Objective: To review the various ways in which baseline neuropsychological functioning is measured in the extant literature on pediatric brain tumors, describe the pros and cons of each approach, and increase the awareness of researchers as to the implications of each.

Method: We reviewed the literature from 1993 to 2013, and classified studies by baseline approach and explicitness of selection of approach.

Results: There are multiple approaches to operationalizing baseline levels of ability and to assess change from baseline. Each approach has strengths and weaknesses, and selection may depend on the question under investigation. Approaches to baseline estimation varied widely with a trend over time toward reliance on statistical modeling. Researchers were often insufficiently explicit about the reasons for adopting a particular approach. The common use of standardized scores requires caution as they obscure critical inferential limitations about change and magnitude of change. Some viable approaches were infrequently used, such as actuarial prediction formulas. Multiple simultaneous methods akin to theory testing and formal methods of construct validation could enhance scientific yield since all approaches are fallible.

Conclusions: Estimating baseline neuropsychological functioning is very challenging, particularly when it concerns children in the preschool years. Nevertheless, it is a crucial methodological decision with important implications for the interpretation of research findings that needs to be dealt with explicitly.

Download full-text PDF

Source
http://dx.doi.org/10.1080/13854046.2016.1216070DOI Listing

Publication Analysis

Top Keywords

brain tumors
8
baseline neuropsychological
8
neuropsychological functioning
8
baseline approach
8
baseline
6
measurement neurodevelopmental
4
neurodevelopmental changes
4
changes children
4
children treated
4
treated radiation
4

Similar Publications

CDK5: Insights into its roles in diseases.

Mol Biol Rep

January 2025

Institute of Pathogenic Biology, Guilin Medical University, Guilin, 541199, China.

Cyclin-dependent kinase 5 (CDK5), a unique member of the CDK family, is a proline-directed serine/threonine protein kinase with critical roles in various physiological and pathological processes. Widely expressed in the central nervous system, CDK5 is strongly implicated in neurological diseases. Beyond its neurological roles, CDK5 is involved in metabolic disorders, psychiatric conditions, and tumor progression, contributing to processes such as proliferation, migration, immune evasion, genomic stability, and angiogenesis.

View Article and Find Full Text PDF

Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues.

View Article and Find Full Text PDF

Mutations in Sonic Hedgehog (SHH) signaling pathway genes, for example, (SUFU), drive granule neuron precursors (GNP) to form medulloblastomas (MB). However, how different molecular lesions in the Shh pathway drive transformation is frequently unclear, and mutations in the cerebellum seem distinct. In this study, we show that fibroblast growth factor 5 (FGF5) signaling is integral for many infantile MB cases and that expression is uniquely upregulated in infantile MB tumors.

View Article and Find Full Text PDF

Introduction: Medulloblastoma (MB) is the most common malignant childhood brain tumor. Molecular subgrouping of MB has become a major determinant of management in high-income countries. Subgrouping is still very limited in low- and middle-income countries (LMICs), and its relevance to management with the incorporation of risk stratification (low risk, standard risk, high risk, and very high risk) has yet to be evaluated in this setting.

View Article and Find Full Text PDF

Utilizing machine-learning techniques on MRI radiomics to identify primary tumors in brain metastases.

Front Neurol

January 2025

Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Objective: To develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).

Materials And Methods: A total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC]  = 194, brain metastases of breast cancer [BMBC]  = 108, brain metastases of gastrointestinal tumor [BMGiT]  = 48) and test sets (BMLC  = 50, BMBC  = 27, BMGiT  = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!