1. Evaluating Different Physician’s Prescribing Preference Based Instrumental Variables in the Study of Beta2-Agonist Use and the Risk of Acute Myocardial Infarction
Md Jamal Uddin, RHH Groenwold, A de Boer, ASM Afonso, P Primatesta, C Becker, SV Belitser, AW Hoes, KCB Roes, OH Klungel
Division of Pharmacoepidemiology and Clinical Pharmacology
University of Utrecht, Netherlands

2. Disclosures
Acknowledgements: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/ ) for the Innovative Medicine Initiative ( under Grant Agreement n° The research leading to these results was conducted as part of the PROTECT consortium (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium, which is a public-private partnership coordinated by the European Medicines Agency.
Conflicts of interest: “Olaf Klungel had received unrestricted funding for pharmacoepidemiological research from the Dutch private-public funded Top Institute Pharma.”

3. Background
Instrumental variable (IV) analysis with physician’s prescribing preference (PPP) as an IV has been used to control for unmeasured confounding
PPP can be defined in several ways, but it is unclear how different definitions of PPPs perform across databases
We aimed to assess the performance of PPPs in a study of long-acting beta2-agonist (LABA) use and myocardial infarction (MI)

4. Methods Database Mondriaan, Netherlands (N=1.4 M) CPRD, UK (N=5 M)
Study Population
Adult patients with a diagnosis of asthma and/or COPD
At least one prescription of inhaled beta2-agonists or inhaled muscarinic antagonists (new users)
Cohorts
COPD, Asthma, COPD & Asthma, Combined

5. Exposure:
Time-fixed: LABA vs. Non-LABA (first prescription)
Time-varying: Current LABA users vs. all other users (Non-LABA, Past and recent LABA)
Outcome:
Myocardial Infarction (MI)
Data were analysed using conventional method and the IV methods

6. Characteristics of study population
CPRD
Mondriaan
Cohort size
490,499
27,459
Number of MI cases
5,739
447
LABA users
15%
29%
Follow-up period
Median follow-up time (years)
4.58
3.50
Mean age of patients (years) 51 52

7. Exposure Time-varying
Definition of Instrumental Variables
Exposure Time-fixed
Exposure Time-varying

8. Definition of Instrumental Variables
Exposure: Time-fixed
Physician’s prescribing preference with previous
single prescription (PPP1)
5 prescriptions (PPP5)
10 prescriptions (PPP10)
Proportion of LABA prescriptions (PLP)
Exposure: Time-Varying
Proportions of time for current LABA use (PTL) in a practice

9. MI Assessment of IV assumptions Instrumental variables LABA vs.
Non-LABA
Correlation, Odds Ratio MI
Standardized Difference
Ref: Brookhart et al. 2006, Epidemiology

10. Results

11. Violation (X) of Assumptions of Instrumental Variables
Assumption-I IV is associated with exposure
Assumption-II is independent of confounders

13. Neither of the IVs we considered appears to be valid, hence, the HRs were invalid

14. Key Findings
For time-fixed LABA exposure, the IV PPP10 outperformed the other IVs regarding strength of the IV and balance of confounders between IV categories
None of the IVs we considered appeared valid for time- varying LABA exposure, hence estimates were not valid
CPRD included approximately 18 times more subjects than Mondriaan, and thus IVs estimates appeared more precise

15. Conclusions
The apparent validity of IV analysis using PPP strongly depends on how this IV is defined and in which database it is applied
We recommend to consider several plausible IVs, assess their validity, and only proceed with the IV analysis with apparently valid IV(s)

16. Thank You!!!