title: Biomarker-based predictive models for prognosis in amyotrophic lateral sclerosis.
abstract: OBJECTIVE
  Although median survival in amyotrophic lateral sclerosis (ALS) is 2 to 4 years, survival ranges from months to decades, creating prognostic uncertainty. Strategies to predict prognosis would benefit clinical management and outcomes assessments of clinical trials.
  
  
  OBJECTIVE
  To identify biomarkers in plasma and cerebrospinal fluid (CSF) of patients with ALS that can predict prognosis.
  
  
  METHODS
  We conducted a retrospective study of plasma (n = 29) and CSF (n = 33) biomarkers identified in samples collected between March 16, 2005, and August 22, 2007, from patients with ALS at an academic tertiary care center. Participants included patients who were undergoing diagnostic evaluation in the neurology outpatient clinic and were eventually identified as having definite, probable, laboratory-supported probable, or possible ALS as defined by revised El-Escorial criteria. All were white and none had a family history of ALS. Clinical information extended from initial presentation to death. Genotyping for hemochromatosis (HFE) gene status was performed. Multiplex and immunoassay analysis of plasma and CSF was used to measure levels of 35 biomarkers. Statistical modeling was used to identify biomarker panels that could predict total disease duration.
  
  
  METHODS
  Total disease duration, defined as the time from symptom onset to death, was the main outcome. The hypothesis being tested was formulated after data collection.
  
  
  RESULTS
  Multivariable models for total disease duration using biomarkers from plasma, CSF, and plasma and CSF combined incorporated 7, 6, and 6 biomarkers to achieve goodness-of-fit R2 values of 0.769, 0.617, and 0.962, respectively. After classification into prognostic categories, actual and predicted values achieved moderate to good agreement, with Cohen κ values of 0.526, 0.515, and 0.930 for plasma, CSF, and plasma and CSF combined models, respectively. Inflammatory biomarkers, including select interleukins, growth factors such as granulocyte colony-stimulating factor, and l-ferritin, had predictive value.
  
  
  CONCLUSIONS
  This study provides proof-of-concept for a novel multivariable modeling strategy to predict ALS prognosis. These results support unbiased biomarker discovery efforts in larger patient cohorts with detailed longitudinal follow-up.
authors.affiliation: George M. Leader Family Laboratory, Department of Neurosurgery, The Pennsylvania State University College of Medicine, Hershey.
authors.forename: Xiaowei William
authors.initials: XW
authors.lastname: Su
authors.affiliation: Department of Neurology, The Pennsylvania State University College of Medicine, Milton S. Hershey Medical Center, Hershey.
authors.forename: Zachary
authors.initials: Z
authors.lastname: Simmons
authors.affiliation: George M. Leader Family Laboratory, Department of Neurosurgery, The Pennsylvania State University College of Medicine, Hershey3now with Department of Otolaryngology, University of Washington Medical Center, Seattle.
authors.forename: Ryan Michael
authors.initials: RM
authors.lastname: Mitchell
authors.affiliation: Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey.
authors.forename: Lan
authors.initials: L
authors.lastname: Kong
authors.affiliation: Department of Neurology, The Pennsylvania State University College of Medicine, Milton S. Hershey Medical Center, Hershey.
authors.forename: Helen Elizabeth
authors.initials: HE
authors.lastname: Stephens
authors.affiliation: George M. Leader Family Laboratory, Department of Neurosurgery, The Pennsylvania State University College of Medicine, Hershey.
authors.forename: James Robert
authors.initials: JR
authors.lastname: Connor
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000690:Amyotrophic Lateral Sclerosis / Q000097:blood / Q000134:cerebrospinal fluid / Q000175:diagnosis / Q000235:genetics; D015415:Biomarkers / Q000097:blood* / Q000134:cerebrospinal fluid*; D018450:Disease Progression; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D005916:Globulins / Q000378:metabolism; D000071020:Hemochromatosis Protein; D015395:Histocompatibility Antigens Class I / Q000235:genetics; D006801:Humans; D008297:Male; D008565:Membrane Proteins / Q000235:genetics; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012720:Severity of Illness Index; D014168:Transferrin / Q000378:metabolism
chemical_list: D015415:Biomarkers; D005916:Globulins; C103673:HFE protein, human; D000071020:Hemochromatosis Protein; D015395:Histocompatibility Antigens Class I; D008565:Membrane Proteins; D014168:Transferrin