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Editors Selection IGR 9-4

Cooperation with medical therapy: Gap analysis and persistence

Comment by Paul Healey on:

19938 A gap analysis approach to assess patient persistence with glaucoma medication, Lee PP; Walt JG; Chiang TH et al., American Journal of Ophthalmology, 2007; 144: 520-524

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Although doctors may feel they are treating patients when they prescribe medications, they are really only facilitating the patients' treating themselves. While we are familiar with the concept of compliance (the consistency and accuracy of prescribed treatment), successful medical treatment of glaucoma requires long duration of treatment, the measure of which is called persistence. In this paper, Lee et al. (1468) examine methodological approaches to measuring persistence using a retail pharmacy database. Refill patterns of 95 417 patients were examined over the course of one year and the more commonly used Kaplan-Meier survival analysis compared to an estimate of the number of days without therapy. Because actual days off therapy could not be known, Lee et al. chose 'allowable refill periods' of 45, 60 and 90 days and measured gaps between the end of these periods and the refill of medication. The results provide information which both complement and contrast with Kaplan-Meier analysis. They showed that using a 45 day cut-off, about half of the patients had three or more gaps in their therapy. Importantly, after a gap, patients refilled (and presumably) recommenced their therapy. This highlight a weakness of Kaplan-Meier analysis, which always assumes that any discontinuance of therapy is always permanent. The authors make a persuasive argument that a gap analysis methodology better reflects the real clinical experience. Gap analysis also provides additional information such as when a patient refills a prescription, how long and frequent are therapy gaps and how long is the total time off therapy. This data will allow us to make estimates of the effect of time off treatment on glaucoma progression and better estimates of the relationship between clinical trial and population-derived data concerning glaucoma treatment and progression. The study is limited by some important weaknesses which are common to almost all persistence studies. Most of these are clearly identified by the authors. Refill periods are a surrogate for the true data on medicine usage and neither filling a prescription, nor having a prolonged period between refills really tells us whether a person is taking their drops. Using pharmacy database data also has several limitations. As the authors point out, patients who do not refill medication via those participating pharmacies will be missed.

We must always be aware that findings from these datasets may reflect something other than the truth we are seeking

We also do not know how characteristic one pharmacy database will be compared to national or regional patterns. Although this is not as important in a methodological study, it may limit the generalisability of future studies. The last limitation is rarely mentioned but must always be kept in mind when reading reports based on large administrative databases. The nature of a well-conducted randomised controlled trial or large epidemiological study, the personalities of the investigators and the scrutiny of published peer-reviewed reports serves as a guarantee of the veracity of the data collected. Administrative data is not intended for scientific research, nor is it collected by obsessive, meticulous scientists whose career depends on its quality. As such, we must always be aware that findings from these datasets may reflect something other than the truth we are seeking.

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