Comparative safety of the novel anticoagulants vs warfarin

Transcription

1 Comparative safety of the novel anticoagulants vs warfarin Sonal Singh, MD, MPH Phd Candidate ( Epidemiology- Part time) Johns Hopkins University Research in Progress Seminar, Center for Drug Safety and Effectiveness, Johns Hopkins University October 15

2 Conflicts of Interest None Funding sources: None

3 Background Atrial fibrillation (AF) is the most common arrhythmia in the US. AF carries substantial morbidity and mortality because of stroke based on CHADS2 score For more than half a century, oral warfarin has been the cornerstone for the prevention of stroke in atrial fibrillation. Am J Cardiol 2009; 104:

4 Novel anticoagulants ( noacs) Dabigatran etexilate is the only direct thrombin inhibitor (DTI) clinically available for oral administration Rivaroxaban also approved for stroke prevention recently-oral direct factor Xa inhibitor Apixaban pending approval later this year RELY Trial, ROCKET AF, ARISTOTLE;NEJM 2009; 361: NEJM 2011; 365: NEJM; 2011;365:

5 BJCP 2010;70 (1):14-15 Journal compilation Copyright 2010 The British Pharmacological Society

6 Patterns of use Dabigatran etexilate had become the DOC at about 19% of office visits for oral anticoagulation, compared with 81% for warfarin by end of 2011 ( Rivaroxaban only approved Nov 2011) increasing rates of off-label use of dabigatran over time Circ Cardiovasc Qual Outcomes 2012; 5:

7 Pivotal Trials of noacs Dabigatran at 150 mg associated with lower rates of stroke and systemic embolism (1.11% vs. 1.71%, p<0.001) in RELY Rivaroxaban at 10 mg dose non-inferior on stroke and systemic embolism in the ROCKET-AF. Apixaban similar effect in the ARISTOTLE trial. Annual major bleeding risk 3.32% vs. 3.57%, p=0.32 for dabigatran compared to warfarin). However the rates of serious ICB were lower but the rates of GIB higher with dabigatran. No differences in rates of major bleeding between warfarin and rivaroxaban in the ROCKET-AF trial. 3 Rates of ICH were also lower in the rivaroxaban arm RELY Trial, ROCKET AF, ARISTOTLE;NEJM 2009; 361: NEJM 2011; 365: NEJM; 2011;365:

8 Pharmacologic hypothesis Is the risk of bleeding and GI bleeding higher with noacs compared to warfarin The active compound dabigatran is hardly absorbed from the gastrointestinal tract Spontaneous reports to FAERS of uncontrollable GI bleed not reversible by any agent with dabigatran; * BJCP 2010;70 (1):14-15; ISMP report

9 Operational hypothesis 1, 2 Operational : Does this increase risk of bleeding represent differences between users Why me? Operational : Does this differential risk of bleeding represent differences within users Why now? McLure, PDS 2012; 21(S1): 50 61

10 Specific aims AIM 1.To determine the comparative safety of noacs and warfarin on major bleeding (including gastrointestinal hemorrhage and hemorrhagic stroke) among patients with atrial fibrillation. AIM 2. To determine the timing of the occurrence of major bleeding with rivaroxaban and dabigatran AIM 3. To determine whether periods on rivaroxaban or dabigatran use represent greater risk for bleeding than periods off anticoagulants among adult patients with atrial fibrillation in a general population.

11 Analytic Framework AIM 1SR and network MA AIM 3 New user incipient cohort propensity matched portal HTN; UGIB gastric or duodenal ulcer and coagulation disorders Charlson comorbidity index, CHADS 2,trauma, renalfailure and demographics( Age, Sex) Adult user of noac with AF Intervention: Dabigatran, Rivaroxaban and Apixaban Comparator: Warfarin Primary Outcomes; Major bleeding ; Secondary outcome GI bleeding Antiplatelet agents Bidirectional SCCS Time-invariant within person confounders and selection- healthy users, aspirin, alcohol

12 Rationale for Designs-I Variation within exposure to noacs Variation between individuals Variation between providers Propensity score new user RC Self controlled case series Instrumental vari Adapted from Schneiweissl PEDS :

13 Rationale for designs- II Proportion of users stop and restart ( within person exposure variation- SCCS) ( RELY trial approximated > 20% interruption Also variation between persons on anticoagulant use- PS Variation between provider use patterns- IV analysis Adapted from Schneiweissl PEDS : ; Madigan et al Report to OMOP on SCCS designs; ** Blood 2008;

14 Population Study : Random sample of adult AF users on OACs from the source Source: Adults > 18 enrolled in exposure to OACs Target : Adult >18 yr with AF in the US Study Source Target

15 Population in RCTs Study : adult AF users on OACs in RCTs (selective) Source: Adults > 18 enrolled in RCTs of anticoagulants from through Target : Adult >18 yr with AF in the US from Oct Target Source Study

16 Steps of the systematic review Question Literature search Selection of studies Assessment of methodological quality including ROB and strength of evidence Data extraction Synthesis of the data (network metaanalysis) Conclusions 16

17 Primary Outcomes for SR Primary : anticoagulant associated major bleeding (includes hemorrhagic stroke, fatal bleed) using International Society of Thrombosis and Hemostasis criteria Secondary : Gastrointestinal Bleeding Journal of Thrombosis and Haemostasis, 3:

18 ISTH major bleed 1 Fatal bleeding, and/or 2 Symptomatic bleeding in a critical area or organ, such as intracranial, intraspinal, intraocular, retroperitoneal, intraarticular or pericardial, or intramuscular with compartment syndrome, and/or 3 Bleeding causing a fall in hemoglobin level of 20 g L)1 (1.24 mmol L)1) or more, or leading to transfusion of two or more units of whole blood or red cells. Should result in death, life-threatening, cause chronic sequelae or consume major health-care resources. Journal of Thrombosis and Haemostasis, 3:

19 Mills et al ( Puhan). JAMA Users Guide on how to interpret a study of network MA 2012; J Clin Epidemiol 1997; 50(6):683-91; Indirect treatment calculator from CADTH. Statistical analysis -SR Relative Risk meta-analysis with sensitivity analysis for rare events for direct metaanalysis Network meta-analysis has been sparingly used for safety outcomes-concerns about consistency and power Dabigatran Rivaroxaban Warfarin Placebo Apixaban

20 Limitations of trials in documenting safety 1. Selectiveness : All noac trials excluded those with previous GIB *; in real world about one-third of participants who would receive noacs have GI bleed risk factors. ** 2. Limitation in statistical power 3. Detection of unexpected SAEs 4. Commercial biases unpublished data- anonymous ; ** Blood 2008; ; Singh and Loke Trials 2012 [ epub ahead of print]

21 Analytic Challenges Network MA: Inhomogeneity and inconsistency; secular trends over time since warfarin trials are older with changes of pattern of treatments over time Mills, Puhan et al. JAMA users guide 2012

22 Ideal Population Study : Random sample of adult AF users on OACs from the source Source: Adults > 18 enrolled in exposure to OACs Target : Adult >18 yr with AF in the US Study Source Target

23 Population in RC study Study : Random sample of adult AF users on OACs from the source ( continuous users and continuous nonusers) Source: Adults > 18 enrolled in administrative health database with claims for AF and exposure to oral anticoagulants from Target : Adult >18 yr with AF in the US from Oct Minimize random error by using entire source Study Source Target

24 Study Cohort Open cohort patients >18 y who have a prescription for any OAC between October and Dec Claims run out would be 90 days following this date to ensure all claims are filed. To capture new users we will require no prescription claim for any OAC in the previous 180 days Minimum number of dispensing events for inclusion in the cohort (2 events). Exclude perioperative AF

25 Followup fill date for 1 st qualifying RX define date of entry New users followed until outcomes, death, loss of eligibility in enrollment, a gap in continous treatment exceeding 14 days, a Rx fill for another anticoagulant, a non-end point hospitalization, or end of study period (December 2012). To avoid informative censoring endpoints occurring within 30 d following a gap in continuous treatment will be counted in. For e.g., bleeding events occurring 15 days after the last dose of OACs will be captured. Not applicable to administrative censoring at end of study or when there are switches between OACs

26 New User open RC New users of dabigatran, rivaroxaban Study end date June 2012; 7 and 30 day washout 6 months of look back for covariate information, to ensure no use of OACs. New users of warfarin

27 J Manag Care Pharm 2011; 17: J Manag Care Pharm 2011; 17: Data Source Commercially insured with million patients in various practice sites across the USA. Available files needed include enrollment records, inpatients and outpatient claims, and records of filled prescriptions (date, name, dose quantity, duration). The population age and sex is representative of commercially insured, working populations in the US, except for racial differences. Social Security s Death Master Data is linked to claims to ascertain deaths. Each matching record here has a code indicating the quality of the match from a perfect match of all names, DOB and SSN to less restrictive matches. All data on patients in the study are appropriately de-identified. J Managed Care Pharmacy 2011;17;531-46

28 Exposure and Validation Prescription data as a proxy for drug exposure. Using 10 digit NDC codes for OACs-Define active compounds, the drug dose and route of exposure, the number of units prescribed and the actual prescriptions and duration Although exposure to OACs has not been previously validated, it is likely similar to exposure to other drugs which is reasonably accurate in the Optum Database. High correlation between claims and prescription taken for chronic meds. Med Care 1999;37:846-57

29 Outcomes & Validation Dichotomous, Binary, Incident, recurrent (?) bleeding outcome Major bleeding ( PPV 89 99%) ICH PPV ( 77%) GIB PPV( 67%) Pharmacoepidemiol Drug Saf 2011; 20:560-6; Med Care 2005;43: ; APT 2006;24:

30 Validation of outcomes and select covariates

31 Pharmacoepidemiol Drug Saf 2011; 20: Propensity Score PS for exposure to OACs using multivariate LR to control for confounding and improve balance between patients in exposure cohorts. Variables included will include covariates in AF if associated with bleeding and anticoagulants (confounders) or bleeding alone (outcome). Consider psmatch2 command in Stata v11.0 to match individuals in the dabigatran or rivaroxaban cohort using 1:1 matching without replacement within a caliper width of 0.1. Consider weighting or full matching after examining data, sample size, and overlap Pharmacoepi and Drug Safety 2011; 20;551-9

32 Statistical Analysis Baseline comparisons of the cohorts using SMD KM cumulative incidence plots for time to event Time-dependant Cox proportional hazard model. HR 30 d, 90 d, 180 days, 365 days with 7 and 30 days washouts The proportional hazard assumption will be examined using weighted residuals and Wald Chi square test for the respective time windows. Stat Med 97: 16:611-26

33 Controlled Clinical Trials 1990; 11: Sample Size-cohort Matched sets of patients receiving the dabigatran and warfarin treatments with 10 matched warfarin(s) per patient on dabigatran because we will have a larger number of warfarin users. Prior data indicate that the probability of bleeding among warfarin is We assume that the correlation coefficient for exposure between matched experimental and a control subject is 0. If the true relative risk for bleeding in dabigatran subjects relative to warfarin subjects is 1.3, we will need to study 3656 subjects on dabigatran with 10 matched control(s) on warfarin to be able to reject the null hypothesis that this risk ratio equals 1 with probability (power) 0.8. The Type I error probability associated with this test of this null hypothesis is Controlled Clinical Trials 1990:11:116-28

34 Ideal Population Study : Random sample of adult AF users on OACs from the source Source: Adults > 18 enrolled in administrative health database with claims for AF and exposure to oral anticoagulants from Target : Adult >18 yr with AF in the US from Oct Study Source Target

35 SCCS Population Study : Random sample of adult AF users on OACs from the source- ( intermittent users who switch between levels of exposure) Source: Adults > 18 enrolled in administrative database with claims for AF and exposure to OACs from Target : Adult >18 yr with AF in the US from Oct Study Source Target

36 A single participant in SCCS Adapted from Expert Opin Drug Saf 2011; 10:337-40

37 SCCS Population individuals aged > 18 years who filled at least one Rx for any OAC between October 2010 and December 2012 and have experienced a bleed AND switch between levels of exposure to OACs (cross-over) Cases in which the diagnosis of major bleeding is recorded at the same time as first prescription will be excluded. The date of onset of bleeding will be altered to the first date for participants who have recently [last 8 weeks] had claims for either GI endoscopy or colonoscopy or emergency room visits before their diagnosed date of major bleeding events indicative of bleeding. Those who receive transfusion or IV PPI more than 8 wks prior to the diagnosis of major bleed will be excluded as prevalent events

38 Unidirectional vs Bidirectional SCCS Unidirectional SCCS reduce reverse causality bias ( bleeding may cause transient stopping of anticoagulants.) but prone to exposure trend biases- Exposure to product rising rapidly so only discordant pairs are discordant exposed few discordant unexposed- spurious high RR Bidirectional SCCS designs reduce exposure trend bias. Pharmacoepidemiology and Drug Safety; 2012;21 S1:50-61

39 Biometrics 1995; 51: Statistical Analysis for SCCS Crude and adjusted incidence rate ratios (IRR) and 95% CI for the outcome of incident major bleeding associated with use of anticoagulants during risk periods compared with baseline periods using conditional Poisson regression. Adjust for age using 10 year bands, sex and potential confounders that are time-varying. No need to adjust for time invariant confounders ( Sex) Sensitivity analyses to determine risks among those with long term exposure [6 mos] Biometrics 95;51:228-35

40 Stat Med 2006; 25: Sample size SCCS Sample size estimates for our self controlled case series study will vary depending on underlying assumptions about the incidence of major bleeding and its variation with age. Assuming a 2 tailed alpha of 0.05 and power of. 8 and accounting for increasing age effects, we will need 592 bleeding events to reliably estimate a 1.5 increased incidence rate ratio of major bleeding. Stat Med 2006; 25:2618-3

41 Analytic challenges Misclassification of exposure and outcome. Confounding by indication: Missing confounders : OTC Aspirin, PS: examine for matching ( if no overlap- PS=0). In that case Multivariate regression will be imprecise and PS not applicable

42 Analytic challenge Selection bias : Loss of participants from competing risks, dropout, missing data;; linkages to death master accounts for competing risk of death Prevalent user bias minimized by new user design Missing data : Multiple imputation for Missing at Random, unable to test for MNAR since unobserved variables J Clin Epidemiol 2006; 59:1102-9

43 Complementary information SCCS intermittent users that switch between use and non-use to evaluate acute transient effect of an exposure after controlling within person confounding, selection bias, cumulative exposure. Tradeoff that prescription data reflect an accurate timing of drug exposure. two different operational hypothesis for the same biologically plausible effect ; cumulative vs transient effects. Plausible that RR higher for SCCS and RR lower for Cohort. Pharmacoepidemiology and Drug Safety. 2007; 16(8):

44 ?' versus 'why now?'--differences between operational hypotheses in casecontrol versus case-crossover studies. Pharmacoepidemiology and Drug Safety. 2007; 16(8): Complementary [ /pds.1438] information Trials: internal validity at the cost of representativeness New user RC propensity score: better exposure classification if focused on continuous users and nonusers; control for available confounders; tradeoff unavailable confounders ( healthy users, ASA, alcohol) SCCTs cases only; intermittent users that switch between use and non-use; acute transient effect of noacs after controlling within person confounding and timeinvariant selection bias and also cumulative exposure; tradeoff prescription data reflect an accurate timing of drug exposure. Madigan et al. Report.pdf

45 Synthesis- Concordance If both observational study designs consistently show similar results in direction of effect more confidence in the estimates Inconsistency in direction will be examined for explanation by population, intervention and outcome Why me vs Why now? Pharmacoepidemiology and Drug Safety. 2007; 16(8):

46 Inferential challenges Generalizability to target population, especially since smaller sample of > 65 or in administrative claims data Type 2 errors : absence of statistically significant effect in underpowered studies does not constitute absence of effect Singh and Loke Trials 2012 [ epub ahead of print

47 Investigators: Advisory Committee Caleb Alexander, MD, MS ( Primary)- Associate Professor, Medicine & Epidemiology, JHU; keywords: pharmacoepi and longitudinal administrative claims Milo A Puhan, MD, PhD Associate Professor- Epidemiology and Medicine, JHU. Keywords Network MA Stephan Ehrhardt MD, PhD Associate Professor- Epidemiology, JHU; Epi, Keywords : selection bias, epidemiology Elizabeth Stuart, PhD Associate Professor- Biostatistics and Mental Health, JHU, key words : propensity score

48 Extra-PPV claims For GIB Restricting the diagnosis of a UGIE to ICD-9 CM code 531.xx (gastric ulcer), ICD-9 CM code 532.xx (duodenal ulcer) or ICD- 9 CM code 578.xx (GI haemorrhage) with a CPT procedural code for upper endoscopy (432.xx, 443.xx) in any position, yielded a sensitivity of 66% and an NPV of 88% while improving the specificity to 88% and the PPV to 67% (c-statistic of 0.75). Aliment Pharmacol Ther Jul 15;24(2): OMOP%20Systematic%20Literature%20Review%20Hemorrhage%20Final%20Report% pdf

49 Extra-Validation of major outcome Jensen et al. A systematic review of validated methods for atrial fibrillation using administrative data. Pharmacoepidemiol Drug Saf 2012; 21(S1): Cunningham A, Stein CM, Chung CP, Daugherty JR, Smalley WE, Ray WA. An automated database case definition for serious bleeding related to oral anticoagulant use. Pharmacoepidemiol Drug Saf 2011; 20: Choma NN, Griffin MR, Huang RL, Mitchel EF Jr, Kaltenbach LA, Gideon P, Stratton SM, Roumie CL. An algorithm to identify incident myocardial infarction using Medicaid data. Pharmacoepidemiol Drug Saf 2009; 18: