Gaps in Patient Education on Safe Handling and Disposal of Oral Chemotherapy Drugs: A Pilot Prospective Cohort Survey Study

Background Oral anticancer chemotherapy (OC) has been misperceived as being safer than intravenous chemotherapy, leading to its increased risk of improper handling and disposal. This survey study assessed the knowledge, practices and attitudes of pharmacists and patients regarding OC handling and disposal, gaps in knowledge and barriers to patient education. Methods Surveys were developed based on literature review and pilot study validation results. Patients completed a 33-item paper or electronic survey whereas pharmacists completed a 38-item electronic survey. Descriptive statistics and Fisher’s exact test computed using the R Project were used for analyses. Results Pharmacist group (16/25, 62.5%) and patient group (14/29, 48.3%) believed that the oral route is safer than IV. Average overall correct response rates for pharmacist and patient groups were 78.3% and 61.9%, respectively. Significant gaps in knowledge between groups were observed in three sections (p \u3c 0.05). Common barriers to providing patient education were insufficient training (70.8%) and insufficient time (50%). Conclusion Pharmacist and patient knowledge, awareness and practices of OC safe handling and disposal are suboptimal. Areas of knowledge gaps and barriers to patient education were identified. Enhanced supports are needed to empower pharmacists to assume an active role in patient education on safe handling and disposal of OC

Pathological Investigation of Congenital Bicuspid Aortic Valve Stenosis, Compared with Atherosclerotic Tricuspid Aortic Valve Stenosis and Congenital Bicuspid Aortic Valve Regurgitation

Congenital bicuspid aortic valve (CBAV) is the main cause of aortic stenosis (AS) in young adults. However, the histopathological features of AS in patients with CBAV have not been fully investigated.We examined specimens of aortic valve leaflets obtained from patients who had undergone aortic valve re/placement at our institution for severe AS with CBAV (n = 24, CBAV-AS group), severe AS with tricuspid aortic valve (n = 24, TAV-AS group), and severe aortic regurgitation (AR) with CBAV (n = 24, CBAV-AR group). We compared the histopathological features among the three groups. Pathological features were classified using semi-quantitative methods (graded on a scale 0 to 3) by experienced pathologists without knowledge of the patients' backgrounds. The severity of inflammation, neovascularization, and calcium and cholesterol deposition did not differ between the CBAV-AS and TAV-AS groups, and these four parameters were less marked in the CBAV-AR group than in the CBAV-AS (all p<0.01). Meanwhile, the grade of valvular fibrosis was greater in the CBAV-AS group, compared with the TAV-AS and CBAV-AR groups (both p<0.01). In AS patients, thickness of fibrotic lesions was greater on the aortic side than on the ventricular side (both p<0.01). Meanwhile, thickness of fibrotic lesions was comparable between the aortic and ventricular sides in CBAV-AR patients (p = 0.35).Valvular fibrosis, especially on the aortic side, was greater in patients with CBAV-AS than in those without, suggesting a difference in the pathogenesis of AS between CBAV and TAV

Adaptation and psychometric evaluation of the Chinese version of the functional assessment of chronic illness therapy spiritual well-being scale among Chinese childhood cancer patients in China

BackgroundSpiritual well-being is a strength for childhood cancer patients to cope with cancer. The availability of a valid and reliable instrument for assessing spiritual well-being is crucial. This study translated and adapted the Functional Assessment of Chronic Illness Therapy Spiritual Well-being scale (FACIT-Sp) for Chinese childhood cancer patients and examined the psychometric properties and factor structure in this population.MethodsThis was a methodological study. The FACIT-Sp was translated into Chinese. Adaptation was based on our qualitative study. For psychometric evaluation, a convenience sample of 412 were recruited based on the suggested sample size for the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Childhood cancer patients were included if they aged 8–17 years, with parental consent to participate, able to communicate that they were being treated for cancer, and able to communicate and read Chinese. Participants answered the Chinese version of the adapted FACIT-Sp, the Center for Epidemiology Studies Depression Scale for Children (CES-DC), and the Pediatric Quality of Life Inventory 3.0 Cancer Module (PedsQL). Content validity, convergent validity, internal consistency and test–retest reliability were examined. Both EFA and CFA assessed the structural validity of the adapted FACIT-Sp.ResultsThe content validity index values for items ranged 0.8–1.0 and that for the scale was 0.84, indicating appropriate content validity. The scale had good internal consistency, with a Cronbach’s alpha of 0.815. The FACIT-Sp scores positively correlated with the CES-DC scores, and negatively correlated with PedsQL scores, suggesting that the Chinese version of the adapted FACIT-Sp had reasonable convergent validity. EFA yielded a four-factor (meaning, peace, faith, and connection with others) model. The CFA results revealed that the four-factor model achieved a better fit than the original three-factor model (Chi-Square Mean/Degree of Freedom = 2.240 vs. 3.557, Comparative Fit Index = 0.953 vs. 0.916, Goodness of Fit Index = 0.909 vs. 0.884, Root Mean Square Error of Approximation = 0.078 vs. 0.112).ConclusionThe Chinese version of the adapted FACIT-Sp is a reliable and valid instrument for assessing spiritual well-being among Chinese childhood cancer patients. This instrument can be applied in clinical settings for routine assessment

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

Autoimmune PaneLs as PrEdictors of Toxicity in Patients TReated with Immune Checkpoint InhibiTors (ALERT)

Background: Immune-checkpoint inhibitors (ICI) can lead to immune-related adverse events (irAEs) in a significant proportion of patients. The mechanisms underlying irAEs development are mostly unknown and might involve multiple immune effectors, such as T cells, B cells and autoantibodies (AutoAb). Methods: We used custom autoantigen (AutoAg) microarrays to profile AutoAb related to irAEs in patients receiving ICI. Plasma was collected before and after ICI from cancer patients participating in two clinical trials (NCT03686202, NCT02644369). A one-time collection was obtained from healthy controls for comparison. Custom arrays with 162 autoAg were used to detect IgG and IgM reactivities. Differences of median fluorescent intensity (MFI) were analyzed with Wilcoxon sign rank test and Kruskal–Wallis test. MFI 500 was used as threshold to define autoAb reactivity. Results: A total of 114 patients and 14 healthy controls were included in this study. irAEs of grade (G) ≥ 2 occurred in 37/114 patients (32%). We observed a greater number of IgG and IgM reactivities in pre-ICI collections from patients versus healthy controls (62 vs 32 p &lt; 0.001). Patients experiencing irAEs G ≥ 2 demonstrated pre-ICI IgG reactivity to a greater number of AutoAg than patients who did not develop irAEs (39 vs 33 p = 0.040). We observed post-treatment increase of IgM reactivities in subjects experiencing irAEs G ≥ 2 (29 vs 35, p = 0.021) and a decrease of IgG levels after steroids (38 vs 28, p = 0.009). Conclusions: Overall, these results support the potential role of autoAb in irAEs etiology and evolution. A prospective study is ongoing to validate our findings (NCT04107311)

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial.

BACKGROUND: Opioid-related adverse events are a serious problem in hospitalized patients. Little is known about patients who are likely to experience opioid-induced respiratory depression events on the general care floor and may benefit from improved monitoring and early intervention. The trial objective was to derive and validate a risk prediction tool for respiratory depression in patients receiving opioids, as detected by continuous pulse oximetry and capnography monitoring. METHODS: PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) was a prospective, observational trial of blinded continuous capnography and oximetry conducted at 16 sites in the United States, Europe, and Asia. Vital signs were intermittently monitored per standard of care. A total of 1335 patients receiving parenteral opioids and continuously monitored on the general care floor were included in the analysis. A respiratory depression episode was defined as respiratory rate ≤5 breaths/min (bpm), oxygen saturation ≤85%, or end-tidal carbon dioxide ≤15 or ≥60 mm Hg for ≥3 minutes; apnea episode lasting \u3e30 seconds; or any respiratory opioid-related adverse event. A risk prediction tool was derived using a multivariable logistic regression model of 46 a priori defined risk factors with stepwise selection and was internally validated by bootstrapping. RESULTS: One or more respiratory depression episodes were detected in 614 (46%) of 1335 general care floor patients (43% male; mean age, 58 ± 14 years) continuously monitored for a median of 24 hours (interquartile range [IQR], 17-26). A multivariable respiratory depression prediction model with area under the curve of 0.740 was developed using 5 independent variables: age ≥60 (in decades), sex, opioid naivety, sleep disorders, and chronic heart failure. The PRODIGY risk prediction tool showed significant separation between patients with and without respiratory depression (P \u3c .001) and an odds ratio of 6.07 (95% confidence interval [CI], 4.44-8.30; P \u3c .001) between the high- and low-risk groups. Compared to patients without respiratory depression episodes, mean hospital length of stay was 3 days longer in patients with ≥1 respiratory depression episode (10.5 ± 10.8 vs 7.7 ± 7.8 days; P \u3c .0001) identified using continuous oximetry and capnography monitoring. CONCLUSIONS: A PRODIGY risk prediction model, derived from continuous oximetry and capnography, accurately predicts respiratory depression episodes in patients receiving opioids on the general care floor. Implementation of the PRODIGY score to determine the need for continuous monitoring may be a first step to reduce the incidence and consequences of respiratory compromise in patients receiving opioids on the general care floor