Predictors of Treatment Response for Depression and Inadequate Social Support – The ENRICHD Randomized Clinical Trial

Background: The cyclic adenosine monophosphate response element-binding proteins (CREB) and their interaction with brain-derived neurotrophic factor (BDNF) are essential elements in signal transduction pathways important for cellular resilience and neuroplasticity. They play a decisive role in the concept of altered neuroplasticity in major depression. We have previously demonstrated that the increase in phosphorylated CREB (pCREB) in T lymphocytes is significantly associated with clinical improvement in patients treated with antidepressants. In the present study, we focused on patients treated only with psychotherapy to exclude direct pharmacological actions. In addition to pCREB, we also measured the BDNF plasma levels. Methods: pCREB in T lymphocytes was determined by Western blot; the BDNF plasma levels with solid-phase ELISA. Psychopathology was evaluated with the Hamilton Rating Scale for Depression (HAMD). Thirty patients meeting DSM-IV criteria for major depressive episodes (MDE) were recruited into this 6-week study. They received interpersonal psychotherapy (IPT) twice weekly. Results: After 6 weeks of IPT, 17 patients responded (reduction of ≥50% of baseline HAMD); after 1 week of treatment pCREB increased significantly compared to the nonresponder group. Measurement of the BDNF plasma levels revealed no differences between the responder and nonresponder groups. Furthermore, the correlations between BDNF plasma levels and pCREB were not significant. Conclusions: The early increase in pCREB is related to treatment response and does not depend on pharmacological interventions or BDNF plasma levels. For the first time, cellular biological markers could be associated with response to psychotherapy.

Section: Discussionmentioning

confidence: 99%

Changes in CREB Phosphorylation and BDNF Plasma Levels during Psychotherapy of Depression

Koch

Hinze-Selch

Stingele

et al. 2009

“…Little attention, however, has been paid to the effect of family involvement on chronic physical diseases among adults. A separate analysis of chronic physical diseases is reasonable, as evidence suggests that this patient group is more resistant to psychosocial interventions than those presenting mental diseases [21,22]. In view of the limited recovery rates for traditional biomedical approaches, there is a broad consensus that additional non-pharmacological interventions will be crucial in improving the health outcomes in chronic physical diseases [2,23].…”

Section: Introductionmentioning

confidence: 99%

Effects of Interventions Involving the Family in the Treatment of Adult Patients with Chronic Physical Diseases: A Meta-Analysis

Hartmann

Bäzner

Wild

et al. 2010

231

185

Background: Families can have considerable influence on the health of a patient with a chronic physical disease, and attempts have been made to optimise treatment by involving family members. This meta-analysis aimed to systematically assess the effects of family-oriented interventions on adults with chronic physical diseases. Methods: A systematic literature search was conducted to identify randomised clinical trials that have evaluated the effects of family-based interventions for adult patients compared to standard treatment. Interventions were classified as psychoeducation or addressing family relationships. The outcomes studied were the patient’s physical and mental health and the health of the family members. The effect sizes were calculated as Hedges’ g and combined using random-effects models. Results: Fifty-two relevant randomised controlled trials (including 8,896 patients) were extracted. The main disease groups were cardiovascular diseases including stroke, cancer and arthritis. Meta-analysis showed that family involvement resulted in significantly better health than standard treatment for all outcomes. The mean overall effect sizes were 0.32 for the patients’ physical health, 0.28 for the patients’ mental health and 0.35 for the family members’ health. Overall, the effects were not large, but they were broad, significant and stable over a long period of time. There was a tendency towards higher effects in favour of relationship-focused family interventions compared to educational interventions. Conclusions: Psychosocial interventions involving family members in the treatment of chronic physical diseases have positive effects on the health outcome for both the patient and his/her family. Further high-quality research is necessary to investigate differential effects.

“…Clinical tools such as the Diagnostic Criteria for Psychosomatic Research scale [41] could be applied to patients with somatic diseases. Distinct and effective pharmacological and nonpharmacological treatments specifically targeted to dysthymic disorder [42] potentially have impact on quality of life and medical morbidity as already shown for the effects for cognitive behavior therapy in depression comorbid with coronary heart disease [43]. Future research is required to clarify the time sequence of the onset of dysthymic disorder and medical disorders.…”

Section: Discussionmentioning

confidence: 99%

The Effects of Dysthymic Disorder on Health-Related Quality of Life and Disability Days in Persons with Comorbid Medical Conditions in the General Population

Baune

Caniato

Arolt³

et al. 2009

Background: We aimed to investigate in medical disorders the effects of comorbid dysthymic disorder as compared to major depressive disorder (MDD) on health-related quality of life (HR-QoL) and disability days in the general population. Methods: In a population-based study 4,181 individuals were assessed for the presence of dysthymic disorder and depression, utilizing the Composite International Diagnostic Interview. Each participant received a thorough medical examination to assess the presence of comorbid somatic conditions. HR-QoL was evaluated using the Medical Outcomes Survey Short-Form 36 (SF-36) and disability days were provided by self-report. Descriptive statistics, analysis of variance and multivariable logistic regression were used. Results: Comorbidity with illnesses from a maximum of 6 somatic disease groups was more prevalent in persons with dysthymic disorder (78.7%) than in those with MDD (70.4%). Persons with dysthymic disorder had a significantly lower mental health summary score in the SF-36 and more disability days than those with MDD. The physical health summary scores were not significantly different between participants with dysthymic disorder and MDD (after Bonferroni correction), suggesting that limitations in physical functioning due to comorbid medical conditions were similar in both affective disorder groups. Conclusions: These results show that affective disorders comorbid with medical, somatic illnesses have a major impact on HR-QoL and disability with more pronounced effects in dysthymic disorder than in MDD. Differences in the time course of both conditions might contribute to this finding. Our results support the need for an improved identification and treatment of affective disorders in patients with somatic illnesses.