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29 Mendeley
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Article details
Title
A post hoc evaluation of a sample size re-estimation in the Secondary Prevention of Small Subcortical Strokes study
Published in
Clinical Trials, July 2016
DOI 10.1177/1740774516643689
Pubmed ID
Authors
Abstract

The use of adaptive designs has been increasing in randomized clinical trials. Sample size re-estimation is a type of adaptation in which nuisance parameters are estimated at an interim point in the trial and the sample size re-computed based on these estimates. The Secondary Prevention of Small Subcortical Strokes study was a randomized clinical trial assessing the impact of single- versus dual-antiplatelet therapy and control of systolic blood pressure to a higher (130-149 mmHg) versus lower (<130 mmHg) target on recurrent stroke risk in a two-by-two factorial design. A sample size re-estimation was performed during the Secondary Prevention of Small Subcortical Strokes study resulting in an increase from the planned sample size of 2500-3020, and we sought to determine the impact of the sample size re-estimation on the study results. We assessed the results of the primary efficacy and safety analyses with the full 3020 patients and compared them to the results that would have been observed had randomization ended with 2500 patients. The primary efficacy outcome considered was recurrent stroke, and the primary safety outcomes were major bleeds and death. We computed incidence rates for the efficacy and safety outcomes and used Cox proportional hazards models to examine the hazard ratios for each of the two treatment interventions (i.e. the antiplatelet and blood pressure interventions). In the antiplatelet intervention, the hazard ratio was not materially modified by increasing the sample size, nor did the conclusions regarding the efficacy of mono versus dual-therapy change: there was no difference in the effect of dual- versus monotherapy on the risk of recurrent stroke hazard ratios (n = 3020 HR (95% confidence interval): 0.92 (0.72, 1.2), p = 0.48; n = 2500 HR (95% confidence interval): 1.0 (0.78, 1.3), p = 0.85). With respect to the blood pressure intervention, increasing the sample size resulted in less certainty in the results, as the hazard ratio for higher versus lower systolic blood pressure target approached, but did not achieve, statistical significance with the larger sample (n = 3020 HR (95% confidence interval): 0.81 (0.63, 1.0), p = 0.089; n = 2500 HR (95% confidence interval): 0.89 (0.68, 1.17), p = 0.40). The results from the safety analyses were similar to 3020 and 2500 patients for both study interventions. Other trial-related factors, such as contracts, finances, and study management, were impacted as well. Adaptive designs can have benefits in randomized clinical trials, but do not always result in significant findings. The impact of adaptive designs should be measured in terms of both trial results, as well as practical issues related to trial management. More post hoc analyses of study adaptations will lead to better understanding of the balance between the benefits and the costs.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Japan 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 5 17%
Researcher 4 14%
Student > Master 3 10%
Student > Doctoral Student 2 7%
Professor > Associate Professor 2 7%
Other 5 17%
Unknown 8 28%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 8 28%
Mathematics 2 7%
Nursing and Health Professions 2 7%
Environmental Science 1 3%
Sports and Recreations 1 3%
Other 1 3%
Unknown 14 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2016.
All research outputs
#24,759,078
of 34,433,373 outputs
Outputs from Clinical Trials
#789
of 1,075 outputs
Outputs of similar age
#226,557
of 336,700 outputs
Outputs of similar age from Clinical Trials
#8
of 14 outputs
Altmetric has tracked 34,433,373 research outputs across all sources so far. This one is in the 27th percentile – i.e., 27% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,075 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,700 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.