Objectives: This study compared neurofilament light chain (NFL) levels in the cerebrospinal fluid (CSF) of patients with sporadic amyotrophic lateral sclerosis (sALS) with levels in patients with other neurological diseases and healthy controls and assessed correlations between NFL levels and clinical indicators of sALS. Methods: We used enzyme-linked immunosorbent assays to determine the NFL levels in the CSF of 45 patients with sALS, 21 patients with other central nervous system diseases (OCNSDs), 18 with immune-mediated peripheral neuropathy (IMPN), 14 with non-immune-mediated peripheral neuropathy (NIMPN), and 19 healthy controls (HCs). Results: The median NFL levels in the CSF of the sALS, OCNSD, IMPN, NIMPN, and HC groups were 6510, 5372, 4320, 1477, and 756 pg/mL, respectively. The CSF NFL levels did not differ significantly among the sALS, IMPN, and OCNSD groups, but were significantly higher than those of the NIMPN and HC groups. The NFL CSF levels were significantly higher in the NIMPN group than the HCs. There was a negative correlation between the NFL level and ALS function score (ALSFRS-R), and a positive correlation with the disease progression rate in patients with sALS. Conclusion: CSF NFL may not be sufficient to distinguish ALS from other central nervous system diseases or peripheral neuropathy, but it predicts ALS severity and progression.

It is important to determine prognostic factors for the outcome of amyotrophic lateral sclerosis (ALS) at an early stage. The time taken for symptoms to spread from spinal or bulbar regions to both (time to generalization; TTG) is considered a strong predictor of survival; however, this has rarely been studied in Asian populations. The aim of this retrospective study was to evaluate potential factors affecting prognosis in Chinese patients with sporadic ALS, with a focus on the association between TTG and overall survival. Seventy-one patients with sporadic ALS who were hospitalized at Chinese PLA General Hospital from 2009 to 2016 were followed up until December 2017. Survival analysis was performed using univariate Kaplan-Meier log-rank and multivariate Cox proportional hazards models. The clinical data of the patients were recorded and analyzed. Variables studied were age at symptom onset, sex, site of symptom onset, diagnostic latency, TTG, diagnostic category, ALS Functional Rating Scale-revised score, percent predicted forced vital capacity (FVC%), and disease progression rate (DPR) at diagnosis. The mean age at onset was 54 (SD = 10.2) years, and the median survival time from symptom onset was 41 months (95% confidence interval: 34–47). By univariate analysis, factors independently affecting survival were age at symptom onset (Log rank = 15.652, P < 0.0001), TTG (Log rank = 14.728, P < 0.0001), diagnostic latency (Log rank = 11.997, P = 0.001), and DPR (Log rank = 6.50, P = 0.011). In the Cox multivariate model, TTG had the strongest impact on survival time (hazard ratio = 0.926, P = 0.01). TTG can be used as an effective indicator of prognosis in patients with sporadic ALS.

Objectives: To analyze the factors affecting prognosis of patients with sporadic amyotrophic lateral sclerosis (ALS), to establish a nomogram predictive model. Methods: A total of 236 patients with sporadic ALS hospitalized in the Department of Neurology of the First Medical Center, Chinese PLA General Hospital, from March 2011 to November 2021 were enrolled in the study. Basic information and clinical and laboratory data of patients were collected, including sex, age at onset, body mass index, disease duration, diagnostic grade, and serum levels of creatine kinase (CK), creatinine (Cr), uric acid (UA), and ferritin. Kaplan-Meier univariate and multivariate Cox proportional hazard regression models were used to analyze the prognostic factors, and a nomogram predictive model was established. Results: Univariate analysis showed that ferritin, CK, Cr, age at onset, disease duration, and body mass index (BMI) were all correlated with prognosis of ALS. Multivariate analysis showed that ferritin, Cr, disease duration, age at onset, and BMI were the strongest predictors. ROC curve and correction curve analyses verified the accuracy of the nomogram prediction model. Conclusions: Ferritin, Cr, disease duration, age at onset, and BMI are independent predictors of survival in patients with ALS. Based on these clinical and biological prognostic factors, we established a quantitative model for predicting survival probability, and may assist in the prognostic evaluation of ALS, pending further validation.