Stroke of Consistency: Streamlining Multicenter Protocols for Enhanced Reproducibility of Infarct Volumes in Preclinical Stroke Research.

BACKGROUND: The discrepancy between experimental research and clinical trial outcomes is a persistent challenge in preclinical studies, particularly in stroke research. A possible factor contributing to this issue is the lack of standardization across experimental stroke models, leading to poor reproducibility in multicenter studies. This study addresses this gap by aiming to enhance reproducibility and the efficacy of multicenter studies through the harmonization of protocols and training of involved personnel. METHODS: We established a set of standard operating procedures for various stroke models and the Neuroscore. These standard operating procedures were implemented across multiple research centers, followed by specialized, in-person training for all participants. We measured the variability in infarct volume both before and after the implementation of these standardized protocols and training sessions. RESULTS: The standardization process led to a significant reduction in variability of infarct volume across different stroke models (40%-50% reduction), demonstrating the effectiveness of our harmonized protocols and training. Additionally, the implementation of the Neuroscore system across centers showed low variability and consistent results up to 28 days poststroke, underscoring its utility in chronic phase evaluations. CONCLUSIONS: The harmonization of protocols and surgeon training significantly reduced variability in experimental outcomes across different centers. This improvement can increase the comparability of data between research groups and enhance the statistical power of multicenter studies. Our findings also establish the Neuroscore as a reliable tool for long-term assessment in stroke research, paving the way for more consistent and impactful multicenter preclinical studies.

Assessing the impact of risk-based data monitoring on outcomes for a paediatric multicentre randomised controlled trial.

BACKGROUND/AIMS: Regulatory guidelines recommend that sponsors develop a risk-based approach to monitoring clinical trials. However, there is a lack of evidence to guide the effective implementation of monitoring activities encompassed in this approach. The aim of this study was to assess the efficiency and impact of the risk-based monitoring approach used for a multicentre randomised controlled trial comparing treatments in paediatric patients undergoing cardiac bypass surgery. METHODS: This is a secondary analysis of data from a randomised controlled trial that implemented targeted source data verification as part of the risk-based monitoring approach. Monitoring duration and source to database error rates were calculated across the monitored trial dataset. The monitored and unmonitored trial dataset, and simulated trial datasets with differing degrees of source data verification and cohort sizes were compared for their effect on trial outcomes. RESULTS: In total, 106,749 critical data points across 1,282 participants were verified from source data either remotely or on-site during the trial. The total time spent monitoring was 365 hours, with a median (interquartile range) of 10 (7, 16) minutes per participant. An overall source to database error rate of 3.1% was found, and this did not differ between treatment groups. A low rate of error was found for all outcomes undergoing 100% source data verification, with the exception of two secondary outcomes with error rates >10%. Minimal variation in trial outcomes were found between the unmonitored and monitored datasets. Reduced degrees of source data verification and reduced cohort sizes assessed using simulated trial datasets had minimal impact on trial outcomes. CONCLUSIONS: Targeted source data verification of data critical to trial outcomes, which carried with it a substantial time investment, did not have an impact on study outcomes in this trial. This evaluation of the cost-effectiveness of targeted source data verification contributes to the evidence-base regarding the context where reduced emphasis should be placed on source data verification as the foremost monitoring activity.

The symbolic two-step method applied to cancer care delivery research: Safeguarding against designing an underpowered cluster randomized trial with a continuous outcome by accounting for the imprecision in the within- and between-center variation.

BACKGROUND: Knowing the predictive factors of the variation in a center-level continuous outcome of interest is valuable in the design and analysis of parallel-arm cluster randomized trials. The symbolic two-step method for sample size planning that we present incorporates this knowledge while simultaneously accounting for patient-level characteristics. Our approach is illustrated through application to cluster randomized trials in cancer care delivery research. The required number of centers (clusters) depends on the between- and within-center variance; the within-center variance is a function of estimates obtained by regressing the log within-center variance on predictive factors. Obtaining accurate estimates of the components needed to characterize the within-center variation is challenging. METHODS: Using our previously derived sample size formula, our objective in the current research is to directly account for the imprecision in these estimates, using a Bayesian approach, to safeguard against designing an underpowered study when using the symbolic two-step method. Using estimates of the required components, including the number of centers that contribute to those estimates, we make formal allowance for the imprecision in these estimates on which a sample size will be based. RESULTS: The mean of the distribution for power is consistently smaller than the single point estimate that the sample size formula yields. The reduction in power is more pronounced in the presence of increased uncertainty about the estimates with the reduction becoming more attenuated with increased numbers of centers that contribute to the estimates. CONCLUSIONS: Accounting for imprecision in the estimates of the components required for sample size estimation using the symbolic two-step method in the design of a cluster randomized trial yields conservative estimates of power.

Cautionary note on regional consistency evaluation in multiregional clinical trials with binary outcomes.

Multiregional clinical trials (MRCTs) have become increasingly common during the development of new drugs to obtain simultaneous drug approvals worldwide. When planning MRCTs, a major statistical challenge is determination of the regional sample size. In general, the regional sample size must be determined as the sample size such that the regional consistency probability, defined as the probability of meeting the regional consistency criterion, is greater than a prespecified value. The Japanese Ministry of Health, Labour and Welfare proposed two criteria for regional consistency. Moreover, many researchers have proposed corresponding closed-form formulas for calculating regional consistency probabilities when the primary outcome is continuous. Although some researchers have argued that those formulas are also applicable to cases with binary outcomes, it remains questionable whether such an argument can be true. Based on simulation results, we demonstrate that the existing formulas are inappropriate for binary cases, even when the regional sample size is sufficiently large. To address this issue, we develop alternative formulas and use simulation to show that they provide accurate regional consistency probabilities. Furthermore, we present an application of our proposed formulas for an MRCT of advanced or metastatic clear-cell renal cell carcinoma.

[The possibilities and advantages of conducting multicenter clinical trials on the basis of outpatient clinics in Moscow].

The article presents the special role of the outpatient unit (urban polyclinics) in the system of urban medical organizations, which has significant development potential in the field of clinical research. This activity became possible due to the systematic work on equipping outpatient clinics with the most modern diagnostic equipment, the availability of specialists trained in the organization and conduct of clinical trials according to the international rules of good clinical practice. A special value lies in the fact that the polyclinic network has an extensive database that includes millions of patients and provides the opportunity to perform the highest level of medical expertise and research.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Mitigating site effects in covariance for machine learning in neuroimaging data.

To acquire larger samples for answering complex questions in neuroscience, researchers have increasingly turned to multi-site neuroimaging studies. However, these studies are hindered by differences in images acquired across multiple sites. These effects have been shown to bias comparison between sites, mask biologically meaningful associations, and even introduce spurious associations. To address this, the field has focused on harmonizing data by removing site-related effects in the mean and variance of measurements. Contemporaneously with the increase in popularity of multi-center imaging, the use of machine learning (ML) in neuroimaging has also become commonplace. These approaches have been shown to provide improved sensitivity, specificity, and power due to their modeling the joint relationship across measurements in the brain. In this work, we demonstrate that methods for removing site effects in mean and variance may not be sufficient for ML. This stems from the fact that such methods fail to address how correlations between measurements can vary across sites. Data from the Alzheimer's Disease Neuroimaging Initiative is used to show that considerable differences in covariance exist across sites and that popular harmonization techniques do not address this issue. We then propose a novel harmonization method called Correcting Covariance Batch Effects (CovBat) that removes site effects in mean, variance, and covariance. We apply CovBat and show that within-site correlation matrices are successfully harmonized. Furthermore, we find that ML methods are unable to distinguish scanner manufacturer after our proposed harmonization is applied, and that the CovBat-harmonized data retain accurate prediction of disease group.

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

Cognitive Impairment and Dementia After Stroke: Design and Rationale for the DISCOVERY Study.

Stroke is a leading cause of the adult disability epidemic in the United States, with a major contribution from poststroke cognitive impairment and dementia (PSCID), the rates of which are disproportionally high among the health disparity populations. Despite the PSCID's overwhelming impact on public health, a knowledge gap exists with regard to the complex interaction between the acute stroke event and highly prevalent preexisting brain pathology related to cerebrovascular and Alzheimer disease or related dementia. Understanding the factors that modulate PSCID risk in relation to index stroke event is critically important for developing personalized prognostication of PSCID, targeted interventions to prevent it, and for informing future clinical trial design. The DISCOVERY study (Determinants of Incident Stroke Cognitive Outcomes and Vascular Effects on Recovery), a collaborative network of thirty clinical performance clinical sites with access to acute stroke populations and the expertise and capacity for systematic assessment of PSCID will address this critical challenge. DISCOVERY is a prospective, multicenter, observational, nested-cohort study of 8000 nondemented ischemic and hemorrhagic stroke patients enrolled at the time of index stroke and followed for a minimum of 2 years, with serial cognitive evaluations and assessments of functional outcome, with subsets undergoing research magnetic resonance imaging and positron emission tomography and comprehensive genetic/genomic and fluid biomarker testing. The overall scientific objective of this study is to elucidate mechanisms of brain resilience and susceptibility to PSCID in diverse US populations based on complex interplay between life-course exposure to multiple vascular risk factors, preexisting burden of microvascular and neurodegenerative pathology, the effect of strategic acute stroke lesions, and the mediating effect of genomic and epigenomic variation.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research.

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

Comparison of traveling-subject and ComBat harmonization methods for assessing structural brain characteristics.

Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and development. Measurement biases-caused by site differences in scanner/image-acquisition protocols-negatively influence the reliability and reproducibility of image-analysis methods. Harmonization can reduce bias and improve the reproducibility of multisite datasets. Herein, a traveling-subject (TS) dataset including 56 T1-weighted MRI scans of 20 healthy participants in three different MRI procedures-20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively-was considered to compare the reproducibility of TS-GLM, ComBat, and TS-ComBat harmonization methods. The minimum participant count required for harmonization was determined, and the Cohen's d between different MRI procedures was evaluated as a measurement-bias indicator. The measurement-bias reduction realized with different methods was evaluated by comparing test-retest scans for 20 healthy participants. Moreover, the minimum subject count for harmonization was determined by comparing test-retest datasets. The results revealed that TS-GLM and TS-ComBat reduced measurement bias by up to 85 and 81.3%, respectively. Meanwhile, ComBat showed a reduction of only 59.0%. At least 6 TSs were required to harmonize data obtained from different MRI scanners, complying with the imaging protocol predetermined for multisite investigations and operated with similar scan parameters. The results indicate that TS-based harmonization outperforms ComBat for measurement-bias reduction and is optimal for MRI data in well-prepared multisite investigations. One drawback is the small sample size used, potentially limiting the applicability of ComBat. Investigation on the number of subjects needed for a large-scale study is an interesting future problem.

Comparison of one-month versus twelve-month dual antiplatelet therapy after implantation of drug-eluting stents guided by either intravascular ultrasound or angiography in patients with acute coronary syndrome: rationale and design of prospective, multicenter, randomized, controlled IVUS-ACS and ULTIMATE-DAPT trial.

BACKGROUND: Current guidelines recommend administering dual antiplatelet therapy (DAPT) for 12 months to patients with acute coronary syndromes (ACS) and without contraindications after drug-eluting stent (DES) implantation. A recent study reported that 3 months of DAPT followed by ticagrelor monotherapy is effective and safe in ACS patients undergoing DES implantation compared with the standard duration of DAPT. However, it is unclear whether antiplatelet monotherapy with ticagrelor alone versus ticagrelor plus aspirin reduces the incidence of clinically relevant bleeding without increasing the risk of major adverse cardiovascular and cerebrovascular events (MACCEs) in ACS patients undergoing percutaneous coronary intervention (PCI) with DES implantation guided by either intravascular ultrasound (IVUS) or angiography who have completed a 1-month course of DAPT with aspirin plus ticagrelor. METHODS: The IVUS-ACS and ULTIMATE-DAPT is a prospective, multicenter, randomized, controlled trial designed to determine (1) whether IVUS-guided versus angiography-guided DES implantation in patients with ACS reduces the risk of target vessel failure (TVF) at 12 months and (2) whether ticagrelor alone versus ticagrelor plus aspirin reduces the risk of clinically relevant bleeding without increasing the risk of MACCE 1-12 months after the index PCI in ACS patients undergoing DES implantation guided by either IVUS or angiography. This study will enroll 3486 ACS patients eligible for DES implantation, as confirmed by angiographic studies. The patients who meet the inclusion criteria and none of the exclusion criteria will be randomly assigned in a 1:1 fashion to the IVUS- or angiography-guided group (first randomization). All enrolled patients will complete a 1-month course of DAPT with aspirin plus ticagrelor after the index PCI. Patients with no MACCEs or major bleeding (≥Bleeding Academic Research Consortium (BARC) 3b) within 30 days will be randomized in a 1:1 fashion to either the ticagrelor plus matching placebo (SAPT)group or ticagrelor plus aspirin (DAPT)group for an additional 11 months (second randomization). The primary endpoint of the IVUS-ACS trial is TVF at 12 months, including cardiac death, target vessel myocardial infarction (TVMI), or clinically driven target vessel revascularization (CD-TVR). The primary superiority endpoint of the ULTIMATE-DAPT trial is clinically relevant bleeding, defined as BARC Types 2, 3, or 5 bleeding, and the primary non-inferiority endpoint of the ULTIMATE-DAPT trial is MACCE, defined as cardiac death, myocardial infarction, ischemic stroke, CD-TVR, or definite stent thrombosis occurring 1-12 months in the second randomized population. CONCLUSION: The IVUS-ACS and ULTIMATE-DAPT trial is designed to test the efficacy and safety of 2 different antiplatelet strategies in ACS patients undergoing PCI with DES implantation guided by either IVUS or angiography. This study will provide novel insights into the optimal DAPT duration in ACS patients undergoing PCI and provide evidence on the clinical benefits of IVUS-guided PCI in ACS patients.

Phase 3 DREAM-HF Trial of Mesenchymal Precursor Cells in Chronic Heart Failure.

Advanced heart failure (HF) is a progressive disease characterized by recurrent hospitalizations and high risk of mortality. Indeed, outcomes in late stages of HF approximate those seen in patients with various aggressive malignancies. Clinical trials assessing beneficial outcomes of new treatments in patients with cancer have used innovative approaches to measure impact on total disease burden or surrogates to assess treatment efficacy. Although most cardiovascular outcomes trials continue to use time-to-first event analyses to assess the primary efficacy end point, such analyses do not adequately reflect the impact of new treatments on the totality of the chronic disease burden. Consequently, patient enrichment and other strategies for ongoing clinical trial design, as well as new statistical methodologies, are important considerations, particularly when studying a population with advanced chronic HF. The DREAM-HF trial (Double-Blind Randomized Assessment of Clinical Events With Allogeneic Mesenchymal Precursor Cells in Advanced Heart Failure) is an ongoing, randomized, sham-controlled phase 3 study of the efficacy and safety of mesenchymal precursor cells as immunotherapy in patients with advanced chronic HF with reduced ejection fraction. Mesenchymal precursor cells have a unique multimodal mechanism of action that is believed to result in polarization of proinflammatory type 1 macrophages in the heart to an anti-inflammatory type 2 macrophage state, inhibition of maladaptive adverse left ventricular remodeling, reversal of cardiac and peripheral endothelial dysfunction, and recovery of deranged vasculature. The objective of DREAM-HF is to confirm earlier phase 2 results and evaluate whether mesenchymal precursor cells will reduce the rate of nonfatal recurrent HF-related major adverse cardiac events while delaying or preventing progression of HF to terminal cardiac events. DREAM-HF is an example of an ongoing contemporary events-driven cardiovascular cell-based immunotherapy study that has utilized the concepts of baseline disease enrichment, prognostic enrichment, and predictive enrichment to improve its efficiency by using accumulating data from within as well as external to the trial. Adaptive enrichment designs and strategies are important components of a rational approach to achieve clinical research objectives in shorter clinical trial timelines and with increased cost-effectiveness without compromising ethical standards or the overall statistical integrity of the study. The DREAM-HF trial also presents an alternative approach to traditional composite time-to-first event primary efficacy end points. Statistical methodologies such as the joint frailty model provide opportunities to expand the scope of events-driven HF with reduced ejection fraction clinical trials to utilize time to recurrent nonfatal HF-related major adverse cardiac events as the primary efficacy end point without compromising the integrity of the statistical analyses for terminal cardiac events. In advanced chronic HF with reduced ejection fraction studies, the joint frailty model is utilized to reflect characteristics of the high-risk patient population with important unmet therapeutic needs. In some cases, use of the joint frailty model may substantially reduce sample size requirements. In addition, using an end point that is acceptable to the Food and Drug Administration and the European Medicines Agency, such as recurrent nonfatal HF-related major adverse cardiac events, enables generation of clinically relevant pharmacoeconomic data while providing comprehensive views of the patient's overall cardiovascular disease burden. The major goal of this review is to provide lessons learned from the ongoing DREAM-HF trial that relate to biologic plausibility and flexible clinical trial design and are potentially applicable to other development programs of innovative therapies for patients with advanced cardiovascular disease. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02032004.

Use of endpoints in multiple myeloma randomized controlled trials over the last 15 years: A systematic review.

Surrogate endpoints are being used more frequently in randomized controlled trials, even though they do not consistently corelate with patient outcomes. We systemically evaluated the use of surrogate endpoints in multiple myeloma randomized controlled trials over the past 15 years. We searched three databases (Pubmed, Embase, Cochrane) for multiple myeloma randomized controlled trials from January 1, 2005 to December 30, 2019. The primary outcome of our study was the proportion of randomized controlled trials that used overall survival as their primary endpoint. Secondary outcomes included the use of surrogate endpoints, and trends over time, and whether they differed based on study sponsorship. We included 151 randomized controlled trials in our analysis. The primary endpoint was overall survival (OS) in 17 (11.3%) of studies, progression free survival (PFS) or event-defined endpoints in 91 studies (60.3%) and response-based endpoints in 44 studies (29.1%). Quality of life was a primary endpoint in only three studies (2%). The use of OS as a primary endpoint decreased from 28.5% of trials from 2005 to 2009 to 5.5% from 2015 to 2019. There has been a decrease in the clinically meaningful endpoint of OS over the past 15 years in multiple myeloma randomized controlled trials. Use of quality of life as a primary endpoint remains exceedingly low. It remains paramount to recognize that the use of surrogate endpoints is imperfect, and care based upon them requires constant physician and patient re-analysis.

Efficacy and safety of fenfluramine in patients with Dravet syndrome: A meta-analysis.

BACKGROUND: Dravet syndrome (DS) is a severe, drug-resistant, developmental epileptic encephalopathy. Despite multiple anti-epileptic drug regimens, the syndrome remains poorly controlled and nearly half of patients still experience at least four tonic-clonic seizure per month. Recently, several clinical trials demonstrated that fenfluramine may provide a significant reduction in convulsive seizure frequency in the treatment of Dravet syndrome. METHODS: A computerized literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar was performed from inception until December 31, 2019. We included randomized placebo-controlled trials for the treatment of Dravet syndrome. We calculated the risk ratio (RR) of ≥50% and 100% reduction seizure frequency from baseline, along with the treatment-related withdrawals and serious adverse events, using the fixed-effect model. Quality assessment of included studies was performed with the Cochrane Collaboration's tool. KEY RESULTS: Two trials with a total of 206 patients were included. The pooled RR of 5.49 (95% CI 3.13-9.65) showed that a significantly greater proportion in the fenfluramine group achieved ≥50% reduction in monthly convulsive seizure frequency (MCSF). As for the complete seizure free rate, the pooled RR of 5.75 (95% CI 1.03-32.07) also demonstrated the favorable efficacy of fenfluramine, even though the difference was not statistically significant (p = 0.046). However, a significantly greater proportion of patients in the fenfluramine group experienced no more than one seizure during the treatment period (RR 13.82, 95% CI 2.68-71.27, p = 0.002). There were no significant differences in withdrawals and serious adverse events between the two treatment groups. No valvular heart disease or pulmonary arterial hypertension was observed in participants. The most common adverse events reported by included trials were diarrhea, fatigue, lethargy, nasopharyngitis, pyrexia, seizure, decreased appetite, and weight loss. CONCLUSIONS: Fenfluramine is an effective antiepileptic drug for pediatric patients with Dravet syndrome, demonstrating clinically meaningful reduction in convulsive frequency, and generally could be well tolerated.

Genetic identification of inherited cystic kidney diseases for implementing precision medicine: a study protocol for a 3-year prospective multicenter cohort study.

BACKGROUND: Inherited cystic kidney disease is a spectrum of disorders in which clusters of renal cysts develop as the result of genetic mutation. The exact methods and pipelines for defining genetic mutations of inherited cystic kidney disease are not clear at this point. This 3-year, prospective, multicenter, cohort study was designed to set up a cohort of Korean patients with inherited cystic kidney disease, establish a customized genetic analysis pipeline for each disease subtype, and identify modifying genes associated with the severity of the disease phenotype. METHODS/DESIGN: From May 2020 to May 2022, we aim to recruit 800 patients and their family members to identify pathogenic mutations. Patients with more than 3 renal cysts in both kidneys are eligible to be enrolled. Cases of simple renal cysts and acquired cystic kidney disease that involve cyst formation as the result of renal failure will be excluded from this study. Demographic, laboratory, and imaging data as well as family pedigree will be collected at baseline. Renal function and changes in total kidney volume will be monitored during the follow-up period. Genetic identification of each case of inherited cystic kidney disease will be performed using a targeted gene panel of cystogenesis-related genes, whole exome sequencing (WES) and/or family segregation studies. Genotype-phenotype correlation analysis will be performed to elucidate the genetic effect on the severity of the disease phenotype. DISCUSSION: This is the first nationwide cohort study on patients with inherited cystic kidney disease in Korea. We will build a multicenter cohort to describe the clinical characteristics of Korean patients with inherited cystic kidney disease, elucidate the genotype of each disease, and demonstrate the genetic effects on the severity of the disease phenotype. TRIAL REGISTRATION: This cohort study was retrospectively registered at the Clinical Research Information Service ( KCT0005580 ) operated by the Korean Center for Disease Control and Prevention on November 5th, 2020.

A Blueprint for the Conduct of Large, Multisite Trials in Telemedicine.

Recent literature supports the efficacy and efficiency of telemedicine in improving various health outcomes despite the wide variability in results. Understanding site-specific issues in the implementation of telemedicine trials for broader replication and generalizability of results is needed. Lessons can be learned from existing trials, and a blueprint can guide researchers to conduct these challenging studies using telemedicine more efficiently and effectively. This viewpoint presents relevant challenges and solutions for conducting multisite telemedicine trials using 7 ongoing and completed studies funded by the Patient-Centered Outcomes Research Institute portfolio of large multisite trials to highlight the challenges in implementing telemedicine trials. Critical issues of ensuring leadership and buy-in, appropriate funding, and diverse and representative trials are identified and described, as well as challenges related to clinical, informatics, regulatory, legal, quality, and billing. The lessons learned from these studies were used to create a blueprint of key aspects to consider for the design and implementation of multisite telemedicine trials.

Utility-Weighted Modified Rankin Scale Scores for the Assessment of Stroke Outcome: Pooled Analysis of 20 000+ Patients.

BACKGROUND AND PURPOSE: Patient-centered care prioritizes patient beliefs and values towards wellbeing. We aimed to map functional status (modified Rankin Scale [mRS] scores) and health-related quality of life on the European Quality of Life 5-dimensional questionnaire (EQ-5D) to derive utility-weighted (UW) stroke outcome measures and test their statistical properties and construct validity. METHODS: UW-mRS scores were derived using linear regression, with mRS as a discrete ordinal explanatory response variable in 8 large international acute stroke trials. Linear regression models were used to validate UW-mRS scores by assessing differences in mean UW-mRS scores between the treatment groups of each trial. To explore the variability in EQ-5D between individual mRS categories, we generated receiver operator characteristic curves for EQ-5D to differentiate between sequential mRS categories and misclassification matrix to classify individual patients into a matched mRS category based on the closest UW-mRS value to their observed individual EQ-5D value. RESULTS: Among 22 946 acute stroke patients, derived UW-mRS across mRS scores 0 to 6 were 0.96, 0.83, 0.72, 0.54, 0.22, -0.18, and 0, respectively. Both UW-mRS and ordinal mRS scores captured divergent treatment effects across all 8 acute stroke trials. The sample sizes required to detect the treatment effects using UW-mRS scores as a continuous variable were almost half that required in trials for a binary cut point on the mRS. Area under receiver operator characteristic curves based on EQ-5D utility values varied from 0.66 to 0.81. Misclassification matrix showed moderate agreement between actual and matched mRS scores (kappa, 0.68 [95% CI, 0.67-0.68]). CONCLUSIONS: Medical strategies that target avoiding dependency may provide maximum benefit in terms of poststroke health-related quality of life. Despite variable differences with mRS scores, the UW-mRS provides efficiency gains as a smaller sample size is required to detect a treatment effect in acute stroke trials through use of continuous scores. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00226096, NCT00716079, NCT01422616, NCT02162017, NCT00120003, NCT02123875. URL: http://ctri.nic.in; Unique identifier: CTRI/2013/04/003557. URL: https://www.isrctn.com; Unique identifier: ISRCTN89712435.

A multicenter trial of a shared DECision Support Intervention for Patients offered implantable Cardioverter-DEfibrillators: DECIDE-ICD rationale, design, Medicare changes, and pilot data.

Shared decision making (SDM) facilitates delivery of medical therapies that are in alignment with patients' goals and values. Medicare national coverage decision for several interventions now includes SDM mandates, but few have been evaluated in nationwide studies. Based upon a detailed needs assessment with diverse stakeholders, we developed pamphlet and video patient decision aids (PtDAs) for implantable cardioverter/defibrillator (ICD) implantation, ICD replacement, and cardiac resynchronization therapy with defibrillation to help patients contemplate, forecast, and deliberate their options. These PtDAs are the foundation of the Multicenter Trial of a Shared Decision Support Intervention for Patients Offered Implantable Cardioverter-Defibrillators (DECIDE-ICD), a multicenter, randomized trial sponsored by the National Heart, Lung, and Blood Institute aimed at understanding the effectiveness and implementation of an SDM support intervention for patients considering ICDs. Finalization of a Medicare coverage decision mandating the inclusion of SDM for new ICD implantation occurred shortly after trial initiation, raising novel practical and statistical considerations for evaluating study end points. METHODS/DESIGN: A stepped-wedge randomized controlled trial was designed, guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) planning and evaluation framework using an effectiveness-implementation hybrid type II design. Six electrophysiology programs from across the United States will participate. The primary effectiveness outcome is decision quality (defined by knowledge and values-treatment concordance). Patients with heart failure who are clinically eligible for an ICD are eligible for the study. Target enrollment is 900 participants. DISCUSSION: Study findings will provide a foundation for implementing decision support interventions, including PtDAs, with patients who have chronic progressive illness and are facing decisions involving invasive, preference-sensitive therapy options.