Flucoazole Prophylaxis

Abstract: Infection is the most common cause of morbidity and mortality associated with current ALL treatment. Although antifungal drug is more commonly used in adults with leukemia, its use in children is controversial due to insufficient evidence of effectiveness and concerns about its potential antimicrobial resistance. The use of drugs to prevent fungal infections may lead to cognitive impairment in children1.

In this study, we used resting functional magnetic resonance imaging (fMRI) and Partial least squares (PLS) methods to compare the relationships of the 150 children who did not undergo fungal prophylaxis, 70 received fluconazole prophylaxis and 50 received other prophylaxis2.

 The results showed that antifungal prophylaxis during induction therapy significantly reduced the incidence of infectious events. However, the use of antifungal drugs has negative effects on children’s cognitive function.

Infection is a major complication in pediatric patients with acute lymphoblastic leukemia during chemotherapy, and it is an important cause of death in ALL treatment of children. Currently, 4% of ALL children die from infection, even nonfatal infections can lead to permanent central nerve injury, delayed chemotherapy, changes in treatment regimens, and increased use of antibiotics. Moreover, most infections occur during chemotherapy-induced therapy.

Currently, there are no relevant studies on the prevention of fungal infection with acute lymphoblastic leukemia in China, but in 2017, some Australian institutions studied the prevention effect of levofloxacin in the stage of induction therapy, Prophylactic therapies prevent febrile neutropenia and systemic inflammation. Levofloxacin precautionary measures have reduced antibiotic use and greatly reduced use of c. difficile infections, but the use of levofloxacin for fungal prophylaxis has been banned in China. Therefore, we mainly studied the preventive effect of fluconazole used in China.

Our experimental data come from xi ‘an children’s hospital, We collected information on 310 children with ALL, Patients who had clinical or microbiological records of infection before induction therapy began, or who had a fever that required prolonged antibiotic therapy (4 days) before induction therapy, were excluded from this analysis.

Remaining 150 children who did not undergo fungal prophylaxis, 70 received fluconazole prophylaxis and 50 received other prophylaxis are included. Behavioural and MRI data will be collected within a year. All subjects will have a resting MRI scan and fill out a behavior rating inventory of executive function3.

PLS analysis

Partial least square method is a new multivariate statistical data analysis method2. In a first step, the cross-covariance between the two matrices is computed. Singular value decomposition is then applied to the resulting cross-covariance matrix4. This identifies a set of orthogonal latent variables (LVs), which represent the maximal covariance between brain measures and behavioural measures5. LVs consist of d (the singular value), brain saliences, and behaviour saliences. The number of LVs is equal to the number of behavioural measures included in the analysis6.

Then, every subject’s original brain data (in X ) onto the multivariate brain salience pattern(in V ) produces so-called “brain scores” Lx=XV. Those brain scores give a measure on the similarity of a subject’s individual brain data with the salient brain pattern. Similarly, so-called “design scores” can be computed by Ly =YU, which are every subject’s design variables onto the respective design saliences7. In this analysis, we first used PLSR8 to predict the effect of fluconazole on infection prevention, ALL children were treated with different chemotherapy drugs, which had different effects on the development of their cognitive function. Therefore, PLSC method was first used to analyze the effects of different chemotherapy drugs9. On this basis, we further analyzed the effects of taking the preventive drug fluconazole on the cognitive function of children.

Results (At present, our experiment has no result)

With reference to a similar article (Levofloxacin Prophylaxis During Induction Therapy for Pediatric Acute Lymphoblastic Leukemia. [J] Clinical Infectious Diseases,2017,65(11)), we can assume that our results are Patients who took fluconazole prophylaxis were less likely to become infected, and the drug did not significantly impair cognitive function.

Conclusions (This is our guess of the result of the experiment)

This is a study of fungal prophylaxis in ALL children during induction therapy. We found that the use of fluconazole for fungal prophylaxis in ALL children is effective and generalizable. And in the process we found that the use of amphotericin B, a chemotherapy drug, had an effect on the structure of the temporal lobe of the brain cognitive region in patients with acute lymphoblastic leukemia, leading to a decline in the cognitive function of the patients.

References:

1. Joshua W, Tang L, Patricia M, et al. Levofloxacin prophylaxis during induction therapy for pediatric acute lymphoblastic leukemia[J].Clinical Infectious Diseases, 2017,65(11)
2. Krishnan A, Williams L J , Mcintosh A R, Abdi H, et al. Partial Least Squares (PLS) methods for neuroimaging: a tutorial and review[J]. Neuroimage, 2011, 56 (2) :455-475.
3. Roon P V, Zakizadeh J, Chartier S P, et al. Partial Least Squares tutorial for analyzing neuroimaging data[J]. Tutorials in Quantitative Methods for Psychology, 2014, 10 (2) :200-215
4. Mcintosh A R, Chau W K, Protzner A B, et al. Spatiotemporal analysis of event-related fMRI data using partial least squares[J]. Neuroimage, 2004, 23 (2) :764-775
5. Ziegler G, Dahnke R, Winkler A D, et al. Partial least squares correlation of multivariate cognitive abilities and local brain structure in children and adolescents[J]. Neuroimage, 2013, 82 (2) :284-294
6. Kovacevic N???Mcintosh A R, et al. Groupwise independent component decomposition of EEG data and partial least square analysis[J]. Neuroimage, 2007, 35 (3) :1103-1112
7. Churchill N, Spring N, Abdi H, et al. The stability of behavioral PLS results in ill-posed neuroimaging problems[J]. Springer New York , 2013 , 56 (1) :171-183
8. Z?¶ller D, Schaer M, Scariati E, et al. Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome[J]. Neuroimage, 2017, 149 :85-97
9. Wiebels K, Waldie K E, Roberts P R, et al. Identifying grey matter changes in schizotypy using partial least squares correlation[J]. Cortex, 2016, 81 :137-150

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