title: Scoring methods for building genotypic scores: an application to didanosine resistance in a large derivation set.
abstract: BACKGROUND
  Several attempts have been made to determine HIV-1 resistance from genotype resistance testing. We compare scoring methods for building weighted genotyping scores and commonly used systems to determine whether the virus of a HIV-infected patient is resistant.
  
  
  RESULTS
  Three statistical methods (linear discriminant analysis, support vector machine and logistic regression) are used to determine the weight of mutations involved in HIV resistance. We compared these weighted scores with known interpretation systems (ANRS, REGA and Stanford HIV-db) to classify patients as resistant or not. Our methodology is illustrated on the Forum for Collaborative HIV Research didanosine database (N = 1453). The database was divided into four samples according to the country of enrolment (France, USA/Canada, Italy and Spain/UK/Switzerland). The total sample and the four country-based samples allow external validation (one sample is used to estimate a score and the other samples are used to validate it). We used the observed precision to compare the performance of newly derived scores with other interpretation systems. Our results show that newly derived scores performed better than or similar to existing interpretation systems, even with external validation sets. No difference was found between the three methods investigated. Our analysis identified four new mutations associated with didanosine resistance: D123S, Q207K, H208Y and K223Q.
  
  
  CONCLUSIONS
  We explored the potential of three statistical methods to construct weighted scores for didanosine resistance. Our proposed scores performed at least as well as already existing interpretation systems and previously unrecognized didanosine-resistance associated mutations were identified. This approach could be used for building scores of genotypic resistance to other antiretroviral drugs.
authors.affiliation: INSERM U943, Paris, France. ahoussaini@ccde.chups.jussieu.fr
authors.forename: Allal
authors.initials: A
authors.lastname: Houssaini
authors.forename: Lambert
authors.initials: L
authors.lastname: Assoumou
authors.forename: Veronica
authors.initials: V
authors.lastname: Miller
authors.forename: Vincent
authors.initials: V
authors.lastname: Calvez
authors.forename: Anne-Geneviève
authors.initials: AG
authors.lastname: Marcelin
authors.forename: Philippe
authors.initials: P
authors.lastname: Flandre
mesh_terms: D019380:Anti-HIV Agents / Q000494:pharmacology / Q000627:therapeutic use; D002170:Canada; D016208:Databases, Factual; D016049:Didanosine / Q000494:pharmacology / Q000627:therapeutic use; D024882:Drug Resistance, Viral / Q000235:genetics*; D005602:France; D005838:Genotype; D015658:HIV Infections / Q000175:diagnosis / Q000188:drug therapy; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D007558:Italy; D015233:Models, Statistical; D009154:Mutation; D059645:Mutation Rate; D015203:Reproducibility of Results; D013030:Spain; D013557:Switzerland; D006113:United Kingdom; D014481:United States
chemical_list: D019380:Anti-HIV Agents; D016049:Didanosine
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