000280242 001__ 280242
000280242 005__ 20250827101637.0
000280242 0247_ $$2doi$$a10.1186/s12874-025-02626-x
000280242 0247_ $$2pmid$$apmid:40739200
000280242 0247_ $$2pmc$$apmc:PMC12309037
000280242 037__ $$aDZNE-2025-00920
000280242 041__ $$aEnglish
000280242 082__ $$a610
000280242 1001_ $$aHendrickx, Niels$$b0
000280242 245__ $$aComparing randomized trial designs to estimate treatment effect in rare diseases with longitudinal models: a simulation study showcased by Autosomal Recessive Cerebellar Ataxias using the SARA score.
000280242 260__ $$aLondon$$bBioMed Central$$c2025
000280242 3367_ $$2DRIVER$$aarticle
000280242 3367_ $$2DataCite$$aOutput Types/Journal article
000280242 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1754895766_31916
000280242 3367_ $$2BibTeX$$aARTICLE
000280242 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000280242 3367_ $$00$$2EndNote$$aJournal Article
000280242 520__ $$aParallel designs with an end-of-treatment analysis are commonly used for randomised trials, but they remain challenging to conduct in rare diseases due to small sample size and heterogeneity. A more powerful alternative could be to use model-based approaches. We investigated the performance of longitudinal modelling to evaluate disease-modifying treatments in rare diseases using simulations. Our setting was based on a model describing the progression of the standard clinician-reported outcome SARA score in patients with ARCA (Autosomal Recessive Cerebellar Ataxia), a group of ultra-rare, genetically defined, neurodegenerative diseases. We performed a simulation study to evaluate the influence of trials settings on their ability to detect a treatment effect slowing disease progression, using a previously published non-linear mixed effect logistic model. We compared the power of parallel, crossover and delayed start designs, investigating several trial settings: trial duration (2 or 5 years); disease progression rate (slower or faster); magnitude of residual error (σ=2 or σ=0.5); number of patients (100 or 40); method of statistical analysis (longitudinal analysis with non-linear or linear models; standard statistical analysis), and we investigated their influence on the type 1 error and corrected power of randomised trials. In all settings, using non-linear mixed effect models resulted in controlled type 1 error and higher power (88% for a parallel design) than a rich (75% for a parallel design) or sparse (49% for a parallel design) linear mixed effect model or standard statistical analysis (36% for a parallel design). Parallel and delayed start designs performed better than crossover designs. With slow disease progression and high residual error, longer durations are needed for power to be greater than 80%, 5 years for slower progression and 2 years for faster progression ataxias. In our settings, using non-linear mixed effect modelling allowed all three designs to have more power than a standard end-of-treatment analysis. Our analysis also showed that delayed start designs are promising as, in this context, they are as powerful as parallel designs, but with the advantage that all patients are treated within this design.
000280242 536__ $$0G:(DE-HGF)POF4-353$$a353 - Clinical and Health Care Research (POF4-353)$$cPOF4-353$$fPOF IV$$x0
000280242 588__ $$aDataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
000280242 650_7 $$2Other$$aClinical trial design
000280242 650_7 $$2Other$$aModel-based analysis
000280242 650_7 $$2Other$$aNon-linear Mixed effect models
000280242 650_7 $$2Other$$aRare disease
000280242 650_7 $$2Other$$aSimulation study
000280242 650_2 $$2MeSH$$aHumans
000280242 650_2 $$2MeSH$$aRandomized Controlled Trials as Topic: methods
000280242 650_2 $$2MeSH$$aCerebellar Ataxia: therapy
000280242 650_2 $$2MeSH$$aCerebellar Ataxia: genetics
000280242 650_2 $$2MeSH$$aComputer Simulation
000280242 650_2 $$2MeSH$$aLongitudinal Studies
000280242 650_2 $$2MeSH$$aDisease Progression
000280242 650_2 $$2MeSH$$aResearch Design
000280242 650_2 $$2MeSH$$aRare Diseases: therapy
000280242 650_2 $$2MeSH$$aTreatment Outcome
000280242 7001_ $$aMentré, France$$b1
000280242 7001_ $$aHamdan, Alzahra$$b2
000280242 7001_ $$aKarlsson, Mats O$$b3
000280242 7001_ $$aHooker, Andrew C$$b4
000280242 7001_ $$0P:(DE-2719)9000792$$aTraschütz, Andreas$$b5$$udzne
000280242 7001_ $$aGagnon, Cynthia$$b6
000280242 7001_ $$0P:(DE-2719)2812018$$aSchüle-Freyer, Rebecca$$b7$$udzne
000280242 7001_ $$0P:(DE-2719)2811275$$aSynofzik, Matthis$$b8$$eLast author$$udzne
000280242 7001_ $$aComets, Emmanuelle$$b9
000280242 7001_ $$aARCA Study Group, EVIDENCE-RND consortium$$b10$$eCollaboration Author
000280242 7001_ $$aChen, Xiaomei$$b11$$eContributor
000280242 7001_ $$aHeussen, Nicole Maria$$b12$$eContributor
000280242 7001_ $$aHilgers, Ralf-Dieter$$b13$$eContributor
000280242 7001_ $$0P:(DE-2719)2810314$$aKlockgether, Thomas$$b14$$eContributor$$udzne
000280242 7001_ $$aRyeznik, Yevgen$$b15$$eContributor
000280242 7001_ $$aSverdlov, Oleksandr$$b16$$eContributor
000280242 773__ $$0PERI:(DE-600)2041362-2$$a10.1186/s12874-025-02626-x$$gVol. 25, no. 1, p. 179$$n1$$p179$$tBMC medical research methodology$$v25$$x1471-2288$$y2025
000280242 8564_ $$uhttps://pub.dzne.de/record/280242/files/DZNE-2025-00920.pdf$$yOpenAccess
000280242 8564_ $$uhttps://pub.dzne.de/record/280242/files/DZNE-2025-00920%20SUP.docx
000280242 8564_ $$uhttps://pub.dzne.de/record/280242/files/DZNE-2025-00920.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000280242 909CO $$ooai:pub.dzne.de:280242$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
000280242 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)9000792$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b5$$kDZNE
000280242 9101_ $$0I:(DE-HGF)0$$6P:(DE-2719)2812018$$aExternal Institute$$b7$$kExtern
000280242 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2811275$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b8$$kDZNE
000280242 9101_ $$0I:(DE-HGF)0$$6P:(DE-2719)2810314$$aExternal Institute$$b14$$kExtern
000280242 9131_ $$0G:(DE-HGF)POF4-353$$1G:(DE-HGF)POF4-350$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lNeurodegenerative Diseases$$vClinical and Health Care Research$$x0
000280242 9141_ $$y2025
000280242 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-18
000280242 915__ $$0LIC:(DE-HGF)CCBYNCND4$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
000280242 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBMC MED RES METHODOL : 2022$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-04-10T15:34:47Z
000280242 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-04-10T15:34:47Z
000280242 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000280242 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2024-12-18
000280242 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
000280242 9201_ $$0I:(DE-2719)1210000$$kAG Gasser$$lParkinson Genetics$$x0
000280242 980__ $$ajournal
000280242 980__ $$aVDB
000280242 980__ $$aUNRESTRICTED
000280242 980__ $$aI:(DE-2719)1210000
000280242 9801_ $$aFullTexts