With intention to treat population, imputation technique is needed to deal with the early termination subjects. While the fancy technique such as multiple imputation may be more statistically sound, some practical imputation techniques may be more popular. Here are some of them that I have used.
LOCF (last observation carried forward): this is probably the most common technique used in the practice in handling the missing data (especially for continuous measures). This is also the technique mentioned in ICH E9 "Statistical principles for clinical trials". It states "...Imputation techniques, ranging from the carrying forward of the last observation to the use of complex mathematical models, may also be used in an attempt to compensate for missing data..."
LOCF can be easily implemented in SAS. See a SUGI paper titled "The DOW (not that DOW!!!) and the LOCF in Clinical Trials"
BOCF (baseline observation carried forward): this approach may be more conservative if the symptoms are gradually improving over the course of the study. I used this technique in several clinical trials testing the analgesic drug (pain killer) in dental surgery patients. At the baseline right after the dental surgery, the pain scale is the worst. With time, the pain intensity is supposed to decrease. In this situation, BOCF technique is more conservative than LOCF. There is a web article to look at the feature of BOCF. BOCF along with LOCF and a modified BOCF are discussed in a most recent FDA advisory committee on Cymbalta for the Treatment of Chronic Pain
WOCF (Worst observation carried forward): this approach is the most conservative comparing to LOCF and BOCF. This technique has been used in analgesia drug as well as the trials with laboratory results as endpoint. For example, WOCF technique is mentioned in FDA Summary on Durolane.
LOCF, BOCF, and WOCF are handy technique for continuous measures. For a trial with endpoint as dichotomous variable (success vs failure; responder vs. non-responder),a technique called MVTF can be used. MVTF stands for missing value treated as failure. For example, this technique is mentioned in Statistical Review of NDA 21-385 in dermatology indication. In one of studies I participated, we employed the same technique (even though we did not use the term MVTF) to treat all subjects who discontinued from the study early as non-responders. This is a very conservative approach. The treatment effect may be neutralized a little bit during the implementation of this technique.
There are many other techniques used in the practice. Some of them may be just different terms for the same technique. In FDA Executive Summary Prepared for the
July 30, 2010 meeting of the Ophthalmic Devices Panel P080030, the following imputation techniques are mentioned.
- Last Observation Carried Forward (LOCF) analysis
- Best Reasonable Case analysis
- Worst Reasonable Case analysis
- Non-Responder analysis
- Best Case analysis
- Worst Case analysis
it must be pointed out that these practical missing data handling techniques have no statistical basis and have been criticized by many professionals especially in academic setting. These techniques that seem to be very conservative, may not be conservative in some situations.
Since LOCF is a technique used most, the critics are usually centered on the comparison of LOCF and other model based techniques (for example, Mixed-Effect Model Repeated Measure (MMRM) model). Some of the comparisons and discussions can be found at:
- MMRM vs. LOCF: A Comprehensive Comparison Based on Simulation Study and 25 NDA Datasets
- Recommendations for the Primary Analysis of Continuous Endpoints in Longitudinal Clinical Trials
- LOCF and MMRM: Thoughts on Comparisons