Post-market Authorized Generic Evaluation (PAGE)
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1 Post-market Authorized Generic Evaluation (PAGE) U01FD November 18 th, 2016 Peggy L. Peissig Richard Berg Michael Caldwell James Linneman Richard Hansen Jingjing Qian Motiur Rahman Ning Cheng Yasser Alatawi David Page Enrique Seoane- Vazquez
2 Project Overview 2
3 Specific Aim 1 To determine and compare switchback rates, medical service utilization, and clinical outcomes between authorized generics (AGs) and generics using healthcare claim data with electronic medical records. 3
4 Aim 1 Methods Study design: a retrospective cohort study Study population: Marshfield Clinic (MC) Security Health Plan (SHP) claims data with linked electronic health records (EHR) data in Inclusion criteria: Continuous enrollment (CE) in 6-mon prior to generic introduction through at least the first Rx fill after generic availability At least 1 brand Rx in 6-mon prior and 1 Rx fill of a medication in the therapeutic area within 12-mon after generic availability At least 1 MC healthcare encounter/year during eligible periods 4
5 Aim 1 Methods (cont d) Pre-index Branded treatment initiation Generic entry Brand Non-switchers: stay on brand Index date for generic switch Generic switch Switchback Brand Generic Switchers: switchback to brand Switchers: stay on generic Index date for switchback Generic switch: switch from a brand drug to an authorized or independent generic drug within 30 months following generic entry Switchback: among those who had a brand to generic switch, generic to brand switchback rates were calculated in 30 months following the index switch date 5
6 Aim 1 Methods (cont d) Revised drugs of interest: Drugs Generic Switch Switchback alendronate x x amlodipine x x citalopram x x gabapentin x x glimepiride x losartan x metformin x paroxetine x x sertraline x x simvastatin x x 6
7 Rates of Switching Time from generic entry to generic switch by drug Drugs Brand to AG Switch Type Brand to OG All drugs (n=5234) 1138 (23%) 3762 (77%) Alendronate (n=930) 41 (5%) 832 (95%) Amlodipine (n=1487) 289 (20%) 1156 (80%) Citalopram (n=813) 74 (10%) 670 (90%) Gabapentin (n=279) 25 (11%) 199 (89%) Paroxetine (n=669) 302 (48%) 328 (52%) Sertraline (n=730) 278 (40%) 417 (60%) Simvastatin (n=636) 176 (30%) 408 (70%) *Factors associated with a higher likelihood of generic switch in the overall drug cohort included pre-index defined daily dose and allcause hospitalization 7
8 Rates of Switching Back to Brand Brand switchback rate from AG vs. OG Factors Brand to Generic Switchback Hazard Ratio 95% Confidence Interval IG (REF=AG) Age 1.02 * Male 0.59 * Proportion of pre-index brand medication use 2.43 * Defined daily dose prior to switching Charlson comorbidity index Pre-index hospitalization Pre-index ED visit Count of pre-index outpatient visits *P<0.05, multivariable Cox proportional hazards model 8
9 Health Services Use & Outcomes Adjusted medical service utilization and outcomes for AG vs. OG users Outcome Number of all-cause outpatient visists per year Number of all-cause urgent care visits per year Estimate Lower CI Upper CI P-Value All-cause emergency department visits Any visit Number per year All-cause hospitalizations Any visit Number per year Medication discontinuation Favors OG 1 Favors AG 2 Estimate *Medical service utilization and outcomes were measured during a 12-month period after generic switch. Generalized logistic regression was used to model binary outcomes and negative binomial regression were used to mode count outcomes. Age, defined daily dose, and Charlson score were controlled as covariates in these models. 9
10 Specific Aim 2 To analyze brand versus generic adverse event reporting rates in the FDA Adverse Event Reporting System (FAERS) 10
11 Methods Data FAERS data Approach Method 1 verbatim assignment by name Method 2 assign reports to manufacturer Exclude direct reports Sensitivity analyses around which reports to include, such as primary suspect, serious, only, validated Analyses Disproportionality analyses Segmented regression 11
12 Drugs Alendronate Amlodipine Azithromycin Carbamazepine XR Escitalopram Lamotrigine Leflunomide Losartan Metoprolol XR Modafinil Oxcarbazepine Sertraline Venlafaxine ER Zolpidem 12
13 Events Coded by Preferred Terms (PT) or Standardized MedDRA Query (SMQ) Drug specific events defined by label Universal events - Accidents & injuries - Lack of efficacy - Anaphylactic reactions - Ischemic heart disease - Embolic & thrombotic events - Hematopoietic cytopenias - Hemorrhages - Death 13
14 Report Percentage Report Type as Percentage of Total 120 BRAND% AG% GENERIC% ---- Inclusive of all drugs Generic Entry 14
15 Lamotrigine Labeled Events 15
16 Segmented Regression Full Segmented Regression Model* (unadjusted for prescription sales) FDA time Intercept β (P= 0.71) Trend before AG entered into market 87 (Period 1) β 1 Total Adverse Events (P=0. 37) Level change after AG but before other -139 IG entered into market (Period 2) β 2 Trend change after AG but before other -80 IG entered into market (Period 2) β 3 (P= 0.71) (P= 0.51) Level change after other IG entered into 27 market (Period 3) β 4 (P= 0.92) Trend change after other IG entered into -12 market (Period 3) β 5 (P= 0.89) Lamotrigine EVENT time 524 (P= 0.01) 22 (P= 0.64) -166 (P= 0.39) 11 (P= 0.87) -197 (P= 0.12) -38 (P= 0.42) MFR time 525 (P=0.005) 15 (P= 0.07) -62 (P= 0.72) -17 (P= 0.83) -112 (P= 0.40) -1 (P= 0.99) Serious Adverse Events FDA time 41 (P=0.46) 17 (P=0.08) -18 (P=0.62) -22 (P=0.06) 9 (P=0.73) 7 (P=0.42) EVENT time 88 (P=0.03) 5 (P=0.46) -18 (P=0.52) -5 (P=0.56) -2 (P=0.90) 0.48 (P=0.94) MFR time 90 (P=0.17) 7 (P=0.72) 19 (P=0.81) -13 (P=0.63) -1 (P=0.99) 8 (P=0.68) 16
17 Methodological Challenges Limited Authorized Generic Formulations Only specific formulations available as AG Lamotrigine chewable Extended release carbamazepine, metoprolol, venlafaxine Authorized Generic Availability Strength of connection between brand and AG Greenstone and Pfizer Dual marketing of AG and ANDA-approved generic Dr. Reddy s Simvastatin 17
18 Methodological Approach Illustrated with alendronate Which report types? Which time? Ignore the AG? Illustrated with carbamazepine XR Multiple formulations with and without AG? 18
19 Sensitivity Analysis: Report Type? Alendronate Gastritis 19
20 Sensitivity Analysis: Count All Time? Alendronate 20
21 Sensitivity Analysis: Ignore AG? Alendronate 21
22 Sensitivity Analysis: Modified Formulations? Carbamazepine 22
23 REPORTS REPORTS REPORTS 4000 Sensitivity Analysis: FDA_date Event_date Report_date AG/IG Entry YEAR FDA_Time EVENT_Time MFR_Time Brand Authorized Generic AG/IG Entry YEAR FDA_Time EVENT_Time MFR_Time Alendronate AG/IG Entry YEAR FDA_Time EVENT_Time MFR_Time Generic 23
24 Suicide / Suicidal Ideation in FAERS 24
25 Suicide / Suicidal Ideation in SHP Sertraline Gabapentin Methylphenidate Zolpidem BRAND GENERIC BRAND GENERIC BRAND GENERIC BRAND GENERIC SAMPLE SIZE Event count (n, %) 35 (0.5%) 249 (1.3%) 14 (0.4%) 103 (0.5%) 25 (0.4%) 16 (1.0%) 39 (0.5%) 123 (0.9%) Unadjusted p- value <.0001 Ref Ref Ref Ref Hazard Ratio (95% CI) 0.53 ( ) Ref 1.07 ( ) Ref 0.37 ( ) Ref 0.85 ( ) Ref Adjusted p- value Ref Ref Ref Ref 25
26 Specific Aim 3 To develop a pilot surveillance system to compare patient experience for authorized generics and independent generics with brand name drugs for differential adverse event signal detection. 26
27 Marshfield s Population Security Health Plan MC Primary Service Area
28 Analysis Decision Points Analysis cohort (e.g. first-time users of the drug vs. switch cohort) Maximum length of observation time (e.g. 365 days vs. 30 days) Inclusion / Exclusion of those with events prior to drug exposure Inclusion / Exclusion of those with events documented on a single date Statistical model (e.g. PH model of time to first event, negative binomial) Covariates Gender Age Charlson comorbidity score Diabetes indicator Smoking indicator MESA residency indicator Estimated SHP rate for the event of interest
29 Surveillance System Development Process Initial screening Secondary analysis Review the raw data Initial model based analysis Are numbers small? Review unadjusted/adjusted significance Are hazard ratios reasonable? Evaluate results after varying decision points Evaluate subsetting cohort to limit date of first exposure Gather extensive data pre-exposure Evaluate associations with B/G and outcome Develop propensity score to improve B/G comparability Use another drug as secondary comparison group Expert Review Trained research coordinator review Expert evaluation
30 30
31 Contact Information Richard Hansen, RPh, PhD Auburn University Harrison School of Pharmacy Department of Health Outcomes Research & Policy 31
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