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Can We Predict the Toxicity and Response to Thiopurines in Inflammatory Bowel Diseases?


ABSTRACT: Thiopurines are a cheap, effective treatment option in the management of inflammatory bowel disease (IBD). However, with the growing choice of targeted therapies available, as well as the well-documented toxicities of thiopurines, the role of thiopurines has been questioned. Nevertheless, given their inexpense in an era of spiraling healthcare costs, thiopurines remain an attractive option in the right patients. In the age of personalized medicine, being able to predict patients who will respond as well as those that will develop toxicity to a treatment is vital to tailoring therapy. This review will summarize the available literature with respect to predictors of response and toxicity to thiopurines in order to guide management in IBD. Specifically, toxicities addressed will include myelotoxicity, hepatotoxicity, pancreatitis, alopecia, gastrointestinal and flu-like symptoms, and complications associated with Epstein-Barr virus. While more work needs to be done to further our ability to predict both response to and side effects from therapies, pharmacogenomic research shows significant promise in its ability to personalize our use of thiopurines.

SUBMITTER: Luber RP 

PROVIDER: S-EPMC6892750 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Can We Predict the Toxicity and Response to Thiopurines in Inflammatory Bowel Diseases?

Luber Raphael P RP   Honap Sailish S   Cunningham Georgina G   Irving Peter M PM  

Frontiers in medicine 20191128


Thiopurines are a cheap, effective treatment option in the management of inflammatory bowel disease (IBD). However, with the growing choice of targeted therapies available, as well as the well-documented toxicities of thiopurines, the role of thiopurines has been questioned. Nevertheless, given their inexpense in an era of spiraling healthcare costs, thiopurines remain an attractive option in the right patients. In the age of personalized medicine, being able to predict patients who will respond  ...[more]

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