Update on Alcohol, Other Drugs, and Health

1. Update on Alcohol, Other Drugs, and Health May–June 2014 www.aodhealth.org

2. Studies on Interventions & Assessments www.aodhealth.org 2

3. Implementation of Screening and Brief Intervention with Fidelity in Trauma Centers: Challenging but Not Impossible Zatzick D, Donovan DM, Jurkovich G, et al. Addiction. 2014;109:754–765. Summary by Peter D. Friedmann, MD, MPH www.aodhealth.org 3

4. Objectives/Methods This study randomized 20 trauma centers either to receive enhanced training in motivational interviewing (MI) for nursing and social work screening and brief intervention (SBI) providers (1 day of training and 4 30-minute follow-up coaching sessions), or to no additional training for SBI staff (control). To assess MI skills, providers from both groups participated in 7 20-minute standardized telephone MI sessions with patient-actors, and the sessions were scored using a coding system. www.aodhealth.org 4

5. Objectives/Methods (cont’d) The study then enrolled 878 in-patient trauma patients with positive blood alcohol levels who were assessed for alcohol consumption and consequences (using the AUDIT) at the initial trauma visit and at 6- and 12-month follow-up. www.aodhealth.org 5

6. Results Providers who received the training demonstrated greater MI skills and spent twice as much time at the bedside delivering alcohol SBI than those who did not. The rates of hazardous alcohol use declined in both groups, but the MI group experienced an 8% greater reduction and had a greater increase in days abstinent over the follow-up year. The MI had a greater effect (15%) on hazardous alcohol use in patients without traumatic brain injury (TBI). www.aodhealth.org 6

7. Comments Implementation of SBI with fidelity in health care settings is challenging, but this study shows that even brief training of providers can have a positive clinical effect. If these findings generalize to the 30 million patients who present with traumatic injury annually in the US, the reductions in alcohol use—particularly among patients without TBI—would have an important population impact. However, replication and dissemination of the intensive training, practice, and coaching required might also prove challenging but not impossible. www.aodhealth.org 7

8. Predictors of Sustained Heavy Episodic Drinking Among Young Adults Wellman RJ, Contreras GA, Dugas EN, et al. Alcohol Clin Exp Res. 2014;38(5):1409–1415. Summary by Kevin L. Kraemer, MD, MSc www.aodhealth.org 8

9. Objectives To assess predictors of sustained heavy episodic drinking during the young adult years, researchers analyzed data from 2 assessments (average ages 20 and 24 years, respectively) of 609 participants, who at the first assessment reported heavy episodic drinking (defined as ≥5 alcoholic beverages on at least 1 occasion in the past year). Participants who reported heavy episodic drinking at both assessments were categorized as “sustainers,” whereas those who reported it at the first assessment only were categorized as “stoppers.” www.aodhealth.org 9

10. Results Of all participants, 85% were categorized as “sustainers” and 15% as “stoppers.” “Sustainers” were more likely to be younger, male, less educated, younger at first drink, have higher frequency of heavy episodic drinking at a younger age, and to report greater novelty seeking and impulsivity. Among “sustainers,” 20% had heavy episodic drinking weekly, 44% monthly, and 36% less than monthly. A higher frequency of heavy episodic drinking at the second assessment was predicted by similar factors as above, with the addition of depressive symptoms at an earlier age. www.aodhealth.org 10

11. Comments This study identified factors associated with sustained heavy episodic drinking during young adulthood that may be useful for identifying those at greatest risk. Future research should assess whether frequent heavy drinking and alcohol use disorders are “sustained” at this same level. The more salient finding may be that 77% of young adults in the study reported heavy episodic drinking and 85% of those sustained some level of it over 4 years. This suggests that all young adults should be screened for unhealthy alcohol use. www.aodhealth.org 11

12. No Clear Advantage of In-Person Versus Computer-Based Brief Interventions for Illicit Drug Use Schwartz RP, Gryczynski J, Mitchell SG, et al. Addiction. 2014;109(7):1091–1098. Summary by Nicolas Bertholet, MD, MSc www.aodhealth.org 12

13. Objectives/Methods The implementation of screening, brief intervention, and referral to treatment for illicit drug use in primary care has been supported by the US government despite a clear evidence base, and several barriers to delivery exist, notably medical providers’ time constraints or the need to hire behavioral health counselors. These barriers may be overcome with the use of computer-based brief interventions. www.aodhealth.org 13

14. Objectives/Methods (cont’d) Researchers compared computer-based with in-person brief interventions in a parallel randomized controlled trial among 360 adult primary care patients with Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) scores of 4–26, indicating “moderate risk” drug use. At baseline, 88% of patients scored in the moderate risk range for marijuana use, 28% for alcohol, 20% for opioids, 18% for cocaine, 12% for sedatives, and 11% for amphetamines or methamphetamines. www.aodhealth.org 14

15. Results There was no change in the overall prevalence of drug-positive hair tests from baseline to 3 months (62% positive at both baseline and follow-up, no difference by treatment group). At 3 months, there were no differences in global ASSIST drug use scores or hair tests for drug use between participants who received the in-person and those who received the computer-based brief interventions. There were significant advantages for the computer-based over the in-person brief intervention for specific ASSIST scores for marijuana use (mean difference = -1.73 [n = 314]) and cocaine use (mean difference = -4.48 [n = 66]). No differences were observed on other specific ASSIST scores (alcohol, amphetamines or methamphetamines, sedatives, or opioids). www.aodhealth.org 15

16. Comments By comparing two modes of brief intervention delivery, this study did not demonstrate efficacy of screening and brief intervention for drug use or the superiority of an in-person or computer-based intervention. Additional evidence of the efficacy of screening and brief intervention for drug use, independent of its delivery mode, is still needed. www.aodhealth.org 16

17. Patients at Risk for Opioid Overdose can be Identified through Prescription Drug Monitoring Programs Baumblatt JA, Wiedeman C, Dunn JR, et al. JAMA Intern Med. 2014;174(5):796–801. Summary by Darius A. Rastegar, MD www.aodhealth.org 17

18. Objectives/Methods Prescription opioid overdose deaths have increased dramatically in the U.S. in recent years. To address this problem, most states have established prescription drug monitoring programs (PDMP). Researchers used data from the Tennessee PDMP to compare individuals who had an opioid-related death in 2009/2010 with randomly selected age and sex-matched controls who had also received at least one opioid prescription in the year prior to the death of the matched case. www.aodhealth.org 18

19. Results Each year, approximately 2 million Tennessee residents filled an opioid prescription, nearly one-third of the state population. Rates increased from 2007 to 2011 and were higher for women and for people in rural counties. There were 932 opioid-related deaths during the 24 months studied; 592 (64%) were patients in the PDMP. Opioid-related deaths were associated with having 4 or more prescribers (adjusted odds ratio [aOR], 6.5), using 4 or more pharmacies (aOR, 6.0), and receiving more than 100 mg of morphine milligram equivalents daily (aOR, 11.2); 55% of individuals who died had at least 1 of these risk factors and 6% had all 3. 19 www.aodhealth.org

20. Comments This study confirms prior observations that dose prescribed and number of prescribers and pharmacies are associated with an increased risk of opioid overdose. The number of individuals at risk steadily increased during this time period despite the availability of the PDMP, suggesting that access to this data alone does not change practitioner behavior. www.aodhealth.org 20

21. Chiodo LM, Delany-Black V, Sokol RJ, et al.Alcohol Clin Exp Res. 2014;38(5):1401–1408.Summary by Kevin L. Kraemer, MD, MSc What is the Optimal T-ACE Screening Cut-Point for At-Risk Alcohol Use in Pregnant Women? www.aodhealth.org 21

22. Objectives/Methods The T-ACE* screener was developed to detect at-risk alcohol use among pregnant women; however, in some settings the usual cut-point of ≥2 points may produce false-positives. * T-ACE screener: Tolerance – “How many drinks does it take to make you feel high?” (2 points for “2 or more drinks”); Annoy – “Has anybody ever annoyed you by complaining about your drinking?” (1 point for “Yes”); Cut Down – “Have you ever felt you ought to cut down on your drinking?” (1 point for “Yes”); Eye-opener – “Have you ever needed a drink first thing in the morning to get going?” (1 point for “Yes”). A T-ACE score of ≥3 is labeled “TACER-3” by the authors of the report. 22 www.aodhealth.org

23. Objectives/Methods (cont’d) To assess the potential advantage of increasing the T-ACE cut-point to 3 points, researchers administered the T-ACE to 239 urban-dwelling African-American pregnant women (mean age = 25 years; gestational age at screen = 23 weeks) at their first prenatal visit and compared different T-ACE scores for detecting alcohol use at conception, at the first prenatal visit, and across pregnancy. Alcohol use was measured by validated semi-structured interview. www.aodhealth.org 23

24. Results Of all participants, 42% had a T-ACE score of ≥2 and 12% had a T-ACE of ≥3. Participants with a T-ACE score of ≥3 were significantly more likely to have greater mean daily alcohol consumption and consumption on a drinking day at conception, the first prenatal visit, and across pregnancy than participants with a T-ACE equal to 2 (30% of participants), and those with a T-ACE of <2. 24 www.aodhealth.org

25. Comments This study found that women in this cohort with a T-ACE score of ≥3 points reported higher levels of alcohol use at several key points in pregnancy than those with lower scores. Unfortunately, the study’s implications for screening in the prenatal setting are not clear because an “at-risk” alcohol use screening target was not defined; the main comparison T-ACE cut-point was a score equal to 2 points rather than ≥2; and the usual screening tool measures of sensitivity, specificity, positive predictive value, and negative predictive value were not reported. Regardless, it remains important to identify and address any drinking during pregnancy to reduce the risk for fetal alcohol effects. www.aodhealth.org 25

26. Studies on Health Outcomes www.aodhealth.org 26

27. Methadone Results in Longer Treatment Retention than Buprenorphine; Higher Doses are Associated with Longer Retention for both Medications Hser Y, Saxon AJ, Huang D et al. Addiction.2014;109:79–87. Summary by Alexander Y. Walley, MD, MSc www.aodhealth.org 27

28. Objectives/Methods Previous studies have demonstrated similar effects of methadone and buprenorphine in reducing heroin use, but worse treatment retention among patients receiving buprenorphine. Many treatment providers cap buprenorphine doses at 16 mg because neuroimaging studies show high opioid receptor occupancy at that dose level, and some insurers discourage higher doses. Researchers conducted a 24-week multi-site open-label randomized controlled trial of buprenorphine versus methadone among 1267 subjects with opioid use disorder to measure retention in treatment. Medications were administered daily (except Sundays and holidays) by staff at opioid treatment programs. www.aodhealth.org

29. Results At 24 weeks, 74% of the patients receiving methadone remained in treatment (mean days = 141), versus 46% of those receiving buprenorphine (mean days = 104). Within the first 30 days, 25% of the patients receiving buprenorphine versus 8% of those receiving methadone dropped out of treatment. www.aodhealth.org 29

30. Results (cont’d) • For both methadone and buprenorphine patients, higher dose was associated with more time in treatment. • For methadone, doses of ≥60 mg resulted in retention rates of >80%, whereas rates for doses of ≤40 mg were <40%. • For buprenorphine, doses of 30–32 mg resulted in retention rates close to 60%, whereas rates for doses of ≤10 mg were <20%. • During the first 9 weeks of treatment, opioid positive urine results were lower in the buprenorphine versus methadone groups (odds ratio, 0.63), but were similar for weeks 10–24 at approximately 40% in both groups. www.aodhealth.org 30

31. Comments This study demonstrated substantially better treatment retention for methadone compared with buprenorphine. Furthermore, retention was better at higher doses for both medications. Dose limits on buprenorphine at 16 mg should be reconsidered and warrant examination in controlled trials. www.aodhealth.org 31

32. Baggio S, N’Goran AA, Deline S, et al.Addiction. 2014;109(6):937–945.Summary by Peter D. Friedmann, MD, MPH Symptoms—Not Frequency of Use—Predict Adverse Health Effects Associated with Cannabis Use in Young Men www.aodhealth.org 32

33. Objectives/Methods This prospective cohort study examined cannabis use and self-reported health issues among 5084 men in their early twenties over an average of 15 months follow-up. Researchers used the Cannabis Use Disorder Identification Test (CUDIT) to measure symptoms of cannabis use disorder; the Major Depressive Inventory to measure depression; and the Short-Form Health Survey (SF-12) to measure physical and mental health. Health consequences included accident/injury, emergency department admission, suicide attempt, need for medical treatment, overnight hospitalization, and outpatient surgery. www.aodhealth.org 33

34. Results Of all participants, 62% reported no cannabis use; 23% had continuing use throughout the study; 8% initiated use during the follow-up period; and 7% had use at baseline and then stopped. Among the 1149 participants who continued cannabis use, 49% reported monthly use or less, and 16% daily or almost daily. They averaged 7 symptoms of cannabis use disorder on the CUDIT. In cross-lagged longitudinal models, the number of symptoms of cannabis use disorder—not the frequency of use—predicted depression, other mental health, and physical health consequences over follow-up. www.aodhealth.org 34

35. Comments Without intervention, the pattern of cannabis use is stable among young men and daily use is common. In assessing the risk of developing health problems, a formal assessment of the number of symptoms of cannabis use disorder has greater prognostic value than the frequency or magnitude of cannabis use. Whether these findings generalize to women and more diverse populations, and how to use them in a targeted intervention, will require further study. www.aodhealth.org 35

36. Maintenance Therapy as Harm Reduction: Reducing Overdose Deaths with Opioid Agonist Treatment Volkow ND, Frieden TR, Hyde PS, Cha SS. N Engl J Med. 2014;370(22):2063–2066. Summary by Jeanette M. Tetrault, MD www.aodhealth.org 36

37. Objectives/Methods In this perspective piece, Nora Volkow, MD, the Director of the National Institute on Drug Abuse (NIDA), and colleagues from the Substance Abuse and Mental Health Services Administration, the Centers for Disease Control and Prevention, and the Centers for Medicare and Medicaid Services outline some of the efforts made by multiple agencies to reduce harmful opioid use and safeguard legitimate and appropriate access to opioid agonist treatment (OAT). www.aodhealth.org

38. Results There are a number of barriers contributing to the underutilization of and poor access to OAT: A lack of trained providers as well as misunderstandings about addiction pharmacotherapy, including the notion that OAT simply replaces one addiction with another, abstinence-based treatment models, and systematic under-dosing of OAT. Policy barriers, including dosage limits, annual or lifetime medication limits, prior authorization and reauthorization requirements, minimal coverage of counseling, “fail first” criteria, and lack of coverage of certain OAT by commercial insurance plans. Department of Health and Human Services agencies are working collaboratively to reduce these barriers by improving utilization of and expanding access to OAT along with other efforts to reduce opioid overdoses. www.aodhealth.org 38

39. Comments Implementation of the Affordable Care Act along with the Mental Health Parity and Addiction Equity Act will increase access to addiction treatment services for many Americans. One aspect of reducing opioid overdose deaths is to improve utilization of and access to OAT, which is recognized as a priority area by many federal agencies. However, to be successful, these efforts require buy-in from the medical community as a whole. www.aodhealth.org 39

40. Buprenorphine Treatment: A Missed Opportunity to Offer Smoking Cessation Treatment Nahvi S, Blackstock O, Sohler NL, et al. J Subst Abuse Treat. 2014 [Epub ahead of print]. doi:10.1016/j.jsat.2014.04.001. Summary by Jeanette M. Tetrault, MD 40 www.aodhealth.org

41. Objectives/Methods Patients with opioid use disorder are three-to-four times more likely than the general population to have tobacco use, yet smoking cessation treatment is rarely offered in substance use treatment settings. Office-based buprenorphine treatment provides a unique opportunity to engage patient populations with a high prevalence of tobacco use disorder. The authors of this study investigated smoking status, prescription of smoking cessation medications, and factors associated with receipt of smoking cessation medications among 319 patients treated for opioid use disorder in an office-based buprenorphine treatment program over a 5-year period. 41 www.aodhealth.org

42. Results Of the sample, 67% smoked at initiation of buprenorphine treatment; 16% were prescribed smoking cessation medications. Buprenorphine treatment retention at 6 months was associated with prescription of smoking cessation medications (25% of retained patients versus 10% of non-retained patients were prescribed medications for smoking cessation). 42 www.aodhealth.org

43. Comments Although tobacco use is common among patients with opioid use disorder at buprenorphine treatment initiation, documentation of both smoking status and motivation to quit throughout treatment—as well as provision of medications for smoking cessation—are uncommon. This represents a missed opportunity to make an impact on a highly prevalent disease that has widespread consequences. www.aodhealth.org 43

44. Heavy Episodic Drinking Greatly Increases Mortality Risk Among People with Low-Risk Alcohol Use Holahan CJ, Schutte KK, Brennan PL, et al. Alcohol Clin Exp Res. 2014;38(5):1432–1438. Summary by R. Curtis Ellison, MD www.aodhealth.org 44

45. Objectives/Methods An association between heavy episodic drinking and adverse health outcomes has been demonstrated in epidemiologic studies for decades. This study evaluated total mortality among 446 people aged 55–65 with an average consumption of ≤½ drink in a day for women or ≤2 for men, comparing those with heavy episodic drinking* (N=74) with those without (N=372). * Defined as ≥4 drinks in an occasion for women and ≥5 for men. www.aodhealth.org 45

46. Results Compared with subjects who engaged in heavy episodic drinking, those who did not were significantly higher in socio-economic status and were less likely to smoke, or have depressive symptoms or obesity. In analyses adjusted for potential confounders, subjects with heavy episodic drinking had more than 2 times higher odds of 20-year mortality than those without heavy episodic drinking. www.aodhealth.org 46

47. Comments The results of this study support previous findings of an association between heavy episodic drinking and mortality. However, the study had some weaknesses: There were relatively few participants with heavy episodic drinking in the analysis; and There were no data on potential changes in drinking habits over 20 years. A key implication is that simply knowing a subject’s average consumption is inadequate for classification; details on patterns of drinking are crucial. www.aodhealth.org 47

48. Underreporting of Alcohol Intake Affects the Relation of Alcohol to the Risk of Cancer Klatsky AL, Udaltsova N, Li Y, et al. Cancer Causes Control. 2014;25(6):693–699. Summary by R. Curtis Ellison, MD www.aodhealth.org 48

49. Objectives/Methods People with certain adverse health effects who report very low levels of alcohol consumption are often assumed to be underreporting their intake. Investigators reviewed 127,176 patients’ medical records for diseases and conditions that are known to occur predominantly in people with heavy alcohol use (e.g., liver cirrhosis, alcoholic neuropathy, and alcoholism). www.aodhealth.org 49

50. Objectives/Methods (cont’d) Subjects with such diagnoses who reported “light” (average <1 drink in a day) or “moderate” (average 1–2 drinks in a day) alcohol use were considered to be “likely underreporters” of their alcohol intake (18%). Subjects reporting the same levels of consumption with no evidence of risky alcohol use in their records (47%) were classified as “unlikely underreporters.” During an average follow-up period of 18 years, 14,880 subjects developed cancer. There were 23,363 subjects who reported “light” or “moderate” alcohol consumption. www.aodhealth.org 50