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0145-6008/00/2407-1041$03.00/0 ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH

Vol. 24, No. 7 July 2000

Sertraline Treatment for Alcohol Dependence: Interactive Effects of Medication and Alcoholic Subtype

Helen M. Pettinati, Joseph R. Volpicelli, Henry R. Kranzler, Gary Luck, Margaret R. Rukstalis, and Avital Cnaan

Background Characteristic behaviors of some alcohol-dependent individuals, e.g., binge drinking, comorbid psychopathology, and some types of alcohol-related problems, have been linked to abnormalities in serotonergic neurotransmission. However, studies that have evaluated serotonergic pharmacotherapy for reducing drinking have yielded conflicting results. One explanation for these findings is a general failure to distinguish alcohol subgroups that may be differentiated on the basis of serotonergic abnormalities. How- ever, in 1996, Kranzler and colleagues reported that Type B alcoholics, who are characterized by high levels of premorbid vulnerability, alcohol dependence severity, and comorbid psychopathology, showed less favorable drinking outcomes in response to treatment with fluoxetine, a serotonin reuptake inhibitor, than with placebo. This medication effect was not seen in Type A alcoholics, i.e., those with lower riskiseverity of alcoholism and psychopathology. The aim of the present study was to explore the validity of differential responding by alcohol-dependent subtypes using the serotonin reuptake inhibitor, sertraline.

Methods: A k-means clustering procedure was applied to a sample of alcohol-dependent subjects enrolled in a 14-week, placebo-controlled trial of 200 mg/day of sertraline, classifying them into lower-riskl severity (Type A: n = 5 5 ) and higher-riskiseverity (Type B: n = 45) subgroups.

Results: A significant interaction between alcoholic subtype and medication condition was found, confirming the findings of Kranzler and colleagues that alcoholic subtypes responded differentially to serotonergic medication. Somewhat at variance with their results, however, the present study showed that the lower riskiseverity (Type A) subjects had more favorable outcomes when treated with sertraline compared to placebo.

Conclusions: Alcoholic subtypes differentially responded to sertraline when used as a treatment to reduce alcohol drinking, with one subtype having more favorable outcomes. Subtyping alcoholics may help to resolve conflicting findings in the literature on serotonergic treatment of alcohol dependence.

Key Words: Alcoholism, Alcoholic Subtypes, SSRI Pharmacotherapy, Sertraline.

EROTONIN (5-HT) DYSFUNCTION has been impli- S cated in alcohol dependence (Buydens-Branchey et al., 1989a,b; Heinz et al., 1998; Kranzler and Anton, 1994; Pettinati, 1996; Swann et al., 1999; Virkkunen and Linnoila, 1993) as well as in psychiatric disorders that frequently

From the Center for the Study of Addictions, Department of Psychiatry, University of Pennsylvania School of Medicine, and the Philadelphia Veterans Affairs Medical Center (H.M.P., J.R.V, G.L., M.R.R., A.C.), Philadelphia, Pennsylvania, and the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine (H. R.K), Farmington, Connecticut.

Received for publication November 23, 1999; accepted April 13, 2000. The work was supported by grants fiom the National Institute on Alcohol

Abuse and Alcoholism (ROl-AAO9544 to Dr. Pettinati and KO2-AA 00239 to Dr. Kranzler) and from the Veterans AfJairs Medical Center. PJzer, Inc. generous& donated sertraline and matching placebo.

Preliminay versions of these data were presented at the Annual Meeting of the Research Society on Alcoholism in Hilton Head, June 20-25, 1998, and at the Annual Meeting on the American College of Neuropsychopharmacology, Las Croabas, Puerto Rico, December 11-15, 1998.

Reprint requests: Helen Pettinati, Ph. D., Dept. of Psychiatry, University of Pennsylvania School of Medicine, Addiction Treatment Research Center, 3900 Chestnut Street, Philadelphia, PA 19104-61 78; Fax: 215-386-6770; E-mail: [email protected]

Copyright 0 2000 by the Research Society on Alcoholism.

Alcohol CIin Exp Res, Vol24, No 7, 2000: pp 1041-1049

co-occur with alcohol dependence, including mood, personality (Coccaro et al., 1989; Maes and Meltzer 1995; Moeller et al., 1996), and impulse control disorders (Coccaro and Murphy, 1990). Consequently, one pharmacologic approach to treating alcohol dependence and the comorbid conditions commonly associated with it has been the use of selective serotonin reuptake inhibitors (SSRIs).

5-HT PHARMACOLOGY AND ALCOHOL CONSUMPTION

Animal studies have consistently demonstrated reductions in alcohol consumption with the administration of a variety of 5-HT agonists (Higley et al., 1998; Meyers and Quarfordt, 1991; Naranjo et al., 1986). Results from human studies, however, have been conflicting. A series of placebo-controlled trials of SSRIs (including zimelidine, citalopram, viqualine, and fluoxetine) consistently showed modest reductions in alcohol consumption in heavy social drinkers (Naranjo et al., 1984, 1987, 1989, 1990, 1992). These studies were of short duration and not directly relevant to the use of SSRIs for the treatment of patients with alcohol dependence. Subsequently, in treatment-seeking alcohol-dependent patients, three out of four studies of

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fluoxetine have had negative results (Gorelick and Pardes, 1992; Kabel and Petty, 1996; Kranzler et al., 1995). Of the three negative studies, the largest one randomly assigned 101 alcohol-dependent patients to a maximum of 60 mglday fluoxetine or placebo for 12 weeks. In this study, both medication and placebo groups reduced drinking by over 75%, and there was no advantage for fluoxetine over placebo (Kranzler et al., 1995). The one positive treatment study found that fluoxetine provided a significant advantage in the treatment of 51 patients with current depression who also met diagnostic criteria for alcohol dependence. Fluoxetine-treated patients reduced the number of depres- sive symptoms and their frequency of drinking, compared to placebo-treated patients (Cornelius et al., 1997).

ALCOHOLIC SUBTYPES: 5-HT DYSFUNCTION AND SSRI PHARMACOTHERAPY

Alcohol dependence is a complex, multidimensional disorder (Babor et a]., 1988; Kranzler et al., 1996), and the extent of potential 5-HT abnormalities is likely to vary across patients. One example of a homogeneous alcohol subgroup of higher-riskheverity are those whom Babor and colleagues (1992) have called “Type B” alcoholics. These individuals have earlier-onset alcoholism, more childhood risk factors, sociopathy, psychopathology (e.g., depression), alcohol-related problems, severe alcohol dependence, and polydrug use than individuals with less severe alcohol dependence, whom Babor and colleagues (1992) have called “Type A’ alcoholics. Type A alcoholics are relatively un- complicated in their history and presentation, despite high levels of alcohol consumption.

Many of the characteristics associated with Type B alcohol dependence have been identified with 5-HT dysfunction (Mann et al., 1996; Pettinati, 1996; Pettinati et al., 2000). For example, early-onset alcoholism has been linked to abnormalities in 5-HT transmission (Benkelfat et al., 1991; Buydens-Branchey et al., 1989a, 1989b; Fils-Aime et al., 1996; Krystal et al., 1996; 1994; Swann et al., 1999). Also, in studies of nonalcoholics, depression, lack of impulse control, and sociopathy have been linked to 5-HT dysfunction (Coscina, 1997; Lewis, 1991; Maes and Meltzer, 1995).

To date, there has been only one published study that has examined whether alcoholic subtypes respond differentially to 5-HT pharmacotherapy. Kranzler and colleagues (1996) evaluated drinking outcomes for Type A and B alcoholics who had participated in a 12-week placebo-controlled trial of fluoxetine (60 mg/day). They found that Type B (higher- riskheverity) alcoholics had worse drinking outcomes with fluoxetine than placebo. In this study, there were no differences in drinking outcomes in Type A (lower risldseverity) alcoholics taking fluoxetine or placebo. Thus, although it had been suggested that 5-HT agonist treatment may ame- liorate 5-HT dysfunction (Kranzler and Anton, 1994; Pet- tinati, 1996), the results of this clinical study raised the

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question of whether SSRIs could aggravate 5-HT dysfunction in some types of alcoholics (Kranzler et al., 1996; Sahakian et al., 1986; Virkkunen and Narvanen, 1987). These findings warranted further evaluation using a different SSRI.

The overall goal of the present study was to evaluate the efficacy of the SSRI, sertraline, in the treatment of patients with alcohol dependence, subgrouped on the basis of presumed 5-HT dysfunction or absence thereof. A univariate approach to subgrouping based on etiologic variables was a possibility for reflecting presumed 5-HT dysfunction, e.g., early versus late onset: younger versus older than 25 years at the time of first intoxication (Irwin et al., 1990; Johnson et al., 2000). However, the multidimensional approach of the A/B typology had intuitive appeal because it aggregated multiple systems affected by 5-HT pathways, and permitted a test of the finding by Kranzler and colleagues (1996) that alcoholic subtypes responded differentially to serotonergic medication.

METHODS

After medical and psychiatric evaluation and clinical laboratory testing, 100 subjects who met DSM-111-R criteria for alcohol dependence (based on administration of the Structured Clinical Interview for DSM-III-R, Spitzer et al., 1992) were enrolled in a double-blind, placebo-controlled treatment trial of sertraline. A brief description of the methods used in the clinical trial follows. (For a detailed description, see Pettinati et al., alcohol dependence, manuscript submitted for publication, 1999).

This was a prospective study comparing drinking outcomes of alcohol- dependent subjects, with or without lifetime depression, who were treated with 200 mgiday of sertraline or four placebo capsulesiday for 14 weeks. Comparable numbers of subjects with (n = 53) and without (n = 47) a lifetime DSM-111-R diagnosis of major depression were recruited to participate in the study. Randomization to sertraline or placebo was done separately within each of these groups. All subjects received weekly sessions of Twelve-Step Facilitation (TSF) therapy (Nowinski et al., 1995). The TSF was manual guided and delivered by clinicians with Masters’ degrees who worked in the same setting as the medical practitioners dispensing and monitoring the pharmacotherapy for this study. The clinicians were supervised by a senior therapist who also checked audiotapings of the sessions for adherence to the TSF model. Adequate information with respect to pretreatment profiles and relevant outcome measures permitted the inclusion of 100% of the sample in the subtyping procedure described in the next section.

Subjects

One hundred outpatients, 52 men and 48 women, were recruited through advertisements and referrals. All subjects provided written in- formed consent to participate in the study. Obtaining eligibility and pretreatment measures took approximately 2 weeks, planned to maximize a period of abstinence prior to randomization. All subjects were completely abstinent from alcohol for at least 3 days before randomization. Subjects were 18 years or older, met DSM-111-R criteria for alcohol dependence, were actively drinking in the preceding 30 days, and were seeking treatment. Patients were excluded if they met criteria for a current substance dependence disorder other than alcohol or nicotine, had a serious or unstable physical illness, had a history of dementia or psychosis, or cur- rently needed other psychotropic medications.

SERTRALINE TREATMENT FOR ALCOHOL DEPENDENCE 1043

Treatment Procedures

Sertraline or an inactive placebo was provided in identical, two-toned 50-mg capsules in blistercards. Subjects were instructed to start the first few days with one capsule each morning. The dosage was increased by one capsule every 3-5 days, as tolerated, until a maximum daily dosage of 200 mgiday of sertraline or four placebo capsules was attained. The maximum daily dosage typically was achieved within 2 weeks and then maintained until the final 2 weeks of double-blind treatment, at which time tapering was initiated. For those who could not tolerate the maximum daily dosage of 200 mgiday, downward dosage adjustments were made to retain the subject in the trial. Also included in the daily dose was 100 mg of riboflavin, with urine samples collected weekly and examined for the presence of riboflavin, which provided a less subjective measure of compliance with the medication regimen (Del Boca et al., 1996). Subjects who regularly took vitamin supplements were asked to take only the riboflavin- free vitamins that we supplied over the course of the study. Subjects were seen weekly by a physician to monitor adverse events and medication compliance; and by a counselor for Twelve-Step Facilitation (TSF) sessions. All subjects were encouraged to attend community-based support groups as part of their treatment.

Statistical Analysis

All randomized subjects who received at least one dose of double-blind medication (n = 100) were included in a k-means cluster analysis using SPSS for Windows (Norusis, 1997). Missing data were not recoded, but across baseline and outcome measures reported in this study, it was determined that the maximum data missing for any one variable was 15%-with 100% of the data collected per variable being the norm. Most of the outcome data were obtained, even in subjects who left treatment early, because drinking data during the trial were collected retrospectively at follow-up visits using the TLFB.

The k-means cluster analysis entailed the use of the 13 assessment measures described earlier to distinguish higher-riswseverity (Type B) from lower-risklseverity (Type A) subjects. Although the measures were not identical to those used by Babor and colleagues (1992), our procedures for identifying clusters replicated theirs, and also were comparable to those reported in other studies (Kranzler et al., 1996; Litt et al., 1992; Schuckit et al., 1995). Solutions producing more than two clusters were attempted. However, three or more clusters yielded fewer than four subjects in those clusters.

To provide a smaller set of variables with potential utility in clinical practice, a forward conditional stepwise logistic regression was performed to identify which of the 13 variables in the cluster analysis independently contributed to the discrimination of Type A and B alcohol dependence. In this analysis, the significance of adding each variable into the model is evaluated using the score statistic. A cutoff p-value equal to 0.05 divided by 13 variables (to yield 0.00385) was used to determine the optimal model.

Demographics and pretreatment severity variables were compared among four study groups using a multivariate analysis of variance (MANOVA) 2 X 2 model (Type .WE3 X sertralineiplacebo). The MANOVA allowed us to evaluate overall differences at pretreatment across all the demographic or severity measures between the two medication conditions, two alcoholic subtype classifications, and the interaction between medication condition and alcoholic subtype. By definition, we anticipated a number of differences in pretreatment measures between subtype classifications. However, for any significant interaction or main effect for medication condition, group comparisons were made with an analysis of variance (ANOV-A) for continuous measures, and with a 2 test of independence for categorical measures.

All comparisons of in-trial and outcome data that permitted covariates included pretreatment drinking as a covariate (specifically, percent days drinking in the 90 days prior to treatment). The use of pretreatment drinking as a covariate controls for large individual differences in the extent of drinking during the pretreatment period.

Comparisons among groups on treatment participation and response to sertraline were evaluated as a function of Type A and B alcohol dependence. There were four treatment participation measures: (1) number of TSF sessions attended; (2) number of support group meetings attended; (3) whether or not subjects completed the treatment trial; and (4) pill compliance. The number of TSF sessions attended and pill compliance rates were each tested with a univariate analysis of covariance (AN- COVA). Attendance at support group meetings was tested with the median rank test, due to the skewed distribution. Treatment retention was tested with a binary logistic regression.

Three drinking measures, preselected from among those used most frequently in prior literature, were evaluated for their response to sertraline with respect to Type A or B alcohol dependence. All of the drinking measures were derived from the TLFB: (1) the number of weeks to relapse, defined as drinking five or more drinks in one day; (2) the percent days drinking during treatment; and (3) the proportion of subjects who maintained continuous abstinence over the 14 weeks of treatment. Of note, drinks per drinking day, another frequently reported drinking measure, was not evaluated as an outcome variable because it played a highly significant role in the cluster analysis that determined the AIS typology.

Time to relapse was tested with a Cox regression survival analysis; the percent days drinking in-trial was tested using the median rank test, due to

Assessments

Most of the assessments used for the cluster procedure to define alcohol subgroups were conducted at the time of study enrollment. These measures were used to determine study eligibility and identify pretreatment clinical characteristics. In addition, information on attendance at TSF sessions and community-based support groups was collected weekly during treatment, with a modification of the Treatment Services Review (TSR) (McLellan et al., 1992a). The amount of daily drinking was re- corded weekly during treatment with the Timeline Followback (TLFB) (Sobell and Sobell, 1992). If the subject discontinued treatment prior to the completion of 14 weeks, the TLFB was administered at the end of the scheduled treatment period so as to obtain a continuous daily record of drinking during the 14 weeks.

Babor’s Alcoholic Subtypes. Subtype assignment was based on four dimensions, represented by 13 measures. All scores were standardized before being entered into the cluster analysis to avoid disproportionate contributions to the solution based on different metrics. Higher scores indicated greater risWseverity.

Vulnerability and Risk (Life Stressors and Heritability). (1) Familial alcohol risk was determined by a question from the Addiction Severity Index (ASI) (McLellan et al., 1992b) where subjects are asked to list all first-degree relatives who had or have problems with alcohol; (2) Number of childhood conduct disorder symptoms from the Antisocial Personality Disorder module of the Structured Clinical Interview for DSM-111-R Personality Disorders (SCID-11) (Spitzer and Williams, 1987); and (3) Life Change Index (Holmes, 1967) determines “life crisis level” based on lifetime major stressors.

Addiction Seventy. (4-5) Alcohol and Drug Composite scores from the ASI, which measure the severity of alcohol- and drug-related problems; (6) Obsessive-Compulsive Drinking Scale total score (OCDS) (Anton et al., 1996), which measures the extent of drinking-related behaviors, i.e., thoughts and compulsions around drinking; and (7) Drinks per drinking day in the 90 days prior to treatment, derived from the Timeline Follow- back (TLFB) (Sobell and Sobell, 1992).

Chronicity. (8) The Michigan Alcoholism Screening Test (SMAST) (Selzer et al., 1975), which measures the number of lifetime alcohol- related negative consequences; and (9-11) Medical, Legal, and Family/ Social Composite scores from the ASI, which measure severity of medical, legal and familyisocial problems due to substance abuse.

Psychopathology. (12) Psychiatric Composite score from the ASI, which measures psychiatric severity; and (13) 24-item Hamilton Rating Scale for Depression (HAM-D-24) (Hamilton, 1960) at time of randomization.


Table 1. Demographics for Four Subject Groupsa

Type A-lower riskheverity Type B-higher riskheverity

Total Sertraline Placebo Total Sertraline Placebo (n = 55) (n = 30) (n = 25) (n = 45) (n = 20) (n = 25)

No. males (%) 26 (47.3%) 16 (53.3%) 10 (40.0%) 26 (57.8%) 10 (50.0%) 16 (64.0%) Age (Y) 47.9 2 10.4 46.7 2 9.5 49.3 2 11.4 40.6 2 8.5 39.9 2 9.3 41.3 2 8.0 No. Caucasian (%) 44 (80.0%) 22 (73.3%) 22 (88.0%) 36 (80.0%) 15 (75.0%) 21 (84.0%)

15 (60.0%) No. married (%) 18 (32.7%) 7 (23.3%) 11 (44.0%) 24 (53.3%) 9 (45.0%) Education (y) 14.8 2 2.4 14.6 2 2.4 15.0 2 2.4 13.7 2 2.2 13.4 2 2.3 14.0 2 2.2 No. rnidhpper SES (%) 26 (47.3%) 13 (43.3%) 13 (52.0%) 27 (60.0%) 12 (60.0%) 15 (60.0%)

14.1 2 10.8 Days worked (in 30) 17.6 2 8.7 18.4 2 7.4 16.6 2 10.1 15.5 2 10.0 17.2 2 8.8 No. years of problem drinking 17.1 2 11.1 17.7 2 12.1 16.4 2 10.0 13.5 2 8.6 11.8 2 9.4 14.8 2 7.9 No. prior alcohol treatments 1.2 2 4.0 1.4 2 5.4 1.0 -e 0.9 0.8 2 1.2 0.6 2 0.8 1.0 ? 1.5

% Days drinking (in 90) 76.0 2 29.1 75.7 2 30.2 76.4 2 28.3 64.9 2 30.5 61.8 2 33.6 67.3 2 28.3 Drinkddrinking day (in 90) 7.1 2 3.0 7.3 2 3.3 6.8 ? 2.7 12.2 2 6.0 12.6 2 7.0 11.9 2 .1

a MANOVA revealed differences on some of the 11 variables between alcoholic subtype [F(I 1,85) = 4.64, p < 0.00011; but othetwise revealed no differences between medication conditions [F(11,85) = 0.95; p = 0.491, nor were there any significant differences by way of an interaction between medication condition and alcoholic subtype [F(11,85) = 0.48; p = 0.911. ’ Values are given as mean 2 SD unless otherwise indicated. SES, socioeconomic status.

the skewedness of the distribution, and the proportion of subjects with continuous abstinence while in treatment was tested with a binary logistic regression. To determine significance and support posthoc comparisons, all tests required a p level of 0.05. All significant interactions were further examined in posthoc subgroup comparisons using an ANOVA for the Cox regression survival analysis of time to relapse, a split-sample median rank test for the percent days drinking during treatment, and the 2 test of independence for the logistic regression of the proportion of subjects who maintained continuous abstinence over the 14 weeks of treatment.

Also, we report the goodness of fit of the model using the Hosmer- Lemeshow test for all logistic regressions performed in this study. Odds ratios were derived for significant interactions in logistic regression models. Effect sizes were derived from power analysis for significant interactions in ANOVA and ANCOVA models.

RESULTS

The total study group (N = 100) was 52% male and 80% Caucasian, and the mean age was 44.6 _f 10.2 years. Most subjects were employed, were of middle-to-upper socioeconomic status, and were of moderate-to-severe alcohol dependence. For the total sample, the average number of years of problem drinking was 19.6 2 10.3 years, and the number of previous alcohol treatments was 1.0 * 3.1. Dur- ing the 90 days prior to treatment, subjects drank an average of 9.4 ? 5.2 drinks per drinking day, drinking on approximately 71% +- 30.1% of the days.

Determining Type A and B Subjects Cluster analysis yielded two groups: n = 55 lower-risk/

severity (Type A) subjects (n = 30 sertraline; n = 25 placebo), and n = 45 higher-riskheverity (Type B) subjects (n = 20 sertraline; n = 25 placebo). This sample had a relatively comparable ratio of Type A: B subjects to that reported by Kranzler and colleagues (1996) i.e., 1.2:l vs. 1.7: 1 [g = 0.68, df = 1 , p > 0.651.

The forward conditional stepwise logistic regression analysis revealed that three of the 13 measures used in the k-means cluster analysis were significant, independent measures that differentiated lower riskheverity (Type A) from

higher riskheverity (Type B) subjects. These three measures classified 94.0% of the subjects exactly the same as the k-means cluster model. This represented excellent con- cordance between the two methods of classification. The three measures, in the order in which they were entered into the analysis, are: (1) HAM-D, i.e., the number of depression symptoms (score = 39.5, p < 0.0001, R = 0.577); (2) number of drinks per drinking day (score = 15.9, p = 0.0001, R = 0.350); and (3) number of childhood antisocial personality symptoms (score = 9.2, p = 0.002, R = 0.251). There was no reason to believe that this model was inappropriate based on the Hosmer-Lemeshow goodness-of-fit test (2 = 5.1, df = 8, p’ = 0.75).

Demographics, Clinical Profile, and Treatment Participation Demographic Measures. Demographic and key historical

variables for lower riskheverity (Type A) and higher risk/ severity (Type B) subjects, with respect to their medication condition, are presented in Table 1. There was no significant interaction between medication condition and alcoholic subtype for the 11 variables [F(11,85) = 0.48; p = 0.911. There were also no significant differences between medication conditions, i.e., all variables were comparable between sertraline- and placebo-treated subjects [F(11,85) = 0.95; p = 0.491. As anticipated, there were a number of demographic/drinking history differences between alcoholic subtypes, indicated by a significant main effect for alcoholic subtype [F(11,85) = 4 . 6 4 ; ~ < 0.00011. Some differences were, of course, anticipated between Type A and B subjects, because we included a number of pretreatment measures in the clustering procedure to dif- ferentiate the more severe (Type B) from the less severe (Type A) subjects.

Clinical Severity Profiles. The pretreatment severity evaluation consisted primarily of the 13 measures that were used to distinguish lower riskheverity (Type A) and higher risMseverity (Type B) subjects. These 13 measures are listed in Table 2 for the two alcoholic subtypes, according to


Table 2. Clinical Profiles at Treatment Entry for Four Subject Groups (from 13 Measures used to derive alcoholic subtypes)a

Type A-lower riskkeverity Type &higher riskheverity

Total Sertraline Placebo Total Sertraline Placebo (n = 55) (n = 30) (n = 25) (n = 45) (n = 20) (n = 25)

Vulnerabilityhisk Family history

Conduct disorder history

Life Change Index 221 2 147 205 ? 145 242 ? 150 241 2 156

No. relatives with alcohol 2.8 f 2.1b 3.3 f 2.2 2.2 t 2.0 3.0 t 2.3 2.8 5 2.4 3.2 f 2.2

No. child sxs-SCID 2 0.37 t 0.77 0.48 f 0.85 0.24 f 0.66 1.32 2 2.02 1.28 2 2.30 1.35 f 1.82 251 i- 140 227 t 177

Addiction seventy AS1

Alcohol 0.72 t 0.15 0.73 t 0.16 0.71 5 0.14 0.73 t 0.17 0.74 t 0.18 0.72 f 0.1 7 0.01 Ifl 0.02 Drug 0.01 2 0.03 0.00 c 0.00 0.01 ? 0.05 0.01 f 0.03 0.02 ? 0.05 22.6 f 4.8 22.6 t 8.0 22.6 t 6.2 OCDS Craving 15.8 t 6.9 15.6 t 7.4 16.1 f 6.4

Drinkddrinking day 7.1 t 3.0 7.3 t 3.3 6.8 ? 2.7 12.2 t 6 0 12.6 t 7.0 11.9 f 5.1

Chronicity SMAST AS1

Medical Legal Social

6.9 t 2.4 7.3 t 2.3 6.5 2 2.5 9.1 f 2.3 9.4 t 2.2 8.8 t 2.4

0.17 f 0.27 0.01 f 0.06 0.28 t 0.24

0.19 f 0.27 0.16 t 0.27 0.23 5 0.27 0.15 t 0.26 0.13 t 0.25 0.04 f 0.13 0.06 t 0.17 0.01 2 0.04 0.02 t 0.09 0.03 t 0.12 0.13 f 0.17 0.17 t 0.19 0.08 2 0.14 0.26 t 0.24 0.24 t 0.25

Psychopathology Hamilton Depression 5.3 t 4.3 4.6 t 4.0 6.1 f 4.7 14.6 c 7.3 15.1 f 6.8 14.2 ? 7.9 ASI-Psychological 0.10 t 0.16 0.05 t 0.12 0.16 Ifl 0.18 0.36 t 0.19 0.36 -C 0.18 0.37 2 0.20

a MANOVA revealed differences on some of the 13 variables between alcoholic subtype [F(13,67) = 15.77, pl< O.OOOl]; but otherwise revealed no differences between medication conditions [f(13,67) = 1.12; p = 0.361, nor were there any significant differences by way of an interaction between medication condition and alcoholic subtype [F(13,67) = 0.73; p = 0.731.

'Values are given as mean t SD unless otherwise indicated. ASI, Addiction Severity Index; OCDS, Obsessive-Compulsive Drinking Scale; SClD 2, Structured Clinical Interview for DSM Axis II Diagnoses; SMAST, Short

Michigan Alcohol Screening Test; sxs, symptoms.

whether subjects received sertraline or placebo. There was no significant interaction between medication condition and alcoholic subtype for the 13 variables [F(13,67) = 0.73; p = 0.731. There also were no significant differences between medication conditions, i.e., all variables were comparable between sertraline and placebo-treated subjects [F(13,67) = 1.12; p = 0.361. As anticipated, there were a number of clinical severity differences between alcoholic subtypes, indicated by a significant main effect for alcoholic subtype [F(13,67) = 15.77, p < 0.00011.

As can be seen in Table 2, not all measures significantly discriminated the two groups. However, the majority of the mean values per measure for the two subtypes are in the anticipated direction of greater severity in Type B than Type A subjects. Thus, despite a number of pretreatment differences between lower riskheverity (Type A) and higher riskheverity (Type B) subjects, mostly due to the clustering procedure, there were no significant pretreatment differences between sertraline and placebo groups within each of the two alcoholic subtypes with respect to demographics or in their clinical severity upon entering treatment.

Treatment Participation. All study groups (Type A sertraline/placebo, and Type B sertraline/placebo) had comparable attendance at TSF sessions. In the Type A groups, sertraline- and placebo-treated subjects attended 8.0 and 7.8 TSF sessions, respectively; In the Type B groups, sertraline- and placebo-treated subjects attended 8.5 and

8.6 TSF sessions, respectively. Results were as follows: medication effect: [F(1,95) = 0.01, p = 0.921; subtype effect: [F(1,95) = 0.28, p = 0.601; interaction effect: [F(1,95) = 0 . 0 2 , ~ = 0.883. Also, there were no significant differences among the study groups in attendance at support group meetings. Median number of support group meetings attended by Type A sertraline and placebo subjects were 2.0 and 1.0 meeting; and Type B subjects, sertraline versus placebo, were 1.0 vs. 14.0. Results were as follows: medication effect: 2 = 0.0, df = 1, p = 1.00; alcoholic subtype effect: 2 = 1.77, df = 1, p = 0.18; interaction effect: 2 = 7.01, df = 3,p = 0.07.

Treatment discontinuation rates also did not differ among the study groups. Type A sertraline versus placebo had a discontinuation rate of 40.0% vs 56.0%; Type B sertraline versus placebo had a discontinuation rate of 30.0% vs 40.0% (medication effect: Wald = 0.38, df = 1, p = 0.54; subtype effect: Wald = 0.22, df = 1,p = 0.64; interaction effect: Wald = 0.09, df = 1, p = 0.76). There was no reason to believe that this model was inappropriate based on the Hosmer-Lemeshow Goodness-of-Fit test (2 = 0.78, df = 8, p = 0.99). Generally, the reasons for not completing treatment, summed across sertraline and placebo groups, were noncompliance in treatment attendance (24%), adverse events (lo%), and clinical deterioration (8%), defined as a persistence in the severity of depression or a serious increase in drinking, or both. There were no differences in the reasons given for discontinuing treatment


between sertraline and placebo conditions (2 = 3.0, df = 3, p = 0.39). Importantly, although the mean discontinuation rate for the sample approximated 40%, drinking data were still obtained using the TLFB.

Medication Compliance and Safety Most of the subjects (87%) tolerated 200 mg/day, or 4

placebo capsules, as their daily dose. The mean daily dosage for the sample was 169.5 mg/day. There were three frequently reported adverse symptoms, with more reports associated with sertraline treatment than placebo:

1. Sexual disturbance: 38.8% vs 6.0%, respectively, 2 = 15.4, df = 1, p < 0.001. The most prevalent complaints were decreased libido and anorgasmia.

2. Fatigue: 36.7% vs 16.0%, respectively, 2 = 5.5, df = 1,

3. Headache: 34.7% vs 14.0%, respectively; 2 = 5.8, df =

Gastrointestinal distress (e.g., nausea, diarrhea) and dry mouth also were reported frequently, but these complaints did not differ significantly between sertraline and placebo (Gastrointestinal: 55.1% vs 38.0%, respectively, 2 = 2.91, df = 1,p = 0.09; Dry mouth: 34.7% vs 18%, respectively; 2 = 3.56, df = 1,p = 0.06). Despite these complaints, only 10 subjects discontinued treatment due to adverse events (six taking sertraline and four taking placebo).

Medication compliance was monitored by pill counts and urinary riboflavin. Pill counts, as measured by the number of prescribed capsules that were taken per day, did not differ statistically across the study groups (Type A sertraline versus placebo: 3.07 -+ 0.95 vs. 3.32 -+ 0.99; Type B sertraline versus placebo: 3.50 -+ 0.57 vs. 3.69 -+ 0.60). The following results were obtained: medication effect: F(1,64) = 1.13, p = 0.29; alcoholic subtype effect: F(1,64) = 3 . 0 4 , ~ = 0.09; interaction effect: F(1,64) = 0.01, p = 0.91. Weekly urine samples were positive for riboflavin in approximately 75% of the urines collected, i.e., Type A sertraline versus placebo: 71.6% vs 76.1%; Type B sertraline versus placebo: 77.9% vs 83.6%. These rates did not differ statistically between medication and placebo groups [F(1,95) = 3 . 5 1 , ~ = 0.061, although Type A subjects had a lower compliance rate than Type B subjects [F(1,95) =

6 . 6 3 , ~ = 0.011.

p < 0.02.

1,p < 0.02.

Treatment Response to Sertraline in Type A and B Subjects A significant advantage for sertraline treatment was

found on two of the three drinking outcome measures, and this advantage differed depending on alcoholic subtype. The two drinking outcome measures were the percent days drinking during treatment, and the number of subjects who had continuous abstinence throughout the trial.

For the percent days drinking during treatment, there was no difference by alcoholic subtype (2 = 0.06, df = 1, p = 0.81) or medication group (2 = 1.44, df = 1,p = 0.23),

.f 20%

P P S

.- b g 10%

n $?

0

0%

PLACEBO

SERTRALINE Type A Type 0

Alcohol Subtype n = 55 n=45

Fig. 1. The median percent days of alcohol drinking during the 14-week trial was compared for alcohol-dependent Type A (lower risklseverity) and Type B (higher risklseverity) subjects, with respect to their double-blind medication status. There was a significant advantage with settraline treatment for subjects with Type A alcohol dependence, but not for those with Type B alcohol dependence. -

but there was a significant interaction between medication condition and alcoholic subtype (2 = 7.63, df = 3, p = 0.05) (Fig. 1). Further inspection showed that in Type A subjects, sertraline was associated with fewer days drinking compared to placebo: the median percent days drinking in-trial for Type A sertraline versus placebo was 0.0% days vs 22.4% days, respectively; 2 = 6.56, df = 1, p = 0.01. There was no statistical difference in the contrast between sertraline- and placebo-treated subjects in the higher risk/ severity (Type B) subjects inthis sample: Type B sertraline versus placebo: 8.2% days vs 4.1% days, respectively; 2 = 0.54, df = 1 , p = 0.46.

In evaluating the number of subjects maintaining continuous abstinence for the 14 weeks of treatment, there was a significant main effect for alcoholic subtype, such that there were more lower riskheverity (Type A) subjects with continuous abstinence during treatment than higher riskheverity (Type B) subjects (Wald = 8.46, df = 1,p < 0.004, R = -0.23, odds ratio = 0.08). There was also a significant interaction between medication condition and alcoholic subtype (Wald = 6.90, df = 1 , p < 0.009, R = 0.20, odds ratio = 18.5) (Fig. 2).

Further inspection revealed that the lower riskheverity (Type A) subjects who received sertraline were significantly more likely to maintain continuous abstinence for the 14 weeks of treatment compared to those taking placebo. Results for Type A, sertraline versus placebo, were as follows: 53.3% vs 16.0%, respectively, stayed abstinent; 2 = 8.2, df = 1,p = 0.004. There was no statistical difference in the contrast between sertraline- and placebo-treated subjects in the higher riskheverity (Type B) subjects in this sample. Results for Type B, sertraline versus placebo, were as follows: 10.0% vs 24.0%, respectively, stayed abstinent; 2 = 1.49, df = 1 , p = 0.22.


50%. Y C al c u)

.I 40%.

9

p 20%.

u) 30%. .+I u al

cn 1 0%.

8

0%

PLACEBO

SERTRALlNE

Type A n = 55 n = 45

Alcohol Subtype Fig. 2. The proportion of alcohol-dependent Type A (lower riskfseverity) and B

(higher riskfseverity) subjects who were completely abstinent during the 14-week treatment trial, with respect to their double-blind medication status. There was a significant advantage with sertraline treatment for subjects with Type A alcohol dependence, but not for those with Type B alcohol dependence.

For the drinking outcome variable time to relapse to heavy drinking, the number of weeks to relapse for Type A sertraline versus placebo was 5.0 vs. 4.0 weeks, respectively; for Type B, sertraline versus placebo was 3.7 vs 3.8 weeks. There was no medication effect (Wald = 0.03, df = l ,p = 0.86), but there was a significant difference in the time to relapse between alcoholic subtypes, such that lower risk/ severity (Type A) subjects took longer to relapse than higher-riskheverity (Type B) subjects: Wald = 6.24, df = 1, p = 0.013, R = -0.09, odds ratio = 0.34. The interaction between medication condition and alcoholic subtype ap- proached, but did not reach, significance: Wald = 2.5, df =

These findings suggest that a multivariate approach to subtyping, i.e., Type A and B, may be important for evaluating the effects of sertraline in the treatment of alcohol dependence. To test the specificity of this subtyping procedure, we repeated all of the outcome analyses for the three drinking variables utilizing a univariate approach to subtyping, namely, early versus late age of onset of regular intoxication (younger versus older than 25 years). Results showed only one significant interaction with medication treatment: number of weeks to relapse. In addition, there were no significant main effects for alcoholic subtype using the early/late typology, indicating that even anticipated differences between the more and less severe alcoholic subtypes could not be confirmed with this univariate method of alcohol subtyping.

1,p = 0.11.

DISCUSSION

One of the key findings in this study of sertraline pharmacotherapy is consistent with the results of an earlier placebo-controlled clinical study of fluoxetine treatment

for alcohol dependence (Kranzler et al., 1996). That is, alcoholic subtypes responded differentially to sertraline when used as a treatment to reduce alcohol drinking. This confirms that subtyping alcoholics may help to resolve conflicting findings in the literature on serotonergic treatment of alcohol dependence.

In the present study, we found that a favorable response to sertraline, compared to placebo, was observed on two of three drinking outcome variables in lower risk/severity subjects (Type A). That is, in Type A alcohol dependence, sertraline treatment was associated with fewer drinking days and a greater likelihood of continuous abstinence during the treatment trial. There was a nonsignificant trend for a similar effect on the number of weeks to first relapse. These positive effects did not appear to be confounded by medication noncompliance or by treatmenj attrition. This finding requires replication, but it does suggest that a subgroup of patients with alcohol dependence may clinically benefit from a course of sertraline treatment.

We also found that higher riskheverity (Type B) alcoholics treated with sertraline tended to report more days drinking, compared to those treated with placebo, although this difference was not statistically significant. This observation, however, was also consistent with a nonsignificant lower likelihood for Type B subjects to maintain abstinence during treatment if they were treated with sertraline rather than placebo. This lack of a beneficial effect of sertraline for Type B alcoholics, together with the finding reported by Kranzler and colleagues (1996), suggests that treatment with an SSRI is not indicated among higher riskheverity alcoholics. However, the findings reported here do support the value of sertraliw in combination with psychosocial treatment for lower riskheverity alcoholics.

This study has several limitations. Because the results were obtained in a clinical trial and not in a typical treatment setting, they may not readily generalize to some clinical settings, e.g., those that treat predominantly patients with polysubstance use. Also, some of our treatment participation measures, e.g., all of our drinking measures and pill compliance, were based primarily on self-report. How- ever, drinking data were collected by experienced staff who had received supervised training in the use of the Timeline Follow-back, a semistructured interview with excellent psy- chometric properties. Also, the blind was kept intact throughout the study, and there would be no reason to suspect differences in self-reports between medication and placebo conditions. Measurement of urinary riboflavin help to validate self-reported pill compliance. Since there is the possibility for dietary riboflavin to confound riboflavin reports, vitamin supplements without riboflavin were provided to any subjects who regularly took vitamins.

Finally, better identification or classification of subjects with potential 5-HT abnormalities could further clarify these findings. Although to some degree the findings support those reported by Kranzler et al. (1996), both studies depended on a complex statistical procedure to subtype

1048 PETTINAT1 ET AL.

alcoholics. However, when age of onset of regular intoxication (i.e., younger versus older than 25 years) was used to subtype alcoholics in place of A/s alcoholic subtype, the interaction of an earlyflate typology with medication condition was significant for only one of the three primary outcome variables. In addition, anticipated differences between alcoholic subtypes, which provide construct valida- tion to the classification, were absent for an earlyjlate typology. Taken together, these findings suggest that a univariate typology based upon age of onset, while easier to derive, is a less valid approach to subtyping alcoholics as a predictor of the response to sertraline treatment. This is consistent with the observation that one-dimensional ty- pologies based on etiologic variables, presenting symptoms or drinking patterns typically are poor independent predic- tors of outcome status (Babor et al., 1988). Thus, the utility of the A/B typology appeared to be greater in relation to 5-HT pharmacotherapy than did the earlybate typology.

Although the clinical utility of a multivariate clustering approach seems limited at this time, the identification of three variables that accounted for nearly all of the variance in assignment suggests that a clinically relevant procedure may be feasible. Replication of these results will be important to further establish the utility of the A/B typology in evaluating the differential efficacy of 5-HT pharmacother- apies. Other patient samples could yield different results if the ranges of these three discriminating variables were widely different from those reported in this study.

Clinical Significance Given the widespread use of SSRIs in clinical practice,

both in primary care and psychiatric settings where substance dependence may not be systematically evaluated, these findings appear to have important clinical implications. Although, the clustering procedure needs more development before it can be translated easily into clinical use, the present study suggests that careful monitoring of drinking outcomes in alcohol-dependent patients taking SSRIs is important, and that there is a subgroup of alcohol- dependent patients where a regimen of sertraline (200 mg/day for at least 14 weeks) may prove to be a useful adjunct to psychosocial treatment. In sum, we recommend that SSRIs be considered a potentially viable strategy for reducing alcohol consumption, but that they should be used judiciously and the patient’s progress should be closely monitored, particularly among patients with multiple features typical of Type B (higher risklseverity) alcohol dependence. Efforts to replicate the findings reported here for sertraline treatment should be accompanied by further efforts to refine a subtyping procedure that can be readily applied in the clinic.

ACKNOWLEDGMENT

We thank Ann Semwanga, Alexia Wolf, Rick Saini, Thomas Bartlett, and Simon Murray for their oversight of the project,

including data collection; Raymond Anton (Medical University of South Carolina) for his expert advice in all phases of the project; Craig Lipkin for data re-analyses; and Kelly Decker, Donna Maiuri, John Monterosso, and Heather Wallace for technical assistance.

REFERENCES Anton RF, Moak DH, Lathan PK (1996) The Obsessive Compulsive

Drinking Scale: A new method of assessing outcome in alcoholism treatment studies. Arch Gen Psychiatry 53:225-231.

Babor T, Dolinsky Z, Meyer R, Hesselbrock M, Hofmann M, Tennen H (1992) Types of alcoholics: Concurrent and predictive validity of some common classification schemes. Br J Addict 87:1415-1431.

Babor T, Dolinsky Z, Rounsaville B, Jaffe J (1988) Unitary versus multidimensional models of alcoholism treatment outcome: An empirical

Benkelfat C, Murphy D, Hill J, George DT, Nutt D, Linnoila M (1991) Ethanol like properties of the serotonergic partial agonist, m-chlorophenylpiperazine in chronic alcoholic patients. Arch Gen Psy- chiatry 48:383.

Buydens-Branchey L, Branchey MH, Noumair D (1989a) Age of alcoholism onset. I. Relationship to psychopathology. Arch Gen Psychiatry

Buydens-Branchey L, Branchey MH, Noumair D, Lieber CS (1989b) Age of alcoholism onset. 11. Relationship to susceptibility to serotonin pre- cursor availability. Arch Gen Psychiatry 46:231-236.

Coccaro E, Murphy D (1990) Serotonin in Major PJychiatric Disorders. American Psychiatric Press, Washington, DC.

Coccaro E, Siever L, Mar H, Maurer G, Cochrane K, Cooper TB, Mohs RC, Davis KL (1989) Serotonergic studies in patients with affective and personality disorders. Arch Gen Psychiatry 465877599,

Cornelius J, Salloum I, Ehler J, Jarrett PJ, Cornelius MD, Perel JM, Thase ME, Black A (1997) Fluoxetine in depressed alcoholics. Arch Gen Psychiatry 54:700-705.

Coscina DV (1997) The biopsychology of impulsivity: Focus on brain serotonin, in Impulsivity (Webster CD, Jackson MA, eds). pp 95-115, Guilford Press, New York.

Del Boca FK, Kranzler HR, Brown J, Korner PF (1996) Assessment of medication compliance in alcoholics through UV light detection of a riboflavin tracer. Alcohol Clin Exp Res 201412-1417.

Fils-Aime M, Eckhardt M, George D, Brown GL, Mefford I, Linnoila M (1996) Early-onset alcoholics have lower cerebral spinal fluid 5-hydroxyindoleacetic acid levels than late-onset alcoholics. Arch Gen Psychiatry 53:211-216.

Gorelick D, Pardes A (1992) Effect of fluoxetine on alcohol consumption in male alcoholics. Alcohol Clin Exp Res 16:261-265.

Hamilton M (1960) A rating scale for depression. J Neurol Neurosurg Psychiatry 23:56-62.

Heinz A, Ragan P, Jones D, Hommer D, Williams W, Knable MB, Gorey JG, Doty L, Geyer C, Lee KS, Coppola R, Weinberger DR, Linnoila M (1998) Reduced central serotonin transporters in alcoholism. Am J Psychiatry 155:1544-1549.

Higley J, Hasert M, Suomi S, Linnoila M (1998) The serotonin reuptake inhibitor sertraline reduces excessive alcohol consumption in nonhuman primates: Effect of stress. Neuropsychopharmacology 18:431-443.

Holmes T (1967) Life Change Index Scale, The Holmes and Rahe Social Readjustment Rating Scale. Pergamon Press, New York.

Irwin M, Schuckit M, Smith T (1990) Clinical importance of age at onset in type 1 and type 2 primary alcoholics. Arch Gen Psychiatry 47:320- 324.

Johnson BA, Cloninger CR, Roache JD, Bordnick PF, Ruiz P (2000) Age of onset as a discrimination between alcoholic subtypes in a treatment- seeking outpatient population. Am J Addict 9:17-27.

Kabel D, Petty F (1996) A double-blind study of fluoxetine in severe alcohol dependence: Adjunctive therapy during and after inpatient treatment. Alcohol Clin Exp Res 20780-784.

study. J Stud Alcohol 49~167-177.

46:225-230.


Kranzler H, Anton R (1994) Implications of recent neuropharmacologic research for understanding the etiology and development of alcoholism. J Cons Clin Psychology 62:1116-1126.

Kranzler HR, Burleson JA, Brown J, Babor TF (1996) Fluoxetine treatment seems to reduce the beneficial effects of cognitive-behavioral therapy in Type B alcoholics. Alcohol Clin Exp Res 20:1534-1541.

Kranzler HR, Burleson JA, Korner P, Del Boca FK, Bohn MJ, Brown J, Liebowitz N (1995) Placebo-controlled trial of fluoxetine as an adjunct to relapse prevention in alcoholics. Am J Psychiatry 152:391-397.

Krystal JH, Webb E, Cooney N, Kranzler HR, Charney DS (1994) Spec- ificity of ethanol-like effects elicited by serotonergic and noradrenergic mechanisms. Arch Gen Psychiatry 51:898-911.

Krystal J, Webb E, Cooney N, Kranzler HR, Southwick SW, Heninger GR, Charney DS (1996) Serotonergic and noradrenergic dysregulation in alcoholism: m-CPP and yohimbine effects in recently detoxified alcoholics and healthy comparison subjects. Am J Psychiatry 153:83-92.

Lewis C (1991) Neurochemical mechanisms of chronic antisocial behavior (psychopathy): A literature review. J New Men Dis 179:720-727.

Litt M, Babor T, DelBoca F, Kadden RM, Cooney NL (1992) Types of alcoholics. 11. Application of an empirically derived typology to treatment matching. Arch Gen Psychiatry 49:609-614.

Maes M, Meltzer H (1995) The serotonin hypothesis of major depression, in Psychophamacology: The Fourth Generation of Progress (Bloom F, Kupfer D, eds) pp 933-944, Raven Press, New York.

Mann J, Malone K, Diehl D, Perel J, Cooper TB, Mintun MA (1996) Demonstration in vivo of reduced serotonin responsivity in the brain of untreated depressed patients. Am J Psychiatry 153:174-182.

McLellan AT, Alterman AI, Cacciola J, Metzger D, O’Brien CP (1992a) A new measure of substance abuse treatment: Initial studies of the Treatment Services Review. J Nerv Ment Dis 18O:lOO-110.

McLellan AT, Kushner AH, Metzger DS, Peters R, Smith I, Grissom G, Pettinati H, Argeriou M (1992b) The fifth edition of the Addiction Severity Index. J Subst Abuse Treat 9:199-213.

Meyers R, Quarfordt S (1991) Alcohol drinking attenuated by sertraline in rats with 6-OHDA or 5,7-DHT lesions of N. accumbens: A caloric response? Pharmacol Biochem Behav 40:923-928.

Moeller F, Dougherty D, Swam A, Collins D, Davis CM, Cherek DR (1996) Tryptophan depletion and aggressive responding in healthy males. Psychopharmacology (Ber1)126:97-103.

Naranjo C, Kadlec K, Sanhueza P, Woodley-Remus D, Sellers EM (1990) Fluoxetine differentially alters alcohol intake and other consummatory behaviors in problem drinkers. Clin Pharrnacol Ther 47490-498.

Naranjo CA, Poulos CX, Bremner KE, Lanctot KL (1992) Citalopram decreases desirability, liking, and consumption of alcohol in alcohol- dependent drinkers. Clin Pharmacol Ther 51:729-739.

Naranjo C, Sellers E, Lawrin M (1986) Modulation of ethanol intake by serotonin uptake inhibitors. J Clin Psychiatry 47(supp14):16-22.

Naranjo CA, Sellers EM, Roach CA, Woodley DV, Sanchez-Craig M, Sykora K (1984) Zimelidine-induced variations in alcohol intake by nondepressed heavy drinkers. Clin Pharmacol Ther 35:374-381.

Naranjo C, Sellers E, Sullivan J, Woodley DV, Kadlec K, Sykora K (1987) The serotonin uptake inhibitor citalopram attenuates ethanol intake. Clin Pharmacol Ther 41:266-274.

Naranjo C, Sullivan J, Kadlec K, Woodley-Remus DV, Kennedy G , Sellers EM (1989) Differential effects of viqualine on alcohol intake and other consummatory behaviors. Clin Pharmacol Ther 463001-3009.

Norusis M (1997) SPSS 7.5 Guide to Data Analysis. Prentice Hall, Engle- wood Cliffs, NJ.

Nowinski J, Baker S, Carroll K (1995) Twelve-Step Facilitation Therapy Manual: A Clinical Research Guide for Therapists Treating Individuals With Alcohol Abuse and Dependence. National Institute on Alcohol Abuse and Alcoholism, Rockville, Maryland.

Pettinati HM (1996) Use of serotonin selective pharmacotherapy in the treatment of alcohol dependence. Alcohol Clin Exp Res 20 (Suppl):

Pettinati HM, Volpicelli JR, Luck G, Kranzler HR, Rukstalis MR, Cnaan A (2000) Double-blind clinical trial of sertraline treatment for alcohol dependence. J Clin Psychopharm (in press).

Pettinati HM, Oslin DW, Decker K (2000) Role of serotonin and serotonin-selective pharmacotherapy in alcohol dependence. CNS Spectrums 5(2):33-46.

Sahakian B, Sarna G, Kantamaneni D, Jackson A, Hutson PH, Curzon G (1986) CSF tryptophan and transmitter amine turnover may predict social behaviour in the normal rat. Brain Res 399162-166.

Schuckit M, Tipp J, Smith T, Shapiro E, Hesselbrock VM, Bucholz KK, Reich T, Nurnberger JI Jr (1995) An evaluation of Type A and B alcoholics. Addiction 90: 1189-1203.

Selzer ML, Vinokur A, van Rooijen L (1975). A self-administered Short Michigan Alcoholism Screening Test (SMAST). J Stud Alcohol 36117- 126.

Sobell L, Sobell M (1992) Timeline follow-back: A technique for assessing self-reported alcohol consumption, in Measuring Alcohol Consumption (Litten R and Allen J eds). The Humana Press, Totowa, New Jersey.

Spitzer R, Williams J (1987) Structured Clinical interview for DSM-III-R. 3rd ed., rev. American Psychiatric Association, Washington, DC.

Spitzer RL, Williams BW,. Gibbon M, First MB (1992) The structured clinical interview for DSM-111-R (SCID). I. History, rationale, and description. Arch Gen Psychiatry 49524-629.

Swann AC, Johnson BA, Cloninger CR, Chen YR (1999) Relationships of plasma tryptophan availability to course of illness and clinical features of alcoholism: A preliminary study. Psycbopharm 143:380-384.

Virkkunen M, Linnoila M (1993) Brain serotonin, Type I1 alcoholism and impulsive violence. J Stud Alcohol ll(Suppl):163-169.

Virkkunen M, Narvanen S (1987) Plasma insulin, tryptophan and serotonin levels during the glucose tolerance test among habitually violent and impulsive offenders. Neuropsychobiology 17(1-2):19-23.

23A-29A.