Ravela Jaideep, Betts Bradley J, Brun-Vézinet Francoise, Vandamme Anne-Mieke, Descamps Diane, van Laethem Kristel, Smith Kate, Schapiro Jonathan M, Winslow Dean L, Reid Caroline, Shafer Robert W
Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, California 94301, USA.
J Acquir Immune Defic Syndr. 2003 May 1;33(1):8-14. doi: 10.1097/00126334-200305010-00002.
Several rules-based algorithms have been developed to interpret results of HIV-1 genotypic resistance tests. To assess the concordance of these algorithms and to identify sequences causing interalgorithm discordances, we applied four publicly available algorithms to the sequences of isolates from 2,045 individuals in northern California. Drug resistance interpretations were classified as S for susceptible, I for intermediate, and R for resistant. Of 30,675 interpretations (2,045 sequences x 15 drugs), 4.4% were completely discordant, with at least one algorithm assigning an S and another an R; 29.2% were partially discordant, with at least one algorithm assigning an S and another an I, or at least one algorithm assigning an I and another an R; and 66.4% displayed complete concordance, with all four algorithms assigning the same interpretation. Discordances between nucleoside reverse transcriptase inhibitor interpretations usually resulted from several simple, frequently occurring mutational patterns. Discordances between protease inhibitor interpretations resulted from a larger number of more complex mutation patterns. Discordances between nonnucleoside reverse transcriptase inhibitor interpretations were uncommon and resulted from a small number of individual drug resistance mutations. Determining the clinical significance of these mutation patterns responsible for interalgorithm discordances will improve interalgorithm concordance and the accuracy of genotypic resistance interpretation.
已经开发了几种基于规则的算法来解释HIV-1基因型耐药性检测结果。为了评估这些算法的一致性并识别导致算法间不一致的序列,我们将四种公开可用的算法应用于加利福尼亚北部2045名个体的分离株序列。耐药性解释分为S(敏感)、I(中度)和R(耐药)。在30675次解释(2045个序列×15种药物)中,4.4%完全不一致,至少有一种算法判定为S而另一种判定为R;29.2%部分不一致,至少有一种算法判定为S而另一种判定为I,或至少有一种算法判定为I而另一种判定为R;66.4%显示完全一致,所有四种算法给出相同的解释。核苷类逆转录酶抑制剂解释之间的不一致通常源于几种简单的、频繁出现的突变模式。蛋白酶抑制剂解释之间的不一致源于大量更复杂的突变模式。非核苷类逆转录酶抑制剂解释之间的不一致并不常见,且源于少数个别耐药突变。确定这些导致算法间不一致的突变模式的临床意义将提高算法间的一致性和基因型耐药性解释的准确性。