Exact(28)
For responder prediction, AUC was 0.750 in the training set and 0.665 for the test set (Table 4, Fig. 3).
For responder analyses (LDAS, DAS28-defined remission and HAQ-DI responders), data are based on all patients, with those who discontinued considered non-responders.
In order to test for responder bias, age, gender, ethnicity, deprivation, and time since diagnosis distributions for respondents and non-respondents were compared using χ tests.
The probit estimator requires a binary outcome variable, in this case whether the patient responded to the SF-36 or not (coded 1 for responder, 0 for non-responder).
This article addresses these two issues, offering a novel approach for responder analysis that could both improve the power of responder analysis and explore different responder cutoffs if an agreed-upon common cutoff is not present.
As with every survey, there is a significant risk for responder bias.
Similar(32)
Background information was obtained from medical records for responders and non-responders.
Surprising results were found for responders too.
This analysis introduces the Hull criteria for responders as a tool to evaluate response to OnabotulinumtoxinA.
This analysis allows clinicians to justify continued treatment for responders identified within a defined period.
Looking forward, Concrn is hoping to raise $250,000 to continue developing the service and launch an app for responders.
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