This program is based on a predictive patient enrollment model built on a poisson-gamma distribution, under the assumption that the recruitment has been started, and is currently at an interim time point (Anisimov and Fedorov, 20071).The program first estimates the parameters with maximum likelihood method using enrollment data collected so far. The estimated parameters are then used to predicts future enrollment pattern. If the target time will be missed by a user-defined probability, adaptive adjustment will be launched by predicting the number of new centers necessary for the target enrollment to be reached by the deadline.
Running Patient Recruitment for the Nicardipine study with a target goal of recruiting 600 additional subjects within 9 months generates the report shown below:
Note: The recruitment target number and date in the example shown here were chosen to ensure that the Adaptive Adjustment algorithm was invoked.
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Patient Recruitment: Displays recruitment history and predictions.
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Adaptive Adjustment: Displays number of additional study centers needed to meet the recruitment deadline and the predicted date of completion. Note: This section is displayed only when recruitment is predicted to be insufficient.
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Click
 to view the associated data tables. Refer to View Data for more information. |
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Click
 to generate a standardized pdf- or rtf-formatted report containing the plots and charts of selected sections. |
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Click
 to take notes, and store them in a central location. Refer to Add Notes for more information. |
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Click
 to read user-generated notes. Refer to View Notes for more information. |
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Click the arrow to reopen the completed report dialog used to generate this output.
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Click the gray border to the left of the Options tab to open a dynamic report navigator that lists all of the reports in the review. Refer to Report Navigator for more information.
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Anisimov, V.V. and V.V. Fedorov. 2007. Modeling, prediction and adaptive adjustment of recruitment in multicentre trials. Statist. Med. 26:4958–4975.