Acute pain pathways: protocol for a prospective cohort study.

INTRODUCTION: Opioid analgesics are often used to treat moderate-to-severe acute non-cancer pain; however, there is little high-quality evidence to guide clinician prescribing. An essential element to developing evidence-based guidelines is a better understanding of pain management and pain control among individuals experiencing acute pain for various common diagnoses. METHODS AND ANALYSIS: This multicentre prospective observational study will recruit 1550 opioid-naïve participants with acute pain seen in diverse clinical settings including primary/urgent care, emergency departments and dental clinics. Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. Participants will be enrolled to represent diverse races and ethnicities and pain conditions, as well as geographical diversity. Data analysis will focus on assessing patients' patterns of pain and opioid analgesic use, along with other pain treatments; associations between patient and condition characteristics and patient-centred outcomes including resolution of pain, satisfaction with care and long-term use of opioid analgesics; and descriptive analyses of patient management of leftover opioids. ETHICS AND DISSEMINATION: This study has received approval from IRBs at each site. Results will be made available to participants, funders, the research community and the public. TRIAL REGISTRATION NUMBER: NCT04509115.

Comparing clotting factors attributes across different methods of preference elicitation in haemophilia patients.

INTRODUCTION: Emerging, systematic approaches for capturing patient input, such as preference elicitation, can provide valuable information for the benefit-risk assessment of medical products for treating bleeding disorders, such as haemophilia. AIM: This study aims to identify existing and develop new methods to capture, rank and summarize preference scores for clotting factor therapies. METHODS: Haemophilia patient preference data were compiled from studies identified through literature review and publicly available US FDA patient-focused drug development meeting documents. Text mining was performed to identify major themes across studies. A standardized preference score was estimated and aggregated. RESULTS: Ten preference studies that employed qualitative (n = 3), and quantitative methods (n = 7) met the inclusion criteria. Text mining of qualitative and quantitative studies revealed similar themes as the standardized preference attribute importance. We found that seven quantitative studies employed discrete choice experiments (DCE)/conjoint analysis (CA) and examined a range of 5-12 attributes. For DCE/CA studies published prior to 2014 (n = 4), safety attributes (inhibitor and viral safety) were among the most important attributes, accounting for ~46% of the total utility measured. DCE/CA studies published after 2014 (n = 3) focused on frequency of infusion and reduction of bleeding risk, accounting for ~67% of the total utility. Interestingly, two studies that used different preference elicitation approaches (DCE and a monadic conjoint approach) both ranked infusion frequency as the most important attribute. CONCLUSIONS: Although there are few published patient preference studies for haemophilia, the results of this study can be viewed in the larger context of enhancing scientific methods of incorporating patient input in medical product development.

Advancing the science of patient input throughout the regulatory decision-making process.

The US Food and Drug Administration (FDA) understands the value of patient input in the regulatory decision-making process and has worked to enhance meaningful engagement. In recent years, there has been an increased scientific demand for more systematic and quantitative approaches to incorporate patient input throughout the medical product lifecycle, including to inform regulatory benefit-risk assessments. The use of patient preference information (PPI), elicited using established scientific methods, is a promising strategy for accomplishing this. Although much of the science behind PPI is not new, its application in a regulatory setting will require adapting and advancing the science of identifying, collecting, and evaluating patient input for informing regulatory decision making. Patient input and empowerment are foundational to a learning healthcare system. A learning healthcare system paradigm can also help us better understand and continuously improve the incorporation of the patient perspective in regulatory decision making. In this article, we highlight the Food and Drug Administration's Center for Biologics Evaluation and Research experience and current initiatives on advancing the science of patient input in a regulatory setting, in particular, PPI. We provide a use case that explores how the principles and benefits of PPI applied in shared clinical decision making can be realized and leveraged to enhance regulatory evaluation of innovative therapies. To further advance the application of the science of patient input in our regulatory framework, we compiled a list of example resources that support stakeholders in designing and conducting PPI studies. More collaborative research among stakeholders is needed to establish best practice approaches, ensure scientific validity, and continuously learn and improve the systematic incorporation of scientific patient input throughout the regulatory decision-making process.

Early discontinuation of treatment for osteoporosis.

PURPOSE: To identify factors associated with early treatment discontinuation of three agents commonly prescribed for women with low bone density. METHODS: A telephone survey was conducted in 2000 to 2001 in a random sample of women aged 45 years or older who had bone density T-scores -1.0 or lower and who had initiated treatment with hormone replacement therapy, raloxifene, oral endronate. Logistic regression was used to estimate adjusted odds ratios for early treatment discontinuation. RESULTS: Among 956 women who were interviewed an average of 7 months after treatment initiation, 334 were taking hormone therapy, and 88 (26%) had discontinued; 256 were taking raloxifene, and 48 (19%) had discontinued (P = 0.03 vs. hormone therapy); and 366 were taking alendronate, and 70(19%) had discontinued (P = 0.02 vs. hormone therapy). Women with bothersome side effects (somewhat bothered: odds ratio [OR] = 4.0; 95% confidence interval [CI]: 2.5 to 6.5; very or extremely bothered: OR = 25; 95% CI: 16 to 39) or who thought that their bone density test results did not show osteoporosis (OR = 1.6; 95% CI: 1.0 to 2.5) were more likely to discontinue therapy, as compared with women reporting regular exercise (OR = 0.7; 95% CI: 0.4 to 1.0) or a willingness to take prescribed medications (OR = 0.6; 95% CI: 0.4 to 0.9). After adjustment for side effects and patient characteristics, the odds of early treatment discontinuation did not differ significantly among treatments. CONCLUSION: Improved adherence to osteoporosis treatment requires that treatment side effects be minimized and women be educated regarding their bone density test results.