Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials.

BACKGROUND: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. AIMS: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. METHOD: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. RESULTS: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, ßpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, ßpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (ßpooled = 0.16) and the IMD index (ßpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. CONCLUSIONS: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis.

BACKGROUND: Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers). METHODS: Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs). RESULTS: Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01). CONCLUSIONS: Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Predictors of treatment attendance in patients with posttraumatic stress disorder and comorbid personality disorders.

INTRODUCTION: High dropout and low treatment attendance rates among patients with posttraumatic stress disorder (PTSD) and personality disorders (PDs) continue to pose a significant challenge. Despite numerous studies focusing on enhancing treatment attendance, the identification of consistent and reliable predictors in patients with PTSD and comorbid PDs remains limited. OBJECTIVES: This study aims to investigate a wide range of potential predictors of treatment attendance, encompassing demographic, patient-severity, treatment, and therapist-related variables in patients with PTSD and comorbid borderline and/or cluster C PDs. METHODS: Utilizing data from 255 patients participating in two randomized controlled trials comparing trauma-focused treatment with or without concurrent PD treatment, candidate predictors were individually analyzed in univariate regression models. Significant predictors were then combined in a multiple ordinal regression model. RESULTS: In total, 40% of patients attended fewer trauma-focused treatment sessions than the minimum recommended in treatment guidelines. Out of the 38 candidate predictors examined, five significant, independent predictors of treatment attendance emerged in a multiple ordinal regression model. Higher baseline PTSD severity (OR = 1.04, p = .036), higher education level (OR = 1.22, p = .009) and a stronger patient-rated working alliance (OR = 1.72, p = .047) with the therapist predicted higher treatment attendance. Conversely, inadequate social support from friends (OR = 0.90, p = .042) and concurrent PD treatment and trauma-focused treatment (OR = 0.52, p = .022) were associated with lower treatment attendance. CONCLUSIONS: In conclusion, this constitutes the first study investigating predictors of treatment attendance in patients with PTSD and comorbid PDs. The results highlight the complexity of pinpointing reliable predictors. Nevertheless, the identification of five predictors provides valuable insights, aiding clinicians in customizing treatment strategies for individual patients and enhancing overall treatment attendance.

Economic evaluation of intensive home treatment in comparison to care as usual alongside a randomised controlled trial.

BACKGROUND: There is a dearth of research on the cost-effectiveness of intensive home treatment (IHT), an alternative to psychiatric hospitalisation for patients experiencing psychiatric crises. We therefore present a health economic evaluation alongside a pre-randomised controlled trial of IHT compared to care as usual (CAU). METHOD: Patients were pre-randomised to IHT or CAU using a double-consent open-label Zelen design. For the cost-utility analysis, the EuroQol 5-dimensional instrument was used. The cost-effectiveness was assessed using the Brief Psychiatric Rating Scale (BPRS). RESULTS: Data of 198 patients showed that each additional QALY gained from offering IHT instead of CAU was on average associated with an extra cost of €48,003. There is a 38% likelihood that IHT will lead to more QALYs at lower costs compared to CAU. An improvement of one additional point on the BPRS by offering IHT instead of CAU was associated with an extra cost of €19,203. There is a 38% likelihood that IHT will lead to higher BPRS score improvements at lower costs. Based on the NICE willingness-to-pay threshold of £30,000 (€35,000) per QALY, IHT could potentially be considered cost-effective with a likelihood of 55-60% when viewed from a societal perspective, and > 75% from a health care perspective. CONCLUSIONS: IHT appears slightly more attractive in terms of cost-utility and cost-effectiveness than CAU, although differences in both costs and effects are small especially when viewed from the societal costs perspective. From the health care sector costs perspective, IHT has a higher probability of being cost-effective compared to CAU. TRIALS REGISTRATION: Netherlands Trial Register: NTR6151.

Toward an improved conceptualization of emotions in patients with cancer.

Cancer and its associated treatment is a major stressor, leading to emotions such as anxiety or depressive mood. Human emotions have developed through the course of evolution because they facilitate adaptation to important events, such as cancer and its associated treatment. On the other hand, emotions can be maladaptive and interfere with adaptation to cancer. Emotions are maladaptive if they are disproportionally severe or persistent, and if they interfere with functioning. We aim to expand the conceptualization of adaptive and maladaptive emotions in patients with cancer. We draw on major theories in the field of mental disorder and mental health, and apply these theories to conceptualize adaptive and maladaptive emotions in patients with cancer. (i) Maladaptive emotions have two essential features: mental dysfunction and patient harm. Maladaptive emotions are characterized by a network of strongly associated emotional symptoms, which may include cancer-related somatic symptoms. The dysfunctional symptom network is hypothesized to be the result of disturbance of life goal pursuit caused by cancer. (ii) Adaptive emotions have two essential features: ability to deal with cancer and functioning well. The ability to use emotions in an adaptive way depends on skills to recognize, express, and regulate emotions in a flexible manner. A secure attachment style facilitates adaptive emotional responses to cancer. The present conceptualization of adaptive and maladaptive emotions is expected to contribute to better understanding and management of emotions in patients with cancer.

The role of immuno-metabolic depression features in the effects of light therapy in patients with depression and type 2 diabetes mellitus: A randomized controlled trial.

OBJECTIVE: Immuno-metabolic depression (IMD) is proposed to be a form of depression encompassing atypical, energy-related symptoms (AES), low-grade inflammation and metabolic dysregulations. Light therapy may alleviate AES by modulating inflammatory and metabolic pathways. We investigated whether light therapy improves clinical and biological IMD features and whether effects of light therapy on AES or depressive symptom severity are moderated by baseline IMD features. Associations between changes in symptoms and biomarkers were explored. METHODS: In secondary analyses, clinical trial data was used from 77 individuals with depression and type 2 diabetes mellitus (T2DM) randomized to four weeks of light therapy or placebo. AES severity and depressive symptom severity were based on the Inventory of Depressive Symptomatology. Biomarkers included 73 metabolites (Nightingale) summarized in three principal components and CRP, IL-6, TNF-α, INF-γ. Linear regression analyses were performed. RESULTS: Light therapy had no effect on AES severity, inflammatory markers and metabolite principle components versus placebo. None of these baseline features moderated the effects of light therapy on AES severity. Only a principle component reflecting metabolites implicated in glucose homeostasis moderated the effects of light therapy on depressive symptom severity (ßinteraction = 0.65, P = 0.001, FDR = 0.003). Changes in AES were not associated with changes in biomarkers. CONCLUSION: Findings do not support the efficacy of light therapy in reducing IMD features in patients with depression and T2DM. We find limited evidence that light therapy is a more beneficial depression treatment among those with more IMD features. Changes in clinical and biological IMD features did not align over four-weeks' time. TRIAL REGISTRATION: The Netherlands Trial Register (NTR) NTR4942.

Trauma-focused and personality disorder treatment for posttraumatic stress disorder and comorbid cluster C personality disorder: a randomized clinical trial.

Background: Posttraumatic stress disorder (PTSD) is associated with high rates of cluster C personality disorders (PD), which may negatively affect PTSD treatment. It is unknown whether concurrent treatment for PTSD and comorbid PD leads to superior treatment effects, compared to standard trauma-focused treatment.Objective: The objective was to test the efficacy of adding personality disorder treatment (group schema therapy; GST) to individual trauma-focused treatment (imagery rescripting; ImRs).Method: A two-arm randomized clinical trial (1:1 allocation ratio) was conducted between 2018 and 2023 at two sites of a mental health institution in the Netherlands. Raters were blind to treatment allocation. Adult outpatients with PTSD and comorbid cluster C personality disorders were randomized to receive either ImRs (12-18 sessions) or ImRs + GST (12-18 ImRs + 52-58 GST). The main outcome was PTSD severity one year after start of treatment measured with the Clinician-Administered PTSD Scale for DSM-5.Results: Of 130 patients (mean [SD] age = 40.6 [11.2], 110 [85%] females), 66 were assigned to ImRs and 64 to ImRs + GST. At 12 months, there were large decreases in PTSD severity (dImRs = 2.42, 95%CI = 1.97-2.87; dImRs + GST = 2.44, 95%CI = 1.99-2.90), but there was no significant difference between conditions (d = 0.02, 95%CI = -0.33-0.36, p = .944). Reductions in personality disorder symptoms and all other secondary outcomes were observed in both conditions. There were no significant differences between conditions on any of the secondary outcomes at 12 months.Conclusion: The more intensive concurrent trauma-focused and personality disorder treatment (ImRs + GST) was not superior to trauma-focused treatment alone (ImRs) for patients with PTSD and comorbid CPD. This suggests that trauma-focused treatment is the preferred primary treatment in patients presenting with both internalizing personality disorder and PTSD, reserving the stepping up to more intensive psychotherapy aimed at the personality disorder as a second line of treatment.Trial registration: ClinicalTrials.gov identifier: NCT03833531.

Concurrent trauma-focused and personality disorder treatment was not superior to only trauma-focused treatment for patients with posttraumatic stress disorder (PTSD) and comorbid cluster C personality disorders.Large reductions in PTSD severity and medium-to-large reductions in all secondary outcomes, including personality disorder symptoms, were observed in both treatment arms.These findings are remarkable, given the higher therapy dosage and specialized treatment for personality disorder comorbidity in the combined treatment arm.

Network analysis used to investigate the interplay among somatic and psychological symptoms in patients with cancer and cancer survivors: a scoping review.

PURPOSE: Patients with cancer often experience multiple somatic and psychological symptoms. Somatic and psychological symptoms are thought to be connected and may reinforce each other. Network analysis allows examination of the interconnectedness of individual symptoms. The aim of this scoping review was to examine the current state of knowledge about the associations between somatic and psychological symptoms in patients with cancer and cancer survivors, based on network analysis. METHODS: This scoping review followed the five-stage framework of Arksey and O'Malley. The literature search was conducted in May, 2023 in PubMed, APA PsycINFO, Embase Cochrane central, and CINAHL databases. RESULTS: Thirty-two studies were included, with eleven using longitudinal data. Seventeen studies reported on the strength of the associations: somatic and psychological symptoms were associated, although associations among somatic as well as among psychological symptoms were stronger. Other findings were the association between somatic and psychological symptoms was stronger in patients experiencing more severe symptoms; associations between symptoms over time remained rather stable; and different symptoms were central in the networks, with fatigue being among the most central in half of the studies. IMPLICATIONS FOR CANCER SURVIVORS: Although the associations among somatic symptoms and among psychological symptoms were stronger, somatic and psychological symptoms were associated, especially in patients experiencing more severe symptoms. Fatigue was among the most central symptoms, bridging the somatic and psychological domain. These findings as well as future research based on network analysis may help to untangle the complex interplay of somatic and psychological symptoms in patients with cancer.