Search

(1) Background: International cancer treatment guidelines recommend low-threshold psycho-oncological support based on nurses’ routine distress screening (e.g., via the distress thermometer and problem list). This study aims to explore factors which are associated with declining psycho-oncological support in order to increase nurses’ efficiency in screening patients for psycho-oncological support needs. (2) Methods: Using machine learning, routinely recorded clinical data from 4064 patients was analyzed for predictors of patients declining psycho-oncological support. Cross validation and nested resampling were used to guard against model overfitting. (3) Results: The developed model detects patients who decline psycho-oncological support with a sensitivity of 89% (area under the cure of 79%, accuracy of 68.5%). Overall, older patients, patients with a lower score on the distress thermometer, fewer comorbidities, few physical problems, and those who do not feel sad, afraid, or worried refused psycho-oncological support. (4) Conclusions: Thus, current screening procedures seem worthy to be part of daily nursing routines in oncology, but nurses may need more time and training to rule out misconceptions of patients on psycho-oncological support.

Abstract Introduction International guidelines on cancer treatment recommend screening for early detection and treatment of distress. However, screening rates are insufficient. In the present study, a survey was developed to assess perceived systemic barriers to distress screening. Methods A three‐step approach was used for the study. Based on qualitative content analysis of interviews and an expert panel, an initial survey with 53 questions on barriers to screening was designed. It was completed by 98 nurses in a large comprehensive cancer center in Switzerland. From this, a short version of the survey with 24 questions was derived using exploratory principal component analysis. This survey was completed by 150 nurses in four cancer centers in Switzerland. A confirmatory factor analysis was then performed on the shortened version, yielding a final set of 14 questions. Results The initial set of 53 questions was reduced to a set of 14 validated questions retaining 53% of the original variance. These 14 questions allow for an assessment within 2–3 min that identifies relevant barriers to distress screening from the perspective of those responsible for implementation of distress screening. Across several hospitals in Switzerland, the timing of the first distress screening, lack of capacity, patient and staff overload, and refusal of distressed patients to be referred to support services emerged as major problems. Conclusion The validated 14 questions on barriers to screening cancer patients for distress enable clinicians and hospital administrators to quickly identify relevant issues and take action to improve screening programs.

Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer’s disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aβ42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05–3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57–2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00–1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26–0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid β beyond age.

Background: Psycho-oncological support (PO) is an effective measure to reduce distress and improve the quality of life in patients with cancer. Currently, there are only a few studies investigating the (expressed) wish for PO. The aim of this study was to evaluate the number of patients who request PO and to identify predictors for the wish for PO. Methods: Data from 3063 cancer patients who had been diagnosed and treated at a Comprehensive Cancer Center between 2011 and 2019 were analyzed retrospectively. Potential predictors for the wish for PO were identified using logistic regression. As a novelty, a Back Propagation Neural Network (BPNN) was applied to establish a prediction model for the wish for PO. Results: In total, 1752 patients (57.19%) had a distress score above the cut-off and 14.59% expressed the wish for PO. Patients’ requests for pastoral care (OR = 13.1) and social services support (OR = 5.4) were the strongest predictors of the wish for PO. Patients of the female sex or who had a current psychiatric diagnosis, opioid treatment and malignant neoplasms of the skin and the hematopoietic system also predicted the wish for PO, while malignant neoplasms of digestive organs and older age negatively predicted the wish for PO. These nine significant predictors were used as input variables for the BPNN model. BPNN computations indicated that a three-layer network with eight neurons in the hidden layer is the most precise prediction model. Discussion: Our results suggest that the identification of predictors for the wish for PO might foster PO referrals and help cancer patients reduce barriers to expressing their wish for PO. Furthermore, the final BPNN prediction model demonstrates a high level of discrimination and might be easily implemented in the hospital information system.

(1) Background: International cancer treatment guidelines recommend low-threshold psycho-oncological support based on nurses' routine distress screening (e.g., via the distress thermometer and problem list). This study aims to explore factors which are associated with declining psycho-oncological support in order to increase nurses' efficiency in screening patients for psycho-oncological support needs. (2) Methods: Using machine learning, routinely recorded clinical data from 4064 patients was analyzed for predictors of patients declining psycho-oncological support. Cross validation and nested resampling were used to guard against model overfitting. (3) Results: The developed model detects patients who decline psycho-oncological support with a sensitivity of 89% (area under the cure of 79%, accuracy of 68.5%). Overall, older patients, patients with a lower score on the distress thermometer, fewer comorbidities, few physical problems, and those who do not feel sad, afraid, or worried refused psycho-oncological support. (4) Conclusions: Thus, current screening procedures seem worthy to be part of daily nursing routines in oncology, but nurses may need more time and training to rule out misconceptions of patients on psycho-oncological support. [ABSTRACT FROM AUTHOR]

Introduction: International guidelines on cancer treatment recommend screening for early detection and treatment of distress. However, screening rates are insufficient. In the present study, a survey was developed to assess perceived systemic barriers to distress screening. Methods: A three‐step approach was used for the study. Based on qualitative content analysis of interviews and an expert panel, an initial survey with 53 questions on barriers to screening was designed. It was completed by 98 nurses in a large comprehensive cancer center in Switzerland. From this, a short version of the survey with 24 questions was derived using exploratory principal component analysis. This survey was completed by 150 nurses in four cancer centers in Switzerland. A confirmatory factor analysis was then performed on the shortened version, yielding a final set of 14 questions. Results: The initial set of 53 questions was reduced to a set of 14 validated questions retaining 53% of the original variance. These 14 questions allow for an assessment within 2–3 min that identifies relevant barriers to distress screening from the perspective of those responsible for implementation of distress screening. Across several hospitals in Switzerland, the timing of the first distress screening, lack of capacity, patient and staff overload, and refusal of distressed patients to be referred to support services emerged as major problems. Conclusion: The validated 14 questions on barriers to screening cancer patients for distress enable clinicians and hospital administrators to quickly identify relevant issues and take action to improve screening programs. [ABSTRACT FROM AUTHOR]

Introduction: Research suggests a global shortfall of psycho-oncological assessment and care during the COVID-19 pandemic in addition to delayed diagnosis of cancer. The present study is the first to explore the effect of the pandemic on the provision of psycho-oncological care, stage of cancer at first diagnosis, and duration of hospitalizations. Method: Retrospective latent class analysis of 4,639 electronic patient files with all types, treatment types, and stages of cancer, 370 of which were treated during the pandemic prior to availability of vaccinations. Discussion: Latent class analysis identified four subgroups based on differences in screening for distress, provision of psycho-oncological support (consultation with a psychiatrist or clinical psychologist), administration of psychotropic medication, use of 1:1 observation, stage of cancer at first diagnosis, and duration of hospitalizations. Yet, the pandemic had no effect on subgrouping. Thus, the COVID-19 pandemic had no effect on the provision of psycho-oncological support. Conclusion: Results are contrary to prior research. The efficiency and quality of procedures implemented to provide psycho-oncological support during and prior to the pandemic are critically reflected. [ABSTRACT FROM AUTHOR]

This study explores the role of steroid administration in identifying distressed or even mentally disordered cancer patients (so‐called case finding). Charts of 12 298 cancer patients (4499 treated with prednisone equivalents) were analysed descriptively. A subset of 10 945 was further explored via latent class analysis (LCA). LCA avoids confounding by indication because it subgroups patients without prior preconceptions based on homogeneous expression of traits (i.e. the variables examined). LCA identified four subgroups: two subgroups with high dosages of prednisone equivalent (≥80 mg/day on average over all treatment days) and two with low dosages. The two subgroups with high average dosages had an increased likelihood of psychotropic drug administration, but only one was more likely to require 1:1 observation. In one subgroup, low dosages of prednisone equivlents correlated with a slightly increased probability for a psychiatric assessment and psychotropic drug administration. The subgroup least likely to receive steroid treatment was also the least likely to receive a psychiatric assessment and psychotropic drug administration. Descriptive statistics on age, sex, cumulative inpatient treatment, type of cancer, stage of cancer at first diagnosis, mental disorders, severe mental disorders and psychotropic drug administration (antidepressants, antipsychotics, benzodiazepines, anticonvulsants/mood stabilizers, opioids) are provided for patients receiving no, less and more than 80 mg of prednisone equivalent. [ABSTRACT FROM AUTHOR]

Background: Psycho-oncological support (PO) is an effective measure to reduce distress and improve the quality of life in patients with cancer. Currently, there are only a few studies investigating the (expressed) wish for PO. The aim of this study was to evaluate the number of patients who request PO and to identify predictors for the wish for PO. Methods: Data from 3063 cancer patients who had been diagnosed and treated at a Comprehensive Cancer Center between 2011 and 2019 were analyzed retrospectively. Potential predictors for the wish for PO were identified using logistic regression. As a novelty, a Back Propagation Neural Network (BPNN) was applied to establish a prediction model for the wish for PO. Results: In total, 1752 patients (57.19%) had a distress score above the cut-off and 14.59% expressed the wish for PO. Patients' requests for pastoral care (OR = 13.1) and social services support (OR = 5.4) were the strongest predictors of the wish for PO. Patients of the female sex or who had a current psychiatric diagnosis, opioid treatment and malignant neoplasms of the skin and the hematopoietic system also predicted the wish for PO, while malignant neoplasms of digestive organs and older age negatively predicted the wish for PO. These nine significant predictors were used as input variables for the BPNN model. BPNN computations indicated that a three-layer network with eight neurons in the hidden layer is the most precise prediction model. Discussion: Our results suggest that the identification of predictors for the wish for PO might foster PO referrals and help cancer patients reduce barriers to expressing their wish for PO. Furthermore, the final BPNN prediction model demonstrates a high level of discrimination and might be easily implemented in the hospital information system. [ABSTRACT FROM AUTHOR]