Prescription opioid use and mortality in adults from a community sample

(REGARDS Study)

Yulia Khodneva1, Paul Muntner2, Stefan Kertesz1, Monika M. Safford1

1Division of Preventive Medicine, Department of Medicine, 2Department of Epidemiology, School of Public Health, UAB

Supported by NHLBI R01 HL080477; KL2 RR025776; NINDS/NIH U01- NS041588

Background• Opioid analgesics are increasingly commonly used in the US to

treat acute and chronic non-cancer pain. An estimated 6-20% of US community-dwelling adults aged >18 now report therapeutic use of opioids.

• Previous research: increased mortality related to overdose and/or abuse of prescription opioids has been reported. These effects of opioids may be more harmful for women.

• Population-based studies: have not examined the relationship between therapeutic prescription opioid use and mortality using sample characteristic balancing techniques such as propensity score matching.

Objectives1. To examine the association of prescription

opiate use with a. All-cause mortalityb. Specific causes of death

2. To examine sex differences

Methods• REasons for Geographic And Racial Differences in Stroke

(REGARDS) Study• National prospective longitudinal cohort N=30,239

– Age > 45– Over sampling:

• Stroke Belt (Southeast) • Blacks (42%)

– Recruited 2003-7• Baseline data:

– Phone interview – In-home study visit

• Follow-up: – Telephone call every 6 months– Expert adjudication of endpoints based on medical records

WhiteAfrican American

N = 30,239

REGARDS Participants

Exposure: Prescription Opioid Use

• Any use of prescription opioids ascertained by pill bottle review during the in-home study visit

Outcomes• All-cause mortality

• Specific Causes of Deaths: – Cardiovascular disease (CVD) (MI, stroke, heart failure, or other CVD)

– Sudden death– Cancer – Chronic obstructive pulmonary disease (COPD)– Infections– Accidents, suicide, homicide

– Expert adjudicated using medical records, death certificates, proxy interviews, autopsy report, National Death Index

Analysis• Propensity for prescription opioid use (POU)

– Logistic regression using 56 noncollinear baseline characteristics

• Multiple Imputation of missing data on baseline characteristics– Using chained equations in 30 datasets in STATA 12

• Cox proportional hazard regression models of risk of death stratified by sex – Participants with POU matched with participants without POU within

quintiles of propensity score– Sensitivity analysis using 1:1 matching

Variables included in calculation of propensity score indicating probability of opioid prescription at baseline Age Number of heart attacksRace Number of stroke symptomsSexRegion of residence

History of transient ischemic attackHeart failure symptoms

Education Chronic pulmonary diseaseIncome History of pulmonary embolismMarital status Pacemaker usePhysical activity Leg amputationsSmoking (pack-years) Gum diseaseBody Mass Index History of deep venous thrombosisDiabetes History of fallsSystolic blood pressure Cognitive functioningTotal cholesterol Past year use of antibioticshsC-Reactive protein Insulin useUrinary albumin-to-creatinine ratio Use of estrogen replacement therapyAtrial Fibrillation HemoglobinCoronary Heart Disease White blood cell countCVD (stroke, PAD, AA) Platelet countQT corrected interval from EKG data Diastolic blood pressureStatin Use Health insuranceAntihypertensive medication use Alcohol use (mean number of drinks per week)Aspirin use Social networkNSAID use Caregiver statusDepressive Symptoms Perceived stressChronic pain Mental Component of SF-12 scalePhysical Component of SF-12 scale Medication adherence (Morisky score)Adherence to Mediterranean diet Awareness of antihypertensive medication needTriglycerides Awareness of lipid-lowering medication need

Results• Final analytic sample 29,025• 3060 deaths through December 31, 2011• Mean follow-up: 5.6 ± 2.0 years

Total REGARDS participants N=30239

Missing pill bottle review, n=69

Initial cohort N=29670

Missing follow up n=569

Analytic Cohort N=29025

Propoxyphene users, n=576

Prescription Opioid Use in REGARDS• 1,907 (6.6%)* used prescription opioids at baseline

– Among them - 93.9 % had a prescription for opioids

* 569 propoxyphene users are excluded

Baseline Characteristics of POUsers POUser,

n=1,907Not a user, n=27,118

Age, years, mean, (SD) 63.9 (9.3) 64.9(9.4)Female, % 64.3 54.1African American, % 44.8 40.8Education < high school, % 18.4 11.8Annual income < $35,000, % 55.2 40.9 Smoking (pack-years), mean, (SD) 17.1(25.2) 13.2(22.8)Never exercises, % 47.9 33.1Diabetes, % 30.4 21.3Coronary Heart Disease,% 22.5 17.0Baseline stroke, PAD or aortic aneurism,% 13.3 8.5 Depressive symptoms (CES-D=>4), % 24.4 9.9Pain (moderate to severe), % 59.5 19.4SF-12 Mental Component, mean, (SD) 50.4(11.3) 54.4(8.1)SF-12 Physical Component, mean, (SD) 35.9(11.9) 47.3(9.9)Fall in the past year, % 28.4 15.2

p-values for all comparisons < .0001

Baseline Characteristics in the middle Quintile of propensity to use prescription opioids

POUser,n=196

Not a user, n=5,609

P-value

Age, years, mean, (SD) 65.5(9.8) 64.4(9.6) 0.12Female, % 55.1 58.6 0.33African American, % 43.4 40.7 0.46Education < high school, % 12.2 11.7 0.08Annual income < $35,000, % 50.6 50.5 0.97 Smoking(pack-years), mean (SD) 12.8(20.8) 13.5(22.6) 0.66Never exercises, % 36.8 32.5 0.21Diabetes, % 24.0 20.9 0.30Coronary Heart Disease,% 16.3 15.2 0.68Baseline stroke, PAD or aortic aneurism,% 8.7 6.8 0.31 Depressive symptoms (CES-D=>4), % 10.4 7.5 0.14Pain (moderate to severe), % 3.1 3.2 0.89SF-12 Mental Component, mean, (SD) 55.0(8.1) 54.9(7.3) 0.93SF-12 Physical Component, mean, (SD) 49.7(5.2) 50.0(5.2) 0.54Fall in the past year, % 15.8 13.8 0.42

Deaths, n HR (95% CI)

POU Non-Users

All Cause Mortality

Women 175 1024 1.37 (1.16 1.62)

Men 125 1736 1.01 (0.84 1.22)

CVDWomen 85 445 1.53 (1.20 1.95)

Men 40 749 0.77 (0.55 1.06)

Sudden Death

Women 24 115 1.76 (1.11 2.81)

Men 10 228 0.63 (0.33 1.21)

Women 42 355 1.28 (0.91 1.79)

Cancer Men 41 582 1.16 (0.83 1.61)

Women 14 71 1.08 (0.60 1.95)

COPD Men 13 99 1.38 (0.76 2.50)

Women 17 136 0.92 (0.55 1.55)

Infection Men 24 214 1.62 (1.04 2.52)

Accidents/Suicide

Women 11 43 2.35 (1.15 4.78)

Men 6 78 1.44 (0.61 3.42)

Sex-stratified hazard ratio of death estimated for POUsers vs. non-users matched by propensity score quintiles

Conclusions• Therapeutic POU may be independently associated with

increased mortality among women, but not men

• The higher risk of death in women was primarily attributable to cardiovascular, sudden death and accidents

• Importantly, there was no significantly elevated risk for other causes of death, and there were no sex differences in the association of POU and other causes of death like cancer or COPD

Limitations• Potential of residual confounding by indication even after

propensity score matching• No information on baseline musculoskeletal conditions• Information on dose and duration of opioid use not available• Data in some covariates (health behaviors, depression) self-

reported• Limited information on diversion or misuse

Implications

• Concerns about the safety of prescription opioid use for non-cancer pain among women. – Especially for cardiovascular disease mortality and sudden

death.

Additional analyses

Two methods of opioid propensity score matched analysis Hazard Ratios of Death for POU

1:1 Matched Matched within quintilesHR (95% CI) HR (95% CI)

All Cause Mortality

Women 1.21 (0.99 1.48) 1.37 (1.16 1.62)

Men 0.91 (0.72 1.14) 1.01 (0.84 1.22)

CVDWomen 1.53 (1.08 2.17) 1.53 (1.20 1.95)

Men 0.70 (0.46 1.05) 0.77 (0.55 1.06)

Sudden Death

Women 2.41 (1.10 5.29) 1.76 (1.11 2.81)

Men 0.64 (0.26 1.55) 0.63 (0.33 1.21)

Women 1.25 (0.79 1.99) 1.28 (0.91 1.79)

Cancer Men 0.85 (0.54 1.35) 1.16 (0.83 1.61)

Women 0.52 (0.27 1.03) 1.08 (0.60 1.95)

COPD Men 1.24 (0.54 2.87) 1.38 (0.76 2.50)

Women 0.75 (0.40 1.40) 0.92 (0.55 1.55)

Infection Men 1.14 (0.63 2.08) 1.62 (1.04 2.52)

Accidents/Suicide

Women 2.83 (0.91 8.84) 2.35 (1.15 4.78)

Men 1.72 (0.41 7.24) 1.44 (0.61 3.42)