OPERATIONAL LESSONS FROM THE PATHWAYS TO DESISTANCE PROJECT

Implementing a large, longitudinal study of any sample is a major undertaking. The challenges are compounded when the study involves multiple sites and a high-risk sample. This article outlines the methodology for the Pathways to Desistance study, a multisite, longitudinal study of serious juvenile offenders, and discusses the key operational decisions with the greatest impact on the study design.

Decentralized and reproducible geocoding and characterization of community and environmental exposures for multisite studies

Objective

Geocoding and characterizing geographic, community, and environmental characteristics of study participants is frequently done in epidemiological studies. However, participant addresses are identifiable protected health information (PHI) and geocoding must be conducted in a Health Insurance Portability and Accountability Act–compliant manner. Our objective was to create a software application for this process that addresses limitations in current approaches.

Materials and Methods

We used a containerization platform to create DeGAUSS (Decentralized Geomarker Assessment for Multi-Site Studies), a software application that facilitates reproducible geocoding and geomarker assessment while maintaining the confidentiality of PHI. To validate the software, 215 350 addresses in Hamilton County, Ohio, were geocoded using DeGAUSS, ArcGIS, Google, and SAS and compared to a gold-standard approach. We distributed the DeGAUSS software to sites in an ongoing multisite study (Electronic Medical Records and Genomics, or eMERGE), and individual sites independently geocoded and assigned median census tract–level income and distance to nearest major roadway to their participants’ addresses, removed associated PHI, and returned deidentified data.

Results

Within a multisite study, 52 244 study participants’ addresses across 5 sites were geocoded with a median distance to roadway of 10 022m and a median census tract income of $57 266, demonstrating the feasibility of DeGAUSS within a multisite study. Compared to other commonly used geocoding platforms, DeGAUSS had similar geocoding and geomarker assessment accuracies.

Conclusion

The open source DeGAUSS software overcomes multiple challenges in the use of address data in multisite studies and also serves as a more general reproducible research tool for geocoding and geomarker assessment.

How reliable are gray matter disruptions in specific reading disability across multiple countries and languages? Insights from a large-scale voxel-based morphometry study

The neural basis of specific reading disability (SRD) remains only partly understood. A dozen studies have used voxel-based morphometry (VBM) to investigate gray matter volume (GMV) differences between SRD and control children, however, recent meta-analyses suggest that few regions are consistent across studies. We used data collected across three countries (France, Poland, and Germany) with the aim of both increasing sample size (236 SRD and controls) to obtain a clearer picture of group differences, and of further assessing the consistency of the findings across languages. VBM analysis reveals a significant group difference in a single cluster in the left thalamus. Furthermore, we observe correlations between reading accuracy and GMV in the left supramarginal gyrus and in the left cerebellum, in controls only. Most strikingly, we fail to replicate all the group differences in GMV reported in previous studies, despite the superior statistical power. The main limitation of this study is the heterogeneity of the sample drawn from different countries (i.e., speaking languages with varying orthographic transparencies) and selected based on different assessment batteries. Nevertheless, analyses within each country support the conclusions of the cross-linguistic analysis. Explanations for the discrepancy between the present and previous studies may include: (1) the limited suitability of VBM to reveal the subtle brain disruptions underlying SRD; (2) insufficient correction for multiple statistical tests and flexibility in data analysis, and (3) publication bias in favor of positive results. Thus the study echoes widespread concerns about the risk of false-positive results inherent to small-scale VBM studies.

The Nordic long-term OCD treatment study (NordLOTS): rationale, design, and methods

BACKGROUND

This paper describes and discusses the methodology of the Nordic long-term OCD-treatment study (NordLOTS). The purpose of this effectiveness study was to study treatment outcome of CBT, to identify CBT non- or partial responders and to investigate whether an increased number of CBT-sessions or sertraline treatment gives the best outcome; to identify treatment refractory patients and to investigate the outcome of aripiprazole augmentation; to study the outcome over a three year period for each responder including the risk of relapse, and finally to study predictors, moderators and mediators of treatment response.

METHODS

Step 1 was an open and uncontrolled clinical trial with CBT, step 2 was a controlled, randomised non-blinded study of CBT non-responders from step 1. Patients were randomized to receive either sertraline plus CBT-support or continued and modified CBT. In step 3 patients who did not respond to either CBT or sertraline were treated with aripiprazole augmentation to sertraline.

CONCLUSIONS

This multicenter trial covering three Scandinavian countries is going to be the largest CBT-study for paediatric OCD to date. It is not funded by industry and tries in the short and long-term to answer the question whether further CBT or SSRI is better in CBT non-responders.

A COMPREHENSIVE EXAMINATION OF WHITE MATTER TRACTS AND CONNECTOMETRY IN MAJOR DEPRESSIVE DISORDER

BACKGROUND

Major depressive disorder (MDD) is a debilitating disorder characterized by widespread brain abnormalities. The literature is mixed as to whether or not white matter abnormalities are associated with MDD. This study sought to examine fractional anisotropy (FA) in white matter tracts in individuals with MDD using diffusion tensor imaging (DTI).

METHODS

139 participants with MDD and 39 healthy controls (HC) in a multisite study were included. DTI scans were acquired in 64 directions and FA was determined in the brain using four methods: region of interest (ROI), tract-based spatial statistics (TBSS), and diffusion tractography. Diffusion connectometry was used to identify white matter pathways associated with MDD.

RESULTS

There were no significant differences when comparing FA in MDD and HC groups using any method. In the MDD group, there was a significant relationship between depression severity and FA in the right medial orbitofrontal cortex, and between age of onset of MDD and FA in the right caudal anterior cingulate cortex using the ROI method. There was a significant relationship between age of onset and connectivity in the thalamocortical radiation, inferior longitudinal fasciculus, and cerebellar tracts using diffusion connectometry.

CONCLUSIONS

The lack of group differences in FA and connectometry analysis may result from the clinically heterogenous nature of MDD. However, the relationship between FA and depression severity may suggest a state biomarker of depression that should be investigated as a potential indicator of response. Age of onset may also be a significant clinical feature to pursue when studying white matter tracts.

Differentiation of schizophrenia using structural MRI with consideration of scanner differences: A real-world multisite study

AIM

Neuroimaging studies have revealed that patients with schizophrenia exhibit reduced gray matter volume in various regions. With these findings, various studies have indicated that structural MRI can be useful for the diagnosis of schizophrenia. However, multisite studies are limited. Here, we evaluated a simple model that could be used to differentiate schizophrenia from control subjects considering MRI scanner differences employing voxel-based morphometry.

METHODS

Subjects were 541 patients with schizophrenia and 1252 healthy volunteers. Among them, 95 patients and 95 controls (Dataset A) were used for the generation of regions of interest (ROI), and the rest (Dataset B) were used to evaluate our method. The two datasets were comprised of different subjects. Three-dimensional T1-weighted MRI scans were taken for all subjects and gray-matter images were extracted. To differentiate schizophrenia, we generated ROI for schizophrenia from Dataset A. Then, we determined volume within the ROI for each subject from Dataset B. Using the extracted volume data, we calculated a differentiation feature considering age, sex, and intracranial volume for each MRI scanner. Receiver-operator curve analyses were performed to evaluate the differentiation feature.

RESULTS

The area under the curve ranged from 0.74 to 0.84, with accuracy from 69% to 76%. Receiver-operator curve analysis with all samples revealed an area under the curve of 0.76 and an accuracy of 73%.

CONCLUSION

We moderately successfully differentiated schizophrenia from control using structural MRI from differing scanners from multiple sites. This could be useful for applying neuroimaging techniques to clinical settings for the accurate diagnosis of schizophrenia.

Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks

BACKGROUND

Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.

AIMS

To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.

METHOD

We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.

RESULTS

We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19-85.74%; sensitivity, 75.31-89.29% and area under the receiver operating characteristic curve, 0.797-0.909.

CONCLUSIONS

These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

Application of a Machine Learning Algorithm for Structural Brain Images in Chronic Schizophrenia to Earlier Clinical Stages of Psychosis and Autism Spectrum Disorder: A Multiprotocol Imaging Dataset Study

BACKGROUND AND HYPOTHESIS

Machine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs).

STUDY DESIGN

Total 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat.

STUDY RESULTS

The accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%).

CONCLUSION

We built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.

Does 'Time Together' increase quality of interaction and decrease stress? A study protocol of a multisite nursing intervention in psychiatric inpatient care, using a mixed method approach

INTRODUCTION

Despite the long-known significance of the nurse-patient relationship, research in psychiatric inpatient care still reports unfulfilled expectations of, and difficulties in, interactions and relationships between patients and staff. Interventions that create structures to allow quality interactions between patients and staff are needed to solve these problems. The aim of this project is to test effects of the nursing intervention Time Together and to evaluate the intervention process.

METHODS AND ANALYSIS

This is a multisite study with a single-system experimental design using frequent measures. The primary outcomes are quality interactions for patients and perceived stress for staff. Secondary outcomes are levels of symptoms of anxiety and depression for patients and stress of conscience for staff. A process evaluation is performed to describe contextual factors and experiences. Data are collected using questionnaires, participant observations and semistructured interviews. For analysis of quantitative data, both visual and statistical methods will be used. Qualitative data will be analysed using qualitative content analysis.

ETHICS AND DISSEMINATION

Ethical approval was granted by the Ethical Review Board in the region (Dnr 2016/339-31). The findings will contribute to the development of nursing interventions in general, but more specifically to the development of the intervention. This is relevant both nationally and internationally as similar interventions are needed but sparse. The findings will be disseminated through conference presentations and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

NCT02981563.

Reflections on the Use of Audio Diaries to Access Young People's Lived Experiences of HIV in Zimbabwe

This methodological article reflects on the contribution audio diaries can make to accessing important, and commonly silenced, dimensions of the lived experience of growing up with HIV and their acceptability to children. Audio diaries were used by 12 young people, aged 11 to 13 years, as part of a longitudinal qualitative study embedded within the Anti-Retroviral Research for Watoto (ARROW) clinical trial. The method provided an alternative means for young people to express detailed reflections on their day-to-day encounters, as well as ordinarily silenced topics, including hidden and suppressed emotions regarding the circumstance surrounding their perinatal infection. Although the audio diary has great potential as method, its efficacy rests on young people's understanding of how to use it. There are ethical challenges around maintaining confidentiality while participants are in possession of the diaries and provision of appropriate support. The technology used in the study was in many ways cumbersome compared with opportunities increasingly available.

White matter tract alterations in schizophrenia identified by DTI-based probabilistic tractography: a multisite harmonisation study

INTRODUCTION

It has been suggested that schizophrenia involves dysconnectivity between functional brain regions and also the white matter structural disorganisation. Thus, diffusion tensor imaging (DTI) has widely been used for studying schizophrenia. However, most previous studies have used the region of interest (ROI) based approach. We, therefore, performed the probabilistic tractography method in this study to reveal the alterations of white matter tracts in the schizophrenia brain.

METHODS

A total of four different datasets consisted of 189 patients with schizophrenia and 213 healthy controls were investigated. We performed retrospective harmonisation of raw diffusion MRI data by dMRIharmonisation and used the FMRIB Software Library (FSL) for probabilistic tractography. The connectivities between different ROIs were then compared between patients and controls. Furthermore, we evaluated the relationship between the connection probabilities and the symptoms and cognitive measures in patients with schizophrenia.

RESULTS

After applying Bonferroni correction for multiple comparisons, 11 different tracts showed significant differences between patients with schizophrenia and healthy controls. Many of these tracts were associated with the basal ganglia or cortico-striatal structures, which aligns with the current literature highlighting striatal dysfunction. Moreover, we found that these tracts demonstrated statistically significant relationships with few cognitive measures related to language, executive function, or processing speed.

CONCLUSION

We performed probabilistic tractography using a large, harmonised dataset of diffusion MRI data, which enhanced the statistical power of our study. It is important to note that most of the tracts identified in this study, particularly callosal and cortico-striatal streamlines, have been previously implicated in schizophrenia within the current literature. Further research with harmonised data focusing specifically on these brain regions could be recommended.

Negative effects during multicomponent group-based treatment: A multisite study

Objective Negative effects (NEs) in group treatments remain an under-researched area. This study aimed to explore the prevalence of various types of NEs in a multicomponent group-based treatment and to determine their predictors. Method: A total of 330 patients participating in a multicomponent group-based treatment were recruited across seven clinical sites. At the end of treatment, the Negative Effects Questionnaire (NEQ) was used to measure NEs. Item-level descriptive analysis was conducted to explore the prevalence of various types of NEs, and structural equation modeling was used to determine predictors of these NEs. Results: The most frequently reported type of NEs was the worsening of symptoms, and the single most frequently reported item was the resurfacing of unpleasant memories. Predictors of NEs included the overall distress level, alexithymia, attachment avoidance, low working alliance, problem actuation, and worse outcomes; psychological mindedness was a protective factor. Conclusion: Patients who experience higher levels of distress at the beginning of treatment, who perceive the group working alliance as problematic, and who experience high in-session emotional arousal related to their problem seem to be especially prone to reporting NEs. Furthermore, the findings do not support the assumption that NEs are a prerequisite for therapeutic change.Trial registration: ISRCTN.org identifier: ISRCTN13532466.

International evaluation study of a highly efficient culture assay for detection of residual human pluripotent stem cells in cell therapies

Aim & methods: The Health and Environmental Sciences Institute Cell Therapy-TRAcking, Circulation & Safety Technical Committee launched an international, multisite study to evaluate the sensitivity and reproducibility of the highly efficient culture (HEC) assay, an in vitro assay to detect residual undifferentiated human pluripotent stem cells (hPSCs) in cell therapy products. Results: All facilities detected colonies of human induced pluripotent stem cells (hiPSCs) when five hiPSCs were spiked into 1 million hiPSC-derived cardiomyocytes. Spiking with a trace amount of hiPSCs revealed that repeatability accounts for the majority of reproducibility while the true positive rate was high. Conclusion: The results indicate that the HEC assay is highly sensitive and robust and can be generally applicable for tumorigenicity evaluation of hPSC-derived cell therapy products.

Planning and managing a complex multisite study in the age of technology

A 2-year long, multisite research study that evaluated cardiopulmonary resuscitation skill decay among nursing students was conducted at 10 schools of nursing across the United States. The study was conducted in two phases and required carefully timed sessions for skill performance. Multisite studies in nursing education need to be carefully planned. Time delays should be anticipated with processes and Institutional Review Board protocols across sites. All team members were trained and consistently supported during the entire study. While challenges and obstacles were identified, innovative solutions were implemented that assisted the research team to successfully complete the study. The use of new and existing technology allowed the team to surmount many of the challenges encountered in this study. The purpose of this article is to describe the logistics, processes, challenges, and lessons learned related to conducting a complex multisite study.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.