Fear of cancer recurrence in breast cancer: A moderated serial mediation analysis of a prospective international study.

OBJECTIVE: Women dealing with breast cancer (BC) face many challenges, one of which is the fear of cancer recurrence (FCR). This study examined whether disease severity predicts FCR 6 months after cancer diagnosis through psychological distress and whether cognitive-emotion regulation moderates this effect. METHOD: The study sample included 656 women from Italy (27.5%), Finland (31.9%), Israel (19.8%), and Portugal (20.8%) diagnosed with Stages I-III of BC. Participants' age ranged between 40 and 70 years (M = 54.92, SD = 8.22). Participants were tracked following BC diagnosis and at 3 and 6 months follow-up. Participants filled out self-report questionnaires, including the FCR inventory-short form, the Hospital Anxiety and Depression Scale, and the cognitive-emotion regulation questionnaire along with medical-social-demographic data. RESULTS: Greater disease severity at baseline indicated by higher cancer stage predicted greater psychological distress, which in turn predicted greater psychological distress at 3 months. The latter predicted greater FCR at 6 months. This serial mediation model was moderated by negative cognitive-emotion regulation. The mediating effect of disease severity on FCR through psychological distress was significant only in women with mean or higher levels of negative cognitive-emotion regulation. CONCLUSION: This study suggests that facilitating psychological well-being and effective cognitive-emotion regulation in the early stages after a cancer diagnosis may protect women from FCR. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reducing motor evoked potential amplitude variability through normalization.

Background: Transcranial Magnetic Stimulation (TMS) is used for in vivo assessment of human motor cortical excitability, with application of TMS pulses over the motor cortex resulting in muscle responses that can be recorded with electromyography (EMG) as Motor Evoked Potentials (MEPs). These have been widely explored as potential biomarkers for neuropsychiatric disorders but methodological heterogeneity in acquisition, and inherent high variability, have led to constraints in reproducibility. Normalization, consisting in scaling the signal of interest to a known and repeatable measurement, reduces variability and is standard practice for between-subject comparisons of EMG. The effect of normalization on variability of MEP amplitude has not yet been explored and was assessed here using several methods. Methods: Three maximal voluntary isometric contractions (MVICs) and 40 MEPs were collected from the right hand in healthy volunteers, with a retest session conducted 4 to 8 weeks later. MEP amplitude was normalized using either external references (MVICs) or internal references (extreme MEPs). Iterative re-sampling of 30 normalized MEPs per subject was repeated 5,000 times to define, for each normalization method, distributions for between-subject coefficients of variation (CV) of the mean MEP amplitude. Intra-class correlation coefficients (ICC) were used to assess the impact of normalization on test­retest stability of MEP amplitude measurements. Results: In the absence of normalization, MEPs collected from the right hand of 47 healthy volunteers were within reported values regarding between-subject variability (95% confidence intervals for the CV: [1.0567,1.0577]) and showed good temporal stability (ICC = 0.77). Internal reference normalization substantially reduced between-subject variability, by values of up to 64%, while external reference normalization had no impact or increased between-subject variability. Normalization with the smallest references reduced test­retest stability, with use of the largest references resulting in slight reduction or improvement of ICCs. Internal reference normalization using the largest MEPs was found to be robust to several sensitivity analyses. Conclusion: Internal, but not external, reference normalization reduces between-subject variability of MEP amplitude, and has a minimal impact on within-subject variability when conducted with the largest references. Additional research is necessary to further validate these normalization methods toward potential use of MEPs as biomarkers of neuropsychiatric disorders.

Correction: Cotovio et al. Regulatory Clearance and Approval of Therapeutic Protocols of Transcranial Magnetic Stimulation for Psychiatric Disorders. Brain Sci. 2023, 13, 1029.

Missing Citation [...].

Treatment-Resistant Depression in Real-World Clinical Practice: A Systematic Literature Review of Data from 2012 to 2022.

OBJECTIVE: Real-world evidence in treatment-resistant depression (TRD; commonly defined as non-response to ≥ 2 consecutive treatments at adequate dosage and duration) is lacking. A systematic literature review was conducted to understand disease burden and treatment outcomes for patients with TRD, studied in a real-world setting over the last decade. DATA SOURCES: A literature search was conducted in May 2022 in MEDLINE, Embase, The Cochrane Libraries and PsycINFO, comprising studies published from 2012 to 2022. Bibliographies of all relevant identified systematic reviews and relevant conference proceedings from 2020 to 2022 were manually hand-searched. STUDY SELECTION: Real-world studies, including cohort, cross-sectional, case-control, chart review and registry studies, published in English and reporting outcomes in adults with TRD, were included. DATA EXTRACTION: Extracted data included study and baseline disease characteristics, treatment type, treatment response, clinical outcomes and health-related quality of life. RESULTS: Twenty studies were included. Criteria for TRD varied, but patients typically experienced long-lasting depression (range 1.4 to 16.5 years). Across studies, mean disease severity scores demonstrated moderate to severe depression, reflecting a high burden of disease at baseline. Remission rates were typically low but generally increased with longer follow-up durations. However, the heterogeneity of interventions, follow-up durations (range 2 weeks to 9.4 years) and assessment tools precluded their quantitative synthesis. Studies were frequently limited by low sample size (range 14 to 411 patients) and health-related quality of life was infrequently assessed. CONCLUSIONS: There is a lack of clinical consensus regarding the definition, assessment and monitoring of TRD in real-world practice. Nevertheless, TRD carries a high burden of illness and there is an unmet need for faster and more effective treatments. To better understand the personal burden of affected patients, future studies would benefit from standardisation of severity assessment and measures of treatment effectiveness, as well as greater consideration of health-related quality of life.

Many people continue to experience depression even after trying two or more medications. This is called treatment-resistant depression (TRD). Most of the information we have on TRD comes from clinical trials, which take place under tightly-controlled conditions. It is important to understand the effects of TRD and TRD treatments on people in their day-to-day lives. Researchers studying people's day-to-day lives call this researching in a "real-world setting". We searched for studies carried out in real-world settings in the last 10 years. We found 20 relevant studies. As these studies were in real-world settings, there were many differences between them, including differences in how TRD was diagnosed, the treatments used, how long people were monitored and how results were measured. This made it difficult to compare how successful different treatments were. Most studies included a small number of people and monitored them for a relatively short time. We found people with TRD had usually lived with it for many years and their symptoms were moderate or severe. Only two studies asked people how TRD affected their lives. These two studies found health-related quality of life and work productivity was low. Most studies found lots of people still had symptoms of depression after treatment. However, symptoms typically improved more when studies monitored people for a longer time. To improve our knowledge of TRD, future studies should monitor more people for longer and use the same ways of measuring results. They should also ask how TRD affects people's daily lives.

Indirect adjusted comparison of 6-month clinical outcomes between esketamine nasal spray and other real-world polypharmacy treatment strategies for treatment resistant depression: results from the ICEBERG study.

Background: The efficacy of esketamine nasal spray (NS) as a rapid-acting agent for treatment resistant depression (TRD) was demonstrated in comparisons with placebo, when both were given in addition to a newly initiated selective serotonin reuptake inhibitor (SSRI)/serotonin norepinephrine reuptake inhibitor (SNRI). How esketamine NS compares with commonly used real-world (RW) polypharmacy treatment strategies is not known. Method: ICEBERG was an adjusted indirect treatment comparison that analysed data from SUSTAIN-2 (NCT02497287; clinicaltrials.gov), a long-term, open-label study of esketamine NS plus SSRI/SNRI, and the European Observational TRD Cohort (EOTC; NCT03373253; clinicaltrials.gov), an observational study of routine clinical practice. Data were compared between patients receiving esketamine NS (SUSTAIN-2) and those from the EOTC treated with polypharmacy treatment strategies, either combination or augmentation. Analyses were adjusted for potential confounders, using rescaled average treatment effect among treated estimates. Threshold analyses were conducted to assess potential impact of unmeasured confounders on the robustness of analyses where esketamine NS was found to be significantly superior. Sensitivity analyses were used to understand the impact of analysis method selection and data handling. Results: Esketamine NS treatment resulted in a higher probability of 6-month response (49.7% [95% confidence interval (CI) 45.6-53.9]) and remission (33.6% [95% CI 29.7-37.6]) versus RW polypharmacy (26.8% [95% CI 21.0-32.5] and 19.4%, [95% CI 14.2-24.6], respectively). Relative risk calculations showed esketamine NS was 1.859 (95% CI 1.474-2.345; p < 0.0001) times as likely to result in response and 1.735 (1.297-2.322; p = 0.0002) times as likely to result in remission versus RW polypharmacy at 6 months. Threshold and extensive sensitivity analyses supported that analyses of esketamine NS superiority were robust. Conclusion: ICEBERG supports esketamine NS being superior to current RW individualized polypharmacy strategies, including augmentation, with benefits extending beyond acute use, to improved chance of 6-month response and remission. While unobserved confounding factors may certainly impact results of an indirect comparison, threshold analysis supported a low likelihood of this affecting the conclusions.To view an animated summary of this publication, please click on the Supplementary video.

ICEBERG study: an indirect adjusted comparison estimating the long-term benefit of esketamine nasal spray when compared with routine treatment of treatment resistant depression in general psychiatry.

Background: Treatment resistant depression (TRD) affects 10-30% of patients with major depressive disorder. In 4-week trials, esketamine nasal spray (NS) was efficacious vs. placebo when both were initiated in addition to a new selective serotonin or serotonin norepinephrine reuptake inhibitor. However, comparison with an extended range of real-world treatments (RWT) is lacking. Methods: ICEBERG was an adjusted indirect treatment comparison using propensity score-based inverse probability weighting, performed on 6-month response and remission data from patients receiving esketamine NS plus oral antidepressant from the SUSTAIN-2 (NCT02497287; clinicaltrials.gov) study, compared with patients receiving other RWT from the European Observational TRD Cohort (EOTC; NCT03373253; clinicaltrials.gov) study. SUSTAIN-2 was a long-term open-label study of esketamine NS, while the EOTC was conducted at a time when esketamine NS was not available as RWT. Threshold and sensitivity analyses were conducted to assess how robust the primary analyses were. Results: Patients receiving esketamine NS had a higher probability of 6-month response (49.7% [95% confidence interval (CI) 45.6-53.9]) and remission (33.6% [95% CI 29.7-37.6]) vs. patients receiving RWT (26.4% [95% CI 21.5-31.4] and 18.2% [95% CI 13.9-22.5], respectively), according to rescaled average treatment effect among treated estimates. Resulting adjusted odds ratios (OR) and relative risk (RR) favoured esketamine NS over RWT for 6-month response (OR 2.756 [95% CI 2.034-3.733], p < 0.0001; RR 1.882 [95% CI 1.534-2.310], p < 0.0001) and remission (OR 2.276 [95% CI 1.621-3.196], p < 0.0001; RR 1.847 [95% CI 1.418-2.406], p < 0.0001). Threshold analyses suggested that differences between the two studies were robust, and results were consistent across extensive sensitivity analyses. Conclusion: ICEBERG supports that, at 6 months, esketamine NS has a substantial and significant benefit over RWT for patients with TRD. While results may be affected by unobserved confounding factors, threshold analyses suggested these were unlikely to impact the study conclusions.To view an animated summary of this publication, please click on the Supplementary video.

Esketamine Nasal Spray versus Quetiapine for Treatment-Resistant Depression.

BACKGROUND: In treatment-resistant depression, commonly defined as a lack of response to two or more consecutive treatments during the current depressive episode, the percentage of patients with remission is low and the percentage with relapse is high. The efficacy and safety of esketamine nasal spray as compared with extended-release quetiapine augmentation therapy, both in combination with ongoing treatment with a selective serotonin reuptake inhibitor (SSRI) or a serotonin-norepinephrine reuptake inhibitor (SNRI), in patients with treatment-resistant depression are unknown. METHODS: In an open-label, single-blind (with raters unaware of group assignments), multicenter, phase 3b, randomized, active-controlled trial, we assigned patients, in a 1:1 ratio, to receive flexible doses (according to the summary of product characteristics) of esketamine nasal spray (esketamine group) or extended-release quetiapine (quetiapine group), both in combination with an SSRI or SNRI. The primary end point was remission, defined as a score of 10 or less on the Montgomery-Åsberg Depression Rating Scale (MADRS), at week 8 (scores range from 0 to 60, with higher scores indicating more severe depression). The key secondary end point was no relapse through week 32 after remission at week 8. All patients were included in the analysis; patients who discontinued the trial treatment were considered as having had an unfavorable outcome (i.e., they were grouped with patients who did not have remission or who had a relapse). Analyses of the primary and key secondary end points were adjusted for age and number of treatment failures. RESULTS: Overall, 336 patients were assigned to the esketamine group and 340 to the quetiapine group. More patients in the esketamine group than in the quetiapine group had remission at week 8 (91 of 336 patients [27.1%] vs. 60 of 340 patients [17.6%]; P = 0.003) and had no relapse through week 32 after remission at week 8 (73 of 336 patients [21.7%] vs. 48 of 340 patients [14.1%]). Over 32 weeks of follow-up, the percentage of patients with remission, the percentage of patients with a treatment response, and the change in the MADRS score from baseline favored esketamine nasal spray. The adverse events were consistent with the established safety profiles of the trial treatments. CONCLUSIONS: In patients with treatment-resistant depression, esketamine nasal spray plus an SSRI or SNRI was superior to extended-release quetiapine plus an SSRI or SNRI with respect to remission at week 8. (Funded by Janssen EMEA; ESCAPE-TRD ClinicalTrials.gov number, NCT04338321.).

Well-being trajectories in breast cancer and their predictors: A machine-learning approach.

OBJECTIVE: This study aimed to describe distinct trajectories of anxiety/depression symptoms and overall health status/quality of life over a period of 18 months following a breast cancer diagnosis, and identify the medical, socio-demographic, lifestyle, and psychological factors that predict these trajectories. METHODS: 474 females (mean age = 55.79 years) were enrolled in the first weeks after surgery or biopsy. Data from seven assessment points over 18 months, at 3-month intervals, were used. The two outcomes were assessed at all points. Potential predictors were assessed at baseline and the first follow-up. Machine-Learning techniques were used to detect latent patterns of change and identify the most important predictors. RESULTS: Five trajectories were identified for each outcome: stably high, high with fluctuations, recovery, deteriorating/delayed response, and stably poor well-being (chronic distress). Psychological factors (i.e., negative affect, coping, sense of control, social support), age, and a few medical variables (e.g., symptoms, immune-related inflammation) predicted patients' participation in the delayed response and the chronic distress trajectories versus all other trajectories. CONCLUSIONS: There is a strong possibility that resilience does not always reflect a stable response pattern, as there might be some interim fluctuations. The use of machine-learning techniques provides a unique opportunity for the identification of illness trajectories and a shortlist of major bio/behavioral predictors. This will facilitate the development of early interventions to prevent a significant deterioration in patient well-being.

Regulatory Clearance and Approval of Therapeutic Protocols of Transcranial Magnetic Stimulation for Psychiatric Disorders.

Non-invasive brain stimulation techniques (NIBS) have been widely used in both clinical and research contexts in neuropsychiatry. They are safe and well-tolerated, making NIBS an interesting option for application in different settings. Transcranial magnetic stimulation (TMS) is one of these strategies. It uses electromagnetic pulses for focal modulate ion of neuronal activity in brain cortical regions. When pulses are applied repeatedly (repetitive transcranial magnetic stimulation-rTMS), they are thought to induce long-lasting neuroplastic effects, proposed to be a therapeutic mechanism for rTMS, with efficacy and safety initially demonstrated for treatment-resistant depression (TRD). Since then, many rTMS treatment protocols emerged for other difficult to treat psychiatric conditions. Moreover, multiple clinical studies, including large multi-center trials and several meta-analyses, have confirmed its clinical efficacy in different neuropsychiatric disorders, resulting in evidence-based guidelines and recommendations. Currently, rTMS is cleared by multiple regulatory agencies for the treatment of TRD, depression with comorbid anxiety disorders, obsessive compulsive disorder, and substance use disorders, such as smoking cessation. Importantly, current research supports the potential future use of rTMS for other psychiatric syndromes, including the negative symptoms of schizophrenia and post-traumatic stress disorder. More precise knowledge of formal indications for rTMS therapeutic use in psychiatry is critical to enhance clinical decision making in this area.

Personalized Risk Analysis to Improve the Psychological Resilience of Women Undergoing Treatment for Breast Cancer: Development of a Machine Learning-Driven Clinical Decision Support Tool.

BACKGROUND: Health professionals are often faced with the need to identify women at risk of manifesting poor psychological resilience following the diagnosis and treatment of breast cancer. Machine learning algorithms are increasingly used to support clinical decision support (CDS) tools in helping health professionals identify women who are at risk of adverse well-being outcomes and plan customized psychological interventions for women at risk. Clinical flexibility, cross-validated performance accuracy, and model explainability permitting person-specific identification of risk factors are highly desirable features of such tools. OBJECTIVE: This study aimed to develop and cross-validate machine learning models designed to identify breast cancer survivors at risk of poor overall mental health and global quality of life and identify potential targets of personalized psychological interventions according to an extensive set of clinical recommendations. METHODS: A set of 12 alternative models was developed to improve the clinical flexibility of the CDS tool. All models were validated using longitudinal data from a prospective, multicenter clinical pilot at 5 major oncology centers in 4 countries (Italy, Finland, Israel, and Portugal; the Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back [BOUNCE] project). A total of 706 patients with highly treatable breast cancer were enrolled shortly after diagnosis and before the onset of oncological treatments and were followed up for 18 months. An extensive set of demographic, lifestyle, clinical, psychological, and biological variables measured within 3 months after enrollment served as predictors. Rigorous feature selection isolated key psychological resilience outcomes that could be incorporated into future clinical practice. RESULTS: Balanced random forest classifiers were successful at predicting well-being outcomes, with accuracies ranging between 78% and 82% (for 12-month end points after diagnosis) and between 74% and 83% (for 18-month end points after diagnosis). Explainability and interpretability analyses built on the best-performing models were used to identify potentially modifiable psychological and lifestyle characteristics that, if addressed systematically in the context of personalized psychological interventions, would be most likely to promote resilience for a given patient. CONCLUSIONS: Our results highlight the clinical utility of the BOUNCE modeling approach by focusing on resilience predictors that can be readily available to practicing clinicians at major oncology centers. The BOUNCE CDS tool paves the way for personalized risk assessment methods to identify patients at high risk of adverse well-being outcomes and direct valuable resources toward those most in need of specialized psychological interventions.

Replicability of motor cortex-excitability modulation by intermittent theta burst stimulation.

OBJECTIVE: Transcranial Magnetic Stimulation (TMS) allows for cortical-excitability (CE) assessment and its modulation has been associated with neuroplasticity-like phenomena, thought to be impaired in neuropsychiatric disorders. However, the stability of these measures has been challenged, defying their potential as biomarkers. This study aimed to test the temporal stability of cortical-excitability modulation and study the impact of individual and methodological factors in determining within- and between-subject variability. METHODS: We recruited healthy-subjects to assess motor cortex (MC) excitability modulation, collecting motor evoked potentials (MEP) from both hemispheres, before and after left-sided intermittent theta burst stimulation (iTBS), to obtain a measure of MEPs change (delta-MEPs). To assess stability across-time, the protocol was repeated after 6 weeks. Socio-demographic and psychological variables were collected to test association with delta-MEPs. RESULTS: We found modulatory effects on left MC and not on right hemisphere following iTBS of left MC. Left delta-MEP was stable across-time when performed immediately after iTBS (ICC = 0.69), only when obtained first in left hemisphere. We discovered similar results in a replication cohort testing only left MC (ICC = 0.68). No meaningful associations were found between demographic and psychological factors and delta-MEPs. CONCLUSIONS: Delta-MEP is stable immediately after modulation and not impacted by different individual factors, including expectation about TMS-effect. SIGNIFICANCE: Motor cortex excitability modulation immediately after iTBS should be further explored as a potential biomarker for neuropsychiatric diseases.

Personalized prediction of one-year mental health deterioration using adaptive learning algorithms: a multicenter breast cancer prospective study.

Identifying individual patient characteristics that contribute to long-term mental health deterioration following diagnosis of breast cancer (BC) is critical in clinical practice. The present study employed a supervised machine learning pipeline to address this issue in a subset of data from a prospective, multinational cohort of women diagnosed with stage I-III BC with a curative treatment intention. Patients were classified as displaying stable HADS scores (Stable Group; n = 328) or reporting a significant increase in symptomatology between BC diagnosis and 12 months later (Deteriorated Group; n = 50). Sociodemographic, life-style, psychosocial, and medical variables collected on the first visit to their oncologist and three months later served as potential predictors of patient risk stratification. The flexible and comprehensive machine learning (ML) pipeline used entailed feature selection, model training, validation and testing. Model-agnostic analyses aided interpretation of model results at the variable- and patient-level. The two groups were discriminated with a high degree of accuracy (Area Under the Curve = 0.864) and a fair balance of sensitivity (0.85) and specificity (0.87). Both psychological (negative affect, certain coping with cancer reactions, lack of sense of control/positive expectations, and difficulties in regulating negative emotions) and biological variables (baseline percentage of neutrophils, thrombocyte count) emerged as important predictors of mental health deterioration in the long run. Personalized break-down profiles revealed the relative impact of specific variables toward successful model predictions for each patient. Identifying key risk factors for mental health deterioration is an essential first step toward prevention. Supervised ML models may guide clinical recommendations toward successful illness adaptation.

Trajectories of Quality of Life among an International Sample of Women during the First Year after the Diagnosis of Early Breast Cancer: A Latent Growth Curve Analysis.

The current study aimed to track the trajectory of quality of life (QoL) among subgroups of women with breast cancer in the first 12 months post-diagnosis. We also aimed to assess the number and portion of women classified into each distinct trajectory and the sociodemographic, clinical, and psychosocial factors associated with these trajectories. The international sample included 699 participants who were recruited soon after being diagnosed with breast cancer as part of the BOUNCE Project. QoL was assessed at baseline and after 3, 6, 9, and 12 months, and we used Latent Class Growth Analysis to identify trajectory subgroups. Sociodemographic, clinical, and psychosocial factors at baseline were used to predict latent class membership. Four distinct QoL trajectories were identified in the first 12 months after a breast cancer diagnosis: medium and stable (26% of participants); medium and improving (47%); high and improving (18%); and low and stable (9%). Thus, most women experienced improvements in QoL during the first year post-diagnosis. However, approximately one-third of women experienced consistently low-to-medium QoL. Cancer stage was the only variable which was related to the QoL trajectory in the multivariate analysis. Early interventions which specifically target women who are at risk of ongoing low QoL are needed.

Criterion and construct validity of the Beck Depression Inventory (BDI-II) to measure depression in patients with cancer: The contribution of somatic items

Background/Objective: Screening for depression in patients with cancer can be difficult due to overlap between symptoms of depression and cancer. We assessed validity of the Beck Depression Inventory (BDI-II) in this population. Method: Data was obtained in an outpatient neuropsychiatry unit treating patients with and without cancer. Psychometric properties of the BDI-II Portuguese version were assessed separately in 202 patients with cancer, and 376 outpatients with mental health complaints but without cancer. Results: Confirmatory factor analysis suggested a three-factor structure model (cognitive, affective and somatic) provided best fit to data in both samples. Criterion validity was good for detecting depression in oncological patients, with an area under the ROC curve (AUC) of 0.85 (95% confidence interval [CI], 0.76–0.91). A cut-off score of 14 had sensitivity of 87% and specificity of 73%. Excluding somatic items did not significantly change the ROC curve for BDI-II (difference AUCs = 0.002, p=0.9). A good criterion validity for BDI-II was also obtained in the non-oncological population (AUC = 0.87; 95% CI 0.81–0.91), with a cut-off of 18 (sensitivity=84%; specificity=73%). Conclusions: The BDI-II demonstrated good psychometric properties in patients with cancer, comparable to a population without cancer. Exclusion of somatic items did not affect screening accuracy. (AU)

Striatal dopamine D2-like receptors availability in obesity and its modulation by bariatric surgery: a systematic review and meta-analysis.

There is significant evidence linking a 'reward deficiency syndrome' (RDS), comprising decreased availability of striatal dopamine D2-like receptors (DD2lR) and addiction-like behaviors underlying substance use disorders and obesity. Regarding obesity, a systematic review of the literature with a meta-analysis of such data is lacking. Following a systematic review of the literature, we performed random-effects meta-analyses to determine group differences in case-control studies comparing DD2lR between individuals with obesity and non-obese controls and prospective studies of pre- to post-bariatric surgery DD2lR changes. Cohen's d was used to measure effect size. Additionally, we explored factors potentially associated with group differences in DD2lR availability, such as obesity severity, using univariate meta-regression. In a meta-analysis including positron emission tomography (PET) and single-photon emission computed tomography (SPECT) studies, striatal DD2lR availability did not significantly differ between obesity and controls. However, in studies comprising patients with class III obesity or higher, group differences were significant, favoring lower DD2lR availability in the obesity group. This effect of obesity severity was corroborated by meta-regressions showing inverse associations between the body mass index (BMI) of the obesity group and DD2lR availability. Post-bariatric changes in DD2lR availability were not found, although a limited number of studies were included in this meta-analysis. These results support lower DD2lR in higher classes of obesity which is a more targeted population to explore unanswered questions regarding the RDS.

Psychological and somatic symptoms among breast cancer patients in four European countries: A cross-lagged panel model.

Psychological and physical health among women with breast cancer are linked. However, more research is needed to test the interrelations between psychological and somatic symptoms, over time and throughout the different phases of breast cancer treatment, to determine when and which interventions should be prioritized. Six hundred and eighty nine women from four countries (Finland, Israel, Italy and Portugal) completed questionnaires during their first clinical consultation following diagnosis with breast cancer, and again after 3 and 6 months. The questionnaires included self-reported measures of psychological symptoms (Hospital Anxiety and Depression Scale; the Positive and Negative Affect Schedule Short Form) and somatic symptoms [selected items from the International European Organization for Research and Treatment of Cancer (EORTC) questionnaires]. Psychological and somatic symptoms were relatively stable across the three time-points. Cross-lagged paths leading from somatic to psychological symptoms (beta coefficients of 0.08-0.10), as well as vice-versa (beta 0.11-0.12), were found to be significant. No evidence was found for cross-cultural differences in mutual effects of psychological and somatic symptoms. The findings of this study call for tailoring personal interventions for breast cancer patients-either from a somatic perspective or a psychological perspective-and adjust them to the specific experiences of the individual patient.

Criterion and construct validity of the Beck Depression Inventory (BDI-II) to measure depression in patients with cancer: The contribution of somatic items.

Background/Objective: Screening for depression in patients with cancer can be difficult due to overlap between symptoms of depression and cancer. We assessed validity of the Beck Depression Inventory (BDI-II) in this population. Method: Data was obtained in an outpatient neuropsychiatry unit treating patients with and without cancer. Psychometric properties of the BDI-II Portuguese version were assessed separately in 202 patients with cancer, and 376 outpatients with mental health complaints but without cancer. Results: Confirmatory factor analysis suggested a three-factor structure model (cognitive, affective and somatic) provided best fit to data in both samples. Criterion validity was good for detecting depression in oncological patients, with an area under the ROC curve (AUC) of 0.85 (95% confidence interval [CI], 0.76-0.91). A cut-off score of 14 had sensitivity of 87% and specificity of 73%. Excluding somatic items did not significantly change the ROC curve for BDI-II (difference AUCs = 0.002, p=0.9). A good criterion validity for BDI-II was also obtained in the non-oncological population (AUC = 0.87; 95% CI 0.81-0.91), with a cut-off of 18 (sensitivity=84%; specificity=73%). Conclusions: The BDI-II demonstrated good psychometric properties in patients with cancer, comparable to a population without cancer. Exclusion of somatic items did not affect screening accuracy.