Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies

Large-scale, case-control genome-wide association studies (GWASs) have revealed genetic variations associated with diverse neurological and psychiatric disorders. Recent advances in neuroimaging and genomic databases of large healthy and diseased cohorts have empowered studies to characterize effects of the discovered genetic factors on brain structure and function, implicating neural pathways and genetic mechanisms in the underlying biology. However, the unprecedented scale and complexity of the imaging and genomic data requires new advanced biomedical data science tools to manage, process and analyze the data. In this work, we introduce Neuroimaging PheWAS (phenome-wide association study): a web-based system for searching over a wide variety of brain-wide imaging phenotypes to discover true system-level gene-brain relationships using a unified genotype-to-phenotype strategy. This design features a user-friendly graphical user interface (GUI) for anonymous data uploading, study definition and management, and interactive result visualizations as well as a cloud-based computational infrastructure and multiple state-of-art methods for statistical association analysis and multiple comparison correction. We demonstrated the potential of Neuroimaging PheWAS with a case study analyzing the influences of the apolipoprotein E (APOE) gene on various brain morphological properties across the brain in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Benchmark tests were performed to evaluate the system's performance using data from UK Biobank. The Neuroimaging PheWAS system is freely available. It simplifies the execution of PheWAS on neuroimaging data and provides an opportunity for imaging genetics studies to elucidate routes at play for specific genetic variants on diseases in the context of detailed imaging phenotypic data.

Optimizing drug inventory management with a web-based information system: The TBTC Study 31/ACTG A5349 experience

INTRODUCTION

Efficient management of study drug inventory shipments is critical to keep research sites enrolling into multisite clinical treatment trials. A standard manual drug-management process used by the Tuberculosis Trials Consortium (TBTC), did not accommodate import permit approval timelines, shipment transit-times and time-zone differences. We compared a new web-based solution with the manual process, during an international 34-site clinical trial conducted by the TBTC and the AIDS Clinical Trials Group (ACTG); TBTC Study 31/ACTG A5349.

MATERIAL AND METHODS

We developed and implemented a technological solution by integrating logistical and regulatory requirements for drug importation with statistical simulations that estimated stock-out times in an online Drug Management Module (DMM). We measured the average shipment-related drug stock-outs and time to drug availability, to assess the efficiency of the DMM compared to the manual approach.

RESULTS

An Interrupted Time-Series (ITS) analysis showed a 15.4% [p-value = 0.03; 95% C.I. (-28.8%, -2.0%)] reduction in average shipment-related study drug stock-out after DMM implementation. The DMM streamlined the restocking process at study sites, reducing median transit-time for sites associated with a depot by 2 days [95% C.I. (-3.0, -1.0)]. Under the DMM, study drugs were available for treatment assignment on the day received, compared to one day after receipt under the manual process.

DISCUSSION

The DMM provided TBTC's Data and Coordinating Center and site staff with more efficient procedures to manage and consistently maintain study drug inventory at enrolling sites. This DMM framework can improve efficiency in future multicenter clinical trials.

TRIAL REGISTRATION

This trial was registered with ClinicalTrials.gov (Identifier: NCT02410772) on April 8, 2015.

Web-based personalised information and support for patients with a neuroendocrine tumour: randomised controlled trial

Background

Patients with a neuroendocrine tumour (NET) frequently have physical and psychosocial complaints. Aim of this study is to determine whether a web-based, personalised information and support system (WINS) reduces distress and/or improves patients’ perception of and satisfaction with information received.

Methods

Patients with NET, stratified for those newly diagnosed (< 6 months, n = 28) and with a longer history of disease (n = 74), were randomised between standard care (n = 49) and intervention, consisting of access to WINS (n = 53). Primary outcome was change of distress and satisfaction with perceived information measured with the distress thermometer and problem list and the QoL questionnaire (QLQ)-INFO25. The intervention group also completed a questionnaire based on the technical acceptance model (TAM).

Results

We observed no difference in distress slope and slope of median global score on perceived information and satisfaction between the intervention and control group. Interestingly, 55% of patients wished to receive more information at baseline.

Conclusions

In a population of NET patients, access to WINS did not improve indicators for distress, perception of information and satisfaction with information received, more than standard care only. Despite the need for more information, the WINS does not have added value to the information and care provided by health care professionals.

Clinical trial registration

ClinicalTrials.gov (NCT02472678). Registered 6th Jan 2015. Retrospectively registered 1st May 2017.

Electronic supplementary material

The online version of this article (10.1186/s13023-019-1035-3) contains supplementary material, which is available to authorized users.

iDEAS: A web-based system for dry eye assessment

BACKGROUND AND OBJECTIVES

Dry eye disease is a public health problem, whose multifactorial etiology challenges clinicians and researchers making necessary the collaboration between different experts and centers. The evaluation of the interference patterns observed in the tear film lipid layer is a common clinical test used for dry eye diagnosis. However, it is a time-consuming task with a high degree of intra- as well as inter-observer variability, which makes the use of a computer-based analysis system highly desirable. This work introduces iDEAS (Dry Eye Assessment System), a web-based application to support dry eye diagnosis.

METHODS

iDEAS provides a framework for eye care experts to collaboratively work using image-based services in a distributed environment. It is composed of three main components: the web client for user interaction, the web application server for request processing, and the service module for image analysis. Specifically, this manuscript presents two automatic services: tear film classification, which classifies an image into one interference pattern; and tear film map, which illustrates the distribution of the patterns over the entire tear film.

RESULTS

iDEAS has been evaluated by specialists from different institutions to test its performance. Both services have been evaluated in terms of a set of performance metrics using the annotations of different experts. Note that the processing time of both services has been also measured for efficiency purposes.

CONCLUSIONS

iDEAS is a web-based application which provides a fast, reliable environment for dry eye assessment. The system allows practitioners to share images, clinical information and automatic assessments between remote computers. Additionally, it save time for experts, diminish the inter-expert variability and can be used in both clinical and research settings.

The wisdom of crowds in action: Forecasting epidemic diseases with a web-based prediction market system

BACKGROUND

The quest for an effective system capable of monitoring and predicting the trends of epidemic diseases is a critical issue for communities worldwide. With the prevalence of Internet access, more and more researchers today are using data from both search engines and social media to improve the prediction accuracy. In particular, a prediction market system (PMS) exploits the wisdom of crowds on the Internet to effectively accomplish relatively high accuracy.

OBJECTIVE

This study presents the architecture of a PMS and demonstrates the matching mechanism of logarithmic market scoring rules. The system was implemented to predict infectious diseases in Taiwan with the wisdom of crowds in order to improve the accuracy of epidemic forecasting.

METHODS

The PMS architecture contains three design components: database clusters, market engine, and Web applications. The system accumulated knowledge from 126 health professionals for 31 weeks to predict five disease indicators: the confirmed cases of dengue fever, the confirmed cases of severe and complicated influenza, the rate of enterovirus infections, the rate of influenza-like illnesses, and the confirmed cases of severe and complicated enterovirus infection.

RESULTS

Based on the winning ratio, the PMS predicts the trends of three out of five disease indicators more accurately than does the existing system that uses the five-year average values of historical data for the same weeks. In addition, the PMS with the matching mechanism of logarithmic market scoring rules is easy to understand for health professionals and applicable to predict all the five disease indicators.

CONCLUSIONS

The PMS architecture of this study affords organizations and individuals to implement it for various purposes in our society. The system can continuously update the data and improve prediction accuracy in monitoring and forecasting the trends of epidemic diseases. Future researchers could replicate and apply the PMS demonstrated in this study to more infectious diseases and wider geographical areas, especially the under-developed countries across Asia and Africa.

Assessing the Effects of Participant Preference and Demographics in the Usage of Web-based Survey Questionnaires by Women Attending Screening Mammography in British Columbia

BACKGROUND

Increased usage of Internet applications has allowed for the collection of patient reported outcomes (PROs) and other health data through Web-based communication and questionnaires. While these Web platforms allow for increased speed and scope of communication delivery, there are certain limitations associated with this technology, as survey mode preferences vary across demographic groups.

OBJECTIVE

To investigate the impact of demographic factors and participant preferences on the use of a Web-based questionnaire in comparison with more traditional methods (mail and phone) for women participating in screening mammography in British Columbia, Canada.

METHODS

A sample of women attending the Screening Mammography Program of British Columbia (SMPBC) participated in a breast cancer risk assessment project. The study questionnaire was administered through one of three modes (ie, telephone, mail, or website platform). Survey mode preferences and actual methods of response were analyzed for participants recruited from Victoria General Hospital. Both univariate and multivariate analyses were used to investigate the association of demographic factors (ie, age, education level, and ethnicity) with certain survey response types.

RESULTS

A total of 1192 women successfully completed the study questionnaire at Victoria General Hospital. Mail was stated as the most preferred survey mode (509/1192, 42.70%), followed by website platform (422/1192, 35.40%), and telephone (147/1192, 12.33%). Over 80% (955/1192) of participants completed the questionnaire in the mode previously specified as their most preferred; mail was the most common method of response (688/1192, 57.72%). Mail was also the most preferred type of questionnaire response method when participants responded in a mode other than their original preference. The average age of participants who responded via the Web-based platform (age 52.9, 95% confidence interval [CI] 52.1-53.7) was significantly lower than those who used mail and telephone methods (age 55.9, 95% CI 55.2-56.5; P<.001); each decade of increased age was associated with a 0.97-fold decrease in the odds of using the website platform (P<.001). Web-based participation was more likely for those who completed higher levels of education; each interval increase leading to a 1.83 increase in the odds of website platform usage (P<.001). Ethnicity was not shown to play a role in participant preference for the website platform (P=.96).

CONCLUSIONS

It is beneficial to consider participant survey mode preference when planning to collect PROs and other patient health data. Younger participants and those of higher education level were more likely to use the website platform questionnaire; Web-based participation failed to vary across ethnic group. Because mail questionnaires were still the most preferred survey mode, it will be important to employ strategies, such as user-friendly design and Web-based support, to ensure that the patient feedback being collected is representative of the population being served.