State of the art in benefit–risk analysis: Medicines

A similarity-based deep learning approach for determining the frequencies of drug side effects

The side effects of drugs present growing concern attention in the healthcare system. Accurately identifying the side effects of drugs is very important for drug development and risk assessment. Some computational models have been developed to predict the potential side effects of drugs and provided satisfactory performance. However, most existing methods can only predict whether side effects will occur and cannot determine the frequency of side effects. Although a few existing methods can predict the frequency of drug side effects, they strongly depend on the known drug-side effect relationships. Therefore, they cannot be applied to new drugs without known side effect frequency information. In this paper, we develop a novel similarity-based deep learning method, named SDPred, for determining the frequencies of drug side effects. Compared with the existing state-of-the-art models, SDPred integrates rich features and can be applied to predict the side effect frequencies of new drugs without any known drug-side effect association or frequency information. To our knowledge, this is the first work that can predict the side effect frequencies of new drugs in the population. The comparison results indicate that SDPred is much superior to all previously reported models. In addition, some case studies also demonstrate the effectiveness of our proposed method in practical applications. The SDPred software and data are freely available at https://github.com/zhc940702/SDPred, https://zenodo.org/record/5112573 and https://hub.docker.com/r/zhc940702/sdpred.

Benefit-Risk Assessment of Vaccines. Part I: A Systematic Review to Identify and Describe Studies About Quantitative Benefit-Risk Models Applied to Vaccines

Introduction

Understanding the balance between the benefits and risks of vaccination is essential to ensure informed and adequate public health decision making. Quantitative benefit–risk models (qBRm) represent useful tools to help decision makers with supporting benefit–risk assessment throughout the lifecycle of a medical product. However, few initiatives have been launched to harmonise qBRm approaches, specifically for vaccines.

Objectives

The aim of this paper was to identify publications about qBRm applied to vaccines through a systematic literature review, and to describe their characteristics.

Methods

Medline, Scopus and Institute for Scientific Information Web of Knowledge databases were searched to identify articles in English, published from database inceptions up to December 2019. The search strategy included the combination of three key concepts: ‘benefit–risk’, ‘modelling’ and ‘vaccines’. Data extracted included the modelling context and the methodological approaches used.

Results

Of 3172 publications screened, 48 original publications were included. Most of the selected studies were published over the past decade and focused on rotavirus (15), dengue (10) and influenza (6) vaccines. The majority (30) of studies reported analyses related to high-income countries. The methodology of the studies differed, particularly in modelling techniques, benefit–risk measures, and sensitivity analyses. The present work also pointed out a high level of variability in the quality of reporting across studies, with particular regard to input parameters and methodological approaches.

Conclusions

This review provides an extensive list of qBRm applied to vaccines. Discrepancies across studies were identified during our review. While the number of published qBRm studies is increasing, no reporting guidance for qBRm applied to vaccines is currently available. This may affect decision makers’ confidence in the results and their benefit–risk assessment(s); therefore, the development of such reporting guidance is highly needed.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00984-7) contains supplementary material, which is available to authorized users.

Risk-benefit in food safety and nutrition - Outcome of the 2019 Parma Summer School

Risk-benefit assessment is the comparison of the risk of a situation to its related benefits, i.e. a comparison of scenarios estimating the overall health impact. The risk-benefit analysis paradigm mirrors the classical risk analysis one: risk-benefit assessment goes hand-in-hand with risk-benefit management and risk-benefit communication. The various health effects associated with food consumption, together with the increasing demand for advice on healthy and safe diets, have led to the development of different research disciplines in food safety and nutrition. In this sense, there is a clear need for a holistic approach, including and comparing all of the relevant health risks and benefits. The risk-benefit assessment of foods is a valuable approach to estimate the overall impact of food on health. It aims to assess together the negative and positive health effects associated with food intake by integrating chemical and microbiological risk assessment with risk and benefit assessment in food safety and nutrition. The 2019 Parma Summer School on risk-benefit in food safety and nutrition had the objective was to provide an opportunity to learn from experts in the field of risk-benefit approach in food safety and nutrition, including theory, case studies, and communication of risk-benefit assessments plus identify challenges for the future. It was evident that whereas tools and approaches have been developed, more and more case studies have been performed which can form an inherent validation of the risk-benefit approach. Executed risk-benefit assessment case studies apply the steps and characteristics developed: a problem formulation (with at least 2 scenarios), a tiered approach until a decision can be made, one common currency to describe both beneficial and adverse effects (DALYs in most instances). It was concluded that risk-benefit assessment in food safety and nutrition is gaining more and more momentum, while also many challenges remain for the future. Risk-benefit is on the verge of really enrolling into the risk assessment and risk analysis paradigm. The interaction between risk-benefit assessors and risk-benefit managers is pivotal in this, as is the interaction with risk-benefit communicators.

Using Discretely Integrated Condition Event Simulation To Construct Quantitative Benefit-Risk Models: The Example of Rotavirus Vaccination in France

PURPOSE

Although quantitative benefit-risk models (qBRms) are indisputably valuable tools for gaining comprehensive assessments of health care interventions, they are not systematically used, probably because they lack an integrated framework that provides methodologic structure and harmonization. An alternative that allows all stakeholders to design operational models starting from a standardized framework was recently developed: the discretely integrated condition event (DICE) simulation. The aim of the present work was to assess the feasibility of implementing a qBRm in DICE, using the example of rotavirus vaccination.

METHODS

A model of rotavirus vaccination was designed using DICE and implemented in spreadsheet software with 3 worksheets: Conditions, Events, and Outputs. Conditions held the information in the model; this information changed at Events, and Outputs were special Conditions that stored the results collected during the analysis. A hypothetical French birth cohort was simulated for the assessment of rotavirus vaccination over time. The benefits were estimated for up to 5 years, and the risks in the 7 days following rotavirus vaccination versus no vaccination were assessed, with the results expressed as benefit-risk ratios.

FINDINGS

This qBRm model required 8 Events, 38 Conditions, and 9 Outputs. Two Events cyclically updated the rates of rotavirus gastroenteritis (RVGE) and intussusception (IS) according to age. Vaccination occurred at 2 additional Events, according to the vaccination scheme applied in France, and affected the occurrence of the other Events. Outputs were the numbers of hospitalizations related to RVGE and to IS, and related deaths. The entire model was specified in a small set of tables contained in a 445-KB electronic workbook. Analyses showed that for each IS-related hospitalization or death caused, 1613 (95% credible interval, 1001-2800) RVGE-related hospitalizations and 787 (95% credible interval, 246-2691) RVGE-related deaths would be prevented by vaccination. These results are consistent with those from a published French study using similar inputs but a very different modeling approach.

IMPLICATIONS

A limitation of the DICE approach was the extended run time needed for completing the sensitivity analyses when implemented in the electronic worksheets. DICE provided a user-friendly integrated framework for developing qBRms and should be considered in the development of structured approaches to facilitate benefit-risk assessment.

Benefit-Risk Assessment of Esketamine Nasal Spray vs. Placebo in Treatment-Resistant Depression

This post hoc analysis assessed the benefit–risk profile of esketamine nasal spray + oral antidepressant (AD) induction and maintenance treatment in patients with treatment‐resistant depression (TRD). The Benefit–Risk Action Team framework was utilized to assess the benefit–risk profile using data from three induction studies and one maintenance study. Benefits were proportion of remitters or responders in induction studies and proportion of stable remitters or stable responders who remained relapse‐free in the maintenance study. Risks were death, suicidal ideation, most common adverse events (AEs), and potential long‐term risks. Per 100 patients on esketamine + AD vs. AD + placebo in induction therapy, 5–21 additional patients would remit and 14–17 additional patients would respond. In maintenance therapy, 19–32 fewer relapses would occur with esketamine. In both cases, there was little difference in serious or severe common AEs (primarily dissociation, vertigo, and dizziness). These findings support a positive benefit–risk balance for esketamine + AD as induction and maintenance treatment in patients with TRD.

Standards of evidence and causality in regulatory science: Risk and benefit assessment

In this paper we analyze the Russo-Williamson Thesis (RWT) as a standard of evidence in regulatory science, in risk as well as benefit assessment. In our analysis we take account of the recent controversies that have taken place in regulation with respect to the evidentiary requirements necessary for regulatory decision making. RWT's main point is that not only probabilistic but also mechanistic evidence is necessary for being able to infer the existence of causal links. We ask in which way RWT could have an impact upon current decision making about subjecting to regulation (or, to the contrary, leaving them unregulated) certain chemical substances, food stuffs, health claims, and other typical objects of regulation. We show that the application of RWT resolves some of the problems posed by current standards of evidence. RWT makes it possible to determine with higher accuracy if a particular substance should be subjected to regulation or not, even though under certain circumstances RWT itself may turn into a source of regulatory error. The adequacy of RWT as a standard of evidence depends on the precise manner of its application to regulation (particularly the consideration of mechanistic evidence as a complementary or necessary requirement), as well as the assessment of its non-epistemic consequences.

Benefit-risk assessment of paliperidone oral extended-release tablet versus monthly injectable for maintenance treatment of schizophrenia

The purpose of this study was to conduct a post-hoc benefit-risk assessment of paliperidone palmitate once-monthly (PP1M) injectable versus oral paliperidone extended-release (ER) in schizophrenia maintenance treatment. The Benefit-Risk Action Team framework was used to structure the analysis based on patient-level data from two similar, double-blind, placebo-controlled relapse studies. Efficacy outcomes were relapse, psychiatric hospitalization, Clinical Global Impression-Severity scale, Personal and Social Performance (PSP) scale, and Positive and Negative Syndrome Scale (PANSS). Safety outcomes were extrapyramidal symptom-related adverse events, weight gain, prolactin-related adverse events, somnolence, orthostatic hypotension, anticholinergic use, fasting plasma glucose, and total cholesterol/high-density lipoprotein. For the first 8 weeks of maintenance treatment, most efficacy outcomes significantly favored PP1M compared with paliperidone ER. Per 1000 patients, there would be 165, 115, 85, and 53 fewer cases of PSP worsening, relapse, PANSS worsening, and hospitalizations, respectively. For the first 40 weeks, PSP worsening significantly favored PP1M (140 fewer cases). Relapse, PANSS, hospitalizations, and Clinical Global Impression-Severity scale showed a consistent pattern favoring PP1M but were not significant. Safety outcomes for both 8-week and 40-week periods demonstrated no statistically significant differences between groups. These analyses suggest a benefit-risk profile favoring PP1M over oral paliperidone ER throughout 40 weeks of treatment, particularly in early treatment.

Critical appraisal of the assessment of benefits and risks for foods, 'BRAFO Consensus Working Group'

BRAFO, Benefit-Risk Analysis for Foods, was a European Commission project funded within Framework Six as a Specific Support Action and coordinated by ILSI Europe. BRAFO developed a tiered methodology for assessing the benefits and risks of foods and food components, utilising a quantitative, common scale for health assessment in higher tiers. This manuscript reports on the implications of the experience gained during the development of the project for the further improvement of benefit-risk assessment methodology. It was concluded that the methodology proposed is applicable to a range of situations and that it does help in optimising resource utilisation through early identification of those benefit-risk questions where benefit clearly outweighs risk or vice versa. However, higher tier assessments are complex and demanding of time and resources, emphasising the need for prioritisation. Areas identified as requiring further development to improve the utility of benefit-risk assessment include health weights for different populations and endpoints where they do not currently exist, extrapolation of effects from studies in animals to humans, use of in vitro data in benefit-risk assessments, and biomarkers of early effect and how these would be used in a quantitative assessment.