Social media and internet search data to inform drug utilization: A systematic scoping review.

Introduction: Drug utilization is currently assessed through traditional data sources such as big electronic medical records (EMRs) databases, surveys, and medication sales. Social media and internet data have been reported to provide more accessible and more timely access to medications' utilization. Objective: This review aims at providing evidence comparing web data on drug utilization to other sources before the COVID-19 pandemic. Methods: We searched Medline, EMBASE, Web of Science, and Scopus until November 25th, 2019, using a predefined search strategy. Two independent reviewers conducted screening and data extraction. Results: Of 6,563 (64%) deduplicated publications retrieved, 14 (0.2%) were included. All studies showed positive associations between drug utilization information from web and comparison data using very different methods. A total of nine (64%) studies found positive linear correlations in drug utilization between web and comparison data. Five studies reported association using other methods: One study reported similar drug popularity rankings using both data sources. Two studies developed prediction models for future drug consumption, including both web and comparison data, and two studies conducted ecological analyses but did not quantitatively compare data sources. According to the STROBE, RECORD, and RECORD-PE checklists, overall reporting quality was mediocre. Many items were left blank as they were out of scope for the type of study investigated. Conclusion: Our results demonstrate the potential of web data for assessing drug utilization, although the field is still in a nascent period of investigation. Ultimately, social media and internet search data could be used to get a quick preliminary quantification of drug use in real time. Additional studies on the topic should use more standardized methodologies on different sets of drugs in order to confirm these findings. In addition, currently available checklists for study quality of reporting would need to be adapted to these new sources of scientific information.

Fingolimod versus interferon beta 1-a: Benefit-harm assessment approach based on TRANSFORMS individual patient data.

Background: Fingolimod is a disease-modifying drug approved for multiple sclerosis but its benefit-harm balance has never been assessed compared to other active treatments. Objectives: Our aim was to compare the benefits and harms of fingolimod with interferon beta-1a using individual patient data from TRial Assessing injectable interferon versus FTY720 Oral in RRMS trial. Methods: We modelled the health status of patients over time including Expanded Disability Status Scale measurements, relapses and any adverse events. We assessed the mean health status between arms and the proportion of patients whose health deteriorated or improved relatively to baseline, using a prespecified minimal important difference of 4.6. We performed sensitivity analyses to test our assumptions. Results: Main and sensitivity analyses favoured fingolimod 0.5 mg over interferon beta-1a. The average health status difference was 1.01 (95% CI 0.93-1.08). Patients on fingolimod 0.5 mg were 0.47 (95% CI: 0.35-0.63, p < 0.001) times less likely to experience a relevant decline in health status compared to interferon beta-1a patients, with a number needed to treat of 7.10 [5.18, 11.23]. Conclusions: Fingolimod's net benefit over interferon beta-1a did not reach the clinical relevance over 1 year, but the decreased risk for health status deterioration may be more pronounced more long term and patients may prefer less treatment burden associated with fingolimod.

Benefit-harm balance of fingolimod in patients with MS: A modelling study based on FREEDOMS.

BACKGROUND: Fingolimod lowers the number of relapses in multiple sclerosis (MS) patients and slows down disease progression, but causes a broad spectrum of side effects. Our aim was to estimate the benefit-harm balance of fingolimod using individual patient data from FREEDOMS, a randomized controlled trial that compared two different dosages of fingolimod to placebo. METHODS: We modelled the health status of patients over two years on a scale ranging from 0 (worst health or death) to 100 (maximum health). The model considered Expanded Disability Status Scale measurements, relapses and adverse events. We compared the mean health status between arms, and the proportion of trial participants for whom health declined or improved compared to baseline by a predefined minimal important difference of 4.6 or more. RESULTS: The main analysis showed a net benefit for fingolimod 0.5mg compared to placebo, with an average health status difference over two years of 2.7 (95% CI 2.2 to 3.2). Patients on fingolimod 0.5mg were 0.53 (95% CI 0.40-0.72, p<0.001) times less likely to have a relevant decline in health status compared to patients on placebo, corresponding to a number needed to treat of 8 to prevent one relevant decline in health status. All sensitivity analyses favoured fingolimod 0.5mg. CONCLUSION: Although fingolimod's net benefit did not reach the clinical relevance on average, the decreased risk for a decline in health over two years may be relevant. This approach could be applied to other MS drugs and provide an objective evidence base for guideline recommendations.

Adverse Drug Reaction Risk Measures: A Comparison of Estimates from Drug Surveillance and Randomised Trials.

BACKGROUND: Most drug regulatory agencies and pharmaceutical companies hold databases of spontaneous reports of suspected adverse drug reactions (ADRs). Detection systems for ADR signals have been created by specialists to analyse such reports, based on the concept of disproportionality, in order to support safety decision making. However, these measures are often misinterpreted by non-specialists in pharmacovigilance. OBJECTIVES: Our aim was to assess agreement between estimates of risk from spontaneous reports of suspected ADRs and estimates of risks of ADRs from randomised controlled trials (RCTs). METHODS: From 150 drugs randomly selected from the US Food and Drug Administration's Adverse Event Reporting System (FAERS), we identified drugs where FAERS provided reporting odds ratios (RORs) and corresponding systematic reviews from the Cochrane database gave (pooled) odds ratios (ORs) for the same drugs and adverse reactions. We assessed agreement between (ln) RORs and (ln) ORs using the Pearson correlation coefficient and the Bland-Altman agreement method, and performed sensitivity analyses. RESULTS: We identified 6 drugs and 125 ADRs. Overall, there was a weak correlation (r = 0.20) between RORs (FAERS) and ORs (RCTs). However, we observed a stronger correlation (r = 0.78) between RORs and ORs for one drug (roflumilast) that received market approval relatively recently (2011). CONCLUSIONS: Spontaneous reporting of suspected ADRs is an important tool for regulatory agencies and pharmaceutical companies in making decisions and detecting drug safety signals. Although there was moderate-to-strong agreement between ADR risk estimates from drug surveillance and RCTs for one drug, this study illustrates the current recommendations not to use disproportionality measures as valid proxies for risk estimates.