BACKGROUND: A growing arsenal of treatment options for relapsing multiple sclerosis (RMS) emphasises the need for early prognostic biomarkers. While evidence for individual markers exists, comprehensive analyses at the time of diagnosis are sparse. METHODS: Brain and spinal cord lesion numbers, cerebrospinal fluid parameters, initial symptoms, and Expanded Disability Status Scale (EDSS) score were determined at the time of diagnosis. Confirmed disability accumulation (CDA), defined as a sustained EDSS increase over 6 months, was determined during a 5-year follow-up. All-subsets multivariable logistic regression was performed to identify predictors of CDA. Model performance was assessed via receiver operating characteristic analysis, and individual risks were calculated. Analyses were repeated with progression independent of relapse activity (PIRA) as an outcome. RESULTS: 113/417 (27.1%) people with RMS experienced CDA on follow-up. Intrathecal IgG synthesis, a higher number of spinal cord lesions, age and polysymptomatic manifestation were identified as independent predictors of CDA. The resulting prediction model yielded an area under the curve (AUC) of 0.75 with a 95% CI of 0.70 to 0.80. Individuals exceeding the optimal thresholds for the three most significant predictors had a 61.8% likelihood of experiencing CDA, whereas those below all three thresholds had a CDA rate of 4.5%. The only significant baseline predictor differentiating PIRA from relapse-associated worsening was a higher number of spinal cord lesions (AUC=0.64, 95% CI 0.54 to 0.74). CONCLUSIONS: Intrathecal IgG synthesis, spinal cord lesion number, age and polysymptomatic manifestation are independent predictors of early CDA in newly diagnosed RMS.