TY - JOUR
T1 - Prognosis for patients with amyotrophic lateral sclerosis
T2 - development and validation of a personalised prediction model
AU - Westeneng, Henk Jan
AU - Debray, Thomas P.A.
AU - Visser, Anne E.
AU - van Eijk, Ruben P.A.
AU - Rooney, James P.K.
AU - Calvo, Andrea
AU - Martin, Sarah
AU - McDermott, Christopher J.
AU - Thompson, Alexander G.
AU - Pinto, Susana
AU - Kobeleva, Xenia
AU - Rosenbohm, Angela
AU - Stubendorff, Beatrice
AU - Sommer, Helma
AU - Middelkoop, Bas M.
AU - Dekker, Annelot M.
AU - van Vugt, Joke J.F.A.
AU - van Rheenen, Wouter
AU - Vajda, Alice
AU - Heverin, Mark
AU - Kazoka, Mbombe
AU - Hollinger, Hannah
AU - Gromicho, Marta
AU - Körner, Sonja
AU - Ringer, Thomas M.
AU - Rödiger, Annekathrin
AU - Gunkel, Anne
AU - Shaw, Christopher E.
AU - Bredenoord, Annelien L.
AU - van Es, Michael A.
AU - Corcia, Philippe
AU - Couratier, Philippe
AU - Weber, Markus
AU - Grosskreutz, Julian
AU - Ludolph, Albert C.
AU - Petri, Susanne
AU - de Carvalho, Mamede
AU - Van Damme, Philip
AU - Talbot, Kevin
AU - Turner, Martin R.
AU - Shaw, Pamela J.
AU - Al-Chalabi, Ammar
AU - Chiò, Adriano
AU - Hardiman, Orla
AU - Moons, Karel G.M.
AU - Veldink, Jan H.
AU - van den Berg, Leonard H.
N1 - Funding Information:
JPKR reports grants from the Irish Health Research Board (grant number HPF-2014-537). CJM was supported by the UK Motor Neurone Disease Association. MAvE serves on the Motor Neurone Disease Association biomedical research advisory panel, has consulted for Biogen and received travel grants from Baxalta, and funding sources include the Netherlands Organization for Health Research and Development (Veni scheme), The Thierry Latran Foundation, the ALS Foundation Netherlands, and the European Union (EU) Joint Programme Neurodegenerative Disease Research (JPND). MW reports personal fees from Biogen Idec and Mitsubishi Tanabe Pharma. SP reports grants from the German Neuromuscular Society, the German Federal Ministry of Education and Research, clinical trial funding from Cytokinetics, GlaxoSmithKline, and Orion Pharma, and speaking fees from Teva Pharmaceutical Industries. PVD reports personal fees for advisory work from Cytokinetics, and personal fees for advisory work (paid to his institution) from Biogen, Pfizer, CSL Behring, and Treeway. KT is supported by the Motor Neurone Disease Association and the UK Medical Research Council (MRC). MRT is supported by the UK MRC and Motor Neurone Disease Association Lady Edith Wolfson Senior Clinical Fellowship (MR/K01014X/1). PJS reports grants from the UK National Institute of Health Research (NIHR; Senior Investigator Award), Sheffield NIHR Biomedical Research Centre for Translational Neuroscience, the Motor Neurone Disease Association, the EU JPND (STRENGTH project), the UK MRC, EU Horizon 2020 (Modifying Immune Response and Outcomes in ALS [MIROCALS] trial) and grants from ReNeuron; and clinical trial funding from Cytokinetics, Orion Pharma, and Biogen Idec. AA-C is a consultant for Mitsubishi Tanabe Pharma, Chronos Therapeutics, Orion Pharma, Cytokinetics, and Treeway. AC reports grants from Italfarmaco, and personal fees from Biogen Idec and Mitsubishi. OH is a journal editor for Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration; and reports grants from the Irish Health Research Board (CSA 2012/11), Science Foundation Ireland (15/SPP/3244 and 16/ERCD/3854), and the charity Research Motor Neurone. LHvdB reports grants from The Netherlands ALS Foundation, The Netherlands Organization for Health Research and Development (ZonMw; Vici scheme), the EU 7th framework programme (grant number 259867) for the Euro-MOTOR project, The Netherlands Organization for Health Research and Development (Sampling and biomarker OPtimization and Harmonization In ALS and other motor neuron diseases [SOPHIA], funded through JPND), and Baxalta; and personal fees from Biogen, Cytokinetics, and Baxalta. All other authors declare no competing interests.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/5/30
Y1 - 2018/5/30
N2 - Background: Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods: We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal–external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings: Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9–168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63–1·79), age at onset (1·03, 1·03–1·03), definite versus probable or possible ALS (1·47, 1·39–1·55), diagnostic delay (0·52, 0·51–0·53), forced vital capacity (HR 0·99, 0·99–0·99), progression rate (6·33, 5·92–6·76), frontotemporal dementia (1·34, 1·20–1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31–1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77–0·80; 95% prediction interval [PI] 0·74–0·82) and the calibration slope was 1·01 (95% CI 0·95–1·07; 95% PI 0·83–1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation: We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding: Netherlands ALS Foundation.
AB - Background: Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods: We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal–external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings: Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9–168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63–1·79), age at onset (1·03, 1·03–1·03), definite versus probable or possible ALS (1·47, 1·39–1·55), diagnostic delay (0·52, 0·51–0·53), forced vital capacity (HR 0·99, 0·99–0·99), progression rate (6·33, 5·92–6·76), frontotemporal dementia (1·34, 1·20–1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31–1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77–0·80; 95% prediction interval [PI] 0·74–0·82) and the calibration slope was 1·01 (95% CI 0·95–1·07; 95% PI 0·83–1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation: We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding: Netherlands ALS Foundation.
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U2 - 10.1016/S1474-4422(18)30089-9
DO - 10.1016/S1474-4422(18)30089-9
M3 - Article
C2 - 29598923
AN - SCOPUS:85044357075
SN - 1474-4422
VL - 17
SP - 423
EP - 433
JO - The Lancet Neurology
JF - The Lancet Neurology
IS - 5
ER -