Human Subjects with MS and Non-immunological Neurological Diseases
In a study involving 61 patients with multiple sclerosis (MS) and controls, the κ-FLC index identified MS with high accuracy (AUC of 0.93). This index showed comparable results to other metrics like CSF κ-FLC and Qκ-FLC. However, these results did not hold significance after accounting for age-related adjustments.
- Tags
- #MSResearch
- Most relevant to
- —
Why it matters
The κ-FLC index may help differentiate MS from other neurological conditions, which is crucial for accurate diagnosis. High AUC values suggest this metric could be valuable in clinical settings.
What this does not prove
The initial predictive validity of unadjusted cut-offs did not maintain significance after adjusting for other variables, such as age at onset, which limits the strength of the findings.
Next milestone
No next milestone was established from the available source.
Study facts
- Study design
- Observational
- Participants / samples
- 61 · basis not reported
- Randomised
- Not reported
- Controlled
- Yes
- Primary endpoint met
- No
- Relevant MS type
- Not reported
- Publication date
- 2026-10-02
- Evidence reviewed
- Abstract only
- Regulatory approval
- Not reported
- Research areas
- Not classified
Original sources
- Primary evidenceDiagnostic accuracy and age-dependent prognostic confounding of kappa free light chain parameters in multiple sclerosis. ↗DOI: 10.1016/j.msard.2026.107955
Supporting passages (8)
study designIn this retrospective study across two tertiary centers, we included patients with MS and controls with non-immunological neurological disease.
subjectsWe evaluated 61 patients with MS and 18 non-immunological neurological diseases over a median follow-up of 8.1 years.
sample sizeWe evaluated 61 patients with MS and 18 non-immunological neurological diseases over a median follow-up of 8.1 years.
controlledMETHODS: In this retrospective study across two tertiary centers, we included patients with MS and controls with non-immunological neurological disease.
primary endpoint metAlthough unadjusted cut-offs appeared predictive on standard log-rank testing, no κ-FLC metric retained prognostic significance after correction for threshold optimization or multivariable adjustment for age at onset.
findingsThe κ-FLC index discriminated MS from controls with an area under the curve (AUC) of 0.93 (cut-off: 5.7), performing comparably to CSF κ-FLC (AUC: 0.94) and Qκ-FLC (AUC: 0.97).
limitationsAlthough unadjusted cut-offs appeared predictive on standard log-rank testing, no κ-FLC metric retained prognostic significance after correction for threshold optimization or multivariable adjustment for age at onset.
publication datePublication date: 2026-10-02
AI assessment, not yet reviewed by a person · version 1 · Community votes are separate from evidence review.