title: Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients.
abstract: Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression tree (CART) analyses to identify clinical factors, including amikacin concentration thresholds that predicted audiometry-confirmed ototoxicity among 28 multidrug-resistant pulmonary tuberculosis patients in Botswana. Amikacin concentrations were measured for all patients. The quantitative relationship between predictive factors and the probability of ototoxicity were then identified using probit analyses. The primary predictors of ototoxicity on CART analyses were cumulative days of therapy, followed by cumulative area under the concentration-time curve (AUC), which improved on the primary predictor by 87%. The area under the receiver operating curve was 0.97 on the test set. Peak and trough were not predictors in any tree. When algorithms were forced to pick peak and trough as primary predictors, the area under the receiver operating curve fell to 0.46. Probit analysis revealed that the probability of ototoxicity increased sharply starting after 6 months of therapy to near maximum at 9 months. A 10% probability of ototoxicity occurred with a threshold cumulative AUC of 87,232 days · mg · h/liter, while that of 20% occurred at 120,000 days · mg · h/liter. Thus, cumulative amikacin AUC and duration of therapy, and not peak and trough concentrations, should be used as the primary decision-making parameters to minimize the likelihood of ototoxicity in multidrug-resistant tuberculosis.
authors.affiliation: Division of Infectious Diseases, University of Pennsylvania, Philadelphia, Pennsylvania, USA Botswana-University of Pennsylvania Partnership, Gaborone, Botswana.
authors.forename: Chawangwa
authors.initials: C
authors.lastname: Modongo
authors.affiliation: Office of Global Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Jotam G
authors.initials: JG
authors.lastname: Pasipanodya
authors.affiliation: Division of Infectious Diseases, University of Pennsylvania, Philadelphia, Pennsylvania, USA Botswana-University of Pennsylvania Partnership, Gaborone, Botswana Department of Medicine, University of Botswana, Gaborone, Botswana.
authors.forename: Nicola M
authors.initials: NM
authors.lastname: Zetola
authors.affiliation: Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.
authors.forename: Scott M
authors.initials: SM
authors.lastname: Williams
authors.affiliation: Centro di Ricerca, Ospedale San Pietro Fatebenefratelli, Rome, Italy.
authors.forename: Giorgio
authors.initials: G
authors.lastname: Sirugo
authors.affiliation: Office of Global Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA Department of Medicine, University of Cape Town, Observatory, South Africa Tawanda.Gumbo@BaylorHealth.edu.
authors.forename: Tawanda
authors.initials: T
authors.lastname: Gumbo
mesh_terms: D000328:Adult; D000583:Amikacin / Q000009:adverse effects / Q000493:pharmacokinetics*; D000995:Antitubercular Agents / Q000009:adverse effects / Q000493:pharmacokinetics*; D019540:Area Under Curve; D001299:Audiometry; D000066491:Clinical Decision-Making; D005260:Female; D006319:Hearing Loss, Sensorineural / Q000139:chemically induced / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D011336:Probability; D012372:ROC Curve; D018088:Tuberculosis, Multidrug-Resistant / Q000188:drug therapy* / Q000382:microbiology
chemical_list: D000995:Antitubercular Agents; D000583:Amikacin