ABSTRACT
Around 30-60% of patients with rheumatoid arthritis (RA) present treatment failure to conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Chitinase-like proteins (CLPs) (YKL-40, YKL-39, SI-CLP) might play a role, as they are associated with the inflammatory process. This study aimed to evaluate CLP utility as a biomarker in the treatment failure of csDMARDs. A case-control study included 175 RA patients classified into two groups based on therapeutic response according to DAS28-ESR: responders (DAS28 < 3.2); non-responders (DAS28 ≥ 3.2). CLP serum levels were determined by ELISA. Multivariable logistic regression and receiver operating characteristic (ROC) curves were used to evaluate CLPs' utility as biomarkers of treatment failure. Non-responders presented higher levels of YKL-40, YKL-39, and SI-CLP compared with responders (all: p < 0.001). YKL-40 correlated positively with YKL-39 (rho = 0.39, p < 0.001) and SI-CLP (rho = 0.23, p = 0.011) and YKL-39 with SI-CLP (rho = 0.34, p < 0.001). The addition of CLPs to the regression models improves diagnostic accuracy (AUC 0.918) compared to models including only clinical classical variables (AUC 0.806) p < 0.001. Non-responders were positive for all CLPs in 35.86%. Conclusions: CLPs could be considered as a useful biomarker to assess treatment failure, due to their association with clinical variables and improvement to the performance of regression models.
ABSTRACT
Epidemiological studies are essential in medicine and public health as they help identify risk factors and causes of diseases. Additionally, they are key to planning, implementing, and evaluating health interventions aimed at preventing and controlling the spread of diseases. Among these studies, analytical observational studies, such as cross-sectional, case-control, and cohort studies, are the most used. The validity of their results largely depends on the robustness of the design, execution, and statistical analysis. Objective: The objective of this study is to examine the most common errors in the selection of methodological design and statistical tests in analytical observational studies and to provide recommendations to correct them. Methodology: A comprehensive review of the available literature on methodology in epidemiological observational studies was conducted, focusing on cross-sectional, case-control, and cohort studies. Common errors in the selection of designs and statistical tests were identified and analyzed. Results and Conclusions: Errors in the selection of methodological design and statistical tests are common in epidemiological observational studies. Based on the identified errors, a series of recommendations is provided to improve the selection of methodological design and statistical tests, thereby increasing the reliability of the results in cross-sectional, case-control, and cohort studies.
