Skip to main content

Advertisement

Log in

Sample size calculations for clinical trials targeting tauopathies: a new potential disease target

  • Original Communication
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

Disease-modifying therapies are being developed to target tau pathology, and should, therefore, be tested in primary tauopathies. We propose that progressive apraxia of speech should be considered one such target group. In this study, we investigate potential neuroimaging and clinical outcome measures for progressive apraxia of speech and determine sample size estimates for clinical trials. We prospectively recruited 24 patients with progressive apraxia of speech who underwent two serial MRI with an interval of approximately 2 years. Detailed speech and language assessments included the Apraxia of Speech Rating Scale and Motor Speech Disorders severity scale. Rates of ventricular expansion and rates of whole brain, striatal and midbrain atrophy were calculated. Atrophy rates across 38 cortical regions were also calculated and the regions that best differentiated patients from controls were selected. Sample size estimates required to power placebo-controlled treatment trials were calculated. The smallest sample size estimates were obtained with rates of atrophy of the precentral gyrus and supplementary motor area, with both measures requiring less than 50 subjects per arm to detect a 25 % treatment effect with 80 % power. These measures outperformed the other regional and global MRI measures and the clinical scales. Regional rates of cortical atrophy, therefore, provide the best outcome measures in progressive apraxia of speech. The small sample size estimates demonstrate feasibility for including progressive apraxia of speech in future clinical treatment trials targeting tau.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Boxer AL, Lang AE, Grossman M, Knopman DS, Miller BL, Schneider LS et al (2014) Davunetide in patients with progressive supranuclear palsy: a randomised, double-blind, placebo-controlled phase 2/3 trial. Lancet Neurol 13:676–685

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  2. Litvan I, Agid Y, Calne D, Campbell G, Dubois B, Duvoisin RC et al (1996) Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): report of the NINDS-SPSP international workshop. Neurology 47:1–9

    Article  CAS  PubMed  Google Scholar 

  3. Tolosa E, Litvan I, Hoglinger GU, Burn D, Lees A, Andres MV et al (2014) A phase 2 trial of the GSK-3 inhibitor tideglusib in progressive supranuclear palsy. Mov Disord 29:470–478

    Article  CAS  PubMed  Google Scholar 

  4. Josephs KA, Dickson DW (2003) Diagnostic accuracy of progressive supranuclear palsy in the Society for Progressive Supranuclear Palsy brain bank. Mov Disord 18:1018–1026

    Article  PubMed  Google Scholar 

  5. Paviour DC, Price SL, Lees AJ, Fox NC (2007) MRI derived brain atrophy in PSP and MSA-P. Determining sample size to detect treatment effects. J Neurol 254:478–481

    Article  PubMed  Google Scholar 

  6. Whitwell JL, Xu J, Mandrekar JN, Gunter JL, Jack CR Jr, Josephs KA (2012) Rates of brain atrophy and clinical decline over 6 and 12-month intervals in PSP: determining sample size for treatment trials. Parkinsonism Relat Disord 18:252–256

    Article  PubMed Central  PubMed  Google Scholar 

  7. Golden E, Duffy JR, Strand EA, Parisi JE, Dickson DW, Josephs KA (2014) Primary progressive apraxia of speech associated with progressive supranuclear palsy pathology. Am J Neurodegener Dis 3:131 [conference abstract]

    Google Scholar 

  8. Josephs KA, Boeve BF, Duffy JR, Smith GE, Knopman DS, Parisi JE et al (2005) Atypical progressive supranuclear palsy underlying progressive apraxia of speech and nonfluent aphasia. Neurocase 11:283–296

    Article  CAS  PubMed  Google Scholar 

  9. Josephs KA, Duffy JR, Strand EA, Whitwell JL, Layton KF, Parisi JE et al (2006) Clinicopathological and imaging correlates of progressive aphasia and apraxia of speech. Brain 129:1385–1398

    Article  PubMed Central  PubMed  Google Scholar 

  10. Duffy JR (2005) Motor speech disorders: substrates, differential diagnosis, and management. Mosby, St Louis

    Google Scholar 

  11. Josephs KA, Duffy JR, Strand EA, Machulda MM, Senjem ML, Lowe VJ et al (2013) Syndromes dominated by apraxia of speech show distinct characteristics from agrammatic PPA. Neurology 81:337–345

    Article  PubMed Central  PubMed  Google Scholar 

  12. Josephs KA, Duffy JR, Strand EA, Machulda MM, Senjem ML, Master AV et al (2012) Characterizing a neurodegenerative syndrome: primary progressive apraxia of speech. Brain 135:1522–1536

    Article  PubMed Central  PubMed  Google Scholar 

  13. Deramecourt V, Lebert F, Debachy B, Mackowiak-Cordoliani MA, Bombois S, Kerdraon O et al (2010) Prediction of pathology in primary progressive language and speech disorders. Neurology 74:42–49

    Article  CAS  PubMed  Google Scholar 

  14. Dickson DW, Ahmed Z, Algom AA, Tsuboi Y, Josephs KA (2010) Neuropathology of variants of progressive supranuclear palsy. Curr Opin Neurol 23:394–400

    Article  PubMed  Google Scholar 

  15. Josephs KA, Duffy JR, Strand EA, Machulda MM, Senjem ML, Gunter JL et al (2014) The evolution of primary progressive apraxia of speech. Brain 137:2783–2795

    Article  PubMed  Google Scholar 

  16. Wicklund MR, Duffy JR, Strand EA, Whitwell JL, Machulda MM, Josephs KA (2013) Aphasia with left occipitotemporal hypometabolism: a novel presentation of posterior cortical atrophy? J Clin Neurosci 20:1237–1240

    Article  PubMed Central  PubMed  Google Scholar 

  17. Borroni B, Alberici A, Grassi M, Turla M, Zanetti O, Bianchetti A et al (2010) Is frontotemporal lobar degeneration a rare disorder? Evidence from a preliminary study in Brescia county, Italy. J Alzheimer’s Dis 19:111–116

    Google Scholar 

  18. Johnson JK, Diehl J, Mendez MF, Neuhaus J, Shapira JS, Forman M et al (2005) Frontotemporal lobar degeneration: demographic characteristics of 353 patients. Arch Neurol 62:925–930

    PubMed  Google Scholar 

  19. Whitwell JL, Duffy JR, Strand EA, Machulda MM, Senjem ML, Gunter JL et al (2013) Neuroimaging comparison of primary progressive apraxia of speech and progressive supranuclear palsy. Eur J Neurol 20:629–637

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Strand EA, Duffy JR, Clark HM, Josephs K (2014) The apraxia of speech rating scale: a tool for diagnosis and description of apraxia of speech. J Commun Disord 51:43–50

    Article  PubMed Central  PubMed  Google Scholar 

  21. Yorkson K, Strand EA, Miller R, Hillel A, Smith K (1993) Speech deterioration in amyotrophic lateral sclerosis: implications for the timing of intervention. J Med Speech Lang Pathol 1:35–46

    Google Scholar 

  22. Lewis EB, Fox NC (2004) Correction of differential intensity inhomogeneity in longitudinal MR images. Neuroimage 23:75–83

    Article  PubMed  Google Scholar 

  23. Freeborough PA, Fox NC (1997) The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI. IEEE Trans Med Imaging 16:623–629

    Article  CAS  PubMed  Google Scholar 

  24. Gunter JL, Shiung MM, Manduca A, Jack CR Jr (2003) Methodological considerations for measuring rates of brain atrophy. J Magn Reson Imaging 18:16–24

    Article  PubMed Central  PubMed  Google Scholar 

  25. Jack CR Jr, Wiste HJ, Knopman DS, Vemuri P, Mielke MM, Weigand SD et al (2014) Rates of beta-amyloid accumulation are independent of hippocampal neurodegeneration. Neurology 82:1605–1612

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N et al (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289

    Article  CAS  PubMed  Google Scholar 

  27. Acion L, Peterson JJ, Temple S, Arndt S (2006) Probabilistic index: an intuitive non-parametric approach to measuring the size of treatment effects. Statist Med 25:591–602

    Article  Google Scholar 

  28. Newcombe RG (2006) Confidence intervals for an effect size measure based on the Mann-Whitney statistic. Part 1: general issues and tail-area-based methods. Statist Med 25:543–557

    Article  Google Scholar 

  29. Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New York

    Google Scholar 

  30. Whitwell JL, Duffy JR, Strand EA, Xia R, Mandrekar J, Machulda MM et al (2013) Distinct regional anatomic and functional correlates of neurodegenerative apraxia of speech and aphasia: an MRI and FDG-PET study. Brain Lang 125:245–252

    Article  PubMed Central  PubMed  Google Scholar 

  31. Litvan I, Kong M (2014) Rate of decline in progressive supranuclear palsy. Mov Disord 29:463–468

    Article  PubMed  Google Scholar 

  32. Hua X, Lee S, Yanovsky I, Leow AD, Chou YY, Ho AJ et al (2009) Optimizing power to track brain degeneration in Alzheimer’s disease and mild cognitive impairment with tensor-based morphometry: an ADNI study of 515 subjects. Neuroimage 48:668–681

    Article  PubMed Central  PubMed  Google Scholar 

  33. Fox NC, Ridgway GR, Schott JM (2011) Algorithms, atrophy and Alzheimer’s disease: cautionary tales for clinical trials. Neuroimage 57:15–18

    Article  PubMed  Google Scholar 

  34. Ard MC, Edland SD (2011) Power calculations for clinical trials in Alzheimer’s disease. J Alzheimer’s Dis 26(Suppl 3):369–377

    Google Scholar 

  35. Hua X, Lee S, Hibar DP, Yanovsky I, Leow AD, Toga AW et al (2010) Mapping Alzheimer’s disease progression in 1309 MRI scans: power estimates for different inter-scan intervals. Neuroimage 51:63–75

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

This study was funded by R01-DC12519 (PI Whitwell), R01-DC010367 (PI Josephs) and U01-AG06786 (PI Petersen).

Conflicts of interest

The authors declare that they have no conflict of interest.

Ethical standard

The study was approved by the Mayo Clinic Institutional Review Board and was, therefore, performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All subjects were consented for enrolment into the study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jennifer L. Whitwell.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Whitwell, J.L., Duffy, J.R., Strand, E.A. et al. Sample size calculations for clinical trials targeting tauopathies: a new potential disease target. J Neurol 262, 2064–2072 (2015). https://doi.org/10.1007/s00415-015-7821-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-015-7821-5

Keywords

Navigation