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

Theranostic Innovation by Humane N-of-One Cancer Care in Real-World Patients

Patients with relapsed or refractory metastatic cancer unresponsive to standard therapies have motivated nuclear physicians to develop innovative radioligands, precisely targeted to tumor molecular receptors, for effective treatment of specific advanced malignancies. Individual practitioners in departments of nuclear medicine across the world have performed first-in-human studies on compassionate patient usage N-of-One protocols. These physician-sponsored studies then evolved into early-phase clinical trials and obtained real-world data to demonstrate real-world evidence of effectiveness in prolonging survival and enhancing quality of life of many so-called "End-Stage" cancer patients. Virtually all the therapeutic radiopharmaceuticals in current clinical oncology have been discovered and developed into effective specific treatments of targetable cancers by individual doctors in the course of their hospital practice. Pharma industry was not involved until many years later when performance of mandated Phase 3 randomized controlled trials became necessary to achieve regulatory agency approval. This article traces the history of several novel theranostic agents developed from compassionate N-of-One studies by hospital physicians over the past 36 years. It acknowledges the collegiality and collaboration of individual nuclear medicine specialists, worldwide, in pioneering effective humane therapy of particular advanced cancers unresponsive to conventional treatments.

Rise of single-case experimental designs: A historical overview of the necessity of single-case methodology

ABSTRACTWindelband ([1894]1980) advocated that two approaches are used for accumulating scientific knowledge. The first is the idiographic approach that derives knowledge from a single unit, and the second is the nomothetic approach that accumulates knowledge of a group. Given these two approaches, the former matches case studies while the latter is more appropriate with experimental group studies. Scientists have criticized both methodologies for their various limitations. Later, the single-case methodology emerged as an alternative that potentially allays these limitations. In this context, this narrative review aims to describe the historical roots of single-case experimental designs (SCEDs) that have emerged to eliminate the tension of nomothetic and idiographic approaches over time. First, the review focuses on the emergence of SCEDs. Second, the strengths and challenges of SCEDs are reviewed, including those to address the limitations of group experimental and case studies. Third, the use and analyses of SCEDs are outlined, considering their current status. Fourth, this narrative review continues to delineate the dissemination of SCEDs in the modern scientific world. As a result, SCEDs can be evaluated as a method that has the potential to overcome the issues encountered in case description and group experimental research. Thus, that helps accumulate nomothetic and idiographic knowledge in determining evidence-based practices.

Leveraging Single-Case Experimental Designs to Promote Personalized Psychological Treatment: Step-by-Step Implementation Protocol with Stakeholder Involvement of an Outpatient Clinic for Personalized Psychotherapy

Our objective is to implement a single-case experimental design (SCED) infrastructure in combination with experience-sampling methods (ESM) into the standard diagnostic procedure of a German outpatient research and training clinic. Building on the idea of routine outcome monitoring, the SCED infrastructure introduces intensive longitudinal data collection, individual effectiveness measures, and the opportunity for systematic manipulation to push personalization efforts further. It aims to empower psychotherapists and patients to evaluate their own treatment (idiographic perspective) and to enable researchers to analyze open questions of personalized psychotherapy (nomothetic perspective). Organized around the principles of agile research, we plan to develop, implement, and evaluate the SCED infrastructure in six successive studies with continuous stakeholder involvement: In the project development phase, the business model for the SCED infrastructure is developed that describes its vision in consideration of the context (Study 1). Also, the infrastructure's prototype is specified, encompassing the SCED procedure, ESM protocol, and ESM survey (Study 2 and 3). During the optimization phase, feasibility and acceptability are tested and the infrastructure is adapted accordingly (Study 4). The evaluation phase includes a pilot implementation study to assess implementation outcomes (Study 5), followed by actual implementation using a within-institution A-B design (Study 6). The sustainability phase involves continuous monitoring and improvement. We discuss to what extent the generated data could be used to address current questions of personalized psychotherapy research. Anticipated barriers and limitations during the implementation processes are outlined.

The Permutation Distancing Test for dependent single-case observational AB-phase design data: A Monte Carlo simulation study

The Permutation Distancing Test (PDT) is a nonparametric test for evaluating treatment effects in dependent single-case observational design (SCOD) AB-phase data without linear trends. Monte Carlo methods were used to estimate the PDT power and type I error rate, and to compare them to those of the Single-Case Randomization Test (SCRT) assuming a randomly determined intervention point and the traditional permutation test assuming full exchangeability. Data were simulated without linear trends for five treatment effect levels (- 2, - 1, 0, 1, 2), five autocorrelation levels (0, .15, .30, .45, .60), and four observation number levels (30, 60, 90, 120). The power was calculated multiple times for all combinations of factor levels each generating 1000 replications. With 30 observations, the PDT showed sufficient power (≥ 80%) to detect medium treatment effects up to autocorrelation ≤ .45. Using 60 observations, the PDT showed sufficient power to detect medium treatment effects regardless of autocorrelation. With ≥ 90 observations, the PDT could also detect small treatment effects up to autocorrelation ≤ .30. With 30 observations, the type I error rate was 5-7%. With 60 observations and more, the type I error rate was ≤ 5% with autocorrelation < .60. The PDT outperformed the SCRT regarding power, particularly with a small number of observations. The PDT outperformed the traditional permutation test regarding type I error rate control, especially when autocorrelation increased. In conclusion, the PDT is a useful and promising nonparametric test to evaluate treatment effects in dependent SCOD AB-phase data without linear trends.

Characteristics of Missing Data in Single-Case Experimental Designs: An Investigation of Published Data

Single-case experimental designs (SCEDs) have grown in popularity in the fields such as education, psychology, medicine, and rehabilitation. Although SCEDs are valid experimental designs for determining evidence-based practices, they encounter some challenges in analyses of data. One of these challenges, missing data, is likely to be occurred frequently in SCEDs research due to repeated measurements over time. Since missing data is a critical factor that can weaken the validity and generalizability of a study, it is important to determine the characteristics of missing data in SCEDs, which are especially conducted with a small number of participants. In this regard, this study aimed to describe missing data features in SCEDs studies in detail. To accomplish this goal, 465 published SCEDs studies within the recent 5 years in six journals were included in the investigation. The overall results showed that the prevalence of missing data among SCEDs articles in at least one phase, as at least one data point, was approximately 30%. In addition, the results indicated that the missing data rates were above 10% within most studies where missing data occurred. Although missing data is so common in SCEDs research, only a handful of studies (5%) have handled missing data; however, their methods are traditional. In analyzing SCEDs data, several methods are proposed considering missing data ratios in the literature. Therefore, missing data rates determined in this study results can shed light on the analyses of SCEDs data with proper methods by improving the validity and generalizability of study results.

Exploring the contribution of case study research to the evidence base for occupational therapy: a scoping review

BACKGROUND

Case study research is generating interest to evaluate complex interventions. However, it is not clear how this is being utilized by occupational therapists or how feasible it is to contribute to the evidence base. This scoping review explores case study research within occupational therapy in terms of how it is defined, the methodological characteristics adopted, such as data collection and analysis, and the range of practice contexts in which it is applied. We consider the viability of case study research for contributing to our evidence base.

METHODS

Opinion, text and empirical studies within an occupational therapy practice context were included. A three-step extensive search following Joanna Briggs Institute methodology was conducted in June 2020 and updated in July 2021 across ten databases, websites, peer-reviewed and grey literature from 2016 onwards. Study selection was completed by two independent reviewers. A data extraction table was developed and piloted and data charted to align with research questions. Data extraction was completed by one reviewer and a 10% sample cross checked by another.

RESULTS

Eighty-eight studies were included in the review consisting of (n = 84) empirical case study and (n = 4) non-empirical papers. Case study research has been conducted globally, with a range of populations across different settings. The majority were conducted in a community setting (n = 48/84; 57%) with populations experiencing neurodevelopmental disorder (n = 32/84; 38%), stroke (n = 14/84;17%) and non-diagnosis specific (n = 13/84; 15%). Methodologies adopted quantitative (n = 42/84; 50%), mixed methods (n = 22/84; 26%) and qualitative designs (n = 20/84; 24%). However, identifying the methodology and 'case' was a challenge due to methodological inconsistencies.

CONCLUSIONS

Case study research is useful when large-scale inquiry is not appropriate; for cases of complexity, early intervention efficacy, theory testing or when small participant numbers are available. It appears a viable methodology to contribute to the evidence base for occupation and health as it has been used to evaluate interventions across a breadth of occupational therapy practice contexts. Viability could be enhanced through consistent conduct and reporting to allow pooling of case data. A conceptual model and description of case study research in occupational therapy is proposed to support this.

SYSTEMATIC REVIEW REGISTRATION

Open Science Framework 10.17605/OSF.IO/PCFJ6.

Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review

N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.

Personalised and Sustainable IEQ Monitoring: Use of Multi-Modal and Pervasive Technologies

BACKGROUND

Monitoring indoor environmental quality (IEQ) is important to better understand occupant health. Passive IEQ monitoring with digital technologies may provide insightful quantitative data to better inform, e.g., health interventions. Yet, many traditional approaches with known IEQ technologies have limited utility due to high costs or coarse granularity-focusing on the collective rather than individuals. Equally, subjective approaches (e.g., manual surveys) have poor adherence (i.e., are burdensome). There is a need for holistic IEQ measurement techniques that are sustainable (affordable, i.e., low-cost) and personalised. Here, the aim of this case report is to explore the use of low-cost digital approaches to gather personalised quantitative and qualitative data.

METHODS

This study deploys a personalised monitoring approach with IEQ devices coupled to wearables, weather data, and qualitative data, captured through a post-study interview.

RESULTS

The mixed-method, single-case approach gathered data continuously for six months with a reduced burden, by using digital technologies to affirm environmental factors, which were subjectively evaluated by the participant. Quantitative data reinforced qualitative data, removing the need for generalising qualitative findings against a collective.

CONCLUSIONS

This study showed that the single-case, mixed-method approach used here can provide a holistic approach not previously obtainable with traditional pen-and-paper techniques alone. The use of a low-cost multi-modal device linked with common home and wearable technology suggest a contemporary and sustainable IEQ measurement approach that could inform future work to better determine occupant health.

Exploring human biology with N-of-1 clinical trials

Studies on humans that exploit contemporary data-intensive, high-throughput 'omic' assay technologies, such as genomics, transcriptomics, proteomics and metabolomics, have unequivocally revealed that humans differ greatly at the molecular level. These differences, which are compounded by each individual's distinct behavioral and environmental exposures, impact individual responses to health interventions such as diet and drugs. Questions about the best way to tailor health interventions to individuals based on their nuanced genomic, physiologic, behavioral, etc. profiles have motivated the current emphasis on 'precision' medicine. This review's purpose is to describe how the design and execution of N-of-1 (or personalized) multivariate clinical trials can advance the field. Such trials focus on individual responses to health interventions from a whole-person perspective, leverage emerging health monitoring technologies, and can be used to address the most relevant questions in the precision medicine era. This includes how to validate biomarkers that may indicate appropriate activity of an intervention as well as how to identify likely beneficial interventions for an individual. We also argue that multivariate N-of-1 and aggregated N-of-1 trials are ideal vehicles for advancing biomedical and translational science in the precision medicine era since the insights gained from them can not only shed light on how to treat or prevent diseases generally, but also provide insight into how to provide real-time care to the very individuals who are seeking attention for their health concerns in the first place.

A protocol for longitudinal monitoring of individual building occupants and their environments

Buildings account for approximately 40% of the energy consumption across the European Union, so there is a requirement to strive for better energy performance to reduce the global impact of urbanised societies. However, energy performant buildings can negatively impact building occupants (e.g., comfort, health and/or wellbeing) due to a trade-off between airtightness and air circulation. Thus, there is a need to monitor Indoor Environmental Quality (IEQ) to inform how it impacts occupants and hence redefine value within building performance metrics. An individualised study design would enable researchers to gain new insights into the effects of environmental changes on individuals for more targeted e.g., health interventions or nuanced and improved building design(s). This paper presents a protocol to conduct longitudinal monitoring of an individual and their immediate environment. Additionally, a novel approach to environmental perception gathering is proposed that will monitor environmental factors at an individual level to investigate subjective survey data pertaining to the participant’s perceptions of IEQ (e.g., perceived air quality, thermal conditions, light, and noise). This protocol has the potential to expose time-differential phenomena between environmental changes and an individual’s behavioural and physiological responses. This could be used to support building performance monitoring by providing an interventional assessment of building performance renovations. In the future it could also provide building scientists with a scalable approach for environmental monitoring that focuses specifically on individual health and wellbeing.

Single-case design standards: An update and proposed upgrades

In this paper, we provide a critique focused on the What Works Clearinghouse (WWC) Standards for Single-Case Research Design (Standards 4.1). Specifically, we (a) recommend the use of visual-analysis to verify a single-case intervention study's design standards and to examine the study's operational issues, (b) identify limitations of the design-comparable effect-size measure and discuss related statistical matters, (c) review the applicability and practicality of Standards 4.1 to single-case designs (SCDs), and (d) recommend inclusion of content pertaining to diversity, equity, and inclusion in future standards. Within the historical context of the WWC Pilot Standards for Single-Case Design (1.0), we suggest that Standards 4.1 may best serve as standards for meta-analyses of SCDs but will need to make clear distinctions among the various types of SCD studies that are included in any research synthesis. In this regard, we argue for transparency in SCD studies that meet design standards and those that do not meet design standards in any meta-analysis emanating from the WWC. The intent of these recommendations is to advance the science of SCD research both in research synthesis and in promoting evidence-based practices.