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Gera RG, Friede T. Blinded sample size recalculation in multiple composite population designs with normal data and baseline adjustments. Biom J 2023; 65:e2000326. [PMID: 37309256 DOI: 10.1002/bimj.202000326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 12/13/2022] [Accepted: 03/07/2023] [Indexed: 06/14/2023]
Abstract
The increasing interest in subpopulation analysis has led to the development of various new trial designs and analysis methods in the fields of personalized medicine and targeted therapies. In this paper, subpopulations are defined in terms of an accumulation of disjoint population subsets and will therefore be called composite populations. The proposed trial design is applicable to any set of composite populations, considering normally distributed endpoints and random baseline covariates. Treatment effects for composite populations are tested by combining p-values, calculated on the subset levels, using the inverse normal combination function to generate test statistics for those composite populations while the closed testing procedure accounts for multiple testing. Critical boundaries for intersection hypothesis tests are derived using multivariate normal distributions, reflecting the joint distribution of composite population test statistics given no treatment effect exists. For sample size calculation and sample size, recalculation multivariate normal distributions are derived which describe the joint distribution of composite population test statistics under an assumed alternative hypothesis. Simulations demonstrate the absence of any practical relevant inflation of the type I error rate. The target power after sample size recalculation is typically met or close to being met.
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Affiliation(s)
- Roland G Gera
- Department of Medical Statistics, University Medical Centre Göttingen, Göttingen, Germany
| | - Tim Friede
- Department of Medical Statistics, University Medical Centre Göttingen, Göttingen, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany
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Schulz I, Kruse N, Gera RG, Kremer T, Cedarbaum J, Barbour R, Zago W, Schade S, Otte B, Bartl M, Hutten SJ, Trenkwalder C, Mollenhauer B. Systematic Assessment of 10 Biomarker Candidates Focusing on α-Synuclein-Related Disorders. Mov Disord 2021; 36:2874-2887. [PMID: 34363416 DOI: 10.1002/mds.28738] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/30/2021] [Accepted: 07/14/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Objective diagnostic biomarkers are needed to support a clinical diagnosis. OBJECTIVES To analyze markers in various neurodegenerative disorders to identify diagnostic biomarker candidates for mainly α-synuclein (aSyn)-related disorders (ASRD) in serum and/or cerebrospinal fluid (CSF). METHODS Upon initial testing of commercially available kits or published protocols for the quantification of the candidate markers, assays for the following were selected: total and phosphorylated aSyn (pS129aSyn), neurofilament light chain (NfL), phosphorylated neurofilament heavy chain (pNfH), tau protein (tau), ubiquitin C-terminal hydrolase L1 (UCHL-1), glial fibrillary acidic protein (GFAP), calcium-binding protein B (S100B), soluble triggering receptor expressed on myeloid cells 2 (sTREM-2), and chitinase-3-like protein 1 (YKL-40). The cohort comprised participants with Parkinson's disease (PD, n = 151), multiple system atrophy (MSA, n = 17), dementia with Lewy bodies (DLB, n = 45), tau protein-related neurodegenerative disorders (n = 80, comprising patients with progressive supranuclear palsy (PSP, n = 38), corticobasal syndrome (CBS, n = 16), Alzheimer's disease (AD, n = 11), and frontotemporal degeneration/amyotrophic lateral sclerosis (FTD/ALS, n = 15), as well as healthy controls (HC, n = 20). Receiver operating curves (ROC) with area under the curves (AUC) are given for each marker. RESULTS CSF total aSyn was decreased. NfL, pNfH, UCHL-1, GFAP, S100B, and sTREM-2 were increased in patients with neurodegenerative disease versus HC (P < 0.05). As expected, some of the markers were highest in AD (i.e., UCHL-1, GFAP, S100B, sTREM-2, YKL-40). Within ASRD, CSF NfL levels were higher in MSA than PD and DLB (P < 0.05). Comparing PD to HC, interesting serum markers were S100B (AUC: 0.86), sTREM2 (AUC: 0.87), and NfL (AUC: 0.78). CSF S100B and serum GFAP were highest in DLB. CONCLUSIONS Levels of most marker candidates tested in serum and CSF significantly differed between disease groups and HC. In the stratification of PD versus other tau- or aSyn-related conditions, CSF NfL levels best discriminated PD and MSA. CSF S100B and serum GFAP best discriminated PD and DLB. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.
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Affiliation(s)
| | - Niels Kruse
- Department of Neuropathology, University Medical Centre Goettingen, Goettingen, Germany
| | - Roland G Gera
- Department of Medical Statistics, University Medical Centre Goettingen, Goettingen, Germany
| | - Thomas Kremer
- Roche Pharmaceutical Research and Early Development, NRD Neuroscience and Rare Disease, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Jesse Cedarbaum
- Coeruleus Clinical Sciences LLC, Woodbidge, Connecticut, USA.,Yale University School of Medicine, New Haven, Connecticut, USA
| | - Robin Barbour
- Prothena Biosciences Inc., San Francisco, California, USA
| | - Wagner Zago
- Prothena Biosciences Inc., San Francisco, California, USA
| | - Sebastian Schade
- Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
| | - Birgit Otte
- Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
| | - Michael Bartl
- Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
| | - Samantha J Hutten
- The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA
| | - Claudia Trenkwalder
- Paracelsus-Elena-Klinik, Kassel, Germany.,Department of Neurosurgery, University Medical Centre Goettingen, Goettingen, Germany
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany.,Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
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Mollenhauer B, Dakna M, Kruse N, Galasko D, Foroud T, Zetterberg H, Schade S, Gera RG, Wang W, Gao F, Frasier M, Chahine LM, Coffey CS, Singleton AB, Simuni T, Weintraub D, Seibyl J, Toga AW, Tanner CM, Kieburtz K, Marek K, Siderowf A, Cedarbaum JM, Hutten SJ, Trenkwalder C, Graham D. Validation of Serum Neurofilament Light Chain as a Biomarker of Parkinson's Disease Progression. Mov Disord 2020; 35:1999-2008. [PMID: 32798333 PMCID: PMC8017468 DOI: 10.1002/mds.28206] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 05/20/2020] [Accepted: 06/19/2020] [Indexed: 01/15/2023] Open
Abstract
Background: The objective of this study was to assess neurofilament light chain as a Parkinson’s disease biomarker. Methods: We quantified neurofilament light chain in 2 independent cohorts: (1) longitudinal cerebrospinal fluid samples from the longitudinal de novo Parkinson’s disease cohort and (2) a large longitudinal cohort with serum samples from Parkinson’s disease, other cognate/neurodegenerative disorders, healthy controls, prodromal conditions, and mutation carriers. Results: In the Parkinson’s Progression Marker Initiative cohort, mean baseline serum neurofilament light chain was higher in Parkinson’s disease patients (13 ± 7.2 pg/mL) than in controls (12 ± 6.7 pg/mL), P = 0.0336. Serum neurofilament light chain increased longitudinally in Parkinson’s disease patients versus controls (P < 0.01). Motor scores were positively associated with neurofilament light chain, whereas some cognitive scores showed a negative association. Conclusions: Neurofilament light chain in serum samples is increased in Parkinson’s disease patients versus healthy controls, increases over time and with age, and correlates with clinical measures of Parkinson’s disease severity. Although the specificity of neurofilament light chain for Parkinson’s disease is low, it is the first blood-based biomarker candidate that could support disease stratification of Parkinson’s disease versus other cognate/neurodegenerative disorders, track clinical progression, and possibly assess responsiveness to neuroprotective treatments. However, use of neurofilament light chain as a biomarker of response to neuroprotective interventions remains to be assessed.
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Affiliation(s)
- Brit Mollenhauer
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany.,Paracelsus-Elena Klinik, Kassel, Germany
| | - Mohammed Dakna
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Niels Kruse
- Department of Neuropathology, University Medical Center Goettingen, Goettingen, Germany
| | - Douglas Galasko
- Department of Neurosciences, University of California, San Diego, San Diego, California, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom.,UK Dementia Research Institute at UCL, London, United Kingdom
| | - Sebastian Schade
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Roland G Gera
- Department of Medical Statistics, University Medical Center Goettingen, Goettingen, Germany
| | - Wenting Wang
- Biostatistics, Biogen, Cambridge, Massachusetts, USA
| | - Feng Gao
- Biostatistics, Biogen, Cambridge, Massachusetts, USA
| | - Mark Frasier
- The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA
| | - Lana M Chahine
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Christopher S Coffey
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, Iowa, USA
| | - Andrew B Singleton
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Tanya Simuni
- Parkinson's Disease and Movement Disorders Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Weintraub
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John Seibyl
- Institute for Neurodegenerative Disorders, New Haven, Connecticut, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, University of Southern California, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, USA
| | - Caroline M Tanner
- Department of Neurology, University of California San Francisco, San Francisco, California, USA, and Parkinson's Disease Research Education and Clinical Center, San Francisco Veterans Affairs Health Care System, San Francisco, California, USA
| | - Karl Kieburtz
- Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New York, USA
| | - Kenneth Marek
- The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA.,Institute for Neurodegenerative Disorders, New Haven, Connecticut, USA
| | - Andrew Siderowf
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Samantha J Hutten
- The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA
| | | | - Danielle Graham
- Discovery and Early Development Biomarkers, Biogen, Cambridge, Massachusetts, USA
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Behme D, Gera RG, Tsogkas I, Colla R, Liman J, Maier IL, Liebeskind DS, Psychogios MN. Impact of Time on Thrombolysis in Cerebral Infarction Score Results. Clin Neuroradiol 2019; 30:345-353. [PMID: 31069414 DOI: 10.1007/s00062-019-00786-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Accepted: 04/19/2019] [Indexed: 11/26/2022]
Abstract
PURPOSE Extended thrombolysis in cerebral infarction (eTICI) score results of 2b or higher are known to be predictors for favorable outcome after acute stroke. Additionally, time is a major factor influencing outcome after ischemic stroke. Until today only little is known about the impact of time on angiographic results regarding the outcome after mechanical thrombectomy; however, this impact might be of interest if an initially unfavorable angiographic result has to be improved. METHODS Retrospective study of 164 patients with large vessel occlusion of the anterior circulation treated by mechanical thrombectomy. Multiple logistic regression analysis of relevant periprocedural and procedural times in respect to the probability of achieving functional independence at 90 days in respect to different eTICI results was performed to build a time and TICI score-dependent model for outcome prediction in which the influence of time was assumed to be steady among the TICI grades. RESULTS The probability of achieving a favorable outcome is significantly different between eTICI2b-50, 67, TICI2c and TICI3 results (p < 0.001). The odds for achieving a favorable outcome decrease over time and differ for each TICI category and time point. The individual odds for each patient, time point and TICI grade can be calculated based on this model. CONCLUSION The impact of periprocedural and procedural times and eTICI reperfusion results adds a new dimension to the decision-making process in patients with primary unfavorable angiographic results.
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Affiliation(s)
- D Behme
- Department of Neuroradiology, University Medical Center Göttingen, Robert Koch Str. 40, 37099, Göttingen, Germany.
| | - R G Gera
- Department of Medical Statistics, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - I Tsogkas
- Department of Neuroradiology, University Medical Center Göttingen, Robert Koch Str. 40, 37099, Göttingen, Germany
| | - R Colla
- Department of Neuroradiology, University Medical Center Göttingen, Robert Koch Str. 40, 37099, Göttingen, Germany
| | - J Liman
- Department of Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - I L Maier
- Department of Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - D S Liebeskind
- Neurovascular Imaging Research Core and Stroke Center, Department of Neurology, UCLA, Los Angeles, CA, USA
| | - M N Psychogios
- Department of Neuroradiology, University Medical Center Göttingen, Robert Koch Str. 40, 37099, Göttingen, Germany
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Behme D, Tsogkas I, Colla R, Gera RG, Schregel K, Hesse AC, Maier IL, Liman J, Liebeskind DS, Psychogios MN. Validation of the extended thrombolysis in cerebral infarction score in a real world cohort. PLoS One 2019; 14:e0210334. [PMID: 30629664 PMCID: PMC6328192 DOI: 10.1371/journal.pone.0210334] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 12/20/2018] [Indexed: 11/19/2022] Open
Abstract
Background A thrombolysis in cerebral infarction (TICI) score of 2b is defined as a good recanalization result although the reperfusion may only cover 50% of the affected territory. An additional mTICI2c category was introduced to further differentiate between mTICI scores. Despite the new mTICI2c category, mTICI2b still covers a range of 50–90% reperfusion which might be too imprecise to predict neurological improvement after therapy. Aim To compare the 7-point “expanded TICI” (eTICI) scale with the traditional mTICI in regard to predict functional independence at 90 days. Methods Retrospective review of 225 patients with large artery occlusion. Angiograms were graded by 2 readers according the 7-point eTICI score (0% = eTICI0; reduced clot = eTICI1; 1–49% = eTICI2a, 50–66% = eTICI2b50; 67–89% = eTICI2b67, 90–99% = eTICI2c and complete reperfusion = eTICI3) and the conventional mTICI score. The ability of e- and mTICI to predict favorable outcome at 90days was compared. Results Given the ROC analysis eTICI was the better predictor of favorable outcome (p-value 0.047). Additionally, eTICI scores 2b50, 2b67 and 2c (former mTICI2b) were significantly superior at predicting the probability of a favorable outcome at 90 days after endovascular therapy with a p-value of 0.033 (probabilities of 17% for mTICI2b50, 24% for mTICI2b67 and 54% for mTICI2c vs. 36% for mTICI2b). Conclusions The 7-point eTICI allows for a more accurate outcome prediction compared to the mTICI score because it refines the broad range of former mTICI2b results.
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Affiliation(s)
- Daniel Behme
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
| | - Ioannis Tsogkas
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
| | - Ruben Colla
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
| | - Roland G. Gera
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
| | - Katharina Schregel
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
| | - Amélie C. Hesse
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
| | - Ilko L. Maier
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Jan Liman
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - David S. Liebeskind
- Neurovascular Imaging Research Core and Stroke Center, Department of Neurology, UCLA, Los Angeles, CA, United States of America
| | - Marios-Nikos Psychogios
- Department of Neuroradiology, University Medical Center Göttingen, Göttingen, Germany
- * E-mail:
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