Genetic alterations landscape in paediatric thyroid tumours and/or differentiated thyroid cancer: Systematic review.

Differentiated thyroid cancer (DTC) is a rare disease in the paediatric population (≤ 18 years old. at diagnosis). Increasing incidence is reflected by increases in incidence for papillary thyroid carcinoma (PTC) subtypes. Compared to those of adults, despite aggressive presentation, paediatric DTC has an excellent prognosis. As for adult DTC, European and American guidelines recommend individualised management, based on the differences in clinical presentation and genetic findings. Therefore, we conducted a systematic review to identify the epidemiological landscape of all genetic alterations so far investigated in paediatric populations at diagnosis affected by thyroid tumours and/or DTC that have improved and/or informed preventive and/or curative diagnostic and prognostic clinical conduct globally. Fusions involving the gene RET followed by NTRK, ALK and BRAF, were the most prevalent rearrangements found in paediatric PTC. BRAF V600E was found at lower prevalence in paediatric (especially ≤ 10 years old) than in adults PTC. We identified TERT and RAS mutations at very low prevalence in most countries. DICER1 SNVs, while found at higher prevalence in few countries, they were found in both benign and DTC. Although the precise role of DICER1 is not fully understood, it has been hypothesised that additional genetic alterations, similar to that observed for RAS gene, might be required for the malignant transformation of these nodules. Regarding aggressiveness, fusion oncogenes may have a higher growth impact compared with BRAF V600E. We reported the shortcomings of the systematized research and outlined three key recommendations for global authors to improve and inform precision health approaches, glocally.

Standardised data on initiatives-STARDIT: Beta version.

BACKGROUND AND OBJECTIVE: There is currently no standardised way to share information across disciplines about initiatives, including fields such as health, environment, basic science, manufacturing, media and international development. All problems, including complex global problems such as air pollution and pandemics require reliable data sharing between disciplines in order to respond effectively. Current reporting methods also lack information about the ways in which different people and organisations are involved in initiatives, making it difficult to collate and appraise data about the most effective ways to involve different people. The objective of STARDIT (Standardised Data on Initiatives) is to address current limitations and inconsistencies in sharing data about initiatives. The STARDIT system features standardised data reporting about initiatives, including who has been involved, what tasks they did, and any impacts observed. STARDIT was created to help everyone in the world find and understand information about collective human actions, which are referred to as 'initiatives'. STARDIT enables multiple categories of data to be reported in a standardised way across disciplines, facilitating appraisal of initiatives and aiding synthesis of evidence for the most effective ways for people to be involved in initiatives. This article outlines progress to date on STARDIT; current usage; information about submitting reports; planned next steps and how anyone can become involved. METHOD: STARDIT development is guided by participatory action research paradigms, and has been co-created with people from multiple disciplines and countries. Co-authors include cancer patients, people affected by rare diseases, health researchers, environmental researchers, economists, librarians and academic publishers. The co-authors also worked with Indigenous peoples from multiple countries and in partnership with an organisation working with Indigenous Australians. RESULTS AND DISCUSSION: Over 100 people from multiple disciplines and countries have been involved in co-designing STARDIT since 2019. STARDIT is the first open access web-based data-sharing system which standardises the way that information about initiatives is reported across diverse fields and disciplines, including information about which tasks were done by which stakeholders. STARDIT is designed to work with existing data standards. STARDIT data will be released into the public domain (CC0) and integrated into Wikidata; it works across multiple languages and is both human and machine readable. Reports can be updated throughout the lifetime of an initiative, from planning to evaluation, allowing anyone to be involved in reporting impacts and outcomes. STARDIT is the first system that enables sharing of standardised data about initiatives across disciplines. A working Beta version was publicly released in February 2021 (ScienceforAll.World/STARDIT). Subsequently, STARDIT reports have been created for peer-reviewed research in multiple journals and multiple research projects, demonstrating the usability. In addition, organisations including Cochrane and Australian Genomics have created prospective reports outlining planned initiatives. CONCLUSIONS: STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems.

All major problems, including complex global problems such as air pollution and pandemics, require reliable data sharing between disciplines in order to respond effectively. Such problems require evidence-informed collaborative methods, multidisciplinary research and interventions in which the people who are affected are involved in every stage. However, there is currently no standardised way to share information about initiatives and problem-solving across and between fields such as health, environment, basic science, manufacturing, education, media and international development. A multi-disciplinary international team of over 100 citizens, experts and data-users has been involved in co-creating STARDIT to help everyone in the world share, find and understand information about collective human actions, which are referred to as 'initiatives'. STARDIT is an open access data-sharing system to standardise the way that information about initiatives is reported, including information about which tasks were done by different people. Reports can be updated at all stages, from planning to evaluation, and can report impacts in many languages, using Wikidata. STARDIT is free to use, and data can be submitted by anyone. Report authors can be verified to improve trust and transparency, and data checked for quality. STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems. Among its main benefits, STARDIT offers those carrying out research and interventions access to standardised information which enables well-founded comparisons of the effectiveness of different methods. This article outlines progress to date; current usage; information about submitting reports; planned next steps and how anyone can become involved.

Public engagement in health technology assessment in Brazil: the case of the Trastuzumab public consultation.

BACKGROUND: Public engagement in health technology assessment (HTA) is increasing worldwide. There are several forms of public engagement and it is not always possible to determine which stakeholders participate in the HTA process and how they contribute. Our objective was to investigate which types of social representatives contributed to the public consultation on the incorporation of Trastuzumab for early-stage breast cancer treatment within the public health system in Brazil, held in 2012 by the National Committee for Health Technology Incorporation (CONITEC). METHODS: A mixed methods approach was used to analyze social representativeness and the composition of the corpus from the public consultation, which consisted of 127 contributions. Three types of analysis were performed using IRaMuTeQ software: classic lexical analysis, descending hierarchical classification and specificities analysis. The contributions were clustered according to the main categories of discourse observed, into four social representation categories: 1) patient representation/advocacy; 2) pharmaceutical industry/advocacy; 3) healthcare professionals; and 4) individual contributions. RESULTS: Category 1 contained words related to increased survival due to use of the drug and a low score for words pertaining to studies on Trastuzumab. The word "safety" obtained a positive score only in category 2, which was also the only category that exhibited a negative score for the word "risk". Category 3 displayed the lowest scores for "diagnosis" and "safety". The word "efficacy" had a negative score only in category 4. CONCLUSIONS: Each category exhibited different results for words related to health systems and to key concepts linked to HTA. Our analysis enabled the identification of the most prominent contributions for each category. Despite the promising results obtained, further research is needed to validate this software for use in analyzing public contributions.