Loss to FollowUp In clinical medicine and research loss to follow up refers to a person who has not returned for continued care or evaluation eg because of death disability relocation or dropout ID: 689598
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Slide1
Study Design
Methods to Handle NoncomplianceSlide2
Loss to Follow-Up
In clinical medicine and research, loss to follow up refers to a person who has not returned for continued care or evaluation (e.g., because of death, disability, relocation, or drop-out).Slide3
Loss to Follow Up
Loss to follow-up can occur when researchers lose contact with participants in a trial for such reasons as migration or failure to maintain contact prior to the termination of a study or of planned endpoints. Planned data collection is incomplete as a result.Slide4
Loss to follow-up (LTF) bias
Loss to follow-up bias can occur when persons leaving the study are different to persons who stay in the study with respect to both the exposure
and the
outcomeSlide5
Loss to follow-up bias
If loss to follow up is low, loss to follow up bias is unlikely. If not low, identify whether loss to follow up was similar across groups. If not similar, identify whether loss to follow up was related to both the exposure
and the outcome.Slide6
Loss to follow-up bias
Vulnerable study designs are:
RCT (Randomized Controlled Trial)
Prospective cohort
Retrospective cohort
Case-control studies are not vulnerable because there is no follow-upSlide7
Loss to follow-up bias
There is much confusion about how to determine the proportion of patients lost to follow-up. In order to correctly calculate the follow-up rate, one needs to know the denominator.Slide8
Loss to follow-up
In a randomized controlled trial (RCT), the denominator for each group is the number of patients who were randomized,
not the number who received the treatment
. Slide9
Loss to follow-up
In a prospective cohort study the denominator is the entire group recruited at the start of the study.Slide10
Loss to follow-up
When calculating loss to follow-up in a retrospective cohort study, all individuals receiving treatment during the study period should be used as the denominator, not just those with complete data.Slide11
Intention to Treat Analysis
The preferred method of analysis of all subjects when there has been a significant drop-out or crossover rate is to use an intention-to-treat methodology. Slide12
Intention to Treat Analysis
In this method, all patient outcomes are counted with the group to which the patient was originally assigned even if the patient dropped out or switched groups. This approximates real life where some patients drop out or are non-compliant for various reasons. Slide13
Intention to Treat Analysis
Patients who dropped out or switched therapies must still be accounted for at the end of the trial since if their fates are unknown, it is impossible to accurately determine their outcomes. Some studies will attempt to use statistical models to estimate the outcomes that those patients should have had if they had completed the study, but the accuracy of this depends on the ability of the model to mimic reality.Slide14
Intention to Treat Analysis
Another biased technique involves removing patients from the study. Removing patients after randomization for reasons associated with the outcome is patently biased and grounds to invalidate the study. Leaving them in the analysis as an intention-to-treat is honest and will not inflate the results.Slide15
Intention to Treat Analysis
If the outcomes of patients who left the study are not known, a best case/worst case scenario should be applied and clearly described so that the reader can determine the range of effects applicable to the therapy.Slide16
Question
A researcher wants to compare decompression plus lumbar fusion with decompression alone in disc
herniation
and the data available are all patients receiving either treatment in the last 5 years (N = 275). However, the database from which the data are obtained is incomplete and only 190 have the necessary data available. Since the investigators stated as part of the inclusion criteria that only those patients with complete data are included, they consider the follow-up to be 100% (190/190). This is an example of a wrong conclusion being drawn in a:
Prospective Cohort Study
Randomized Controlled Trial
Retrospective Cohort StudySlide17
Answer
Retrospective Cohort Study
When calculating loss to follow-up in a retrospective cohort study, all individuals receiving treatment during the study period should be used as the denominator, not just those with complete data.
The denominator should include all patients who underwent the surgery irrespective of completeness of data. The follow-up rate for this example is 69% (190/275).Slide18
Question
Which of the following statements best describes an intention-to-treat analysis?
Analyses compare characteristics of participants who did and did not adhere to the randomized treatment.
Analyses exclude all participants who did not adhere to the assigned randomized treatment.
Analyses maintain the original randomized assignment of treatments in the definition of intervention and control groups.
Analyses reorganize participants into intervention and control groups based on their actual participation.Slide19
Answer
Analyses maintain the original randomized assignment of treatments in the definition of intervention and control groups.