Publications by Year: 2016

2016
Donneyong MM, Bykov K, Bosco-Levy P, Dong Y-H, Levin R, Gagne JJ. Risk of mortality with concomitant use of tamoxifen and selective serotonin reuptake inhibitors: multi-database cohort study. BMJ. 2016;354 :i5014.Abstract
OBJECTIVE:  To compare differences in mortality between women concomitantly treated with tamoxifen and selective serotonin reuptake inhibitors (SSRIs) that are potent inhibitors of the cytochrome-P450 2D6 enzyme (CYP2D6) versus tamoxifen and other SSRIs. DESIGN:  Population based cohort study. SETTING:  Five US databases covering individuals enrolled in private and public health insurance programs from 1995 to 2013. PARTICIPANTS:  Two cohorts of women who started taking tamoxifen. In cohort 1, women started taking an SSRI during tamoxifen treatment. In cohort 2, women were already taking an SSRI when they started taking tamoxifen. MAIN OUTCOME MEASURES:  All cause mortality in each cohort in women taking SSRIs that are potent inhibitors of CYP2D6 (paroxetine, fluoxetine) versus other SSRIs. Propensity scores were used to match exposure groups in a variable ratio fashion. Results were measured separately for each cohort and combined hazard ratios calculated from Cox regression models across the two cohorts with random effects meta-analysis. RESULTS:  There were 6067 and 8465 new users of tamoxifen in cohorts 1 and 2, respectively. Mean age was 55. A total of 991 and 1014 deaths occurred in cohorts 1 and 2 during a median follow-up of 2.2 (interquartile range 0.9-4.5) and 2.0 (0.8-3.9) years, respectively. The pooled hazard ratio for death for potent inhibitors (rate 58.6/1000 person years) compared with other SSRIs (rate 57.9/1000 person years) across cohorts 1 and 2 was 0.96 (95% confidence interval 0.88 to 1.06). Results were consistent across sensitivity analyses. CONCLUSION:  Concomitant use of tamoxifen and potent CYP2D6 inhibiting SSRIs versus other SSRIs was not associated with an increased risk of death.
Leonard CE, Bilker WB, Brensinger CM, Han X, Flory JH, Flockhart DA, Gagne JJ, Cardillo S, Hennessy S. Severe hypoglycemia in users of sulfonylurea antidiabetic agents and antihyperlipidemics. Clin Pharmacol Ther. 2016;99 (5) :538-47.Abstract
Drug-drug interactions causing severe hypoglycemia due to antidiabetic drugs is a major clinical and public health problem. We assessed whether sulfonylurea use with a statin or fibrate was associated with severe hypoglycemia. We conducted cohort studies of users of glyburide, glipizide, and glimepiride plus a statin or fibrate within a Medicaid population. The outcome was a validated, diagnosis-based algorithm for severe hypoglycemia. Among 592,872 persons newly exposed to a sulfonylurea+antihyperlipidemic, the incidence of severe hypoglycemia was 5.8/100 person-years. Adjusted hazard ratios (HRs) for sulfonylurea+statins were consistent with no association. Most overall HRs for sulfonylurea+fibrate were elevated, with sulfonylurea-specific adjusted HRs as large as 1.50 (95% confidence interval (CI): 1.24-1.81) for glyburide+gemfibrozil, 1.37 (95% CI: 1.11-1.69) for glipizide+gemfibrozil, and 1.63 (95% CI: 1.29-2.06) for glimepiride+fenofibrate. Concomitant therapy with a sulfonylurea and fibrate is associated with an often delayed increased rate of severe hypoglycemia.
Gagne JJ, Han X, Hennessy S, Leonard CE, Chrischilles EA, Carnahan RM, Wang SV, Fuller C, Iyer A, Katcoff H, et al. Successful Comparison of US Food and Drug Administration Sentinel Analysis Tools to Traditional Approaches in Quantifying a Known Drug-Adverse Event Association. Clin Pharmacol Ther. 2016;100 (5) :558-564.Abstract
The US Food and Drug Administration's Sentinel system has developed the capability to conduct active safety surveillance of marketed medical products in a large network of electronic healthcare databases. We assessed the extent to which the newly developed, semiautomated Sentinel Propensity Score Matching (PSM) tool could produce the same results as a customized protocol-driven assessment, which found an adjusted hazard ratio (HR) of 3.04 (95% confidence interval [CI], 2.81-3.27) comparing angioedema in patients initiating angiotensin-converting enzyme (ACE) inhibitors vs. beta-blockers. Using data from 13 Data Partners between 1 January 2008, and 30 September 2013, the PSM tool identified 2,211,215 eligible ACE inhibitor and 1,673,682 eligible beta-blocker initiators. The tool produced an HR of 3.14 (95% CI, 2.86-3.44). This comparison provides initial evidence that Sentinel analytic tools can produce findings similar to those produced by a highly customized protocol-driven assessment.
Gagne JJ, Polinski JM, Jiang W, Dutcher SK, Xie J, Lii J, Fulchino LA, Kesselheim AS. Switch-backs associated with generic drugs approved using product-specific determinations of therapeutic equivalence. Pharmacoepidemiol Drug Saf. 2016;25 (8) :944-52.Abstract
PURPOSE: US Food and Drug Administration approval for generic drugs relies on demonstrating pharmaceutical equivalence and bioequivalence; however, some drug products have unique attributes that necessitate product-specific approval pathways. We evaluated rates of patients' switching back to brand-name versions from generic versions of four drugs approved via such approaches. METHODS: We used data from Optum LifeSciences Research Database to identify patients using a brand-name version of a study drug (acarbose tablets, salmon calcitonin nasal spray, enoxaparin sodium injection, and venlafaxine extended release tablets) or a control drug. We followed patients to identify switching to generic versions and then followed those who switched to identify whether they switched back to brand-name versions. We calculated switch and switch-back rates and used Kaplan-Meier and log-rank tests to compare rates between study and control drugs. RESULTS: Our cohort included 201 959 eligible patients. Brand-to-generic switch rates ranged from 66 to 106 switches per 100 person-years for study drugs and 80 to 110 for control drugs. Rates of switch-back to brand-name versions ranged from 5 to 37 among study drugs and 3 to 53 among control drugs. Switch-back rates were higher for venlafaxine vs. sertraline (p < 0.01) and calcitonin vs. alendronate (p = 0.01). Switch-back rates were lower for venlafaxine vs. paroxetine (p < 0.01) and acarbose vs. nateglinide (p < 0.01). Rates were similar for acarbose vs. glimepiride (p = 0.97) and for enoxaparin vs. fondiparinux (p = 0.11). CONCLUSION: As compared to control drugs, patients were not more likely to systematically switch back from generic to brand-name versions of the four study drugs. Copyright © 2016 John Wiley & Sons, Ltd.
Kesselheim AS, Bykov K, Gagne JJ, Wang SV, Choudhry NK. Switching generic antiepileptic drug manufacturer not linked to seizures: A case-crossover study. Neurology. 2016;87 (17) :1796-1801.Abstract
OBJECTIVE: With more antiepileptic drugs (AED) becoming available in generic form, we estimated the risk of seizure-related events associated with refilling generic AEDs and the effect of switching between different manufacturers of the same generic drug. METHODS: We designed a population-based case-crossover study using the Medicaid Analytic eXtract and a US commercial health insurance database. We identified 83,001 generic AED users who experienced a seizure-related hospital admission or emergency room visit between 2000 and 2013 and assessed whether they received a refill of the same AED from the same manufacturer or a different manufacturer. Patients served as their own controls and conditional logistic regression was used to compare exposure to a refill during the hazard period, defined as days 2-36 preceding the seizure-related event, to exposure during the control period, defined as days 51-85 preceding the seizure-related event. RESULTS: Generic AED refilling was associated with an 8% increase in the odds of seizure-related events (odds ratio [OR] 1.08; 95% confidence interval [CI] 1.06-1.11). The OR following a switch to a different manufacturer of the same AED was 1.09 (95% CI 1.03-1.15); however, after adjusting for the process of refilling, there was no association between switching and seizure-related hospital visits (OR 1.00; 95% CI 0.94-1.07). CONCLUSIONS: Among patients on a generic AED, refilling the same AED was associated with an elevated risk of seizure-related event; however, there was no additional risk from switching during that refill to a different manufacturer. Generic AEDs available to US patients, with Food and Drug Administration-validated bioequivalence, appear to be safe clinical choices.
Pottegård A, Friis S, dePont Christensen R, Habel LA, Gagne JJ, Hallas J. Time for integrating clinical, lifestyle and molecular data to predict drug responses - Authors' reply. EBioMedicine. 2016;7 :11.
Mott K, Graham DJ, Toh S, Gagne JJ, Levenson M, Ma Y, Reichman ME. Uptake of new drugs in the early post-approval period in the Mini-Sentinel distributed database. Pharmacoepidemiol Drug Saf. 2016;25 (9) :1023-32.Abstract
PURPOSE: Several factors limit the statistical power of drug safety surveillance during the early post-approval period, including uptake of the drug and lag in data availability. This study characterized new drug uptake in the Mini-Sentinel Distributed Database and determined statistical power to detect levels of risk in post-launch safety assessments. METHODS: The cumulative exposure among initiators of 46 new molecular entities approved from 2008 to 2011 was assessed. Using a Poisson estimation method, minimum incidence rate ratios (IRRs) detectable, with 80% power, were calculated under varying background incidence rates. RESULTS: Twelve products (26.1%) had more than 15 000 new users after 2 years. With comparator group incidence rate of 1/1000 person-years, 16 (33.3%) products had enough exposure to detect an IRR of 5 with 24 months of data collected that would be available for assessment at 33 months post-launch. With an incidence rate of 5/1000 person-years, 23 (50%) products had enough exposure to detect an IRR of ≥3 with 2 years of data collected. At 33 months post-launch, only two (4.3%) of the drugs examined had enough data availability to detect IRR of <2, and eight (17.4%) of <3, with a background rate of 1/1000 person-years. CONCLUSION: This study highlights the importance of drug uptake and data availability in early post-approval drug safety surveillance in Mini-Sentinel. There is limited ability to detect rate ratios below three for events with background rates of 1/1000 person-years or lower. This is largely due to low product uptake. Copyright © 2016 John Wiley & Sons, Ltd.
Kesselheim AS, Gagne JJ, Franklin JM, Eddings W, Fulchino LA, Avorn J, Campbell EG. Variations in Patients' Perceptions and Use of Generic Drugs: Results of a National Survey. J Gen Intern Med. 2016;31 (6) :609-14.Abstract
BACKGROUND: Over 84 % of all prescriptions in the US are filled as generic drugs, though in prior surveys, patients reported concerns about their quality. OBJECTIVE: We aimed to survey patients' perceptions and use of generic drugs. DESIGN: Our survey (administered August 2014) assessed patients' skepticism about generic drug safety and effectiveness and how often they requested brand-name drugs. Chi-square tests and two-sample t-tests assessed associations between patient demographics and the outcomes. PARTICIPANTS: Our sample frame was the CVS Advisor Panel, a national database of 124,621 CVS customers. We randomly selected 1450 patients with self-reported chronic conditions who filled at least one prescription in the prior 3 months. MAIN MEASURES: We assessed how often patients reported asking their physicians to prescribe a brand-name over a generic drug in the last year, and "generic skepticism," defined as not believing generic drugs were as safe, effective, had the same side effects, and contained the same active ingredients as brand-name drugs. KEY RESULTS: Of the 1,442 patients with valid addresses, 933 responded (65 % response rate) and 753 took the full survey. A vast majority (83 %) agreed that physicians should prescribe generic drugs when available, and 54 % said they had not asked their physicians to prescribe a brand-name drug over a generic in the past year. Most respondents considered generic drugs to be as effective (87 %) and safe (88 %) as their brand-name counterparts, and to have the same side effects (80 %) and active ingredients (84 %). Non-Caucasians were more likely than Caucasians to request a brand-name drug over a generic (56 % vs. 43 %, p < 0.01), and were also more skeptical of generic drugs' clinical equivalence (43 % vs. 29 %, p < 0.01). CONCLUSIONS: We found a substantial shift towards more patients having positive views of generic drugs, but lingering negative perceptions will have to be overcome to ensure continued cost-savings and improved patient outcomes from generic drugs.
Sinnott S-J, Polinski JM, Byrne S, Gagne JJ. Measuring drug exposure: concordance between defined daily dose and days' supply depended on drug class. J Clin Epidemiol. 2016;69 :107-13.Abstract
OBJECTIVES: To determine the concordance between two methods to measure drug exposure duration from pharmacy claim data. STUDY DESIGN AND SETTING: We conducted a cohort study using 2002-2007 US Medicaid data. Initiators of eight drug groups were identified: statins, metformin, atypical antipsychotics, warfarin, proton pump inhibitors (PPIs), angiotensin-converting enzyme (ACE) inhibitors, nonsteroidal anti-inflammatory drugs (ns-NSAIDs), and coxibs. For each patient, we calculated two measures of exposure duration using (1) observed days' supply available in US pharmacy claims and (2) the World Health Organisation's Defined Daily Dose (DDD) methodology. We used Wilcoxon signed rank tests to compare medians and Spearman correlations to assess correlation between the two measures. RESULTS: Cohort sizes ranged from 143,885 warfarin users to >3,000,000 ns-NSAID users. Similar median exposure durations were observed for ACE inhibitors (70 days vs.75 days), PPIs (44 days vs. 45 days), and coxibs (44 days vs. 45 days). The DDD method overestimated exposure duration for ns-NSAIDs and underestimated for the remaining drug groups, relative to days' supply. Spearman correlation coefficients ranged from 0.2 to 0.8. CONCLUSION: Using DDDs to estimate drug exposure duration can result in misclassification. The magnitude of this misclassification might depend on doses used which can vary according to factors such as local prescribing practices, renal function, and age.

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