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MOdified NARanjo Causality Scale for ICSRs (MONARCSi): A Decision Support Tool for Safety Scientists.

ABSTRACT: INTRODUCTION:Within the field of Pharmacovigilance, the most common approaches for assessing causality between a report of a drug and a corresponding adverse event are clinical judgment, probabilistic methods and algorithms. Although multiple methods using these three approaches have been proposed, there is currently no universally accepted method for assessing drug-event causality in ICSRs and variability in drug-event causality assessments is well documented. OBJECTIVE:This study describes the development and validation of an Individual Case Safety Report (ICSR) Causality Decision Support Tool to assist Safety Professionals (SPs) performing causality assessments. METHODS:Roche developed this model with nine drug-event pair features capturing important aspects of Naranjo's scoring system, selected Bradford-Hill criteria, and internal Roche safety practices. Each of the features was weighted based on individual safety professional (n?=?65) assessments of the importance of that feature when assessing causality, using an ordinal weighting scale (0?=?no importance, 4?=?very high importance). The mean and associated standard deviation for each feature weight was calculated and were used as inputs to a fitted logistic equation, which calculated the probability of a causal relationship between the drug and adverse event. Model training, validation, and testing were conducted by comparing MONARCSi causality classifications to previous company causality assessments for 978 randomly selected, clinical trial drug-event pairs based on their respective features and weights. RESULTS:The final model test, a two-by-two comparison of the results, showed substantial agreement (Gwet Kappa?=?0.77) between MONARCSi and Roche safety professionals' assessments of causality, using global introspection. The model exhibited moderate sensitivity (65%) and high specificity (93%), high positive and negative predictive values (79 and 88%, respectively), and an F1 score of 71%. CONCLUSION:Analysis suggests that the MONARCSi model could potentially be a useful decision support tool to assist pharmacovigilance safety professionals when evaluating drug-event causality in a consistent and documentable manner.

SUBMITTER: Comfort S

PROVIDER: S-EPMC6182464 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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MOdified NARanjo Causality Scale for ICSRs (MONARCSi): A Decision Support Tool for Safety Scientists.

Comfort Shaun S Dorrell Darren D Meireis Shawman S Fine Jennifer J

Drug safety 20181101 11

<h4>Introduction</h4>Within the field of Pharmacovigilance, the most common approaches for assessing causality between a report of a drug and a corresponding adverse event are clinical judgment, probabilistic methods and algorithms. Although multiple methods using these three approaches have been proposed, there is currently no universally accepted method for assessing drug-event causality in ICSRs and variability in drug-event causality assessments is well documented.<h4>Objective</h4>This stud ...[more]

PMID: 29876835

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Project description:Appropriate thromboprophylaxis for patients with atrial fibrillation or atrial flutter (AF) remains a national challenge. The recent availability of direct oral anticoagulants (DOACs) with comparable efficacy and improved safety compared with warfarin alters the balance between risk factors for stroke and benefit of anticoagulation. Our objective was to examine the impact of DOACs as an alternative to warfarin on the net benefit of oral anticoagulant therapy (OAT) in a real-world population of AF patients.This is a retrospective cohort study of patients with paroxysmal or persistent nonvalvular AF. We updated an Atrial Fibrillation Decision Support Tool (AFDST) to include DOACs as treatment options. The tool generates patient-specific recommendations based upon individual patient risk factor profiles for stroke and major bleeding using quality-adjusted life-years (QALYs) calculated for each treatment strategy by a decision analytic model. The setting included inpatient and ambulatory sites in an academic health center in the midwestern United States. The study involved 5,121 adults with nonvalvular AF seen for any ambulatory visit or inpatient hospitalization over the 1-year period (January through December 2016). Outcome measure was net clinical benefit in QALYs.When DOACs are a therapeutic option, the AFDST recommends OAT for 4,134 (81%) patients and no antithrombotic therapy or aspirin for 489 (9%). A strong recommendation for OAT could not be made in 498 (10%) patients. When warfarin is the only option, OAT is recommended for 3,228 (63%) patients and no antithrombotic therapy or aspirin for 973 (19%). A strong recommendation for OAT could not be made in 920 (18%) patients. In total, 1,508 QALYs could be gained if treatment were changed to that recommended by the AFDST.Availability of DOACs increases the proportion of patients for whom oral anticoagulation therapy is recommended in a real-world cohort of AF patients and increased projected QALYs by more than 1,500 when all patients are receiving thromboprophylaxis as recommended by the AFDST compared with current treatment.

Project description:BackgroundPromising health interventions tested in pilot studies will only achieve population-wide impact if they are implemented at scale across communities and health systems. Scaling up effective health interventions is vital as not doing so denies the community the most effective services and programmes. However, there remains a paucity of practical tools to assess the suitability of health interventions for scale-up. The Intervention Scalability Assessment Tool (ISAT) was developed to support policy-makers and practitioners to make systematic assessments of the suitability of health interventions for scale-up.MethodsThe ISAT was developed over three stages; the first stage involved a literature review to identify similar tools and frameworks that could be used to guide scalability assessments, and expert input to develop draft ISAT content. In the second stage, the draft ISAT tool was tested with end users. The third stage involved revising and re-testing the ISAT with end users to further refine the language and structure of the final ISAT.ResultsA variety of information and sources of evidence should be used to complete the ISAT. The ISAT consists of three parts. Part A: 'setting the scene' requires consideration of the context in which the intervention is being considered for scale-up and consists of five domains, as follows: (1) the problem; (2) the intervention; (3) strategic/political context; (4) evidence of effectiveness; and (5) intervention costs and benefits. Part B asks users to assess the potential implementation and scale-up requirements within five domains, namely (1) fidelity and adaptation; (2) reach and acceptability; (3) delivery setting and workforce; (4) implementation infrastructure; and (5) sustainability. Part C generates a graphical representation of the strengths and weaknesses of the readiness of the proposed intervention for scale-up. Users are also prompted for a recommendation as to whether the intervention (1) is recommended for scale-up, (2) is promising but needs further information before scaling up, or (3) does not yet merit scale-up.ConclusionThe ISAT fills an important gap in applied scalability assessment and can become a critical decision support tool for policy-makers and practitioners when selecting health interventions for scale-up. Although the ISAT is designed to be a health policy and practitioner tool, it can also be used by researchers in the design of research to fill important evidence gaps.

Dataset Information

MOdified NARanjo Causality Scale for ICSRs (MONARCSi): A Decision Support Tool for Safety Scientists.

Publications

MOdified NARanjo Causality Scale for ICSRs (MONARCSi): A Decision Support Tool for Safety Scientists.

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