N-of-1 trials for assessing the effects of deprescribing medications on short-term clinical outcomes in older adults: a systematic review

A qualitative study on the facilitators and barriers to adopting the N-of-1 trial methodology as part of clinical practice: potential versus implementation challenges

PURPOSE

To investigate opinions among healthcare stakeholders whether implementation of the N-of-1 trial approach in clinical practice is a feasible way to optimize evidence-based treatment results for unique patients.

METHODS

We interviewed clinicians, researchers, and a patient advocate (n = 13) with an interest in or experience with N-of-1 trials on the following topics: experience with N-of-1, measurement, validity and reliability, informally gathered data usability, and influence on physician-patient relationship. Interviews were analysed using qualitative, thematic analysis.

RESULTS

The N-of-1 approach has the potential to shift the current healthcare system towards embracing personalized medicine. However, its application in clinical practice carries significant challenges in terms of logistics, time investment and acceptability. New skills will be required from patients and healthcare providers, which may alter the patient-physician relationship. The rise of consumer technology enabling self-measurement may leverage the uptake of N-of-1 approaches in clinical practice.

CONCLUSIONS

There is a strong belief that the N-of-1 approach has the potential to play a prominent role in transitioning the current healthcare system towards embracing personalized medicine. However, there are many barriers deeply ingrained in our healthcare system that hamper the uptake of the N-of-1 approach, making it momentarily only interesting for research purposes.

Deprescribing: An umbrella review

This umbrella review examined systematic reviews of deprescribing studies by characteristics of intervention, population, medicine, and setting. Clinical and humanistic outcomes, barriers and facilitators, and tools for deprescribing are presented. The Medline database was used. The search was limited to systematic reviews and meta-analyses published in English up to April 2022. Reviews reporting deprescribing were included, while those where depre-scribing was not planned and supervised by a healthcare professional were excluded. A total of 94 systematic reviews (23 meta--analyses) were included. Most explored clinical or humanistic outcomes (70/94, 74 %); less explored attitudes, facilitators, or barriers to deprescribing (17/94, 18 %); few focused on tools (8/94, 8.5 %). Reviews assessing clinical or humanistic outcomes were divided into two groups: reviews with deprescribing intervention trials (39/70, 56 %; 16 reviewing specific deprescribing interventions and 23 broad medication optimisation interventions), and reviews with medication cessation trials (31/70, 44 %). Deprescribing was feasible and resulted in a reduction of inappropriate medications in reviews with deprescribing intervention trials. Complex broad medication optimisation interventions were shown to reduce hospitalisation, falls, and mortality rates. In reviews of medication cessation trials, a higher frequency of adverse drug withdrawal events underscores the importance of prioritizing patient safety and exercising caution when stopping medicines, particularly in patients with clear and appropriate indications.

Implementation considerations of deprescribing interventions: A scoping review

Over half of older adults experience polypharmacy, including medications that may be inappropriate or unnecessary. Deprescribing, which is the process of discontinuing or reducing inappropriate and/or unnecessary medications, is an effective way to reduce polypharmacy. This review summarizes (1) the process of deprescribing and conceptual models and tools that have been developed to facilitate deprescribing, (2) barriers, enablers, and factors associated with deprescribing, and (3) characteristics of deprescribing interventions in completed trials, as well as (4) implementation considerations for deprescribing in routine practice. In conceptual models of deprescribing, multilevel factors of the patient, clinician, and health-care system are all related to the efficacy of deprescribing. Numerous tools have been developed for clinicians to facilitate deprescribing, yet most require substantial time and, thus, may be difficult to implement during routine health-care encounters. Multiple deprescribing interventions have been evaluated, which mostly include one or more of the following components: patient education, medication review, identification of deprescribing targets, and patient and/or provider communication about high-risk medications. Yet, there has been limited consideration of implementation factors in prior deprescribing interventions, especially with regard to the personnel and resources in existing health-care systems and the feasibility of incorporating components of deprescribing interventions into the routine care processes of clinicians. Future trials require a more balanced consideration of both effectiveness and implementation when designing deprescribing interventions.

Optimizing pharmacotherapy and deprescribing strategies in older adults living with multimorbidity and polypharmacy: EuGMS SIG on pharmacology position paper

Inappropriate polypharmacy is highly prevalent among older adults and presents a significant healthcare concern. Conducting medication reviews and implementing deprescribing strategies in multimorbid older adults with polypharmacy are an inherently complex and challenging task. Recognizing this, the Special Interest Group on Pharmacology of the European Geriatric Medicine Society has compiled evidence on medication review and deprescribing in older adults and has formulated recommendations to enhance appropriate prescribing practices. The current evidence supports the need for a comprehensive and widespread transformation in education, guidelines, research, advocacy, and policy to improve the management of polypharmacy in older individuals. Furthermore, incorporating deprescribing as a routine aspect of care for the ageing population is crucial. We emphasize the importance of involving geriatricians and experts in geriatric pharmacology in driving, and actively participating in this transformative process. By doing so, we can work towards achieving optimal medication use and enhancing the well-being of older adults in the generations to come.

Individual Treatment Trials—Do Experts Know and Use This Option to Improve the Treatability of Mucopolysaccharidosis?

Mucopolysaccharidoses (MPS) are a group of rare, heterogeneous, lysosomal storage disorders. Patients show a broad spectrum of clinical features with a substantial unmet medical need. Individual treatment trials (ITTs) might be a valid, time- and cost-efficient way to facilitate personalized medicine in the sense of drug repurposing in MPS. However, this treatment option has so far hardly been used—at least hardly been reported or published. Therefore, we aimed to investigate the awareness and utilization of ITTs among MPS clinicians, as well as the potential challenges and innovative approaches to overcome key hurdles, by using an international expert survey on ITTs, namely, ESITT. Although 74% (20/27) were familiar with the concept of ITTs, only 37% (10/27) ever used it, and subsequently only 15% (2/16) published their results. The indicated hurdles of ITTs in MPS were mainly the lack of time and know-how. An evidence-based tool, which provides resources and expertise needed for high-quality ITTs, was highly appreciated by the vast majority (89%; 23/26). The ESITT highlights a serious deficiency of ITT implementation in MPS—a promising option to improve its treatability. Furthermore, we discuss the challenges and innovative approaches to overcome key barriers to ITTs in MPS.

How "age-friendly" are deprescribing interventions? A scoping review of deprescribing trials

OBJECTIVE

To assess how age-friendly deprescribing trials are regarding intervention design and outcome assessment. Reduced use of potentially inappropriate medications (PIMs) can be addressed by deprescribing-a systematic process of discontinuing and/or reducing the use of PIMs. The 4Ms-"Medication", "Mentation", "Mobility", and "What Matters Most" to the person-can be used to guide assessment of age-friendliness of deprescribing trials.

DATA SOURCE

Published literature.

STUDY DESIGN

Scoping review.

DATA EXTRACTION METHODS

The literature was identified using keywords related to deprescribing and polypharmacy in PubMed, EMBASE, Web of Science, ProQuest, CINAHL, and Cochrane and snowballing. Study characteristics were extracted and evaluated for consideration of 4Ms.

PRINCIPAL FINDINGS

Thirty-seven of the 564 trials identified met the review eligibility criteria. Intervention design: "Medication" was considered in the intervention design of all trials; "Mentation" was considered in eight trials; "Mobility" (n = 2) and "What Matters Most" (n = 6) were less often considered in the design of intervention. Most trials targeted providers without specifying how matters important to older adults and their families were aligned with deprescribing decisions.

OUTCOME ASSESSMENT

"Medication" was the most commonly assessed outcome (n = 33), followed by "Mobility" (n = 13) and "Mentation" (n = 10) outcomes, with no study examining "What Matters Most" outcomes.

CONCLUSIONS

"Mentation" and "Mobility", and "What Matters Most" have been considered to varying degrees in deprescribing trials, limiting the potential of deprescribing evidence to contribute to improved clinical practice in building an age-friendly health care system.

N-of-1 trials to facilitate evidence-based deprescribing: Rationale and case study

Deprescribing has emerged as an important aspect of patient-centred medication management but is vastly underutilized in clinical practice. The current narrative review will describe an innovative patient-centred approach to deprescribing-N-of-1 trials. N-of-1 trials involve multiple-period crossover design experiments conducted within individual patients. They enable patients to compare the effects of two or more treatments or, in the case of deprescribing N-of-1 trials, continuation with a current treatment versus no treatment or placebo. N-of-1 trials are distinct from traditional between-patient studies such as parallel-group or crossover designs which provide an average effect across a group of patients and obscure differences between individuals. By generating data on the effect of an intervention for the individual rather than the population, N-of-1 trials can promote therapeutic precision. N-of-1 trials are a particularly appealing strategy to inform deprescribing because they can generate individual-level evidence for deprescribing when evidence is uncertain, and can thus allay patient and physician concerns about discontinuing medications. To illustrate the use of deprescribing N-of-1 trials, we share a case example of an ongoing series of N-of-1 trials that compare maintenance versus deprescribing of beta-blockers in patients with heart failure with preserved ejection fraction. By providing quantifiable data on patient-reported outcomes, promoting personalized pharmacotherapy, and facilitating shared decision making, N-of-1 trials represent a potentially transformative strategy to address polypharmacy.

Status of N-of-1 Trials in Chronic Pain Management: A Narrative Review

N-of-1 trials are randomized controlled clinical trials conducted exclusively on a single patient. The ultimate aim of N-of-1 trials is to optimize a strategy in a particular individual. Chronic pain is a common but refractory clinical problem. Its diverse etiologies and broad variations among patients often lead to the requirement of individualizing medicine. Thus, chronic pain represents a classical condition for N-of-1 clinical trials. Studies have indicated that N-of-1 benefits patients with chronic pain, multiple comorbidities, and uncertain variations during therapies; however, this approach it is not yet adopted as the first choice in pain clinics. To dissect the current status of N-of-1 in chronic pain management, as well as the limitations for its implementation, we herein studied all N-of-1 studies related to chronic pain by searching three major databases (PubMed, ClinicalTrial.gov, Cochrane Library) for publications between 1985 and 2020. Of 35 eligibility papers, 19 were selected for analysis. Results confirmed that N-of-1 trials have solved the refractory cases including osteoarthritis, chronic musculoskeletal pain, and neuropathic pain; however, none of the trials dealt with cancer pain. Longer time and more efforts are needed from investigators when carrying out N-of-1 trials, which inevitably result in implementation difficulties. Of note, all recruited trials were conducted in developed countries. As mobile devices have been introduced and protocols improve, renewed interest in the implementation of N-of-1 trials will occur. Collectively, a previously underestimated conflict between "precision medicine" and "poor implementation" has put N-of-1 in a challenging position for chronic pain management.

Patient-Reported Barriers and Facilitators to Deprescribing Cardiovascular Medications

BACKGROUND

Medications endorsed by clinical practice guidelines, such as cardiovascular medications, could still have risks that outweigh potential benefits, and could thus warrant deprescribing.

OBJECTIVES

The objective of this study was to develop a framework of facilitators and barriers specific to deprescribing cardiovascular medications in the setting of uncertain benefit. Given the frequent use of β-blockers in heart failure with preserved ejection fraction, and its uncertain benefits with potential for harm, we used this scenario as an example case for a cardiovascular medication that may be reasonable to deprescribe.

METHODS

We conducted one-on-one, semi-structured interviews of older adults until we reached thematic saturation. Two coders independently reviewed each interview, and developed codes using deductive thematic analysis based on a prior conceptual framework for deprescribing. Subthemes and themes were finalized with a third coder.

RESULTS

Ten participants were interviewed. We identified three key previously described patient-reported facilitators to deprescribing: (1) appropriateness of cessation; (2) process of cessation; and (3) dislike of medications; and identified three key previously described patient-reported barriers: (1) appropriateness of cessation; (2) process of cessation; and (3) fear. We found that these facilitators and barriers often co-occurred within the same individual. This observation, coupled with subthemes from our patient interviews, yielded two barriers to deprescribing specific to cardiovascular medications-uncertainty and conflicting attitudes.

CONCLUSION

We adapted a new framework of patient-reported barriers and facilitators specific to deprescribing cardiovascular medications. In addition to addressing barriers previously described, future deprescribing interventions targeting cardiovascular medications must also address uncertainty and conflicting attitudes.

Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal.

Practice-Based Research in Complementary Medicine: Could N-of-1 Trials Become the New Gold Standard?

Complementary medicines and therapies are popular forms of healthcare with a long history of traditional use. Yet, despite increasing consumer demand, there is an ongoing exclusion of complementary medicines from mainstream healthcare systems. A lack of evidence is often cited as justification. Until recently, high-quality evidence of treatment efficacy was defined as findings from well-conducted systematic reviews and meta-analyses of randomized controlled trials. In a recent and welcome move by the Oxford Centre for Evidence-Based Practice, however, the N-of-1 trial design has also been elevated to the highest level of evidence for treatment efficacy of an individual, placing this research design on par with the meta-analysis. N-of-1 trial designs are experimental research methods that can be implemented in clinical practice. They incorporate much of the rigor of group clinical trials, but are designed for individual patients. Individualizing treatment interventions and outcomes in research designs is consistent with the movement towards patient-centered care and aligns well with the principles of holism as practiced by naturopaths and many other complementary medicine practitioners. This paper explores whether rigorously designed and conducted N-of-1 trials could become a new ‘gold standard’ for demonstrating treatment efficacy for complementary medicine interventions in individual patients in clinical practice.

The Feasibility of Using N-Of-1 Trials to Investigate Deprescribing in Older Adults with Dementia: A Pilot Study

N-of-1 trials may provide insights into the impact of deprescribing medications in populations where evidence is currently lacking, such as the effect of statins on cognition in people with dementia. For this pilot, N-of-1, double-blinded, deprescribing trial, adults over 80 years of age with dementia taking statins for at least 6-months were recruited from a hospital’s geriatric medicine outpatient clinic in Sydney, Australia. Participants discontinued and restarted statins over the study period. At enrolment, the hospital pharmacy—using a random number generator, randomised recruited participants to their usual statin or placebo regimen, with assessment and switching of treatment every 5 weeks from baseline (0-weeks) until Visit 4 (15-weeks). Primary outcome was measured using the rate of change in Alzheimer’s Disease Assessment Score-Cognitive Subscale (ADAS-CoG). Over 6-months, 81 participants were screened, 14 were eligible, and four were randomised. One participant (female, 88 years) completed all four assessments with no major harms reported. Cognitive impairment, as measured by ADAS-CoG score, was similar on placebo (15.5/70) compared to statin (15/70). This study suggests there are significant challenges in performing N-of-1 trials and recruiting people with dementia into deprescribing trials from outpatient settings.

Comparison of Aggregated N-of-1 Trials with Parallel and Crossover Randomized Controlled Trials Using Simulation Studies

Background: N-of-1 trials offer an innovative approach to delivering personalized clinical care together with population-level research. While increasingly used, these methods have raised some statistical concerns in the healthcare community. Methods: We discuss concerns of selection bias, carryover effects from treatment, and trial data analysis conceptually, then rigorously evaluate concerns of effect sizes, power and sample size through simulation study. Four variance structures for patient heterogeneity and model error are considered in a series of 5000 simulated trials with 3 cycles, which compare aggregated N-of-1 trials to parallel randomized controlled trials (RCTs) and crossover trials. Results: Aggregated N-of-1 trials outperformed both traditional parallel RCT and crossover designs when these trial designs were simulated in terms of power and required sample size to obtain a given power. N-of-1 designs resulted in a higher type-I error probability than parallel RCT and cross over designs when moderate-to-strong carryover effects were not considered or in the presence of modeled selection bias. However, N-of-1 designs allowed better estimation of patient-level random effects. These results reinforce the need to account for these factors when planning N-of-1 trials. Conclusion: N-of-1 trial designs offer a rigorous method for advancing personalized medicine and healthcare with the potential to minimize costs and resources. Interventions can be tested with adequate power with far fewer patients than traditional RCT and crossover designs. Operating characteristics compare favorably to both traditional RCT and crossover designs.

Health professionals' and researchers' opinions on conducting clinical deprescribing trials

While clinical deprescribing trials are increasingly being performed, there is no guidance on the optimum conduction of such studies. The aim of this survey was to explore the perspectives, attitudes, interests, barriers, and enablers of conducting clinical deprescribing trials among health professionals and researchers. An anonymous survey was developed, reviewed, and piloted by all investigators and informed by consultation with experts, as well as current deprescribing guidelines. The questions were formulated around current clinical trial frameworks and incorporated identified enablers and barriers of performing deprescribing studies. The survey was sent to members of Australian and international deprescribing, pharmacological, and pharmacy organizations, and other researchers published in deprescribing. A total of 96 respondents completed the survey (92.3% completion rate). Respondents indicated the main deprescribing trial rationale is to generate evidence to optimize patient-centered outcomes (79.2%). Common barriers identified included the time and effort required (18.2%), and apprehension of health professionals involved in trials (17.1%). Studies are enabled by positive attitudes toward deprescribing of treating prescribers (24.4%) and patients (20.9%). Classical randomized controlled trials (RCTs) were deemed the most appropriate methodology (93.2%). Sixty percent of participants indicated a good clinical practice framework is required to guide the conduct of deprescribing trials. There were no significant differences in responses based on previous experience in conducting clinical deprescribing trials. In conclusion, clinical deprescribing trials should be conducted to investigate whether deprescribing medications improves patient care. A future deprescribing trial framework should use classical RCTs as a model, ensure participant safety, and target patient-centered outcomes.

Individualized metabolomics: opportunities and challenges

The goal of advancing science in health care is to provide high quality treatment and therapeutic opportunities to patients in need. This is especially true in precision medicine, wherein the ultimate goal is to link disease phenotypes to targeted treatments and novel therapeutics at the scale of an individual. With the advent of -omics technologies, such as genomics, proteomics, microbiome, among others, the metabolome is of wider and immediate interest for its important role in metabolic regulation. The metabolome, of course, comes with its own questions regarding technological challenges. In this opinion article, I attempt to interrogate some of the main challenges associated with individualized metabolomics, and available opportunities in the context of its clinical application. Some questions this article addresses and attempts to find answers for are: Can a personal metabolome (n = 1) be inexpensive, affordable and informative enough (i.e. provide predictive yet validated biomarkers) to represent the entirety of a population? How can a personal metabolome complement advances in other -omics areas and the use of monitoring devices, which occupy our personal space?

Advancing personalized treatment of Alzheimer's disease: a call for the N-of-1 trial design

There has not been a new treatment for Alzheimer's disease (AD) for over a decade, with a large number of Phase II/III randomized clinical trials failing. Randomized clinical trials examine group effects that may be difficult to extrapolate to the individual patient given the multifactorial pathogenic processes associated with AD, and are increasingly long in duration, expensive to run, requiring large sample sizes that are difficult to recruit. An alternative approach is to consider N-of-1 trial designs. The N-of-1 trial is ideal to evaluate effectiveness of interventions for chronic conditions combining the rigor of a randomized trial with the tailoring of therapy to an individual. This review examines the N-of-1 design, its benefits and limitations, and how it could be implemented to investigate new therapies for AD.