Examining differential effects of psychosocial treatments for cocaine dependence: an application of latent trajectory analyses

Symptom change trajectories in patients with persistent somatic symptoms and their association to long-term treatment outcome

OBJECTIVE

This study investigated symptom change trajectory for patients with persistent somatic symptoms (PSS) during psychotherapy and the association of these patterns with pre-treatment characteristics and long-term outcome.

METHODS

Growth mixture modeling was used to identify trajectory curves in a sample of N = 210 outpatients diagnosed with PSS and treated either with conventional cognitive behavioral therapy (CBT) or CBT enriched with emotion regulation training (ENCERT).

RESULTS

We identified three subgroups of patients with similar symptom change patterns over the course of treatment (a "no change," "strong response," and "slow change" subgroup). Higher initial anxiety symptoms were significantly associated with the no change and strong response subgroups; symptom-related disability in daily routine with no changes. Patients with a strong response had the highest proportion of reliable improvement at termination and at six-month-follow-up.

CONCLUSION

Our results indicate that, instead of one common change pattern, patients with PSS respond differently to treatment. Due to the high association of symptom curves with long-term outcome, the identification and prediction of an individual's trajectory could provide important information for clinicians to identify non-responding patients that are at risk for failure. Selecting personalized treatment interventions could increase the effectiveness of psychotherapy.Trial registration: ClinicalTrials.gov identifier: NCT01908855..

Early Change Trajectories in Cognitive-Behavioral Therapy for Binge-Eating Disorder

Rapid response is considered the most well-established outcome predictor across treatments of binge-eating disorder (BED), including cognitive-behavioral therapy (CBT). This study sought to identify latent trajectories of early change in CBT and compare them to common rapid response classifications. In a multicenter randomized trial, 86 adults with BED (DSM-IV) or subsyndromal BED provided weekly self-reports of binge eating over the first 4 weeks of CBT, which were analyzed to predict binge eating, depression, and body mass index at posttreatment, 6-, and 18-month follow-up. Using latent growth mixture modeling, three patterns of early change-including moderate and low decreasing-as well as low stable binge eating were identified, which significantly predicted binge-eating remission at 6-month follow-up. Other classifications of rapid response based on Receiver Operating Characteristics curve analyses or on the literature (≥ 10% reduction in binge eating at week 1, ≥ 70% reduction in binge eating at week 4) only predicted posttreatment remission or overall depression, respectively. Latent change trajectories, but not other rapid response classifications, predicted binge-eating frequency over time. A fine-grained analysis of change over the first 4 weeks of CBT for BED revealed different trajectories of early change in binge eating that led to an improved prediction of binge-eating outcome, compared to that of common rapid response classifications. Thorough monitoring of early change trajectories during treatment may have clinical utility.

Patterns of early change and their relationship to outcome and early treatment termination in patients with panic disorder

OBJECTIVE

Recently, innovative statistical tools have been used to model patterns of change in psychological treatments. These tools can detect patterns of change in patient progress early in treatment and allow for the prediction of treatment outcomes and treatment length.

METHOD

We used growth mixture modeling to identify different latent classes of early change in patients with panic disorder (N = 326) who underwent a manualized cognitive-behavioral treatment.

RESULTS

Four latent subgroups were identified, showing clusters of change trajectories over the first 5 sessions. One of the subgroups consisted of patients whose symptoms rapidly decreased and also showed the best outcomes. This information improved treatment prediction by 16.1% over patient intake characteristics. Early change patterns also significantly predicted patients' early treatment termination. Patient intake characteristics that significantly predicted class membership included functional impairment and separation anxiety.

CONCLUSIONS

These findings suggest that early treatment changes are uniquely predictive of treatment outcome.

Imaging genetics and the neurobiological basis of individual differences in vulnerability to addiction

BACKGROUND

Addictive disorders are heritable, but the search for candidate functional polymorphisms playing an etiological role in addiction is hindered by complexity of the phenotype and the variety of factors interacting to impact behavior. Advances in human genome sequencing and neuroimaging technology provide an unprecedented opportunity to explore the impact of functional genetic variants on variability in behaviorally relevant neural circuitry. Here, we present a model for merging these technologies to trace the links between genes, brain, and addictive behavior.

METHODS

We describe imaging genetics and discuss the utility of its application to addiction. We then review data pertaining to impulsivity and reward circuitry as an example of how genetic variation may lead to variation in behavioral phenotype. Finally, we present preliminary data relating the neural basis of reward processing to individual differences in nicotine dependence.

RESULTS

Complex human behaviors such as addiction can be traced to their basic genetic building blocks by identifying intermediate behavioral phenotypes, associated neural circuitry, and underlying molecular signaling pathways. Impulsivity has been linked with variation in reward-related activation in the ventral striatum (VS), altered dopamine signaling, and functional polymorphisms of DRD2 and DAT1 genes. In smokers, changes in reward-related VS activation induced by smoking abstinence may be associated with severity of nicotine dependence.

CONCLUSIONS

Variation in genes related to dopamine signaling may contribute to heterogeneity in VS sensitivity to reward and, ultimately, to addiction. These findings illustrate the utility of the imaging genetics approach for investigating the neurobiological basis for vulnerability to addiction.

Treatment of substance abusing patients with comorbid psychiatric disorders

OBJECTIVE

To update clinicians on the latest in evidence-based treatments for substance use disorders (SUD) and non-substance use disorders among adults and suggest how these treatments can be combined into an evidence-based process that enhances treatment effectiveness in comorbid patients.

METHOD

Articles were extracted from Pubmed using the search terms "dual diagnosis," "comorbidity" and "co-occurring" and were reviewed for evidence of effectiveness for pharmacologic and psychotherapeutic treatments of comorbidity.

RESULTS

Twenty-four research reviews and 43 research trials were reviewed. The preponderance of the evidence suggests that antidepressants prescribed to improve substance-related symptoms among patients with mood and anxiety disorders are either not highly effective or involve risk due to high side-effect profiles or toxicity. Second generation antipsychotics are more effective for treatment of schizophrenia and comorbid substance abuse and current evidence suggests clozapine, olanzapine and risperidone are among the best. Clozapine appears to be the most effective of the antipsychotics for reducing alcohol, cocaine and cannabis abuse among patients with schizophrenia. Motivational interviewing has robust support as a highly effective psychotherapy for establishing a therapeutic alliance. This finding is critical since retention in treatment is essential for maintaining effectiveness. Highly structured therapy programs that integrate intensive outpatient treatments, case management services and behavioral therapies such as Contingency Management (CM) are most effective for treatment of severe comorbid conditions.

CONCLUSIONS

Creative combinations of psychotherapies, behavioral and pharmacological interventions offer the most effective treatment for comorbidity. Intensity of treatment must be increased for severe comorbid conditions such as the schizophrenia/cannabis dependence comorbidity due to the limitations of pharmacological treatments.

A "SMART" design for building individualized treatment sequences

Interventions often involve a sequence of decisions. For example, clinicians frequently adapt the intervention to an individual's outcomes. Altering the intensity and type of intervention over time is crucial for many reasons, such as to obtain improvement if the individual is not responding or to reduce costs and burden when intensive treatment is no longer necessary. Adaptive interventions utilize individual variables (severity, preferences) to adapt the intervention and then dynamically utilize individual outcomes (response to treatment, adherence) to readapt the intervention. The Sequential Multiple Assignment Randomized Trial (SMART) provides high-quality data that can be used to construct adaptive interventions. We review the SMART and highlight its advantages in constructing and revising adaptive interventions as compared to alternative experimental designs. Selected examples of SMART studies are described and compared. A data analysis method is provided and illustrated using data from the Extending Treatment Effectiveness of Naltrexone SMART study.

Lending an ear to feedback systems: evaluation of recovery and non-response in psychotherapy in a German outpatient setting

Systems providing feedback on treatment progress have been implemented in outpatient psychotherapy. They are recognized as a helpful tool to identify possible treatment failures. This report presents the ideas underlying the planning of feedback interventions and the implementation of such programs into practice settings. Strategies to identify patients at risk for treatment failure (rationally- and empirically-derived decision rules) are presented. Additionally, evidence for the usefulness of feedback systems is discussed. The report ends with the description of an ongoing feedback intervention study in private practices in Germany (aimed at gathering information on 400 therapists with 2,000 patients).

Psychosocial treatments for cocaine dependence: the role of depressive symptoms

BACKGROUND

The association between cocaine use and depression has been frequently observed. However, less is known about the significance of depression in the treatment of cocaine use disorders. This study examined possible interrelations between drug use and depression severity among cocaine-dependent patients in psychosocial treatments for cocaine dependence.

METHODS

Monthly assessed drug use and depression severity scores of N = 487 patients during 6-month psychosocial treatments for cocaine dependence were analyzed using hybrid latent growth models.

RESULTS

Results indicated a moderate but statistically significant (z = 3.13, p < .01) influence of depression severity on increased drug use in the upcoming month, whereas drug use did not affect future depression severity.

CONCLUSIONS

Findings suggest that depression symptoms are an important predictor of drug use outcomes during psychosocial treatments for cocaine dependence and, hence, underline the importance of adequately addressing depression symptoms to improve treatment outcomes.