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

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.

The Potential of Integrative Cancer Treatment Using Melatonin and the Challenge of Heterogeneity in Population-Based Studies: A Case Report of Colon Cancer and a Literature Review

Melatonin is a multifunctional hormone regulator that maintains homeostasis through circadian rhythms, and desynchronization of these rhythms can lead to gastrointestinal disorders and increase the risk of cancer. Preliminary clinical studies have shown that exogenous melatonin alleviates the harmful effects of anticancer therapy and improves quality of life, but the results are still inconclusive due to the heterogeneity of the studies. A personalized approach to testing clinical parameters and response to integrative treatment with nontoxic and bioavailable melatonin in patient-centered N-of-1 studies deserves greater attention. This clinical case of colon cancer analyzes and discusses the tumor pathology, the adverse effects of chemotherapy, and the dynamics of markers of inflammation (NLR, LMR, and PLR ratios), tumors (CEA, CA 19-9, and PSA), and hemostasis (D-dimer and activated partial thromboplastin time). The patient took melatonin during and after chemotherapy, nutrients (zinc, selenium, vitamin D, green tea, and taxifolin), and aspirin after chemotherapy. The patient's PSA levels decreased during CT combined with melatonin (19 mg/day), and melatonin normalized inflammatory markers and alleviated symptoms of polyneuropathy but did not help with thrombocytopenia. The results are analyzed and discussed in the context of the literature on oncostatic and systemic effects, alleviating therapy-mediated adverse effects, association with survival, and N-of-1 studies.

SECRETS: Subject-efficient clinical randomized controlled trials using synthetic intervention

Background

The parallel-group randomized controlled trial (RCT) is commonly used in Phase-3 clinical trials to establish treatment effectiveness but requires hundreds-to-thousands of subjects, making it difficult to implement, which leads to high Phase-3 trial failure rates. One approach to increasing power of a trial is to augment data collected from an RCT with external data from prospective studies or prior RCTs. However, this requires that external data be comparable to data from the study of interest, a condition that does not hold for new interventions or populations being studied. Another approach is to lower sample size requirements by using the cross-over design, which measures individual treatment effects (ITEs) to remove inter-subject variability; however, this design is only suitable for chronic conditions and interventions with effects that wash out rapidly.

Method

We propose a novel and practical framework called SECRETS (Subject-Efficient Clinical Randomized Controlled Trials using Synthetic Intervention) to increase power of any parallel-group RCT by simulating the cross-over design using only data collected from the study. SECRETS first estimates ITEs across all subjects recruited to the RCT by using a state-of-the-art counterfactual estimation algorithm called synthetic intervention (SI). Since SI induces dependencies among the ITEs, we introduce a novel hypothesis testing strategy to test for treatment effectiveness.

Results

We show that SECRETS can increase the power of an RCT while maintaining comparable significance levels; in particular, on three real-world clinical RCTs (Phase-3 trials), SECRETS increases power over the baseline method by 6 - 54 % (average: 21.5%, standard deviation: 15.8%), thereby reducing the number of subjects needed to obtain a typically desired statistical operating point of 80% power and 5% significance level by 25 - 76 % (10-3,957 fewer subjects per arm). Our analyses show that SECRETS increases power by consistently reducing the variance of the average treatment effect, thereby mimicking the effects of a cross-over design.

Conclusion

SECRETS increases subject efficiency of an RCT by simulating the cross-over design using only data collected from the RCT; therefore, it is a feasible solution for increasing the trial's power, especially under settings where satisfying sample size requirements is difficult.

ABkPowerCalculator: An App to Compute Power for Balanced (AB)k Single Case Experimental Designs

Single case experimental designs are an important research design in behavioral and medical research. Although there are design standards prescribed by the What Works Clearinghouse for single case experimental designs, these standards do not include statistically derived power computations. Recently we derived the equations for computing power for (AB)k designs. However, these computations and the software code in R may not be accessible to applied researchers who are most likely to want to compute power for their studies. Therefore, we have developed an (AB)k power calculator Shiny App (https://abkpowercalculator.shinyapps.io/ABkpowercalculator/) that researchers can use with no software training. These power computations assume that the researcher would be interested in fitting multilevel models with autocorrelations or conduct similar analyses. The purpose of this software contribution is to briefly explain how power is derived for balanced (AB)k designs and to elaborate on how to use the Shiny App. The app works well on not just computers but mobile phones without installing the R program. We believe this can be a valuable tool for practitioners and applied researchers who want to plan their single case studies with sufficient power to detect appropriate effect sizes.

Clinical Trial-Ready Patient Cohorts for Multiple System Atrophy: Coupling Biospecimen and iPSC Banking to Longitudinal Deep-Phenotyping

Multiple system atrophy (MSA) is a fatal neurodegenerative disease of unknown etiology characterized by widespread aggregation of the protein alpha-synuclein in neurons and glia. Its orphan status, biological relationship to Parkinson's disease (PD), and rapid progression have sparked interest in drug development. One significant obstacle to therapeutics is disease heterogeneity. Here, we share our process of developing a clinical trial-ready cohort of MSA patients (69 patients in 2 years) within an outpatient clinical setting, and recruiting 20 of these patients into a longitudinal "n-of-few" clinical trial paradigm. First, we deeply phenotype our patients with clinical scales (UMSARS, BARS, MoCA, NMSS, and UPSIT) and tests designed to establish early differential diagnosis (including volumetric MRI, FDG-PET, MIBG scan, polysomnography, genetic testing, autonomic function tests, skin biopsy) or disease activity (PBR06-TSPO). Second, we longitudinally collect biospecimens (blood, CSF, stool) and clinical, biometric, and imaging data to generate antecedent disease-progression scores. Third, in our Mass General Brigham SCiN study (stem cells in neurodegeneration), we generate induced pluripotent stem cell (iPSC) models from our patients, matched to biospecimens, including postmortem brain. We present 38 iPSC lines derived from MSA patients and relevant disease controls (spinocerebellar ataxia and PD, including alpha-synuclein triplication cases), 22 matched to whole-genome sequenced postmortem brain. iPSC models may facilitate matching patients to appropriate therapies, particularly in heterogeneous diseases for which patient-specific biology may elude animal models. We anticipate that deeply phenotyped and genotyped patient cohorts matched to cellular models will increase the likelihood of success in clinical trials for MSA.

Cannabidiol (Epidyolex®) for severe behavioral manifestations in patients with tuberous sclerosis complex, mucopolysaccharidosis type III and fragile X syndrome: protocol for a series of randomized, placebo-controlled N-of-1 trials

BACKGROUND

Many rare genetic neurodevelopmental disorders (RGNDs) are characterized by intellectual disability (ID), severe cognitive and behavioral impairments, potentially diagnosed as a comorbid autism spectrum disorder or attention-deficit hyperactivity disorder. Quality of life is often impaired due to irritability, aggression and self-injurious behavior, generally refractory to standard therapies. There are indications from previous (case) studies and patient reporting that cannabidiol (CBD) may be an effective treatment for severe behavioral manifestations in RGNDs. However, clear evidence is lacking and interventional research is challenging due to the rarity as well as the heterogeneity within and between disease groups and interindividual differences in treatment response. Our objective is to examine the effectiveness of CBD on severe behavioral manifestations in three RGNDs, including Tuberous Sclerosis Complex (TSC), mucopolysaccharidosis type III (MPS III), and Fragile X syndrome (FXS), using an innovative trial design.

METHODS

We aim to conduct placebo-controlled, double-blind, block-randomized, multiple crossover N-of-1 studies with oral CBD (twice daily) in 30 patients (aged ≥ 6 years) with confirmed TSC, MPS III or FXS and severe behavioral manifestations. The treatment is oral CBD up to a maximum of 25 mg/kg/day, twice daily. The primary outcome measure is the subscale irritability of the Aberrant Behavior Checklist. Secondary outcome measures include (personalized) patient-reported outcome measures with regard to behavioral and psychiatric outcomes, disease-specific outcome measures, parental stress, seizure frequency, and adverse effects of CBD. Questionnaires will be completed and study medication will be taken at the participants' natural setting. Individual treatment effects will be determined based on summary statistics. A mixed model analysis will be applied for analyzing the effectiveness of the intervention per disorder and across disorders combining data from the individual N-of-1 trials.

DISCUSSION

These N-of-1 trials address an unmet medical need and will provide information on the effectiveness of CBD for severe behavioral manifestations in RGNDs, potentially generating generalizable knowledge at an individual-, disorder- and RGND population level.

TRIAL REGISTRATION

EudraCT: 2021-003250-23, registered 25 August 2022, https://www.clinicaltrialsregister.eu/ctr-search/trial/2021-003250-23/NL .

Power analysis for idiographic (within-subject) clinical trials: Implications for treatments of rare conditions and precision medicine

Power analysis informs a priori planning of behavioral and medical research, including for randomized clinical trials that are nomothetic (i.e., studies designed to infer results to the general population based on interindividual variabilities). Far fewer investigations and resources are available for power analysis of clinical trials that follow an idiographic approach, which emphasizes intraindividual variabilities between baseline (control) phase versus one or more treatment phases. We tested the impact on statistical power to detect treatment outcomes of four idiographic trial design factors that are under researchers' control, assuming a multiple baseline design: sample size, number of observations per participant, proportion of observations in the baseline phase, and competing statistical models (i.e., hierarchical modeling versus piecewise regression). We also tested the impact of four factors that are largely outside of researchers' control: population size, proportion of intraindividual variability due to residual error, treatment effect size, and form of outcomes during the treatment phase (phase jump versus gradual change). Monte Carlo simulations using all combinations of the factors were sampled with replacement from finite populations of 200, 1750, and 3500 participants. Analyses characterized the unique relative impact of each factor individually and all two-factor combinations, holding all others constant. Each factor impacted power, with the greatest impact being from larger treatment effect sizes, followed respectively by more observations per participant, larger samples, less residual variance, and the unexpected improvement in power associated with assigning closer to 50% of observations to the baseline phase. This study's techniques and R package better enable a priori rigorous design of idiographic clinical trials for rare diseases, precision medicine, and other small-sample studies.

Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects

BACKGROUND

The aggregation of a series of N-of-1 trials presents an innovative and efficient study design, as an alternative to traditional randomized clinical trials. Challenges for the statistical analysis arise when there is carry-over or complex dependencies of the treatment effect of interest.

METHODS

In this study, we evaluate and compare methods for the analysis of aggregated N-of-1 trials in different scenarios with carry-over and complex dependencies of treatment effects on covariates. For this, we simulate data of a series of N-of-1 trials for Chronic Nonspecific Low Back Pain based on assumed causal relationships parameterized by directed acyclic graphs. In addition to existing statistical methods such as regression models, Bayesian Networks, and G-estimation, we introduce a carry-over adjusted parametric model (COAPM).

RESULTS

The results show that all evaluated existing models have a good performance when there is no carry-over and no treatment dependence. When there is carry-over, COAPM yields unbiased and more efficient estimates while all other methods show some bias in the estimation. When there is known treatment dependence, all approaches that are capable to model it yield unbiased estimates. Finally, the efficiency of all methods decreases slightly when there are missing values, and the bias in the estimates can also increase.

CONCLUSIONS

This study presents a systematic evaluation of existing and novel approaches for the statistical analysis of a series of N-of-1 trials. We derive practical recommendations which methods may be best in which scenarios.

A Smartphone Intervention to Promote a Sustainable Healthy Diet: Protocol for a Pilot Study

BACKGROUND

Changing current dietary patterns into sustainable healthy diets (ie, healthy diets with low environmental impact and socioeconomic fairness) is urgent. So far, few eating behavior change interventions have addressed all the dimensions of sustainable healthy diets at once and used cutting-edge methods from the field of digital health behavior change.

OBJECTIVE

The primary objectives of this pilot study were to assess the feasibility and effectiveness of an individual behavior change intervention toward the adoption of a more environmentally sustainable healthy diet as a whole and changes in specific relevant food groups, food waste, and obtaining food from fair sources. The secondary objectives included the identification of mechanisms of action that potentially mediate the effect of the intervention on behaviors, identification of potential spillover effects and covariations among different food outcomes, and identification of the role of socioeconomic status in behavior changes.

METHODS

We will run a series of ABA n-of-1 trials over a year, with the first A phase corresponding to a 2-week baseline evaluation, the B phase to a 22-week intervention, and the second A phase to a 24-week postintervention follow-up. We plan to enroll 21 participants from low, middle, and high socioeconomic statuses, with 7 from each socioeconomic group. The intervention will involve sending text messages and providing brief individualized web-based feedback sessions based on regular app-based assessments of eating behavior. The text messages will contain brief educational messages on human health and the environmental and socioeconomic effects of dietary choices; motivational messages to encourage the adoption of sustainable healthy diets by participants, providing tips to achieve their own behavioral goals; or links to recipes. Both quantitative and qualitative data will be collected. Quantitative data (eg, on eating behaviors and motivation) will be collected through self-reported questionnaires on several weekly bursts spread through the study. Qualitative data will be collected through 3 individual semistructured interviews before the intervention period, at the end of the intervention period, and at the end of the study. Analyses will be performed at both the individual and group levels depending on the outcome and objective.

RESULTS

The first participants were recruited in October 2022. The final results are expected by October 2023.

CONCLUSIONS

The results of this pilot study will be useful for designing future larger interventions on individual behavior change for sustainable healthy diets.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/41443.

Promoting Daily Well-being in Adolescents using mHealth

Adolescents are at increased risk for developing mental health problems. The Grow It! app is an mHealth intervention aimed at preventing mental health problems through improving coping by cognitive behavioral therapy (CBT)-inspired challenges as well as self-monitoring of emotions through Experience Sampling Methods (ESM). Yet, little is known about daily changes in well-being and coping during a stressful period, like the COVID-19 pandemic. The current study aimed to elucidate daily changes in positive and negative affect, and adaptive coping, and to better understand the within-person's mechanisms of the Grow It! app. The sample consisted of 12-25-year old Dutch adolescents in two independent cohorts (cohort 1: N = 476, Mage = 16.24, 76.1% female, 88.7% Dutch; cohort 2: N = 814, Mage = 18.45, 82.8% female, 97.2% Dutch). ESM were used to measure daily positive and negative affect and coping (cohort 1: 42 days, 210 assessments per person; cohort 2: 21 days, 105 assessments). The results showed that, on average, adolescents decreased in daily positive affect and adaptive coping, and increased in their experienced negative affect. A positive relation between adaptive coping and positive affect was found, although independent of the CBT-based challenges. Latent class analysis identified two heterogeneous trajectories for both positive and negative affect, indicating that the majority of participants with low to moderate-risk on developing mental health problems were likely to benefit from the Grow It! app.

Can we Reconcile Evidence-based Medicine with Personalized Medicine: Poised on a Cusp!

How to cite this article: Kulkarni AP, Mishra RC. Can we Reconcile Evidence-based Medicine with Personalized Medicine: Poised on a Cusp! Indian J Crit Care Med 2022;26(S2):S1-S2.

Multiple N-of-1 trials to investigate hypoxia therapy in Parkinson's disease: study rationale and protocol

Background

Parkinson’s disease (PD) is a neurodegenerative disease, for which no disease-modifying therapies exist. Preclinical and clinical evidence suggest that hypoxia-based therapy might have short- and long-term benefits in PD. We present the contours of the first study to assess the safety, feasibility and physiological and symptomatic impact of hypoxia-based therapy in individuals with PD.

Methods/Design

In 20 individuals with PD, we will investigate the safety, tolerability and short-term symptomatic efficacy of continuous and intermittent hypoxia using individual, double-blind, randomized placebo-controlled N-of-1 trials. This design allows for dose finding and for including more individualized outcomes, as each individual serves as its own control. A wide range of exploratory outcomes is deployed, including the Movement Disorders Society Unified Parkinson’s Disease Rating scale (MDS-UPDRS) part III, Timed Up & Go Test, Mini Balance Evaluation Systems (MiniBES) test and wrist accelerometry. Also, self-reported impression of overall symptoms, motor and non-motor symptoms and urge to take dopaminergic medication will be assessed on a 10-point Likert scale. As part of a hypothesis-generating part of the study, we also deploy several exploratory outcomes to probe possible underlying mechanisms of action, including cortisol, erythropoietin and platelet-derived growth factor β. Efficacy will be assessed primarily by a Bayesian analysis.

Discussion

This evaluation of hypoxia therapy could provide insight in novel pathways that may be pursued for PD treatment. This trial also serves as a proof of concept for deploying an N-of-1 design and for including individualized outcomes in PD research, as a basis for personalized treatment approaches.

Trial registration

ClinicalTrials.gov Identifier: NCT05214287 (registered January 28, 2022).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02770-7.

StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials

N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.

Genetically-Guided Medical Nutrition Therapy in Type 2 Diabetes Mellitus and Pre-diabetes: A Series of n-of-1 Superiority Trials

Type 2 diabetes mellitus (T2DM) is a heterogeneous metabolic disorder of multifactorial etiology that includes genetic and dietary influences. By addressing the latter, medical nutrition therapy (MNT) contributes to the management of T2DM or pre-diabetes toward achieving glycaemic control and improved insulin sensitivity. However, the clinical outcomes of MNT vary and may further benefit from personalized nutritional plans that take into consideration genetic variations associated with individual responses to macronutrients. The aim of the present series of n-of-1 trials was to assess the effects of genetically-guided vs. conventional MNT on patients with pre-diabetes or T2DM. A quasi-experimental, cross-over design was adopted in three Caucasian adult men with either diagnosis. Complete diet, bioclinical and anthropometric assessment was performed and a conventional MNT, based on the clinical practice guidelines was applied for 8 weeks. After a week of “wash-out,” a precision MNT was prescribed for an additional 8-week period, based on the genetic characteristics of each patient. Outcomes of interest included changes in body weight (BW), fasting plasma glucose (FPG), and blood pressure (BP). Collectively, the trials indicated improvements in BW, FPG, BP, and glycosylated hemoglobin (HbA1c) following the genetically-guided precision MNT intervention. Moreover, both patients with pre-diabetes experienced remission of the condition. We conclude that improved BW loss and glycemic control can be achieved in patients with pre-diabetes/T2DM, by coupling MNT to their genetic makeup, guiding optimal diet, macronutrient composition, exercise and oral nutrient supplementation in a personalized manner.

Epilepsy in the mTORopathies: opportunities for precision medicine

The mechanistic target of rapamycin signalling pathway serves as a ubiquitous regulator of cell metabolism, growth, proliferation and survival. The main cellular activity of the mechanistic target of rapamycin cascade funnels through mechanistic target of rapamycin complex 1, which is inhibited by rapamycin, a macrolide compound produced by the bacterium Streptomyces hygroscopicus. Pathogenic variants in genes encoding upstream regulators of mechanistic target of rapamycin complex 1 cause epilepsies and neurodevelopmental disorders. Tuberous sclerosis complex is a multisystem disorder caused by mutations in mechanistic target of rapamycin regulators TSC1 or TSC2, with prominent neurological manifestations including epilepsy, focal cortical dysplasia and neuropsychiatric disorders. Focal cortical dysplasia type II results from somatic brain mutations in mechanistic target of rapamycin pathway activators MTOR, AKT3, PIK3CA and RHEB and is a major cause of drug-resistant epilepsy. DEPDC5, NPRL2 and NPRL3 code for subunits of the GTPase-activating protein (GAP) activity towards Rags 1 complex (GATOR1), the principal amino acid-sensing regulator of mechanistic target of rapamycin complex 1. Germline pathogenic variants in GATOR1 genes cause non-lesional focal epilepsies and epilepsies associated with malformations of cortical development. Collectively, the mTORopathies are characterized by excessive mechanistic target of rapamycin pathway activation and drug-resistant epilepsy. In the first large-scale precision medicine trial in a genetically mediated epilepsy, everolimus (a synthetic analogue of rapamycin) was effective at reducing seizure frequency in people with tuberous sclerosis complex. Rapamycin reduced seizures in rodent models of DEPDC5-related epilepsy and focal cortical dysplasia type II. This review outlines a personalized medicine approach to the management of epilepsies in the mTORopathies. We advocate for early diagnostic sequencing of mechanistic target of rapamycin pathway genes in drug-resistant epilepsy, as identification of a pathogenic variant may point to an occult dysplasia in apparently non-lesional epilepsy or may uncover important prognostic information including, an increased risk of sudden unexpected death in epilepsy in the GATORopathies or favourable epilepsy surgery outcomes in focal cortical dysplasia type II due to somatic brain mutations. Lastly, we discuss the potential therapeutic application of mechanistic target of rapamycin inhibitors for drug-resistant seizures in GATOR1-related epilepsies and focal cortical dysplasia type II.

Individualized therapy trials: navigating patient care, research goals and ethics

'Individualized therapy' trials (sometimes called n-of-1 trials) use patients as their own controls to evaluate treatments. Here we divide such trials into three categories: multi-crossover trials aimed at individual patient management, multi-crossover trial series and pre-post trials. These trials all customize interventions for patients; however, the latter two categories also aim to inform medical practice and thus embody tensions between the goals of care and research that are typical of other types of clinical trials. In this Perspective, we discuss four domains where such tensions play out-clinical equipoise, informed consent, reporting and funding, and we provide recommendations for addressing each.

N-of-1 Clinical Trials: A Scientific Approach to Personalized Medicine for Patients with Rare Retinal Diseases Such as Retinitis Pigmentosa

N-of-1 trials are randomized, prospective, controlled, multiple crossover trials in a single patient. Effects of one or more treatments are studied by following individual patients who receive alternative treatments (eg, therapeutic intervention). Such trials may provide a path to assess treatments for rare diseases with rigor equal to or greater than that afforded by parallel group randomized clinical trials provided that the condition is reasonably stable during the trial and has a sign/symptom that responds reversibly to the therapy and that can be measured repeatedly. In this article, the authors propose that N-of-1 trials may improve the feasibility and affordability of clinical trials for patients with rare inherited retinal diseases.

Establishment of an International Collaborative Network for N-of-1 Trials and Single-Case Designs

In this article we briefly examine the unique features of Single-Case Designs (SCDs) (studies in a single participant), their history and current trends, and real-world clinical applications. The International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN) is a formal collaborative network for individuals with an interest in SCDs. The ICN was established in 2017 to support the SCD scientific community and provide opportunities for collaboration, a global communication channel, resource sharing and knowledge exchange. In May 2021, there were more than 420 members in 31 countries. A member survey was undertaken in 2019 to identify priorities for the ICN for the following few years. This article outlines the key priorities identified and the ICN's progress to date in these key areas including network activities (developing a communications strategy to increase awareness, collecting/sharing a comprehensive set of resources, guidelines and tips, and incorporating the consumer perspective) and scientific activities (writing position papers and guest editing special journal issues, exploring key stakeholder perspectives about SCDs, and working to streamline ethical approval processes for SCDs). The ICN provides a practical means to engage with this methodology through membership. We encourage clinicians, researchers, industry, and healthcare consumers to learn more about and conduct SCDs, and to join us in our mission of using SCDs to improve health outcomes for individuals and populations.

Innovative methods for observing and changing complex health behaviors: four propositions

Precision health initiatives aim to progressively move from traditional, group-level approaches to health diagnostics and treatments toward ones that are individualized, contextualized, and timely. This article aims to provide an overview of key methods and approaches that can help facilitate this transition in the health behavior change domain. This article is a narrative review of the methods used to observe and change complex health behaviors. On the basis of the available literature, we argue that health behavior change researchers should progressively transition from (i) low- to high-resolution behavioral assessments, (ii) group-only to group- and individual-level statistical inference, (iii) narrative theoretical models to dynamic computational models, and (iv) static to adaptive and continuous tuning interventions. Rather than providing an exhaustive and technical presentation of each method and approach, this article articulates why and how researchers interested in health behavior change can apply these innovative methods. Practical examples contributing to these efforts are presented. If successfully adopted and implemented, the four propositions in this article have the potential to greatly improve our public health and behavior change practices in the near future.

Exploring Symptom Fluctuations and Triggers in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Novel Patient-Centred N-of-1 Observational Designs: A Protocol for a Feasibility and Acceptability Study

BACKGROUND

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic condition of unknown aetiology associated with a range of disabling symptoms, including post-exertional malaise, chronic fatigue, musculoskeletal pain, orthostatic intolerance, unrefreshing sleep, and cognitive dysfunction. ME/CFS is a heterogeneous disorder, with significant variation in symptom type and severity between individuals, as well as within individuals over time. The diversity of ME/CFS symptom presentation makes management challenging; treatments supported by data from randomised controlled trials may not work for all individuals due to the variability in experienced symptoms. Studies using quantitative N-of-1 observational designs involve repeated outcome measurements in an individual over time and can generate rigorous individual-specific conclusions about symptom patterns and triggers in individuals with ME/CFS. This study aims to explore the feasibility and acceptability of using novel patient-centred N-of-1 observational designs to explore symptom fluctuations and triggers in ME/CFS at the individual level.

METHODS AND ANALYSIS

Individuals with a medical diagnosis of ME/CFS will be recruited through ME/CFS patient organisations to participate in a series of patient-centred N-of-1 observational studies. Using a wrist-worn electronic diary, participants will complete ecological momentary assessments of fatigue, stress, mood, and cognitive demand, three times per day for a period of 6-12 weeks. Personally relevant symptoms and triggers will also be incorporated into the questionnaire design. Physical activity will be objectively measured via an integrated accelerometer. Feasibility and acceptability outcomes will be assessed including the percentage of diary entries completed, as well as recruitment and retention rate, feasibility of analysing and interpreting the data collected, and participant views about participation elicited via a post-study semi-structured interview.

DISCUSSION

This study will assess the feasibility and acceptability of patient-centred N-of-1 observational studies to assess diseases with complex presentations such as ME/CFS, as well as provide individual-level evidence about fluctuations and triggers of ME/CFS symptoms that may aid self-management.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry: ACTRN12618001898246. Registered on 22 November 2018.

Systematic Review of N-of-1 Studies in Rare Genetic Neurodevelopmental Disorders: The Power of 1

OBJECTIVE

To improve the use of N-of-1 studies in rare genetic neurodevelopmental disorders, we systematically reviewed the literature and formulated recommendations for future studies.

METHODS

The systematic review protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews (CRD42020154720). EMBASE and MEDLINE were searched for relevant studies. Information was recorded on types of interventions, outcome measures, validity, strengths, and limitations using standard reporting guidelines and critical appraisal tools. Qualitative and descriptive analyses were performed.

RESULTS

Twelve studies met the N-of-1 inclusion criteria, including both single trials and series. Interventions were mainly directed to neuropsychiatric manifestations. Main strengths were the use of personalized and clinically relevant outcomes in most studies. Generalizability was compromised due to limited use of validated and generalizable outcome measures.

CONCLUSION

N-of-1 studies are sporadically reported in rare genetic neurodevelopmental disorders. Properly executed N-of-1 studies may provide a powerful alternative to larger randomized controlled trials in rare disorders and a much needed bridge between practice and science. We provide recommendations for future N-of-1 studies in rare genetic neurodevelopmental disorders, ultimately optimizing evidence-based and personalized care.

A Bayesian-bandit adaptive design for N-of-1 clinical trials

N-of-1 trials, which are randomized, double-blinded, controlled, multiperiod, crossover trials on a single subject, have been applied to determine the heterogeneity of the individual's treatment effect in precision medicine settings. An aggregated N-of-1 design, which can estimate the population effect from these individual trials, is a pragmatic alternative when a randomized controlled trial (RCT) is infeasible. We propose a Bayesian adaptive design for both the individual and aggregated N-of-1 trials using a multiarmed bandit framework that is estimated via efficient Markov chain Monte Carlo. A Bayesian hierarchical structure is used to jointly model the individual and population treatment effects. Our proposed adaptive trial design is based on Thompson sampling, which randomly allocates individuals to treatments based on the Bayesian posterior probability of each treatment being optimal. While we use a subject-specific treatment effect and Bayesian posterior probability estimates to determine an individual's treatment allocation, our hierarchical model facilitates these individual estimates to borrow strength from the population estimates via shrinkage to the population mean. We present the design's operating characteristics and performance via a simulation study motivated by a recently completed N-of-1 clinical trial. We demonstrate that from a patient-centered perspective, subjects are likely to benefit from our adaptive design, in particular, for those individuals that deviate from the overall population effect.

Translating CRISPR-Cas Therapeutics: Approaches and Challenges

CRISPR-Cas clinical trials have begun, offering a first glimpse at how DNA and RNA targeting could enable therapies for many genetic and epigenetic human diseases. The speedy progress of CRISPR-Cas from discovery and adoption to clinical use is built on decades of traditional gene therapy research and belies the multiple challenges that could derail the successful translation of these new modalities. Here, we review how CRISPR-Cas therapeutics are translated from technological systems to therapeutic modalities, paying particular attention to the therapeutic cascade from cargo to delivery vector, manufacturing, administration, pipelines, safety, and therapeutic target profiles. We also explore potential solutions to some of the obstacles facing successful CRISPR-Cas translation. We hope to illuminate how CRISPR-Cas is brought from the academic bench toward use in the clinic.

Analysing N-of-1 observational data in health psychology and behavioural medicine: a 10-step SPSS tutorial for beginners

Background: N-of-1 observational studies can be used to describe natural intra-individual changes in health-related behaviours or symptoms over time, to test behavioural theories and to develop highly personalised health interventions. To date, N-of-1 observational methods have been under-used in health psychology and behavioural medicine. One reason for this may be the perceived complexity of statistical analysis of N-of-1 data.

Objective: This tutorial paper describes a 10-step procedure for the analysis of N-of-1 observational data using dynamic regression modelling in SPSS for researchers, students and clinicians who are new to this area. The 10-step procedure is illustrated using real data from an N-of-1 observational study exploring the relationship between pain and physical activity.

Conclusion: The availability of a user-friendly and robust statistical technique for the analysis of N-of-1 data using SPSS may foster increased awareness, knowledge and skills and establish N-of-1 designs as a useful methodological tool in health psychology and behavioural medicine.