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The Prevention and Treatment of Missing Data in Clinical Trials
chronic pain. These trials are typically conducted over 12 weeks, and they are subject to very high rates of treatment discontinuation. The reasons for treatment discontinuation usually differ between the treatment and the control groups. For example, in placebo-controlled trials, discontinuation in the placebo group often stems from inadequate efficacy (i.e., lack of pain relief), while discontinuation in the treatment group more often arises because of poor tolerability (of the medication being tested). Trial designs that involve fixed doses leave few treatment options for patients who experience inadequate efficacy or poor tolerability. Patients who stop study treatment usually switch to a proven (approved) effective therapy, and the trial sponsors typically stop collecting pain response data on those patients who discontinue study treatment.
In current practice, the data from these types of clinical trials have been analyzed by using (single-value) imputation to fill in for the missing outcome values. In particular, it has been common to use the last observation carried forward (LOCF) imputation technique to impute for missing values. LOCF implicitly assumes that a participant who had good pain control in the short term and then dropped out would have had good pain control in the long term. This assumption seems questionable in many settings. Another frequently used, although somewhat less traditional imputation technique is the baseline observation carried forward (BOCF) technique, which assumes that a participant’s pain control is the same as that measured at the beginning of the trial. Since most patients in chronic pain studies, including those on placebos, improve substantially from the baseline over time, BOCF is likely to underestimate the effectiveness of any treatment. Furthermore, use of such imputation schemes, in conjunction with complete data techniques, can result in estimated standard errors for treatment effects that fail to properly reflect the uncertainty due to missing data.
Trials for the Treatment of HIV
The goal of many HIV trials is to determine whether a new drug has safety and efficacy that is comparable with that of an approved drug used for initial antiretroviral treatment (ART). The studies involve samples of ART-naïve participants and use noninferiority designs (U.S. Food and Drug Administration, 2002). The focus for current purposes is on the primary efficacy outcome, which is the percentage of participants with sufficiently low viral load at the end of the reference period. (Other considerations, such as choice of control, noninferiority margin, and blinding, are therefore ignored.) Since combination treatment is the norm for HIV, the typical design in this setting is new drug A plus background treatment compared with current drug B plus the same background treatment, measured over a period of 24 or 48 weeks.