A quantitative benefit-risk assessment approach to improve decision making in drug development: Application of a multicriteria decision analysis model in the development of combination therapy for overactive bladder

Proposal for capturing patient experience through extended value frameworks of health technologies

BACKGROUND: Inclusion of patient experience (PEx) in health technology assessment (HTA) has become increasingly important; however, no harmonized approach exists to help manufacturers or decision makers ensure PEx considerations are fair, consistent, and thorough within global HTA frameworks. OBJECTIVE: To develop a proposal for including PEx in the HTA frameworks of health technologies. METHODS: A systematic literature review (SLR) on existing value frameworks (VFs) was conducted to capture how PEx-related value judgment is currently considered. Guided by the results of the SLR, a research group including HTA experts and patient representatives used an iterative process to develop potential value domains to capture PEx, in accordance with international guidelines. Subsequently, a panel of international payer experts was used to challenge the proposed PEx domains and provide recommendations for implementation. RESULTS: The SLR found 61 VFs and multi-criteria decision analyses (MCDAs) that considered PEx; however, PEx-related value elements were often referred to superficially, without clear definitions. Five potential PEx domains, with proposed measures for each, were developed and refined using expert feedback: (1) responsiveness to patient's individual needs, (2) improved health literacy and empowerment, (3) patient and caregiver reported outcomes, (4) household's financial burden, and (5) improved access for vulnerable patient populations. A flexible approach for framework implementation was proposed. CONCLUSIONS: Proposed PEx domains could be implemented at multiple levels of healthcare decision making to formalize consideration of PEx in the assessment of value, either through the extension of existing VFs or to create new PEx-focused VFs and more holistic decision making tools. DISCLOSURES: This study was funded and sponsored by UCB Pharma. The funding agreement ensured the authors' independence in designing the study, interpreting the data, writing, and publishing the report. Charokopou, Mountain, and Szegvari are employed by UCB Pharma. Inotai, Jakab, and Kalo are employed by Syreon Research Institute, which received funding from UCB Pharma for this research. Brixner has received fees from AbbVie, Elevar, Millcreek Outcomes Group, Novartis, Sanofi, UCB Pharma, and Xcenda. Campbell has received grants and contracts from the PhRMA Foundation and the Institute for Clinical and Economic Review. During a sabbatical leave, Campbell collaborated with Syreon Research Institute on research projects that included funding from UCB Pharma. Hawkins has received consultancy fees from UCB Pharma. Kristensen has received speakers bureau fees from Pfizer, AbbVie, Amgen, UCB Pharma, Celgene, Bristol-Myers Squibb, MSD, Novartis, Eli Lilly, and Janssen Pharmaceuticals and consultancy fees from UCB Pharma.

Structured benefit-risk evaluation for medicinal products: review of quantitative benefit-risk assessment findings in the literature

A favorable benefit–risk profile remains an essential requirement for marketing authorization of medicinal drugs and devices. Furthermore, prior subjective, implicit and inconsistent ad hoc benefit–risk assessment methods have rightly evolved towards more systematic, explicit or “structured” approaches. Contemporary structured benefit–risk evaluation aims at providing an objective assessment of the benefit–risk profile of medicinal products and a higher transparency for decision making purposes. The use of a descriptive framework should be the preferred starting point for a structured benefit–risk assessment. In support of more precise assessments, quantitative and semi-quantitative methodologies have been developed and utilized to complement descriptive or qualitative frameworks in order to facilitate the structured evaluation of the benefit–risk profile of medicinal products. In addition, quantitative structured benefit–risk analysis allows integration of patient preference data. Collecting patient perspectives throughout the medical product development process has become increasingly important and key to the regulatory decision-making process. Both industry and regulatory authorities increasingly rely on descriptive structured benefit–risk evaluation and frameworks in drug, vaccine and device evaluation and comparison. Although varied qualitative methods are more commonplace, quantitative approaches have recently been emphasized. However, it is unclear how frequently these quantitative frameworks have been used by pharmaceutical companies to support submission dossiers for drug approvals or to respond to the health authorities’ requests. The objective of this study has been to identify and review, for the first time, currently available, published, structured, quantitative benefit–risk evaluations which may have informed health care professionals and/or payor as well as contributed to decision making purposes in the regulatory setting for drug, vaccine and/or device approval.

Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art

BACKGROUND

Multi-criteria decision analysis (MCDA) concepts, models and tools have been used increasingly in health technology assessment (HTA), with several studies pointing out practical and theoretical issues related to its use. This study provides a critical review of published studies on MCDA in the context of HTA by assessing their methodological quality and summarising methodological challenges.

METHODS

A systematic review was conducted to identify studies discussing, developing or reviewing the use of MCDA in HTA using aggregation approaches. Studies were classified according to publication time and type, country of study, technology type and study type. The PROACTIVE-S approach was constructed and used to analyse methodological quality. Challenges and limitations reported in eligible studies were collected and summarised; this was followed by a critical discussion on research requirements to address the identified challenges.

RESULTS

129 journal articles were eligible for review, 56% of which were published in 2015-2017; 42% focused on pharmaceuticals; 36, 26 and 18% reported model applications, issues regarding MCDA implementation analyses, and proposing frameworks, respectively. Poor compliance with good methodological practice (< 25% complying studies) was found regarding behavioural analyses, discussion of model assumptions and uncertainties, modelling of value functions, and dealing with judgment inconsistencies. The five most reported challenges related to evidence and data synthesis; value system differences and participant selection issues; participant difficulties; methodological complexity and resource balance; and criteria and attributes modelling. A critical discussion on ways to address these challenges ensues.

DISCUSSION

Results highlight the need for advancement in robust methodologies, procedures and tools to improve methodological quality of MCDA in HTA studies. Research pathways include developing new model features, good practice guidelines, technologies to enable participation and behavioural research.

Exposure-Response-Based Product Profile-Driven Clinical Utility Index for Ipatasertib Dose Selection in Prostate Cancer

The aims of this work were to characterize ipatasertib exposure–response (E‐R) relationships in a phase II study and to quantitatively assess benefit‐risk using a clinical utility index approach to support ipatasertib phase III dose selection in patients with metastatic castration‐resistant prostate cancer. Logistic regression and Cox proportional‐hazards models characterized E‐R relationships for safety and efficacy endpoints, respectively. Exposure metrics with and without considering dose interruptions/reductions (modifications) were tested in the E‐R models. Despite a steeper E‐R relationship when accounting for dose modifications, similar dose‐response projections were generated. The clinical utility index analysis assessed important attributes, weights, and clinically meaningful cutoff/tradeoff values based on predefined minimal, target, and optimistic product profiles. Ipatasertib 400 mg daily, showing the highest probability of achieving the minimal product profiles and better benefit‐risk balance than other doses (200–500 mg daily), was selected for further development in metastatic castration‐resistant prostate cancer.

Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting

WHAT IS KNOWN AND OBJECTIVE

Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies.

METHODS

Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework).

RESULTS AND DISCUSSION

These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference.

WHAT IS NEW AND CONCLUSION

Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment.