Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT01491997 |
| Other study ID # |
AT11-003 - 1 R01 AT007143-01 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
August 2011 |
| Est. completion date |
July 2017 |
Study information
| Verified date |
January 2021 |
| Source |
Rush University Medical Center |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Stress has been linked to chronic health problems, particularly diseases involving
inflammation-mediated tissue injury and organ failure. Accordingly, it is not surprising that
mind/body interventions are advocated for treatment of chronic inflammatory diseases. One
such candidate disease is ulcerative colitis (UC) because: (1) UC is a life-long, relapsing,
disabling inflammatory disorder of the intestine that lacks a non-toxic, efficacious
treatment; (2) the therapeutic goal is to improve quality of life by ameliorating disabling
symptoms and preventing disease progression by preventing disease flare-up, (3) stress
triggers UC flare-up by modifying intestinal function and inflammatory processes,
highlighting the potential therapeutic benefit of reducing physiological stress responses.
The purpose of this study is to see if either of two 8-week mind/body medicine courses has an
effect in reducing stress and affecting the course and severity of UC. Both have been shown
to benefit other aspects of health and well-being.
Description:
Statistical Analysis. The investigator will use the biopsychomarkers identified as the
highest prediction value to determine the relative accuracy to predict response to the
Mindful Intervention (i.e., disease outcome). For response to the mindful intervention, the
investigator will use the use the combination of markers to study whether they correctly
predict the response to the intervention. The investigator will study the accuracy of the
markers using area under the curve (AUC) summary index for ROC curves.181 If the
classification accuracy of the markers is high then the area under the curve will be close to
1. If the predictive accuracy of the combined set of markers were poor then the (AUC) will be
close to 0.5.
Power Estimates UC disease flare-up was quite common in this sample, occurring in well over
half of subjects in the samples collected in the discovery phase. The power analyses,
assuming α = 0.05 for all tests indicated that for models involving analyses of correlational
data, there will be sufficient power at even small effect sizes for the smallest possible
sample with full data across all data points and virtually all variables. For the most
conservative estimate, the investigator base their calculations on having 50 participants
with data with full integrity. With an effect size of r = 0.15 and n = 50, power is 80 or
greater to detect effect sizes of r = 0.20. Effect sizes below this threshold would likely
not be clinically significant or substantively interpretable, as they would explain less than
2% in the variance of the dependent variable. Thus, most effect sizes that would be
reasonably and substantially interpretable will have good power. Each factor that is
suspected of varying between groups can be examined with the chi-square test based on 1
degrees of freedom, by setting it invariant in one model and then allowing it to be freely
estimated in the other. Such a chi-square test provides a power of 0.80 with effect size
difference of 0.15.
For binary categorical measures, such as responsiveness to MSRB, the investigator conducted
separate power analyses.
The power for adjusted analyses of primary predictors of interest will be evaluated as a
function of the risk of outcome when all ancillary variables are set to their mean value, the
predictor is set to the mean value, and proportion of variance in predictor explained by the
ancillary variables, and the odds ratio of outcome variable from increasing the predictor by
an amount equal to one of its standard deviation. The range in probabilities of outcome
variables can be anywhere from 20% for less likely events and 50% for more likely events, the
investigator will provide power calculations over a wide range of probabilities. The
investigator believe that the amount of variation of our typical model ranges from about 20%
to 50%. The table (below) represents the minimum odds ratio than can be detected with 80%
power, which indicate good power for expected outcome.
Proportions R2 =.20 R2=.50 0.10 1.64 1.87 0.20 1.46 1.63 0.30 1.39 1.53 0.40 1.35 1.48 0.50
1.32 1.43
