Benchmarking of survival outcomes following Haematopoietic Stem Cell Transplantation (HSCT): an update of the ongoing project of the European Society for Blood and Marrow Transplantation (EBMT) and Joint Accreditation Committee of ISCT and EBMT (JACIE).

From 2016 EBMT and JACIE developed an international risk-adapted benchmarking program of haematopoietic stem cell transplant (HSCT) outcome to provide individual EBMT Centers with a means of quality-assuring the HSCT process and meeting FACT-JACIE accreditation requirements relating to 1-year survival outcomes. Informed by previous experience from Europe, North America and Australasia, the Clinical Outcomes Group (COG) established criteria for patient and Center selection, and a set of key clinical variables within a dedicated statistical model adapted to the capabilities of the EBMT Registry. The first phase of the project was launched in 2019 to test the acceptability of the benchmarking model through assessment of Centers' performance for 1-year data completeness and survival outcomes of autologous and allogeneic HSCT covering 2013-2016. A second phase was delivered in July 2021 covering 2015-2019 and including survival outcomes. Reports of individual Center performance were shared directly with local principal investigators and their responses were assimilated. The experience thus far has supported the feasibility, acceptability and reliability of the system as well as identifying its limitations. We provide a summary of experience and learning so far in this 'work in progress', as well as highlighting future challenges of delivering a modern, robust, data-complete, risk-adapted benchmarking program across new EBMT Registry systems.

Randomized double-blind placebo-controlled crossover trial with pyridostigmine in spinal muscular atrophy types 2-4.

Hereditary proximal spinal muscular atrophy causes weakness and increased fatigability of repetitive motor functions. The neuromuscular junction is anatomically and functionally abnormal in patients with spinal muscular atrophy. Pharmacological improvement of neuromuscular transmission may therefore represent a promising additional treatment strategy. We conducted a Phase II, monocentre, placebo-controlled, double-blind, cross-over trial with the acetylcholinesterase inhibitor pyridostigmine in treatment-naïve patients with spinal muscular atrophy types 2-4. We investigated the safety and efficacy of pyridostigmine on fatigability and motor function. Each participant received pyridostigmine and a placebo for 8 weeks, in random order. Primary outcomes were the repeated nine-hole peg test for fatigability and motor function measure. Secondary outcomes were patient-reported effects, endurance shuttle test combined scores and adverse events. We included 35 patients. For the repeated nine-hole peg test, the mean difference was 0.17 s/trial (95% confidence interval: -1.17-1.49; P = 0.8), favouring placebo, and for the motor function measure, 0.74% (95% confidence interval: 0.00-1.49; P = 0.05), favouring pyridostigmine. Around 74% of patients reported medium-to-large beneficial effects of pyridostigmine on fatigability, compared with 29.7% in the placebo arm. This was paralleled by a reduced dropout risk of 70% on the endurance shuttle test combined scores (hazard ratio: 0.30; 95% confidence interval: 0.15-0.58) under pyridostigmine. Adverse events, mostly mild and self-limiting, occurred more frequently under pyridostigmine. No serious adverse events related to the study medication were observed. Patients with spinal muscular atrophy tolerated pyridostigmine well. There were no significant differences in primary outcomes, but the self-reported reduction of fatigability and improved endurance shuttle test combined score performance suggest that pyridostigmine may be useful as an additional therapy to survival motor neuron-augmenting drugs. Trial registration number: EudraCT: 2011-004369-34, NCT02941328.

Critical design considerations for time-to-event endpoints in amyotrophic lateral sclerosis clinical trials.

BACKGROUND: Funding and resources for low prevalent neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) are limited, and optimising their use is vital for efficient drug development. In this study, we review the design assumptions for pivotal ALS clinical trials with time-to-event endpoints and provide optimised settings for future trials. METHODS: We extracted design settings from 13 completed placebo-controlled trials. Optimal assumptions were estimated using parametric survival models in individual participant data (n=4991). Designs were compared in terms of sample size, trial duration, drug use and costs. RESULTS: Previous trials overestimated the hazard rate by 18.9% (95% CI 3.4% to 34.5%, p=0.021). The median expected HR was 0.56 (range 0.33-0.66). Additionally, we found evidence for an increasing mean hazard rate over time (Weibull shape parameter of 2.03, 95% CI 1.93 to 2.15, p<0.001), which affects the design and planning of future clinical trials. Incorporating accrual time and assuming an increasing hazard rate at the design stage reduced sample size by 33.2% (95% CI 27.9 to 39.4), trial duration by 17.4% (95% CI 11.6 to 23.3), drug use by 14.3% (95% CI 9.6 to 19.0) and follow-up costs by 21.2% (95% CI 15.6 to 26.8). CONCLUSIONS: Implementing distributional knowledge and incorporating accrual at the design stage could achieve large gains in the efficiency of ALS clinical trials with time-to-event endpoints. We provide an open-source platform that helps investigators to make more accurate sample size calculations and optimise the use of their available resources.

Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised 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 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.