Estimating the effect of current, previous and never use of drugs in studies based on prescription registries

Self-reported medication intake vs information from other data sources such as pharmacy records or medical records: Identification and description of existing publications, and comparison of agreement results for publications focusing on patients with cancer - a systematic review

PURPOSE

To identify and describe publications addressing the agreement between self-reported medication and other data sources among adults and, in a subgroup of studies dealing with cancer patients, seek to identify parameters which are associated with agreement.

METHODS

A systematic review including a systematic search within five biomedical databases up to February 28, 2019 was conducted as per the PRISMA Statement. Studies and agreement results were described. For a subgroup of studies dealing with cancer, we searched for associations between agreement and patients' characteristics, study design, comparison data source, and self-report modality.

RESULTS

The literature search retrieved 3392 publications. Included articles (n = 120) show heterogeneous agreement. Eighteen publications focused on cancer populations, with relatively good agreement identified in those which analyzed hormone therapy, estrogen, and chemotherapy (n = 11). Agreement was especially good for chemotherapy (proportion correct ≥93.6%, kappa ≥0.88). No distinct associations between agreement and age, education or marital status were identified in the results. There was little evaluation of associations between agreement and study design, self-report modality and comparison data source, thus not allowing for any conclusions to be drawn.

CONCLUSION

An overview of the evidence available from validation studies with a description of several characteristics is provided. Studies with experimental design which evaluate factors that might affect agreement between self-report and other data sources are lacking.

Using the "proportion of patients covered" and the Kaplan-Meier survival analysis to describe treatment persistence

PURPOSE

Standard Kaplan-Meier (KM) survival analysis is often used to study treatment persistence estimating the proportion of patients who have not yet experienced a treatment break by a given day after treatment initiation. This method only allows patients to be studied until their first treatment break. The "proportion of patients covered" (PPC) method is another approach to study treatment persistence. It measures the proportion of live patients currently covered by treatment. We aimed to describe the PPC method, show how the KM survival analysis and the PPC method can describe treatment persistence, and discuss the interpretation/application of the methods.

METHODS

We identified new users of statins, selective serotonin reuptake inhibitors, hormone replacement therapy, and ibuprofen. We used KM estimates and the PPC to describe persistence in the 3 years post treatment initiation, using a grace period of 90 days to define a treatment break.

RESULTS

Three years after statin initiation, approximately 40% of patients were still in continuous treatment (KM survival) and 60% of patients still alive were in current treatment (PPC). Corresponding numbers were 12% and 25% for selective serotonin reuptake inhibitors and 9% and 29% for hormone replacement therapy. At 1 year, numbers were 5% and 10% for ibuprofen. The PPC showed markedly less variability than the KM survival analysis with different choices of grace periods.

CONCLUSIONS

The KM survival analysis and the PPC method can be used to study different aspects of treatment persistence. Together, they provide a more complete picture of treatment persistence and drug use patterns.

Refining estimates of prescription durations by using observed covariates in pharmacoepidemiological databases: an application of the reverse waiting time distribution

PURPOSE

The study aimed to develop an automated method to estimate prescription durations in pharmacoepidemiological studies that may depend on patient and redemption characteristics.

METHODS

We developed an estimation algorithm based on maximum likelihood estimation for the reverse waiting time distribution (WTD), which is the distribution of time from the last prescription of each patient within a time window to the end of the time window. The reverse WTD consists of two distinctly different components: one component for prevalent users and one for patients stopping treatment. We extended the model to allow parameters of the reverse WTD to depend on linear combinations of covariates to obtain estimates and confidence intervals for percentiles of the inter-arrival density (time from one prescription to the subsequent). We applied the method to redemptions of warfarin, using the amount of drug filled, patient sex and patient age as covariates.

RESULTS

The estimated prescription durations increased with redeemed amount and age. Women generally had longer prescription durations, which increased more with age than men. For 70-year-old women redeeming 300+ pills, we predicted a 95th percentile of the inter-arrival density of 225 (95%CI: 201, 249) days. For 50-year-old men redeeming 100 pills, the corresponding prediction was 97 (88, 106) days.

CONCLUSIONS

The algorithm allows estimation of prescription durations based on the reverse WTD, which can depend upon observed covariates. Statistical uncertainty intervals and tests allow statistical inference on the influence of observed patient and prescription characteristics. The method may replace ad hoc decision rules. Copyright © 2017 John Wiley & Sons, Ltd.

An algorithm to identify medication nonpersistence using electronic pharmacy databases

OBJECTIVE

Identifying patients who are medication nonpersistent (fail to refill in a timely manner) is important for healthcare operations and research. However, consistent methods to detect nonpersistence using electronic pharmacy records are presently lacking. We developed and validated a nonpersistence algorithm for chronically used medications.

MATERIALS AND METHODS

Refill patterns of adult diabetes patients (n = 14,349) prescribed cardiometabolic therapies were studied. We evaluated various grace periods (30-300 days) to identify medication nonpersistence, which is defined as a gap between refills that exceeds a threshold equal to the last days' supply dispensed plus a grace period plus days of stockpiled medication. Since data on medication stockpiles are typically unavailable for ongoing users, we compared nonpersistence to rates calculated using algorithms that ignored stockpiles.

RESULTS

When using grace periods equal to or greater than the number of days' supply dispensed (i.e., at least 100 days), this novel algorithm for medication nonpersistence gave consistent results whether or not it accounted for days of stockpiled medication. The agreement (Kappa coefficients) between nonpersistence rates using algorithms with versus without stockpiling improved with longer grace periods and ranged from 0.63 (for 30 days) to 0.98 (for a 300-day grace period).

CONCLUSIONS

Our method has utility for health care operations and research in prevalent (ongoing) and new user cohorts. The algorithm detects a subset of patients with inadequate medication-taking behavior not identified as primary nonadherent or secondary nonadherent. Healthcare systems can most comprehensively identify patients with short- or long-term medication underutilization by identifying primary nonadherence, secondary nonadherence, and nonpersistence.

Postmenopausal estrogen therapy and risk of gallstone disease: a population-based case-control study

BACKGROUND

Female gender and increasing age are key risk factors for gallstone disease; therefore, postmenopausal women are at high risk. Estrogen increases cholesterol saturation of bile and may further increase gallstone risk, but population-based evidence is sparse.

OBJECTIVE

Our objective was to examine the association between postmenopausal estrogen therapy and risk of gallstone disease and the impact of duration of treatment and use of opposing progestin.

STUDY DESIGN

We conducted a population-based case-control study. Cases were postmenopausal women (defined as aged ≥45 years) with gallstone disease identified in the period 1996-2010. For each case, we selected ten population controls matched to cases by age and sex. We defined exposure as any use of estrogen (opposed and unopposed by progestin). Cases/controls were categorized as current estrogen users if their last prescription was redeemed <90 days before gallstone diagnosis (or corresponding date for controls); all other users were categorized as former users. The reference group consisted of cases/controls with no/rare estrogen use.

SETTING

Medical databases covering the population of Northern Denmark (2.4 million inhabitants through the period 1996-2010).

MAIN OUTCOME MEASURE

We used conditional logistic regression to compute adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) of gallstone disease in women treated with estrogen. The ORs were adjusted for relevant comorbidity, other drugs known to influence gallstone risk, and parity.

RESULTS

We identified 16,386 cases with gallstone disease and 163,860 controls. A total of 1,425 cases (8.7 %) and 8,930 controls (5.4 %) were current estrogen users, yielding an adjusted OR for gallstone disease of 1.74 (95 % CI 1.64-1.85) compared with non-users. The corresponding adjusted OR for former users was 1.35 (95 % CI 1.28-1.42). The results suggested a duration response for current users. Use of unopposed estrogen was associated with higher adjusted ORs than estrogen opposed by progestin.

CONCLUSION

Postmenopausal estrogen therapy was associated with increased risk of gallstone disease in current and former estrogen users. Use of unopposed estrogen was associated with higher risk than use of estrogen opposed by progestin; this finding needs to be confirmed and explored further in future studies.

Long-term use of antiplatelet drugs by stroke patients: a follow-up study based on prescription register data

PURPOSE

Treatment with antiplatelet drugs is a key element of secondary stroke prevention. We investigated long-term antiplatelet drug use in stroke patients with a focus on non-persistence.

METHODS

Population-based prescription register data were used to determine antiplatelet drug use in a cohort of stroke patients discharged from a Danish neurology department. The antiplatelet drugs comprised acetylsalicylic acid (ASA), clopidogrel and dipyridamole (if combined with ASA use). Non-persistence was defined as failure to present a prescription for antiplatelet drugs within 180 days after the dosage of a previous prescription had run out, or within 180 days after discharge. Cox regression was used to identify risk factors for non-persistence.

RESULTS

The cohort comprised 503 patients with ischaemic stroke discharged in 1999-2001. During follow-up (median 2.8 years, interquartile range 0.8-7.8 years), 486 of the subjects presented prescriptions for antiplatelets. Most subjects used a dual regimen of ASA and dipyridamole (N = 320). Of 110 non-persistent subjects in this group, 64 stopped using ASA, but continued to use dipyridamole in monotherapy. Overall, 181 patients (36 %) were non-persistent. Stroke severity was inversely associated with the risk of non-persistence [NIHSS score on admission 0-3 (reference); 4-6: hazard risk (HR) 0.87, 95 % confidence interval (CI) 0.61-1.25; 7+: HR 0.47, 95 % CI 0.29-0.74].

CONCLUSIONS

Long-term non-persistence with antiplatelet treatment was high and more pronounced in our patients with less severe stroke. Our findings on the use of ASA and dipyridamole indicate that non-persistence may in part be amenable to simple intervention measures.