Virological treatment outcome under HAART : does sex matter?

Background: In Germany, 17% of 59,000 persons living with HIV/AIDS are female. Accordingly, the research focus in clinical studies as well as in cohort analyses has been almost exclusively on HIV-positive men. As a consequence, there is an urgent need to characterize and evaluate the outcome of HAART in HIV-positive women and to identify special requirements of this particular patient population. Methods: Cross-sectional multicentre (n = 31 centres) evaluation to observe characteristics of 1,557 HIV-positive women receiving medical care in Germany between June 2007 and March 2008. Data acquisition was performed using standardized questionnaires. Summary of results: Of 1,557 HIV-positive women studied, 1,191 (77%) received HAART. Mean age was 40 years and average time of known HIV-infection was 9 years. Risk of HIV transmission was: 40% heterosexual intercourse in Germany, 36% heterosexual intercourse in a high prevalence country; 17% IDU; 7% other reasons for transmission. 46% of the women had a migration background. Mean time on antiretroviral treatment was 7 years. 53% of the female participants had been treated with >2 HAART-regimens. 47% of the study subjects received a PI-based regimen, 33% a NNRTI-based regimen; 20% were on other combinations. The most commonly used PI and NNRTI were lopinavir/r and nevirapine, respectively. Only 48% of all women under HAART achieved a viral load <40 copies/ml. There was a significant difference between the PI-treated group with 44% patients <40 copies/ml and the NNRTI-treated group with 56% <40 copies/ml (p = 0.003). Conclusion: We found that HIV-positive women depicted an inferior virological response to HAART compared to those previously published in German cohort analyses dominated by men (response rates >75%). Possible differences in adherence or drug resistance may have impacted these results and are currently being evaluated in ongoing sub-analyses. Of note, the lack of a study arm with male patients is a limitation of this investigation. However, this is partly off-set by the fact that there are good comparative data in the male population found in other cohorts. We conclude that our results are in discordance to the popular assumption that there are no gender specific differences in virological treatment outcome of HAART

A meta-analysis of the relation between therapeutic alliance and treatment outcome in eating disorders.

The therapeutic alliance has demonstrated an association with favorable psychotherapeutic outcomes in the treatment of eating disorders (EDs). However, questions remain about the inter-relationships between early alliance, early symptom improvement, and treatment outcome. We conducted a meta-analysis on the relations among these constructs, and possible moderators of these relations, in psychosocial treatments for EDs. Twenty studies met inclusion criteria and supplied sufficient supplementary data. Results revealed small-to-moderate effect sizes, βs = 0.13 to 0.22 (p < .05), indicating that early symptom improvement was related to subsequent alliance quality and that alliance ratings also were related to subsequent symptom reduction. The relationship between early alliance and treatment outcome was partially accounted for by early symptom improvement. With regard to moderators, early alliance showed weaker associations with outcome in therapies with a strong behavioral component relative to nonbehavioral therapies. However, alliance showed stronger relations to outcome for younger (vs. older) patients, over and above the variance shared with early symptom improvement. In sum, early symptom reduction enhances therapeutic alliance and treatment outcome in EDs, but early alliance may require specific attention for younger patients and for those receiving nonbehaviorally oriented treatments

Defining Early Positive Response to Psychotherapy: An Empirical Comparison Between Clinically Significant Change Criteria and Growth Mixture Modeling

Several different approaches have been applied to identify early positive change in response to psychotherapy so as to predict later treatment outcome and length as well as use this information for outcome monitoring and treatment planning. In this study, simple methods based on clinically significant change criteria and computationally demanding growth mixture modeling (GMM) are compared with regard to their overlap and uniqueness as well as their characteristics in terms of initial impairment, therapy outcome, and treatment length. The GMM approach identified a highly specific subgroup of early improving patients. These patients were characterized by higher average intake impairments and higher pre- to-posttreatment score differences. Although being more specific for the prediction of treatment success, GMM was much less sensitive than clinically significant and reliable change criteria. There were no differences between the groups with regard to treatment length. Because each of the approaches had specific advantages, results suggest a combination of both methods for practical use in routine outcome monitoring and treatment planning

Level of impaired control predicts outcome of moderation-oriented treatment for alcohol problems

Aims To examine the ability of the Impaired Control Scale (ICS) to predict outcome of moderation-oriented treatment for alcohol problems and to compare this predictive ability directly with that of a widely used measure of alcohol dependence, the Severity of Alcohol Dependence Questionnaire (SADQ). Design Prospective follow-up study. Setting Out-patient treatment centres. Participants A combined sample 154 problem drinkers taking part in two clinical trials of Moderation-oriented Cue Exposure in the UK and Australia. Clients were followed-up 6 (UK) and 8 (Australia) months after the end of reatment. Measurements Outcome was categorized by combining drinking behaviour at follow-up with changes on the Alcohol Problems Questionnaire from before treatment to follow-up. Controlling for research site, baseline scores on Part 2 of the ICS (substitution method) and the SADQ-C were entered in logistic regression analyses with three outcome dichotomies as dependent variables. Findings Five per cent of clients were abstinent at follow-up, 13% non-problem drinkers, 25% much improved, 24% somewhat improved and 34% unimproved. Location of treatment and ICS2 scores were significant predictors of whether or not clients achieved a successful outcome (abstinence or non-problem drinking). Using a cut-point of 25 on the ICS, two-thirds of outcomes were classified correctly as either treatment successes or failures. SADQ-C score was not a significant predictor of treatment outcome. Conclusions The ICS predicts outcome of moderation-oriented treatment among moderately dependent problem drinkers recruited mainly via newspaper advertisements. The ICS should replace the SADQ as the basis for advice to clients in this population of problem drinkers regarding whether or not a moderation goal of treatment should be pursued

Relationship of serum prolactin with severity of drug use and treatment outcome in cocaine dependence.

RATIONALE: Alteration in serum prolactin (PRL) levels may reflect changes in central dopamine activity, which modulates the behavioral effects of cocaine. Therefore, serum PRL may have a potential role as a biological marker of drug severity and treatment outcome in cocaine dependence. OBJECTIVE: We investigated whether serum PRL levels differed between cocaine-dependent (CD) subjects and controls, and whether PRL levels were associated with severity of drug use and treatment outcome in CD subjects. METHODS: Basal PRL concentrations were assayed in 141 African-American (AA) CD patients attending an outpatient treatment program and 60 AA controls. Severity of drug use was assessed using the Addiction Severity Index (ASI). Measures of abstinence and retention during 12 weeks of treatment and at 6-month follow-up were employed as outcome variables. RESULTS: The basal PRL (ng/ml) in CD patients (9.28+/-4.13) was significantly higher than controls (7.33+/-2.94) (t=3.77, P\u3c0.01). At baseline, PRL was positively correlated with ASI-drug (r=0.38, P\u3c0.01), ASI-alcohol (r=0.19, P\u3c0.05), and ASI-psychological (r=0.25, P\u3c0.01) composite scores, and with the quantity of cocaine use (r=0.18, P\u3c0.05). However, PRL levels were not significantly associated with number of negative urine screens, days in treatment, number of sessions attended, dropout rate or changes in ASI scores during treatment and at follow-up. Also, basal PRL did not significantly contribute toward the variance in predicting any of the outcome measures. CONCLUSION: Although cocaine use seems to influence PRL levels, it does not appear that PRL is a predictor of treatment outcome in cocaine dependence

Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index

Estimating the long-term effects of treatments is of interest in many fields. A common challenge in estimating such treatment effects is that long-term outcomes are unobserved in the time frame needed to make policy decisions. One approach to overcome this missing data problem is to analyze treatments effects on an intermediate outcome, often called a statistical surrogate, if it satisfies the condition that treatment and outcome are independent conditional on the statistical surrogate. The validity of the surrogacy condition is often controversial. Here we exploit that fact that in modern datasets, researchers often observe a large number, possibly hundreds or thousands, of intermediate outcomes, thought to lie on or close to the causal chain between the treatment and the long-term outcome of interest. Even if none of the individual proxies satisfies the statistical surrogacy criterion by itself, using multiple proxies can be useful in causal inference. We focus primarily on a setting with two samples, an experimental sample containing data about the treatment indicator and the surrogates and an observational sample containing information about the surrogates and the primary outcome. We state assumptions under which the average treatment effect be identified and estimated with a high-dimensional vector of proxies that collectively satisfy the surrogacy assumption, and derive the bias from violations of the surrogacy assumption, and show that even if the primary outcome is also observed in the experimental sample, there is still information to be gained from using surrogates