Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis.

Querying electronic health records databases to accurately identify specific cohorts of patients has countless observational and interventional research applications. Computable phenotypes are computationally executable, explicit sets of selection criteria composed of data elements, logical expressions, and a combination of natural language processing and machine learning techniques enabling expedited patient cohort identification. Phenotyping encompasses a range of implementations, each with advantages and use cases. In this paper, the dermatologic computable phenotype literature is reviewed. We identify and evaluate approaches and community supports for computable phenotyping that have been used both generally and within dermatology and, as a case study, focus on studied phenotypes for atopic dermatitis.

TRANscranial direct current stimulation for FOcal Refractory epilepsy in mitochondrial disease (TRANSFORM): delayed-start, randomised, double-blinded, placebo-controlled study.

BACKGROUND: Focal epilepsy is common in children and adults with mitochondrial disease. Seizures are often refractory to pharmacological treatment and, in this patient group, frequently evolve to refractory focal status epilepticus (also known as epilepsia partialis continua). Where this occurs, the long-term prognosis is poor. Transcranial DC stimulation (tDCS) is a promising, non-invasive, adjunctive treatment alternative to common surgical procedures. Limited recruitment of study participants with this rare disease and the ethical challenges of administering a treatment to one group and not another, while maintaining strict methodological rigour can pose challenges to the design of a clinical study. METHOD: We designed the first delayed start, double-blinded, sham-controlled study to evaluate the efficacy of tDCS as an adjunctive treatment for focal epilepsy. We will include participants with a genetically confirmed diagnosis of mitochondrial disease with drug-resistant focal epilepsy aged ≥ 2 years, aiming to collect 30 episodes of focal status epilepticus, each treated for a maximum period of 14 days. The early start intervention arm will receive tDCS from day 1. The delayed start intervention arm will receive sham stimulation until crossover on day 3. Our primary endpoint is a greater than 50% reduction from baseline (on day 0) in seizure frequency assessed by 3x daily reporting, accelerometery, and video monitoring. Changes in the underlying epileptogenic focus within the brain related to the tDCS intervention will be assessed by magnetic resonance imaging (MRI) and/or electroencephalography (EEG). DISCUSSION: Study results in favour of treatment efficacy would support development of tDCS into a mainstream treatment option for focal epileptic seizures related to mitochondrial disease. TRIALS REGISTRATION: ISRCTN: 18,241,112; registered on 16/11/2021.

A learning health systems approach to scaling up an evidence-based intervention for integrated primary mental healthcare case finding and referral in South Africa.

Despite progress in the development and evaluation of evidence-based primary mental health interventions in low-income and middle-income countries, implementation and scale-up efforts have had mixed results. Considerable gaps remain in the effective translation of research knowledge into routine health system practices, largely due to real-world contextual constraints on implementation and scale-up efforts. The Southern African Research Consortium for Mental Health Integration (S-MhINT) programme used implementation research to strengthen the implementation of an evidence-based integrated collaborative depression care model for primary healthcare (PHC) services in South Africa. To facilitate the scale-up of this model from a testing site to the whole province of KwaZulu-Natal, a capacity building programme was embedded within the Alliance for Health Policy and Systems Research (AHPSR) learning health systems (LHS) approach. The paper discusses efforts to scale up and embed case finding and referral elements of the S-MhINT package within routine PHC. Data from semistructured interviews, a focus group discussion, proceedings from participatory workshops and outputs from the application of continuous quality improvement (CQI) cycles were thematically analysed using the AHPSR LHS framework. Learning particularly occurred through information sharing at routine participatory workshops, which also offered mutual deliberation following periods of applying CQI tools to emergent problems. Individual-level, single-loop learning seemed to be particularly observable elements of the AHPSR LHS framework. Ultimately, our experience suggests that successful scale-up requires strong and sustained relationships between researchers, policy-makers and implementers, investments into learning platforms and organisational participation across all levels to ensure ownership and acceptance of learning processes.

The Danish National Health Survey 2023: study design and participant characteristics.

AIM: To describe the design of the Danish National Health Survey (DNHS) 2023, participants' demographic characteristics and differences in demographic and selected health-related characteristics between respondents invited by web-mode and paper-mode. METHODS: A sample of 25,000 residents in Denmark aged 16 years or above was invited to participate in the DNHS 2023 using a mixed-mode approach (web/paper mode). Web-mode invited were additionally invited to participate in an accelerometer study. The self-administered questionnaire included 83 questions about health, health behaviour and morbidity. Descriptive statistics were used to describe characteristics associated with response and invitation mode. RESULTS: The response proportion was 40.8%. Non-response was more frequent among men, individuals of the youngest age groups, individuals with non-Western backgrounds, unmarried and individuals from densely populated areas. The response proportion was higher among web-mode invited (42.0%) than paper-mode invited (22.6%). Paper-mode invited respondents were more often women, aged 80 years or older, and widowed compared with web-mode invited respondents. CONCLUSIONS: The DNHS 2023 is a national health survey including adult residents in Denmark. Non-response was more pronounced among some subgroups; however, calibrated weights were calculated to minimise non-response bias. The survey is essential for public health surveillance and can be used in health planning and policy development. Furthermore, the data from the survey can be used for research on the population's health and health behaviour. For future waves of the DNHS, it should be considered whether resources should be used to invite people unsubscribed from digital-post due to the low response proportion.

Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples.

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

The association between study design and antidepressant effects in psychedelic-assisted therapy: A meta-analysis.

Different study designs of psychedelic trials may impact the blinding and expectance, leading to biased treatment effects. This study aimed to examine the association between antidepressant efficacy and study designs in psychedelic trials. Six databases were systematically searched. Eligible trials were required to investigate the efficacy of psychedelics (psilocybin, lysergic acid diethylamide [LSD], 3,4-Methylenedioxymethamphetamine [MDMA], and ayahuasca) in adult patients with depressive symptoms. We only considered oral psychedelic-assisted therapy without concomitant use of antidepressants. The primary outcome was the change in depressive symptoms. There were five study designs of psychedelic trials, including non-active-drug-as-placebo, active-drug-as-placebo, waitlist-as-control, fixed-order, and pre-post designs. In non-active-drug -as-placebo design, psilocybin (k = 4, Hedges' g [g] = 0.87, 95 % confidence intervals[CIs] = 0.58 to 1.16) and MDMA (k = 2, g = 0.65, 95%CIs = 0.26 to 1.05) were associated with large and medium effect sizes, respectively. In active-drug-as-placebo design, both psilocybin (k = 2, g = 0.71, 95%CIs = -0.01 to 1.43) and MDMA (k = 3, g = 0.53, 95%CIs = -0.23 to 1.28) were not statistically significant. In pre-post single-arm (k = 3, g = 2.51, 95%CIs = 1.00 to 4.02) and waitlist-as-control (k = 1, g = 2.88, 95%CIs = 1.75 to 4.00) designs, psilocybin showed a large effect size of antidepressant effect. Ayahuasca also showed a large effect size in both pre-post (k = 2, g = 1.88, 95%CIs = 1.18 to 2.57) and non-active-drug-as-placebo (k = 1, g = 1.60, 95%CIs = 0.84 to 2.36) designs. LSD was associated with a significant antidepressant effect only in non-active-drug-as-placebo design (k = 1, g = 1.49, 95%CIs = 0.80 to 2.17) but not in active-drug-as-placebo design (k = 1, g = 0.44, 95%CIs = -0.90 to 1.78). The antidepressant effects of psychedelics may be overestimated in studies with pre-post single-arm, non-active-drugs-as placebo, and waitlist-control designs. Restricted sample size, difficulty with establishing blinding for participants, and over expectancy limit the estimation of the antidepressant effect of psychedelic-assisted therapy.

Optimal survival analyses with prevalent and incident patients.

Period-prevalent cohorts are often used for their cost-saving potential in epidemiological studies of survival outcomes. Under this design, prevalent patients allow for evaluations of long-term survival outcomes without the need for long follow-up, whereas incident patients allow for evaluations of short-term survival outcomes without the issue of left-truncation. In most period-prevalent survival analyses from the existing literature, patients have been recruited to achieve an overall sample size, with little attention given to the relative frequencies of prevalent and incident patients and their statistical implications. Furthermore, there are no existing methods available to rigorously quantify the impact of these relative frequencies on estimation and inference and incorporate this information into study design strategies. To address these gaps, we develop an approach to identify the optimal mix of prevalent and incident patients that maximizes precision over the entire estimated survival curve, subject to a flexible weighting scheme. In addition, we prove that inference based on the weighted log-rank test or Cox proportional hazards model is most powerful with an entirely prevalent or incident cohort, and we derive theoretical formulas to determine the optimal choice. Simulations confirm the validity of the proposed optimization criteria and show that substantial efficiency gains can be achieved by recruiting the optimal mix of prevalent and incident patients. The proposed methods are applied to assess waitlist outcomes among kidney transplant candidates.

The Oncology QCARD Initiative: Fostering efficient evaluation of initial real-world data proposals.

PURPOSE: The oncology quality, characterization, and assessment of real-world data (Oncology QCARD) Initiative was formed to develop a set of minimum study design and data elements needed to evaluate the fitness of the real-world data (RWD) source(s) proposed in an initial study concept as part of early interaction with scientific reviewers. METHODS: A multidisciplinary executive committee (EC) was established to guide the Oncology QCARD Initiative. The EC conducted a landscape review of published literature, guidances, and guidelines to evaluate relevant dimensions of data quality measurement. Guided by the review and informed by expert feedback, the Oncology QCARD Initial Protocol Characterization (IPC) provides a summary of minimum elements needed to adequately describe an initial clinical study concept that involves RWD and is intended to support decision-making. RESULTS: Fit-for-use data and fit-for-purpose design emerged as themes from the landscape analysis. Data that are fit-for-use are both relevant (sufficiently capturing exposure, outcomes, and covariates) and reliable (understanding data accrual and quality control and whether the data represent the underlying concepts they are intended to represent) to answer a specific research question. A fit-for-purpose design takes appropriate steps to ensure internal and external validity and allows for transparency in reporting. The QCARD-IPC focuses on high-level characteristics of RWD sources and study design domains including data temporality, population, medical product exposure, comparators, and covariates, endpoints, statistical analysis, and data quality assurance plans. CONCLUSIONS: Evaluation of studies including RWD requires understanding the data source, study design, and potential biases to preliminarily evaluate whether selected RWD are fit-for-use for the research question. The Oncology QCARD-IPC provides a structured, transparent approach to facilitate early review and enhanced communication between study sponsors and scientific reviewers of initial study proposals including RWD.

How Do We Assess Controversies Using Evidence-Based Radiology?

At its best, the practice of medicine involves careful integration of experience and evidence. Generating evidence to address controversies in radiology - and translating such evidence to practice - requires appropriate selection of methods, and an understanding of the strengths, shortcomings, and biases inherent to different research designs and analyses. Equipped with such knowledge, the radiologic community can ensure that both research and clinical practice in our discipline excels, and that those questions that will be the most critical to answer will be formulated for successful investigation in the years to come.

Concept, study design, and baseline nighttime blood pressure control status of the WISDOM-Night Study using a wrist-type oscillometric home blood pressure monitoring device.

There is growing evidence that nocturnal hypertension is an independent risk factor for cardiovascular diseases, including heart failure. However, brachial blood pressure (BP) measurements during sleep might themselves disturb sleep quality. We initiated a nationwide, multicenter observational prospective study using a wrist-type oscillometric nighttime BP monitoring device with new algorithms to measure supine BP accurately without sleep disturbance. This study, named the Wrist ICT-based Sleep and Circadian Blood Pressure Monitoring Program-Night BP Study (WISDOM-Night Study), was designed to clarify the impact of wrist-measured daily nighttime BPs on cardiovascular prognosis (stroke, coronary artery disease, heart failure, etc.) using 7 days of BP measurements at 2:00 a.m., 3:00 a.m., 4:00 a.m., and 4 h after bedtime. A total of 2751 patients with one or more cardiovascular risk factors were recruited between March 2021 and March 2024 and are currently being followed up for 7 years. Additionally, 1416 of the WISDOM-Night Study-enrolled patients who also agreed to participate in the WISDOM-Hypertension-Mediated Organ Damage (HMOD) Study underwent echocardiography to evaluate the association between wrist-measured BP and left ventricular structure. Data from this WISDOM-Night Study should provide the prospective association between nighttime BP and cardiovascular disease and reveal the indexes of nighttime BP with clinical pathological relevance. This first report of the WISDOM-Night Study describes the study design, baseline characteristics, and BP control status.

Assessing the impact of social determinants of health on diabetes severity and management.

Objective: Adverse Social Determinants of Health (SDoH) are considered major obstacles to effective management of type-2 diabetes. This study aims to quantify the impact of SDoH factors on diabetes management outcomes. Materials and Methods: We quantified the joint impact of multiple SDoH by applying a self-control case series method-which accounts for confounding by using individuals as their own control-to electronic health record data from an academic health system in Maryland. Results: We found a consistent increase in HbA1c levels associated with SDoH across alternative study designs. The estimated total contributions of SDoH ranged 0.014-0.065 across the alternative designs. Transportation issues demonstrated particularly significant contributions, with estimates of 0.077-0.144. When assuming SDoH's risk window to be ±45 days, for example, the total contribution was estimated to be 0.065 (95% CI [0.010, 0.120]) increase in HbA1c and the transportation issues' contribution 0.134 (95% CI [0.020, 0.249]). Discussion and Conclusion: Our result suggests that reducing transportation barriers may be an effective SDoH intervention strategy for diabetes management; however, the clinical impact of such interventions warrants further investigation.

Impact of Digitally Enabled Peer Support Interventions on Diabetes Distress and Depressive Symptoms in People Living with Type 1 Diabetes: A Systematic Review.

PURPOSE OF REVIEW: To explore the impact of digitally-enabled peer support interventions on diabetes distress and depression for individuals living with Type 1 Diabetes (T1D). RECENT FINDINGS: We synthesized the results of nine key studies from a review of 3,623 English-language articles published between January 2012 and January 2024. Three studies demonstrated significant reductions in diabetes distress, and two studies reported reductions in depression. Data were analyzed using a narrative approach, including thematic synthesis. This process was structured around the Behavior Change Wheel framework Effective interventions shared several common features such as (1) involved participatory development approaches, (2) included diabetes education, (3) lasted over a longer time, (4) designed with a psychological framework, and (5) utilized peer mentors. Studies showed that digitally-enabled peer support has the potential to improve diabetes distress and depression among people living with T1D despite heterogeneity in intervention approaches. Moreover, designing interventions with certain features may enhance key psychosocial outcomes.

Underpowered studies in muscle metabolism research: Determinants and considerations.

Biomedical research frequently employs null hypothesis testing to determine whether an observed difference in a sample is likely to exist in the broader population. Null hypothesis testing generally assumes that differences between groups or interventions are non-existent, unless proven otherwise. Because biomedical studies with human subjects are often limited by financial and logistical resources, they tend to have low statistical power, i.e. a low probability of statistically confirming a true difference. As a result, small but potentially clinically important differences may be overseen or ignored simply due to the absence of a statistically significant difference. This absence is often misinterpreted as 'equivalence' of treatments. In this educational paper, we will use practical examples related to the effects of exercise and nutrition on muscle protein metabolism to illustrate the most important determinants of statistical power, as well as their implications for both investigators and readers of scientific articles. Changes in muscle mass occur at a relatively slow rate, making it practically challenging to detect differences between treatment groups in a long-term setting. One way to make it 'easier' to differentiate between groups and hence increase statistical power is to have a sufficiently long study duration to allow treatment effects to become apparent. This is especially relevant when comparing treatments with relatively small expected differences such as the effect of modest changes in daily protein intake. Secondly, one could try to minimize the variance and response heterogeneity within groups, for example by using strict inclusion criteria and standardization protocols (e.g., meal provision), by using cross-over designs, or even within-subject designs where two interventions are compared simultaneously (e.g., studying an exercised limb vs a contralateral control limb) although this might limit the generalizability of the findings (e.g. such single-limb exercise training is not common in practice). In terms of data interpretation, investigators should obviously refrain from drawing strong conclusions from underpowered studies. Yet, such studies still provide valuable data for meta-analyses. Finally, because muscle protein synthesis rates are highly responsive to anabolic stimuli, acute metabolic studies are more sensitive to detect potentially clinically relevant differences in the anabolic response between treatments. Apart from further elaborating on these topics, this educational article encourages readers to more critically question null findings and scientists to more clearly discuss limitations that may have compromised statistical power.

Co-Designing Remote Patient Monitoring Technologies for Inpatients: Systematic Review.

BACKGROUND: The co-design of health technology enables patient-centeredness and can help reduce barriers to technology use. OBJECTIVE: The study objectives were to identify what remote patient monitoring (RPM) technology has been co-designed for inpatients and how effective it is, to identify and describe the co-design approaches used to develop RPM technologies and in which contexts they emerge, and to identify and describe barriers and facilitators of the co-design process. METHODS: We conducted a systematic review of co-designed RPM technologies for inpatients or for the immediate postdischarge period and assessed (1) their effectiveness in improving health outcomes, (2) the co-design approaches used, and (3) barriers and facilitators to the co-design process. Eligible records included those involving stakeholders co-designing RPM technology for use in the inpatient setting or during the immediate postdischarge period. Searches were limited to the English language within the last 10 years. We searched MEDLINE, Embase, CINAHL, PsycInfo, and Science Citation Index (Web of Science) in April 2023. We used the Joanna Briggs Institute critical appraisal checklist for quasi-experimental studies and qualitative research. Findings are presented narratively. RESULTS: We screened 3334 reports, and 17 projects met the eligibility criteria. Interventions were designed for pre- and postsurgical monitoring (n=6), intensive care monitoring (n=2), posttransplant monitoring (n=3), rehabilitation (n=4), acute inpatients (n=1), and postpartum care (n=1). No projects evaluated the efficacy of their co-designed RPM technology. Three pilot studies reported clinical outcomes; their risk of bias was low to moderate. Pilot evaluations (11/17) also focused on nonclinical outcomes such as usability, usefulness, feasibility, and satisfaction. Common co-design approaches included needs assessment or ideation (16/17), prototyping (15/17), and pilot testing (11/17). The most commonly reported challenge to the co-design process was the generalizability of findings, closely followed by time and resource constraints and participant bias. Stakeholders' perceived value was the most frequently reported enabler of co-design. Other enablers included continued stakeholder engagement and methodological factors (ie, the use of flexible mixed method approaches and prototyping). CONCLUSIONS: Co-design methods can help enhance interventions' relevance, usability, and adoption. While included studies measured usability, satisfaction, and acceptability-critical factors for successful implementation and uptake-we could not determine the clinical effectiveness of co-designed RPM technologies. A stronger commitment to clinical evaluation is needed. Studies' use of diverse co-design approaches can foster stakeholder inclusivity, but greater standardization in co-design terminology is needed to improve the quality and consistency of co-design research.

Synthesizing regulatory guidance for demonstrating preclinical efficacy and translating promising cell therapies to early phase clinical trials: a scoping review.

BACKGROUND: Regulatory applications for cell therapy face more objections compared to conventional small molecule or biological drugs, leading to delays in market approval and clinical adoption. Increased regulatory objections frequently relate to issues regarding preclinical evidence, such as experimental design of animal studies, selection of animal models, endpoints, and determination of mechanism of action. Synthesis and clarification of the preclinical evidence necessary to demonstrate treatment efficacy and advance into early-phase clinical trials is needed to help researchers avoid regulatory objections. METHODS: We conducted a scoping review in which we searched repositories of the International Council for Harmonisation and all national member organizations (N = 38) for documents related to preclinical studies of cell therapies. Active guidance documents related to cell therapy were included, with no restrictions based on the year or language of publication. Data extraction was conducted in duplicate with conflicts resolved through consensus discussion. RESULTS: From 1215 identified documents, a total of 182 were included and analyzed, with 71% originating from ten major regulatory agencies. The most prevalent preclinical item addressed was the mechanism of action (n = 161, 88% of documents), underscoring its importance in bridging preclinical findings to clinical application. Most documents (n = 140, 77%) emphasized the importance of using clinically relevant preclinical models, though specific recommendations on models of disease were less common (n = 81, 45%). Selection of clinically relevant intervention parameters (n = 136, 75%) and outcome measures (n = 121, 66%) were also frequently recommended, but selection of relevant comparator groups appeared less frequently (n = 35, 19%). Furthermore, robust study design elements such as randomization and blinding were less frequently recommended, appearing in 31% of documents (n = 57). Comparison with clinical trial guidance revealed a significant gap in the rigor of study design recommendations for preclinical research. CONCLUSIONS: Regulatory guidance for preclinical efficacy studies often recommends a strong emphasis on the clinical relevance of animal models, intervention parameters, outcomes, and mechanism of action. Incorporating these recommendations into early preclinical studies should improve the acceptability of preclinical evidence for approval by the relevant national regulators and can be used as a guide to ensure that all evidence that regulators say they expect is efficiently assembled into new clinical trial applications.

Characteristic of clinical trials related to traumatic brain injury registered on ClinicalTrials.gov over the past two decades (2004-2023).

Objective: The aim of this report is to provide a comprehensive overview of clinical trials and protocols related to traumatic brain injury over the past two decades. Methods: We collected information on clinical trials related to traumatic brain injury (TBI) from the ClinicalTrials.gov database, identified key categorical variables, and assessed their characteristics. Results: A total of 367 TBI-related trials were identified for analysis. All identified trials were interventional clinical trials. Most trials were small-scale, with 75.2% enrolling 1-100 participants, and only about 20% were funded by industry or the National Institutes of Health (NIH). In most trials, participants were gender-neutral (96.5%), and the primary age group was adults and older adults (56.9%). Of all identified TBI trials, 78.2% were randomized, and 69.4% were blinded. Additionally, the primary purpose of 297 trials (80.9%) was treatment, with drug therapy as the most common intervention. A total of 153 trials (41.7%) were completed; however, only 58 trials submitted results to the registry. Furthermore, 81 trials (22.1%) were discontinued early, primarily due to recruitment problems. Clinical trials started between 2004 and 2013 reported a higher proportion of results compared with those started between 2014 and 2023 (35.1% vs. 11.1%, p < 0.001). In addition, between 2014 and 2023, there was an increase in trials for diagnostic purposes (2.4% vs. 6.5%, p < 0.001). Conclusion: Based on the data collected from the ClinicalTrials.gov, our study reveals that most clinical trials related to TBI focus on drug-related treatments, underreporting remains a significant concern, and greater emphasis should be placed on improving the publication and dissemination of clinical trial results.

[What is health services research?] / Was ist Versorgungsforschung?

In health services research, the health care of the population is examined under everyday conditions. Scientific questions include medical, patient-oriented, system-, performance- and quality-related as well as health economics topics. In health services research, complex interventions, e.g., treatment concepts with multiple therapy components, and/or across multiple sectors, are often implemented. The design of studies in health services research is based on the research question, the setting, and the available data, which can come from a variety of sources.

Power analyses to inform Duplex Sequencing study designs for MutaMouse liver and bone marrow.

Regulatory genetic toxicology testing is essential for identifying potentially mutagenic hazards. Duplex Sequencing (DS) is an error-corrected next-generation sequencing technology that provides substantial advantages for mutation analysis over conventional mutagenicity assays including: improved accuracy of mutation detection, ability to measure changes in mutation spectrum, and applicability across diverse biological models. To apply DS for regulatory toxicology testing, power analyses are required to determine suitable sample sizes and study designs. In this study, we explored study designs to achieve sufficient power for various effect sizes in chemical mutagenicity assessment. We collected data from MutaMouse bone marrow and liver samples that were analyzed by DS using TwinStrand's Mouse Mutagenesis Panel. Average duplex reads achieved in two separates studies on liver and bone marrow were 8.4 × 108 (± 7.4 × 107) and 9.5 × 108 (± 1.0 × 108), respectively. Baseline mean mutation frequencies (MF) were 4.6 × 10-8 (± 6.7 × 10-9) and 4.6 × 10-8 (± 1.1 × 10-8), with estimated standard deviations for the animal-to-animal random effect of 0.15 and 0.20, for liver and bone marrow, respectively. We conducted simulation analyses based on these empirically derived parameters. We found that a sample size of four animals per group is sufficient to obtain over 80% power to detect a two-fold change in MF relative to baseline. In addition, we estimated the minimal total number of informative duplex bases sequenced with different sample sizes required to retain power for various effect sizes. Our work provides foundational data for establishing suitable study designs for mutagenicity testing using DS.