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1.
Contemp Clin Trials Commun ; 34: 101100, 2023 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-37388218

RESUMO

A number of principal investigators may have limited access to biostatisticians, a lack of biostatistical training, or no requirement to complete a timely statistical analysis plan (SAP). SAPs completed early will identify design or implementation weak points, improve protocols, remove the temptation for p-hacking, and enable proper peer review by stakeholders considering funding the trial. An SAP completed at the same time as the study protocol might be the only comprehensive method for at once optimizing sample size, identifying bias, and applying rigor to study design. This ordered corpus of SAP sections with detailed definitions and a variety of examples represents an omnibus of best practice methods offered by biostatistical practitioners inside and outside of industry. The article presents a protocol template for clinical research design, enabling statisticians, from beginners to advanced.

2.
Front Health Serv ; 3: 1310694, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38313331

RESUMO

Introduction: Soil-transmitted helminths (STH) are parasitic worms that infect nearly a quarter of the world's population, particularly those living in communities without access to adequate water, sanitation, and housing. Emerging evidence suggests that it may be possible to interrupt transmission of STH by deworming individuals of all ages via community-wide MDA (cMDA), as opposed to only treating children and other focal populations. Transitioning from a policy of STH control to STH elimination in targeted areas would require a fundamental shift in STH policy and programming. This policy change would require updated guidance to support countries as they adapt their current approaches for STH surveillance, supply chain management, community mobilization, and core programmatic activities in pursuit of STH elimination. There is an opportunity to engage with key stakeholders, such as program implementers and implementation partners, to understand what evidence they need to confidently adopt a new policy guideline and to deliver guideline adherent management at scale. Methods: We aimed to engage with STH stakeholders to develop a Target Policy Profile (TPoP), a single document that describes optimal characteristics and evidence requirements that STH stakeholders prioritized in future potential STH transmission interruption efforts. Steps in TPoP development included a scoping review and key informant interviews (KIIs), which were used to design a two-stage Delphi technique to identify and verify TPoP components. Results: The scoping review resulted in 25 articles, and 8 experts participated in KII's. Twenty respondents completed the first Delphi survey and 10 respondents completed the second. This systematic effort resulted in a net of 3 key information domains (background/context, clinical considerations, and implementation considerations) encompassing 24 evidence categories (examples include evidence regarding safety and adverse events, implementation feasibility, or evidence dissemination). For each evidence category, STH stakeholders reviewed, endorsed, or revised a range of options for how the evidence could be presented. Discussion: This information can be used by guideline committees or global policy makers prior to convening guideline advisory groups. The TPoP tool may also speed the process of stakeholder consensus building around guidelines, accelerating progress towards implementing evidence-based policy at scale.

3.
Gates Open Res ; 4: 58, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32656501

RESUMO

It is critical to ensure that COVID-19 studies provide clear and timely answers to the scientific questions that will guide us to scalable solutions for all global regions. Significant challenges in operationalizing trials include public policies for managing the pandemic, public health and clinical capacity, travel and migration, and availability of tests and infrastructure. These factors lead to spikes and troughs in patient count by location, disrupting the ability to predict when or if a trial will reach recruitment goals. The focus must also be on understanding how to provide equitable access to these interventions ensuring that interventions reach those who need them the most, be it patients in low resource settings or vulnerable groups.  We introduce a website to be used by The Bill & Melinda Gates Foundation, Wellcome Trust, and other funders of the COVID Therapeutics Accelerator that accept proposals for future clinical research. The portal enables evaluations of clinical study applications that focus on study qualities most likely to lead to informative outcomes and completed studies.

4.
Front Public Health ; 6: 68, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29594091

RESUMO

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

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