Treatment barriers in PANS/PANDAS: Observations from eleven health care provider families.

INTRODUCTION: Pediatric acute-onset neuropsychiatric syndrome (PANS) and pediatric autoimmune neuropsychiatric disorder associated with streptococcal infections (PANDAS) are severe but highly treatable postinfectious inflammatory brain conditions. Despite published diagnostic and treatment guidelines for this condition, there are long delays in obtaining appropriate care. The reasons for these delays are poorly understood. We sought to identify health care system barriers to timely treatment by examining cases of PANDAS/PANS occurring in children of health care professionals. METHOD: We recruited families via e-mail request through the PANDAS Physicians Network. Participating parents completed a structured questionnaire and provided a written case description. RESULTS: Eleven families completed data collection, representing a broad spectrum of disease (child disease onset age 4-15, 7 males/4 females, mild to severe). Parents included 11 physicians, 2 mental health professionals, 2 nurses, and a PharmD. Nine cases (82%) had "very delayed" diagnosis and treatment (>4 weeks after onset). The most commonly encountered causes for treatment delay were clinician lack of awareness (82%), clinician skepticism (82%), overdependence on diagnostic testing (91%), and out-of-pocket expenses >$100 US (82%). Other common challenges included difficulties finding a provider to spearhead care (64%), psychological misdiagnosis (55%), and children's suppression of behaviors during assessments (55%). CONCLUSIONS: We found numerous barriers to treatment of PANDAS/PANS among children of health care providers. Our findings suggest that even among the medically sophisticated, PANDAS/PANS diagnosis and treatment remains challenging. Improvement in PANDAS/PANS education of clinicians who may encounter children with this disorder is 1 key step toward addressing our identified barriers. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Use of adjectives in abstracts when reporting results of randomized, controlled trials from industry and academia.

OBJECTIVE: Accurate representation of study findings is crucial to preserve public trust. The language used to describe results could affect perceptions of the efficacy or safety of interventions. We sought to compare the adjectives used in clinical trial reports of industry-authored and non-industry-authored research. METHODS: We included studies in PubMed that were randomized trials and had an abstract. Studies were classified as "non-industry-authored" when all authors had academic or governmental affiliations, or as "industry-authored" when any of the authors had industry affiliations. Abstracts were analyzed using a part-of-speech tagger to identify adjectives. To reduce the risk of false positives, the analysis was restricted to adjectives considered relevant to "coloring" (influencing interpretation) of trial results. Differences between groups were determined using exact tests, stratifying by journal. RESULTS: A total of 306,007 publications met the inclusion criteria. We were able to classify 16,789 abstracts; 9,085 were industry-authored research, and 7,704 were non-industry-authored research. We found a differential use of adjectives between industry-authored and non-industry-authored reports. Adjectives such as "well tolerated" and "meaningful" were more commonly used in the title or conclusion of the abstract by industry authors, while adjectives such as "feasible" were more commonly used by non-industry authors. CONCLUSIONS: There are differences in the adjectives used when study findings are described in industry-authored reports compared with non-industry-authored reports. Authors should avoid overusing adjectives that could be inaccurate or result in misperceptions. Editors and peer reviewers should be attentive to the use of adjectives and assess whether the usage is context appropriate.

Five-step authorship framework to improve transparency in disclosing contributors to industry-sponsored clinical trial publications.

Authorship guidelines have established criteria to guide author selection based on significance of contribution and helped to define associated responsibilities and accountabilities for the published findings. However, low awareness, variable interpretation, and inconsistent application of these guidelines can lead to confusion and a lack of transparency when recognizing those who merit authorship. This article describes a research project led by the Medical Publishing Insights and Practices (MPIP) Initiative to identify current challenges when determining authorship for industry-sponsored clinical trials and develop an improved approach to facilitate decision-making when recognizing authors from related publications. A total of 498 clinical investigators, journal editors, publication professionals and medical writers were surveyed to understand better how they would adjudicate challenging, real-world authorship case scenarios, determine the perceived frequency of each scenario and rate their confidence in the responses provided. Multiple rounds of discussions about these results with journal editors, clinical investigators and industry representatives led to the development of key recommendations intended to enhance transparency when determining authorship. These included forming a representative group to establish authorship criteria early in a trial, having all trial contributors agree to these criteria and documenting trial contributions to objectively determine who warrants an invitation to participate in the manuscript development process. The resulting Five-step Authorship Framework is designed to create a more standardized approach when determining authorship for clinical trial publications. Overall, these recommendations aim to facilitate more transparent authorship decisions and help readers better assess the credibility of results and perspectives of the authors for medical research more broadly. Please see related article: http://www.biomedcentral.com/1741-7015/12/214.

Adverse event detection in drug development: recommendations and obligations beyond phase 3.

Premarketing studies of drugs, although large enough to demonstrate efficacy and detect common adverse events, cannot reliably detect an increased incidence of rare adverse events or events with significant latency. For most drugs, only about 500 to 3000 participants are studied, for relatively short durations, before a drug is marketed. Systems for assessment of postmarketing adverse events include spontaneous reports, computerized claims or medical record databases, and formal postmarketing studies. We briefly review the strengths and limitations of each. Postmarketing surveillance is essential for developing a full understanding of the balance between benefits and adverse effects. More work is needed in analysis of data from spontaneous reports of adverse effects and automated databases, design of ad hoc studies, and design of economically feasible large randomized studies.