Why non-inferiority is more challenging than superiority?

2017 ◽  
Vol 23 (6) ◽  
pp. 790-791 ◽  
Author(s):  
Maria Pia Sormani
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Sample Sizes ◽  
Superiority Trials

Demonstrating non-inferiority in clinical trials is usually more challenging than showing superiority. In multiple sclerosis (MS), non-inferiority trials are rarely designed since they would require prohibitive sample sizes. In this brief report, the reasons why non-inferiority trials are usually larger than superiority trials is explored.

Time to first relapse as an endpoint in multiple sclerosis clinical trials

2012 ◽  
Vol 19 (4) ◽  
pp. 466-474 ◽  
Author(s):  
MP Sormani ◽  
A Signori ◽  
P Siri ◽  
N De Stefano
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Primary Outcome ◽  
Model Fitting ◽  
Clinical Trial Design ◽  
Fixed Time ◽  
Sound Design ◽  
Sample Sizes ◽  
Design Strategies ◽  
First Relapse

Background: The increasing number of effective therapies to treat multiple sclerosis (MS) raises ethical concerns for the use of placebo in clinical trials, suggesting that new clinical trial design strategies are needed. Objectives: To evaluate time to first relapse as an endpoint for MS clinical trials. Methods: A recently-developed model fitting the distribution of time to first relapse in MS was used for simulations estimating the sample sizes of trials using this as an outcome, and for comparison with the size of trials using the annualized relapse rate (ARR) as the primary outcome. Results: Trials based on time to first relapse were feasible, requiring sample sizes that were similar or even smaller than if the study was based on ARR instead. In the case of low ARR (0.4 relapses/year), as is expected in future trials, the 1-year trials designed to detect a treatment effect of 30%, with 90% power, require fewer patients when based on time to first relapse (470 patients/arm) than if based on ARR (540 patients/arm). Conclusions: Our simulations show that time to first relapse is not less powerful than ARR in MS trials; thus, this measure would be a potentially useful primary outcome offering the advantage of an ethically sound design, as the patients randomized to placebo can then switch to the active drug, once they relapse. A potential drawback is the loss of information for other endpoints collected at fixed time points.

Digital Technology in Clinical Trials for Multiple Sclerosis: a systematic review. (Preprint)

2020 ◽  
Author(s):  
Marcello De Angelis ◽  
Luigi Lavorgna ◽  
Antonio Carotenuto ◽  
Martina Petruzzo ◽  
Roberta Lanzillo ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Outcome Measures ◽  
Digital Technology ◽  
Clinical Trial Design ◽  
Motor Rehabilitation ◽  
Robot Assisted ◽  
Future Directions ◽  
Treatment Side Effects

BACKGROUND Clinical trials in multiple sclerosis (MS) have leveraged the use of digital technology to overcome limitations in treatment and disease monitoring. OBJECTIVE To review the use of digital technology in concluded and ongoing MS clinical trials. METHODS In March 2020, we searched for “multiple sclerosis” and “trial” on pubmed.gov and clinicaltrials.gov using “app”, “digital”, “electronic”, “internet” and “mobile” as additional search words, separately. Overall, we included thirty-five studies. RESULTS Digital technology is part of clinical trial interventions to deliver psychotherapy and motor rehabilitation, with exergames, e-training, and robot-assisted exercises. Also, digital technology has become increasingly used to standardise previously existing outcome measures, with automatic acquisitions, reduced inconsistencies, and improved detection of symptoms. Some trials have been developing new patient-centred outcome measures for the detection of symptoms and of treatment side effects and adherence. CONCLUSIONS We will discuss how digital technology has been changing MS clinical trial design, and possible future directions for MS and neurology research.

scholarly journals Disability improvement as a clinically relevant outcome in clinical trials of relapsing forms of multiple sclerosis

2021 ◽  
pp. 135245852110002
Author(s):  
Bruce AC Cree ◽  
Jeffrey A Cohen ◽  
Anthony T Reder ◽  
Davorka Tomic ◽  
Diego Silva ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Therapeutic Benefit ◽  
Disease Modifying Therapies ◽  
Long Term Follow Up ◽  
Post Hoc ◽  
Switch Group ◽  
Relevant Outcome

Background: Disease-modifying therapies (DMTs) can reduce the risk of disability worsening in patients with relapsing forms of multiple sclerosis (RMS). High-efficacy DMTs can lead to confirmed or sustained disability improvement (CDI and SDI). Objective and Methods: Post hoc analyses of data from the TRANSFORMS, FREEDOMS, and FREEDOMS II trials and their extensions assessed the effects of fingolimod (0.5–1.25 mg/day) on stabilizing or improving disability over ⩽8 years in participants with RMS. CDI and SDI rates were compared between participants initially randomized to fingolimod, interferon (IFNβ-1a), or placebo. Results: At 8 years’ follow-up in TRANSFORMS, 35.1% (95% confidence interval [CI], 28.2%–43.1%) of assessed participants in the IFNβ-1a–fingolimod switch group and 41.9% (36.6%–47.6%) on continuous fingolimod experienced CDI; disability did not worsen in approximately 70%. Similar results were seen in the combined FREEDOMS population. Proportionally fewer TRANSFORMS participants achieved SDI in the IFNβ-1a–fingolimod switch group than on continuous fingolimod (5.4% [3.0%–9.5%] vs 14.2% [10.8%–18.4%], p = 0.01). Conclusion: CDI and SDI are outcomes of interest for clinical trials and for long-term follow-up of participants with RMS. Monitoring CDI and SDI in addition to disability worsening may facilitate understanding of the therapeutic benefit of RMS treatments.

scholarly journals Sample sizes in dosage investigational clinical trials: a systematic evaluation

2015 ◽  
pp. 305 ◽  
Author(s):  
Jihan Huang ◽  
Qianmin Su ◽  
juan yang ◽  
yinghua lv ◽  
yingchun he ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Systematic Evaluation ◽  
Sample Sizes

scholarly journals Using magnetic resonance imaging in animal models to guide drug development in multiple sclerosis

2013 ◽  
Vol 20 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Nabeela Nathoo ◽  
V Wee Yong ◽  
Jeff F Dunn
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Magnetic Resonance ◽  
Animal Models ◽  
Mr Imaging ◽  
Preclinical Studies ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Potential Therapeutics

Major advances are taking place in the development of therapeutics for multiple sclerosis (MS), with a move past traditional immunomodulatory/immunosuppressive therapies toward medications aimed at promoting remyelination or neuroprotection. With an increase in diversity of MS therapies comes the need to assess the effectiveness of such therapies. Magnetic resonance imaging (MRI) is one of the main tools used to evaluate the effectiveness of MS therapeutics in clinical trials. As all new therapeutics for MS are tested in animal models first, it is logical that MRI be incorporated into preclinical studies assessing therapeutics. Here, we review key papers showing how MR imaging has been combined with a range of animal models to evaluate potential therapeutics for MS. We also advise on how to maximize the potential for incorporating MRI into preclinical studies evaluating possible therapeutics for MS, which should improve the likelihood of discovering new medications for the condition.

Sample Sizes for Clinical Trials by JULIOUS, S. A.

Biometrics ◽  
2012 ◽  
Vol 68 (1) ◽  
pp. 327-328
Author(s):  
Janet T. Wittes
Keyword(s):  
Clinical Trials ◽  
Sample Sizes

Control arm heterogeneity in trials for unselected advanced triple-negative breast cancer (aTNBC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1082-1082
Author(s):  
Kinisha Gala ◽  
Ankit Kalucha ◽  
Samuel Martinet ◽  
Anushri Goel ◽  
Kalpana Devi Narisetty ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Single Agent ◽  
Progression Free Survival ◽  
Sample Sizes ◽  
Time To Event ◽  
Sample Size Calculations ◽  
Subgroup Analyses ◽  
Combination Regimens

1082 Background: Primary endpoints of clinical trials frequently include subgroup-analyses. Several solid cancers such as aTNBC are heterogeneous, which can lead to unpredictable control arm performance impairing accurate assumptions for sample size calculations. We explore the value of a comprehensive clinical trial results repository in assessing control arm heterogeneity with aTNBC as the pilot. Methods: We identified P2/3 trials reporting median overall survival (mOS) and/or median progression-free survival (mPFS) in unselected aTNBC through a systematic search of PubMed, clinical trials databases and conference proceedings. Trial arms with sample sizes ≤25 or evaluating drugs no longer in development were excluded. Due to inconsistency among PD-L1 assays, PD-L1 subgroup analyses were not assessed separately. The primary aim was a descriptive analysis of control arm mOS and mPFS across all randomized trials in first line (1L) aTNBC. Secondary aims were to investigate time-to-event outcomes in control arms in later lines and to assess time-trends in aTNBC experimental and control arm outcomes. Results: We included 33 trials published between June 2013-Feb 2021. The mOS of control arms in 1L was 18.7mo (range 12.6-22.8) across 5 trials with single agent (nab-) paclitaxel [(n)P], and 18.1mo (similar range) for 7 trials including combination regimens (Table). The mPFS of control arms in 1L was 4.9mo (range 3.8-5.6) across 5 trials with single-agent (n)P, and 5.6mo (range 3.8-6.1) across 8 trials including combination regimens. Control arm mOS was 13.1mo (range 9.4-17.4) for 3 trials in first and second line (1/2L) and 8.7mo (range 6.7-10.8) across 5 trials in 2L and beyond. R2 for the mOS best-fit lines across control and experimental arms over time was 0.09, 0.01 and 0.04 for 1L, 1/2L and 2L and beyond, respectively. Conclusions: Median time-to-event outcomes of control arms in 1L aTNBC show considerable heterogeneity, even among trials with comparable regimens and large sample sizes. Disregarding important prognostic factors at stratification can lead to imbalances between arms, which may jeopardize accurate sample size calculations, trial results and interpretation. Optimizing stratification and assumptions for power calculations is of utmost importance in aTNBC and beyond. A digitized trial results repository with precisely defined patient populations and treatment settings could improve accuracy of assumptions during clinical trial design.[Table: see text]

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