Clinical trials in pediatric ALS: a TRICALS feasibility study.

Background: Pediatric investigation plans (PIPs) describe how adult drugs can be studied in children. In 2015, PIPs for Amyotrophic Lateral Sclerosis (ALS) became mandatory for European marketing-authorization of adult treatments, unless a waiver is granted by the European Medicines Agency (EMA).Objective: To assess the feasibility of clinical studies on the effect of therapy in children (<18 years) with ALS in Europe.Methods: The EMA database was searched for submitted PIPs in ALS. A questionnaire was sent to 58 European ALS centers to collect the prevalence of pediatric ALS during the past ten years, the recruitment potential for future pediatric trials, and opinions of ALS experts concerning a waiver for ALS.Results: Four PIPs were identified; two were waived and two are planned for the future. In total, 49 (84.5%) centers responded to the questionnaire. The diagnosis of 44,858 patients with ALS was reported by 46 sites; 39 of the patients had an onset < 18 years (prevalence of 0.008 cases per 100,000 or 0.087% of all diagnosed patients). The estimated recruitment potential (47 sites) was 26 pediatric patients within five years. A majority of ALS experts (75.5%) recommend a waiver should apply for ALS due to the low prevalence of pediatric ALS.Conclusions: ALS with an onset before 18 years is extremely rare and may be a distinct entity from adult ALS. Conducting studies on the effect of disease-modifying therapy in pediatric ALS may involve lengthy recruitment periods, high costs, ethical/legal implications, challenges in trial design and limited information

Comparing methods to combine functional loss and mortality in clinical trials for amyotrophic lateral sclerosis

Ruben PA van Eijk,1 Marinus JC Eijkemans,2 Dimitris Rizopoulos,3 Leonard H van den Berg,4,* Stavros Nikolakopoulos5,* 1Department of Neurology, University Medical Center Utrecht, Utrecht, the Netherlands; 2Department of Biostatistics, University Medical Center Utrecht, Utrecht, the Netherlands; 3Department of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands; 4Department of Neurology, University Medical Center Utrecht, Utrecht, the Netherlands; 5Department of Biostatistics, University Medical Center Utrecht, Utrecht, the Netherlands *These authors contributed equally to this work Objective: Amyotrophic lateral sclerosis (ALS) clinical trials based on single end points only partially capture the full treatment effect when both function and mortality are affected, and may falsely dismiss efficacious drugs as futile. We aimed to investigate the statistical properties of several strategies for the simultaneous analysis of function and mortality in ALS clinical trials. Methods: Based on the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we simulated longitudinal patterns of functional decline, defined by the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R) and conditional survival time. Different treatment scenarios with varying effect sizes were simulated with follow-up ranging from 12 to 18&nbsp;months. We considered the following analytical strategies: 1) Cox model; 2) linear mixed effects (LME) model; 3) omnibus test based on Cox and LME models; 4) composite time-to-6-point decrease or death; 5) combined assessment of function and survival (CAFS); and 6) test based on joint modeling framework. For each analytical strategy, we calculated the empirical power and sample size. Results: Both Cox and LME models have increased false-negative rates when treatment exclusively affects either function or survival. The joint model has superior power compared to other strategies. The composite end point increases false-negative rates among all treatment scenarios. To detect a 15% reduction in ALSFRS-R decline and 34% decline in hazard with 80% power after 18&nbsp;months, the Cox model requires 524 patients, the LME model 794 patients, the omnibus test 526 patients, the composite end point 1,274 patients, the CAFS 576 patients and the joint model 464 patients. Conclusion: Joint models have superior statistical power to analyze simultaneous effects on survival and function and may circumvent pitfalls encountered by other end points. Optimizing trial end points is essential, as selecting suboptimal outcomes may disguise important treatment clues. Keywords: joint models, CAFS, clinical trials, amyotrophic lateral sclerosi

Prediction of personalised prognosis in patients with amyotrophic lateral sclerosis: development and validation of a prediction model

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 noninvasive 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&lt;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.</p