RESUMO
BACKGROUND: Our objective was to explore various biomarkers for predicting suboptimal responses to disease-modifying treatments (DMTs) in patients with MS (pwMS). METHODS: We conducted a longitudinal, bicentric study with pwMS stratified based on their DMTs responses. Treatment failure (TF) was defined as the onset of a second relapse, presence of two or more T2 new lesions, or disability progression independent of relapse during the follow-up period. We evaluated intrathecal synthesis (ITS) of IgG and IgM using OCB, linear indices, and Reibergrams. Free kappa light chains ITS was assessed using the linear index (FKLCi). NfL and GFAP in serum and CSF, and CHI3L1 in CSF were quantified. Quantitative variables were dichotomized based on the third quartile. Predictive efficacy was assessed through bivariate and multivariate analyses, adjusting for age, sex, EDSS, acute inflammatory activity (AI) -defined as the onset of a relapse or gadolinium-enhancing lesions within a 90-day window of lumbar puncture-, treatment modality, study center, and time from disease onset to treatment initiation. In case of collinearity, multiple models were generated or confounding variables were excluded if collinearity existed between them and the biomarker. The same methodology was used to investigate the predictive potential of various combinations of two biomarkers, based on whether any of them tested positive or exceeded the third quartile. RESULTS: A total of 137 pwMS were included. FKLCi showed no differences based on AI, no correlation with EDSS and was significantly higher in pwMS with TF (p = 0.008). FKLCi>130 was associated with TF in bivariate analysis (Log-Rank p = 0.004). Due to collinearity between age and EDSS, two different models were generated with each of them and the rest of the confounding variables, in which FKLCi>130 showed a Hazard Ratio (HR) of 2.69 (CI: 1.35-5.4) and 2.67 (CI: 1.32-5.4), respectively. The combination of either FKLC or sNfL exceeding the third quartile was also significant in bivariate (Log-Rank p = 0.04) and multivariate (HR=3.1 (CI: 1.5-6.5)) analyses. However, when analyzed independently, sNfL did not show significance, and FKLCi mirrored the pattern obtained in the previous model (HR: 3.04; CI: 1.51-6.1). Treatment with highefficacy DMTs emerged as a protective factor in all models. DISCUSSION: Our analysis and the fact that FKLCi is independent of EDSS and AI suggest that it might be a valuable parameter for discriminating aggressive phenotypes. We propose implementing high-efficacy drugs in pwMS with elevated FKLCi.
Assuntos
Biomarcadores , Humanos , Feminino , Masculino , Adulto , Biomarcadores/sangue , Biomarcadores/líquido cefalorraquidiano , Pessoa de Meia-Idade , Estudos Longitudinais , Fatores Imunológicos/administração & dosagem , Fatores Imunológicos/farmacologia , Proteínas de Neurofilamentos/sangue , Proteínas de Neurofilamentos/líquido cefalorraquidiano , Esclerose Múltipla/líquido cefalorraquidiano , Esclerose Múltipla/sangue , Esclerose Múltipla/tratamento farmacológico , Esclerose Múltipla/diagnóstico , Proteína Glial Fibrilar Ácida/líquido cefalorraquidiano , Proteína Glial Fibrilar Ácida/sangue , Imunoglobulina G/líquido cefalorraquidiano , Imunoglobulina G/sangue , Falha de Tratamento , Proteína 1 Semelhante à Quitinase-3/sangue , Proteína 1 Semelhante à Quitinase-3/líquido cefalorraquidiano , Imunoglobulina M/líquido cefalorraquidiano , Imunoglobulina M/sangue , PrognósticoRESUMO
The present investigation assessed the Liaison® diagnostic performance in detecting Epstein-Barr (EBV) IgM-VCA in a large patient cohort, considering age and symptomatology. VIDAS® were employed as a benchmark for acute EBV infection. The study also probed other coexisting conditions and potential cross-reactivity for error sources. A total of 1311 samples were analyzed, with notable associations found only among paediatric (kappa=0.75) and young adult (kappa=0.58) populations with compatible symptoms. ROC analysis revealed varying optimal cutoff values based on age and symptom categorizations. Logistic regression models identified age and patients from Oncology or Infectious Disease as significant factors for false positives. Potential interferences emerged with RF, ANCA, cytomegalovirus-IgM and VHS-IgM. Notably, Liaison® couldn´t distinguish EBV patients from Oncology, Haemathology or Internal Medicine. This study provides valuable insights, such as implementing ageand symptom-specific thresholds or reviewing test requests, for optimizing EBV serology in microbiology laboratories, leading to faster and more reliable responses.