Time spent on documenting quality indicator data and associations between the perceived burden of documenting these data and joy in work among professionals in intensive care units in the Netherlands: a multicentre cross-sectional survey.

OBJECTIVES: The number of indicators used to monitor and improve the quality of care is debatable and may influence professionals' joy in work. We aimed to assess intensive care unit (ICU) professionals' perceived burden of documenting quality indicator data and its association with joy in work. DESIGN: Cross-sectional survey. SETTING: ICUs of eight hospitals in the Netherlands. PARTICIPANTS: Health professionals (ie, medical specialists, residents and nurses) working in the ICU. MEASUREMENTS: The survey included reported time spent on documenting quality indicator data and validated measures for documentation burden (ie, such documentation being unreasonable and unnecessary) and elements of joy in work (ie, intrinsic and extrinsic motivation, autonomy, relatedness and competence). Multivariable regression analysis was performed for each element of joy in work as a separate outcome. RESULTS: In total, 448 ICU professionals responded to the survey (65% response rate). The overall median time spent on documenting quality data per working day is 60 min (IQR 30-90). Nurses spend more time documenting these data than physicians (medians of 60 min vs 35 min, p<0.01). Most professionals (n=259, 66%) often perceive such documentation tasks as unnecessary and a minority (n=71, 18%) perceive them as unreasonable. No associations between documentation burden and measures of joy in work were found, except for the negative association between unnecessary documentations and sense of autonomy (ß=-0.11, 95% CI -0.21 to -0.01, p=0.03). CONCLUSIONS: Dutch ICU professionals spend substantial time on documenting quality indicator data they often regard as unnecessary. Despite the lacking necessity, documentation burden had limited impact on joy in work. Future research should focus on which aspects of work are affected by documentation burden and whether diminishing the burden improves joy in work.

Good versus bad news consultations in advanced breast cancer: the role of empathy in information recall - an observational study.

OBJECTIVE: We explored, in advanced breast cancer, whether: (1) patients recall less information following bad versus good news consultations; (2) empathy has a greater effect on recalled information following bad versus good news consultations. METHODS: Observational study using audio-recorded consultations. Participants' recall of provided information about treatment options, aims/positive effects and side-effects was assessed. Clinician-expressed empathy and consultation type were determined. Regression analyses assessed associations between consultation type and recall, exploring moderating influences of clinician-expressed empathy. RESULTS: For 41 consultations (18 bad news, 23 good news), recall data were completed; total recall (47% vs 73%, p=0.03) and recall about treatment options (67% vs 85%, p=0.08, trend) were significantly worse following bad news compared with good news consultations. Recall about treatment aims/positive effects (53% vs 70%, p=0.30) and side-effects (28% vs 49%, p=0.20) was not significantly worse following bad news. Empathy moderated the relationship between consultation type and total recall (p<0.01), recall about treatment options (p=0.03) and about aims/positive effects (p<0.01) but not about side-effects (p=0.10). Only following good news consultations empathy influenced recall favourably. CONCLUSIONS: This explorative study suggests that in advanced cancer, information recall is especially impaired following bad news consultations, for which empathy does not improve remembered information.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

BACKGROUND: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. METHODS: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. RESULTS: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. CONCLUSIONS: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.

INCIDENCE, RISK FACTORS, AND OUTCOME OF SUSPECTED CENTRAL VENOUS CATHETER-RELATED INFECTIONS IN CRITICALLY ILL COVID-19 PATIENTS: A MULTICENTER RETROSPECTIVE COHORT STUDY.

ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.

The effect of trastuzumab on cardiac function in patients with HER2-positive metastatic breast cancer and reduced baseline left ventricular ejection fraction.

We investigated the effect of trastuzumab on cardiac function in a real-world historic cohort of patients with HER2-positive metastatic breast cancer (MBC) with reduced baseline left ventricular ejection fraction (LVEF). Thirty-seven patients with HER2-positive MBC and baseline LVEF of 40% to 49% were included. Median LVEF was 46% (interquartile range [IQR] 44%-48%) and median follow-up was 18 months (IQR 9-34 months). During this period, the LVEF did not worsen in 24/37 (65%) patients, while 13/37 (35%) patients developed severe cardiotoxicity defined as LVEF <40% with median time to severe cardiotoxicity of 7 months (IQR 4-10 months) after beginning trastuzumab. Severe cardiotoxicity was reversible (defined as LVEF increase to a value <5%-points below baseline value) in 7/13 (54%) patients, partly reversible (defined as absolute LVEF increase ≥10%-points from nadir to a value >5%-points below baseline) in 3/13 (23%) patients and irreversible (defined as absolute LVEF increase <10%-points from nadir and to a value >5%-points below baseline) in 3/13 (23%) patients. Likelihood of reversibility was numerically higher in patients who received cardio-protective medications (CPM), including ACE-inhibitors, beta-blockers and angiotensine-2 inhibitors, compared to those who did not receive any CPM (71% vs 13%, P = .091). Sixty-five percent of patients who received trastuzumab for HER2-positive MBC did not develop severe cardiotoxicity during a median follow-up of 18 months, despite having a compromised baseline LVEF. If severe cardiotoxicity occurred, it was at least partly reversible in more than two-thirds of the cases. Risks and benefits of trastuzumab use should be balanced carefully in this vulnerable population.

Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.

BACKGROUND: The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. METHODS: This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. RESULTS: Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/-24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64-0.71], 0.61 [CI 0.58-0.66], 0.67 [CI 0.63-0.70], 0.70 [CI 0.67-0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). CONCLUSIONS: Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.

Predictors for extubation failure in COVID-19 patients using a machine learning approach.

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

OBJECTIVES: As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS: One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS: We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS: This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. METHODS: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. RESULTS: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. CONCLUSIONS: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.

BACKGROUND: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. METHODS: The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. RESULTS: A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. CONCLUSION: Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes.

Baseline effector cells predict response and NKT cells predict pulmonary toxicity in advanced breast cancer patients treated with everolimus and exemestane.

BACKGROUND: The mTOR inhibitor everolimus used in cancer has immune-modulating effects, potentially contributing to an antitumor response but also leading to pulmonary toxicity. We studied the association of immunological cell subsets with antitumor response and pulmonary toxicity in breast cancer patients treated with everolimus plus exemestane. METHODS: In this exploratory analysis, peripheral blood mononuclear cells (PBMCs) were collected at baseline and 14, 35, 60, and 90 days after start of treatment, and at the moment of pulmonary toxicity. The percentage and absolute number of T-cells, B-cells, NK-cells, monocytes and numerous subtypes were measured in peripheral blood using flow cytometric analysis and were compared using a (paired) t-test. RESULTS: From 20 patients, a total of 89 samples were collected. At baseline, responders versus non-responders had 0.86% versus 0.32% CD4+ effector cells (CD45RA+CD27-) (p = 0.1266) and non-response could be predicted with 0.71 sensitivity and 0.82 specificity. Patients who developed pulmonary toxicity compared to patients without pulmonary toxicity had relatively more NKT-cells at baseline (6.0% versus 1.3%, p = 0.0068, 59 k versus 12 k * 109/l, p = 0.0081) and at the moment of toxicity (5.2% versus 1.2%, p = 0.0106 and 47 k versus 16 k * 109/l, p = 0.0466). Baseline percentage NKT cells predicted pulmonary toxicity with 0.78 sensitivity and 1.0 specificity. CONCLUSIONS: Our results suggest that baseline CD4+ effector cells may be predictive of antitumor responses and baseline NKT cells may be predictive of pulmonary toxicity. These results warrant further validation.

The power of clinician-expressed empathy to increase information recall in advanced breast cancer care: an observational study in clinical care, exploring the mediating role of anxiety.

OBJECTIVE: Experimental studies have found that clinician-expressed empathy improves patients' information recall in (advanced) cancer consultations. It remains unclear, however, whether these results are generalizable to clinical care and, if so, what the underlying mechanism is. We aimed to i) determine the relationship between clinician-expressed empathy and patients' information recall in clinical advanced breast cancer consultations; and ii) test whether the relationship between clinician-expressed empathy and recall is mediated by a decrease in patients' anxiety. METHODS: Forty-one consultations between oncologists and female patients with advanced breast cancer were audio recorded. Patients' post-consultation information recall and pre- and post-consultation anxiety (0-100) were assessed. Recall was scored according to a self-created questionnaire. Clinician-expressed empathy (0-100) was assessed by observers. Structural Equation Modelling was used for all analyses. RESULTS: Participants remembered 61% of the information discussed. Clinician-expressed empathy significantly increased patients' total information recall (p = .041) and recall of treatment aims/positive effects (p = .028). The mediating role of anxiety could not be established. CONCLUSION: Although the underlying mechanism remains unclear, clinicians have a powerful tool to improve seriously ill breast cancer patients' recall of information: empathy. PRACTICE IMPLICATIONS: These insights should encourage clinicians to express empathy; practical communication training might prove helpful.

Hospital-based or home-based administration of oncology drugs? A micro-costing study comparing healthcare and societal costs of hospital-based and home-based subcutaneous administration of trastuzumab.

OBJECTIVE: To investigate resource use and time investments of healthcare professionals, patients and their family and to compare healthcare and societal costs of one single hospital-based and one single home-based subcutaneous administration of trastuzumab in The Netherlands. METHOD: We conducted a bottom-up micro-costing study. Patients diagnosed with HER2+ early or metastatic breast cancer were recruited in four Dutch hospitals. For healthcare costs, data were collected on drug use, consumables, use of healthcare facilities, time of healthcare professionals, and travelling distance of the nurse. For societal costs, data were collected on patient and family costs (including travelling expenses and time of informal caregivers) and productivity losses of paid and unpaid work. RESULTS: Societal costs of one single administration of SC trastuzumab were €1753 within the home-based and €1724 within the hospital-based setting. Drug costs of trastuzumab were identical in both settings (€1651). Healthcare costs were higher for home-based administration (€91 versus €47) mainly because of more time of healthcare professionals (110 versus 38 minutes). Costs for patient and family were, however, lower for home-based administration due to travelling expenses (€7 versus €0) and time of informal caregivers (€14 versus €4). Costs for productivity losses were similar for both settings. CONCLUSIONS: Home-based subcutaneous administration of trastuzumab is more time consuming for healthcare professionals and therefore more costly than hospital-based administration. The total budget impact can be large considering that a large number of patients receive a large number of cycles of oncology treatments. If home-based administration is the way forward, novel approaches are crucial for ensuring efficiency of home-based care.

Patients' and Clinicians' Perceptions of Clinician-Expressed Empathy in Advanced Cancer Consultations and Associations with Patient Outcomes.

Background: Empathy is a cornerstone of effective communication. However, clinicians' and patients' perceptions of clinician-expressed empathy might differ. The independent perceptions of patients and clinicians on clinician-expressed empathy in advanced cancer consultations and the associations of these perceptions with patient outcomes are unknown. Objective: We assessed (1) patients' and clinicians' independent perceptions of clinician-(self-)expressed empathy in advanced cancer consultations and (2) the associations between these perceptions and affective patient outcomes. Methods: This observational study included data from 41 consultations in the advanced breast cancer setting. Postconsultation, patients' and clinicians' perceptions of clinician-expressed empathy were assessed, as well as patients' (1) pre-post anxiety, (2) post-anxiety, (3) emotional well-being, and (4) satisfaction. Multilevel regression analyses were run to draw conclusions. Results: Patients perceived higher levels of empathy than clinicians, without a significant relationship between the two (mean [M] = 85.47, standard deviation [SD] = 14.00 vs. M = 61.88, SD = 15.30, 0-100 scale; ß = 0.14, p < 0.138, 95% confidence interval [CI] = -0.04 to 0.32). Higher patient-perceived empathy was associated with decreased anxiety [(1) ß = -0.67, p = 0.039, 95% CI = -1.30 to -0.03; (2) ß = -0.15, p = 0.042, 95% CI = -0.30 to -0.01], higher satisfaction (ß = 0.05, p < 0.001, 95% CI = 0.03 to 0.08), and lower emotional distress (ß = -0.32, p < 0.001, 95% CI = -0.48 to -0.16). There were no associations with clinicians' perceptions [(1) ß = -0.34, p = 0.307, 95% CI = -1.00 to 0.31; (2) ß = -0.02, p = 0.824, 95% CI = -0.17 to 0.14; (3) ß < 0.01, p = 0.918, 95% CI = -0.03 to 0.02; (4) ß = 0.08, p = 0.335, 95% CI = -0.08 to 0.25]. Conclusions: Patients' and clinicians' empathy perceptions differed. In improving patient outcomes, the focus should be on patients' perceptions of clinician-expressed empathy. Future research could focus on ways to elicit patients' perceptions of empathy with the higher aim of improving patient outcomes.

The Use of Expectancy and Empathy When Communicating With Patients With Advanced Breast Cancer; an Observational Study of Clinician-Patient Consultations.

Background: Information provision about prognosis, treatments, and side-effects is important in advanced cancer, yet also associated with impaired patient well-being. To counter potential detrimental effects, communication strategies based on placebo and nocebo effect mechanisms might be promising to apply in daily practice. This study aimed to provide more insight into how often and how oncologists use expectancy and empathy expressions in consultations with patients with advanced breast cancer. Methods: Forty-five consultations between oncologists and patients were audiotaped. To determine how often expectancy and empathy expressions were used, a coding scheme was created. Most consultations (n = 33) were coded and discussed by two coders, and the remaining 13 were coded by one coder. To determine how expectancy and empathy expressions were used, principles of inductive content analysis were followed. Results: Discussed evaluation (i.e., scan) results were good (n = 26,58%) or uncertain (n = 12,27%) and less often bad (n = 7,15%). Uncertain expectations about prognosis, treatment outcomes, and side effects occurred in 13, 38, and 27 consultations (29%, 85%, and 56%), followed by negative expectations in 8, 26, and 28 consultations (18%, 58%, and 62%) and positive expectations in 6, 34, and 17 consultations (13%, 76%, and 38%). When oncologists provided expectancy expressions, they tapped into three different dimensions: relational, personal, and explicit. Positive expectations emphasized the doctor-patient relationship, while negative expectations focused on the severity of the illness, and uncertainty was characterized by a balance between (potential) negative outcomes and hope. Observed generic or specific empathy expressions were regularly provided, most frequently understanding (n = 29,64% of consultations), respecting (n = 17,38%), supporting (n = 16,36%), and exploring (n = 16,36%). A lack of empathy occurred less often and contained, among others, not responding to patients' emotional concerns (n = 13,27% of consultations), interrupting (n = 7,16%), and an absence of understanding (n = 4,9%). Conclusion: In consultations with mainly positive or uncertain medical outcomes, oncologists predominantly made use of uncertain expectations (hope for the best, prepare for the worst) and used several empathic behaviors. Replication studies, e.g., in these and other medical situations, are needed. Follow-up studies should test the effect of specific communication strategies on patient outcomes, to counter potential negative effects of information provision. Studies should focus on uncertain situations. Ultimately, specific placebo and nocebo effect-inspired communication strategies can be harnessed in clinical care to improve patient outcomes.

Prospective Study of Drug-induced Interstitial Lung Disease in Advanced Breast Cancer Patients Receiving Everolimus Plus Exemestane.

BACKGROUND: Everolimus-related interstitial lung disease (ILD) (also: pneumonitis) poses a difficulty for physicians, as it is hard to discriminate ILD from other causes of respiratory symptoms and to decide on safe treatment continuation. OBJECTIVE: We investigated the capability of pulmonary function tests (PFT), plasma biomarkers, everolimus pharmacokinetics, and FDG-PET to discriminate between everolimus-related ILD and other causes of respiratory problems and to predict the severity of ILD. PATIENTS AND METHODS: Women starting treatment with everolimus plus exemestane for advanced breast cancer were included. At baseline and during the first 3 months, respiratory symptoms, PFT with diffusion capacity of the lungs for carbon monoxide corrected for hemoglobin (DLCOc) and forced vital capacity, serum plasma biomarkers (including SP-D and YKL-40), everolimus trough concentration, and 18F-FDG-PET were prospectively recorded. RESULTS: Twenty-seven (out of 29 included) patients were evaluable for analysis. Fifteen patients (56%) developed everolimus-related respiratory signs or symptoms and four patients (15%) needed everolimus discontinuation and received corticosteroids. Change in DLCOc differentiated ILD from alternative diagnoses with 0.91 sensitivity and 0.78 specificity. Decrease in DLCOc (non-significant) was greatest in patients who needed everolimus discontinuation. Serum SP-D and YKL-40 could differentiate ILD from alternative diagnoses with 0.83 and 0.83 sensitivity, and 0.85 and 0.62 specificity, respectively. 18F-FDG-PET abnormalities did not precede clinical symptoms. No relationship between ILD and everolimus trough concentration was found. CONCLUSIONS: This study shows that everolimus-related ILD occurs frequently. Prospective monitoring of DLCOc in combination with measurement of serum SP-D and YKL-40 appear useful to discriminate ILD from other causes of respiratory symptoms. Clinicaltrials.gov identifier: NCT01978171.

Everolimus Exposure and Early Metabolic Response as Predictors of Treatment Outcomes in Breast Cancer Patients Treated with Everolimus and Exemestane.

BACKGROUND: Treating breast cancer patients with everolimus and exemestane can be challenging due to toxicity and suboptimal treatment responses. OBJECTIVE: We investigated whether everolimus exposure and early metabolic response are predictors for toxicity and effectiveness in these patients. PATIENTS AND METHODS: We performed pharmacokinetic assessments 14 and 35 days after starting treatment. [18F]fluorodeoxyglucose-positron emission tomography (18F-FDG-PET) was performed at baseline, and 14 and 35 days after the start of the therapy. We recorded toxicity, defined as dose interventions within 3 months, and progression-free survival (PFS). RESULTS: Among 44 evaluable patients, the geometric mean (GM) Ctrough was higher in patients with toxicity compared to patients without (17.4 versus 12.3 µg/L (p = 0.02)). The optimal cut-off value to predict toxicity was Ctrough > 19.2 µg/L. GM Ctrough of patients with and without progressive disease (PD) within 3 months was not significantly different (12.0 versus 15.2 µg/L (p = 0.118)). In 28 evaluable patients, PD within 3 months could best be predicted using the percentage decrease in peak standardized uptake value normalized by lean body mass of the lesion with highest FDG uptake (SULpeak high) at day 14. Patients with <11% versus >11% decrease in SULpeak high at day 14 had a median PFS of 90 days versus 411 days, respectively (p = 0.0013) and more frequently had PD within 3 months: 70 vs 11%, respectively. CONCLUSIONS: Our results show that everolimus toxicity is related to everolimus Ctrough. No relation was observed between everolimus exposure and treatment effectiveness. An early FDG-PET can identify patients at high risk of nonresponse. These results warrant further validation. Clinicaltrials.gov identifier: NCT01948960.

Potential cost savings owing to the route of administration of oncology drugs: a microcosting study of intravenous and subcutaneous administration of trastuzumab and rituximab in the Netherlands.

There is little evidence on the costs associated with the route of administration of oncology drugs. We investigated time and resource use for hospitals and patients and compared healthcare and societal costs for intravenous (IV) and subcutaneous (SC) administration of trastuzumab and rituximab. Data for the preparation and administration of both drugs were collected at the hospital pharmacy and at the oncology day care unit. Patients completed a questionnaire for obtaining information on societal costs (productivity losses, informal care and traveling expenses). A total of 126 patients were recruited in six hospitals; 82 received trastuzumab (37 IV and 45 SC) and 44 received rituximab (23 IV and 21 SC). The costs per administration (including societal cost but excluding drug costs) were &OV0556;167 and &OV0556;264 for IV and &OV0556;76 and &OV0556;146 for SC trastuzumab and rituximab, respectively. The costs for SC administration were lower in all categories. The largest cost component was related to time spent at the day care unit (overhead costs). This resulted in savings of &OV0556;47 for SC trastuzumab and &OV0556;69 for SC rituximab. The costs related to time of healthcare professionals was &OV0556;9 lower for both drugs. The costs for consumables resulted in another &OV0556;12 savings. Societal costs were &OV0556;22 lower for SC trastuzumab and &OV0556;28 lower for SC rituximab. Although administration costs are relatively a small part of the total costs, important savings can be generated by switching to an SC route of administration especially because a large number of patients receive oncology drugs and patients receive more than one administration.

First-Line Palliative HER2-Targeted Therapy in HER2-Positive Metastatic Breast Cancer Is Less Effective After Previous Adjuvant Trastuzumab-Based Therapy.

BACKGROUND: Survival of patients with human epidermal growth receptor 2 (HER2)-positive metastatic breast cancer (MBC) has improved dramatically since trastuzumab has become available, although the disease eventually progresses in most patients. This study investigates the outcome (overall survival [OS] and time to next treatment [TNT]) in MBC patients pretreated with trastuzumab in the adjuvant setting (TP-group) compared with trastuzumab-naïve patients (TN-group) in order to investigate the possibility of trastuzumab resistance. PATIENTS AND METHODS: Patients treated with first-line HER2-targeted-containing chemotherapy were eligible for the study. A power analysis was performed to estimate the minimum size of the TP-group. OS and TNT were estimated using Kaplan-Meier curves and multivariable Cox proportional hazards models. RESULTS: Between January 1, 2000, and June 1, 2014, 469 patients were included, of whom 82 were in the TP-group and 387 were in the TN-group. Median OS and TNT were significantly worse in the TP-group compared with the TN-group (17 vs. 30 months, adjusted hazard ratio [HR] 1.84 [1.15-2.96], p = .01 and 7 vs. 13 months, adjusted HR 1.65 [1.06-2.58], p = .03) after adjustment for age, year of diagnosis, disease-free interval, hormone receptor status, metastatic site, and cytotoxic regimens. CONCLUSION: First-line trastuzumab-containing treatment regimens are less effective in patients with failure of adjuvant trastuzumab compared with trastuzumab-naïve patients and might be due to trastuzumab resistance. The impact of trastuzumab resistance on the response on dual HER2 blockade with trastuzumab and pertuzumab and how resistance mechanisms can be used in the optimization of HER2-targeted treatment lines need further investigation. IMPLICATIONS FOR PRACTICE: Evidence on the efficacy of palliative trastuzumab-based therapy after failure of trastuzumab in the adjuvant setting is limited because of a minority of patients treated with adjuvant trastuzumab in clinical trials. In this study, less clinical benefit of palliative trastuzumab-based therapy was observed in patients relapsing after adjuvant trastuzumab compared with no adjuvant trastuzumab treatment. Subgroup analyses and multivariable analyses revealed that this was independent of possible confounding factors, including adjuvant taxane-treatment. This might suggest a clinically meaningful impaired efficacy of trastuzumab after previous, in this case adjuvant, trastuzumab therapy. These results could have implications for treatment decision-making after short progression-free intervals on trastuzumab-containing regimens in the palliative setting.