W Jeffrey Fessel

Stanford University, Palo Alto, CA, United States

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Publications (38)156.13 Total impact

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    ABSTRACT: The introduction of two new non-nucleoside reverse transcriptase inhibitors (NNRTIs) in the past 5 years and the identification of novel NNRTI-associated mutations have made it necessary to reassess the extent of phenotypic NNRTI cross-resistance. We analysed a dataset containing 1975, 1967, 519 and 187 genotype-phenotype correlations for nevirapine, efavirenz, etravirine and rilpivirine, respectively. We used linear regression to estimate the effects of RT mutations on susceptibility to each of these NNRTIs. Sixteen mutations at 10 positions were significantly associated with the greatest contribution to reduced phenotypic susceptibility (≥10-fold) to one or more NNRTIs, including: 14 mutations at six positions for nevirapine (K101P, K103N/S, V106A/M, Y181C/I/V, Y188C/L and G190A/E/Q/S); 10 mutations at six positions for efavirenz (L100I, K101P, K103N, V106M, Y188C/L and G190A/E/Q/S); 5 mutations at four positions for etravirine (K101P, Y181I/V, G190E and F227C); and 6 mutations at five positions for rilpivirine (L100I, K101P, Y181I/V, G190E and F227C). G190E, a mutation that causes high-level nevirapine and efavirenz resistance, also markedly reduced susceptibility to etravirine and rilpivirine. K101H, E138G, V179F and M230L mutations, associated with reduced susceptibility to etravirine and rilpivirine, were also associated with reduced susceptibility to nevirapine and/or efavirenz. The identification of novel cross-resistance patterns among approved NNRTIs illustrates the need for a systematic approach for testing novel NNRTIs against clinical virus isolates with major NNRTI-resistance mutations and for testing older NNRTIs against virus isolates with mutations identified during the evaluation of a novel NNRTI.
    Journal of Antimicrobial Chemotherapy 08/2013; · 5.34 Impact Factor
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    ABSTRACT: The many genetic manifestations of HIV-1 protease inhibitor (PI) resistance present challenges to research into the mechanisms of PI-resistance and the assessment of new PIs. To address these challenges, we created a panel of recombinant multi-PI resistant infectious molecular clones designed to represent the spectrum of clinically relevant multi-PI resistant viruses. To assess the representativeness of this panel, we examined the sequences of the panel's viruses in the context of a correlation network of PI-resistance amino acid substitutions in sequences from more than 10,000 patients. The panel of recombinant infectious molecular clones comprised 29 of 41 study-defined PI-resistance amino acid substitutions and 23 of the 27 tightest amino acid substitution clusters. Based on their phenotypic properties, the clones were classified into four groups with increasing cross-resistance to the PIs most commonly used for salvage therapy: lopinavir (LPV), tipranavir (TPV), and darunavir (DRV). The panel of recombinant infectious molecular clones has been made available without restriction through the NIH AIDS Research and Reference Reagent Program. The public availability of the panel makes it possible to compare the inhibitory activity of different PIs with one another. The diversity of the panel and the high-level PI resistance of its clones suggest that investigational PIs active against the clones in this panel will retain antiviral activity against most, if not all clinically relevant PI-resistant viruses.
    Antimicrobial Agents and Chemotherapy 06/2013; · 4.57 Impact Factor
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    ABSTRACT: OBJECTIVES: To determine whether pan-protease inhibitor (PI)-resistant virus populations are composed predominantly of viruses with resistance to all PIs or of diverse virus populations with resistance to different subsets of PIs. METHODS: We performed deep sequencing of plasma virus samples from nine patients with high-level genotypic and/or phenotypic resistance to all licensed PIs. The nine virus samples had a median of 12 PI resistance mutations by direct PCR Sanger sequencing. RESULTS: For each of the nine virus samples, deep sequencing showed that each of the individual viruses within a sample contained nearly all of the mutations detected by Sanger sequencing. Indeed, a median of 94.9% of deep sequence reads had each of the PI resistance mutations present as a single chromatographic peak in the Sanger sequence. A median of 5.0% of reads had all but one of the Sanger mutations that were not part of an electrophoretic mixture. CONCLUSIONS: The collinearity of PI resistance mutations in the nine virus samples demonstrated that pan-PI-resistant viruses are able to replicate in vivo despite their highly mutated protease enzymes. We hypothesize that the marked collinearity of PI resistance mutations in pan-PI-resistant virus populations results from the unique requirements for multi-PI resistance and the extensive cross-resistance conferred by many of the accessory PI resistance mutations.
    Journal of Antimicrobial Chemotherapy 10/2012; · 5.34 Impact Factor
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    ABSTRACT: We created a panel of 10 representative multi-nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistant recombinant infectious molecular HIV-1 clones to assist researchers studying NNRTI resistance or developing novel NNRTIs. The cloned viruses contain most of the major NNRTI resistance mutations and most of the significantly associated mutation pairs that we identified in two network analyses. Each virus in the panel has intermediate- or high-level resistance to all or three of the four most commonly used NNRTIs.
    Antimicrobial Agents and Chemotherapy 06/2012; 56(8):4522-4. · 4.57 Impact Factor
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    ABSTRACT: To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often differ in their inclusion and virological response criteria making direct comparisons of study results problematic. Moreover, the absence of a standard method for representing the data comprising a TCE makes it difficult to apply uniform criteria in the analysis of published studies of TCEs. To facilitate data sharing for TCE analyses, we developed an XML (Extensible Markup Language) Schema that represents the temporal relationship between plasma HIV-1 RNA levels, CD4 counts and genotypic drug resistance data surrounding an ARV treatment change. To demonstrate the adaptability of the TCE XML Schema to different clinical environments, we collaborate with four clinics to create a public repository of about 1,500 TCEs. Despite the nascent state of this TCE XML Repository, we were able to perform an analysis that generated a novel hypothesis pertaining to the optimal use of second-line therapies in resource-limited settings. We also developed an online program (TCE Finder) for searching the TCE XML Repository and another program (TCE Viewer) for generating a graphical depiction of a TCE from a TCE XML Schema document. The TCE Suite of applications - the XML Schema, Viewer, Finder, and Repository - addresses several major needs in the analysis of the predictors of virological response to ARV therapy. The TCE XML Schema and Viewer facilitate sharing data comprising a TCE. The TCE Repository, the only publicly available collection of TCEs, and the TCE Finder can be used for testing the predictive value of genotypic resistance interpretation systems and potentially for generating and testing novel hypotheses pertaining to the optimal use of salvage ARV therapy.
    AIDS Research and Therapy 05/2012; 9(1):13. · 2.54 Impact Factor
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    ABSTRACT: Determining the phenotypic impacts of reverse transcriptase (RT) mutations on individual nucleoside RT inhibitors (NRTIs) has remained a statistical challenge because clinical NRTI-resistant HIV-1 isolates usually contain multiple mutations, often in complex patterns, complicating the task of determining the relative contribution of each mutation to HIV drug resistance. Furthermore, the NRTIs have highly variable dynamic susceptibility ranges, making it difficult to determine the relative effect of an RT mutation on susceptibility to different NRTIs. In this study, we analyzed 1,273 genotyped HIV-1 isolates for which phenotypic results were obtained using the PhenoSense assay (Monogram, South San Francisco, CA). We used a parsimonious feature selection algorithm, LASSO, to assess the possible contributions of 177 mutations that occurred in 10 or more isolates in our data set. We then used least-squares regression to quantify the impact of each LASSO-selected mutation on each NRTI. Our study provides a comprehensive view of the most common NRTI resistance mutations. Because our results were standardized, the study provides the first analysis that quantifies the relative phenotypic effects of NRTI resistance mutations on each of the NRTIs. In addition, the study contains new findings on the relative impacts of thymidine analog mutations (TAMs) on susceptibility to abacavir and tenofovir; the impacts of several known but incompletely characterized mutations, including E40F, V75T, Y115F, and K219R; and a tentative role in reduced NRTI susceptibility for K64H, a novel NRTI resistance mutation.
    Antimicrobial Agents and Chemotherapy 02/2012; 56(5):2305-13. · 4.57 Impact Factor
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    ABSTRACT: The availability of 24 antiretroviral (ARV) drugs within six distinct drug classes has transformed HIV-1 infection (AIDS) into a treatable chronic disease. However, the ability of HIV-1 to develop resistance to multiple classes continues to present challenges to the treatment of many ARV treatment-experienced patients. In this case report, we describe the response to ibalizumab, an investigational CD4-binding monoclonal antibody (mAb), in a patient with advanced immunodeficiency and high-level five-class antiretroviral resistance. After starting an ibalizumab-based salvage regimen, the patient had an approximately 4.0 log(10) reduction in viral load. An inadvertently missed infusion at week 32 led to the rapid loss of virologic response and decreased susceptibility to the remainder of the patient's salvage therapy regimen. Following the reinstitution of ibalizumab, phenotypic and genotypic resistance to ibalizumab was detected. Nonetheless, plasma HIV-1 RNA levels stabilized at ∼2.0 log(10) copies/ml below pre-ibalizumab levels. Continued ARV drug development may yield additional clinical and public health benefits. This report illustrates the promise of mAbs for HIV-1 therapy in highly treatment-experienced patients. Therapeutic mAbs may also have a role in pre-exposure prophylaxis in high-risk uninfected populations and may facilitate directly observed therapy (DOT) if two or more synergistic long acting agents become available.
    Antiviral research 12/2011; 92(3):484-7. · 3.61 Impact Factor
  • W Jeffrey Fessel, Quyen Chau, Davis Leong
    AIDS (London, England) 11/2011; 25(18):2305-6. · 4.91 Impact Factor
  • W Jeffrey Fessel, Quyen Chau, Davis Leong
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    ABSTRACT: We questioned whether heightened impairment of regenerative capacity of osteoblasts might account for the excess of osteonecrosis and osteoporosis seen in HIV-infected patients. Were that the case, patients with osteonecrosis would have more osteoporosis than the patients without osteonecrosis. Eleven thousand, five hundred and six patients with HIV infection were studied for the presence of osteonecrosis and osteoporosis and for confounding factors. Depending upon whether dual-energy X-ray absorptiometry (DEXA) was before or after the diagnosis of osteonecrosis, osteoporosis was between 6.3 and 18 times more frequent in those with than in those without osteonecrosis. Those who received DEXA were similar to those who did not in median CD4 level at the time of DEXA or at a comparable time after their first recorded CD4 cell count in our system; in nadir CD4 level; and in use and amount of corticosteroids. Those with osteonecrosis and osteoporosis did not use more corticosteroids than those with osteoporosis without osteonecrosis. Alcohol abuse had not been diagnosed more often before the occurrence of osteonecrosis than in those without osteonecrosis. Tenofovir was not more used by those with than by those without osteoporosis. Osteonecrosis and osteoporosis in HIV-infected patients were concurrent more often than expected.
    AIDS (London, England) 08/2011; 25(15):1877-80. · 4.91 Impact Factor
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    ABSTRACT: The effects of many protease inhibitor (PI)-selected mutations on the susceptibility to individual PIs are unknown. We analyzed in vitro susceptibility test results on 2,725 HIV-1 protease isolates. More than 2,400 isolates had been tested for susceptibility to fosamprenavir, indinavir, nelfinavir, and saquinavir; 2,130 isolates had been tested for susceptibility to lopinavir; 1,644 isolates had been tested for susceptibility to atazanavir; 1,265 isolates had been tested for susceptibility to tipranavir; and 642 isolates had been tested for susceptibility to darunavir. We applied least-angle regression (LARS) to the 200 most common mutations in the data set and identified a set of 46 mutations associated with decreased PI susceptibility of which 40 were not polymorphic in the eight most common HIV-1 group M subtypes. We then used least-squares regression to ascertain the relative contribution of each of these 46 mutations. The median number of mutations associated with decreased susceptibility to each PI was 28 (range, 19 to 32), and the median number of mutations associated with increased susceptibility to each PI was 2.5 (range, 1 to 8). Of the mutations with the greatest effect on PI susceptibility, I84AV was associated with decreased susceptibility to eight PIs; V32I, G48V, I54ALMSTV, V82F, and L90M were associated with decreased susceptibility to six to seven PIs; I47A, G48M, I50V, L76V, V82ST, and N88S were associated with decreased susceptibility to four to five PIs; and D30N, I50L, and V82AL were associated with decreased susceptibility to fewer than four PIs. This study underscores the greater impact of nonpolymorphic mutations compared with polymorphic mutations on decreased PI susceptibility and provides a comprehensive quantitative assessment of the effects of individual mutations on susceptibility to the eight clinically available PIs.
    Antimicrobial Agents and Chemotherapy 10/2010; 54(10):4253-61. · 4.57 Impact Factor
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    ABSTRACT: Viruses were sequenced from 75 antiretroviral therapy (ARV)-naïve and from 75 ARV-treated patients who subsequently received a raltegravir-containing regimen. No major integrase inhibitor (INI)-resistance mutations were present in the 150 integrase (IN) sequences. Four ARV-naïve (5.3%) and two ARV-treated patients (2.7%) had one of the following minor INI-resistance mutations: L74M, E157Q, G163R, and R263K but there was no association between baseline raltegravir genotype and subsequent response to raltegravir treatment. We also combined our sequences with 4170 previously published group M IN sequences from INI-naïve patients to assess IN sequence variability and compared our findings with those of a study we performed in 2008 using data from 1563 patients. The number of polymorphic IN positions increased from 40% to 41% between the two studies. However, none of the major INI-resistance mutations was found to be polymorphic in either study and there were no significant changes in the prevalence of any of the minor INI-resistance mutations.
    AIDS research and human retroviruses 10/2010; 26(12):1323-6. · 2.18 Impact Factor
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    ABSTRACT: The HIV-1 nucleoside RT inhibitor (NRTI)-resistance mutation, K65R confers intermediate to high-level resistance to the NRTIs abacavir, didanosine, emtricitabine, lamivudine, and tenofovir; and low-level resistance to stavudine. Several lines of evidence suggest that K65R is more common in HIV-1 subtype C than subtype B viruses. We performed ultra-deep pyrosequencing (UDPS) and clonal dideoxynucleotide sequencing of plasma virus samples to assess the prevalence of minority K65R variants in subtype B and C viruses from untreated individuals. Although UDPS of plasma samples from 18 subtype C and 27 subtype B viruses showed that a higher proportion of subtype C viruses contain K65R (1.04% vs. 0.25%; p<0.001), limiting dilution clonal sequencing failed to corroborate its presence in two of the samples in which K65R was present in >1.5% of UDPS reads. We therefore performed UDPS on clones and site-directed mutants containing subtype B- and C-specific patterns of silent mutations in the conserved KKK motif encompassing RT codons 64 to 66 and found that subtype-specific nucleotide differences were responsible for increased PCR-induced K65R mutation in subtype C viruses. This study shows that the RT KKK nucleotide template in subtype C viruses can lead to the spurious detection of K65R by highly sensitive PCR-dependent sequencing techniques. However, the study is also consistent with the subtype C nucleotide template being inherently responsible for increased polymerization-induced K65R mutations in vivo.
    PLoS ONE 01/2010; 5(6):e10992. · 3.73 Impact Factor
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    ABSTRACT: We created an HIV-1 cloning vector, pNL4.3DeltaIN, to generate recombinant infectious molecular clones for analysis of patient-derived HIV-1 integrase coding regions. Using this vector, we constructed a panel of clinically derived viruses with the canonical patterns of raltegravir resistance mutations and submitted the panel to the NIH AIDS Research and Reference Reagent Program. Investigational integrase inhibitors with activity against these clones are likely to retain activity against the most clinically relevant raltegravir-resistant variants.
    Antimicrobial Agents and Chemotherapy 11/2009; 54(2):934-6. · 4.57 Impact Factor
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    ABSTRACT: Objectives: K103N, the most common nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistant mutation in patients with transmitted resistance and in patients receiving a failing NNRTI-containing regimen, is fully susceptible to the new NNRTI, etravirine. Therefore, we sought to determine how often NNRTI-resistant mutations other than K103N occur as minority variants in plasma samples for which standard genotypic resistance testing detects K103N alone. Methods: We performed ultradeep pyrosequencing (UDPS; 454 Life Sciences a Roche Company, Branford, CT) of plasma virus samples from 13 treatment-naive and 20 NNRTI-experienced patients in whom standard genotypic resistance testing revealed K103N but no other major NNRTI-resistance mutations. Results: Samples from 0 of 13 treatment-naive patients vs. 7 of 20 patients failing an NNRTI-containing regimen had minority variants with major etravirine-associated NNRTI-resistant mutations (P = 0.03, Fisher exact test): Y181C (7.0%), Y181C (3.6%) + G190A (3.2%), L100I (14%), L100I (32%) + 190A (5.4%), K101E (3.8%) + G190A (4.9%), K101E (4.0%) + G190S (4.8%), and G190S (3.1%). Conclusions: In treatment-naive patients, UDPS did not detect additional major NNRTI-resistant mutations suggesting that etravirine may be effective in patients with transmitted K103N. In NNRTI-experienced patients, UDPS often detected additional major NNRTI-resistant mutations suggesting that etravirine may not be fully active in patients with acquired K103N.
    JAIDS Journal of Acquired Immune Deficiency Syndromes 10/2009; 52(3):309-315. · 4.65 Impact Factor
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    ABSTRACT: The spectrum of human immunodeficiency virus type 1 (HIV-1) protease and reverse transcriptase (RT) mutations selected by antiretroviral (ARV) drugs requires ongoing reassessment as ARV treatment patterns evolve and increasing numbers of protease and RT sequences of different viral subtypes are published. Accordingly, we compared the prevalences of protease and RT mutations in HIV-1 group M sequences from individuals with and without a history of previous treatment with protease inhibitors (PIs) or RT inhibitors (RTIs). Mutations in protease sequences from 26,888 individuals and in RT sequences from 25,695 individuals were classified according to whether they were nonpolymorphic in untreated individuals and whether their prevalence increased fivefold with ARV therapy. This analysis showed that 88 PI-selected and 122 RTI-selected nonpolymorphic mutations had a prevalence that was fivefold higher in individuals receiving ARVs than in ARV-naïve individuals. This was an increase of 47% and 77%, respectively, compared with the 60 PI- and 69 RTI-selected mutations identified in a similar analysis that we published in 2005 using subtype B sequences obtained from one-fourth as many individuals. In conclusion, many nonpolymorphic mutations in protease and RT are under ARV selection pressure. The spectrum of treatment-selected mutations is changing as data for more individuals are collected, treatment exposures change, and the number of available sequences from non-subtype B viruses increases.
    Antimicrobial Agents and Chemotherapy 09/2009; 53(11):4869-78. · 4.57 Impact Factor
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    ABSTRACT: Interpreting human immunodeficiency virus type 1 (HIV-1) genotypic drug-resistance test results is challenging for clinicians treating HIV-1-infected patients. Multiple drug-resistance interpretation algorithms have been developed, but their predictive value has rarely been evaluated using contemporary clinical data sets. We examined the predictive value of 4 algorithms at predicting virologic response (VR) during 734 treatment-change episodes (TCEs). VR was defined as attaining plasma HIV-1 RNA levels below the limit of quantification. Drug-specific genotypic susceptibility scores (GSSs) were calculated by applying each algorithm to the baseline genotype. Weighted GSSs were calculated by multiplying drug-specific GSSs by antiretroviral (ARV) potency factors. Regimen-specific GSSs (rGSSs) were calculated by adding unweighted or weighted drug-specific GSSs for each salvage therapy ARV. The predictive value of rGSSs were estimated by use of multivariate logistic regression. Of 734 TCEs, 475 (65%) were associated with VR. The rGSSs for the 4 algorithms were the variables most strongly predictive of VR. The adjusted rGSS odds ratios ranged from 1.6 to 2.2 (P < .001). Using 10-fold cross-validation, the averaged area under the receiver operating characteristic curve for all algorithms increased from 0.76 with unweighted rGSSs to 0.80 with weighted rGSSs. Unweighted and weighted rGSSs of 4 genotypic resistance algorithms were the strongest independent predictors of VR. Optimizing ARV weighting may further improve VR predictions.
    The Journal of Infectious Diseases 07/2009; 200(3):453-63. · 5.85 Impact Factor
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    ABSTRACT: Expert-based genotypic interpretation systems are standard methods for guiding treatment selection for patients infected with human immunodeficiency virus type 1. We previously introduced the software pipeline geno2pheno-THEO (g2p-THEO), which on the basis of viral sequence predicts the response to treatment with a combination of antiretroviral compounds by applying methods from statistical learning and the estimated potential of the virus to escape from drug pressure. We retrospectively validated the statistical model used by g2p-THEO in approximately 7600 independent treatment-sequence pairs extracted from the EuResist integrated database, ranging from 1990 to 2007. Results were compared with the 3 most widely used expert-based interpretation systems: Stanford HIVdb, ANRS, and Rega. The difference in receiver operating characteristic curves between g2p-THEO and expert-based approaches was significant (P < .001; paired Wilcoxon test). Indeed, at 80% specificity, g2p-THEO found 16.2%-19.8% more successful regimens than did the expert-based approaches. The increased performance of g2p-THEO was confirmed in a 2001-2007 data set from which most obsolete therapies had been removed. Finding drug combinations that increase the chances of therapeutic success is the main reason for using decision support systems. The present analysis of a large data set derived from clinical practice demonstrates that g2p-THEO solves this task significantly better than state-of-the-art expert-based systems. The tool is available at http://www.geno2pheno.org.
    The Journal of Infectious Diseases 03/2009; 199(7):999-1006. · 5.85 Impact Factor
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    ABSTRACT: Q145M, a mutation in a conserved human immunodeficiency virus type 1 reverse transcriptase (RT) region, was reported to decrease susceptibility to multiple RT inhibitors. We report that Q145M and other Q145 mutations do not emerge with RT inhibitors nor decrease RT inhibitor susceptibility. Q145M should not, therefore, be considered an RT inhibitor resistance mutation.
    Antimicrobial Agents and Chemotherapy 03/2009; 53(5):2196-8. · 4.57 Impact Factor
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    ABSTRACT: Inferring response to antiretroviral therapy from the viral genotype alone is challenging. The utility of an intermediate step of predicting in vitro drug susceptibility is currently controversial. Here, we provide a retrospective comparison of approaches using either genotype or predicted phenotypes alone, or in combination. Treatment change episodes were extracted from two large databases from the USA (Stanford-California) and Europe (EuResistDB) comprising data from 6,706 and 13,811 patients, respectively. Response to antiretroviral treatment was dichotomized according to two definitions. Using the viral sequence and the treatment regimen as input, three expert algorithms (ANRS, Rega and HIVdb) were used to generate genotype-based encodings and VircoTYPE() 4.0 (Virco BVBA, Mechelen, Belgium) was used to generate a predicted -phenotype-based encoding. Single drug classifications were combined into a treatment score via simple summation and statistical learning using random forests. Classification performance was studied on Stanford-California data using cross-validation and, in addition, on the independent EuResistDB data. In all experiments, predicted phenotype was among the most sensitive approaches. Combining single drug classifications by statistical learning was significantly superior to unweighted summation (P<2.2x10(-16)). Classification performance could be increased further by combining predicted phenotypes and expert encodings but not by combinations of expert encodings alone. These results were confirmed on an independent test set comprising data solely from EuResistDB. This study demonstrates consistent performance advantages in utilizing predicted phenotype in most scenarios over methods based on genotype alone in inferring virological response. Moreover, all approaches under study benefit significantly from statistical learning for merging single drug classifications into treatment scores.
    Antiviral therapy 01/2009; 14(2):273-83. · 3.07 Impact Factor
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    ABSTRACT: Researchers in clinical science and bioinformatics frequently aim to learn which of a set of candidate biomarkers is important in determining a given outcome, and to rank the contributions of the candidates accordingly. This article introduces a new approach to research questions of this type, based on targeted maximum-likelihood estimation of variable importance measures.The methodology is illustrated using an example drawn from the treatment of HIV infection. Specifically, given a list of candidate mutations in the protease enzyme of HIV, we aim to discover mutations that reduce clinical virologic response to antiretroviral regimens containing the protease inhibitor lopinavir. In the context of this data example, the article reviews the motivation for covariate adjustment in the biomarker discovery process. A standard maximum-likelihood approach to this adjustment is compared with the targeted approach introduced here. Implementation of targeted maximum-likelihood estimation in the context of biomarker discovery is discussed, and the advantages of this approach are highlighted. Results of applying targeted maximum-likelihood estimation to identify lopinavir resistance mutations are presented and compared with results based on unadjusted mutation-outcome associations as well as results of a standard maximum-likelihood approach to adjustment.The subset of mutations identified by targeted maximum likelihood as significant contributors to lopinavir resistance is found to be in better agreement with the current understanding of HIV antiretroviral resistance than the corresponding subsets identified by the other two approaches. This finding suggests that targeted estimation of variable importance represents a promising approach to biomarker discovery.
    Statistics in Medicine 10/2008; 28(1):152-72. · 2.04 Impact Factor

Publication Stats

830 Citations
156.13 Total Impact Points

Institutions

  • 2002–2013
    • Stanford University
      • • Division of Infectious Diseases
      • • Department of Medicine
      • • Stanford Genome Technology Center
      • • Department of Biochemistry
      Palo Alto, CA, United States
  • 2007–2012
    • Kaiser Permanente
      • Section for Infectious Diseases
      Oakland, California, United States
    • University of California, Berkeley
      • Division of Biostatistics
      Berkeley, CA, United States
  • 2011
    • Society for Clinical Trials
      San Francisco, California, United States
  • 2010
    • St. Vincent Medical Center
      • Saint Vincent Hospital
      Bridgeport, Connecticut, United States
    • Stanford Medicine
      • Department of Medicine
      Stanford, CA, United States
  • 2009
    • Spine Group Beverly Hills
      Beverly Hills, California, United States
    • University of Cologne
      • Institute of Virology
      Köln, North Rhine-Westphalia, Germany
  • 2007–2009
    • Max Planck Institute for Informatics
      • Department 3: Computational Biology and Applied Algorithmics
      Saarbrücken, Saarland, Germany