Presentations in this series 1.Introduction 2.Self-matching 3.Proxies 4.Intermediates 5.Instruments 6.Equipoise Avoiding Bias Due to Unmeasured Covariates Alec Walker

TD U

TD U Randomization

TD U Self-matching

Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission Celecoxib, Naproxen and GI Bleeding in the treatment of pain MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB

Confounding by Contraindication High risk for peptic ulcer and bleeding makes treatment with naproxen inadvisable. Celecoxib would be better. No treatment at all is safest. Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB

The physician’s belief, not the true risk, is what affects the choice of therapy. Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB

Celecoxib Ulcer PUB

Celecoxib Ulcer

Celecoxib Ulcer Confounded

Self-Matching Key Celecoxib Naproxen No Therapy Event X X X

Self-Matching Key Celecoxib Naproxen No Therapy Event X X X When there is no event, there is no within-person comparison to be made, if we’re looking at relative risk.

Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB

Matching on person means that all comparisons are within person and therefore at a common level of physician perception. Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB

Celecoxib versus Naproxen versus No Treatment PUB Hospital Admission MD-perceived risk of peptic ulcer & bleeding (PUB) True risk of PUB The time of observation needs to be sufficiently short that true risk and physician perception do not change.

Compare the Exposure at Case Occurrence to Sampled Exposure(s) in the Past

Non-Cases Drop Out of Consideration

Uninformative Time Drops Out as Well Case window Control window

Case and Control Windows  Case window: period preceding the event (GI bleeding) during which the exposure (celecoxib, naproxen, no treatment) may have altered the risk  Control window(s): periods of the same length as, and not overlapping with, the case window that furthermore provide an estimate of the null- hypothesis probability of exposure for each case.  The core study technique is to identify cases, then ascertain exposure status in the case window and at earlier points in time – the control windows.

Estimating the Relative Risk Case Window Control Window Exposed ExposedYesNo Yesf 10 Nof 01  Place each case in the above table, according to exposure in the case window and the control window  Mantel-Haenszel odds ratio for matched sets Reduces to ratio of counts in discordant exposure windows ( f 10 / f 01 ) when there is one control  Conditional logistic regression When there are concurrent time-varying confounders Accommodates many-to-one matching of control and case windows  Concordant case-control windows are uninformative

Pharmacoepidemiology and Drug Safety 2011; 20: 763–771 Risk of hospitalization for upper gastrointestinal adverse events associated with nonsteroidal anti ‐ inflammatory drugs: a nationwide case ‐ crossover study in Taiwan Chia ‐ Hsuin Chang1,2†, Hsi ‐ Chieh Chen1†, Jou ‐ Wei Lin3, Chuei ‐ Wen Kuo4, Wen ‐ Yi Shau5 and Mei ‐ Shu Lai1* 1Institute of Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan 2Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan 3Cardiovascular Center, National Taiwan University Hospital Yun ‐ Lin Branch, Dou ‐ Liou City, Yun ‐ Lin, Taiwan 4National Health Insurance Mediation Committee, Department of Health, Executive Yuan, Taipei, Taiwan 5Division of Health Technology Assessment, Center for Drug Evaluation, Taipei, Taiwan ABSTRACT Purpose This study aimed to evaluate the risks of upper gastrointestinal (GI) adverse events across a variety of oral and parenteral coxibs and nonselective nonsteroidal anti ‐ inflammatory drugs (nsNSAIDs) in the general population of Taiwan. Methods In a case ‐ crossover study, all patients aged ≥20 years who were hospitalized for upper GI adverse events (peptic ulcer and bleeding; gastritis and duodenitis) in 2006 were identified using the International Classification of Diseases, 9th Revision, Clinical Modification diagnosis codes from inpatient claims from the Taiwan National Health Insurance Database. For each patient, the case period was defined as 1–30 days and the control period as 31–60 days before the date of hospitalization. Outpatient pharmacy prescription database was searched for individual NSAID use during the case and control periods. A conditional logistic regression model was applied, and adjusted self ‐ matched odds ratios (OR) and their 95% confidence intervals (95%CI) were reported. Results A total of patients hospitalized for upper GI adverse events were included. The adjusted OR was 1.52 (95%CI: 1.27–1.82) for celecoxib and 2.56 (95%CI: 2.44–2.69) for oral nsNSAIDs. The ORs were above 2 for oral piroxicam, diclofenac, ketorolac, ketoprofen, acemetacin, and naproxen and were around 1.5 for tiaprofenic acid, indomethacin, mefenamic acid, and ibuprofen. Higher risks were evident for parenteral NSAIDs, in particular ketorolac with an OR of 5.76 (95%CI: 5.14–6.44). Conclusion Use of celecoxib and all nsNSAIDs studied was associated with a greater risk of upper GI toxicity as compared with nonuse. Parenteral NSAIDs posed a higher risk, but celecoxib, ibuprofen, and mefenamic acid posed a lower risk than other NSAIDs. Purpose This study aimed to evaluate risks of upper gastrointestinal (GI) adverse events across a variety of oral and parenteral coxibs and nonselective nonsteroidal anti ‐ inflammatory drugs (nsNSAIDs) in the general population of Taiwan. Methods In a case ‐ crossover study, all patients aged ≥20 years who were hospitalized for upper GI adverse events (peptic ulcer and bleeding; gastritis and duodenitis) in 2006 were identified... For each patient, the case period was defined as 1–30 days and the control period as 31–60 days before the date of hospitalization. Outpatient pharmacy prescription database was searched for individual NSAID use during the case and control periods. A conditional logistic regression model was applied... Results A total of patients hospitalized for upper GI adverse events were included. The adjusted OR was 1.52 (95%CI: 1.27–1.82) for celecoxib and 2.56 (95%CI: 2.44–2.69) for oral nsNSAIDs… Conclusion Use of celecoxib and all nsNSAIDs studied was associated with a greater risk of upper GI toxicity as compared with nonuse…

Case Window Control Window Exposed ExposedYesNo Yesf 10 Nof 01 Pharmacoepidemiology and Drug Safety 2011; 20: 763–771

Case Window Control Window Exposed ExposedYesNo Yes413 Nof 01 Pharmacoepidemiology and Drug Safety 2011; 20: 763–771

Case Window Control Window Exposed ExposedYesNo Yes413 No232 Pharmacoepidemiology and Drug Safety 2011; 20: 763–771

Case Window Control Window Exposed ExposedYesNo Yes413 No232 RR crude = 413/232 = 1.78 Pharmacoepidemiology and Drug Safety 2011; 20: 763–771

*Conditional logistic regression adjusted for important potential time ‐ varying confounding variables including selective serotonin reuptake inhibitors, other antidepressants, calcium channel blockers, nitrates, systemic corticosteroids, low ‐ dose aspirin, proton pump inhibitors, histamine 2 receptor blockers, and sucralfate.

 Self-matched studies compare exposure at the time of an outcome event to the probability of exposure in the same person Calculated from the individuals own history Assuming the null hypothesis of no effect of exposure on the risk of outcome.  Unmeasured covariates that do not vary over time within person do not confound the estimate of relative risk.  Self-matched studies work well for intermittent exposures whose associated risks rise and fall quickly  Self-matched studies give mathematical meaning to the question you might well hear from your doctor: “Were you doing anything unusual just before you got sick?”

Presentations in this series 1.Overview and Randomization 2.Self-matching 3.Proxies 4.Intermediates 5.Instruments Avoiding Bias Due to Unmeasured Covariates Alec Walker