CoChat
Sign Up
Cited by 64Statistical Methods in Clinical TrialsStatistical Methods in EpidemiologyAcute Ischemic Stroke Management

Should Stroke Trials Adjust Functional Outcome for Baseline Prognostic Factors?

Open access
The Optimising the Analysis of Stroke Trials (OAST) Collaboration·2009·Stroke
DOI 10.1161/strokeaha.108.519207
Open this paper in CoChat — free accountOpen PDF

Abstract

Background and Purpose— Many stroke trials have provided neutral results. Suboptimal statistical analyses may be failing to detect effective interventions. Adjusting outcomes for baseline prognostic factors in the analysis may improve the efficiency of analysis of outcomes. Methods— Data from 23 stroke trials (25 674 patients) assessing functional outcome were included. The prognostic variables considered were age, sex, and baseline severity. Unadjusted and adjusted ordinal logistic regression models were compared using simulated data from each trial (10 000 simulations per trial). Three levels of treatment effect were assessed with ORs of 0.95, 0.74, and 0.57. The reduction in sample size gained from using the adjusted models, as compared with an unadjusted model, was then calculated as a reflection of the increase in statistical power. Results— Adjusting outcome for baseline factors led to a reduction in sample size, which was similar across all 3 treatment effects (median percentage reduction, interquartile range): OR=0.95: 35.3% (21.0 to 42.1); OR=0.74: 38.4% (29.4 to 42.7); and OR=0.57: 38.4% (27.4 to 42.2). As the treatment effect increased, the proportion of simulations in which the treatment effect for the adjusted model was greater than for the unadjusted model also increased. Conclusion— Adjusting for prognostic factors in stroke trials can reduce sample size by at least 20% to 30% (the lower interquartile range) for a given power. Conversely, trialists may want to power for an unadjusted analysis and then increase statistical power by adjusting for prognostic factors.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1161/strokeaha.108.519207

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The resulting sample size needs to be increased somewhat to deal with participants who are lost to follow-up or crossover treatment groups and reduced significantly if adaptive randomization (minimization), covariate adjustment, and/or population enrichment are used.

    “The resulting sample size needs to be increased somewhat to deal with participants who are lost to follow-up or crossover treatment groups and reduced significantly if adaptive randomization (minimization), covariate adjustment, and/or population enrichment are used.”

    From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [33]

    Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • The key covariates in acute stroke trials are the 2 most powerful prognostic factors: severity (eg, baseline NIHSS) and age.

    “The key covariates in acute stroke trials are the 2 most powerful prognostic factors: severity (eg, baseline National Institutes of Health Stroke Scale) and age”

    From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [33]

    The Discussion identifies baseline severity as the most powerful predictor, and the Relationship of Covariates With Functional Outcome section reports an association with outcome in all trials for severity and 29 of 30 for age. The paper supports using both as important covariates, including NIHSS as a severity measure, but it does not establish that age is the second most powerful prognostic factor among all possible covariates; its analysis included only age, sex, and severity. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • It may also be relevant to add sex as a covariate in acute stroke trials in view of its central biological role.

    “it may also be relevant to add sex as a covariate in view of its central biological role.”

    From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [33]

  • Shift analyses are more powerful statistically if adjusted for baseline prognostic covariates, like binary analyses.

    “Like with binary analyses, shift analyses are more powerful statistically if adjusted for baseline prognostic covariates.”

    From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [33]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 38

  1. Vahedi K, Hofmeijer J, Juettler E, Vicaut E, George B, Algra A, Amelink GJ, Schmiedeck P, Schwab S, Rothwell P, Bousser M-G, van de Worp HB, Hacke W; for the DECIMAL DESTINY and HAMLET Investi- gators. Early decompressive surgery in malignant infarction of the middle cerebral artery: a pooled analysis of three randomised controlled trials. Lancet Neurol. 2007;6:215-222.
  2. Chen ZM, Sandercock P, Pan HC, Counsell C, Collins R, Liu LS, Xie JX, Warlow C, Peto R; on behalf of the CAST and IST Collaborative Groups. Indications for early aspirin use in acute ischemic stroke -a combined analysis of 40 000 randomized patients from the Chinese acute stroke trial and the international stroke trial. Stroke. 2000;31:1240 -1249.
  3. Stroke Unit Trialists' Collaboration. Collaborative systematic review of the randomised trials of organised inpatient (stroke unit) care after stroke. BMJ. 1997;314:1151-1159.
  4. Sena E, van der Worp HB, Howells D, Macleod M. How can we improve the pre-clinical development of drugs for stroke? Trends Neurosci. 2007; 30:433-439.
  5. The Optimising Analysis of Stroke Trials (OAST) Collaboration. Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials. Stroke. 2007;38:1911-1915.
  6. The Optimising Analysis of Stroke Trials (OAST) Collaboration. Calcu- lation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches. Int J Stroke. 2008;3: 78 -84.
  7. Raab GM, Day S, Sales J. How to select covariates to include in the analysis of a clinical trial. Control Clin Trials. 2000;21:330 -342.
  8. Senn SJ. Covariate imbalance and random allocation in clinical trials. Stat Med. 1989;8:797-799.
  9. The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group. Tissue plasminogen activator for acute stroke. N Engl J Med. 1995;333:1581-1587.
  10. Johnston KC, Connors AF, Wagner DP, Haley EC. Risk adjustment effect on stroke clinical trials. Stroke. 2004;35:e43-e45.
  11. Hernandez AV, Steyerberg EW, Butcher I, Mushkudiani N, Taylor GS, Murray GD, Marmarou A, Choi SC, Lu J, Habbema JDF, Maas AIR. Adjustment for strong predictors of outcome in traumatic brain injury trials: 25% reduction in sample size requirements in the impact study. J Neurotrauma. 2006;23:1295-1303.
  12. Hauck WW, Anderson S, Marcus SM. Should we adjust for covariates in nonlinear regression analyses of randomized trials? Control Clin Trials. 1998;19:249 -256.
  13. Lindley RI, Waddell F, Livingstone M, Sandercock P, Dennis MS, Slattery J, Smith B, Warlow C. Can simple questions assess outcome after stroke? Cerebrovasc Dis. 1994;4:314 -324.
  14. Agresti A. Analysis of Ordinal Categorical Data. New York: John Wiley & Sons; 1984.
  15. Weimar C, Konig IR, Kraywinkel K, Ziegler A, Diener H-C, Collabo- ration obotGSS. Age and National Institutes of Health Stroke Scale score within 6 hours after onset are accurate predictors of outcome after cerebral ischemia. Stroke. 2004;35:158 -162.
  16. Juttler E, Schwab S, Schmiedek P, Unterberg A, Hennerici MG, Woitik J, Witte S, Jenetzky E, Hacke W; for the DESTINY Study Group. DEcompressive Surgery for the Treatment of malignant INfarction of the middle cerebral arterY (DESTINY): a randomized, controlled trial. Stroke. 2007;38:2518 -2525.
  17. Stevens RS, Ambler NR. The Dover stroke rehabilitation unit: a ran- domised controlled trial of stroke management. In: Rose FC, ed. Advances in Stroke Therapy. New York: Raven Press; 1982:257-261.
  18. Hernandez AV, Steyerberg EW, Habbema JDF. Clinical trials with dichotomous end-points: covariate adjustment increases power and poten- tially reduces sample size. J Clin Epidemiol. 2004;57:454 -460.
  19. Blanco M, Nombela F, Castellanos M, Rodriguez-Yanez M, Garcia-Gil M, Leira R, Lizasoain I, Serena J, Vivancos J, Moro MA, Davalos A, Castillo J. Statin treatment withdrawal in ischemic stroke. A controlled randomized study. Neurology. 2007;69:904 -910.
  20. Lampl Y, Boaz M, Gilad R, Lorberboym M, Dabby R, Rapoport A, Anca-Hershkowitz M, Sadeh M. Minocycline treatment in acute stroke. An open-label, evaluator-blinded study. Neurology. 2007;69:1404 -1410.
  21. Lees KR, Zivin JA, Ashwood T, Davalos A, Davis SM, Diener H-C, Grotta J, Lyden P, Shuaib A, Hardemark H-G, Wasiewski WW; for the Stroke-Acute Ischemic NXY Treatment (SAINT I) Trial Investigators. NXY-059 for acute ischemic stroke. N Engl J Med. 2006;354:588 -599.
  22. Weir CJ, Lees KR. Comparison of stratification and adaptive methods for treatment allocation in an acute stroke clinical trial. Stat Med. 2003;22: 705-726.
  23. Ali M, Bath P, Curram J, Davis S, Diener HC, Donnan G, Fisher M, Gregson BA, Grotta J, Hacke W, Hennerici MG, Hommel M, Kaste M, Marler JR, Sacco RL, Teal P, Wahlgren NG, Warach S, Weir CJ, Lees KR. The Virtual International Stroke Trials Archive (VISTA). Stroke. 2007;38:1905-1910.
  24. Savitz SI, Benatar M, Saver J, Grotta J, Fisher M. Outcome measures in clinical trial design for acute ischaemic stroke: physicians' attitudes and choices [Abstract]. International Stroke Conference. 2008;39:694.
  25. Abciximab Emergent Stroke Treatment Trial (AbESTT) Investigators. Emergency treatment of abciximab for treatment of patients with acute ischemic stroke. Results of a randomized phase 2 trial. Stroke. 2005;36: 880 -890.
  26. Davis SM, Lees KR, Albers GW, Diener HC, Markabi S, Karlsson G, Norris J; for the ASSIST Investigators. Selfotel in acute ischemic stroke. Possible neurotoxic effects of an NMDA antagonist. Stroke. 2000;31: 347-354.
  27. Clark WM, Warach SJ, Pettigrew LC. A randomised dose-response trial of citicoline in acute ischemic stroke patients. Neurology. 1997;49: 671-678.
  28. Clark WM, Williams BJ, Selzer KA, Zweifler RM, Sabounjian LA, Gammans RE. A randomised efficacy trial of citicoline in patients with acute ischaemic stroke. Stroke. 1999;30:2592-2597.
  29. Warach S, Pettigrew C, Dashe JF, Pullicino P, Lefkowitz DM, Sabounjian L, Harnett D, Schwiderski U, Gammans R, Citicoline 010 investigators. Effect of citicoline on ischemic lesions as measured by diffusion- weighted magnetic resonance imaging. Ann Neurol. 2000;48:713-721.
  30. Clark WM, Wechsler LR, Sabounjian LA, Schwiderski UE. A phase III randomized efficacy trial of 2000 mg citicoline in acute ischemic stroke patients. Neurology. 2001;57:1595-1602.
  31. Saxena R, Wijnhoud AD, Carton H, Hacke W, Kaste M, Przybelski RJ, Stern KN, Koudstaal PJ. Controlled safety study of a haemoglobin-based oxygen carrier, dclhb, in acute ischemic stroke. Stroke. 1999;30:993-996.
  32. Yamaguchi T, Sano K, Takakura K, Saito I, Shinohara Y, Asano T, Yasuhara H. Ebselen in acute ischemic stroke. Stroke. 1998;29:12-17.
  33. The FOOD Trial Collaboration. Effect of timing and method of enteral tube feeding for dysphagic stroke patients (FOOD): a multicentre ran- domised controlled trial. Lancet. 2005;365:764 -772.
  34. Wahlgren NG, MacMahon DG, de Keyser J, Indredavik B, Ryman T, INWEST Study Group. Intravenous Nimodipine West European Stroke Trial (INWEST) of nimodipine in the treatment of acute ischaemic stroke. Cerebrovasc Dis. 1994;4:204 -210.
  35. Multicentre Acute Stroke Trial-Italy (MAST-I) Group. Randomised con- trolled trial of streptokinase, aspirin, and combination of both in treatment of acute ischaemic stroke. Lancet. 1995;346:1509 -1514.
  36. The RANTTAS Investigators. A RANdomized Trial of Tirilazad mesylate in patients with Acute Stroke (RANTTAS). Stroke. 1996;27: 1453-1458.
  37. Haley EC. High-dose tirilazad for acute stroke (RANTTAS II). Stroke. 1998;29:1256 -1257.
  38. Peters GR, Hwang L-J, Musch B, Brosse DM, Orgogozo JM. Safety and efficacy of 6 mg/kg/day tirilizad mesylate in patients with acute ischemic stroke (TESS study). Stroke. 1996;27:195.

Cited by

Sorted by citations

Authors
The Optimising the Analysis of Stroke Trials (OAST) Collaboration
Affiliations
University of Nottingham (GB)
Corresponding author
The Optimising the Analysis of Stroke Trials (OAST) Collaboration
Venue
Stroke
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2009-03
Volume
40
Issue
3
Pages
888-894
ISSN
  • 0039-2499 (ISSN-L)
  • 1524-4628
DOI
10.1161/strokeaha.108.519207
OpenAlex
W148053018
Cited by
64
References
5
Citations by year
2026: 2 · 2025: 3 · 2024: 2 · 2023: 5 · 2022: 1 · 2021: 3 · 2020: 3 · 2019: 4 · 2018: 2 · 2017: 3 · 2016: 2 · 2015: 5 · 2014: 8 · 2013: 4 · 2012: 5
FWCI
4.71
Type
journal article
Language
en
Open access
Locations
  • Stroke (publishedVersion)
  • PubMed (publishedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Health Sciences › Medicine › Epidemiology › Acute Ischemic Stroke Management
Keywords
stroke trials, functional outcome, sample size reduction, statistical power, ordinal logistic regression, treatment effect estimation, trial design
MeSH terms
Adult, Age Factors, Aged, Computer Simulation, Female, Humans, Male, Middle Aged, Prognosis, Research Design, Sex Factors, Models, Statistical, Logistic Models, Randomized Controlled Trials as Topic, Treatment Outcome, Sample Size, Stroke

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review