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Contains fulltext : 232638.pdf (Publisher’s version ) (Open Access), In rare diseases, typically only a small number of patients are available for a randomized clinical trial. Nevertheless, it is not uncommon that more than one study is performed to evaluate a (new) treatment. Scarcity of available evidence makes it particularly valuable to pool the data in a meta-analysis. When the primary outcome is binary, the small sample sizes increase the chance of observing zero events. The frequentist random-effects model is known to induce bias and to result in improper interval estimation of the overall treatment effect in a meta-analysis with zero events. Bayesian hierarchical modeling could be a promising alternative. Bayesian models are known for being sensitive to the choice of prior distributions for between-study variance (heterogeneity) in sparse settings. In a rare disease setting, only limited data will be available to base the prior on, therefore, robustness of estimation is desirable. We performed an extensive and diverse simulation study, aiming to provide practitioners with advice on the choice of a sufficiently robust prior distribution shape for the heterogeneity parameter. Our results show that priors that place some concentrated mass on small τ values but do not restrict the density for example, the Uniform(-10, 10) heterogeneity prior on the log(τ(2) ) scale, show robust 95% coverage combined with less overestimation of the overall treatment effect, across varying degrees of heterogeneity. We illustrate the results with meta-analyzes of a few small trials.

Item does not contain fulltext, In drug development programs, proof-of-concept Phase II clinical trials typically have a biomarker as a primary outcome, or an outcome that can be observed with relatively short follow-up. Subsequently, the Phase III clinical trials aim to demonstrate the treatment effect based on a clinical outcome that often needs a longer follow-up to be assessed. Early-phase outcomes or biomarkers are typically associated with late-phase outcomes and they are often included in Phase III trials. The decision to proceed to Phase III development is based on analysis of the early-Phase II outcome data. In rare diseases, it is likely that only one Phase II trial and one Phase III trial are available. In such cases and before drug marketing authorization requests, positive results of the early-phase outcome of Phase II trials are then likely seen as supporting (or even replicating) positive Phase III results on the late-phase outcome, without a formal retrospective combined assessment and without accounting for between-study differences. We used double-regression modeling applied to the Phase II and Phase III results to numerically mimic this informal retrospective assessment. We provide an analytical solution for the bias and mean square error of the overall effect that leads to a corrected double-regression. We further propose a flexible Bayesian double-regression approach that minimizes the bias by accounting for between-study differences via discounting the Phase II early-phase outcome when they are not in line with the Phase III biomarker outcome results. We illustrate all methods with an orphan drug example for Fabry disease.

Contains fulltext : 235577.pdf (Publisher’s version ) (Open Access), Objective: The ALSFRS-R is limited by multidimensionality, which originates from the summation of various subscales. This prevents a direct comparison between patients with identical total scores. We aim to evaluate how multidimensionality affects the performance of the ALSFRS-R in clinical trials. Methods: We simulated clinical trial data with different treatment effects for the ALSFRS-R total score and its subscales (i.e. bulbar, fine motor, gross motor and respiratory). We considered scenarios where treatment reduced the rate of ALSFRS-R subscale decline either uniformly (i.e. all subscales respond identically to treatment) or non-uniformly (i.e. subscales respond differently to treatment). Two main analytical strategies were compared: (1) analyzing only the total score or (2) utilizing a subscale-based test (i.e. alternative strategy). For each analytical strategy, we calculated the empirical power and required sample size. Results: Both strategies are valid when there is no treatment benefit and provide adequate control of type 1 error. If all subscales respond identically to treatment, using the total score is the most powerful approach. As the differences in treatment responses between subscales increase, the more the total score becomes affected. For example, to detect a 40% reduction in the bulbar rate of decline with 80% power, the total score requires 1380 patients, whereas this is 336 when using the alternative strategy. Conclusions: Ignoring the multidimensional structure of the ALSFRS-R total score could have negative consequences for ALS clinical trials. We propose determining treatment benefit on a subscale level, prior to stating whether a treatment is generally effective.

BACKGROUND: Surgical site infections (SSIs) are common complications after colorectal surgery. Oral non-absorbable antibiotic prophylaxis (OAP) can be administered preoperatively to reduce the risk of SSIs. Its efficacy without simultaneous mechanical cleaning is unknown. METHODS: The Precaution trial was a double-blind, placebo-controlled randomized clinical trial conducted in six Dutch hospitals. Adult patients who underwent elective colorectal surgery were randomized to receive either a three-day course of preoperative OAP with tobramycin and colistin or placebo. The primary composite endpoint was the incidence of deep SSI or mortality within 30 days after surgery. Secondary endpoints included both infectious and non-infectious complications at 30 days and six months after surgery. RESULTS: The study was prematurely ended due to the loss of clinical equipoise. At that time, 39 patients had been randomized to active OAP and 39 to placebo, which reflected 8.1% of the initially pursued sample size. Nine (11.5%) patients developed the primary outcome, of whom four had been randomized to OAP (4/39; 10.3%) and five to placebo (5/39; 12.8%). This corresponds to a risk ratio in the intention-to-treat analysis of 0.80 (95% confidence interval (CI) 0.23-2.78). In the per-protocol analysis, the relative risk was 0.64 (95% CI 0.12-3.46). CONCLUSIONS: Observational data emerging during the study provided new evidence for the effectiveness of OAP that changed both the clinical and medical ethical landscape for infection prevention in colorectal surgery. We therefore consider it unethical to continue randomizing patients to placebo. We recommend the implementation of OAP in clinical practice and continuing monitoring of infection rates and antibiotic susceptibilities. TRIAL REGISTRATION: The PreCaution trial is registered in the Netherlands Trial Register under NL5932 (previously: NTR6113) as well as in the EudraCT register under 2015-005736-17.

Contains fulltext : 215389.pdf (publisher's version ) (Open Access), The sample size of a randomized controlled trial is typically chosen in order for frequentist operational characteristics to be retained. For normally distributed outcomes, an assumption for the variance needs to be made which is usually based on limited prior information. Especially in the case of small populations, the prior information might consist of only one small pilot study. A Bayesian approach formalizes the aggregation of prior information on the variance with newly collected data. The uncertainty surrounding prior estimates can be appropriately modelled by means of prior distributions. Furthermore, within the Bayesian paradigm, quantities such as the probability of a conclusive trial are directly calculated. However, if the postulated prior is not in accordance with the true variance, such calculations are not trustworthy. In this work we adapt previously suggested methodology to facilitate sample size re-estimation. In addition, we suggest the employment of power priors in order for operational characteristics to be controlled.

Contains fulltext : 215404.pdf (publisher's version ) (Open Access), 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.

Item does not contain fulltext, Radioembolization of liver malignancies with (166)Ho-microspheres has been shown to be safe in a phase 1 dose-escalation study. The purpose of this study was to investigate the efficacy of (166)Ho radioembolization. Methods: In this prospective single-arm study, 56 patients were enrolled, all with liver metastases refractory to systemic therapy and ineligible for surgical resection. The primary outcome was a response by 2 target lesions on triphasic liver CT scans 3 mo after therapy, as assessed using RECIST, version 1.1. Secondary outcomes included overall tumor response, time to imaging progression, overall survival, toxicity, quality of life, and quantification of the microspheres on SPECT and MRI. Results: Between May 2012 and March 2015, 38 eligible patients were treated, one of whom was not evaluable. In 27 (73%) of 37 patients, the target lesions showed complete response, partial response, or stable disease (disease control) at 3 mo (95% confidence interval [CI], 57%-85%). The median overall survival was 14.5 mo (95% CI, 8.6-22.8 mo). For colorectal cancer patients (n = 23), the median overall survival was 13.4 mo (95% CI, 8.2-15.7 mo). Grade 3 or 4 toxic events after treatment (according to the Common Terminology Criteria for Adverse Events, version 4.03) included abdominal pain (in 18% of patients), nausea (8%), ascites (3%), fatigue (3%), gastric stenosis (3%), hepatic failure (3%), liver abscesses (3%), paroxysmal atrial tachycardia (3%), thoracic pain (3%), upper gastrointestinal hemorrhage (3%), and vomiting (3%). On SPECT, (166)Ho could be quantified with high accuracy and precision, with a mean overestimation of 9.3% +/- 7.1% in the liver. Conclusion: Radioembolization with (166)Ho-microspheres induced a tumor response with an acceptable toxicity profile in salvage patients with liver metastases.

Innovations are urgently required for clinical development of antibacterials against multidrug-resistant organisms. Therefore, a European, public-private working group (STAT-Net; part of Combatting Bacterial Resistance in Europe [COMBACTE]), has reviewed and tested several innovative trials designs and analytical methods for randomized clinical trials, which has resulted in 8 recommendations. The first 3 focus on pharmacokinetic and pharmacodynamic modeling, emphasizing the pertinence of population-based pharmacokinetic models, regulatory procedures for the reassessment of old antibiotics, and rigorous quality improvement. Recommendations 4 and 5 address the need for more sensitive primary end points through the use of rank-based or time-dependent composite end points. Recommendation 6 relates to the applicability of hierarchical nested-trial designs, and the last 2 recommendations propose the incorporation of historical or concomitant trial data through Bayesian methods and/or platform trials. Although not all of these recommendations are directly applicable, they provide a solid, evidence-based approach to develop new, and established, antibacterials and address this public health challenge.

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 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 months, the Cox model requires 524 patients, the LME model 794 patients, the omnibus test 526 patients, the composite end poin