PURPOSE: Patients with cancer are an especially vulnerable population to potential drug-drug interactions (DDIs). This makes it important to adequately screen them for DDIs. The objective of this study was to compare the abilities of nine DDI screening tools to detect clinically relevant interactions with oral oncolytics. METHODS: Subscription-based tools (ie, PEPID, Micromedex, Lexicomp, Facts & Comparisons) and free tools (ie, Epocrates Free, Medscape, Drugs.com, RxList, WebMD) were compared for their abilities to detect clinically relevant DDIs for 145 drug pairs including an oral oncology agent. Clinical relevance was determined by a pharmacist using Stockley's Drug Interactions. Descriptive statistics were calculated for each tool, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and then compared grouped by free or subscription-based tools for the secondary analysis and analyzed via generalized estimating equations. RESULTS: For individual metrics, PPV had overall higher values (0.88 to 0.97) relative to the low values included for sensitivity (0.65 to 0.96), specificity (0.53 to 0.93) and NPV (0.38 to 0.83). The top-performing subscription and free tools, Lexicomp and Drugs.com, had no statistically significant differences in performance. Overall, subscription tools had a significantly higher sensitivity (0.85 ± 0.017 v 0.78 ± 0.017; P = .0082) and NPV (0.57 ± 0.039 v 0.48 ± 0.032; P = .031) than free tools. No differences were observed between the specificity and PPV. CONCLUSION: Due to the low performance of some tools for sensitivity, specificity, and NPV, individual performance should be examined and prioritized on the basis of the intended use when selecting a DDI tool. If a strong-performing subscription-based tool is unavailable, a strong-performing free option, like Drugs.com, is available.
PURPOSE: Patients with cancer are an especially vulnerable population to potential drug-drug interactions (DDIs). This makes it important to adequately screen them for DDIs. The objective of this study was to compare the abilities of nine DDI screening tools to detect clinically relevant interactions with oral oncolytics. METHODS: Subscription-based tools (ie, PEPID, Micromedex, Lexicomp, Facts & Comparisons) and free tools (ie, Epocrates Free, Medscape, Drugs.com, RxList, WebMD) were compared for their abilities to detect clinically relevant DDIs for 145 drug pairs including an oral oncology agent. Clinical relevance was determined by a pharmacist using Stockley's Drug Interactions. Descriptive statistics were calculated for each tool, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and then compared grouped by free or subscription-based tools for the secondary analysis and analyzed via generalized estimating equations. RESULTS: For individual metrics, PPV had overall higher values (0.88 to 0.97) relative to the low values included for sensitivity (0.65 to 0.96), specificity (0.53 to 0.93) and NPV (0.38 to 0.83). The top-performing subscription and free tools, Lexicomp and Drugs.com, had no statistically significant differences in performance. Overall, subscription tools had a significantly higher sensitivity (0.85 ± 0.017 v 0.78 ± 0.017; P = .0082) and NPV (0.57 ± 0.039 v 0.48 ± 0.032; P = .031) than free tools. No differences were observed between the specificity and PPV. CONCLUSION: Due to the low performance of some tools for sensitivity, specificity, and NPV, individual performance should be examined and prioritized on the basis of the intended use when selecting a DDI tool. If a strong-performing subscription-based tool is unavailable, a strong-performing free option, like Drugs.com, is available.
Authors: Amer A Koni; Maisa A Nazzal; Bushra A Suwan; Samah S Sobuh; Najiya T Abuhazeem; Asil N Salman; Husam T Salameh; Riad Amer; Sa'ed H Zyoud Journal: BMC Cancer Date: 2022-05-14 Impact factor: 4.638
Authors: Marta Fonseca; Evaline Cheng; Duc Do; Shouvik Haldar; Shelby Kutty; Eric H Yang; Arjun K Ghosh; Avirup Guha Journal: South Asian J Cancer Date: 2021-10-15
Authors: Lauren A Marcath; Taylor D Coe; Faisal Shakeel; Edward Reynolds; Mike Bayuk; Steven Haas; Bruce G Redman; Siu-Fun Wong; Daniel L Hertz Journal: J Patient Saf Date: 2021-01-01 Impact factor: 2.243
Authors: Marc Carrier; Normand Blais; Mark Crowther; Petr Kavan; Grégoire Le Gal; Otto Moodley; Sudeep Shivakumar; Deepa Suryanarayan; Vicky Tagalakis; Cynthia Wu; Agnes Y Y Lee Journal: Curr Oncol Date: 2021-12-18 Impact factor: 3.677