Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome

Sara Lodi,Stephen Evans,James Carpenter,Peter Egger

doi:10.1186/1471-2288-11-36

Abstract

BackgroundThere has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Using the LifeLink claims database in studying the possible anti-inflammatory effects of statins in rheumatoid arthritis (RA), oral steroids (OS) were treated as surrogate of inflammatory flare-ups. We compared two cohort study designs, the first using time to event outcomes and the second using quantitative amount of the surrogate.MethodsRA patients were extracted from the LifeLink database. In the first study, patients were split into two sub-cohorts based on whether they were using OS within a specified time window of the RA index date (first record of RA). Using Cox models we evaluated the association between time-varying exposure to statins and (i) initiation of OS therapy in the non-users of OS at RA index date and (ii) cessation of OS therapy in the users of OS at RA index date. In the second study, we matched new statin users to non users on age and sex. Zero inflated negative binomial models were used to contrast the number of days' prescriptions of OS in the year following date of statin initiation for the two exposure groups.ResultsIn the unmatched study, the statin exposure hazard ratio (HR) of initiating OS in the 31451 non-users of OS at RA index date was 0.96(95% CI 0.9,1.1) and the statin exposure HR of cessation of OS therapy in the 6026 users of OS therapy at RA index date was 0.95 (0.87,1.05). In the matched cohort of 6288 RA patients the statin exposure rate ratio for duration on OS therapy was 0.88(0.76,1.02). There was digit preference for outcomes in multiples of 7 and 30 days.ConclusionsThe 'time to event' study design was preferable because it better exploits information on all available patients and provides a degree of robustness toward confounding. We found no convincing evidence that statins reduce inflammation in RA patients.

Highlights

There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription
For our motivating example we investigate the suggestion that statins may have anti-inflammatory effects [10,11,12,13,14] and, in particular, that they may prevent or delay an inflammatory flare-up in patients with Rheumatoid Arthritis (RA)
Cohort study based on time to change in inflammation After splitting patients according to their use of oral steroids (OS) at rheumatoid arthritis (RA) index date we found 31451 non users of OS at RA index date and 6026 users of OS at RA index date

Summary

Introduction

There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Collected data - such as databases of health care insurance claims or the General Practice Research database (GPRD) - have become a very important source of information for studying secondary effects of drugs [1,2,3] They are useful as they usually provide information on the health care history of many patients for relatively long periods of time. Anti-inflammatory drugs for flare-ups in autoimmune disease or anti-depressant drugs for depression

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