of this analysis and to estimate in each patient the IFI specific risk, we here propose a practical consultation tool composed of a table where risk categories, their related risk factors, and the HMs, are reported and matched (Table 1, part 1 and 2). This estimated risk stratification was developed correlating each disease class with the variables risk factors, categorized according to patient’s features, underlying comorbidities, immunity status, environmental factors, neutropenic status, disease and therapy or transplant’s procedures.
By this approach, each box of the table represents a matching of a specific disease with a specific risk factor. Red boxes, expressing a high risk (HR) of IFI, are used to indicate a reported incidence of IFI above 5%; yellow boxes, expressing an intermediate risk (IR) of IFI, are used to indicate a reported incidence of IFI of 2-5%; green boxes, expressing low risk (LR) of IFI, are used to indicate a reported incidence of IFI minor of 2%. In the case of lacking data, the boxes are white.
Looking at the colored boxes, people can read this table from two different points of view, by focusing on the risk categories or vice versa on the specific HM. In general, the horizontal reading of the table highlights the principal IFI risk factors, regardless of the underlying disease. In particular, red boxes appear to be associated with a long history of HM, with a relapse or refractory disease, a prolong neutropenia, older age, predisposing polymorphisms, pulmonary comorbidities, intense chemotherapy and prolong used of steroids. Some of these risk factors are routinely screened in the clinical practice, others, like predisposing genetic polymorphisms, are used only in experimental setting, but look promising. On the other hand, the vertical reading of the table highlights the disease mostly associated with IFI, in particular, AML and patients undergoing HSCT.
It should be underlined that each disease may present one or more risk factors and that the risk factors may vary during the course of illness and due to the type of treatments. For this reasons, it is important to follow the patient over time, with a dynamic score, evaluating the presence or absence of risk factors, with the aim to start or withdrawn an appropriate antifungal prophylaxis or treatment. In this setting, this table allows a rapid consultation in the clinical practice.
In conclusion, this IFI’s risk table may represent a useful and simple tool to assess over time the risk of developing IFI in patients with HMs and may help to plan an appropriate antifungal stewardship.
Pagano et al., on behalf of SEIFEM (Sorveglianza Epidemiologica Infezioni Fungine nelle Emopatie Maligne) group, recently published a systematic review of the literature on the risk and incidence of IFIs in the setting of HMs with the aim to consider the main predisposing factors and to suggest practical strategies for prevention and treatment of IFIs.[5] In this review, specific IFI predisposing factors are summarized for each disease class. Depending on the risk of developing IFIs, patients are then divided into three groups: high, intermediate, low-risk group. Briefly, patients with acute myeloid leukemia (AML) or treated with an allogeneic hematopoietic stem cell transplantation (HSCT) have per se an increased risk of IFI. Moreover, some conditions predispose a high risk of IFI, independently of the underlying disease, like neutropenia, relapse/refractory disease, previous history of IFI, salvage therapy and a high dose of steroids.
To facilitate the reading of this analysis and to estimate in each patient the IFI specific risk, we here propose a practical consultation tool composed of a table where risk categories, their related risk factors, and the HMs, are reported and matched (Table 1, part 1 and 2). This estimated risk stratification was developed correlating each disease class with the variables risk factors, categorized according to patient’s features, underlying comorbidities, immunity status, environmental factors, neutropenic status, disease and therapy or transplant’s procedures.
| Table 1 (part 1). IFI risk table: risk categories and their related risk factors are reported in the first and second column of the table, respectively; the HMs are listed in the first row of the table. |
| Table 1 (part 2). IFI risk table: risk categories and their related risk factors are reported in the first and second column of the table, respectively; the HMs are listed in the first row of the table. |
By this approach, each box of the table represents a matching of a specific disease with a specific risk factor. Red boxes, expressing a high risk (HR) of IFI, are used to indicate a reported incidence of IFI above 5%; yellow boxes, expressing an intermediate risk (IR) of IFI, are used to indicate a reported incidence of IFI of 2-5%; green boxes, expressing low risk (LR) of IFI, are used to indicate a reported incidence of IFI minor of 2%. In the case of lacking data, the boxes are white.
Looking at the colored boxes, people can read this table from two different points of view, by focusing on the risk categories or vice versa on the specific HM. In general, the horizontal reading of the table highlights the principal IFI risk factors, regardless of the underlying disease. In particular, red boxes appear to be associated with a long history of HM, with a relapse or refractory disease, a prolong neutropenia, older age, predisposing polymorphisms, pulmonary comorbidities, intense chemotherapy and prolong used of steroids. Some of these risk factors are routinely screened in the clinical practice, others, like predisposing genetic polymorphisms, are used only in experimental setting, but look promising. On the other hand, the vertical reading of the table highlights the disease mostly associated with IFI, in particular, AML and patients undergoing HSCT.
It should be underlined that each disease may present one or more risk factors and that the risk factors may vary during the course of illness and due to the type of treatments. For this reasons, it is important to follow the patient over time, with a dynamic score, evaluating the presence or absence of risk factors, with the aim to start or withdrawn an appropriate antifungal prophylaxis or treatment. In this setting, this table allows a rapid consultation in the clinical practice.
In conclusion, this IFI’s risk table may represent a useful and simple tool to assess over time the risk of developing IFI in patients with HMs and may help to plan an appropriate antifungal stewardship.
References
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