Benefit-risk tradeoff preferences for chronic hand eczema treatments

Adverse events from topical corticosteroid use in chronic hand eczema - Findings from the Danish Skin Cohort

Background

Topical corticosteroids (TCS) are used to treat most patients with chronic hand eczema (CHE), but knowledge about TCS-related adverse events in CHE is limited.

Objectives

To investigate patient-reported adverse events to TCS in CHE patients.

Methods

Data on adverse events related to TCS use in patients with CHE were analyzed from the Danish Skin Cohort; a prospective survey of a hospital cohort. We assessed patients' knowledge about TCS use and adverse event risks, and preference of TCS versus a nonsteroidal topical alternative.

Results

Of 724 adults with CHE (64.0% women; mean age 57.5 [standard deviation 12.8] years), 64.1% reported skin atrophy, 41.4% cracks/fissures, 23.9% bleeding, 45.9% pain/stinging sensation, 40.0% reduced hand dexterity, and 40.2% worsening of CHE signs or symptoms from using TCS. We observed CHE-severity-dependent associations (all groups; P < .0001). Most patients (76.4%) would prefer a nonsteroidal option, 10.9% were neutral/indifferent, and 12.7% would prefer TCS for CHE. The median numerical rating scale-score (ranging from 0 to 10) was 10 (interquartile range 6-10) for preferring a nonsteroidal topical treatment.

Limitations

Differences across TCS formulations were unexplored.

Conclusion

TCS-related cutaneous adverse events were common. There is a desire from patients for novel steroid-free topical alternatives for CHE treatment.

Dynamics of Patient-Based Benefit-Risk Assessment of Medicines in Chronic Diseases: A Systematic Review

BACKGROUND

A critical gap exits in understanding the dynamics of patient-based benefit-risk assessment (BRA) of medicines in chronic diseases during the disease journey.

PURPOSE

To systematically review and synthesize current evidence on the changes of patients' preferences about the benefits and risks of medicines during their disease journey including the influence of disease duration and severity, and previous treatment experience.

METHODS

A systematic review of studies identified in PubMed and Embase, from inception to November 2020, was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Articles were eligible if they analyzed adult patient-based BRA of medicines with a chronic disease, based on at least one of the pre-specified dimensions: disease severity, disease duration, or previous treatment experience.

RESULTS

A total of 26,228 articles were identified and 105 were eligible for inclusion. Of these, 85 detected a variation in patient-based BRA of medicines with at least one of the pre-specified criteria. Patients with higher disease severity and more treatment experience have increased risk tolerance. It remains inconclusive whether disease duration directly affects the relative importance of a patient's preference.

CONCLUSION

Factors important for patients' BRA of their medicines during a chronic disease journey vary more with their clinical situation and previous treatment experience than with time since diagnosis. Due to the importance of these factors on patients' perspectives and potential impact on their decision-making and eventually their clinical outcomes, there is a need for more studies to assess the dynamics of patients' BRA in every disease.

Use of Patient Preference Information in Benefit-Risk Assessment, Health Technology Assessment, and Pricing and Reimbursement Decisions: A Systematic Literature Review of Attempts and Initiatives

Objectives: Inclusion of patient preference (PP) data in decision making has been largely discussed in recent years. Healthcare decision makers—regulatory and health technology assessment (HTA)—are more and more conscious of the need for a patient-centered approach to decide on optimal allocation of scarce money, time, and technological resources. This literature review aims to examine the use of and recommendations for the integration of PP in decision making.

Methods: A literature search was conducted through PubMed/Medline in May 2019 to identify publications on PP studies used to inform benefit–risk assessments (BRAs) and HTAs and patient-centered projects and guidelines related to the inclusion of PPs in health policy decision making. After title and abstract screening and full-text review, selected publications were analyzed to retrieve data related to the collection, use, and/or submission of PPs informing BRA or HTA as well as attempts and initiatives in recommendations for PPs integration in decision-making processes.

Results: Forty-nine articles were included: 24 attempts and pilot project discussions and 25 PP elicitation studies. Quantitative approaches, particularly discrete choice experiments, were the most used (24 quantitative elicitation studies and 1 qualitative study). The objective of assessing PPs was to prioritize outcome-specific information, to value important treatment characteristics, to provide patient-focused benefit–risk trade-offs, and to appraise the patients' willingness to pay for new technologies. Moreover, attempts and pilot projects to integrate PPs in BRAs and HTAs were identified at the European level and across countries, but no clear recommendations have been issued yet. No less than seven public and/or private initiatives have been undertaken by governmental agencies and independent organizations to set guidance targeting improvement of patients' involvement in decision making.

Conclusion: Despite the initiatives undertaken, the pace of progress remains slow. The use of PPs remains poorly implemented, and evidence of proper use of these data in decision making is lacking. Guidelines and recommendations formalizing the purpose of collecting PPs, what methodology should be adopted and how, and who should be responsible for generating these data throughout the decision-making processes are needed to improve and empower integration of PPs in BRA and HTA.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

Physician-Specific Maximum Acceptable Risk in Personalized Medicine: Implications for Medical Decision Making

BACKGROUND

In discrete-choice experiments (DCEs), respondents are presented with a series of scenarios and asked to select their preferred choice. In clinical decision making, DCEs allow one to calculate the maximum acceptable risk (MAR) that a respondent is willing to accept for a one-unit increase in treatment efficacy. Most published studies report the average MAR for the whole sample, without conveying any information about heterogeneity. For a sample of psychiatrists prescribing drugs for a series of hypothetical patients with schizophrenia, this article demonstrates how heterogeneity accounted for in the DCE modeling can be incorporated in the derivation of the MAR.

METHODS

Psychiatrists were given information about a group of patients' responses to treatment on the Positive and Negative Syndrome Scale (PANSS) and the weight gain associated with the treatment observed in a series of 26 vignettes. We estimated a random parameters logit (RPL) model with treatment choice as the dependent variable.

RESULTS

Results from the RPL were used to compute the MAR for the overall sample. This was found to be equal to 4%, implying that, overall, psychiatrists were willing to accept a 4% increase in the risk of an adverse event to obtain a one-unit improvement of symptoms - measured on the PANSS. Heterogeneity was then incorporated in the MAR calculation, finding that MARs ranged between 0.5 and 9.5 across the sample of psychiatrists.

LIMITATIONS

We provided psychiatrists with hypothetical scenarios, and their MAR may change when making decisions for actual patients.

CONCLUSIONS

This analysis aimed to show how it is possible to calculate physician-specific MARs and to discuss how MAR heterogeneity could have implications for medical practice.