Reporte estadístico en los análisis de regresión en Biomédica: una revisión y evaluación crítica

Abstract

Introduction: Regression modeling is a statistical method commonly used in health research, especially by observational studies. Objective: The objectives of this paper were to 1) determine the frequency of reporting of regression modeling in original biomedical and public health articles that were published in Biomédica between 2000 and 2017; 2) describe the parameters used in the statistical models, and 3) describe the quality of the information reported by the studies to explain the statistical analyses. Materials and methods: We conducted a critical assessment review of all original articles published in Biomédica between 2000 and 2017 that used regression models for the statistical analysis of the studies main objectives. We generated a 20-item checklist based on four good practice guidelines for the presentation of statistical methods. Results: Most of the studies were observational studies related to public health sciences (65.7%). Less than half (37.2%) of them reported using a combination of conceptual frameworks and statistical criteria for the selection of variables to be included in the regression model. Less than one quarter (22.1%) reported the verification of the assumptions of the model. The most frequently used uncertainty measure was the p-value (73.5%). Conclusion: There are significant limitations in the quality of the reports of statistical regression models, which reviewers and readers need in order to correctly assess and interpret the statistical models. The results, herein, are provided as an invitation to researchers, reviewers, and editors of biomedical journals to develop, promote, and control an appropriate culture for statistical analysis and reporting in Colombia.

Linear regression reporting practices for health researchers, a cross-sectional meta-research study

“…Norstrom et al [58] reviewed 41 papers from public health and found that only one article tested for collinearity. Fernandez-Nino and Hernandaz-Montes [59] found that 15% (17/111) of articles in Biomedica reported assessing collinearity. Our results confirm that proper checking and reporting of collinearity remains poor, with 13 out of 64 (20%) multivariable papers checked for collinearity.…”

Statistical characteristics of analytical studies published in Peruvian medical journals from 2021 to 2022: A methodological study

“…This highlights a gap in reporting standards, emphasizing the need for improved consistency in presenting both unadjusted and adjusted estimates. In contrast, an analysis of 113 studies from a Colombian journal (Biomedica, 2000–2017) revealed nearly 90% reported measures of association coefficients [ 4 ].…”

“…Statistical methods rely on p-values or other statistical methods, while epidemiological approaches involve theoretical rationale and clinical relevance. These variables were chosen according to previous studies [ 4 , 5 , 8 – 10 ]. This data was gathered by thoroughly reviewing each article, with particular focus on the methods and results sections, although additional sections were consulted when required.…”

“…A study performed in the Journal of the American Medical Association (JAMA) showed that in 2010 around half of papers used advanced adjusted regression models [ 3 ]. Conversely, a study in a Colombian medical journal highlighted substandard reporting of statistical regression models [ 4 ]. Moreover, an examination of statistical methodologies in orthopedic papers revealed that one-third needed an alternative analysis [ 5 ].…”