Literature DB >> 31825502

Health Outcomes Among Long-term Opioid Users With Testosterone Prescription in the Veterans Health Administration.

Guneet K Jasuja1,2, Omid Ameli2,3, Joel I Reisman1, Adam J Rose4, Donald R Miller1, Dan R Berlowitz1, Shalender Bhasin5.   

Abstract

Importance: Androgen deficiency is common among male opioid users, and opioid use has emerged as a common antecedent of testosterone treatment. The long-term health outcomes associated with testosterone therapy remain unknown, however. Objective: To compare health outcomes between long-term opioid users with testosterone deficiency who filled testosterone prescriptions and those with the same condition but who did not receive testosterone treatment. Design, Setting, and Participants: This cohort study focused on men in the care of the Veterans Health Administration (VHA) facilities throughout the United States from October 1, 2008, to September 30, 2014. It included male veterans who were long-term opioid users, had low testosterone levels (<300 ng/dL), and received either a testosterone prescription or any other prescription. It excluded male patients with HIV infection, gender dysphoria, or prostate cancer and those who received testosterone in fiscal year 2008. Data were analyzed from April 1, 2017, to April 30, 2019. Exposure: Prescription for testosterone. Main Outcomes and Measures: All-cause mortality and incidence of major adverse cardiovascular events (MACE), vertebral or femoral fractures, and anemia during the 6-year follow-up through September 30, 2015.
Results: After exclusions, 21 272 long-term opioid users (mean [SD] age, 53 [10] years; n = 16 689 [78.5%] white) with low total or free testosterone levels were included for analysis, of whom 14 121 (66.4%) received testosterone and 7151 (33.6%) did not. At baseline, compared with opioid users who did not receive testosterone, long-term opioid users who received testosterone treatment were more likely to have obesity (43.7% vs 49.0%; P < .001), hyperlipidemia (43.0% vs 48.8%; P < .001), and hypertension (53.9% vs 55.2%; P = .07) but had lower prevalence of coronary artery disease (15.9% vs 12.9%; P < .001) and stroke (2.4% vs 1.3%; P < .001). After adjusting for covariates, opioid users who received testosterone had significantly lower all-cause mortality (hazard ratio [HR] = 0.51; 95% CI, 0.42-0.61) and lower incidence of MACE (HR = 0.58; 95% CI, 0.51-0.67), femoral or hip fractures (HR = 0.68; 95% CI, 0.48-0.96), and anemia (HR = 0.73; 95% CI, 0.68-0.79) during the follow-up period of up to 6 years, compared with their counterparts without a testosterone prescription. In covariate-adjusted models, men who received opioids plus testosterone were more likely to have resolved anemia compared with those who received opioids only during the 6-year follow-up (HR = 1.16; 95% CI, 1.02-1.31). Similar results were obtained in propensity score-matched models and when analyses were restricted to opioid users with noncancer pain or those who did not receive glucocorticoids. Conclusions and Relevance: This study found that, in the VHA system, male long-term opioid users with testosterone deficiency who were treated with opioid and testosterone medications had significantly lower all-cause mortality and significantly lower incidence of MACE, femoral or hip fractures, and anemia after a multiyear follow-up. These results warrant confirmation through a randomized clinical trial to ascertain the efficacy of testosterone in improving health outcomes for opioid users with androgen deficiency.

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Year:  2019        PMID: 31825502      PMCID: PMC6991198          DOI: 10.1001/jamanetworkopen.2019.17141

Source DB:  PubMed          Journal:  JAMA Netw Open        ISSN: 2574-3805


Introduction

Opioid use in the United States has reached epidemic proportions.[1] Although deaths from opioid overdose[2,3] have captured the world’s attention, the endocrine complications of chronic opioid use have remained underappreciated. All opioid medications, especially long-acting opioids, suppress testosterone levels, often into the severely hypogonadal range.[4,5] Prescription opioid use has been shown to have an association with testosterone deficiency; nearly 20% of testosterone prescriptions written in the Veterans Health Administration (VHA) system were for men who were opioid users.[6] Testosterone deficiency among opioid users is associated with increased risk of sexual dysfunction, osteoporosis, and bone fractures.[7] However, to our knowledge, no data exist on major health outcomes in opioid users who are hypogonadal and either receive or do not receive testosterone treatment. Testosterone treatment of men with hypogonadism is associated with improved sexual desire, erections, and sexual activity[8,9]; self-reported mobility[10,11,12]; volumetric bone density and estimated bone strength[13,14]; and corrected anemia.[15] However, the long-term association of testosterone treatment with major adverse cardiovascular events (MACE), mortality, and bone fractures remains unknown.[16,17,18,19,20,21,22,23] Little is known about the effects of testosterone treatment on health outcomes in men with opioid-induced androgen deficiency (OPIAD), who often experience marked suppression of testosterone levels. One short-term randomized clinical trial reported improvements in pain sensitivity, sexual desire, and body composition with testosterone treatment in men with OPIAD.[24] However, the long-term implications of testosterone treatment for major health outcomes in opioid users are unknown to date. Patients who receive opioids experience more severe testosterone deficiency, often have multiple comorbid conditions, use multiple prescription drugs, and are at increased risk of mortality,[25] which could influence the benefit to risk ratio of testosterone treatment. In the absence of a long-term randomized clinical trial of testosterone in men with OPIAD, we compared major health outcomes in male long-term opioid users who received testosterone treatment with those who did not receive testosterone. We selected health outcomes, including overall mortality, MACE, fractures (vertebral, femoral, and hip), and incident anemia, that have public health importance and could be ascertained with accuracy. Most randomized testosterone trials[14] have been conducted in men with mild testosterone deficiency. Because opioid use is typically associated with moderate to severe testosterone deficiency, a study of men with OPIAD offers an opportunity to elucidate the association between testosterone treatment and health outcomes among opioid users with moderate to severe testosterone deficiency. Recognizing the limitations of observational studies, we performed propensity matching and several sensitivity analyses to assess the potential effect of confounding owing to observed and unobserved differences between groups.

Methods

Study Design and Participants

This nationwide cohort study included men who received prescriptions within the VHA system from October 1, 2008, to September 30, 2014, and were followed up through September 30, 2015. The institutional review board of Bedford VHA Medical Center approved the study and waived the need for informed consent because deidentified data were used. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. For primary analyses, we selected male veterans who were long-term opioid users, had testosterone deficiency, and received either a testosterone prescription (testosterone recipients) or any other prescription (nonrecipients of testosterone) in each of the 2 or more years after filling an opioid prescription. Opioids and their morphine equivalents are listed in eTable 1 in the Supplement. We focused on long-term opioid users, defined as those who received 120 or more days’ supply of opioids during at least 1 continuous 180-day interval[26] in 2 or more years as indicated by prescription fills. To identify opioid users with testosterone deficiency, we selected those with testosterone levels measured before they received a testosterone prescription. Those with a low total testosterone level (<300 ng/dL; to convert to nanomoles per liter, multiply by 0.0347) or free testosterone level (<70 pg/mL) were included. These cutoff points for testosterone levels were consistent with thresholds in guidelines available at that time and with published reference ranges.[27,28] We excluded, among others, those with HIV infection, gender dysphoria, and prostate cancer and those who received testosterone in fiscal year (FY) 2008 because these individuals could have been using testosterone before receiving an opioid prescription.

Exposure and Outcome Intervals

For patients who received testosterone prescriptions, the earliest testosterone prescription fill between FY 2009 and 2014 was used as the index fill. For patients who did not receive testosterone prescriptions, a fill from FY 2009 to 2012 was chosen at random as the index fill in order to match the time distribution of testosterone fills. To avoid the immortal person time bias,[29] the exposure interval for testosterone recipients was calculated as the interval between the date of their first testosterone prescription and a date 3 months after their last testosterone fill. For nonrecipients of testosterone, the duration of exposure was calculated as the interval between the date of their most recent testosterone-level check preceding their index date and a date 3 months after their last opioid prescription. This definition of exposure period ensured that patients were actively in care at least at the start and end of the period and had sufficient care within the VHA system to be included in the present study cohort. The outcome period started at the beginning of the specific exposure period for both recipients and nonrecipients of testosterone.

Outcomes and Covariates

We selected all-cause mortality and first occurrence of MACE as the primary outcomes of the study and vertebral, femoral, or hip fractures and anemia as the secondary outcomes. These outcomes were selected because they are clinically important and can be ascertained with a high level of accuracy. The date of death was extracted from the VHA Vital Status File, which is compiled by merging data from multiple sources to create a single date of death.[30] Major adverse cardiovascular events included myocardial infarction, ischemic stroke, or death (defined with the International Classification of Diseases, Ninth Revision, Clinical Modification, [ICD-9-CM] codes [eTable 2 in the Supplement]). Vertebral, femoral, or hip fractures were identified using ICD-9-CM diagnosis codes in both outpatient and inpatient data from the VHA Corporate Data Warehouse (CDW) (eTable 2 in the Supplement). Anemia was defined as hemoglobin level less than 12 g/dL (to convert to grams per liter, multiply by 10.0) or a hematocrit reading less than 36%[31]; the measurement closest to the index fill was used as the baseline level. For anemia analyses, patients were required to have both baseline and follow-up hemoglobin or hematocrit values. We separately analyzed the resolution of anemia among those who had anemia at baseline (n = 1567) and the development of anemia among those who did not have anemia at baseline (n = 17 355). We adjusted covariate-adjusted and propensity score–matched models for sociodemographic variables, including age, marital status, copayment, race/ethnicity, and poverty level in residential zip code. We also adjusted for a number of physical and mental comorbidities and specific medications (eTable 1 in the Supplement) using data from the VHA CDW. A 1-year look-back period was used to check for comorbidities and medications that occurred before the date of index prescription for testosterone recipients and nonrecipients of testosterone. These conditions were ascertained by the presence of at least 2 ICD-9-CM codes separated by 7 or more days (eTable 2 in the Supplement).

Statistical Analysis

Baseline characteristics of study population and covariates were noted. We generated unadjusted bivariate- and covariate-adjusted Cox proportional hazards and propensity score–matched models. To minimize covariate imbalance between groups, we used a one-to-one propensity score match with a caliper of 0.001. Propensity scores were estimated using a logistic model, including demographic characteristics; coronary artery disease; hypertension; diabetes; hyperlipidemia; heart failure; stroke; chronic kidney disease; cancers; liver disease; dementia; depression; bipolar disease; indications for pain medication; substance use disorder; alcohol dependence; psychosis; and use of glucocorticoid, antidepressant, and antipsychotic medications. We ran Cox proportional hazard models for up to 6 years of follow-up (FY 2009-2014). Testosterone recipients entered the analyses on the day of their index prescription fill and were followed up until 3 months after the date of their last testosterone fill. Nonrecipients of testosterone entered the analyses at the first date of their testosterone-level check and were followed up until 3 months after the date of their last opioid prescription. Study participants were censored at the earliest of the follow-up date, death, latest date of VHA service use, or September 30, 2015. Baseline comparisons between the recipients and nonrecipients of testosterone were performed with χ2 test, test of proportions, or unpaired, 2-tailed t test as appropriate. From the Cox models we determined hazard ratios (HRs) and 95% CIs associated with the testosterone recipients compared with the nonrecipients of testosterone. For models of outcomes, goodness of fit and proportional hazards assumptions were evaluated. We also used Kaplan-Meier curves to compare the unadjusted probability of survival separately for each primary outcome. All analyses were conducted with SAS, version 9.4 (SAS Institute Inc). A statistical significance threshold of a 2-sided P = .05 was used. Data were analyzed from April 1, 2017, to April 30, 2019.

Sensitivity Analyses

Because of the lack of randomization, confounding owing to baseline between-group differences was a potential challenge. Therefore, we conducted several sensitivity analyses to assess the robustness of associations with outcomes. The first sensitivity analysis excluded patients who had a diagnosis of cancer (n = 20 366), given that the treatment of cancer pain can differ from that of noncancer pain.[32] The second sensitivity analysis excluded men who received glucocorticoids (n = 15 149), given that these medications can suppress testosterone levels and affect outcomes.[33] The third sensitivity analysis examined all-cause mortality and MACE outcomes as a function of different testosterone formulations (injections, gels, and patches), comparing testosterone recipients with nonrecipients because difference in outcomes have been reported with different formulations.[34] The fourth sensitivity analysis used a simulation algorithm to examine the role of a potential unobserved confounder as discussed by Higashi et al.[35] We assumed the omitted confounder to be a binary variable and simulated it to correlate with death in patients who received long-term opioid plus testosterone therapy. We estimated the degree of correlation that would be needed between the unmeasured confounder and outcome (death) and the exposure (use of opioid plus testosterone treatment) to explain the association with survival.

Results

Sample Characteristics

Among the 1 437 460 men who received an outpatient prescription in a VHA facility between FY 2008 and FY 2014, we excluded 10 001 men (0.7%) with HIV infection, 508 (0.04%) with gender dysphoria, 13 112 (0.9%) with 1 or more prescriptions filled only in FY 2008 but not before, and 189 857 (13.2%) without any filled prescription in FY 2008 (Figure 1). We excluded 33 694 men (2.3%) who received testosterone in FY 2008; 35 393 (2.5%) who had prostate cancer; and 1 017 323 (70.8%) who received no opioids, received opioids but less than the 120 days’ supply during any continuous 180 days, or received opioids but for less than 1 year from earliest to latest opioid prescription. From the 111 101 long-term opioid users, we selected those who received testosterone prescription fills for 2 or more years (testosterone recipients) or any other prescription fill for 2 or more years (nonrecipients of testosterone). In all, 21 272 men (19.1%) with a total testosterone level less than 300 ng/dL or free testosterone level less than 70 pg/mL were included in the analyses.
Figure 1.

STROBE Diagram of Analytical Sample Selection

Long-term opioid use was defined as use by patients who received 120 or more days’ supply of opioids during at least 1 continuous 180-day interval in 2 or more years. Low testosterone level was defined as total testosterone level of less than 300 ng/dL (to convert to nanomoles per liter, multiply by 0.0347) or free testosterone level of less than 70 pg/mL in the past 1 year. PS indicates propensity score.

STROBE Diagram of Analytical Sample Selection

Long-term opioid use was defined as use by patients who received 120 or more days’ supply of opioids during at least 1 continuous 180-day interval in 2 or more years. Low testosterone level was defined as total testosterone level of less than 300 ng/dL (to convert to nanomoles per liter, multiply by 0.0347) or free testosterone level of less than 70 pg/mL in the past 1 year. PS indicates propensity score. Among the 21 272 long-term opioid users in this study, 14 121 (66.4%) received testosterone and 7151 (33.6%) did not. The race/ethnicity of most patients was white (n = 16 689 [78.5%]), and the mean (SD) age of the entire sample was 53 (10) years (Table 1). Compared with opioid users who did not receive testosterone, a slightly higher proportion of opioid users who received testosterone had hypertension (53.9% vs 55.2%; P = .07), hyperlipidemia (43.0% vs 48.8%; P < .001), obesity (43.7% vs 49.0%; P < .001), and posttraumatic stress disorder (24.2% vs 25.6%; P = .02) and were more likely to be receiving an opioid dose greater than 50 morphine milligram equivalents (MME) (29.4% vs 42.8%; P < .001). A slightly lower proportion of testosterone recipients compared with nonrecipients had prevalent coronary artery disease (12.9% vs 15.9%; P < .001) and stroke (1.3% vs 2.4%; P < .001). The distribution of these characteristics in the 2 groups was similar after the propensity score match, as expected.
Table 1.

Baseline Characteristics of the Sample

VariableBefore Propensity Matching, %aAfter Propensity Matching, %a
Nonrecipients of TestosteroneRecipients of TestosteroneNonrecipients of TestosteroneRecipients of Testosterone
No. of participants715114 12166766676
Age, mean (SD), y54.8 (10.6)b52.8 (10.0)b54.3 (10.5)54.2 (10.5)
Age, y
20-398.9b10.6b9.39.6
40-4917.1b21.2b17.917.8
50-5942.5b43.9b42.843.0
60-6924.6b21.1b24.424.1
70-795.6b2.7b4.64.6
≥801.2b0.5b0.90.9
Race/ethnicity
Non-Hispanic
White74.4b80.5b76.076.1
Black13.8b8.4b12.312.3
Hispanic4.1b3.4b4.04.1
Other, specified2.3b2.3b2.32.2
Unknown5.4b5.5b5.45.3
BMI, mean (SD)31.3 (6.4)b32.6 (6.7)b31.6 (6.4)31.8 (6.6)
BMI
≤18.4 0.5b0.4b0.40.4
18.5-24 (Normal weight)13.6b9.0b12.412.4
25-29 (Overweight)32.6b29.4b32.032.0
30-39 (Obesity)43.7b49.0b45.144.8
≥40 (Morbid obesity)9.6b12.3b10.010.3
Diabetes35.6b32.7b35.235.1
Hypertension53.955.253.853.2
Hyperlipidemia43.0b48.8b44.143.2
COPD15.3c13.7c15.014.8
Obstructive sleep apnea5.95.35.85.7
CHF5.1 b3.3 b4.54.5
Coronary artery disease15.9 b12.9 b15.115.0
Stroke2.4 b1.3 b2.01.9
TIA0.30.40.40.3
Peripheral artery disease5.4 b3.1 b4.74.1
Chronic kidney disease5.3b3.2b4.64.5
Bipolar disorder5.4c6.6c5.65.8
Antidepressant use61.5b69.6b63.263.5
Anxiety disorder11.8b13.9b12.112.4
PTSD24.2c25.6c24.624.6
Alcohol abuse6.86.26.66.5
Glucocorticoid use, systemic29.128.628.929.2
Baseline total testosterone, mean (SD), ng/dL248.7 (88.1)b174.3 (81.2)b248.6 (87.5)b178.3 (81.4)b
Formulation of testosterone
InjectionNA62.7NA62.3
GelNA14.6NA14.5
PatchNA22.7NA23.2
High-dose opioid therapy >50 MME29.4b42.8b31.131.1
Exposure time, d
Mean (SD)654 (470)b1034 (447)b654 (470)b1012 (442)b
Median (range)752 (366-2280)929 (369-2274)754 (366-2280)900 (370-2274)

Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; MME, morphine milligram equivalents; NA, not applicable; PTSD, posttraumatic stress disorder; TIA, transient ischemic attack.

SI conversion factor: To convert testosterone from nanograms per deciliter to nanomoles per liter, multiply by 0.0347.

Results of statistical comparison between those who received testosterone and those who did not. P > .05 unless otherwise indicated.

P < .001

Between P = .001 and P = .05.

Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; MME, morphine milligram equivalents; NA, not applicable; PTSD, posttraumatic stress disorder; TIA, transient ischemic attack. SI conversion factor: To convert testosterone from nanograms per deciliter to nanomoles per liter, multiply by 0.0347. Results of statistical comparison between those who received testosterone and those who did not. P > .05 unless otherwise indicated. P < .001 Between P = .001 and P = .05.

All-Cause Mortality, MACE, Fractures, and Anemia

In unadjusted and covariate-adjusted models, men who received opioid plus testosterone therapy had statistically significantly lower all-cause mortality than men who received opioids only during the follow-up period of up to 6 years (HR = 0.51; 95% CI, 0.42-0.61) (Table 2 and Figure 2). The incidence of MACE was also significantly lower in recipients of opioids plus testosterone treatment compared with recipients of opioids only during follow-up in the covariate-adjusted models (HR = 0.58; 95% CI, 0.51-0.67).
Table 2.

Likelihood of Outcomes in the 6-Year Follow-up Period as a Function of Long-term Opioid or Testosterone Use Status

OutcomeUnadjusted EstimatesHR (95% CI)
Outcome Events, No. (Unadjusted Incidence Rate per 100 Person-Years)Bivariate HR (95% CI)Covariate-Adjusted Cox Model (Model 1)aPS-Matched Cox Model (Model 2)
No.NA21 27221 27213 352
All-cause mortality
No testosterone203 (1.4)1 [Reference]1 [Reference]1 [Reference]
Testosterone327 (0.7)0.41 (0.34-0.49)0.51 (0.42-0.61)0.54 (0.44-0.67)
Incidence of MACE or deathsb
No testosterone358 (2.5)1 [Reference]1 [Reference]1 [Reference]
Testosterone605 (1.2)0.48 (0.42-0.54)0.58 (0.51-0.67)0.60 (0.52-0.70)
Incidence of vertebral fractures (ICD-9-CM codes 805 and 806)
No testosterone60 (0.43)1 [Reference]1 [Reference]1 [Reference]
Testosterone154 (0.31)0.80 (0.59-1.08)0.86 (0.63-1.18)0.91 (0.64-1.30)
Incidence of femoral or hip fractures (ICD-9-CM codes 808, 820, and 821)
No testosterone55 (0.39)1 [Reference]1 [Reference]1 [Reference]
Testosterone94 (0.19)0.54 (0.39-0.76)0.68 (0.48-0.96)0.60 (0.40-0.89)
Incidence of vertebral, femoral, or hip fractures (ICD-9-CM codes 805, 806, 808, 820, and 821)
No testosterone107 (0.76)1 [Reference]1 [Reference]1 [Reference]
Testosterone239 (0.48)0.70 (0.59-0.88)0.80 (0.63-1.01)0.78 (0.59-1.02)
Anemia
Subgroup 1: patients with baseline anemiac
Baseline anemia resolved, No.NA15671567876
No testosterone469 (115.6)1 [Reference]1 [Reference]1 [Reference]
Testosterone837 (133.2)1.18 (1.06-1.33)1.16 (1.02-1.31)1.17 (1.01-1.35)
Subgroup 2: patients without baseline anemiac
New anemia emerged, No.NA17 35517 35510 596
No testosterone1104 (13.0)1 [Reference]1 [Reference]1 [Reference]
Testosterone2205 (7.6)0.63 (0.59-0.68)0.73 (0.68-0.79)0.73 (0.67-0.80)

Abbreviations: HR, hazard ratio; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; MACE, major adverse cardiovascular events; NA, not applicable; PS, propensity score.

Adjusted for age, race/ethnicity, marital status, body mass index, copay requirement, zip code poverty level, and baseline status of the following clinical conditions: indications for pain, chronic pain conditions, use of glucocorticoid medications, congestive heart failure, cancers, coronary artery disease, hypertension, diabetes, hyperlipidemia, liver disease, chronic kidney disease, stroke or transient ischemic attack, dementia, depression, bipolar disease, substance use disorder, alcohol dependence, psychosis, and use of antipsychotic medications.

Incident cases (new occurrence) of myocardial infarction or thrombotic stroke or death (eTable 2 in the Supplement).

Based on measurements closest to the index date. Anemia is defined as hemoglobin level less than 12 g/dL (to convert to grams per liter, multiply by 10.0) or a hematocrit reading less than 36%. Included patients had to have both preindex and postindex hemoglobin or hematocrit values.

Figure 2.

Kaplan-Meier Curves of Survival Probability Overall and Without Major Adverse Cardiovascular Events During 6-Year Follow-up

Y-axes show covariate-adjusted survival rates. Orange line indicates long-term opioid users who did not receive testosterone; navy line, long-term opioid users who received testosterone treatment.

Abbreviations: HR, hazard ratio; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; MACE, major adverse cardiovascular events; NA, not applicable; PS, propensity score. Adjusted for age, race/ethnicity, marital status, body mass index, copay requirement, zip code poverty level, and baseline status of the following clinical conditions: indications for pain, chronic pain conditions, use of glucocorticoid medications, congestive heart failure, cancers, coronary artery disease, hypertension, diabetes, hyperlipidemia, liver disease, chronic kidney disease, stroke or transient ischemic attack, dementia, depression, bipolar disease, substance use disorder, alcohol dependence, psychosis, and use of antipsychotic medications. Incident cases (new occurrence) of myocardial infarction or thrombotic stroke or death (eTable 2 in the Supplement). Based on measurements closest to the index date. Anemia is defined as hemoglobin level less than 12 g/dL (to convert to grams per liter, multiply by 10.0) or a hematocrit reading less than 36%. Included patients had to have both preindex and postindex hemoglobin or hematocrit values.

Kaplan-Meier Curves of Survival Probability Overall and Without Major Adverse Cardiovascular Events During 6-Year Follow-up

Y-axes show covariate-adjusted survival rates. Orange line indicates long-term opioid users who did not receive testosterone; navy line, long-term opioid users who received testosterone treatment. The incidence of femoral and hip fractures was significantly lower in recipients of opioids plus testosterone than in recipients of opioids only in unadjusted and covariate-adjusted models during follow-up (HR = 0.68; 95% CI, 0.48-0.96). When vertebral fractures were considered individually (HR = 0.86; 95% CI, 0.63-1.18) or when all fractures (vertebral plus femoral and hip fractures) were considered (HR = 0.80; 95% CI, 0.63-1.01), the associations with testosterone treatment were not significant. Among participants who were anemic at baseline, testosterone treatment was significantly associated with the resolution of anemia during the 6-year follow-up (HR = 1.16; 95% CI, 1.02-1.31) in the covariate-adjusted model. Long-term opioid users who received testosterone had a significantly lower risk of incident anemia compared with opioid users who did not receive testosterone (HR = 0.73; 95% CI, 0.68-0.79). The findings of propensity score–adjusted models were similar to those of the covariate-adjusted models (Table 2). Cox proportional hazards models for propensity score–matched samples demonstrated a significantly lower hazard for all-cause mortality (HR = 0.54; 95% CI, 0.44-0.67); significantly lower incidence of MACE (HR = 0.60; 95% CI, 0.52-0.70), femoral or hip fractures (HR = 0.60; 95% CI, 0.40-0.89), and anemia (HR = 0.73; 95% CI, 0.67-0.80); and significantly higher rates of resolved anemia (HR = 1.17; 95% CI, 1.01-1.35) for testosterone recipients compared with nonrecipients. In a sensitivity analysis that excluded men with cancer pain, testosterone recipients in covariate-adjusted models had significantly lower all-cause mortality (HR, 0.51; 95% CI, 0.42-0.62) and lower incidence of MACE (HR, 0.58; 95% CI, 0.50-0.67), femoral or hip fracture (HR, 0.65; 95% CI, 0.45-0.94), and anemia (HR, 0.74; 95% CI, 0.68-0.80) compared with nonrecipients of testosterone, a finding consistent with that of the primary analysis (Table 3). When the analysis was limited to patients who did not receive glucocorticoid medication, with the exception of femoral or hip fractures, the results were comparable (mortality: HR, 0.56 [95% CI, 0.44-0.71]; MACE: HR, 0.57 [95% CI, 0.48-0.68]; anemia: HR, 0.71 [95% CI, 0.64-0.78]) (eTable 3 in the Supplement).
Table 3.

Subgroup (Patients Without Cancer) Analysis of Outcomes in the 6-Year Follow-up Period as a Function of Long-term Opioid or Testosterone Use Status

OutcomeUnadjusted EstimatesHR (95% CI)
Outcome Events, No. (Unadjusted Incidence Rate per 100 Person-Years)Bivariate HR (95% CI)Covariate-Adjusted Cox Model (Model 1)aPS-Matched Cox Model (Model 2)
No.NA20 36620 36612 702
All-cause mortality
No testosterone179 (1.3)1 [Reference]1 [Reference]1 [Reference]
Testosterone298 (0.6)0.42 (0.35-0.50)0.51 (0.42-0.62)0.53 (0.42-0.66)
Incidence of MACE or deathsb
No testosterone328 (2.4)1 [Reference]1 [Reference]1 [Reference]
Testosterone563 (1.2)0.48 (0.42-0.55)0.58 (0.50-0.67)0.59 (0.50-0.69)
Incidence of vertebral fractures (ICD-9-CM codes 805 and 806)
No testosterone55 (0.41)1 [Reference]1 [Reference]1 [Reference]
Testosterone145 (0.30)0.81 (0.59-1.11)0.87 (0.63-1.20)0.91 (0.63-1.32)
Incidence of femoral or hip fractures (ICD-9-CM codes 808, 820, and 821)
No testosterone51 (0.38)1 [Reference]1 [Reference]1 [Reference]
Testosterone85 (0.18)0.52 (0.37-0.74)0.65 (0.45-0.94)0.56 (0.37-0.85)
Incidence of vertebral, femoral, or hip fractures (ICD-9-CM codes 805, 806, 808, 820, and 821)
No testosterone98 (0.73)1 [Reference]1 [Reference]1 [Reference]
Testosterone223 (0.47)0.71 (0.56-0.90)0.80 (0.62-1.03)0.77 (0.58-1.03)
Anemia
Subgroup 1: patients with baseline anemiac
Baseline anemia resolved, No.NA13991399782
No testosterone399 (112.9)1 [Reference]1 [Reference]1 [Reference]
Testosterone771 (131.5)1.19 (1.06-1.35)1.14 (1.00-1.30)1.17 (1.00-1.37)
Subgroup 2: patients without baseline anemiac
New anemia emerged, No.NA16 66716 66710 150
No testosterone1019 (12.5)1 [Reference]1 [Reference]1 [Reference]
Testosterone2067 (7.4)0.64 (0.59-0.69)0.74 (0.68-0.80)0.73 (0.67-0.80)

Abbreviations: HR, hazard ratio; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; MACE, major adverse cardiovascular events; NA, not applicable; PS, propensity score.

See note a in Table 2.

See note b in Table 2.

See note c in Table 2.

Abbreviations: HR, hazard ratio; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; MACE, major adverse cardiovascular events; NA, not applicable; PS, propensity score. See note a in Table 2. See note b in Table 2. See note c in Table 2. In sensitivity analyses comparing different testosterone formulations on all-cause mortality and MACE, all testosterone formulations were associated with lower likelihood of mortality (HR, 0.51; 95% CI, 0.42-0.61) and MACE (HR, 0.58; 95% CI, 0.51-0.67) in fully adjusted models comparing testosterone recipients with nonrecipients (eTable 4 in the Supplement). We examined the potential role of an unobserved confounder and identified the critical levels for correlation of a potential confounder with all-cause mortality and testosterone exposure that would completely explain the observed effects (eTable 5 in the Supplement). The association between treatment with opioid plus testosterone therapy and mortality was moderately sensitive to unmeasured confounding. An unmeasured confounder with 0.3 correlation with opioid plus testosterone treatment would need to have a −0.06 (HR, 1.09; 95% CI, 0.90-1.32; P = .37) correlation or stronger with mortality to eliminate the negative implication of testosterone for mortality.

Discussion

Among long-term opioid users in the VHA, men who received opioid plus testosterone therapy had significantly lower all-cause mortality and significantly lower incidence of MACE, anemia, and femoral or hip fractures compared with men who received opioid treatment alone. The association between testosterone treatment and MACE and mortality was robust to analyses, which used both covariate-adjusted and propensity score–matched models. Sensitivity analyses in men who had noncancer pain or who did not receive glucocorticoids confirmed the findings of the primary analysis. This cohort study, a first step toward understanding the association of testosterone treatment with health outcomes in long-term opioid users, has clinical implications because of the high prevalence of opioid use among US military veterans and high rates of androgen deficiency and testosterone use among opioid users. These findings need confirmation in a randomized clinical trial. Because assignment to testosterone treatment was not randomized, the differences in outcomes between those treated with opioids plus testosterone and those who received opioids only cannot be attributed with certainty to testosterone treatment. Although differences in outcomes remained statistically significant even after propensity score matching, baseline differences between patient groups may have been factors in outcomes in ways not captured by propensity score. Compared with men who received opioids only, men who received opioids plus testosterone had a higher mean body mass index and higher prevalence of hyperlipidemia, hypertension, and psychiatric disorders. The men who received opioids only had slightly higher prevalence of some other comorbid conditions, including coronary artery disease and stroke. We attempted to address this concern by propensity score matching and by simulating the implication of a potential unobserved confounder. The simulation analyses showed that an unobserved confounder (eg, better access to health care) would need to be moderately correlated with both the exposure (receipt of testosterone and opioids) and the outcome (mortality) to explain these findings beyond adjustment for observed covariates. Because we used propensity score matching to account for baseline differences between groups, the existence of such strong, unmeasured confounding was not likely, but it cannot be ruled out entirely. Propensity scores can balance only observed covariates, and findings could be subject to bias from unmeasured confounding variables. Furthermore, establishing the index date for individuals not receiving medications is complex. On the basis of similar previous approaches to identifying an index date for individuals not receiving medications,[36,37] we used the date of documented testosterone level as the beginning of exposure for nonrecipients of testosterone. To our knowledge, this cohort study is the first to examine the association between testosterone treatment in long-term opioid users and MACE, fractures, anemia, and all-cause mortality. The only short-term randomized clinical trial in men with OPIAD found that testosterone treatment improved sexual function, pain sensitivity, and body composition.[24] Similar improvements in sexual function[38] have been reported in uncontrolled short-term studies in patients treated with opioid medications.[39] Opioid agonists used in the treatment of opioid addiction and treatment have been shown to differently affect testosterone levels and sexual function in opioid-dependent men. Compared with methadone, buprenorphine has been found to be associated with substantially lower suppression of testosterone levels and with lower rates of sexual dysfunction.[40,41] These findings are in contrast to reports that testosterone therapy was associated with adverse cardiovascular events in men with low testosterone, most of whom did not have long-term use of opioids.[16,17,18] However, not all studies found this association between testosterone and increased risk of death or cardiovascular outcomes, and some studies even reported cardiovascular advantages.[19,20,42]

Strengths and Limitations

This study has several strengths, one of which is its use of the large and detailed VHA CDW. The CDW included medication dispensing records, laboratory results, ICD-9-CM diagnosis codes, and demographics. The large sample size and long follow-up period enabled the reliable assessment of MACE, mortality, and fracture outcomes, which would not have been possible in smaller studies of shorter duration. The study included hard outcomes that are clinically important. The concern about confounding by indication owing to testosterone recipients having low testosterone levels at baseline was accounted for by requiring control patients to meet that criterion as well. In addition, we used propensity score matching to minimize the factors in baseline differences, and we performed additional sensitivity analyses to assess the effect of unmeasured confounding. We included only patients who received an opioid prescription in the year before receiving a testosterone prescription and who had a confirmed low total or free testosterone level before receiving testosterone. To avoid the immortal person time bias,[29] we defined the exposure by the dates of the first and last testosterone prescription fills. This study’s limitations include its observational design, whereby unmeasured confounding could have affected the findings. Physicians also could have selected healthier patients to receive testosterone therapy. We attempted to control for confounding by adjusting for a wide range of relevant demographics, conditions, and medications; by using propensity score matching; and by simulating the potential effect of an unobserved confounder. However, unmeasured confounding cannot be fully excluded. The quality of the assays for total and free testosterone levels within the VHA varied. Immunoassays for testosterone commonly used in this period were susceptible to inaccuracy in the low range; some patients on testosterone treatment might not have been hypogonadal, whereas some men with hypogonadism may have been misdiagnosed as eugonadal. The protective influence of testosterone on mortality in patients taking opioids remained robust in each of these different analyses. We only had access to VHA pharmacy data; some patients may have filled a testosterone prescription outside the system. Because medication costs in the VHA system were lower than outside the system, it was unlikely that many patients obtained their testosterone prescription externally. Furthermore, this factor would only dilute the treatment effect and drive the results toward null. Sexual function, quality of life, and well-being outcomes could not be ascertained from the VHA CDW, and mental health outcomes were not assessed. Although ICD-9-CM codes are commonly used to identify conditions, these codes may not have been recorded accurately. Study outcomes were ascertained based on clinical coding and were not adjudicated. The total number of fractures was small, and the study may not have had sufficient statistical power to detect between-group differences in fracture events. Opioid use was defined according to prescription fills, and low testosterone levels were identified by documented laboratory results. On-treatment testosterone levels in men who received testosterone treatment varied widely[43]; however, testosterone levels during treatment were not consistently monitored. Although we required all patients to have documented opioid prescriptions in 2 or more years, a patient in either group could have stopped using opioids or could have changed their use pattern within the study period. Patients in the VHA system typically have a greater burden of comorbid conditions compared with the general population, which may affect the generalizability of these findings to non-VHA patients.[44]

Conclusions

This cohort study found that, among men who were long-term opioid users, those who received a testosterone prescription had significantly lower all-cause mortality and a significantly lower incidence of MACE, anemia, and femoral or hip fractures in up to 6 years of follow-up compared with male opioid users who did not receive testosterone therapy. Because of the observational nature of this study, confounding owing to known and unknown differences between groups cannot be disregarded. Because of the high prevalence of opioid use among US veterans and the high proportion of opioid users who receive testosterone treatment, we believe a randomized clinical trial is warranted to ascertain whether testosterone treatment is safe and whether it is associated with improved health outcomes among opioid users who have androgen deficiency.
  42 in total

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Authors:  Glenn R Cunningham; Alisa J Stephens-Shields; Raymond C Rosen; Christina Wang; Shalender Bhasin; Alvin M Matsumoto; J Kellogg Parsons; Thomas M Gill; Mark E Molitch; John T Farrar; David Cella; Elizabeth Barrett-Connor; Jane A Cauley; Denise Cifelli; Jill P Crandall; Kristine E Ensrud; Laura Gallagher; Bret Zeldow; Cora E Lewis; Marco Pahor; Ronald S Swerdloff; Xiaoling Hou; Stephen Anton; Shehzad Basaria; Susan J Diem; Vafa Tabatabaie; Susan S Ellenberg; Peter J Snyder
Journal:  J Clin Endocrinol Metab       Date:  2016-06-29       Impact factor: 5.958

2.  Association of Testosterone Levels With Anemia in Older Men: A Controlled Clinical Trial.

Authors:  Cindy N Roy; Peter J Snyder; Alisa J Stephens-Shields; Andrew S Artz; Shalender Bhasin; Harvey J Cohen; John T Farrar; Thomas M Gill; Bret Zeldow; David Cella; Elizabeth Barrett-Connor; Jane A Cauley; Jill P Crandall; Glenn R Cunningham; Kristine E Ensrud; Cora E Lewis; Alvin M Matsumoto; Mark E Molitch; Marco Pahor; Ronald S Swerdloff; Denise Cifelli; Xiaoling Hou; Susan M Resnick; Jeremy D Walston; Stephen Anton; Shehzad Basaria; Susan J Diem; Christina Wang; Stanley L Schrier; Susan S Ellenberg
Journal:  JAMA Intern Med       Date:  2017-04-01       Impact factor: 21.873

3.  Relation of Testosterone Normalization to Mortality and Myocardial Infarction in Men With Previous Myocardial Infarction.

Authors:  Olurinde A Oni; Seyed Hamed Hosseini Dehkordi; Mohammad-Ali Jazayeri; Rishi Sharma; Mukut Sharma; Reza Masoomi; Ram Sharma; Kamal Gupta; Rajat S Barua
Journal:  Am J Cardiol       Date:  2019-07-25       Impact factor: 2.778

4.  Who Gets Testosterone? Patient Characteristics Associated with Testosterone Prescribing in the Veteran Affairs System: a Cross-Sectional Study.

Authors:  Guneet K Jasuja; Shalender Bhasin; Joel I Reisman; Joseph T Hanlon; Donald R Miller; Anthony P Morreale; Leonard M Pogach; Francesca E Cunningham; Angela Park; Dan R Berlowitz; Adam J Rose
Journal:  J Gen Intern Med       Date:  2016-12-19       Impact factor: 5.128

Review 5.  Opioids for cancer pain - an overview of Cochrane reviews.

Authors:  Philip J Wiffen; Bee Wee; Sheena Derry; Rae F Bell; R Andrew Moore
Journal:  Cochrane Database Syst Rev       Date:  2017-07-06

6.  Testosterone treatment and mortality in men with low testosterone levels.

Authors:  Molly M Shores; Nicholas L Smith; Christopher W Forsberg; Bradley D Anawalt; Alvin M Matsumoto
Journal:  J Clin Endocrinol Metab       Date:  2012-04-11       Impact factor: 5.958

7.  Effects of Testosterone Supplementation for 3 Years on Muscle Performance and Physical Function in Older Men.

Authors:  Thomas W Storer; Shehzad Basaria; Tinna Traustadottir; S Mitchell Harman; Karol Pencina; Zhuoying Li; Thomas G Travison; Renee Miciek; Panayiotis Tsitouras; Kathleen Hally; Grace Huang; Shalender Bhasin
Journal:  J Clin Endocrinol Metab       Date:  2017-02-01       Impact factor: 5.958

8.  Quality of care is associated with survival in vulnerable older patients.

Authors:  Takahiro Higashi; Paul G Shekelle; John L Adams; Caren J Kamberg; Carol P Roth; David H Solomon; David B Reuben; Lillian Chiang; Catherine H MacLean; John T Chang; Roy T Young; Debra M Saliba; Neil S Wenger
Journal:  Ann Intern Med       Date:  2005-08-16       Impact factor: 25.391

Review 9.  Effective medical treatment of opiate addiction. National Consensus Development Panel on Effective Medical Treatment of Opiate Addiction.

Authors: 
Journal:  JAMA       Date:  1998-12-09       Impact factor: 56.272

10.  Open-label pilot study of testosterone patch therapy in men with opioid-induced androgen deficiency.

Authors:  Harry W Daniell; Robin Lentz; Norman A Mazer
Journal:  J Pain       Date:  2006-03       Impact factor: 5.820

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