The Healthy User Effect: Ubiquitous and Uncontrollable S. R. Majumdar, MD MPH FRCPC FACP

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The Healthy User Effect: Ubiquitous and Uncontrollable S. R. Majumdar, MD MPH FRCPC FACP Professor of Medicine, Endowed Chair in Patient Health Management, Health Scholar of the Alberta Heritage Foundation, Faculties of Medicine and Dentistry and Pharmacy and Pharmaceutical Sciences and School of Public Health, University of Alberta, Edmonton, AB, Canada

Take Home Messages Non-randomized studies reporting unanticipated benefits of treatment should be interpreted with great caution Confounding by the healthy-user effect is ubiquitous and often a better or alternate explanation for unanticipated benefits The healthy-user effect probably cannot be controlled without randomized trials (or very rich clinical data)

Interchangeable Terms Capturing the Same Construct Healthy user effect Healthy user bias Healthy adherer effect Compliance bias Healthy vaccinnee effect?frailty bias?(physician) selection bias etc

Statin Effectiveness in Two 70-Year Old Men 6-Months After ICD9-410x Doesn t take a statin Asks for and gets statin Doesn t fill any new Rx Sort of takes old meds Keeps smoking Gains weight Doesn t get labs done Doesn t see family doc Doesn t get flu jab Referred to me Fills all new Rx >80% pill adherence Stop smoking Loses weight All labs done Sees family doc q2m Gets flu (and other) jabs Referred to cardiologist

The Healthy-User Effect The healthy-user tends to have: less severe disease (for any given ICD-code) higher socio-economic status better functional, cognitive, health status better habits re: diet, alcohol, smoking, exercise greater inclination to screening (mammography, FOBT) and prevention (MD visits, immunization) more motivation and health consciousness greater adherence to meds and other MD advice (Ray. Arch Intern Med. 2002; Brookhart. Am J Epi. 2007; Eurich, Majumdar. JGIM. 2012)

Percent Alive Good Adherence to Advice about Self Monitoring of Blood Glucose 100 99 SMBG No Tests Incident cohort of 3268 patients with type 2 DM (ROSSO) 98 SMBG defined as 1-year of testing 97 96 95 Adjusted HR = 0.6 (p=0.035) 1 2 3 4 5 years Extensive direct adjustment Result independent of glycemic control (Martin et al. Diabetologia. 2006;49:271)

Increased Likelihood (%) Good Adherence to Meds Increases Likelihood of Good Adherence to Preventive Measures 60 50 40 30 20 10 0 BMD Flu Jab SM FOBT PPV Jab PSA (Brookhart et al. Am J Epi. 2007;166:348 and related Preventive Services Index recently developed by Williams et al. Prev Chronic Dz. 2010;7:110)

Good Adherence to Placebo Odds ratio (95% CI) Coronary Drug Project Research Group 1980 w1 β blocker heart attack trial (men) 1990 w2 β blocker heart attack trial (women) 1993 w3 Canadian amiodarone myocardial infarction arrhythmia trial 1999 w8 Cardiac arrhythmia suppression trial 1996 w4 Physicians health study 1990 w16 West of Scotland prevention study 1997 w17 University Group Diabetes Project 1970 w22 1971 w18 Total events: 581 (good adherence), 415 (poor adherence) Test for heterogeneity: χ 2 = 14 (P = 0.05) with I 2 = 51% Test for overall effect: Z = 4 (P < 0.001) Good adherence 0.6 (0.4-0.7) Poor adherence (Simpson SH et al. BMJ. 2006;333:15-9)

Pleiotropic Benefits of Good Adherence to Common Meds in Cohort Studies Post-menopausal hormone therapy Reduce hip fractures Reduce gallstone-related disease Prevent sepsis and infection-related death Prevent dementia Delay onset and progression of diabetes Decrease colorectal cancer incidence Statins Reduce hip fractures Reduce gallstone-related disease Prevent sepsis and infection-related death Prevent dementia Delay onset and progression of diabetes Decrease colorectal cancer incidence

Good Adherence to Statins Outcomes of Interest Intended Effects Adjusted HR 95% CI P-value Myocardial infarction 0.72 0.67-0.78 <0.001 Emergency admission 0.87 0.85-0.89 <0.001 Implausible Associations Drug addiction 0.73 0.65-0.83 <0.001 Car accidents 0.75 0.72-0.79 <0.001 Poisoning 0.86 0.78-0.94 <0.001 Gout 0.89 0.85-0.89 <0.001 (Dormuth et al. Circulation. 2009;119:2051)

Normal function, cognition Better Adherence Better Healthy- More prevention diet and User - meds (HRT, vits, statin) lifestyle - screening (BMD, cancer) - immunizations (flu jab) Better Outcomes

Hip Fractures (per 1000 py) BMD Testing and Hip Fractures 35 30 25 20 15 10 Adjusted OR = 0.6 (95%CI 0.4-0.9) BMD NO BMD Elderly CHS cohort ~3100 with 6 yrs follow-up BMD offered to some patients by investigators (~20% not offered) Direct and PS adjustment using rich clinical data 5 0 All <74 75-84 >85 yr Results independent of starting osteo- meds (Kern et al. Ann Intern Med. 2005;142:173)

BMD Testing and Hip Fractures Differences in Rarely Captured Data Characteristics BMD test NO test P-value College education 47% 29% <0.001 Income > 25k per year 47% 40% 0.001 Good or better health status 44% 40% 0.02 Physical activity (kcal/wk) 820 716 0.001 Normal cognition 91% 86% <0.001 Multivitamins 14% 8% <0.001 Calcium supplements 9% 5% <0.001 (Kern et al. Ann Intern Med. 2005;142:173)

Effect of BMD Testing on Hip Fractures in ~ 70,000 Canadian Women over 10-years In the last 2-years Adjusted HR Hip Fracture 95% CIs P-value Screening BMD 0.90 0.8-1.0 0.05 Screening Mammogram 0.88 0.77-0.99 0.04 Flu Jab 0.78 0.68-0.91 <0.001 (Majumdar et al, preliminary data, unpublished [2013])

Physician Selection Bias Normal function, cognition Better Adherence Better Healthy- More prevention diet and User - meds (HRT, vits, statin) lifestyle - screening (BMD, cancer) - immunizations (flu jab) Better Outcomes

In summary (i) 1. Adherence central to the healthy-user effect 2. Any measure of adherence captures many unmeasured health behaviors and patients destined to have better outcomes 3. To the degree that physicians are good at selecting which patients are healthier and more likely to adhere to their advice the healthy-user effect might be at play

Universal Flu Vaccine for the Elderly Every year, massive flu vaccination efforts are undertaken in the fall and winter Efforts are not intended to prevent influenza transmission per se, rather intended to prevent winter-time hospitalizations and deaths Therefore, vaccination efforts directed at those at highest risk the elderly (65-70 years and older) This leads to $70 savings per person vaccinated and $800 savings per life year gained each year

Event Rates (%) Meta-Analysis of All Randomized Trials of Flu Vaccine Effectiveness in Older Adults One High Quality RCT (n=1838) 12 10 RR = 0.50 RR = 0.69 (0.35-0.61) (0.50-0.87) Flu Jab Placebo 8 6 4 2 RR = 1.97 (0.49-7.84) 0 Serology Clinical Dz Death (Govaert et al. JAMA. 1994;272:1661)

Event Rates (%) Benefits of Flu Jab in the Elderly One High Quality RCT Subgroup (n=544) 12 10 RR = 0.77 RR = 0.90 (0.39-1.51) (0.46-1.79) Flu Jab Placebo 8 6 4 RR = 1.94 (0.49-7.66) 2 0 Serology Clinical Dz Death (Govaert et al. JAMA. 1994;272:1661)

Meta-Analysis of All Non-Randomized Studies of Flu Vaccine Effectiveness 42% RRR (Jefferson et al. Lancet. 2007;370:1199 and replicated in definitive cohort study [n=18 cohorts, 700k person-years] by Nichol et al. N Engl J Med. 2007;357:1373)

Event Rates (%) Pleiotropic Benefits of Flu Vaccine 5 4 3 Vaccinated Not Vaccinated aor 0.77, NNT 145, p<0.001 2 aor 0.80, aor 0.81, aor 0.84, NNT 556, NNT 585, NNT 893, p=0.001 p=0.002 p=0.018 1 0 IHD HF Stroke Any Event (Nichol et al. N Engl J Med. 2003;348:1322)

Vaccination Rates in the Elderly Have Increased Four-Fold Since 1980 Pneumonia All-Cause Mortality 1970 1980 1990 2000 1970 1980 1990 2000 (Simonsen et al. Arch Int Med. 2005;165:265)

In summary (ii) 1. Flu vaccine has small to absent clinical benefit in randomized trials 2. Stable or increasing pneumonia and death rates in the elderly in the face of 400% increases in vaccine coverage 3. But flu vaccine has a huge benefit in every cohort ever studied and published (until recently)

Design of Most Cohort Studies of Flu Vaccine Effectiveness? Population-based samples of community dwelling elderly Exposure = flu vaccination Outcome = all-cause mortality Administrative or claims type data, risk adjustment based on ICD codes X Little info re: healthy-vaccinnee effects (smoking, function, meds, adherence) X Analysis restricted to influenza season

Flu Jab Benefit (RR) Analyses restricted to flu season since no expected benefit when no flu present 1.2 1 0.8 0.6 0.4 0.2 Expected Benefit 0 Late Spring Early Fall Later Fall WINTER Early Spring Late Spring (Simonsen et al. Lancet. 2007;7:658)

Alternate Study Design for Examining Flu Vaccine Benefits Population-based samples of community dwelling elderly Exposure = flu vaccination Outcome = all-cause mortality Administrative or claims type data, risk adjustment based on ICD codes Rich info re: healthy-vaccinnee effects (smoking, function, meds, adherence) Analysis restricted to the off-season

Flu Jab Benefit (RR) Analyses restricted to offseason since no expected benefit when no flu present 1.2 1 0.8 0.6 0.4 0.2 0 Late Spring Early Fall Later Fall WINTER Early Spring Late Spring (Simonsen et al. Lancet. 2007;7:658)

Analytic Approach Using A Population- Based Clinical Registry Excluded patients with pneumonia admitted during the influenza season(s) Created propensity (to be vaccinated) score using 36 variables c-statistic = 0.91 1:1 propensity score matched and covariatebalanced every flu vaccine recipient with an unvaccinated control Multivariable logistic regression

Flu Jabs in ~3500 Patients With Pneumonia Differences in Rarely Captured Data Characteristics Flu Jabs NO Jabs P-value More than 5 regular meds 23% 14% <0.001 Statin user 35% 25% <0.001 Former smoker 42% 30% <0.001 Independent in mobility 97% 92% 0.02 Advanced directive in place 18% 9% <0.001 Etcetera - - -

Receipt of Flu Vaccine (%) Receipt of Flu Vaccine According to Quintiles of Propensity Score 50 40 30 20 10 0 I II III IV V Propensity Score Quintiles p<0.001 for trend

Events (%) Adverse Events in the Spring and Summer, According to Flu Vaccination Status 50 45 40 35 30 25 20 15 10 5 0 OR 0.49 OR 0.08 OR 0.33 p=0.004 p<0.001 p<0.001 8 15 1 10 Death ICU Admission Death or ICU 9 Vaccinated Not Vaccinated 23 (Eurich et al. Am J Resp Crit Care Med. 2008;178:527)

Sequential Adjustment For Correlates of the Healthy-Vaccinnee Effect All-cause mortality pleiotropic benefits (Eurich et al. Am J Resp Crit Care Med. 2008;178:527)

Pleiotropic Benefits or Refractory Confounding? Fully Adjusted OR (95%CI) p-value Death 0.81 (0.35-1.85) 0.6 ICU Admission 0.17 (0.04-0.71) 0.014 Death or ICU 0.50 (0.25-1.00) 0.05 (Eurich et al. Am J Resp Crit Care Med. 2008;178:527)

In summary (iii) 1. There is no plausible mechanism for benefits of flu vaccine in absence of flu 2. Suggests that the mortality benefit of flu vaccine in the elderly in prior studies vastly and systematically over-estimated 3. More broadly, even with rich clinical data it is difficult if not impossible to control for presence of the healthy-user effect

Conclusions Non-randomized studies reporting unanticipated benefits of treatment should be interpreted with great caution Confounding by the healthy-user effect is ubiquitous and often a better or alternate explanation for unanticipated benefits The healthy-user effect probably cannot be controlled without randomized trials (or very rich clinical data)

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