Stuart N. Hoffman

Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system

AIMS Our study sought to assess the prevalence of and risk factors for opioid drug dependence among out-patients on long-term opioid therapy in a large health-care system. METHODS Using electronic health records, we identified out-patients receiving 4+ physician orders for opioid therapy in the past 12 months for non-cancer pain within a large US health-care system. We completed diagnostic interviews with 705 of these patients to identify opioid use disorders and assess risk factors. RESULTS Preliminary analyses suggested that current opioid dependence might be as high as 26% [95% confidence interval (CI) = 22.0-29.9] among the patients studied. Logistic regressions indicated that current dependence was associated with variables often in the medical record, including age <65 [odds ratio (OR) = 2.33, P = 0.001], opioid abuse history (OR = 3.81, P < 0.001), high dependence severity (OR = 1.85, P = 0.001), major depression (OR = 1.29, P = 0.022) and psychotropic medication use (OR = 1.73, P = 0.006). Four variables combined (age, depression, psychotropic medications and pain impairment) predicted increased risk for current dependence, compared to those without these factors (OR = 8.01, P < 0.001). Knowing that the patient also had a history of severe dependence and opioid abuse increased this risk substantially (OR = 56.36, P < 0.001). CONCLUSION Opioid misuse and dependence among prescription opioid patients in the United States may be higher than expected. A small number of factors, many documented in the medical record, predicted opioid dependence among the out-patients studied. These preliminary findings should be useful in future research efforts.

Prevalence of Prescription Opioid-Use Disorder Among Chronic Pain Patients: Comparison of the DSM-5 vs. DSM-4 Diagnostic Criteria

ABSTRACT The authors estimated the prevalence of lifetime prescription opioid-use disorder among outpatients on opioid therapy using criteria from both versions 4 and 5 of the Diagnostic and Statistical Manual of Mental Disorders (DSM). Using electronic records from a large health care system, a random sample of outpatients undergoing long-term opioid therapy for non-cancer pain was identified and 705 participants completed diagnostic interviews. The prevalence of lifetime DSM-5 opioid-use disorder among these patients was 34.9% (95% confidence interval [CI] = 30.5–39.5), similar to the prevalence of DSM-4 opioid dependence (35.5%, 95% CI = 31.1–40.2). The Kappa value between DSM-5 and DSM-4 criteria was high (Kappa = 0.873, p < 0.0001). Logistic regressions suggested DSM-5 opioid-use disorder was associated with age younger than 65 (odds ratio [OR] = 2.25, p = 0.009), history of opioid abuse (OR = 4.94, p < 0.001), higher opioid withdrawal symptoms (OR = 3.01, p = 0.008), and history of substance abuse treatment (OR = 1.62, p = 0.015), similar to DSM-4. Based on DSM-5, 21.7% of patients met criteria for moderate and 13.2% for severe opioid-use disorder, respectively. Given the changes proposed, the finding that the prevalence of and risk factors for DSM-5 opioid-use disorders were similar to DSM-4 were unexpected. Further research is advised.

Association of FKBP5, COMT and CHRNA5 polymorphisms with PTSD among outpatients at risk for PTSD☆

To the Editor: Several genetic components for posttraumatic stress disorder (PTSD) have been identified, including biologic pathways involving the hypothalamic–pituitary–adrenocortical, locus coeruleus/noradrenergic, and the limbic systems (Broekman, et al., 2007; Koenen, 2007; Rauch and Drevets, 2009). In our IRB-approved study, lifetime PTSD was assessed among adult outpatients with chronic, non-malignant pain, a condition commonly associated with PTSD (McFarlane, 2010). We assessed PTSD with an instrument widely used in previous epidemiologic studies (Boscarino et al., 2010). We examined genetic markers using a multivariate design that assessed single nucleotide polymorphisms (SNPs) located within the FK506 binding protein-5 (FKBP5), catechol-O-methyltransferase (COMT), and cholinergic receptor nicotinic alpha3/alpha-5 (CHRNA3/CHRNA5) gene clusters. SNPs were selected using agnostic LD tagging with consideration of prior evidence and functional annotation (Erlich, et al., 2010). The COMT gene is associated with anxiety disorders, psychosis, depression, and other conditions involving catecholamine pathway regulation (Craddock, et al., 2006; Montag et al., 2008). This gene is also associated with PTSD (Kolassa et al., 2010). The FKBP5 gene regulates glucocorticoid receptor sensitivity, is functionally involved in HPA stress axis activity, and is associated with PTSD (Binder, 2009; Gillespie, et al., 2009). The CHRNA3/5 gene cluster, which encodes components of the nicotinic acetylcholine receptor, is associated with nicotine dependence, smoking, and other substance misuse (Erlich, et al., 2010). PTSD is also associated with cigarette smoking and substance use (Boscarino et al., 2006; Fu et al., 2007). Using trained interviewers and following informed consent, we completed diagnostic interviews with 502 subjects and collected DNA to determine if FKBP5, COMT, and CHRNA3/5 SNPs were associated with PTSD (mean age = 55, S.D. = 13.4; PTSD = 15%, 95% CI = 11.7–18.1%). Non-Caucasian patients were excluded from this analysis. Genotyping was performed on an Applied BioSystems 7500 real-time PCR platform, using TaqMan kits. Using multivariate logistic regressions that included demographic (age, gender, income, education, and marital status) and environmental (trauma exposure, childhood adversity, and neuroticism) variables, 3 of 9 SNPs examined were associated with PTSD (p<0.05), including one within each of the FKBP5 (rs9470080), COMT (rs4680), and CHRNA5 (rs16969968) genes. A count of risk alleles in these 3 loci was also associated with PTSD (OR = 1.65, 95% CI = 1.25–2.16, p = 0.000426), suggesting that those with 4 or more PTSD risk alleles had ~ 7 times greater risk of PTSD, compared to those with no risk alleles (1.65 × 4 = 6.6). We also included opioid dependence, reported pain, number of pain prescriptions, and ancestry (Northern European, Eastern European, and Sothern European/Other) in the model as a final analysis step, but this did not alter the results. Examination of risk-allele counts by PTSD status suggested that the “AA” genotype of the rs16969968 (CHRNA5) and rs4680 (COMT), and the “TT” genotype of rs9470080 (FKBP5) are more common among PTSD cases. Since our logistic regression detected a complex interaction between allele count × trauma exposure × childhood adversity × neuroticism (p = 0.029), we used Answer Tree Chi-square Automatic Interaction Detection to examine these effects (SPSS, Chicago, IL). This confirmed interactions with risk-allele count, indicating that those with higher risk-allele counts and exposure to higher trauma, higher childhood adversity, and higher neuroticism, were at much greater risk for PTSD. Conversely, those with no risk alleles appeared highly resilient to PTSD, regardless of environmental exposures. This is the first study to report that SNP markers rs16969968, rs9470080, and rs4680, were each individually associated with PTSD and that a cumulative allele model using these SNPs was associated with higher PTSD risk. FKBP5 polymorphisms are known to regulate the cortisol-binding affinity and nuclear translocation of the glucocorticoid receptor and polymorphisms at this locus have been associated with PTSD. COMT polymorphisms have been found to affect fear extinction and are thought to play a role in anxiety disorders and PTSD. The CHRNA gene has been associated with nicotine dependence and PTSD is associated with cigarette smoking and other substance misuse. Additional research is recommended to confirm these findings. The involvement of the CHRNA gene in PTSD, fear circuitry, and stress regulation is biologically plausible and worthy of further investigation.

Higher FKBP5, COMT, CHRNA5, and CRHR1 allele burdens are associated with PTSD and interact with trauma exposure: implications for neuropsychiatric research and treatment.

Objective The study aim was to assess the cumulative burden of polymorphisms located within four genetic loci previously associated with posttraumatic stress disorder (PTSD) among outpatients at risk for PTSD. Methods Diagnostic interviews were completed and DNA samples collected among 412 pain patients to determine if FKBP5 (rs9470080), COMT (rs4680), CHRNA5 (rs16969968), and CRHR1 (rs110402) single nucleotide polymorphisms were cumulatively associated with increased risk for PTSD. Results In bivariate analyses, it was found that a count of specific PTSD risk alleles located within FKBP5, COMT, CHRNA5, and CRHR1 genetic loci (allele range = 0–6, mean count = 2.92, standard deviation = 1.36) was associated with lifetime (t [409] = 3.430, P = 0.001) and early onset PTSD (t [409] = 4.239, P = 0.000028). In logistic regression, controlling for demographic factors, personality traits, and trauma exposures, this risk allele count remained associated with both lifetime (odds ratio = 1.49, P = 0.00158) and early onset PTSD (odds ratio = 2.36, P = 0.000093). Interaction effects were also detected, whereby individuals with higher risk allele counts and higher trauma exposures had an increased risk of lifetime PTSD (allele count × high trauma, P = 0.026) and early onset PTSD (allele count × high trauma, P = 0.016) in these logistic regressions. Those with no or few risk alleles appeared resilient to PTSD, regardless of exposure history. Conclusion A cumulative risk allele count involving four single nucleotide polymorphisms located within the FKBP5, COMT, CHRNA5, and CRHR1 genes are associated with PTSD. Level of trauma exposure interacts with risk allele count, such that PTSD is increased in those with higher risk allele counts and higher trauma exposures. Since the single nucleotide polymorphisms studied encompass stress circuitry and addiction biology, these findings may have implications for neuropsychiatric research and treatment.

Low serum cholesterol and external-cause mortality: Potential implications for research and surveillance

OBJECTIVE Previous studies suggested that low total cholesterol was associated with external mortality, including deaths from suicide, homicide, and accidents. However, this reported association was potentially confounded, since cholesterol was also reported to be associated with alcohol abuse, anti-social personality disorder, and other risk factors for external mortality. METHOD We examined external-cause mortality among a national sample of 4462 male, US veterans at baseline in 1985. Using Cox regressions to estimate survival time, we assessed the impact of low baseline total cholesterol < or =165 mg/dl, age, race, intelligence, BMI, alcohol abuse, anti-social personality disorder, depression, and other factors at follow-up. Study follow-up continued until December 31, 2000. A total of 55 external mortalities occurred during this approximately 16-year period. RESULTS Multivariate Cox regressions predicting external-cause mortality suggested that three predictor variables were significant: low total cholesterol, morbid depression, and anti-social personality disorder, with hazard ratios (HRs) of 1.97 (p=0.046), 1.76 (p=0.043), and 2.22 (p=0.006), respectively. In addition, a significant interaction was detected for low cholesterol x morbid depression (p<0.005), whereby those with both at baseline were approximately 7 times more likely to die from external mortality (HR=6.5, 95% CI=3.07-13.76). CONCLUSION Among a national random sample of community-based men, lower baseline cholesterol predicted external mortality and revealed an interaction with morbid depression. Patients presenting with low cholesterol and morbid depression in clinical practice may warrant clinical attention and surveillance.

PTSD and Alcohol Use After the World Trade Center Attacks: A Longitudinal Study

Research suggests that posttraumatic stress disorder (PTSD) is associated with increased alcohol use, but the findings have not been consistent. We assessed alcohol use, binge drinking, and psychotropic medication use longitudinally in 1,681 New York City adults, representative of the 2000 census, 2 years after the World Trade Center attacks. We found that, with the exception of a modified CAGE Questionnaire index for alcohol, alcohol use showed a modest increase over time and was related to PTSD symptoms, with an increase of about 1 more drink per month for those with PTSD, even though overall levels appeared to be within the National Institute on Alcohol Abuse and Alcoholisms safe range. Psychotropic medication use followed a similar trend; those with PTSD used psychotropics about 20 more days over the past year than those without. Because the study analyses adjusted for key psychosocial variables and confounders, it is not clear if the increased alcohol use following trauma exposure is associated with self-medication of PTSD symptoms, whether increased alcohol use prior to exposure is a risk for delayed-onset PTSD, or whether a third unmeasured variable is involved. Further research is warranted.

Consistent Association Between Mixed Lateral Preference and PTSD: Confirmation Among a National Study of 2490 US Army Vietnam Veterans

Objective: To evaluate the research-based association between mixed lateral preference for handedness and risk for posttraumatic stress disorder (PTSD) in a large-scale sample of US Army Vietnam veterans exposed to war zone stressors. Method: We used a national sample of 2490 male US Army veterans, who completed the Edinburgh Handedness Inventory (EHI), a measure ranging from −100 (pure left-handedness) to +100 (pure right-handedness). We developed several classifications representing levels of mixed laterality: a) an EHI −70 to +70 (EHI 70, moderate mixed); b) an EHI −50 to +50 (EHI 50, consistent mixed); and c) an EHI 0, plus reports of using either hand on ≥50% of the tasks assessed (EHI 0+, extreme mixed). We controlled for intelligence, race, Army entry age, and Army volunteer status, and we assessed the impact of combat exposure. Results: Although all three handedness measures were associated with current PTSD in bivariate analyses, only Edinburgh 0+ was associated with PTSD in the multivariate model (odds ratio (OR) = 2.1; p = .021). However, when we classified handedness by high combat exposure, all three measures were associated with PTSD, with ORs = 2.5, 2.8, and 4.7 for EHI 70, EHI 50, and EHI 0+, respectively (all p < .001). Veterans with mixed laterality and high combat exposure also had significantly increased PTSD symptoms (all p < .001). Conclusion: Our study confirmed findings reported among mostly smaller clinical samples and suggested that mixed lateral preference was associated with PTSD, especially among those individuals exposed to more severe psychological trauma. EHI = Edinburgh Handedness Inventory; PTSD = posttraumatic stress disorder; DIS = Diagnostic Interview Schedule; NSS = neurological soft signs; RTI = Research Triangle Institute

A brief screening tool for assessing psychological trauma in clinical practice: development and validation of the New York PTSD Risk Score.

OBJECTIVE The objective was to develop a brief posttraumatic stress disorder (PTSD) screening instrument that is useful in clinical practice, similar to the Framingham Risk Score used in cardiovascular medicine. METHODS We used data collected in New York City after the World Trade Center disaster (WTCD) and other trauma data to develop a new PTSD prediction tool--the New York PTSD Risk Score. We used diagnostic test methods to examine different clinical domains, including PTSD symptoms, trauma exposures, sleep disturbances, suicidal thoughts, depression symptoms, demographic factors and other measures to assess different PTSD prediction models. RESULTS Using receiver operating curve (ROC) and bootstrap methods, five prediction domains, including core PTSD symptoms, sleep disturbance, access to care status, depression symptoms and trauma history, and five demographic variables, including gender, age, education, race and ethnicity, were identified. For the best prediction model, the area under the ROC curve (AUC) was 0.880 for the Primary Care PTSD Screen alone (specificity=82.2%, sensitivity=93.7%). Adding care status, sleep disturbance, depression and trauma exposure increased the AUC to 0.943 (specificity=85.7%, sensitivity=93.1%), a significant ROC improvement (P<.0001). Adding demographic variables increased the AUC to 0.945, which was not significant (P=.250). To externally validate these models, we applied the WTCD results to 705 pain patients treated at a multispecialty group practice and to 225 trauma patients treated at a Level I Trauma Center. These results validated those from the original WTCD development and validation samples. CONCLUSION The New York PTSD Risk Score is a multifactor prediction tool that includes the Primary Care PTSD Screen, depression symptoms, access to care, sleep disturbance, trauma history and demographic variables and appears to be effective in predicting PTSD among patients seen in healthcare settings. This prediction tool is simple to administer and appears to outperform other screening measures.

Opioid-use disorder among patients on long-term opioid therapy: impact of final DSM-5 diagnostic criteria on prevalence and correlates.

Aims Previously, we estimated the prevalence and risk factors for prescription opioid-use disorder among outpatients on opioid therapy using the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and DSM-4 criteria. However, at the time, the DSM-5 criteria were not finalized. In the current study, we analyzed these data using the final DSM-5 criteria and compared these results. Methods Using electronic records from a large US health care system, we identified outpatients receiving five or more prescription orders for opioid therapy in the past 12 months for noncancer pain (mean prescription orders =10.72; standard deviation =4.96). In 2008, we completed diagnostic interviews with 705 of these patients using the DSM-4 criteria. In the current study, we reassessed these results using the final DSM-5 criteria. Results The lifetime prevalence of DSM-5 opioid-use disorders using the final DSM-5 criteria was 58.7% for no or few symptoms (<2), 28.1% for mild symptoms (2–3), 9.7% for moderate symptoms (4–5), and 3.5% for severe symptoms (six or more). Thus, the lifetime prevalence of “any” prescription opioid-use disorder in this cohort was 41.3% (95% confidence interval [CI] =37.6–45.0). A comparison to the DSM-4 criteria indicated that the majority of patients with lifetime DSM-4 opioid dependence were now classified as having mild opioid-use disorder, based on the DSM-5 criteria (53.6%; 95% CI =44.1–62.8). In ordinal logistic regression predicting no/few, mild, moderate, and severe opioid-use disorder, the best predictors were age <65 years, current pain impairment, trouble sleeping, suicidal thoughts, anxiety disorders, illicit drug use, and history of substance abuse treatment. Conclusion Given the final DSM-5 criteria, including the elimination of tolerance and withdrawal, inclusion of craving and abuse symptoms, and introduction of a new graded severity classification, the prevalence of opioid-use disorders has changed, while many of the DSM-4 risk factors for opioid dependence were similar. To our knowledge, this is one of the first studies to compare the final results for DSM-5 versus DSM-4 prescription opioid-use disorders among a high-risk patient population.

The New York PTSD Risk Score for Assessment of Psychological Trauma: Male and Female Versions

We previously developed a new posttraumatic stress disorder (PTSD) screening instrument-the New York PTSD Risk Score (NYPRS). Since research suggests different PTSD risk factors and outcomes for men and women, in the current study we assessed the suitability of male and female versions of this screening instrument among 3298 adults exposed to traumatic events. Using diagnostic test methods, including receiver operating characteristic (ROC) curve and bootstrap techniques, we examined different prediction domains, including core PTSD symptoms, trauma exposures, sleep disturbances, depression symptoms, and other measures to assess PTSD prediction models for men and women. While the original NYPRS worked well in predicting PTSD, significant interaction was detected by gender, suggesting that separate models are warranted for men and women. Model comparisons suggested that while the overall results appeared robust, prediction results differed by gender. For example, for women, core PTSD symptoms contributed more to the prediction score than for men. For men, depression symptoms, sleep disturbance, and trauma exposure contributed more to the prediction score. Men also had higher cut-off scores for PTSD compared to women. There were other gender-specific differences as well. The NYPRS is a screener that appears to be effective in predicting PTSD status among at-risk populations. However, consistent with other medical research, this instrument appears to require male and female versions to be the most effective.