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

BACKGROUND: 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. 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. METHODS: RA 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. RESULTS: In 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. CONCLUSIONS: The '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

Post-diagnosis weight gain and breast cancer recurrence in women with early stage breast cancer

To examine whether weight gain after diagnosis of breast cancer affects the risk of breast cancer recurrence. Patients included 3215 women diagnosed with early stage breast cancer (Stage I > 1 cm., II, and IIIA) who were enrolled either in an observational cohort of breast cancer survivors or were part of the comparison group of a dietary intervention trial to prevent breast cancer recurrence. We computed weight change from 1 year prior to diagnosis to study enrollment. Delayed entry Cox proportional hazards models were used to evaluate associations of categories of weight change with time to recurrence, controlling for known prognostic factors. Neither moderate (5-10%) nor large (> 10%) weight gain (HR 0.8, 95% CI, 0.6-1.1; HR 0.9, 95% CI, 0.7-1.2, respectively) after breast cancer diagnosis was associated with an increased risk of breast cancer recurrence in the early years post-diagnosis (median time of 73.7 months from diagnosis). Our research provides evidence that weight gain commonly seen in the first several years following a breast cancer diagnosis does not increase a woman's risk for breast cancer recurrence in the first 5-7 years post-diagnosis. However, this research does not address the effects of weight gain on overall survival or on the risk of other new cancers, other prognostic outcomes of concern to the breast cancer survivor