Abstract:
BACKGROUND:Many medicines are dosed to achieve a particular therapeutic range, and monitored using therapeutic drug monitoring (TDM). The evidence base for a therapeutic range can be evaluated using systematic reviews, to ensure it continues to reflect current indications, doses, routes and formulations, as well as updated adverse effect data. There is no consensus on the optimal methodology for systematic reviews of therapeutic ranges. METHODS:An overview of systematic reviews of therapeutic ranges was undertaken. The following databases were used: Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts and Reviews of Effects (DARE) and MEDLINE. The published methodologies used when systematically reviewing the therapeutic range of a drug were analyzed. Step by step recommendations to optimize such systematic reviews are proposed. RESULTS:Ten systematic reviews that investigated the correlation between serum concentrations and clinical outcomes encompassing a variety of medicines and indications were assessed. There were significant variations in the methodologies used (including the search terms used, data extraction methods, assessment of bias, and statistical analyses undertaken). Therapeutic ranges should be population and indication specific and based on clinically relevant outcomes. Recommendations for future systematic reviews based on these findings have been developed. CONCLUSION:Evidence based therapeutic ranges have the potential to improve TDM practice. Current systematic reviews investigating therapeutic ranges have highly variable methodologies and there is no consensus of best practice when undertaking systematic reviews in this field. These recommendations meet a need not addressed by standard protocols.
journal_name
BMC Med Res Methodoljournal_title
BMC medical research methodologyauthors
Cooney L,Loke YK,Golder S,Kirkham J,Jorgensen A,Sinha I,Hawcutt Ddoi
10.1186/s12874-017-0363-zsubject
Has Abstractpub_date
2017-06-02 00:00:00pages
84issue
1issn
1471-2288pii
10.1186/s12874-017-0363-zjournal_volume
17pub_type
杂志文章,评审abstract:BACKGROUND:Predicting survival of recipients after liver transplantation is regarded as one of the most important challenges in contemporary medicine. Hence, improving on current prediction models is of great interest.Nowadays, there is a strong discussion in the medical field about machine learning (ML) and whether it...
journal_title:BMC medical research methodology
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journal_title:BMC medical research methodology
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