Optimal end points for acute stroke therapy trials: best ways to measure treatment effects of drugs and devices

Abstract

Background and purpose: Over the past decade, analysis of completed actual trials, model population studies, and theoretical work have improved approaches to selecting and analyzing end points in acute stroke treatment trials.

Methods: Narrative review.

Results: Because stroke affects persons in their biological, functional, social, and experiential dimensions, measures of impairment, disability, handicap, and quality of life are all desirable in pivotal trials, with disability being most important. Scales that are valid, reliable, responsive, and easy to administer are preferred; consequently, the modified Rankin Scale has become the most widely used single clinical efficacy measure. Because stroke cripples and kills, most outcome scales array patient outcome in ordered ranks, spread over the entire range from normal to disabled to dead. Generally, shift analysis, analyzing all health state transitions concurrently, is the most efficient analytic technique to detect treatment effects, with sliding dichotomy less efficient and fixed dichotomy least efficient, unless treatment effects strongly cluster at 1 or a few health state transitions that can be prespecified. Test statistics must also take into account interpretability, ie, how well they can be converted into metrics capturing all outcomes the intervention might alter in proportion to the degree they are valued by the patient; full ordinal analysis is most informative, sliding dichotomy is intermediately informative, and fixed dichotomy is least informative regarding this global outcome.

Conclusions: Stroke trial power and interpretation can be substantially enhanced by adherence to the principles delineated in this review. Full ordinal and sliding dichotomy analysis will most often be advantageous compared with fixed dichotomous approaches.

Figure 1

Final 90 day outcome scores in the two NINDS-TPA trials. The NIHSS and Barthel Index both show a markedly skewed, U-shaped distribution, unfavorable for analytic power and clinical interpretation. The Barthel also shows strong ceiling effect. In contrast, the modified Rankin Scale distributes substantial groups of patients among all hierarchical ranks, permitting more robust analysis and interpretation.

Figure 2

Clustering of treatment effect at different health state transitions of the modified Rankin Scale, depending on treatment timing, baseline prognosis, and type of acute stroke intervention. Rows show landmark analyses of three acute ischemic stroke treatments. Final three columns show p values indicating presence or absence of treatment effects at excellent (mRS 0-1), good (mRS 0-2), and fair (mRS 0-4) dichotomizations of the modified Rankin Scale. Cells with p values <0.05 are colored green, 0.06 -0.20 yellow, and >0.20 red. All treatments studied, IV recanalization, IA recanalization, and hemicraniectomy, exert powerful biological effects, so that clustered rather than distributed treatment effects may be expected. In the 2 NINDS trials testing a hyperacute treatment in moderately severe patients, dichotomization at excellent outcome is most efficient. In the PROACT 2 trial testing an early, but not hyperacute, treatment in more severe patients, dichotomization at good outcomes is most efficient. In the hemicraniectomy trials testing a late treatment in extremely severe patients, dichotomization at fair outcomes is most efficient.