Statistical planning in confirmatory clinical trials with multiple treatment groups, multiple visits, and multiple endpoints

2017 ◽  
Vol 28 (1) ◽  
pp. 189-211 ◽  
Author(s):  
Hengrui Sun ◽  
Ellen Snyder ◽  
Gary G. Koch
2021 ◽  
pp. 096228022110130
Author(s):  
Wei Wei ◽  
Denise Esserman ◽  
Michael Kane ◽  
Daniel Zelterman

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.


Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
C Vitale ◽  
P Collins ◽  
G Marazzi ◽  
G Caminiti ◽  
I Lodhi ◽  
...  

Testosterone Transdermal Patch (TTP) has been developed for the treatment of postmeno-pausal women (PMW) with hypoactive sexual desire disorder (HSDD). Since the cardiovascular (CV) effects of testosterone in women are still unclear we conducted a pooled analysis of the large phase III clinical program to evaluate the efficacy and safety of 300 μg/day TTP, alone or in association with hormone replacement therapy (HRT), versus placebo in surgical or natural PMW. Design & Methods: A total of 2795 women aged between 26 –70 years (mean age 52(SD=6.8) years) were included in 5 phase III randomized, double-blind, placebo-controlled clinical trials (treatment duration range 24 – 52 weeks) as part of the TTP Clinical program. 4 studies included PMW (natural and surgical, two each respectively) receiving HRT while 1 study was conducted without HRT, in either surgical or natural PMW. Women with known CV disorders were excluded from the studies. Changes from baseline in standard metabolic and CV risk factors were compared. The incidence of stroke, myocardial infarction (MI) and venous thromboembolism (VTE) alone or as a composite CV endpoint was assessed. Results: The 2795 PMW were randomized to receive either placebo (n=1297) or TTP (n=1498). Baseline mean BMI was 27 kg/m2 (SD=5.3 kg/m2) and 56% were naturally menopausal. The demographic and baseline parameters were similar among the treatment groups. No significant changes in CV risk factors (Total Cholesterol, Triglycerides, Insulin, Glucose, Systolic and Diastolic Blood Pressure) were detected during the study period, apart from a blunting of the increases in HDL-C by TTP at 24 and 52 weeks (Placebo 52-week mean change 2.59 mg/dl vs. TTP 52-week mean change 1.20 mg/dl, p<0.005) and of the decrease in LDL-C by TTP at 24 (p<0.05), but not at 52 weeks. During the double-blind (24 weeks), placebo-controlled period of the combined studies, 4 major CV events (2 MIs and 2 strokes) were reported in placebo patients and 3 (2 MIs and 1 stroke) in those receiving TTP. One VTE occurred in a patient receiving TTP and HRT. Conclusion: TTP therapy in these clinical trials did not adversely affect CV risk profile and did not change the risk of major CV events in these surgical and naturally PMW with or without concomitant HRT.


1998 ◽  
Vol 26 (2) ◽  
pp. 57-65 ◽  
Author(s):  
R Kay

If a trial is to be well designed, and the conclusions drawn from it valid, a thorough understanding of the benefits and pitfalls of basic statistical principles is required. When setting up a trial, appropriate sample-size calculation is vital. If initial calculations are inaccurate, trial results will be unreliable. The principle of intent-to-treat in comparative trials is examined. Randomization as a method of selecting patients to treatment is essential to ensure that the treatment groups are equalized in terms of avoiding biased allocation in the mix of patients within groups. Once trial results are available the correct calculation and interpretation of the P-value is important. Its limitations are examined, and the use of the confidence interval to help draw valid conclusions regarding the clinical value of treatments is explored.


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