Comparative analysis of three drug–drug interaction screening systems against probable clinically relevant drug–drug interactions: a prospective cohort study

2017 ◽  
Vol 73 (7) ◽  
pp. 875-882 ◽  
Author(s):  
Neža Muhič ◽  
Ales Mrhar ◽  
Miran Brvar
2020 ◽  
Vol 26 (8) ◽  
pp. 1843-1849
Author(s):  
Faisal Shakeel ◽  
Fang Fang ◽  
Kelley M Kidwell ◽  
Lauren A Marcath ◽  
Daniel L Hertz

Introduction Patients with cancer are increasingly using herbal supplements, unaware that supplements can interact with oncology treatment. Herb–drug interaction management is critical to ensure optimal treatment outcomes. Several screening tools exist to detect drug–drug interactions, but their performance to detect herb–drug interactions is not known. This study compared the performance of eight drug–drug interaction screening tools to detect herb–drug interaction with anti-cancer agents. Methods The herb–drug interaction detection performance of four subscription (Micromedex, Lexicomp, PEPID, Facts & Comparisons) and free (Drugs.com, Medscape, WebMD, RxList) drug–drug interaction tools was assessed. Clinical relevance of each herb–drug interaction was determined using Natural Medicine and each drug–drug interaction tool. Descriptive statistics were used to calculate sensitivity, specificity, positive predictive value, and negative predictive value. Linear regression was used to compare performance between subscription and free tools. Results All tools had poor sensitivity (<0.20) for detecting herb–drug interaction. Lexicomp had the highest positive predictive value (0.98) and best overall performance score (0.54), while Medscape was the best performing free tool (0.52). The worst subscription tools were as good as or better than the best free tools, and as a group subscription tools outperformed free tools on all metrics. Using an average subscription tool would detect one additional herb–drug interaction for every 10 herb–drug interactions screened by a free tool. Conclusion Lexicomp is the best available tool for screening herb–drug interaction, and Medscape is the best free alternative; however, the sensitivity and performance for detecting herb–drug interaction was far lower than for drug–drug interactions, and overall quite poor. Further research is needed to improve herb–drug interaction screening performance.


2012 ◽  
Vol 15 (2) ◽  
pp. 332 ◽  
Author(s):  
Paulo Roque Obreli-Neto ◽  
Alessandro Nobili ◽  
Divaldo Pereira De Lyra Júnior ◽  
Diogo Pilger ◽  
Camilo Molino Guidoni ◽  
...  

Purpose. The primary objective of this study was to investigate the incidence of drug-drug interactions (DDIs) related to adverse drug reactions (ADRs) in elderly outpatients who attended public primary healthcare units in a southeastern region of Brazil. The secondary objective was to investigate the possible predictors of DDI-related ADRs. Methods. A prospective cohort study was conducted between November 1, 2010, and November 31, 2011, in the primary public healthcare system in the Ourinhos micro-region in Brazil. Patients who were at least 60 years old, with at least one potential DDI, were eligible for inclusion in the study. Eligible patients were assessed by clinical pharmacists for DDI-related ADRs for 4 months. The causality of DDI-related ADRs was assessed independently by four clinicians using three decisional algorithms. The incidence of DDI-related ADRs during the study period was calculated. Logistic regression analysis was used to study DDI-related ADR predictors. Results. A total of 433 patients completed the study. The incidence of DDI-related ADRs was 6.5%. A multivariate analysis indicated that the adjusted odds ratios (ORs) rose from 0.91 (95% confidence interval [CI] = 0.75-1.12, p = 0.06) in patients aged 65-69 years to 4.40 (95% CI = 3.00-6.12, p < 0.01) in patients aged 80 years or older. Patients who presented two to three diagnosed diseases presented lower adjusted ORs (OR = 0.93 [95% CI = 0.68-1.18, p = 0.08]) than patients who presented six or more diseases (OR = 1.12 [95% CI = 1.02-2.01, p < 0.01]). Elderly patients who took five or more drugs had a significantly higher risk of DDI-related ADRs (OR = 2.72 [95% CI = 1.92-3.12, p < 0.01]) than patients who took three to four drugs (OR = 0.93 [95% CI = 0.74-1.11, p = 0.06]). No significant difference was found with regard to sex (OR = 1.08 [95% CI 0.48-2.02, p = 0.44]). Conclusion. The incidence of DDI-related ADRs in elderly outpatients was significant, and most of the events presented important clinical consequences. Because clinicians still have difficulty managing this problem, highlighting the factors that increase the risk of DDI-related ADRs is essential. Polypharmacy was found to be a significant predictor of DDI-related ADRs in our sample. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.


2013 ◽  
Vol 11 (9) ◽  
pp. 826-833 ◽  
Author(s):  
Carina Riediger ◽  
Michael W. Mueller ◽  
Florian Geismann ◽  
Andreas Lehmann ◽  
Tibor Schuster ◽  
...  

Drugs & Aging ◽  
2014 ◽  
Vol 31 (3) ◽  
pp. 225-232 ◽  
Author(s):  
Alexander Bennett ◽  
Danijela Gnjidic ◽  
Mark Gillett ◽  
Peter Carroll ◽  
Slade Matthews ◽  
...  

Author(s):  
Haline Tereza Costa ◽  
Ramon Weyler Duarte Leopoldino ◽  
Tatiana Xavier da Costa ◽  
Antonio Gouveia Oliveira ◽  
Rand Randall Martins

Author(s):  
Vianney Tuloup ◽  
Mathilde France ◽  
Romain Garreau ◽  
Nathalie Bleyzac ◽  
Laurent Bourguignon ◽  
...  

ABSTRACT: Rifamycins are widely used for treating mycobacterial and staphylococcal infections. Drug-drug interactions (DDI) caused by rifampicin (RIF) is a major issue. We used a model-based approach to predict the magnitude of DDI with RIF and rifabutin (RBT) for 217 cytochrome P450 (CYP) substrates. On average, DDI caused by low-dose RIF were twice more potent than those caused by RBT. Contrary to RIF, RBT appears unlikely to cause severe DDI, even with sensitive CYP substrates.


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