Practical and statistical aspects of subgroup analyses in surgical neuro-oncology: A comprehensive review from the PIONEER consortium
Rattachement africain : us, nl, de, jp, ch, be. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Subgroup analyses are essential to generate new hypotheses or to estimate treatment effects in clinically meaningful subgroups of patients. They play an important role in taking the next step toward personalized surgical treatment for brain tumor patients. However, subgroup analyses must be used with consideration and care because they have significant potential risks. Although some recommendations are available on the pearls and pitfalls of these analyses, a comprehensive guide is lacking, especially one focused on surgical neuro-oncology patients. This paper, therefore, reviews and summarizes for the first time comprehensively the practical and statistical considerations that are critical to this field. First, we evaluate the considerations when choosing a study design for surgical neuro-oncology studies and examine those unique to this field. Second, we give an overview of the relevant aspects to interpret subgroup analyses adequately. Third, we discuss the practical and statistical elements necessary to appropriately design and use subgroup analyses. The paper aims to provide an in-depth and complete guide to better understand risk modeling and assist the reader with practical examples of designing, using, and interpreting subgroup analyses.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Practical and statistical aspects of subgroup analyses in surgical neuro-oncology: A comprehensive review from the PIONEER consortium
- Date Crossref
- 07/12/2024
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
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