Browse
Submit Data
Databases
API
Help

Dataset Information

11 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantitative strength testing in ALS clinical trials.

ABSTRACT:

Objective

To study the attributes of quantitative strength testing using hand-held dynamometry (HHD) as an efficacy measure in 2 large phase 3 amyotrophic lateral sclerosis (ALS) trials.

Methods

In the phase 3 trials of ceftriaxone and dexpramipexole, 513 and 943 patients, respectively, were enrolled in double-blind, randomized, placebo-controlled trials with planned follow-up of at least 1 year. Patients were studied every 3 months in the ceftriaxone study and every 2 months in the dexpramipexole study. Evaluators of HHD were trained and had to show evidence of adequate performance of strength testing; the testing paradigm involved testing 9 muscle groups in the upper and lower extremity bilaterally. Neither drug significantly affected any outcome measure. Strength measurements were evaluated by individual muscle and by megascores, which averaged scaled strength measures to produce an overall measure of muscle strength.

Results

A measure combining rate of decline with both within- and between-patient variabilities of measurement, the coefficient of variation for rate of change, was calculated, and showed that HHD overall performed slightly less well than Amyotrophic Lateral Sclerosis Functional Rating Scale-revised (ALSFRS-R) but better than vital capacity. Individual muscles were highly correlated to the identical muscles on the contralateral side, as well as to other muscles in the same body region. Strength decline was correlated both with ALSFRS-R and vital capacity.

Conclusion

Quantitative strength testing using HHD is a reliable and reproducible measure of decline in ALS.

SUBMITTER: Shefner JM

PROVIDER: S-EPMC4977369 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Improved stratification of ALS clinical trials using predicted survival.

Project description:In small trials, randomization can fail, leading to differences in patient characteristics across treatment arms, a risk that can be reduced by stratifying using key confounders. In ALS trials, riluzole use (RU) and bulbar onset (BO) have been used for stratification. We hypothesized that randomization could be improved by using a multifactorial prognostic score of predicted survival as a single stratifier.We defined a randomization failure as a significant difference between treatment arms on a characteristic. We compared randomization failure rates when stratifying for RU and BO ("traditional stratification") to failure rates when stratifying for predicted survival using a predictive algorithm. We simulated virtual trials using the PRO-ACT database without application of a treatment effect to assess balance between cohorts. We performed 100 randomizations using each stratification method - traditional and algorithmic. We applied these stratification schemes to a randomization simulation with a treatment effect using survival as the endpoint and evaluated sample size and power.Stratification by predicted survival met with fewer failures than traditional stratification. Stratifying predicted survival into tertiles performed best. Stratification by predicted survival was validated with an external dataset, the placebo arm from the BENEFIT-ALS trial. Importantly, we demonstrated a substantial decrease in sample size required to reach statistical power.Stratifying randomization based on predicted survival using a machine learning algorithm is more likely to maintain balance between trial arms than traditional stratification methods. The methodology described here can translate to smaller, more efficient clinical trials for numerous neurological diseases.

| S-EPMC5899911 | biostudies-literature

Use of biomarkers in ALS drug development and clinical trials.

Project description:The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis.

| S-EPMC4809521 | biostudies-literature

Analysis of start-up, retention, and adherence in ALS clinical trials.

Project description:ObjectiveTo investigate predictors of trial start-up times, high attrition, and poor protocol adherence in amyotrophic lateral sclerosis (ALS) trials.MethodsRetrospective analysis of start-up times, retention, and protocol adherence was performed on 5 clinical studies conducted by the Northeast ALS Consortium and 50 ALS clinical trials identified by PubMed search. Predictors of start-up times were estimated by accelerated failure time models with random effects. Predictors of retention and protocol deviations were estimated by mixed-model logistic regression.ResultsMedian times for contract execution and institutional review board (IRB) approval were 105 days and 125 days, respectively. Contract execution was faster at sites with more ongoing trials (p = 0.005), and more full-time (p = 0.006) and experienced (p < 0.001) coordinators. IRB approval was faster at sites with more ongoing trials (p = 0.010) and larger ALS clinics (p = 0.038). Site activation after IRB approval was faster at sites with more full-time (p = 0.038) and experienced (p < 0.001) coordinators. Twenty-two percent of surviving participants withdrew before completing the trial. Better participant functional score at baseline was an independent predictor of trial completion (odds ratio 1.29, p = 0.002) and fewer protocol deviations (odds ratio 0.86, p = 0.030).ConclusionDelays in IRB review contribute the most to prolonged trial start-up times, and these timelines are faster in sites with more experienced staff. Strategies to improve protocol adherence and participants' retention may include enrolling people at early disease stages.

| S-EPMC3806927 | biostudies-literature

Testing multiple dose combinations in clinical trials.

Project description:Drug combination trials are often motivated by the fact that individual drugs target the same disease but via different routes. A combination of such drugs may then have an overall better effect than the individual treatments which has to be verified by clinical trials. Several statistical methods have been explored that discuss the problem of comparing a fixed-dose combination therapy to each of its components. But an extension of these approaches to multiple dose combinations can be difficult and is not yet fully investigated. In this paper, we propose two approaches by which one can provide confirmatory assurance with familywise error rate control, that the combination of two drugs at differing doses is more effective than either component doses alone. These approaches involve multiple comparisons in multilevel factorial designs where the type 1 error can be controlled first, by bootstrapping tests, and second, by considering the least favorable null configurations for a family of union intersection tests. The main advantage of the new approaches is that their implementation is simple. The implementation of these new approaches is illustrated with a real data example from a blood pressure reduction trial. Extensive simulations are also conducted to evaluate the new approaches and benchmark them with existing ones. We also present an illustration of the relationship between the different approaches. We observed that the bootstrap provided some power advantages over the other approaches with the disadvantage that there may be some error rate inflation for small sample sizes.

| S-EPMC7309363 | biostudies-literature

Moving forward in clinical trials for ALS: motor neurons lead the way please.

Project description:Amyotrophic lateral sclerosis (ALS) is one of the most complex motor neuron diseases. Even though scientific discoveries are accelerating with an unprecedented pace, to date more than 30 clinical trials have ended with failure and staggering frustration. There are too many compounds that increase life span in mice, but too little evidence that they will improve human condition. Increasing the chances of success for future clinical trials requires advancement of preclinical tests. Recent developments, which enable the visualization of diseased motor neurons, have the potential to bring novel insight. As we change our focus from mice to motor neurons, it is possible to foster a new vision that translates into effective and long-term treatment strategies in ALS and related motor neuron disorders (MND).

| S-EPMC4000750 | biostudies-literature

Revised Airlie House consensus guidelines for design and implementation of ALS clinical trials.

Project description:ObjectiveTo revise the 1999 Airlie House consensus guidelines for the design and implementation of preclinical therapeutic studies and clinical trials in amyotrophic lateral sclerosis (ALS).MethodsA consensus committee comprising 140 key members of the international ALS community (ALS researchers, clinicians, patient representatives, research funding representatives, industry, and regulatory agencies) addressed 9 areas of need within ALS research: (1) preclinical studies; (2) biological and phenotypic heterogeneity; (3) outcome measures; (4) disease-modifying and symptomatic interventions; (5) recruitment and retention; (6) biomarkers; (7) clinical trial phases; (8) beyond traditional trial designs; and (9) statistical considerations. Assigned to 1 of 8 sections, committee members generated a draft set of guidelines based on a "background" of developing a (pre)clinical question and a "rationale" outlining the evidence and expert opinion. Following a 2-day, face-to-face workshop at the Airlie House Conference Center, a modified Delphi process was used to develop draft consensus research guidelines, which were subsequently reviewed and modified based on comments from the public. Statistical experts drafted a separate document of statistical considerations (section 9).ResultsIn this report, we summarize 112 guidelines and their associated backgrounds and rationales. The full list of guidelines, the statistical considerations, and a glossary of terms can be found in data available from Dryad (appendices e-3-e-5, doi.org/10.5061/dryad.32q9q5d). The authors prioritized 15 guidelines with the greatest potential to improve ALS clinical research.ConclusionThe revised Airlie House ALS Clinical Trials Consensus Guidelines should serve to improve clinical trial design and accelerate the development of effective treatments for patients with ALS.

| S-EPMC6448453 | biostudies-literature

Current clinical trials testing combinations of immunotherapy and radiation.

Project description:Preclinical evidence of successful combinations of ionizing radiation with immunotherapy has inspired testing the translation of these results to the clinic. Interestingly, the preclinical work has consistently predicted the responses encountered in clinical trials. The first example came from a proof-of-principle trial started in 2001 that tested the concept that growth factors acting on antigen-presenting cells improve presentation of tumor antigens released by radiation and induce an abscopal effect. Granulocyte-macrophage colony-stimulating factor was administered during radiotherapy to a metastatic site in patients with metastatic solid tumors to translate evidence obtained in a murine model of syngeneic mammary carcinoma treated with cytokine FLT-3L and radiation. Subsequent clinical availability of vaccines and immune checkpoint inhibitors has triggered a wave of enthusiasm for testing them in combination with radiotherapy. Examples of ongoing clinical trials are described in this report. Importantly, most of these trials include careful immune monitoring of the patients enrolled and will generate important data about the proimmunogenic effects of radiation in combination with a variety of immune modulators, in different disease settings. Results of these studies are building a platform of evidence for radiotherapy as an adjuvant to immunotherapy and encourage the growth of this novel field of radiation oncology.

| S-EPMC4640687 | biostudies-literature

Current clinical trials testing the combination of immunotherapy with radiotherapy.

Project description:Increasing evidence demonstrates that radiation acts as an immune stimulus, recruiting immune mediators that enable anti-tumor responses within and outside the radiation field. There has been a rapid expansion in the number of clinical trials harnessing radiation to enhance antitumor immunity. If positive, results of these trials will lead to a paradigm shift in the use of radiotherapy. In this review, we discuss the rationale for trials combining radiation with various immunotherapies, provide an update of recent clinical trial results and highlight trials currently in progress. We also address issues pertaining to the optimal incorporation of immunotherapy with radiation, including sequencing of treatment, radiation dosing and evaluation of clinical trial endpoints.

| S-EPMC5028964 | biostudies-literature

Multiple hypotheses testing procedures in clinical trials and genomic studies.

Project description:We review and compare multiple hypothesis testing procedures used in clinical trials and those in genomic studies. Clinical trials often employ global tests, which draw an overall conclusion for all the hypotheses, such as SUM test, Two-Step test, Approximate Likelihood Ratio test (ALRT), Intersection-Union Test (IUT), and MAX test. The SUM and Two-Step tests are most powerful under homogeneous treatment effects, while the ALRT and MAX test are robust in cases with non-homogeneous treatment effects. Furthermore, the ALRT is robust to unequal sample sizes in testing different hypotheses. In genomic studies, stepwise procedures are used to draw marker-specific conclusions and control family wise error rate (FWER) or false discovery rate (FDR). FDR refers to the percent of false positives among all significant results and is preferred over FWER in screening high-dimensional genomic markers due to its interpretability. In cases where correlations between test statistics cannot be ignored, Westfall-Young resampling method generates the joint distribution of P-values under the null and maintains their correlation structure. Finally, the GWAS data from a clinical trial searching for SNPs associated with nephropathy among Type 1 diabetic patients are used to illustrate various procedures.

| S-EPMC3859974 | biostudies-literature

Improved ALS clinical trials through frequent at-home self-assessment: a proof of concept study.

Project description:ObjectiveTo determine the potential for improving amyotrophic lateral sclerosis (ALS) clinical trials by having patients or caregivers perform frequent self-assessments at home.Methods and participantsWe enrolled ALS patients into a nonblinded, longitudinal 9-month study in which patients and caregivers obtained daily data using several different instruments, including a slow-vital capacity device, a hand grip dynamometer, an electrical impedance myography-based fitness device, an activity tracker, a speech app, and the ALS functional rating scale-revised. Questions as to acceptability were asked at two time points.ResultsA total of 113 individuals enrolled, with 61 (43 men, 18 women, mean age 60.1 ± 9.9 years) collecting a minimum of 7 days data and being included in the analysis. Daily measurements resulted in more accurate assessments of the slope of progression of the disease, resulting in smaller sample size estimates for a hypothetical clinical trial. For example, by performing daily slow-vital capacity measurements, calculated sample size was reduced to 182 subjects/study arm from 882/arm for monthly measurements. Similarly, performing the ALS functional rating scale weekly rather than monthly led to a calculated sample size of 73/arm as compared to 274/arm. Participants generally found the procedures acceptable and, for many, improved their sense of control of their disease.InterpretationFrequent at-home measurements using standard tools holds the prospect of tracking progression and reducing sample size requirements for clinical trials in ALS while also being acceptable to the patients. Future studies in this and other neurological disorders should consider adopting this approach to data collection.

| S-EPMC7359124 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data