Algorithm and clinical validation M. Obermeier 4/2007
Interpretation-systems � Free available: � Rule based: • ANRS • HIVdb • REGA � Truly bioinformatics based: • geno2pheno [resistance] • geno2pheno [THEO] M. Obermeier 4/2007
Interpretations-Systeme � commercial: � Rule based : • TrueGene HIV-1 • ViroSeq � Truly bioinformatics based: • Virtual phenotype M. Obermeier 4/2007
Yet another algorithm? � German initiative for standardization � predict clinical success not phenotype � Integration of combination therapies (resensitising effects) � Rule based systems can be faster adapted to new drugs and easier updated than bioinformatic approaches (need for data!) M. Obermeier 4/2007
HIV-GRADE base � Experts opinion � literature � genotype-phenotype correlations � genotype-virtual phenotype correlations (geno2pheno) � different databases consisting of treatment, genotype and clinical outcome � Scientific board meeting twice a year � actual algorithm version 04-2007 M. Obermeier 4/2007
Special characteristics of HIV-GRADE � Explicit results for resensitising effects _SP-nomenclature (selective pressure) � Results for boosted and non-boosted PIs � 5 level classification: � Hypersusceptible � Susceptible � Limited susceptibility � Intermediate resistance � Resistance M. Obermeier 4/2007
Basis of the HIV-GRADE internet-tool � HIV-Alg module from Stanford-HIVdb � PERL-source-code is freely available � Software is in development since 1999 � Algorithm Specification Interface (ASI) M. Obermeier 4/2007
Workflow sequences mutation-lists identify genes alignment on Consensus send sequences B Sequence to geno2pheno extraction of mutations rule-based analysis geno2pheno report detailled output batch output M. Obermeier 4/2007
Number of rules ANRS 89 REGA 82 HIVDB 18 scoring-rules (+60 comments) GRADE 303 M. Obermeier 4/2007
HIV-GRADE TDF Resistance Intermediate Limited susceptibility � 65R � 2 out of (41L, � 41L � 69 ins � 215F/Y 210W, 215 F/Y) � (41L or 210W) + 2 � 67N + 70R+ � 2 out of (67N, out of (67N, 70R, 219Q/E 70R, 219Q/E) � 70E � 151M 219Q/E) � 41L + 210W + 215 F/Y � 4 out of (41L, 67N, 70R, 210W, 215 F/Y, 219Q/E) M. Obermeier 4/2007
HIV-GRADE DRV Resistance Intermediate Limited susceptibility � 5 out of (11I, � 4 out of (11I, � 3 out of (11I, 32I, 33F, 47V, 32I, 33F, 47V, 32I, 33F, 47V, 50V(x2), 54M 50V(x2), 54M 50V(x2), 54M (x2), 54L, 73S, (x2), 54L, 73S, (x2), 54L, 73S, 76V (x2), 84V, 76V (x2), 84V, 76V (x2), 84V, 89V) 89V) 89V) M. Obermeier 4/2007
Algorithm Specification Interface (ASI) � Rule-based algorithms can be described using xml-syntax � Xml-Files available for Stanford- HIVdb, ANRS and REGA HIV-GRADE can be described in a compatible format. M. Obermeier 4/2007
Rule example <RULE> <CONDITION> EXCLUDE 65R AND (SELECT ATLEAST 2 AND NOTMORETHAN 2 FROM (74V,181C,184V)) AND (SELECT ATLEAST 5 FROM (41L,67N,70R,210W,215FY,219QE)) AND (SELECT ATLEAST 2 AND NOTMORETHAN 2 FROM (41L,210W,215YF)) </CONDITION> <ACTIONS> <LEVEL>5</LEVEL> </ACTIONS> </RULE> M. Obermeier 4/2007
Sequence entry form M. Obermeier 4/2007
Mutation list entry form M. Obermeier 4/2007
Internet Tool output common informations included sequences HIV-1 subtype all mutations resistance associated mutations scored mut results drugs all scored mutations comments M. Obermeier 4/2007
www.hiv-grade.de M. Obermeier 4/2007
Clinical Validation � n=365 � 5 centers � Active drug score from 0 (R) to 1 (S) (ADS) � Inclusion criteria � Treatment failure � Genotype � Treatment before and after change � VL 0-12 weeks before change � VL change 8-16 weeks after change in treatment
Treatment 300 250 before change 200 after change number 150 100 50 0 AZT ddC d4T 3TC TDF FTC NVP SQV RTV NFV APV ATV T20 ddI ABC DLV EFV IDV LPV_r TPV_r r drug M. Obermeier 4/2007
Active drug score (ADS) � transformation of a qualitative statement into a quantitative factor � Resistant => 0 � Intermediate => 0.33 � limited susceptibility => 0.66 � Susceptible => 1 � Hypersusceptible => 1.33 � Sum of all given drugs M. Obermeier 4/2007
Clinical validation GRADE True positive rate HIVDB REGA ANRS False positive rate M. Obermeier 4/2007
Simple linear regression • Simple model: VL = Δ + after _ change log( ) a * ADS b VL before _ change M. Obermeier 4/2007
simple linear regression HIV-GRADE R 2 =0.12 4 2 Δ LOGVL 0 -2 -1 0 1 2 3 Δ ADS M. Obermeier 4/2007
simple linear regression Stanford HIVdb R 2 =0.13 4 2 Δ LOGVL 0 -2 -2 -1 0 1 2 3 Δ ADS M. Obermeier 4/2007
simple linear regression ANRS R 2 =0.07 4 2 Δ LOGVL 0 -2 -2 -1 0 1 2 3 4 Δ ADS M. Obermeier 4/2007
simple linear regression REGA R 2 =0.13 4 2 Δ LOGVL 0 -2 -2 -1 0 1 2 3 Δ ADS M. Obermeier 4/2007
Multiple linear regression = ∑ # drugs VL Δ + after _ change log( ) a * ADS b drug drug ν ν VL = v 1 before _ change M. Obermeier 4/2007
Multiple linear regression results � In this cohort none of the algorithms can correctly predict the resistance against ABC. � HIVdb and GRADE are good in predicting APV resistance (whereas ANRS is not) M. Obermeier 4/2007
simple linear regression HIV-GRADE (w/o ABC) R 2 =0.17 4 3 2 Δ LOGVL 1 0 -1 -2 -1 0 1 2 3 Δ ADS M. Obermeier 4/2007
Multiple regression HIV-GRADE (w/o ABC) R 2 =0.28 4 3 Δ LOGVL 2 1 0 -1 -2 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Δ ADS M. Obermeier 4/2007
Correction of ADS with VL before treatment change R 2 =0.36 4 2 Δ LOGVL 0 -2 1 2 3 4 5 Δ ADS VLco M. Obermeier 4/2007
HIV-GRADE association � Thomas Berg, Medizinisches Labor Dr. Berg, Berlin � Patrick Braun, PZB, Aachen � Martin Däumer, Institut für Virologie, Köln � Josef Eberle, Pettenkofer-Institut, München � Robert Ehret, PZB Aachen � Rolf Kaiser, Institut für Virologie, Köln � Nils Kleinkauf, Charité, Berlin � Klaus Korn, NRZ für Retroviren, Erlangen � Harm Müller, Fenner-Labor, Hamburg � Martin Stürmer, Institut für Medizinische Virologie, Frankfurt � Hauke Walter, NRZ für Retroviren, Erlangen
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