Background The modified Rankin Scale (mRS) at 90 days after stroke onset has become the preferred outcome measure in acute stroke trials, including recent trials of interventional therapies. Reporting the range of mRS scores as a paired horizontal stacked bar graph (colloquially known as ‘Grotta bars’) has become the conventional method of visualizing mRS results. Grotta bars readily illustrate the levels of the ordinal mRS in which benefit may have occurred. However, complementing the available graphical information by including additional features to convey statistical significance may be advantageous.
Methods/results We propose a modification of the horizontal stacked bar graph with illustrative examples. In this suggested modification, the line joining the segments of the bar graph (e.g. mRS 1–2 in treatment arm to mRS 1–2 in control arm) is given a colour and thickness based on the p value of the result at that level (in this example, the p value of mRS 0–1 vs 2–6) – a thick green line for p-values<0.01, thin green for p-values of 0.01 to <0.05, grey for 0.05 to <0.10, thin red for 0.10 to <0.90, and thick red for p-values≥0.90 or outcome favouring the control group. Illustrative examples from four recent trials (ESCAPE, SWIFT-PRIME, IST-3, ASTER) are shown in figure 1 to demonstrate the range of significant and non-significant effects that can be captured using this proposed method.
Discussion By formalizing a display of outcomes which includes statistical tests of all possible dichotomizations of the Rankin scale, this approach also encourages pre-specification of such hypotheses. Prespecifying tests of all six dichotomizations of the Rankin scale provides all possible statistical information in an a priori fashion. Since the result of our proposed approach is six distinct dichotomized tests in addition to a primary test, e.g., of the ordinal Rankin shift, it may be prudent to account for multiplicity in testing by using dichotomized p-values only after adjustment, such as by the Bonferroni or Hochberg-Holm methods. Whether p-values are nominal or adjusted may be left to the discretion of the presenter as long as the presence or absence is clearly stated in the statistical methods. Our proposed modification results in a visually intuitive summary of both the size of the effect – represented by the matched bars and their connecting segments – as well as its statistical relevance.
Disclosures A. Ganesh: None. S. Brown: None. B. Menon: None. M. Hill: None. M. Goyal: None.
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.