A Targeted Literature Search and Phenomenological Review of Perspectives of People with Multiple Sclerosis and Healthcare Professionals of the Immunology of Disease-Modifying Therapies.

INTRODUCTION: The mechanisms of action of disease-modifying therapies (DMTs) for multiple sclerosis (MS) are complex and involve an interplay of immune system components. People with MS (PwMS) may lack a clear understanding of the immunological pathways involved in MS and its treatment; effective communication between healthcare professionals (HCPs) and PwMS is needed to facilitate shared decision-making when discussing the disease and selecting DMTs and is particularly important in the coronavirus disease 2019 (COVID-19) era. METHODS: In this patient-authored two-part review, we performed a targeted literature search to assess the need for better communication between HCPs and PwMS regarding treatment selection, and also conducted a qualitative survey of four patient and care-partner authors to obtain insights regarding their understanding of and preferences for the treatment and management of MS. RESULTS: Following a search of the Embase and MEDLINE databases using Ovid in June 2020, an analysis of 40 journal articles and conference abstracts relating to patient empowerment and decision-making in DMT selection for MS showed a preference for safety and efficacy of treatments, followed by autonomy and convenience of administration. A need for better communication between HCPs and PwMS during treatment selection to improve patient satisfaction was also identified. The open survey responses from the patient authors revealed a need for greater involvement in decision-making processes and desire for improved communication and information tools. CONCLUSIONS: This targeted literature search and phenomenological review confirms PwMS preferences for empowered decision-making in disease management and treatment selection, to optimize independence, safety, and efficacy. It also identifies an unmet need for improved communication and information tools that convey MS information in a relatable manner. Furthermore, this review seeks to address this unmet need by providing plain language figures and descriptions of MS immune mechanisms that can be used to facilitate discussions between HCPs and PwMS.

In multiple sclerosis (MS), there are different cells in the immune system that contribute to the disease. The main cells in the immune system are T and B cells. People with MS (PwMS) might not be familiar with details about the immune system, and healthcare professionals might not always communicate details about how treatments work clearly to PwMS when choosing treatments with them. It is important for PwMS to have all the information they need to help make decisions about treatments. This information needs to be given in a way they can understand. This is especially important during the coronavirus disease 2019 (COVID-19) pandemic. In this paper, we first looked at what research has already been published about what is most important to PwMS when making treatment decisions. The existing research says that safety and effectiveness are the most important things and that PwMS prefer treatments that they can take themselves. PwMS also need better communication and information from doctors to make decisions and to help explain how MS treatments work in the body. Next, we gave a survey to the patients who are authors of this paper to ask about what is important to them when making treatment decisions. Their answers were very similar to the existing research. Overall, PwMS need better communication from healthcare professionals about the immune system. This paper also includes plain language descriptions and figures to help healthcare professionals explain and discuss the importance of the immune system in MS with PwMS.

Putting plain language summaries into perspective.

Publication-associated plain language summaries are brief, jargon-free summaries of scientific publications. They are intended for a broad, non-expert audience to help maximize the accessibility of the publication. Plain language summaries are typically found alongside peer-reviewed publications or in supplementary materials and can be indexed in PubMed. In this narrative commentary, we present the perspectives of five day-to-day users of plain language summaries from different stakeholder groups, gained through semi-structured qualitative interviews about the users' experiences with and opinions of plain language summaries.

Plain language summaries such as this one are an increasingly popular tool for helping readers cut though jargon and understand the key points of a research article faster. To get a better idea of how plain language summaries are being used, we spoke to five people from different backgrounds who read, write and review plain language summaries in their personal and professional lives.

Open Pharma recommendations for plain language summaries of peer-reviewed medical journal publications.

Plain language summaries of peer-reviewed medical journal publications are a means of sharing research with a broad range of audiences and may improve the transparency, accountability, accessibility, discoverability, and inclusivity of medical research. There is currently an ongoing, industry-wide effort to establish consensus on plain language summaries, and initiatives are already in place that provide detailed guidance on plain language best practice, co-creation methods, patient-focused content, graphic and digital considerations, and publisher-specific guidelines. However, there remains a need for a foundational set of recommendations that complement existing initiatives to outline the minimum steps needed to develop discoverable, plain language summaries that are trustworthy, credible, and of high quality. Here, we present the Open Pharma recommendations for plain language summaries of peer-reviewed medical journal publications. These recommendations were initially developed by the Open Pharma Accessibility workstream and were extensively reviewed and refined during an expert roundtable and a focused, public consultation. Open Pharma is a multi-sponsor collaboration of pharmaceutical companies, non-pharmaceutical funders, publishers, patients, academics, regulators, editors, and societies seeking to identify and drive positive changes in the publishing of pharmaceutical company-funded research. We recommend that plain language summaries should be in the style of an abstract, free of technical jargon, unbiased, non-promotional, peer reviewed, and easily accessed. Plain language summaries should also meet the technical requirements to be indexed in directories such as PubMed. Ultimately, these recommendations are intended to be a concise outline of a minimum standard that provides top-line guidance on plain language summaries for authors, medical writers, publishers, and research funders.

PLAIN LANGUAGE SUMMARYArticles published in peer-reviewed medical journals are written using technical language. Plain language summaries are short summaries of these articles, written in everyday language that is easy to understand by anyone interested in medical research. This can include patients, patient advocates, caregivers, healthcare professionals, and policymakers. Sharing research through plain language summaries makes medical information more accessible and inclusive. However, few medical research articles include plain language summaries. The pharmaceutical industry has an opportunity to improve everyone's understanding of medical research by regularly developing plain language summaries of their articles. Plain language summaries can come in many different formats such as infographics and videos. However, text-only summaries are the easiest to find on internet search engines and research websites such as PubMed. Currently, there is limited guidance available to help researchers and medical journal publishers develop plain language summaries for their articles. In this article, 'Open Pharma recommendations for plain language summaries of peer-reviewed medical journal publications', we suggest a set of simple rules to help authors make and share text-only plain language summaries that we believe are possible for all articles reporting medical research. Once these have been met, we encourage researchers to consider making and sharing infographics and video summaries as well, to help people to understand their research even more.

Immune infiltrate diversity confers a good prognosis in follicular lymphoma.

BACKGROUND: Follicular lymphoma (FL) prognosis is influenced by the composition of the tumour microenvironment. We tested an automated approach to quantitatively assess the phenotypic and spatial immune infiltrate diversity as a prognostic biomarker for FL patients. METHODS: Diagnostic biopsies were collected from 127 FL patients initially treated with rituximab-based therapy (52%), radiotherapy (28%), or active surveillance (20%). Tissue microarrays were constructed and stained using multiplex immunofluorescence (CD4, CD8, FOXP3, CD21, PD-1, CD68, and DAPI). Subsequently, sections underwent automated cell scoring and analysis of spatial interactions, defined as cells co-occurring within 30 µm. Shannon's entropy, a metric describing species biodiversity in ecological habitats, was applied to quantify immune infiltrate diversity of cell types and spatial interactions. Immune infiltrate diversity indices were tested in multivariable Cox regression and Kaplan-Meier analysis for overall (OS) and progression-free survival (PFS). RESULTS: Increased diversity of cell types (HR = 0.19 95% CI 0.06-0.65, p = 0.008) and cell spatial interactions (HR = 0.39, 95% CI 0.20-0.75, p = 0.005) was associated with favourable OS, independent of the Follicular Lymphoma International Prognostic Index. In the rituximab-treated subset, the favourable trend between diversity and PFS did not reach statistical significance. CONCLUSION: Multiplex immunofluorescence and Shannon's entropy can objectively quantify immune infiltrate diversity and generate prognostic information in FL. This automated approach warrants validation in additional FL cohorts, and its applicability as a pre-treatment biomarker to identify high-risk patients should be further explored. The multiplex image dataset generated by this study is shared publicly to encourage further research on the FL microenvironment.