Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.
BACKGROUND
Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.


METHODS
Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.


RESULTS
The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001).


CONCLUSIONS
The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.
Ganesalingam
Jeban
J
Department of Clinical Neuroscience, MRC Centre for Neurodegeneration Research, King's College London, Institute of Psychiatry, London, United Kingdom.
Stahl
Daniel
D
Wijesekera
Lokesh
L
Galtrey
Clare
C
Shaw
Christopher E
CE
Leigh
P Nigel
PN
Al-Chalabi
Ammar
A
D000328:Adult; D017668:Age of Onset; D000368:Aged; D000690:Amyotrophic Lateral Sclerosis / Q000145:classification / Q000175:diagnosis* / Q000235:genetics* / Q000401:mortality; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009046:Motor Neurons / Q000378:metabolism*; D010641:Phenotype; D011379:Prognosis; D012044:Regression Analysis; D016019:Survival Analysis