Construction, Training and Clinical Validation of An Interpretation System for Genotypic HIV-1 Drug Resistance Based on Fuzzy Rules Revised by Virological Outcomes
- 1 May 2004
- journal article
- research article
- Published by SAGE Publications in Antiviral Therapy
- Vol. 9 (4) , 583-593
- https://doi.org/10.1177/135965350400900406
Abstract
Objectives: To evaluate whether fuzzy operators can be usefully applied to the interpretation of genotypic HIV-1 drug resistance by experts, and to improve the prediction of salvage therapy outcome by adapting interpretation rules of genotypic resistance on the basis of their association with virological response data. Methods: We used a clinical dataset of 231 patients failing highly active antiretroviral therapy (HAART) and starting salvage therapy with baseline resistance genotyping and virological outcomes after 3 and 6 months. A set of rules predicting genotypic resistance was initially derived from an expert (ADL). Rules were implemented using a fuzzy logic approach and the virological outcomes dataset used for the training phase. The resulting algorithm was validated using a separate set of 184 selected patients by correlating the resulting predicted activity with observed virological response at 3 months. For comparison, the expert systems from the drug resistance group of the Agence Nationale de Recherches sur le SIDA (ANRS-AC11) and the algorithm from the Stanford's HIV drug resistance database (Stanford HIVdb) were evaluated on the same set. Results: The starting algorithm had a correlation with virological outcomes of R2=0.06 ( P=0.0001). After the training phase the correlation with virological outcomes increased to R2=0.19 ( P10 copies/ml; 95% CI -0.39, -0.15). Conclusion: Using fuzzy operators in a virological outcomes training database to implement a rules-based algorithm for genotypic resistance interpretation, significant improvements of outcomes prediction were obtained. The resulting algorithm showed an independent predictive capability of virological outcomes over that of two rules-based interpretation algorithms made by experts. Although the system was trained and validated on a limited number of cases, the approach deserves further evaluation. Presented in part at the XI International Drug Resistance Workshop, Seville, Spain 2002 [Abstract 85]. Antiviral Therapy 2002; 7:S71.Keywords
This publication has 27 references indexed in Scilit:
- Comparison between Rules‐Based Human Immunodeficiency Virus Type 1 Genotype Interpretations and Real or Virtual Phenotype: Concordance Analysis and Correlation with Clinical Outcome in Heavily Treated PatientsThe Journal of Infectious Diseases, 2003
- Antiretroviral Drug Resistance Testing in Adults Infected with Human Immunodeficiency Virus Type 1: 2003 Recommendations of an International AIDS Society–USA PanelClinical Infectious Diseases, 2003
- Variable Prediction of Antiretroviral Treatment Outcome by Different Systems for Interpreting Genotypic Human Immunodeficiency Virus Type 1 Drug ResistanceThe Journal of Infectious Diseases, 2003
- Antiretroviral-Drug Resistance among Patients Recently Infected with HIVNew England Journal of Medicine, 2002
- The Consistency of Adherence to Antiretroviral Therapy Predicts Biologic Outcomes for Human Immunodeficiency Virus–Infected Persons in Clinical TrialsClinical Infectious Diseases, 2002
- Clinical and laboratory guidelines for the use of HIV-1 drug resistance testing as part of treatment management: recommendations for the European settingAIDS, 2001
- Patient-Reported Nonadherence to HAART Is Related to Protease Inhibitor LevelsJAIDS Journal of Acquired Immune Deficiency Syndromes, 2000
- A randomized study of antiretroviral management based on plasma genotypic antiretroviral resistance testing in patients failing therapyAIDS, 2000
- Declining Morbidity and Mortality among Patients with Advanced Human Immunodeficiency Virus InfectionNew England Journal of Medicine, 1998
- The concept of a linguistic variable and its application to approximate reasoning—IInformation Sciences, 1975