Antimicrobial Resistance.

IMPORTANCE: The development of antibiotics is considered among the most important advances of modern science. Antibiotics have saved millions of lives. However, antimicrobial resistance (AMR) threatens this progress and presents significant risks to human health. OBJECTIVE: To identify factors associated with AMR, the current epidemiology of important resistant organisms, and possible solutions to the AMR problem. DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: PubMed (2000-2016), NIH REPORTER, and ClinicalTrials.gov databases were searched for articles and entries related to AMR, focusing on epidemiology, clinical effects of AMR, discovery of novel agents to treat AMR bacterial infections, and nonpharmacological strategies to eliminate or modify AMR bacteria. In addition to articles and entries found in these databases, selected health policy reports and public health guidance documents were reviewed. Of 217 articles, databases, and reports identified, 103 were selected for review. RESULTS: The increase in AMR has been driven by a diverse set of factors, including inappropriate antibiotic prescribing and sales, use of antibiotics outside of the health care sector, and genetic factors intrinsic to bacteria. The problem has been exacerbated by inadequate economic incentives for pharmaceutical development of new antimicrobial agents. A range of specific AMR concerns, including carbapenem- and colistin-resistant gram-negative organisms, pose a clinical challenge. Alternative approaches to address the AMR threat include new methods of antibacterial drug identification and strategies that neutralize virulence factors. CONCLUSIONS AND RELEVANCE: Antimicrobial resistance poses significant challenges for current clinical care. Modified use of antimicrobial agents and public health interventions, coupled with novel antimicrobial strategies, may help mitigate the effect of multidrug-resistant organisms in the future.

Evaluating protocol lifecycle time intervals in HIV/AIDS clinical trials.

BACKGROUND: Identifying efficacious interventions for the prevention and treatment of human diseases depends on the efficient development and implementation of controlled clinical trials. Essential to reducing the time and burden of completing the clinical trial lifecycle is determining which aspects take the longest, delay other stages, and may lead to better resource utilization without diminishing scientific quality, safety, or the protection of human subjects. PURPOSE: In this study, we modeled time-to-event data to explore relationships between clinical trial protocol development and implementation times, as well as to identify potential correlates of prolonged development and implementation. METHODS: We obtained time interval and participant accrual data from 111 interventional clinical trials initiated between 2006 and 2011 by National Institutes of Health's HIV/AIDS Clinical Trials Networks. We determined the time (in days) required to complete defined phases of clinical trial protocol development and implementation. Kaplan-Meier estimates were used to assess the rates at which protocols reached specified terminal events, stratified by study purpose (therapeutic, prevention) and phase group (pilot/phase I, phase II, and phase III/IV). We also examined several potential correlates to prolonged development and implementation intervals. RESULTS: Even though phase grouping did not determine development or implementation times of either therapeutic or prevention studies, overall we observed wide variation in protocol development times. Moreover, we detected a trend toward phase III/IV therapeutic protocols exhibiting longer developmental (median 2½ years) and implementation times (>3 years). We also found that protocols exceeding the median number of days for completing the development interval had significantly longer implementation. LIMITATIONS: The use of a relatively small set of protocols may have limited our ability to detect differences across phase groupings. Some timing effects present for a specific study phase may have been masked by combining protocols into phase groupings. Presence of informative censoring, such as withdrawal of some protocols from development if they began showing signs of lost interest among investigators, complicates interpretation of Kaplan-Meier estimates. Because this study constitutes a retrospective examination over an extended period of time, it does not allow for the precise identification of relative factors impacting timing. CONCLUSION: Delays not only increase the time and cost to complete clinical trials but they also diminish their usefulness by failing to answer research questions in time. We believe that research analyzing the time spent traversing defined intervals across the clinical trial protocol development and implementation continuum can stimulate business process analyses and re-engineering efforts that could lead to reductions in the time from clinical trial concept to results, thereby accelerating progress in clinical research.

Strengthening biostatistics resources in sub-Saharan Africa: research collaborations through U.S. partnerships.

On September 30, 2009, the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH) conducted a workshop on strengthening biostatistics resources in sub-Saharan Africa (SSA). An increase in global spending on health research over the last decade has boosted funds available to conduct biomedical research in low- to mid-income countries. The HIV/AIDS pandemic, the re-emergence of malaria and tuberculosis, and other emerging infectious agents are major driving forces behind the increase in biomedical research and clinical care programs (clinical trials, observational studies and, other public health programs) in SSA (Exp. Biol. Med. 2008; 233:277-285). In addition, the increased engagement of the United States (U.S.) government through the Global Health Initiative, which expands the traditional focus beyond infectious diseases to other causes of poor health and to the recognition of need the to strengthen health systems for a sustainable response, only increases the need for in-depth in-country expertise in all aspects of biomedical research (White House Press Release, 2009). In this workshop, researchers both from the U.S. and SSA were invited to discuss their collaborative work, to discuss ways in which biostatistical activities are carried out within their research projects, and to identify both general and specific needs for capacity building in biostatistics. Capacity building discussions highlighted the critical need to increase the number of well-trained in-country biostatisticians, both to participate in ongoing studies and to contribute to an infrastructure that can produce the next generation of biostatistical researchers.

Data and safety monitoring policy for National Institute of Allergy and Infectious Diseases clinical trials.

BACKGROUND: Historically, four divisions of the National Institute of Allergy and Infectious Diseases (NIAID) that manage clinical trials and oversee data and safety monitoring have operated fairly autonomously with respect to their approaches to Data and Safety Monitoring Board (DSMB) operations. We recognized the need for a revised policy on DSMB operations in an effort to encourage greater harmonization of procedures across the four divisions. PURPOSE: The purpose of this article is to describe the considerations that motivated the development of the new policy, summarize current DSMB policies and ongoing harmonization efforts across the four divisions, and offer some recommendations for DSMB operations in the hope that other organizations may benefit from our experience. METHODS: From 2005 to 2009, a working group undertook a review of DSMB responsibilities, policies, and operations. We analyzed and summarized the final policy document that the working group produced, gathered data describing current DSMB activities, and developed a tabular, cross-sectional overview highlighting how divisions are harmonizing their DSMB operations. RESULTS: In 2010, there were 44 DSMBs in NIAID monitoring 169 protocols, and those DSMBs conducted 209 reviews of the protocols. Review and analysis of DSMB practices across the four divisions have led to recommendations for efficient and successful DSMB operations: adopt an inclusive approach, whereby the trial investigators assist in the process of forming and utilizing DSMBs; structures other than DSMBs can often provide many of the features of DSMBs but with greater flexibility in membership, access to interim data, and scheduling; the trial protocol should specify what safety and other concerns should trigger a DSMB review and what data should be included in prespecified reviews; present data in thoughtful and user-friendly ways that answer specific questions; allow sufficient time to plan for working with the DSMB. LIMITATIONS: We recognize that NIAID's specific circumstances and DSMB policy may not apply to the operation of DSMBs in every organization. Nevertheless, we believe that useful lessons can be learned from our experiences and efforts toward harmonization. CONCLUSIONS: Homogeneity in DSMB operations and management has appeal as a matter of organizational policy and efficiency. Some limited flexibility, as long as it honors fundamental principles of independence, confidentiality of interim trial results, and clear lines of reporting and approval, may be appropriate on occasion. NIAID's 2009 institute-level policy established a collective understanding of the important contribution that DSMBs make to the responsible conduct of clinical trials. Thinking will continue to evolve, leading to further policy refinements and the continued assurance of patient safety in our clinical trials.

Fostering community understanding of sufficient benefit and early stopping for a phase 2B HIV prevention clinical trial in Africa.

BACKGROUND: Most trials of interventions are designed to address the traditional null hypothesis of no benefit. VOICE, a phase 2B HIV prevention trial funded by NIH and conducted in Africa, is designed to assess if the intervention will prevent a substantial fraction of infections. Planned interim analysis may provide conclusive evidence against the traditional null hypothesis without establishing substantial benefit. At this interim point, the Data and Safety Monitoring Board would then face the dilemma of knowing the product has some positive effect, but perhaps not as great an effect as the protocol has declared necessary. PURPOSE: In March 2008, NIH program staff recommended that the VOICE protocol team discuss the stopping rules with stakeholders prior to initiating the protocol. The goals of the workshop were to inform community representatives about the potential ethical dilemma associated with stopping rules and engage in dialogue about these issues. We describe the resulting community consultation and summarize the outcomes. METHODS: A 2-day workshop was convened with the goal of having a clear and transparent consultation with the stakeholders around the question, 'Given emerging evidence that a product could prevent some infections, would the community support a decision to continue accruing to the trial?' Participants included research staff and community stakeholders. Lectures with visual aids, discussions, and exercises using interactive learning tasks were used, with a focus on statistics and interpreting data from trials, particularly interim data. RESULTS: Results of oral and written evaluations by participants were reviewed. The feedback was mostly positive, with some residual confusion regarding statistical concepts. However, discussions with attendees later revealed that not all felt prepared to engage fully in the workshop. LIMITATIONS: This was the presenters' first experience facilitating a formal discussion with an audience that had no advanced science, research, or mathematics training. Community representatives' concern regarding speaking for their communities without consulting them also created a challenge for the workshop. CONCLUSIONS: Open discussion around trial stopping rules requires that all discussants have an understanding of trial design concepts and feel a sense of empowerment to ask and answer questions. The VOICE CWG workshop was a first step toward the goal of open discussion regarding trial stopping rules and interim results for the study; however, ongoing education and dialogue must occur to ensure that all stakeholders fully participate in the process.

Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study.

BACKGROUND: Challenging behaviors are prevalent among individuals with autism spectrum disorder; however, research exploring the impact of challenging behaviors on treatment response is lacking. OBJECTIVE: The purpose of this study was to identify types of autism spectrum disorder based on engagement in different challenging behaviors and evaluate differences in treatment response between groups. METHODS: Retrospective data on challenging behaviors and treatment progress for 854 children with autism spectrum disorder were analyzed. Participants were clustered based on 8 observed challenging behaviors using k means, and multiple linear regression was performed to test interactions between skill mastery and treatment hours, cluster assignment, and gender. RESULTS: Seven clusters were identified, which demonstrated a single dominant challenging behavior. For some clusters, significant differences in treatment response were found. Specifically, a cluster characterized by low levels of stereotypy was found to have significantly higher levels of skill mastery than clusters characterized by self-injurious behavior and aggression (P<.003). CONCLUSIONS: These findings have implications on the treatment of individuals with autism spectrum disorder. Self-injurious behavior and aggression were prevalent among participants with the worst treatment response, thus interventions targeting these challenging behaviors may be worth prioritizing. Furthermore, the use of unsupervised machine learning models to identify types of autism spectrum disorder shows promise.

Ehrlichiosis and anaplasmosis subcommittee report to the Tick-borne Disease Working Group.

Ehrlichioses and anaplasmosis have undergone dramatic increases in incidence, and the geographic ranges of their occurrence and vectors have also expanded. There is marked underreporting of these diseases owing to deficient physician awareness and knowledge of the illnesses as well as limited access to appropriate diagnostic tests. Human monocytic ehrlichiosis and anaplasmosis are life threatening diseases with estimated case fatality rates of 2.7 and 0.3%, respectively. However, knowledge of their full range of signs and symptoms is incomplete, and the incidence of subclinical infections is unknown. Currently available laboratory diagnostic methods are poorly utilized, and with the exception of nucleic acid amplification tests are not useful for diagnosis during the acute stage of illness when timely treatment is needed. The Ehrlichiosis and Anaplasmosis Subcommittee of the Tick-Borne Disease Working Group recommended active clinical surveillance to determine the true incidence, full clinical spectrum, and risk factors for severe illness, as well as standardized surveillance of ticks for these pathogens, and enhanced education of primary medical caregivers and the public regarding these diseases. The subcommittee identified the needs to develop sensitive, specific acute stage diagnostic tests for local clinical laboratories and point-of-care testing, to develop approaches for utilizing electronic medical records, data mining, and artificial intelligence for assisting early diagnosis and treatment, and to develop adjunctive therapies for severe disease.

Pyrosequencing study of fecal microflora of autistic and control children.

There is evidence of genetic predisposition to autism, but the percent of autistic subjects with this background is unknown. It is clear that other factors, such as environmental influences, may play a role in this disease. In the present study, we have examined the fecal microbial flora of 33 subjects with various severities of autism with gastrointestinal symptoms, 7 siblings not showing autistic symptoms (sibling controls) and eight non-sibling control subjects, using the bacterial tag encoded FLX amplicon pyrosequencing (bTEFAP) procedure. The results provide us with information on the microflora of stools of young children and a compelling picture of unique fecal microflora of children with autism with gastrointestinal symptomatology. Differences based upon maximum observed and maximum predicted operational taxonomic units were statistically significant when comparing autistic and control subjects with p-values ranging from <0.001 to 0.009 using both parametric and non-parametric estimators. At the phylum level, Bacteroidetes and Firmicutes showed the most difference between groups of varying severities of autism. Bacteroidetes was found at high levels in the severely autistic group, while Firmicutes were more predominant in the control group. Smaller, but significant, differences also occurred in the Actinobacterium and Proteobacterium phyla. Desulfovibrio species and Bacteroides vulgatus are present in significantly higher numbers in stools of severely autistic children than in controls. If the unique microbial flora is found to be a causative or consequent factor in this type of autism, it may have implications with regard to a specific diagnostic test, its epidemiology, and for treatment and prevention.

Evaluation of an Immersive Virtual Reality Safety Training Used to Teach Pedestrian Skills to Children With Autism Spectrum Disorder.

Children with autism spectrum disorder (ASD) are at an increased risk of injury, making safety skills training essential. Whether such training is conducted in the natural environment or in contrived settings is an important consideration for generalization and safety purposes. Immersive virtual reality (VR) environments may offer the advantages of both contrived and natural environment training settings, providing structure to create repeated learning opportunities in a safe and realistic analogue of the natural environment. The current study evaluated the effectiveness of an immersive VR safety skills training environment in teaching 3 children with ASD to identify whether it is safe to cross the street. After modifications to the VR training environment, all 3 participants reached mastery criteria in both VR and natural environment settings. Findings suggest that immersive VR is a promising medium for the delivery of safety skills training to individuals with ASD.

Applied behavior analytic interventions for children with autism: a description and review of treatment research.

BACKGROUND: Autism is a disorder characterized by pervasive delays in the development of language and socialization, and the presence of stereotyped, repetitive behaviors or nonfunctional interests. Although a multitude of treatments for autism exist, very few have been the subject of scientific research. The only treatment that has been supported by substantial empirical research is treatment based on applied behavior analysis (ABA). METHODS: This article describes components of comprehensive ABA treatment programs, reviews research on effectiveness, and discusses issues related to collaboration between ABA and psychiatry. RESULTS: ABA has been supported by several hundred single case experiments and an increasing number of between-groups studies. Comprehensive ABA treatment programs are comprised of multiple intervention procedures, such as discrete trial instruction and natural environment training, and are founded on basic principles of learning and motivation, such as positive reinforcement, extinction, stimulus control, and generalization. Clinicians in the fields of ABA and psychiatry have similar goals regarding client outcome, and several ABA measurement and analysis procedures produce information that may be useful to psychiatrists. CONCLUSIONS: ABA treatment programs for individuals with autism are supported by a significant amount of scientific evidence and are therefore recommended for use. Patient care would likely benefit from a greater degree of collaboration between practitioners in the fields of ABA and psychiatry.

Retrospective analysis of clinical records in 38 cases of recovery from autism.

BACKGROUND: Twenty years of research on early intensive treatment using applied behavior analysis (ABA) for children with autism has consistently produced robust effects. There appears to be a subset of children whose response to intensive ABA treatments includes achieving a level of functioning that is indistinguishable from typically developing peers. The purpose of this study was to describe a subset of children who recovered from autism following intensive ABA interventions. METHODS: We reviewed the clinical files of 38 children with autism who achieved an optimal outcome after receiving intensive ABA services. RESULTS: The mean age at intake was 40 months. Average IQ was 83.6 at intake and 107.9 at discharge. Mean adaptive skills were 68.04 at intake and 88.87 at discharge. CONCLUSIONS: Our study corroborates the finding that some children with autism who receive early intensive behavioral intervention achieve functioning in the average range.

Development and implementation of clinical trial protocol templates at the National Institute of Allergy and Infectious Diseases.

BACKGROUND: A clinical research protocol document must reflect both sound scientific rationale as well as local, national and, when applicable, international regulatory and human subject protections requirements. These requirements originate from a variety of sources, undergo frequent revision and are subject to interpretation. Tools to assist clinical investigators in the production of clinical protocols could facilitate navigating these requirements and ultimately increase the efficiency of clinical research. PURPOSE: The National Institute of Allergy and Infectious Diseases (NIAID) developed templates for investigators to serve as the foundation for protocol development. These protocol templates are designed as tools to support investigators in developing clinical protocols. METHODS: NIAID established a series of working groups to determine how to improve its capacity to conduct clinical research more efficiently and effectively. The Protocol Template Working Group was convened to determine what protocol templates currently existed within NIAID and whether standard NIAID protocol templates should be produced. After review and assessment of existing protocol documents and requirements, the group reached consensus about required and optional content, determined the format and identified methods for distribution as well as education of investigators in the use of these templates. RESULTS: The templates were approved by the NIAID Executive Committee in 2006 and posted as part of the NIAID Clinical Research Toolkit [1] website for broad access. These documents require scheduled revisions to stay current with regulatory and policy changes. LIMITATIONS: The structure of any clinical protocol template, whether comprehensive or specific to a particular study phase, setting or design, affects how it is used by investigators. Each structure presents its own set of advantages and disadvantages. While useful, protocol templates are not stand-alone tools for creating an optimal protocol document, but must be complemented by institutional resources and support. Education and guidance of investigators in the appropriate use of templates is necessary to ensure a complete yet concise protocol document. Due to changing regulatory requirements, clinical protocol templates cannot become static, but require frequent revisions.

An Evaluation of a Mobile Application Designed to Teach Receptive Language Skills to Children with Autism Spectrum Disorder.

The current study evaluated the effectiveness of a mobile application, Camp Discovery, designed to teach receptive language skills to children with autism spectrum disorder based on the principles of applied behavior analysis. Participants (N = 28) were randomly assigned to an immediate-treatment or a delayed-treatment control group. The treatment group made significant gains, p < .001, M = 58.1, SE = 7.54, following 4 weeks of interaction with the application as compared to the control group, M = 8.4, SE = 2.13. Secondary analyses revealed significant gains in the control group after using the application and maintenance of acquired skills in the treatment group after application usage was discontinued. Findings suggest that the application effectively teaches the targeted skills.

Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning.

BACKGROUND AND OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes. MATERIALS AND METHODS: The present study included a sample of children with ASD (N = 2400), the largest of its kind to date. Unsupervised machine learning was applied to model ASD subgroups as well as their taxonomic relationships. Retrospective treatment data were available for a portion of the sample (n = 1034). Treatment response was examined within each subgroup via regression. RESULTS: The application of a Gaussian Mixture Model revealed 16 subgroups. Further examination of the subgroups through Hierarchical Agglomerative Clustering suggested 2 overlying behavioral phenotypes with unique deficit profiles each composed of subgroups that differed in severity of those deficits. Furthermore, differentiated response to treatment was found across subtypes, with a substantially higher amount of variance accounted for due to the homogenization effect of the clustering. DISCUSSION: The high amount of variance explained by the regression models indicates that clustering provides a basis for homogenization, and thus an opportunity to tailor treatment based on cluster memberships. These findings have significant implications on prognosis and targeted treatment of ASD, and pave the way for personalized intervention based on unsupervised machine learning.

Behaviour problems in institutionalised people with intellectual disability and schizophrenia spectrum disorders.

BACKGROUND: Although our understanding of dual diagnosis has improved, a deficit still exists in our knowledge of how schizophrenia spectrum disorders (SSD) manifest themselves in individuals with intellectual disability (ID). In addition, little is known about the relationship between behaviour problems and psychopathology in this population. METHOD: Utilising the Behavior Problems Inventory (BPI), three areas of problem behaviour (self-injurious, stereotyped, and aggressive/destructive) were assessed in 58 individuals with ID divided into three groups (with SSD, with a diagnosis of psychopathology other than SSD, and with ID only) and a total BPI score was calculated for each. RESULTS: The SSD group was unique when compared to the Control group (ID only) for frequency of stereotyped behaviours. Further, severity of stereotyped behaviours in the SSD group was unique compared to the Psychopathology and Control groups. CONCLUSION: The SSD group was unique compared to the other two groups, particularly for severity of stereotyped behaviours. Many specific behavioural differences were also related to either SSD or general psychopathology.

A Program Evaluation of Home and Center-Based Treatment for Autism Spectrum Disorder.

The present study aimed to retrospectively compare the relative rates of mastery of exemplars for individuals with ASD (N = 313) who received home-based and center-based services. A between-group analysis found that participants mastered significantly more exemplars per hour when receiving center-based services than home-based services. Likewise, a paired-sample analysis found that participants who received both home and center-based services had mastered 100 % more per hour while at the center than at home. These analyses indicated that participants demonstrated higher rates of learning during treatment that was provided in a center setting than in the participant's home.

Intensity and Learning Outcomes in the Treatment of Children With Autism Spectrum Disorder.

Ample research has shown that intensive applied behavior analysis (ABA) treatment produces robust outcomes for individuals with autism spectrum disorder (ASD); however, little is known about the relationship between treatment intensity and treatment outcomes. The current study was designed to evaluate this relationship. Participants included 726 children, ages 1.5 to 12 years old, receiving community-based behavioral intervention services. Results indicated a strong relationship between treatment intensity and mastery of learning objectives, where higher treatment intensity predicted greater progress. Specifically, 35% of the variance in mastery of learning objectives was accounted for by treatment hours using standard linear regression, and 60% of variance was accounted for using artificial neural networks. These results add to the existing support for higher intensity treatment for children with ASD.