Statistical practice and transparent reporting in the neurosciences: Preclinical motor behavioral experiments.

Longitudinal and behavioral preclinical animal studies generate complex data, which may not be well matched to statistical approaches common in this literature. Analyses that do not adequately account for complexity may result in overly optimistic study conclusions, with consequences for reproducibility and translational decision-making. Recent work interrogating methodological shortcomings in animal research has not yet comprehensively investigated statistical shortcomings in the analysis of complex longitudinal and behavioral data. To this end, the current cross-sectional meta-research study rigorously reviewed published mouse or rat controlled experiments for motor rehabilitation in three neurologic conditions to evaluate statistical choices and reporting. Medline via PubMed was queried in February 2020 for English-language articles published January 1, 2017- December 31, 2019. Included were articles that used rat or mouse models of stroke, Parkinson's disease, or traumatic brain injury, employed a therapeutic controlled experimental design to determine efficacy, and assessed at least one functional behavioral assessment or global evaluation of function. 241 articles from 99 journals were evaluated independently by a team of nine raters. Articles were assessed for statistical handling of non-independence, animal attrition, outliers, ordinal data, and multiplicity. Exploratory analyses evaluated whether transparency or statistical choices differed as a function of journal factors. A majority of articles failed to account for sources of non-independence in the data (74-93%) and/or did not analytically account for mid-treatment animal attrition (78%). Ordinal variables were often treated as continuous (37%), outliers were predominantly not mentioned (83%), and plots often concealed the distribution of the data (51%) Statistical choices and transparency did not differ with regards to journal rank or reporting requirements. Statistical misapplication can result in invalid experimental findings and inadequate reporting obscures errors. Clinician-scientists evaluating preclinical work for translational promise should be mindful of commonplace errors. Interventions are needed to improve statistical decision-making in preclinical behavioral neurosciences research.

Incidence and survival trends for medulloblastomas in the United States from 2001 to 2013.

Population-based data examining recent epidemiological trends in medulloblastoma, the most common pediatric brain malignancy, are limited. Therefore, we sought to examine recent population-level trends in medulloblastoma incidence and survival. Central Brain Tumor Registry of the United States (CBTRUS) data were analyzed from 2001 to 2013. Age-adjusted incidence rates (IR) and annual percent changes (APCs) with 95% confidence intervals (CI) were calculated by age, sex, and race. Relative survival rates were calculated by age, sex, and race using Surveillance, Epidemiology and End-Results (SEER) registries; subsets of CBTRUS data. Kaplan-Meier and Cox proportional hazards models were used to examine survival differences. Medulloblastoma incidence remained relatively stable from 2001 to 2013, with minor fluctuations from 2001 to 2009 (APC = 2.2, 95% CI 0.8, 3.5) and 2009-2013 (APC = -4.1, 95% CI -7.5, -0.6). Incidence was highest in patients aged 1-4 years at diagnosis, but patients aged 10-14 years showed increased incidence from 2000 to 2013 (APC = 3.2, 95% CI 0.6, 5.8). Males displayed higher IR relative to females (males: 0.16 vs. females: 0.12), except in patients <1 year-old. Compared to Whites, Blacks displayed a non-significant increase in incidence (APC = 1.7, 95% CI -0.4, 4.0) and in mortality risk (hazard ratio for survival = 0.74; p = 0.09). The current study reports no overall change in medulloblastoma incidence from 2001 to 2013. Male and female patients <1 year-old had equal medulloblastoma incidence rates and poor 5-year relative survival compared to other ages. Non-significant trends in the data suggest disparities in medulloblastoma incidence and survival by race. Thus, analysis of tumor-specific trends by demographic variables can uncover clinically informative trends in cancer burden.