Example datasets with low and high dropout

Quick Summary

These two data sets are made publicly available so that they can be used to demonstrate methods for handling missing data where a continuous outcome is measured repeatedly.The purpose is to contrast similar data with a low dropout rate and that with a high dropout rate. For full details and further explanation see Mallinckrodt et al (1) written by the DIA working party on Missing data.

The data sets are somewhat contrived to avoid implications for marketed drugs. Nevertheless, the key features of the original data were preserved. The original data were from 2 nearly identically designed antidepressant clinical trials that were originally reported by Goldstein et al (2) and Detke et al. (3). Each trial had 4 treatment arms with approximately 90 patients each that included 2 doses of an experimental medication (subsequently granted marketing authorizations in most major jurisdictions), an approved medication, and placebo. Assessments on the Hamilton 17-item rating scale for depression (HAMD17)19 were taken at baseline and weeks 1, 2, 4, 6, and 8 in each trial. All patients from the original placebo arm were included along with a contrived drug arm that was created by randomly selecting patients from the nonplacebo arms. Random selection continued until 100 drug-treated patients were selected. In addition to all the original placebo-treated patients, additional placebo-treated patients were randomly re-selected so that there were also 100 patients in the contrived placebo arms. For these re-selected placebo-treated patients, a new patient identification number was assigned and outcomes were adjusted to create new observations by adding a randomly generated value to each patient’s observations.

These trials are referred to as the low and high dropout data sets. In the high dropout data set, completion rates were 70% for drug and 60% for placebo (Table 2). In the low dropout data set, completion rates were 92% in both the drug and placebo arms. The dropout rates in the contrived data sets closely mirrored those in the corresponding original studies. The design difference that may explain the difference in dropout rates between these two otherwise similar trials was that the low dropout data set came from a study conducted in Eastern Europe that included a 6-month extension treatment period after the 8-week acute treatment phase and used titration dosing. The high dropout data set came from a study conducted in the US that did not have the extension treatment period and used fixed dosing.
1. Mallinckrodt C, Roger J, Chuang-Stein C, Molenberghs G, O’Kelly M, Ratitch B, Janssens M, Bunouf P. Recent Developments in the Prevention and Treatment of Missing Data. Therapeutic Innovation & Regulatory Science 2014; 48: 68.
2. Goldstein DJ, Lu Y, Detke MJ, Wiltse C, Mallinckrodt C, Demitrack MA. Duloxetine in the treatment of depression: a double-blind placebo-controlled comparison with paroxetine. J Clin Psychopharmacol. 2004;24:389-399.
3. Detke MJ, Wiltse CG, Mallinckrodt CH, McNamara RK, Demitrack MA, Bitter I. Duloxetine in the acute and long-term treatment of major depressive disorder: a placebo- and paroxetinecontrolled trial. Eur Neuropsychopharmacol. 2004;14(6):457-470.

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The datasets can be downloaded high_low_datasets.

This page was written by James Roger (james@livedata.co.uk).

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