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Meta-analysis of pharmacogenetic interactions in amyotrophic lateral sclerosis clinical trials.

Author: , Al-ChalabiAmmar, BorgheroGiuseppe, ChioAdriano, DiekstraFrank P, EijkemansMarinus J C, JonesAshley R, LeighP Nigel, MandrioliJessica, MoraGabriele, ShatunovAleksey, ShawChristopher E, ShawPamela J, SprovieroWilliam, VeldinkJan H, VerstraeteEsther, VolantiPaolo, YoungCarolyn A, van EijkRuben P A, van EsMichael A, van RheenenWouter, van den BergLeonard H

Journal ArticleAn article published in an academic or professional journal that reports original research or scholarly analysis.
Meta-AnalysisA statistical technique that integrates the results of multiple studies to draw more general conclusions about a particular issue.
ReviewAn article that critically examines existing research on a particular topic and summarizes the current state of knowledge in the field.

Overview

This study assessed the efficacy of lithium carbonate in treating amyotrophic lateral sclerosis (ALS) based on genetic subgroups. The study found no overall improvement in survival with lithium carbonate, but suggested that specific genetic subgroups may respond to the treatment.
Paper Details　
Original Abstract of the Article :
OBJECTIVE: To assess whether genetic subgroups in recent amyotrophic lateral sclerosis (ALS) trials responded to treatment with lithium carbonate, but that the treatment effect was lost in a large cohort of nonresponders. METHODS: Individual participant data were obtained from 3 randomized trials i...See full text at original site
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引用元：
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664299/

データ提供：米国国立医学図書館（NLM）

Pharmacogenetic Interactions in Amyotrophic Lateral Sclerosis: A Personalized Approach to Treatment

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease, and finding effective treatments remains a major challenge. This research explores the potential of personalized medicine in ALS, investigating whether genetic variations influence the response to lithium carbonate treatment. The authors conducted a meta-analysis of individual participant data from three randomized trials, revealing insights into the complex relationship between genetics and treatment outcomes. This study highlights the potential for genetic testing to guide treatment decisions in ALS, paving the way for a more personalized approach.

Unlocking the Genetic Code of ALS Treatment: Towards Personalized Medicine

This research opens the door to a more personalized approach to ALS treatment by demonstrating the potential of pharmacogenetics. The findings suggest that genetic factors play a significant role in determining treatment response, emphasizing the need for individualized strategies. This discovery is a beacon of hope for individuals with ALS, as it offers the possibility of tailored treatments that maximize efficacy and minimize side effects.

Navigating the Desert of ALS: Seeking Personalized Solutions

The desert of ALS is vast and unforgiving, and finding effective treatments can feel like a daunting journey. This research provides a glimmer of hope, suggesting that genetic insights can guide us towards personalized solutions. By understanding the genetic factors that influence treatment response, we can navigate the complexities of ALS with a more informed approach, leading to tailored therapies that offer a greater chance of success.

Dr. Camel's Conclusion

This research underscores the importance of pharmacogenetics in ALS treatment, highlighting the potential for personalized medicine to transform patient care. The findings suggest that genetic testing can be a valuable tool for guiding treatment decisions, leading to more effective and individualized therapies. By harnessing the power of genetic information, we can navigate the complexities of ALS with a more informed approach, offering a greater chance of success and improving the lives of individuals living with this debilitating disease.

Date :
  1. Date Completed 2017-11-06
  2. Date Revised 2023-11-14
Further Info :

Pubmed ID

28978660

DOI: Digital Object Identifier

PMC5664299

SNS
PICO Info
in preparation
Languages

English

Positive IndicatorAn AI analysis index that serves as a benchmark for how positive the results of the study are. Note that it is a benchmark and requires careful interpretation and consideration of different perspectives.

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