Suppr超能文献

Individualization of therapy using viral markers.

作者信息

Merigan T

机构信息

Stanford University School of Medicine, California 94305, USA.

出版信息

J Acquir Immune Defic Syndr Hum Retrovirol. 1995;10 Suppl 1:S41-6.

PMID:8595507
Abstract

Early intervention with a combination of drugs is generally accepted as the way forward in the management of HIV infection. In general, combination therapy should include agents that demonstrate additive or synergistic activity, do not have similar side-effect profiles, and avoid cross-resistance. Use of these criteria will no doubt lead to the development of more effective combinations. However, it is well known that patients respond to therapy in very different ways. A number of trials have provided clear examples of the individualized nature of patient responses to therapy and have also demonstrated that the use of measures such as viral load and CD4 cell count, in conjunction with phenotypic and genotypic characterization of emerging viral strains, may significantly enhance our ability to predict disease progression. A number of methods are becoming available to quantify accurately viral load, and new methodologies such as the Affymetrix chip-sequencing technique will allow quick detection of genotypic alterations known to be associated with disease progression, such as the appearance of resistance mutations. These developments now enable us to conduct clinical trials to assess the impact of an individualized approach to therapy, i.e., the changing of treatment regimens based on the identification of resistance markers, changes in viral load and CD4 cell count, and conversion from non-syncytium-inducing to syncytium-inducing phenotype. It is hoped that studies conducted in the near future will show that an approach of gaining maximal benefit from one treatment regimen before moving on to another, as a result of genotypic or viral load markers, will prevent destruction of the immune system and will ultimately prolong the well-being and survival of patients with HIV infection.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验