Pharmacogenetics-Based Preliminary Algorithm to Predict the Incidence of Infection in Patients Receiving Cytotoxic Chemotherapy for Hematological Malignancies: A Discovery Cohort.

Autor:	Martinez MF; Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile.; Departamento de Ciencias y Tecnología Farmacéuticas, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago de Chile, Chile.; Latin American Network for the Implementation and Validation of Pharmacogenomic Clinical Guidelines (RELIVAF-CYTED), Madrid, Spain., Alveal E; Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile., Soto TG; Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile.; Departamento De Ciencias Básicas Santiago, Facultad De Ciencias, Universidad Santo Tomás, Santiago, Chile., Bustamante EI; Cancer Institute Arturo López Pérez Foundation, Santiago, Chile., Ávila F; Clinical Hospital of the University of Chile, Santiago, Chile., Bangdiwala SI; Population Health Research Institute, McMaster University, Hamilton, ON, Canada.; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada., Flores I; Cancer Institute Arturo López Pérez Foundation, Santiago, Chile., Monterrosa C; Cancer Institute Arturo López Pérez Foundation, Santiago, Chile., Morales R; Cancer Institute Arturo López Pérez Foundation, Santiago, Chile., Varela NM; Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile.; Latin American Network for the Implementation and Validation of Pharmacogenomic Clinical Guidelines (RELIVAF-CYTED), Madrid, Spain., Fohner AE; Department of Epidemiology and Institute of Public Health Genetics, University of Washington, Seattle, WA, United States., Quiñones LA; Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile.; Latin American Network for the Implementation and Validation of Pharmacogenomic Clinical Guidelines (RELIVAF-CYTED), Madrid, Spain.
Jazyk:	angličtina
Zdroj:	Frontiers in pharmacology [Front Pharmacol] 2021 Mar 10; Vol. 12, pp. 602676. Date of Electronic Publication: 2021 Mar 10 (Print Publication: 2021).
DOI:	10.3389/fphar.2021.602676
Abstrakt:	Introduction: Infections in hematological cancer patients are common and usually life-threatening; avoiding them could decrease morbidity, mortality, and cost. Genes associated with antineoplastics' pharmacokinetics or with the immune/inflammatory response could explain variability in infection occurrence. Objective: To build a pharmacogenetic-based algorithm to predict the incidence of infections in patients undergoing cytotoxic chemotherapy. Methods: Prospective cohort study in adult patients receiving cytotoxic chemotherapy to treat leukemia, lymphoma, or myeloma in two hospitals in Santiago, Chile. We constructed the predictive model using logistic regression. We assessed thirteen genetic polymorphisms (including nine pharmacokinetic-related genes and four inflammatory response-related genes) and sociodemographic/clinical variables to be incorporated into the model. The model's calibration and discrimination were used to compare models; they were assessed by the Hosmer-Lemeshow goodness-of-fit test and area under the ROC curve, respectively, in association with Pseudo-R 2 . Results: We analyzed 203 chemotherapy cycles in 50 patients (47.8 ± 16.1 years; 56% women), including 13 (26%) with acute lymphoblastic and 12 (24%) with myeloblastic leukemia. Pharmacokinetics-related polymorphisms incorporated into the model were CYP3A4 rs2242480C>T and OAT4 rs11231809T>A. Immune/inflammatory response-related polymorphisms were TLR2 rs4696480T>A and IL-6 rs1800796C>G. Clinical/demographic variables incorporated into the model were chemotherapy type and cycle, diagnosis, days in neutropenia, age, and sex. The Pseudo-R 2 was 0.56, the p -value of the Hosmer-Lemeshow test was 0.98, showing good goodness-of-fit, and the area under the ROC curve was 0.93, showing good diagnostic accuracy. Conclusions: Genetics can help to predict infections in patients undergoing chemotherapy. This algorithm should be validated and could be used to save lives, decrease economic costs, and optimize limited health resources. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 Martinez, Alveal, Soto, Bustamante, Ávila, Bangdiwala, Flores, Monterrosa, Morales, Varela, Fohner and Quiñones.)
Databáze:	MEDLINE
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