THIS TALK STATINS REDUCE: Immortal time bias Immeasurable time bias Time-window bias TIME-RELATED BIASES IN PHARMACOEPIDEMIOLOGY

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1 TIME-RELATED BIASES IN PHARMACOEPIDEMIOLOGY Samy Suissa McGill University and Jewish General Hospital Montreal, Canada ISPE mid-year meeting, Miami April 22, 2012 STATINS REDUCE: JAMA 2000: Fracture rate by 45% Lancet 2000: Rate of dementia by 71% Arch Int Med 2003: Rate of depression by 60% and rate of suicidal behaviour by 50% Diab Med 2004: Insulin initiation in diabetes by 26% BMJ 2005: Mortality in patients with IHD by 83% (in combination) ERJ 2007: Mortality in patients with COPD by 43% Chest 2007: Lung cancer incidence by 45% THIS TALK Immortal time bias Immeasurable time bias Time-window bias 1

2 Immortal time bias THE EXAMPLE OF COPD COPD: The Ontario Study Observational study (Ontario Health databases) Cohort of 22,620 patients hospitalised for COPD ( ) 25% readmitted for COPD within a year, 11% died 51% received an ICS within 90 days after discharge Data analysis by intent-to-treat approach using Cox s proportional hazards model, adjusting for covariates 2

3 Ontario Study: RESULTS RR= % reduction in all-cause mortality Ontario Study: RESULTS Ontario Study: Design = death 0 90 Days of follow-up 365 3

4 Ontario Study: Design = death = Inhaled corticosteroid Rx 0 90 Days of follow-up 365 Immortal and unexposed period Time zero: Discharge ICS Rx filled Death ICS users ~ 11,000 ICS non-users ~ 11, Death IMMORTAL TIME BIAS Must use time-dependent analysis 4

5 Replication of the Ontario Study Cohort of 979 patients hospitalised for COPD in Saskatchewan ( ) 40% readmitted for COPD or died within a year 39% received ICS within 90 days of discharge Two analyses: - Time-fixed Cox proportional hazards model (replication of Ontario study) - Time-dependent Cox proportional hazards model (classifies exposure over time) Cox model analysis with various ICS exposure time windows Time-fixed Time-dependent Rate- Ratio 95% CI Rate- Ratio 95% CI 90-day Cox model analysis with various ICS exposure time windows Time-fixed Time-dependent Rate- Ratio 15-day % CI Rate- Ratio 95% CI 30-day day day day

6 Cox model analysis with various ICS exposure time windows Time-fixed Time-dependent Rate- Ratio 95% CI Rate- Ratio 95% CI 15-day day day day day Nasal CS in asthma Study Adams (JACI 2002): Time-based cohort = Asthma ER visit = Nasal corticosteroid Rx Oct 91 Sept 94 Calendar time 6

7 Nasal CS in asthma Study Replication of the Nasal CS Study Adams (JACI 2002): Time-based cohort = Asthma ER visit = Nasal corticosteroid Rx Oct 91 Sept 94 Calendar time 7

8 Replication of the Nasal CS Study Suissa and Ernst, JACI 2005; 115:714-9 Ontario Study: Alternative Design Time zero: Discharge ICS Rx filled Readmission or death ICS user 0 Readmission ICS non-user 0 Ontario Study: Alternative Design Time zero ICS Rx filled Readmission or death ICS user 0 Readmission ICS non-user 0 8

9 GPRD Study Cohort of COPD patients ( ) 3-year follow-up. Outcome = all-cause death. First regular ICS±LABA after cohort entry versus first regular SABA (hierarchical) Intent-to-treat analysis using Cox s proportional hazards model, adjusting for covariates ICS+LABA RR= % reduction in mortality IMMORTAL TIME BIAS SABA 9

10 COPD Diagnosis First immortal time Second immortal time Bronchodilators ICS Rx filled DEATH Immortal time DEATH Replication of GPRD study in COPD IMMORTAL TIME BIAS Suissa, ERJ 2004;23:

11 Kiri et al (2005) Kiri et al (2005) EXCLUDED 2769 IMMORTAL AND UNEXPOSED PATIENTS!!!!! Suissa, AJRCCM 2006; 115:714-9 Kiri Study: Design = death = Inhaled corticosteroid Rx IMMORTAL TIME IMMORTAL TIME Days of follow-up 11

12 Kiri et al (2005) Suissa, AJRCCM 2006; 115:

13 Immeasurable time bias 13

14 RR= % reduction in mortality! Case-control design Hospitalized Case (death) 30 days Prescription filled 30 days Control 14

15 Case-control design Hospitalized (immeasurable time) Case (death) 30 days Prescription filled 30 days Control Cohort design Hospitalized (immeasurable time) Cohort entry Death Prescriptions filled Cohort entry ILLUSTRATION Cohort of 2,049 patients hospitalised for COPD in Saskatchewan ( ) 1313 died during follow-up (cases) matched to 1313 controls Exposure: Inhaled corticosteroid prescription in 30-day period prior to index date Data analysis done 2 ways: irrespective of immeasurable time and accounting for this time 15

16 Cases (deaths) Controls N LOS N LOS All subjects Cases (deaths) Controls N LOS N LOS All subjects ICS prescription (30 days) No ICS prescription 1, immeasurable time Immeasurable time bias Cases Controls Crude RR Adjusted RR (95 % CI) ICS Rx (last 30 days) No 1, Ref Yes

17 Immeasurable time bias Cases Controls Crude RR Adjusted RR (95 % CI) ICS Rx (last 30 days) No 1, Ref Yes Time-adjusted 30-day ICS use Time-window bias 17

18 RR= % reduction in mortality! Case Case Case Prescription filled Prescription filled Control Control Control Start of observation period 18

19 short time window Cases Longer time window Controls Prescription filled ILLUSTRATION Cohort of 365,467 subjects from GPRD aged ( ) 1786 incident cases of lung cancer during follow-up Exposure: The first statin prescription Data analysis done in 3 ways: - Cohort approach with person-time classification - Case-control as in Chest paper - Case-control with sampling of person-moments 19

20 CONCLUSION Observational studies of drug effects important to complement RCTs Drug use varies over time, yet time-dependent analyses often not used Time-related biases (immortal, immeasurable and time-window) explain several observational studies with surprisingly high effectiveness. Rigorous reviews of methods in study design and data analysis are needed when results are surprisingly favorable Suissa and Ernst, JACI 2005; 115:

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