- Email: [email protected]
Increased cortisol levels are associated with low treatment retention in crack cocaine users
Addictive Behaviors 103 (2020) 106260
Contents lists available at ScienceDirect
Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
Increased cortisol levels are associated with low treatment retention in crack cocaine users
T
Karina P. Ligabuea,1, Jaqueline B. Schucha,b,1, Juliana N. Scherera, Felipe Ornella,b, Vinícius S. Roglioa,b, Vanessa Assunçãoa, Fernando P. Rebelattoa,b, Maria Paz Hildalgoc,d, ⁎ Flavio Pechanskya,b,d, Felix Kesslera,b,d, Lisia von Diemena,b,d, a
Center for Drug and Alcohol Research and Collaborating Center on Alcohol and Drugs, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil b Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil c Laboratory of Chronobiology and Sleep, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil d Department of Psychiatry and Legal Medicine, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
H I GH L IG H T S
is a negative correlation between morning cortisol and inpatient treatment time. • There history of SUD seems to moderate the relationship between cortisol and treatment retention. • Family • Crack cocaine users with higher cortisol levels presented worse treatment retention.
A R T I C LE I N FO
A B S T R A C T
Keywords: Substance use disorder Crack cocaine Cortisol Treatment retention Hypothalamus-pituitary-adrenal axis Psychiatric disorders
Background: Dysregulation of the hypothalamic–pituitaryadrenal (HPA) axis has been associated with craving and early relapse among individuals with substance use disorders. However, no association has been postulated regarding treatment retention and prognosis in crack cocaine users. Objective: Our aim was to investigate the association between morning salivary cortisol levels and treatment retention in crack cocaine users. Methods: 44 male crack cocaine users were recruited from a detoxification unit. Saliva collection was performed in the morning of the second treatment day. Substance use profile was assessed using the Addiction Severity Index. Results: The median length of stay in inpatient treatment was 7 days (IQR 3–16). Treatment retention was associated with cortisol levels (r = −0.324; p = 0.032), especially in the group with positive family history. Moreover, treatment retention was correlated with age (r = 0.333, p = 0.027), and number of days of tobacco use (r = 0.332, p = 0.028) and crack use (r = 0.327, p = 0.031). A Cox regression model was performed and showed that inpatients with above normal cortisol levels (≥0.69 µg/dL) presented a worse prognostic related to treatment retention (HR = 2.39, CI95% 1.1–5.1, p = 0.024). Conclusion: Several factors could contribute to increased cortisol levels in these patients, e.g. craving, dysregulation of the HPA axis, chronic drug use, stress due to confinement, and substance abstinence. Nevertheless, our findings could guide further studies about new biomarkers in crack cocaine use disorder, since HPA axis dysregulation at the time of treatment admittance may be a prognostic marker for treatment retention.
1. Introduction Treatment of individuals with psychoactive substance use disorders
(SUD) is considered one of the greatest challenges in psychiatry, mainly due to the complexity of factors that lead to their development and maintenance. Crack cocaine users usually show poor prognosis,
⁎
Corresponding author at: Rua Professor Álvaro Alvim, 400, 90420-020, Porto Alegre, RS, Brazil. E-mail addresses: [email protected], [email protected] (L. von Diemen). 1 These authors contributed equally to this study. https://doi.org/10.1016/j.addbeh.2019.106260 Received 15 May 2019; Received in revised form 13 November 2019; Accepted 15 December 2019 Available online 23 December 2019 0306-4603/ © 2019 Published by Elsevier Ltd.
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
2. Methods
including low treatment efficacy (i.e.: premature discharge, treatment retention, treatment dropout) and high relapse risk (Back et al., 2010; Barnaby & Gibson, 2008; Ferreira et al., 2012; Szupszynski, Sartes, Andretta, & Oliveira, 2014). The identification of biomarkers associated with treatment response has led to personalized intervention in several areas of medicine (Vaughan, 2013). In SUD, although incipient, studies focused on finding biomarkers that are related to or could predict prognosis or treatment response have been prioritized (Volkow, Koob, & Baler, 2015). The hypothalamic pituitary adrenal axis (HPA) is deeply involved in stress response, and has been studied extensively in psychiatric disorders (Zorn et al., 2017) and addictive behaviors (Stephens & Wand, 2012). Cortisol is the main stress hormone that regulates the HPA axis, and its production and responsiveness are factors involved in several mental disorders. The cortisol responsiveness is correlated to the activity of the mesolimbic dopaminergic pathway (Wand et al., 2007), endorsing its role in addictive behaviors. Cortisol has also effects on learning and memory, mainly influencing consolidation processes (van Stegeren, 2009). In this sense, evidence shows that after drug stimulus, the evocation of conditioned responses could aid in the maintenance of drug use (Carter & Tiffany, 1999). Overall, stress system has been consistently associated with craving and drug addiction severity, and could have also effects on prognostic and treatment retention (Majewska, 2002; Manetti, Cavagnini, Martino, & Ambrogio, 2014). For instance, cortisol administration was associated with reduced craving in heroin users, but only in low-dose heroin (Walter et al., 2015). Salivary cortisol levels have been reported as an accessible biomarker for identifying changes in stress response in physical and mental illness, including SUD. Increased cortisol levels have been associated with a substance use (Badrick, Kirschbaum, & Kumari, 2007), withdrawal symptoms (Cohen, al’Absi, & Collins, 2004; Vescovi, Coiro, Volpi, & Passeri, 1992) and early relapse related to drug use (Back et al., 2010; Raby et al., 2014). In addition, upregulation of the HPA axis, which is depicted by increased ACTH levels, measured at baseline, in a resting state, and with cue exposure, has been associated with substance use and relapse among individuals with SUD (Mendelson, Teoh, Mello, Ellingboe, & Rhoades, 1992; Sinha, 2011). Although many studies have evidenced the relationship between cortisol and addiction, there is a lack of studies evaluating if cortisol could predict the treatment retention or efficacy in chronic crack cocaine users. Since cortisol was previously associated with craving and consolidation processes, we suggest that modifications in the cortisol levels could be associated with premature discharge, fact that we observed frequently among crack cocaine users (Barnaby & Gibson, 2008). Studies point out that one of the predictors of successful addiction outcomes and clinical improvement in substance abuse is a longer duration of treatment (Hubbard, Craddock, & Anderson, 2003; Simpson, Joe, & Brown, 1997). Hospitalization days are associated with treatment retention, since patients who spend more time in hospital are more likely to evolve and have a more significant clinical improvement (Simpson et al., 1997). Furthermore, previous studies showed that presence of SUD together with positive family history for addiction could increase cortisol levels (Dai, Thavundayil, Santella, & Gianoulakis, 2007). In fact, children with parents with SUD present HPA changes prior to substance use, implying that family history could be a predisposing factor for altered cortisol response (Lovallo, 2006; Stephens & Wand, 2012). Therefore, our aim was to verify whether morning salivary cortisol levels, together with family history of SUD and substance use pattern, were associated with treatment retention of crack cocaine inpatients during detoxification treatment.
2.1. Sample selection Inpatients were recruited from January to September 2016 at the Addiction Psychiatry Unit of the Hospital de Clínicas de Porto Alegre (HCPA), a teaching hospital in the southernmost state capital of Brazil that provides free public services. The facility’s treatment program is specialized in SUD and reserved for male volunteers, which means that patients can request discharge at any time. The therapeutic strategies offered during the program are based on previously established standard activities for all patients. While in the inpatient program, patients cannot use any type of psychoactive substance, including tobacco, or use the internet or telephone (calls may be made only under the supervision of an assistant team member). Upon admittance (1st day of treatment), every patient is evaluated by a psychiatrist, a nurse and a nutritionist and must provide a urine sample for cocaine detection, as well as perform a breathalyzer test. During the first 48 h, patients are restricted to their room, including meals. During this period, they have contact only with the hospital’s technical and research teams and, at most, another patient sharing the same room. Mealtimes are 8:00 am for breakfast, 11:50 am for lunch, 5:50 pm for dinner and 9:30 pm supper. Hypercaloric or hyperproteic diets are provided according to the patient’s needs. The patients were invited to participate in the present study if they met the following inclusion criteria: crack cocaine users seeking treatment for SUD who were at least 18 years of age and who provided written informed consent. A minimum stay of two days in inpatient treatment was also mandatory for inclusion to guarantee at least two days of abstinence from any psychoactive substance. Individuals codependent on substances other than alcohol or nicotine, individuals with cognitive impairment, individuals with mouth injuries that involved active bleeding and individuals diagnosed with HIV or diabetes were excluded from the study. Of the 88 patients admitted during January and September 2016, 58 fulfilled the inclusion criteria and agreed to participate in the study. However, of these, two were excluded due to a late HIV diagnosis, 11 were excluded for donating saliva samples that could not be analyzed due to impurities, and one was excluded due to early discharge. Thus, the final sample included 44 patients. 2.2. Ethics This study was approved by the HCPA Ethics Committee (number 15-0234). Written informed consent was obtained from all subjects. 2.3. Procedures On the first day after admission, patients meeting the inclusion criteria were invited to participate in the study. Those who accepted were assessed by trained research assistants through interviews between the second and fifth day of hospitalization. All saliva samples were collected on the 2nd day after admission under the supervision of a lead investigator using a SaliCap Set salivary cortisol collection kit (IBL International, RE69995), which is approved for use by the HCPA and determines cortisol levels through a non-invasive quantitative detection technique involving SaliCap Tubes, straws and adhesive labels. Patients were asked to have fasted for at least 30 min and not to have brushed their teeth at least two hours prior to sample collection. Furthermore, prior to sample collection, the subjects rinsed their mouth with water to avoid collecting other substances or interferents (e.g. food). Collection occurred between 8 and 9 AM (at least one hour after waking) to avoid interfering with the cortisol awakening response (the maximum cortisol levels in plasma), which occurs 30–45 min after waking. 2
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
2.4. Instruments and clinical assessment
Table 1 Demographic characteristics, drug use profile, psychiatric comorbidities, and impatient treatment retention among the sample of crack-cocaine users.
Psychiatric information was assessed using the Structured Clinical Interview for DSM Disorders – SCID I (Del-Ben et al., 2001). However, 12 patients did not complete this evaluation due to their limited stay in detoxification treatment. Data related to drug use was assessed using version 6 of the Addiction Severity Index – ASI-6 (Kessler et al., 2012). The number of days in detoxification treatment and other clinical characteristics were assessed using standard medical records. Moreover, family history of SUD (1st degree) could not be determined for one patient, since he requested to be discharged before completing the instrument that collects this information and no related data could be found in his patient record.
Total Sample (n = 44) Agea Marital Statusb Married Single Family historyb Yes No Instruction levelb None Elementary School High School Drug use profile Years of crack usea Crack usec,* Alcohol usec,* Marijuana usec,* Tobacco useb,* Psychiatric comorbiditiesb Major Depressive Episode Substance-induced Mood Disorder Psychotic Symptoms Post-Traumatic Stress Disorder Social Phobia Generalized Anxiety Disorder Treatment retention (days)c
2.5. Salivary cortisol analysis Salivary cortisol levels were measured at the HCPA Pathology Department, following the hospital’s guidelines and standard protocol. After collection, samples were transported to the laboratory under refrigeration and immediately centrifuged at 1000g for two minutes. The supernatant was aliquoted and stored in −80 °C until assay testing. Cortisol levels were measured by electrochemiluminescence (Elecsys and Cobas analyzers®, Roche), using a commercial protocol and following the manufacturer instructions. Previous studies validate and corroborate the results from this technique as similar to others, such as immunoassays (i.e.: enzyme-linked immunosorbent assay) (Elbüken et al., 2014; Saiyudthong, Suwannarat, Trongwongsa, & Srisurapanon, 2010). According to the Pathology Department recommendation, the technical reference value for normal salivary cortisol is < 0.69 µg/dL in the morning (8–10 AM). The minimum detect limit was 0.018 µg/dL.
34.4 ± 8.6 5 (14.3) 30 (85.7) 28 (65.1) 15 (34.9) 8 (18.2) 20 (45.5) 16 (36.4) 9.2 ± 6.2 17.5 [0–30] 0.5 [0–7.5] 0 [0–10] 35 (79.5) 25 (78.1) 21 (65.6) 10 (31.3) 5 (15.6) 13 (40.6) 7 (21.9) 7 [3–16]
*Number of days of use in the last 30 days. n = 32 for psychiatric comorbidities. a Mean ± standard deviation. b Absolute frequency (%). c Median [interquartile range].
2.6. Statistical analysis
and substance-induced mood disorder (65.6%) being the most prevalent, followed by social phobia (40.6%).
Statistical analyses were performed in SPSS version 18. Histograms and the Shapiro-Wilk test were used to test the normality of quantitative variables. Mann-Whitney or Kruskal-Wallis tests were used to analyze cortisol levels and treatment retention between groups (i.e.: presence or absence of psychiatric comorbidities). Correlations between cortisol levels, treatment retention and other continuous variables were determined using the Spearman coefficient. In order to test the effect of morning cortisol levels as a predictor on treatment retention (i.e.: number of days in inpatient treatment or hospitalization days) we performed a survival analysis. We used Kaplan-Meier with log-rank test to investigate bivariate associations. All patients had discharge at some time, so there is no censored data. For this analysis, the sample was divided into two groups according to basal cortisol level using as cutoff the normal salivary cortisol level (following the guideline from the HCPA Pathology Department): under 0.69 µg/dL (considered normal) and over 0.69 µg/dL. Variables associated with the primary outcome in the bivariate analysis for the total sample (n = 44) were included as covariates in a multivariate Cox proportional-hazard model.
3.2. Treatment retention The median length of stay in inpatient treatment was 7 days, and the interquartile range was 3–16 (Table 1). More than 70% of patients requested to be discharged before medical recommendation. The number of days in inpatient treatment was correlated with age (r = 0.333, p = 0.027), and with the number of days of tobacco use (r = 0.332, p = 0.028) and crack use (r = 0.327, p = 0.031). Moreover, an association between social phobia and treatment retention was found, given that patients diagnosed with social phobia stayed in treatment longer than the others (25 days; IQR 8–44 vs. 7 days; IQR 2–12, p = 0.002). No other significant differences related to hospitalization days were found.
3.3. Cortisol levels
3. Results
The median cortisol levels were 0.57 µg/dL (IQR 0.78) (Fig. 1A). A significant negative correlation was found between cortisol levels and number of days in inpatient treatment (r = −0.324, p = 0.032; Fig. 1B), i.e. the higher the cortisol level, the shorter the treatment stay. No other data was associated with morning cortisol levels, except family history (p = 0.047). In order to verify if family history could moderate the relationship between cortisol levels and treatment retention, we compared patients with and without family history of SUD. Our results demonstrated that the correlation remained significant only in the group with positive family history (r = −0.391, p = 0.039) (Fig. 1B).
3.1. Demographic characteristics, drug use profiles, psychiatric comorbidities, and treatment retention Demographic characteristics, drug use profile, psychiatric comorbidities, and hospitalization days of the sample are presented in Table 1. In summary, the sample consisted of young adult males (mean age 34 years) who were, for the most part, single (85.7%) and had little education (63.7% completed less than 8 years of school). About 68% of the subjects had a family history of SUD. The patients averaged 9.2 years of crack use. There was a high prevalence of psychiatric comorbidities in crack inpatients, with major depressive episode (78.1%) 3
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Fig. 1. Basal morning salivary cortisol levels. (A) Salivary cortisol levels in crack cocaine users (dashed line represents the median value and dotted lines, interquartile range values), (B) overall correlation between cortisol levels and treatment retention (n = 44) and according to family history of SUD (presence – n = 28 or absence – n = 15).
3.4. Survival analysis The Kaplan-Meier estimates for treatment retention were significantly different for both cortisol levels (< 0.69 µg/dL: Md = 8, IC95% 3.8–12.2; ≥0.69 µg/dL: Md = 3, IC95% 0–7; p = 0.013) and family history of SUD (Yes: Md = 8, IC95% 2.8–13.2; No: Md = 4, IC95% 0.2–7.8; p = 0.027). To further analyze the influence of cortisol levels in treatment retention, we performed a multivariate Cox proportionalhazard model analysis. Crack use in the last 30 days and age were included in the Cox regression, considering its association with treatment retention. Tobacco use in the last 30 days was not included to avoid multicollinearity, since this variable was correlated to crack use in the last 30 days. Family history of SUD was also included in Cox regression due to the association with cortisol levels. It was observed that individuals with above normal cortisol levels (≥0.69 µg/dL) presented a worse prognostic related to treatment retention (HR = 2.39, CI95% 1.1–5.1, p = 0.024). The other statistics are presented in Table 2, and the survival curves are showed in Fig. 2.
4. Discussion This is the first study to evaluate cortisol levels as a potential biomarker of inpatient treatment retention among crack cocaine users. We found a negative correlation between basal salivary cortisol levels and treatment retention, which was consistent with our initial hypothesis. Further analysis reveals that this correlation remained significant only in the group with positive family history. Moreover, through survival analyses, we could estimate the association between cortisol levels in hospital admission and treatment retention in a specialized unit for drug addiction. Taking into account the relationship between cortisol
Fig. 2. Cox survival curves for treatment retention according to basal morning salivary cortisol levels in crack cocaine users (n = 43).
Table 2 Cox proportional-hazards model results for treatment retention time (days).
Cortisol levels (≥0.69) Family history of SUD (yes) Crack cocaine use in the last 30 days Age
Reg. Coef.
SE
Wald-Statistic
HR
p-value
95% CI
0.87 −0.43 −0.02 −0.05
0.39 0.41 0.01 0.02
5.10 1.09 1.49 7.32
2.39 0.65 0.98 0.95
0.024 0.297 0.222 0.007
1.12–5.08 0.29–1.46 0.96–1.01 0.91–0.99
Reg. Coef. = Cox regression coefficients. SE = Standard error. HR = Hazard ratio. 4
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
for management of early withdrawal symptoms, such as benzodiazepines, beta-blockers, and specific psychostimulants (i.e.: Modafinil). In addition, other drugs have shown good results in relapse prevention, such as GABAergic drugs (Diaper, Law, Melichar, 2014; Kampman, 2005, 2010). Further studies should better explore whether these drugs could have distinct effects on the treatment of addiction according to cortisol levels. Another interesting finding was the possible effect of family history of SUD in the relationship between cortisol levels and treatment retention. Previous studies have shown that stress responsivity and HPA axis function vary according to family history of alcoholism (Clarke et al., 2008; Dai et al., 2007). Moreover, numerous studies have demonstrated the influence of parental history of substance abuse and risk of adolescent drug use (Caudill, Hoffman, Hubbard, Flynn, & Luckey, 1994; Hoffmann & Cerbone, 2002; Weinberg, Rahdert, Colliver, & Glantz, 1998). Taken together, these factors lead us to question whether this influence also affects pathways involved in stress regulation. Our study involves certain limitations. First, we did not collect information on craving status, which could have been important since previous studies have associated craving with cortisol levels (Fox et al., 2005; Sinha, 2013; Sinha et al., 2006). Also, a separate evaluation of self-rated distress, linked to cortisol measure, could improve the assessment of stress disruption. Furthermore, we found that collecting data in a single setting reduces the possibility of comparison with other treatment types and determining whether this can influence treatment retention. Previous studies have also demonstrated that gender influences HPA axis regulation and cortisol release (Fox et al., 2006; Kudielka & Kirschbaum, 2005). Since our sample was exclusively male, we could not determine whether the same variables that influence treatment retention in men also influence women. Similarly, correlation analyses showed that all patients with negative family history of SUD had premature discharge. Therefore, it is possible that our results apply only to patients with a positive family history or even suggest a moderating effect of family history in the relationship of cortisol and treatment retention. Finally, SCID I was not applied to all individuals, and together with our small sample size may prevent us to detect other associations. On the other hand, our study has important strengths, such as the fact that all subjects underwent the same treatment protocol, which improves the consistency of the results and guarantees a controlled environment for data collection. We also highlight the fact that this study included a sample of severe drug users, who generally present very low rates of treatment retention. It is important to develop studies that consider the patients’ clinical reality to achieve results that can be applied to different treatment protocols. In conclusion, our results suggest an association between basal morning cortisol levels and the number of days in an inpatient detoxification program for crack users. The mechanism through which this occurs is still not clear in the literature. Several factors could contribute to elevated cortisol levels in these patients, e.g. craving, dysregulation of the HPA axis, chronic drug use, innate alteration of HPA axis function, stress due to confinement, substance abstinence, etc. However, even without identifying a specific cause, these initial findings could guide further studies about new biomarkers in crack cocaine use disorder, since HPA axis dysregulation at the time of treatment admittance may be a prognostic marker for treatment retention.
and the stress system, these results are in line with previous studies suggesting that dysregulation of the HPA axis could be involved in the pathophysiology of SUD (Koob & Kreek, 2007; Manetti et al., 2014). Drug escalation leads to activation of corticotropin-releasing factor in the extended amygdala (outside the hypothalamus). This is supported by functional magnetic resonance imaging studies showing that stress and drug exposure activate the mesolimbic and mesocortical dopamine projection areas (Briand & Blendy, 2010). Chronic stress affects the dorsolateral striatum-dependent habit system, which could accelerate the transition from goal-directed, voluntary drug use to dependent and compulsive drug-seeking behavior. Some authors have reported that stress or stress hormones could promote or induce a transition from voluntary drug use to dependence or abuse (Schwabe, Dickinson, & Wolf, 2011). The role of adrenocorticosteroids in cocaine reinforcement is further supported by reports showing that adrenalectomized rats did not self-administer cocaine (Uhart & Wand, 2009), although this effect could be reversed by the administration of corticosterone. Stress influences psychoactive substance use in rats, which, concomitantly with HPA axis dysregulation, is associated with hyperreactivity to stress and impulsivity in the face of new stimuli (Duffing, Greiner, Mathias, & Dougherty, 2014). Due to the complexity and limitations of stress studies in humans, most studies involve animals. Nevertheless, the findings observed in studies with substance users are similar to studies with animals. Increased stress-related corticotrophin and cortisol responses were associated with greater amount of cocaine use and shorter time to cocaine relapse (Sinha, Garcia, Paliwal, Kreek, & Rounsaville, 2006). Corroborating our findings, Daughters, Richards, Gorka, and Sinha (2009) have demonstrated an association between cortisol and treatment retention in addiction (Daughters et al., 2009). In this study, individuals with higher cortisol levels were linked to lower treatment retention. It is possible that the inability to tolerate distress may imply a shorter treatment duration or even increased the likelihood of dropout (Brown, Lejuez, Kahler, & Strong, 2002; Daughters et al., 2005). In our study, the inpatients were volunteers in an early withdrawal period and through cortisol levels assessment we could imply an activation of the HPA axis, which corroborates previous evidence. In the same direction, it was already demonstrated that acute withdrawal states reactivate the HPA axis (Koob & Kreek, 2007). Cocaine withdrawal may affect the activity of corticotropin-releasing factor, noradrenaline, and dopamine pathways of the extended amygdala and the mesocorticolimbic system and could alter the nature of the relationship between anxiety and stress-induced cocaine seeking at different times after withdrawal (Erb, 2010). A literature review has also explored findings regarding basal cortisol level alterations in chronic cocaine users (Mello & Mendelson, 1997). Overall, salivary cortisol concentrations were similar to other studies assessing substance users (De Jesus & Prapavessis, 2018; Raby et al., 2014). The association between basal cortisol level and treatment retention among users of this drug, especially the smoked variety, may indicate that craving is associated with stress, especially in a confined environment such as inpatient treatment. In addition, chronic cocaine use represents an lack of normal stress regulation and decreased treatment effects (Raby et al., 2014). We suggest that these phenomena could be predictors of early dropout, especially in early abstinence, when stress may be intensified by the hypodopaminergic condition resulting from drug withdrawal. Strategies focused on regulating intense stress are important elements in this stage of treatment. This could involve pharmacological and behavioral approaches. Patients with high stress levels may benefit from pharmacological interventions based on anxiety management medication, especially during early abstinence. In this sense, animal model studies have shown that anxiety associated with alcohol withdrawal appears to be reduced with the administration of non-selective corticotropin-releasing factor receptor antagonists (Becker, 2012). Currently, there are no FDA-approved drugs to treat cocaine addiction. But some medications seem to be promising
Role of Funding Sources This work was supported by the Fundo de Incentivo à Pesquisa do Hospital de Clínicas de Porto Alegre (FIPE) – grant number 15-0234; and in part by the Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior – Brasil (CAPES) – Finance Code 001. The funding source had no involvement in study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. 5
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Declaration of Competing Interest
Frequency of recent cocaine and alcohol use affects drug craving and associated responses to stress and drug-related cues. Psychoneuroendocrinology, 30(9), 880–891. https://doi.org/10.1016/j.psyneuen.2005.05.002. Hoffmann, J. P., & Cerbone, F. G. (2002). Parental substance use disorder and the risk of adolescent drug abuse: An event history analysis. Drug and Alcohol Dependence, 66, 255–264. https://doi.org/10.1016/S0376-8716(02)00005-4. Hubbard, R. L., Craddock, S. G., & Anderson, J. (2003). Overview of 5-year followup outcomes in the drug abuse treatment outcome studies (DATOS). Journal of Substance Abuse Treatment, 25(3), 125–134. https://doi.org/10.1016/s0740-5472(03)00130-2. Kampman, K. M. (2005). New medications for the treatment of cocaine dependence. Psychiatry (Edgmont), 2(12), 44–48. Kampman, K. M. (2010). What’s new in the treatment of cocaine addiction? Current Psychiatry Reports, 12(5), 441–447. Kessler, F., Cacciola, J., Alterman, A., Faller, S., Souza-Formigoni, M. L., Cruz, M. S., ... Pechansky, F. (2012). Psychometric properties of the sixth version of the Addiction Severity Index (ASI-6) in Brazil. Revista Brasileira de Psiquiatria, 34(1), 24–33. https:// doi.org/10.1590/S1516-44462012000100006. Koob, G., & Kreek, M. J. (2007). Stress, dysregulation of drug reward pathways, and the transition to drug dependence. American Journal of Psychiatry. https://doi.org/10. 1176/appi.ajp.2007.05030503. Kudielka, B. M., & Kirschbaum, C. (2005). Sex differences in HPA axis responses to stress: A review. Biological Psychology. https://doi.org/10.1016/j.biopsycho.2004.11.009. Lovallo, W. R. (2006). Cortisol secretion patterns in addiction and addiction risk. International Journal of Psychophysiology. https://doi.org/10.1016/j.ijpsycho.2005. 10.007. Majewska, M. D. (2002). HPA axis and stimulant dependence: An enigmatic relationship. Psychoneuroendocrinology, 27(1–2), 5–12. https://doi.org/10.1016/S0306-4530(01) 00033-6. Manetti, L., Cavagnini, F., Martino, E., & Ambrogio, A. (2014). Effects of cocaine on the hypothalamic-pituitary-adrenal axis. Journal of Endocrinological Investigation. https:// doi.org/10.1007/s40618-014-0091-8. Mello, N. K., & Mendelson, J. H. (1997). Cocaine’s effects on neuroendocrine systems: Clinical and preclinical studies. Pharmacology Biochemistry and Behavior, 57(3), 571–599. https://doi.org/10.1016/S0091-3057(96)00433-9. Mendelson, J. H., Teoh, S. K., Mello, N. K., Ellingboe, J., & Rhoades, E. (1992). Acute effects of cocaine on plasma adrenocorticotropic hormone, luteinizing hormone and prolactin levels in cocaine-dependent men. The Journal of Pharmacology and Experimental Therapeutics, 263(2), 505–509. Raby, W. N., Sanfilippo, L., Pavlicova, M., Carpenter, K. M., Glass, A., Onyemekwu, C., ... Nunes, E. V. (2014). Dysregulation of diurnal cortisol secretion affects abstinence induction during a lead-in period of a clinical trial for depressed cocaine-dependent patients. American Journal on Addictions, 23(1), 1–6. https://doi.org/10.1111/j.15210391.2013.12060.x. Saiyudthong, S., Suwannarat, P., Trongwongsa, T., & Srisurapanon, S. (2010). Comparison between ECL and ELISA for the detection of salivary Cortisol and determination of the relationship between Cortisol in saliva and serum measured by ECL. ScienceAsia, 36(2), 169–171. https://doi.org/10.2306/scienceasia1513-1874. 2010.36.169. Schwabe, L., Dickinson, A., & Wolf, O. T. (2011). Stress, habits, and drug addiction: A psychoneuroendocrinological perspective. Experimental and Clinical Psychopharmacology, 19(1), 53–63. https://doi.org/10.1037/a0022212. Simpson, D. D., Joe, G. W., & Brown, B. S. (1997). Treatment retention and follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11(4), 294–307. https://doi.org/10.1037/0893-164X.11.4.294. Sinha, R. (2011). New findings on biological factors predicting addiction relapse vulnerability. Current Psychiatry Reports. https://doi.org/10.1007/s11920-011-0224-0. Sinha, R. (2013). The clinical neurobiology of drug craving. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2013.05.001. Sinha, R., Garcia, M., Paliwal, P., Kreek, M. J., & Rounsaville, B. J. (2006). Stress-induced cocaine craving and hypothalamic-pituitary-adrenal responses are predictive of cocaine relapse outcomes. Archives of General Psychiatry, 63(3), 324–331. https://doi. org/10.1001/archpsyc.63.3.324. Stephens, M. A. C., & Wand, G. (2012). Stress and the HPA axis: Role of glucocorticoids in alcohol dependence. Alcohol Research: Current Reviews, 34(4), 468–483. https://doi. org/10.1016/j.psyneuen.2013.08.004. Szupszynski, K. P. D. R., Sartes, L. M. A., Andretta, I., & Oliveira, M.da. S. (2014). Cognitive and behavioral change processes in crack cocaine users in treatment. Revista Brasileira de Terapias Cognitivas, 10(1), 11–18. https://doi.org/10.5935/18085687.20140003. Uhart, M., & Wand, G. S. (2009). Stress, alcohol and drug interaction: An update of human research. Addiction Biology. https://doi.org/10.1111/j.1369-1600.2008. 00131.x. van Stegeren, A. H. (2009). Imaging stress effects on memory: A review of neuroimaging studies. The Canadian Journal of Psychiatry, 54(1), 16–27. https://doi.org/10.1177/ 070674370905400105. Vaughan, L. (2013). Biomarkers in acute medicine. Medicine (United Kingdom), 41(3), 136–141. https://doi.org/10.1016/j.mpmed.2013.01.001. Vescovi, P. P., Coiro, V., Volpi, R., & Passeri, M. (1992). Diurnal variations in plasma ACTH, cortisol and beta-endorphin levels in cocaine addicts. Hormone Research, 37(6), 221–224. https://doi.org/10.1159/000182316. Volkow, N. D., Koob, G., & Baler, R. (2015). Biomarkers in substance use disorders. ACS Chemical Neuroscience. https://doi.org/10.1021/acschemneuro.5b00067. Walter, M., Bentz, D., Schicktanz, N., Milnik, A., Aerni, A., Gerhards, C., ... de Quervain, D. (2015). Effects of cortisol administration on craving in heroin addicts. Translational Psychiatry, 5(7), e610. https://doi.org/10.1038/tp.2015.101. Wand, G. S., Oswald, L. M., McCaul, M. E., Wong, D. F., Johnson, E., Zhou, Y., ... Kumar,
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements We would like to thank all the volunteers for participating in this study. References Back, S. E., Hartwell, K., DeSantis, S. M., Saladin, M., McRae-Clark, A. L., Price, K. L., ... Brady, K. T. (2010). Reactivity to laboratory stress provocation predicts relapse to cocaine. Drug and Alcohol Dependence, 106(1), 21–27. https://doi.org/10.1016/j. drugalcdep.2009.07.016. Badrick, E., Kirschbaum, C., & Kumari, M. (2007). The relationship between smoking status and cortisol secretion. Journal of Clinical Endocrinology and Metabolism, 92(3), 819–824. https://doi.org/10.1210/jc.2006-2155. Barnaby, L., & Gibson, R. C. (2008). Factors affecting completion of a 28-day inpatient substance abuse treatment programme at the University Hospital of the West Indies. The West Indian Medical Journal, 57(4), 364–368. Becker, H. C. (2012). Effects of alcohol dependence and withdrawal on stress responsiveness and alcohol consumption. Alcohol Research: Current Reviews, 34(4), 448–458. Briand, L. A., & Blendy, J. A. (2010). Molecular and genetic substrates linking stress and addiction. Brain Research, 1314, 219–234. https://doi.org/10.1016/j.brainres.2009. 11.002. Brown, R. A., Lejuez, C. W., Kahler, C. W., & Strong, D. R. (2002). Distress tolerance and duration of past smoking cessation attempts. Journal of Abnormal Psychology, 111(1), 180–185. Carter, B. L., & Tiffany, S. T. (1999). Meta-analysis of cue-reactivity in addiction research. Addiction (Abingdon, England), 94(3), 327–340. Caudill, B. D., Hoffman, J. A., Hubbard, R. L., Flynn, P. M., & Luckey, J. W. (1994). Parental history of substance abuse as a risk factor in predicting crack smokers’ substance use, illegal activities, and psychiatric status. The American Journal of Drug and Alcohol Abuse, 20(3), 341–354. https://doi.org/10.3109/00952999409106019. Clarke, T. K., Treutlein, J., Zimmermann, U. S., Kiefer, F., Skowronek, M. H., Rietschel, M., ... Schumann, G. (2008). HPA-axis activity in alcoholism: Examples for a geneenvironment interaction. Addiction Biology. https://doi.org/10.1111/j.1369-1600. 2007.00084.x. Cohen, L. M., al’Absi, M., & Collins, F. L. (2004). Salivary cortisol concentrations are associated with acute nicotine withdrawal. Addictive Behaviors, 29(8), 1673–1678. https://doi.org/10.1016/j.addbeh.2004.02.059. Dai, X., Thavundayil, J., Santella, S., & Gianoulakis, C. (2007). Response of the HPA-axis to alcohol and stress as a function of alcohol dependence and family history of alcoholism. Psychoneuroendocrinology, 32(3), 293–305. https://doi.org/10.1016/j. psyneuen.2007.01.004. Daughters, S. B., Lejuez, C. W., Bornovalova, M. A., Kahler, C. W., Strong, D. R., & Brown, R. A. (2005). Distress tolerance as a predictor of early treatment dropout in a residential substance abuse treatment facility. Journal of Abnormal Psychology, 114(4), 729–734. https://doi.org/10.1037/0021-843X.114.4.729. Daughters, S. B., Richards, J. M., Gorka, S. M., & Sinha, R. (2009). HPA axis response to psychological stress and treatment retention in residential substance abuse treatment: A prospective study. Drug and Alcohol Dependence, 105(3), 202–208. https://doi.org/ 10.1016/j.drugalcdep.2009.06.026. De Jesus, S., & Prapavessis, H. (2018). Affect and cortisol mechanisms through which acute exercise attenuates cigarette cravings during a temporary quit attempt. Addictive Behaviors, 80, 82–88. https://doi.org/10.1016/j.addbeh.2018.01.007. Del-Ben, C. M., Vilela, J. A., de Crippa, J. S. A., Hallak, J. E., Labate, C. M., & Zuardi, A. W. (2001). Reliability of the Structured clinical interview for DSM-IV—Clinical Version translated into Portuguese. Revista Brasileira de Psiquiatria, 23(3), 159. Diaper, A. M., Law, F. D., & Melichar, J. K. (2014). Pharmacological strategies for detoxification. British Journal of Clinical Pharmacology, 77(2), 302–314. Duffing, T. M., Greiner, S. G., Mathias, C. W., & Dougherty, D. M. (2014). Stress, substance abuse, and addiction. Current Topics in Behavioral Neurosciences. Elbüken, G., Köse, K., Karaca, Z., Tanrıverdi, F., Ünlühizarcı, K., Zararsız, G., & Keleştimur, F. (2014). Comparison of electrochemiluminescence and enzyme immunoassay methods for the measurement of salivary cortisol. Turkish Journal of Endocrinology and Metabolism, 18(4), 111–115. https://doi.org/10.4274/tjem.2556. Erb, S. (2010). Evaluation of the relationship between anxiety during withdrawal and stress-induced reinstatement of cocaine seeking. Progress in NeuroPsychopharmacology and Biological Psychiatry, 34(5), 798–807. https://doi.org/10. 1016/j.pnpbp.2009.11.025. Ferreira, A. C. Z., Capistrano, F. C., Maftum, M. A., Kalinke, L. P., Lúcia, A., & Kirchhof, C. (2012). Caracterização de Internações de Dependentes Químicos em Uma Unidade de Reabilitação. Cogitare Enferm, 17(3), 444–451. Fox, H. C., Garcia, M., Kemp, K., Milivojevic, V., Kreek, M. J., & Sinha, R. (2006). Gender differences in cardiovascular and corticoadrenal response to stress and drug cues in cocaine dependent individuals. Psychopharmacology, 185(3), 348–357. https://doi. org/10.1007/s00213-005-0303-1. Fox, H. C., Talih, M., Malison, R., Anderson, G. M., Kreek, M. J., & Sinha, R. (2005).
6
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Adolescent Psychiatry, 37(3), 252–261. https://doi.org/10.1097/00004583199803000-00009. Zorn, J. V., Schür, R. R., Boks, M. P., Kahn, R. S., Joëls, M., & Vinkers, C. H. (2017). Cortisol stress reactivity across psychiatric disorders: A systematic review and metaanalysis. Psychoneuroendocrinology, 77, 25–36. https://doi.org/10.1016/j.psyneuen. 2016.11.036.
A. (2007). Association of amphetamine-induced striatal dopamine release and cortisol responses to psychological stress. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 32(11), 2310–2320. https://doi. org/10.1038/sj.npp.1301373. Weinberg, N. Z., Rahdert, E., Colliver, J. D., & Glantz, M. D. (1998). Adolescent substance abuse: A review of the past 10 years. Journal of the American Academy of Child and
7
Contents lists available at ScienceDirect
Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
Increased cortisol levels are associated with low treatment retention in crack cocaine users
T
Karina P. Ligabuea,1, Jaqueline B. Schucha,b,1, Juliana N. Scherera, Felipe Ornella,b, Vinícius S. Roglioa,b, Vanessa Assunçãoa, Fernando P. Rebelattoa,b, Maria Paz Hildalgoc,d, ⁎ Flavio Pechanskya,b,d, Felix Kesslera,b,d, Lisia von Diemena,b,d, a
Center for Drug and Alcohol Research and Collaborating Center on Alcohol and Drugs, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil b Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil c Laboratory of Chronobiology and Sleep, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil d Department of Psychiatry and Legal Medicine, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
H I GH L IG H T S
is a negative correlation between morning cortisol and inpatient treatment time. • There history of SUD seems to moderate the relationship between cortisol and treatment retention. • Family • Crack cocaine users with higher cortisol levels presented worse treatment retention.
A R T I C LE I N FO
A B S T R A C T
Keywords: Substance use disorder Crack cocaine Cortisol Treatment retention Hypothalamus-pituitary-adrenal axis Psychiatric disorders
Background: Dysregulation of the hypothalamic–pituitaryadrenal (HPA) axis has been associated with craving and early relapse among individuals with substance use disorders. However, no association has been postulated regarding treatment retention and prognosis in crack cocaine users. Objective: Our aim was to investigate the association between morning salivary cortisol levels and treatment retention in crack cocaine users. Methods: 44 male crack cocaine users were recruited from a detoxification unit. Saliva collection was performed in the morning of the second treatment day. Substance use profile was assessed using the Addiction Severity Index. Results: The median length of stay in inpatient treatment was 7 days (IQR 3–16). Treatment retention was associated with cortisol levels (r = −0.324; p = 0.032), especially in the group with positive family history. Moreover, treatment retention was correlated with age (r = 0.333, p = 0.027), and number of days of tobacco use (r = 0.332, p = 0.028) and crack use (r = 0.327, p = 0.031). A Cox regression model was performed and showed that inpatients with above normal cortisol levels (≥0.69 µg/dL) presented a worse prognostic related to treatment retention (HR = 2.39, CI95% 1.1–5.1, p = 0.024). Conclusion: Several factors could contribute to increased cortisol levels in these patients, e.g. craving, dysregulation of the HPA axis, chronic drug use, stress due to confinement, and substance abstinence. Nevertheless, our findings could guide further studies about new biomarkers in crack cocaine use disorder, since HPA axis dysregulation at the time of treatment admittance may be a prognostic marker for treatment retention.
1. Introduction Treatment of individuals with psychoactive substance use disorders
(SUD) is considered one of the greatest challenges in psychiatry, mainly due to the complexity of factors that lead to their development and maintenance. Crack cocaine users usually show poor prognosis,
⁎
Corresponding author at: Rua Professor Álvaro Alvim, 400, 90420-020, Porto Alegre, RS, Brazil. E-mail addresses: [email protected], [email protected] (L. von Diemen). 1 These authors contributed equally to this study. https://doi.org/10.1016/j.addbeh.2019.106260 Received 15 May 2019; Received in revised form 13 November 2019; Accepted 15 December 2019 Available online 23 December 2019 0306-4603/ © 2019 Published by Elsevier Ltd.
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
2. Methods
including low treatment efficacy (i.e.: premature discharge, treatment retention, treatment dropout) and high relapse risk (Back et al., 2010; Barnaby & Gibson, 2008; Ferreira et al., 2012; Szupszynski, Sartes, Andretta, & Oliveira, 2014). The identification of biomarkers associated with treatment response has led to personalized intervention in several areas of medicine (Vaughan, 2013). In SUD, although incipient, studies focused on finding biomarkers that are related to or could predict prognosis or treatment response have been prioritized (Volkow, Koob, & Baler, 2015). The hypothalamic pituitary adrenal axis (HPA) is deeply involved in stress response, and has been studied extensively in psychiatric disorders (Zorn et al., 2017) and addictive behaviors (Stephens & Wand, 2012). Cortisol is the main stress hormone that regulates the HPA axis, and its production and responsiveness are factors involved in several mental disorders. The cortisol responsiveness is correlated to the activity of the mesolimbic dopaminergic pathway (Wand et al., 2007), endorsing its role in addictive behaviors. Cortisol has also effects on learning and memory, mainly influencing consolidation processes (van Stegeren, 2009). In this sense, evidence shows that after drug stimulus, the evocation of conditioned responses could aid in the maintenance of drug use (Carter & Tiffany, 1999). Overall, stress system has been consistently associated with craving and drug addiction severity, and could have also effects on prognostic and treatment retention (Majewska, 2002; Manetti, Cavagnini, Martino, & Ambrogio, 2014). For instance, cortisol administration was associated with reduced craving in heroin users, but only in low-dose heroin (Walter et al., 2015). Salivary cortisol levels have been reported as an accessible biomarker for identifying changes in stress response in physical and mental illness, including SUD. Increased cortisol levels have been associated with a substance use (Badrick, Kirschbaum, & Kumari, 2007), withdrawal symptoms (Cohen, al’Absi, & Collins, 2004; Vescovi, Coiro, Volpi, & Passeri, 1992) and early relapse related to drug use (Back et al., 2010; Raby et al., 2014). In addition, upregulation of the HPA axis, which is depicted by increased ACTH levels, measured at baseline, in a resting state, and with cue exposure, has been associated with substance use and relapse among individuals with SUD (Mendelson, Teoh, Mello, Ellingboe, & Rhoades, 1992; Sinha, 2011). Although many studies have evidenced the relationship between cortisol and addiction, there is a lack of studies evaluating if cortisol could predict the treatment retention or efficacy in chronic crack cocaine users. Since cortisol was previously associated with craving and consolidation processes, we suggest that modifications in the cortisol levels could be associated with premature discharge, fact that we observed frequently among crack cocaine users (Barnaby & Gibson, 2008). Studies point out that one of the predictors of successful addiction outcomes and clinical improvement in substance abuse is a longer duration of treatment (Hubbard, Craddock, & Anderson, 2003; Simpson, Joe, & Brown, 1997). Hospitalization days are associated with treatment retention, since patients who spend more time in hospital are more likely to evolve and have a more significant clinical improvement (Simpson et al., 1997). Furthermore, previous studies showed that presence of SUD together with positive family history for addiction could increase cortisol levels (Dai, Thavundayil, Santella, & Gianoulakis, 2007). In fact, children with parents with SUD present HPA changes prior to substance use, implying that family history could be a predisposing factor for altered cortisol response (Lovallo, 2006; Stephens & Wand, 2012). Therefore, our aim was to verify whether morning salivary cortisol levels, together with family history of SUD and substance use pattern, were associated with treatment retention of crack cocaine inpatients during detoxification treatment.
2.1. Sample selection Inpatients were recruited from January to September 2016 at the Addiction Psychiatry Unit of the Hospital de Clínicas de Porto Alegre (HCPA), a teaching hospital in the southernmost state capital of Brazil that provides free public services. The facility’s treatment program is specialized in SUD and reserved for male volunteers, which means that patients can request discharge at any time. The therapeutic strategies offered during the program are based on previously established standard activities for all patients. While in the inpatient program, patients cannot use any type of psychoactive substance, including tobacco, or use the internet or telephone (calls may be made only under the supervision of an assistant team member). Upon admittance (1st day of treatment), every patient is evaluated by a psychiatrist, a nurse and a nutritionist and must provide a urine sample for cocaine detection, as well as perform a breathalyzer test. During the first 48 h, patients are restricted to their room, including meals. During this period, they have contact only with the hospital’s technical and research teams and, at most, another patient sharing the same room. Mealtimes are 8:00 am for breakfast, 11:50 am for lunch, 5:50 pm for dinner and 9:30 pm supper. Hypercaloric or hyperproteic diets are provided according to the patient’s needs. The patients were invited to participate in the present study if they met the following inclusion criteria: crack cocaine users seeking treatment for SUD who were at least 18 years of age and who provided written informed consent. A minimum stay of two days in inpatient treatment was also mandatory for inclusion to guarantee at least two days of abstinence from any psychoactive substance. Individuals codependent on substances other than alcohol or nicotine, individuals with cognitive impairment, individuals with mouth injuries that involved active bleeding and individuals diagnosed with HIV or diabetes were excluded from the study. Of the 88 patients admitted during January and September 2016, 58 fulfilled the inclusion criteria and agreed to participate in the study. However, of these, two were excluded due to a late HIV diagnosis, 11 were excluded for donating saliva samples that could not be analyzed due to impurities, and one was excluded due to early discharge. Thus, the final sample included 44 patients. 2.2. Ethics This study was approved by the HCPA Ethics Committee (number 15-0234). Written informed consent was obtained from all subjects. 2.3. Procedures On the first day after admission, patients meeting the inclusion criteria were invited to participate in the study. Those who accepted were assessed by trained research assistants through interviews between the second and fifth day of hospitalization. All saliva samples were collected on the 2nd day after admission under the supervision of a lead investigator using a SaliCap Set salivary cortisol collection kit (IBL International, RE69995), which is approved for use by the HCPA and determines cortisol levels through a non-invasive quantitative detection technique involving SaliCap Tubes, straws and adhesive labels. Patients were asked to have fasted for at least 30 min and not to have brushed their teeth at least two hours prior to sample collection. Furthermore, prior to sample collection, the subjects rinsed their mouth with water to avoid collecting other substances or interferents (e.g. food). Collection occurred between 8 and 9 AM (at least one hour after waking) to avoid interfering with the cortisol awakening response (the maximum cortisol levels in plasma), which occurs 30–45 min after waking. 2
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
2.4. Instruments and clinical assessment
Table 1 Demographic characteristics, drug use profile, psychiatric comorbidities, and impatient treatment retention among the sample of crack-cocaine users.
Psychiatric information was assessed using the Structured Clinical Interview for DSM Disorders – SCID I (Del-Ben et al., 2001). However, 12 patients did not complete this evaluation due to their limited stay in detoxification treatment. Data related to drug use was assessed using version 6 of the Addiction Severity Index – ASI-6 (Kessler et al., 2012). The number of days in detoxification treatment and other clinical characteristics were assessed using standard medical records. Moreover, family history of SUD (1st degree) could not be determined for one patient, since he requested to be discharged before completing the instrument that collects this information and no related data could be found in his patient record.
Total Sample (n = 44) Agea Marital Statusb Married Single Family historyb Yes No Instruction levelb None Elementary School High School Drug use profile Years of crack usea Crack usec,* Alcohol usec,* Marijuana usec,* Tobacco useb,* Psychiatric comorbiditiesb Major Depressive Episode Substance-induced Mood Disorder Psychotic Symptoms Post-Traumatic Stress Disorder Social Phobia Generalized Anxiety Disorder Treatment retention (days)c
2.5. Salivary cortisol analysis Salivary cortisol levels were measured at the HCPA Pathology Department, following the hospital’s guidelines and standard protocol. After collection, samples were transported to the laboratory under refrigeration and immediately centrifuged at 1000g for two minutes. The supernatant was aliquoted and stored in −80 °C until assay testing. Cortisol levels were measured by electrochemiluminescence (Elecsys and Cobas analyzers®, Roche), using a commercial protocol and following the manufacturer instructions. Previous studies validate and corroborate the results from this technique as similar to others, such as immunoassays (i.e.: enzyme-linked immunosorbent assay) (Elbüken et al., 2014; Saiyudthong, Suwannarat, Trongwongsa, & Srisurapanon, 2010). According to the Pathology Department recommendation, the technical reference value for normal salivary cortisol is < 0.69 µg/dL in the morning (8–10 AM). The minimum detect limit was 0.018 µg/dL.
34.4 ± 8.6 5 (14.3) 30 (85.7) 28 (65.1) 15 (34.9) 8 (18.2) 20 (45.5) 16 (36.4) 9.2 ± 6.2 17.5 [0–30] 0.5 [0–7.5] 0 [0–10] 35 (79.5) 25 (78.1) 21 (65.6) 10 (31.3) 5 (15.6) 13 (40.6) 7 (21.9) 7 [3–16]
*Number of days of use in the last 30 days. n = 32 for psychiatric comorbidities. a Mean ± standard deviation. b Absolute frequency (%). c Median [interquartile range].
2.6. Statistical analysis
and substance-induced mood disorder (65.6%) being the most prevalent, followed by social phobia (40.6%).
Statistical analyses were performed in SPSS version 18. Histograms and the Shapiro-Wilk test were used to test the normality of quantitative variables. Mann-Whitney or Kruskal-Wallis tests were used to analyze cortisol levels and treatment retention between groups (i.e.: presence or absence of psychiatric comorbidities). Correlations between cortisol levels, treatment retention and other continuous variables were determined using the Spearman coefficient. In order to test the effect of morning cortisol levels as a predictor on treatment retention (i.e.: number of days in inpatient treatment or hospitalization days) we performed a survival analysis. We used Kaplan-Meier with log-rank test to investigate bivariate associations. All patients had discharge at some time, so there is no censored data. For this analysis, the sample was divided into two groups according to basal cortisol level using as cutoff the normal salivary cortisol level (following the guideline from the HCPA Pathology Department): under 0.69 µg/dL (considered normal) and over 0.69 µg/dL. Variables associated with the primary outcome in the bivariate analysis for the total sample (n = 44) were included as covariates in a multivariate Cox proportional-hazard model.
3.2. Treatment retention The median length of stay in inpatient treatment was 7 days, and the interquartile range was 3–16 (Table 1). More than 70% of patients requested to be discharged before medical recommendation. The number of days in inpatient treatment was correlated with age (r = 0.333, p = 0.027), and with the number of days of tobacco use (r = 0.332, p = 0.028) and crack use (r = 0.327, p = 0.031). Moreover, an association between social phobia and treatment retention was found, given that patients diagnosed with social phobia stayed in treatment longer than the others (25 days; IQR 8–44 vs. 7 days; IQR 2–12, p = 0.002). No other significant differences related to hospitalization days were found.
3.3. Cortisol levels
3. Results
The median cortisol levels were 0.57 µg/dL (IQR 0.78) (Fig. 1A). A significant negative correlation was found between cortisol levels and number of days in inpatient treatment (r = −0.324, p = 0.032; Fig. 1B), i.e. the higher the cortisol level, the shorter the treatment stay. No other data was associated with morning cortisol levels, except family history (p = 0.047). In order to verify if family history could moderate the relationship between cortisol levels and treatment retention, we compared patients with and without family history of SUD. Our results demonstrated that the correlation remained significant only in the group with positive family history (r = −0.391, p = 0.039) (Fig. 1B).
3.1. Demographic characteristics, drug use profiles, psychiatric comorbidities, and treatment retention Demographic characteristics, drug use profile, psychiatric comorbidities, and hospitalization days of the sample are presented in Table 1. In summary, the sample consisted of young adult males (mean age 34 years) who were, for the most part, single (85.7%) and had little education (63.7% completed less than 8 years of school). About 68% of the subjects had a family history of SUD. The patients averaged 9.2 years of crack use. There was a high prevalence of psychiatric comorbidities in crack inpatients, with major depressive episode (78.1%) 3
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Fig. 1. Basal morning salivary cortisol levels. (A) Salivary cortisol levels in crack cocaine users (dashed line represents the median value and dotted lines, interquartile range values), (B) overall correlation between cortisol levels and treatment retention (n = 44) and according to family history of SUD (presence – n = 28 or absence – n = 15).
3.4. Survival analysis The Kaplan-Meier estimates for treatment retention were significantly different for both cortisol levels (< 0.69 µg/dL: Md = 8, IC95% 3.8–12.2; ≥0.69 µg/dL: Md = 3, IC95% 0–7; p = 0.013) and family history of SUD (Yes: Md = 8, IC95% 2.8–13.2; No: Md = 4, IC95% 0.2–7.8; p = 0.027). To further analyze the influence of cortisol levels in treatment retention, we performed a multivariate Cox proportionalhazard model analysis. Crack use in the last 30 days and age were included in the Cox regression, considering its association with treatment retention. Tobacco use in the last 30 days was not included to avoid multicollinearity, since this variable was correlated to crack use in the last 30 days. Family history of SUD was also included in Cox regression due to the association with cortisol levels. It was observed that individuals with above normal cortisol levels (≥0.69 µg/dL) presented a worse prognostic related to treatment retention (HR = 2.39, CI95% 1.1–5.1, p = 0.024). The other statistics are presented in Table 2, and the survival curves are showed in Fig. 2.
4. Discussion This is the first study to evaluate cortisol levels as a potential biomarker of inpatient treatment retention among crack cocaine users. We found a negative correlation between basal salivary cortisol levels and treatment retention, which was consistent with our initial hypothesis. Further analysis reveals that this correlation remained significant only in the group with positive family history. Moreover, through survival analyses, we could estimate the association between cortisol levels in hospital admission and treatment retention in a specialized unit for drug addiction. Taking into account the relationship between cortisol
Fig. 2. Cox survival curves for treatment retention according to basal morning salivary cortisol levels in crack cocaine users (n = 43).
Table 2 Cox proportional-hazards model results for treatment retention time (days).
Cortisol levels (≥0.69) Family history of SUD (yes) Crack cocaine use in the last 30 days Age
Reg. Coef.
SE
Wald-Statistic
HR
p-value
95% CI
0.87 −0.43 −0.02 −0.05
0.39 0.41 0.01 0.02
5.10 1.09 1.49 7.32
2.39 0.65 0.98 0.95
0.024 0.297 0.222 0.007
1.12–5.08 0.29–1.46 0.96–1.01 0.91–0.99
Reg. Coef. = Cox regression coefficients. SE = Standard error. HR = Hazard ratio. 4
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
for management of early withdrawal symptoms, such as benzodiazepines, beta-blockers, and specific psychostimulants (i.e.: Modafinil). In addition, other drugs have shown good results in relapse prevention, such as GABAergic drugs (Diaper, Law, Melichar, 2014; Kampman, 2005, 2010). Further studies should better explore whether these drugs could have distinct effects on the treatment of addiction according to cortisol levels. Another interesting finding was the possible effect of family history of SUD in the relationship between cortisol levels and treatment retention. Previous studies have shown that stress responsivity and HPA axis function vary according to family history of alcoholism (Clarke et al., 2008; Dai et al., 2007). Moreover, numerous studies have demonstrated the influence of parental history of substance abuse and risk of adolescent drug use (Caudill, Hoffman, Hubbard, Flynn, & Luckey, 1994; Hoffmann & Cerbone, 2002; Weinberg, Rahdert, Colliver, & Glantz, 1998). Taken together, these factors lead us to question whether this influence also affects pathways involved in stress regulation. Our study involves certain limitations. First, we did not collect information on craving status, which could have been important since previous studies have associated craving with cortisol levels (Fox et al., 2005; Sinha, 2013; Sinha et al., 2006). Also, a separate evaluation of self-rated distress, linked to cortisol measure, could improve the assessment of stress disruption. Furthermore, we found that collecting data in a single setting reduces the possibility of comparison with other treatment types and determining whether this can influence treatment retention. Previous studies have also demonstrated that gender influences HPA axis regulation and cortisol release (Fox et al., 2006; Kudielka & Kirschbaum, 2005). Since our sample was exclusively male, we could not determine whether the same variables that influence treatment retention in men also influence women. Similarly, correlation analyses showed that all patients with negative family history of SUD had premature discharge. Therefore, it is possible that our results apply only to patients with a positive family history or even suggest a moderating effect of family history in the relationship of cortisol and treatment retention. Finally, SCID I was not applied to all individuals, and together with our small sample size may prevent us to detect other associations. On the other hand, our study has important strengths, such as the fact that all subjects underwent the same treatment protocol, which improves the consistency of the results and guarantees a controlled environment for data collection. We also highlight the fact that this study included a sample of severe drug users, who generally present very low rates of treatment retention. It is important to develop studies that consider the patients’ clinical reality to achieve results that can be applied to different treatment protocols. In conclusion, our results suggest an association between basal morning cortisol levels and the number of days in an inpatient detoxification program for crack users. The mechanism through which this occurs is still not clear in the literature. Several factors could contribute to elevated cortisol levels in these patients, e.g. craving, dysregulation of the HPA axis, chronic drug use, innate alteration of HPA axis function, stress due to confinement, substance abstinence, etc. However, even without identifying a specific cause, these initial findings could guide further studies about new biomarkers in crack cocaine use disorder, since HPA axis dysregulation at the time of treatment admittance may be a prognostic marker for treatment retention.
and the stress system, these results are in line with previous studies suggesting that dysregulation of the HPA axis could be involved in the pathophysiology of SUD (Koob & Kreek, 2007; Manetti et al., 2014). Drug escalation leads to activation of corticotropin-releasing factor in the extended amygdala (outside the hypothalamus). This is supported by functional magnetic resonance imaging studies showing that stress and drug exposure activate the mesolimbic and mesocortical dopamine projection areas (Briand & Blendy, 2010). Chronic stress affects the dorsolateral striatum-dependent habit system, which could accelerate the transition from goal-directed, voluntary drug use to dependent and compulsive drug-seeking behavior. Some authors have reported that stress or stress hormones could promote or induce a transition from voluntary drug use to dependence or abuse (Schwabe, Dickinson, & Wolf, 2011). The role of adrenocorticosteroids in cocaine reinforcement is further supported by reports showing that adrenalectomized rats did not self-administer cocaine (Uhart & Wand, 2009), although this effect could be reversed by the administration of corticosterone. Stress influences psychoactive substance use in rats, which, concomitantly with HPA axis dysregulation, is associated with hyperreactivity to stress and impulsivity in the face of new stimuli (Duffing, Greiner, Mathias, & Dougherty, 2014). Due to the complexity and limitations of stress studies in humans, most studies involve animals. Nevertheless, the findings observed in studies with substance users are similar to studies with animals. Increased stress-related corticotrophin and cortisol responses were associated with greater amount of cocaine use and shorter time to cocaine relapse (Sinha, Garcia, Paliwal, Kreek, & Rounsaville, 2006). Corroborating our findings, Daughters, Richards, Gorka, and Sinha (2009) have demonstrated an association between cortisol and treatment retention in addiction (Daughters et al., 2009). In this study, individuals with higher cortisol levels were linked to lower treatment retention. It is possible that the inability to tolerate distress may imply a shorter treatment duration or even increased the likelihood of dropout (Brown, Lejuez, Kahler, & Strong, 2002; Daughters et al., 2005). In our study, the inpatients were volunteers in an early withdrawal period and through cortisol levels assessment we could imply an activation of the HPA axis, which corroborates previous evidence. In the same direction, it was already demonstrated that acute withdrawal states reactivate the HPA axis (Koob & Kreek, 2007). Cocaine withdrawal may affect the activity of corticotropin-releasing factor, noradrenaline, and dopamine pathways of the extended amygdala and the mesocorticolimbic system and could alter the nature of the relationship between anxiety and stress-induced cocaine seeking at different times after withdrawal (Erb, 2010). A literature review has also explored findings regarding basal cortisol level alterations in chronic cocaine users (Mello & Mendelson, 1997). Overall, salivary cortisol concentrations were similar to other studies assessing substance users (De Jesus & Prapavessis, 2018; Raby et al., 2014). The association between basal cortisol level and treatment retention among users of this drug, especially the smoked variety, may indicate that craving is associated with stress, especially in a confined environment such as inpatient treatment. In addition, chronic cocaine use represents an lack of normal stress regulation and decreased treatment effects (Raby et al., 2014). We suggest that these phenomena could be predictors of early dropout, especially in early abstinence, when stress may be intensified by the hypodopaminergic condition resulting from drug withdrawal. Strategies focused on regulating intense stress are important elements in this stage of treatment. This could involve pharmacological and behavioral approaches. Patients with high stress levels may benefit from pharmacological interventions based on anxiety management medication, especially during early abstinence. In this sense, animal model studies have shown that anxiety associated with alcohol withdrawal appears to be reduced with the administration of non-selective corticotropin-releasing factor receptor antagonists (Becker, 2012). Currently, there are no FDA-approved drugs to treat cocaine addiction. But some medications seem to be promising
Role of Funding Sources This work was supported by the Fundo de Incentivo à Pesquisa do Hospital de Clínicas de Porto Alegre (FIPE) – grant number 15-0234; and in part by the Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior – Brasil (CAPES) – Finance Code 001. The funding source had no involvement in study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. 5
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Declaration of Competing Interest
Frequency of recent cocaine and alcohol use affects drug craving and associated responses to stress and drug-related cues. Psychoneuroendocrinology, 30(9), 880–891. https://doi.org/10.1016/j.psyneuen.2005.05.002. Hoffmann, J. P., & Cerbone, F. G. (2002). Parental substance use disorder and the risk of adolescent drug abuse: An event history analysis. Drug and Alcohol Dependence, 66, 255–264. https://doi.org/10.1016/S0376-8716(02)00005-4. Hubbard, R. L., Craddock, S. G., & Anderson, J. (2003). Overview of 5-year followup outcomes in the drug abuse treatment outcome studies (DATOS). Journal of Substance Abuse Treatment, 25(3), 125–134. https://doi.org/10.1016/s0740-5472(03)00130-2. Kampman, K. M. (2005). New medications for the treatment of cocaine dependence. Psychiatry (Edgmont), 2(12), 44–48. Kampman, K. M. (2010). What’s new in the treatment of cocaine addiction? Current Psychiatry Reports, 12(5), 441–447. Kessler, F., Cacciola, J., Alterman, A., Faller, S., Souza-Formigoni, M. L., Cruz, M. S., ... Pechansky, F. (2012). Psychometric properties of the sixth version of the Addiction Severity Index (ASI-6) in Brazil. Revista Brasileira de Psiquiatria, 34(1), 24–33. https:// doi.org/10.1590/S1516-44462012000100006. Koob, G., & Kreek, M. J. (2007). Stress, dysregulation of drug reward pathways, and the transition to drug dependence. American Journal of Psychiatry. https://doi.org/10. 1176/appi.ajp.2007.05030503. Kudielka, B. M., & Kirschbaum, C. (2005). Sex differences in HPA axis responses to stress: A review. Biological Psychology. https://doi.org/10.1016/j.biopsycho.2004.11.009. Lovallo, W. R. (2006). Cortisol secretion patterns in addiction and addiction risk. International Journal of Psychophysiology. https://doi.org/10.1016/j.ijpsycho.2005. 10.007. Majewska, M. D. (2002). HPA axis and stimulant dependence: An enigmatic relationship. Psychoneuroendocrinology, 27(1–2), 5–12. https://doi.org/10.1016/S0306-4530(01) 00033-6. Manetti, L., Cavagnini, F., Martino, E., & Ambrogio, A. (2014). Effects of cocaine on the hypothalamic-pituitary-adrenal axis. Journal of Endocrinological Investigation. https:// doi.org/10.1007/s40618-014-0091-8. Mello, N. K., & Mendelson, J. H. (1997). Cocaine’s effects on neuroendocrine systems: Clinical and preclinical studies. Pharmacology Biochemistry and Behavior, 57(3), 571–599. https://doi.org/10.1016/S0091-3057(96)00433-9. Mendelson, J. H., Teoh, S. K., Mello, N. K., Ellingboe, J., & Rhoades, E. (1992). Acute effects of cocaine on plasma adrenocorticotropic hormone, luteinizing hormone and prolactin levels in cocaine-dependent men. The Journal of Pharmacology and Experimental Therapeutics, 263(2), 505–509. Raby, W. N., Sanfilippo, L., Pavlicova, M., Carpenter, K. M., Glass, A., Onyemekwu, C., ... Nunes, E. V. (2014). Dysregulation of diurnal cortisol secretion affects abstinence induction during a lead-in period of a clinical trial for depressed cocaine-dependent patients. American Journal on Addictions, 23(1), 1–6. https://doi.org/10.1111/j.15210391.2013.12060.x. Saiyudthong, S., Suwannarat, P., Trongwongsa, T., & Srisurapanon, S. (2010). Comparison between ECL and ELISA for the detection of salivary Cortisol and determination of the relationship between Cortisol in saliva and serum measured by ECL. ScienceAsia, 36(2), 169–171. https://doi.org/10.2306/scienceasia1513-1874. 2010.36.169. Schwabe, L., Dickinson, A., & Wolf, O. T. (2011). Stress, habits, and drug addiction: A psychoneuroendocrinological perspective. Experimental and Clinical Psychopharmacology, 19(1), 53–63. https://doi.org/10.1037/a0022212. Simpson, D. D., Joe, G. W., & Brown, B. S. (1997). Treatment retention and follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11(4), 294–307. https://doi.org/10.1037/0893-164X.11.4.294. Sinha, R. (2011). New findings on biological factors predicting addiction relapse vulnerability. Current Psychiatry Reports. https://doi.org/10.1007/s11920-011-0224-0. Sinha, R. (2013). The clinical neurobiology of drug craving. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2013.05.001. Sinha, R., Garcia, M., Paliwal, P., Kreek, M. J., & Rounsaville, B. J. (2006). Stress-induced cocaine craving and hypothalamic-pituitary-adrenal responses are predictive of cocaine relapse outcomes. Archives of General Psychiatry, 63(3), 324–331. https://doi. org/10.1001/archpsyc.63.3.324. Stephens, M. A. C., & Wand, G. (2012). Stress and the HPA axis: Role of glucocorticoids in alcohol dependence. Alcohol Research: Current Reviews, 34(4), 468–483. https://doi. org/10.1016/j.psyneuen.2013.08.004. Szupszynski, K. P. D. R., Sartes, L. M. A., Andretta, I., & Oliveira, M.da. S. (2014). Cognitive and behavioral change processes in crack cocaine users in treatment. Revista Brasileira de Terapias Cognitivas, 10(1), 11–18. https://doi.org/10.5935/18085687.20140003. Uhart, M., & Wand, G. S. (2009). Stress, alcohol and drug interaction: An update of human research. Addiction Biology. https://doi.org/10.1111/j.1369-1600.2008. 00131.x. van Stegeren, A. H. (2009). Imaging stress effects on memory: A review of neuroimaging studies. The Canadian Journal of Psychiatry, 54(1), 16–27. https://doi.org/10.1177/ 070674370905400105. Vaughan, L. (2013). Biomarkers in acute medicine. Medicine (United Kingdom), 41(3), 136–141. https://doi.org/10.1016/j.mpmed.2013.01.001. Vescovi, P. P., Coiro, V., Volpi, R., & Passeri, M. (1992). Diurnal variations in plasma ACTH, cortisol and beta-endorphin levels in cocaine addicts. Hormone Research, 37(6), 221–224. https://doi.org/10.1159/000182316. Volkow, N. D., Koob, G., & Baler, R. (2015). Biomarkers in substance use disorders. ACS Chemical Neuroscience. https://doi.org/10.1021/acschemneuro.5b00067. Walter, M., Bentz, D., Schicktanz, N., Milnik, A., Aerni, A., Gerhards, C., ... de Quervain, D. (2015). Effects of cortisol administration on craving in heroin addicts. Translational Psychiatry, 5(7), e610. https://doi.org/10.1038/tp.2015.101. Wand, G. S., Oswald, L. M., McCaul, M. E., Wong, D. F., Johnson, E., Zhou, Y., ... Kumar,
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements We would like to thank all the volunteers for participating in this study. References Back, S. E., Hartwell, K., DeSantis, S. M., Saladin, M., McRae-Clark, A. L., Price, K. L., ... Brady, K. T. (2010). Reactivity to laboratory stress provocation predicts relapse to cocaine. Drug and Alcohol Dependence, 106(1), 21–27. https://doi.org/10.1016/j. drugalcdep.2009.07.016. Badrick, E., Kirschbaum, C., & Kumari, M. (2007). The relationship between smoking status and cortisol secretion. Journal of Clinical Endocrinology and Metabolism, 92(3), 819–824. https://doi.org/10.1210/jc.2006-2155. Barnaby, L., & Gibson, R. C. (2008). Factors affecting completion of a 28-day inpatient substance abuse treatment programme at the University Hospital of the West Indies. The West Indian Medical Journal, 57(4), 364–368. Becker, H. C. (2012). Effects of alcohol dependence and withdrawal on stress responsiveness and alcohol consumption. Alcohol Research: Current Reviews, 34(4), 448–458. Briand, L. A., & Blendy, J. A. (2010). Molecular and genetic substrates linking stress and addiction. Brain Research, 1314, 219–234. https://doi.org/10.1016/j.brainres.2009. 11.002. Brown, R. A., Lejuez, C. W., Kahler, C. W., & Strong, D. R. (2002). Distress tolerance and duration of past smoking cessation attempts. Journal of Abnormal Psychology, 111(1), 180–185. Carter, B. L., & Tiffany, S. T. (1999). Meta-analysis of cue-reactivity in addiction research. Addiction (Abingdon, England), 94(3), 327–340. Caudill, B. D., Hoffman, J. A., Hubbard, R. L., Flynn, P. M., & Luckey, J. W. (1994). Parental history of substance abuse as a risk factor in predicting crack smokers’ substance use, illegal activities, and psychiatric status. The American Journal of Drug and Alcohol Abuse, 20(3), 341–354. https://doi.org/10.3109/00952999409106019. Clarke, T. K., Treutlein, J., Zimmermann, U. S., Kiefer, F., Skowronek, M. H., Rietschel, M., ... Schumann, G. (2008). HPA-axis activity in alcoholism: Examples for a geneenvironment interaction. Addiction Biology. https://doi.org/10.1111/j.1369-1600. 2007.00084.x. Cohen, L. M., al’Absi, M., & Collins, F. L. (2004). Salivary cortisol concentrations are associated with acute nicotine withdrawal. Addictive Behaviors, 29(8), 1673–1678. https://doi.org/10.1016/j.addbeh.2004.02.059. Dai, X., Thavundayil, J., Santella, S., & Gianoulakis, C. (2007). Response of the HPA-axis to alcohol and stress as a function of alcohol dependence and family history of alcoholism. Psychoneuroendocrinology, 32(3), 293–305. https://doi.org/10.1016/j. psyneuen.2007.01.004. Daughters, S. B., Lejuez, C. W., Bornovalova, M. A., Kahler, C. W., Strong, D. R., & Brown, R. A. (2005). Distress tolerance as a predictor of early treatment dropout in a residential substance abuse treatment facility. Journal of Abnormal Psychology, 114(4), 729–734. https://doi.org/10.1037/0021-843X.114.4.729. Daughters, S. B., Richards, J. M., Gorka, S. M., & Sinha, R. (2009). HPA axis response to psychological stress and treatment retention in residential substance abuse treatment: A prospective study. Drug and Alcohol Dependence, 105(3), 202–208. https://doi.org/ 10.1016/j.drugalcdep.2009.06.026. De Jesus, S., & Prapavessis, H. (2018). Affect and cortisol mechanisms through which acute exercise attenuates cigarette cravings during a temporary quit attempt. Addictive Behaviors, 80, 82–88. https://doi.org/10.1016/j.addbeh.2018.01.007. Del-Ben, C. M., Vilela, J. A., de Crippa, J. S. A., Hallak, J. E., Labate, C. M., & Zuardi, A. W. (2001). Reliability of the Structured clinical interview for DSM-IV—Clinical Version translated into Portuguese. Revista Brasileira de Psiquiatria, 23(3), 159. Diaper, A. M., Law, F. D., & Melichar, J. K. (2014). Pharmacological strategies for detoxification. British Journal of Clinical Pharmacology, 77(2), 302–314. Duffing, T. M., Greiner, S. G., Mathias, C. W., & Dougherty, D. M. (2014). Stress, substance abuse, and addiction. Current Topics in Behavioral Neurosciences. Elbüken, G., Köse, K., Karaca, Z., Tanrıverdi, F., Ünlühizarcı, K., Zararsız, G., & Keleştimur, F. (2014). Comparison of electrochemiluminescence and enzyme immunoassay methods for the measurement of salivary cortisol. Turkish Journal of Endocrinology and Metabolism, 18(4), 111–115. https://doi.org/10.4274/tjem.2556. Erb, S. (2010). Evaluation of the relationship between anxiety during withdrawal and stress-induced reinstatement of cocaine seeking. Progress in NeuroPsychopharmacology and Biological Psychiatry, 34(5), 798–807. https://doi.org/10. 1016/j.pnpbp.2009.11.025. Ferreira, A. C. Z., Capistrano, F. C., Maftum, M. A., Kalinke, L. P., Lúcia, A., & Kirchhof, C. (2012). Caracterização de Internações de Dependentes Químicos em Uma Unidade de Reabilitação. Cogitare Enferm, 17(3), 444–451. Fox, H. C., Garcia, M., Kemp, K., Milivojevic, V., Kreek, M. J., & Sinha, R. (2006). Gender differences in cardiovascular and corticoadrenal response to stress and drug cues in cocaine dependent individuals. Psychopharmacology, 185(3), 348–357. https://doi. org/10.1007/s00213-005-0303-1. Fox, H. C., Talih, M., Malison, R., Anderson, G. M., Kreek, M. J., & Sinha, R. (2005).
6
Addictive Behaviors 103 (2020) 106260
K.P. Ligabue, et al.
Adolescent Psychiatry, 37(3), 252–261. https://doi.org/10.1097/00004583199803000-00009. Zorn, J. V., Schür, R. R., Boks, M. P., Kahn, R. S., Joëls, M., & Vinkers, C. H. (2017). Cortisol stress reactivity across psychiatric disorders: A systematic review and metaanalysis. Psychoneuroendocrinology, 77, 25–36. https://doi.org/10.1016/j.psyneuen. 2016.11.036.
A. (2007). Association of amphetamine-induced striatal dopamine release and cortisol responses to psychological stress. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 32(11), 2310–2320. https://doi. org/10.1038/sj.npp.1301373. Weinberg, N. Z., Rahdert, E., Colliver, J. D., & Glantz, M. D. (1998). Adolescent substance abuse: A review of the past 10 years. Journal of the American Academy of Child and
7