Search

Purpose Adequate integration of palliative care in oncological care can improve the quality of life in patients with advanced cancer. Whether such integration affects the use of diagnostic procedures and medical interventions has not been studied extensively. We investigated the effect of the implementation of a standardized palliative care pathway in a hospital on the use of diagnostic procedures, anticancer treatment, and other medical interventions in patients with incurable cancer at the end of their life. Methods In a pre- and post-intervention study, data were collected concerning adult patients with cancer who died between February 2014 and February 2015 (pre-PCP period) or between November 2015 and November 2016 (post-PCP period). We collected information on diagnostic procedures, anticancer treatments, and other medical interventions during the last 3 months of life. Results We included 424 patients in the pre-PCP period and 426 in the post-PCP period. No differences in percentage of laboratory tests (85% vs 85%, p = 0.795) and radiological procedures (85% vs 82%, p = 0.246) were found between both groups. The percentage of patients who received anticancer treatment or other medical interventions was lower in the post-PCP period (40% vs 22%, p p Conclusions Implementation of a PCP resulted in fewer medical interventions, including anticancer treatments, in the last 3 months of life. Implementation of the PCP may have created awareness among physicians of patients’ impending death, thereby supporting caregivers and patients to make appropriate decisions about medical treatment at the end of life. Trial registration number Netherlands Trial Register; clinical trial number: NL 4400 (NTR4597); date registrated: 2014–04-27.

Purpose: To assess the association of gastrointestinal problems, received nutritional care, and nutritional care needs with quality of life (QoL) in patients with advanced cancer. Methods: A cross-sectional analysis within the observational prospective eQuiPe cohort study on experienced quality of care and QoL in patients with advanced cancer was performed. QoL and gastrointestinal problems were measured using the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ)-C30. Received nutritional care (yes/no) and nutritional care needs (yes/a little bit/no) were measured by two questions. Gastrointestinal problems were categorized as clinically important based on the Giesinger thresholds. Univariable and multivariable linear regression analyses adjusted for age, gender, and treatment were used to analyze the association of gastrointestinal problems, received nutritional care, and nutritional care needs with QoL. Results: Half of the 1080 patients with advanced cancer had clinically important gastrointestinal problems, 17% experienced nutritional care needs, and 14% received nutritional care. Multivariable analyses revealed that the presence of clinically important gastrointestinal problems (β (95% CI): −13.0 (−15.6; −10.4)), received nutritional care (β (95% CI): −5.1 (−8.5; −1.7)), and nutritional care needs (β (95% CI): −8.7 (−11.9; −5.5)) were associated with a low QoL. Conclusion: Many patients with advanced cancer experience gastrointestinal problems, while only few patients receive nutritional care. These gastrointestinal problems, nutritional care needs, and nutritional care are associated with lower QoL, probably due to reversed causality or the irreversible nature of these problems in the palliative phase. More research on the relation of nutritional care, gastrointestinal problems, and QoL is needed to optimize nutritional support in end-of-life care.

ObjectiveThe death of a loved one is considered to be the most stressful of all life events. However, the impact of bereavement on quality of life varies between individuals. The aim of our study was to assess emotional functioning (EF), which is a domain of quality of life, of bereaved relatives after the death of their loved one and its associated factors.MethodA prospective, longitudinal, multicenter, observational study on quality of care and quality of life of patients with advanced cancer and their relatives was conducted (eQuiPe). The association between EF of relatives during bereavement and the following factors was investigated: gender, type of relationship, educational level, pre-bereavement emotional and social functioning and global quality of life, social support pre- and during bereavement, anticipatory complicated grief, support of healthcare professionals during bereavement, age of patient and bereaved relative and duration of survival after primary cancer diagnosis.Results150 bereaved relatives completed the bereavement questionnaire. In 41% of the bereaved relatives EF was ≤71, indicating clinically relevant low EF. Multivariable logistic regression showed that females experienced more often emotional problems (OR = 2.82). Emotional functioning pre-bereavement (OR = 0.96) and social support during bereavement (OR = 0.97) were associated with low EF during bereavement.ConclusionsAlmost half of the bereaved relatives of patients with advanced cancer experienced low EF and this was associated with low EF pre-bereavement and low social support during bereavement. Support for relatives should be initiated before the patient's death. Future research is needed to investigate the impact of such support on relatives' wellbeing during bereavement.

ImportanceTo optimize palliative care in patients with cancer who are in their last year of life, timely and accurate prognostication is needed. However, available instruments for prognostication, such as the surprise question (“Would I be surprised if this patient died in the next year?”) and various prediction models using clinical variables, are not well validated or lack discriminative ability.ObjectiveTo develop and validate a prediction model to calculate the 1-year risk of death among patients with advanced cancer.Design, Setting, and ParticipantsThis multicenter prospective prognostic study was performed in the general oncology inpatient and outpatient clinics of 6 hospitals in the Netherlands. A total of 867 patients were enrolled between June 2 and November 22, 2017, and followed up for 1 year. The primary analyses were performed from October 9 to 25, 2019, with the most recent analyses performed from June 19 to 22, 2022. Cox proportional hazards regression analysis was used to develop a prediction model including 3 categories of candidate predictors: clinician responses to the surprise question, patient clinical characteristics, and patient laboratory values. Data on race and ethnicity were not collected because most patients were expected to be of White race and Dutch ethnicity, and race and ethnicity were not considered as prognostic factors. The models’ discriminative ability was assessed using internal-external validation by study hospital and measured using the C statistic. Patients 18 years and older with locally advanced or metastatic cancer were eligible. Patients with hematologic cancer were excluded.Main Outcomes and MeasuresThe risk of death by 1 year.ResultsAmong 867 patients, the median age was 66 years (IQR, 56-72 years), and 411 individuals (47.4%) were male. The 1-year mortality rate was 41.6% (361 patients). Three prediction models with increasing complexity were developed: (1) a simple model including the surprise question, (2) a clinical model including the surprise question and clinical characteristics (age, cancer type prognosis, visceral metastases, brain metastases, Eastern Cooperative Oncology Group performance status, weight loss, pain, and dyspnea), and (3) an extended model including the surprise question, clinical characteristics, and laboratory values (hemoglobin, C-reactive protein, and serum albumin). The pooled C statistic was 0.69 (95% CI, 0.67-0.71) for the simple model, 0.76 (95% CI, 0.73-0.78) for the clinical model, and 0.78 (95% CI, 0.76-0.80) for the extended model. A nomogram and web-based calculator were developed to support clinicians in adequately caring for patients with advanced cancer.Conclusions and RelevanceIn this study, a prediction model including the surprise question, clinical characteristics, and laboratory values had better discriminative ability in predicting death among patients with advanced cancer than models including the surprise question, clinical characteristics, or laboratory values alone. The nomogram and web-based calculator developed for this study can be used by clinicians to identify patients who may benefit from palliative care and advance care planning. Further exploration of the feasibility and external validity of the model is needed.

Objective The aim of this study is to examine why patients are hospitalised in the last stage of life. Methods Our study was conducted in a large Dutch teaching hospital. We conducted a retrospective chart review of patients aged >= 18 years who died of cancer either during hospitalisation or after discharge to receive terminal care outside the hospital. We collected data about the characteristics of these hospitalisations and indicators of advance care planning. Results Of the 264 deceased patients, 56% had died in the hospital and 44% after hospital discharge. Of all patients, 80% had been admitted to the hospital because of symptom distress. Dyspnoea (39%) and pain (33%) were the most common symptoms. Most patients underwent diagnostic procedures (laboratory tests [97%] and radiology tests [91%]) and received medical treatment (analgesics [71%] and antibiotics [55%]) during their hospitalisation. A 'Do-Not-Resuscitate' code had been recorded before admission in 42% of the patients and in an additional 52% during admission. Conclusion Our study shows that patients with cancer in the last stage of life were mainly admitted to the hospital because of symptom distress. Some hospitalisations and in-hospitals deaths may be avoided by more timely recognition of patients' impending death and start of advance care planning.

Background: The death of a loved one is considered as one of the most stressful life events. During the COVID-19 pandemic, grief processes are potentially affected by measures such as social distancing and self-quarantine. Aim: The aim of this study was to give insight in the impact of the COVID-19 pandemic on quality of life, social support, and self-care of bereaved relatives of people with advanced cancer in order to evaluate whether care for bereaved relatives during the COVID-19 pandemic should be improved. Design: A cross-sectional analysis using data from bereaved relatives of a prospective, longitudinal, multicenter, observational study on quality of care and quality of life of people with advanced cancer and their (bereaved) relatives (eQuiPe). Setting/participants: Quality of life, social support, and self-care of bereaved relatives who completed a questionnaire within 3–6 months after their relative died during COVID-19 (April-November 2020) were compared with bereaved relatives who completed this questionnaire pre-COVID-19 (April-November 2019). Results: Ninety-one bereaved relatives were included in the analysis, 44 bereaved relatives completed the questionnaire pre-COVID-19 and 47 during COVID-19. The median age of the participants was 65 (IQR = 14) years and 58% were female. There were no significant differences between the pre-COVID-19 and during COVID-19 bereaved relatives in quality of life (68 vs 69), social support (17 vs 18), and self-care (20 vs 19). Conclusions: On the short-term, the COVID-19 pandemic did not have significant impact on bereaved relatives’ wellbeing. However, long-term impact of the pandemic on their wellbeing should be assessed.

Purpose: Adequate integration of palliative care in oncological care can improve the quality of life of patients with advanced cancer. Whether such integration affects the use of diagnostic procedures and medical interventions has barely been studied. We studied the effect of implementation of a standardized Palliative Care Pathway in a hospital on the use of diagnostic procedures, anticancer treatment, and other medical interventions for patients with incurable cancer in the last three months of life.Methods: In a pre- and post-intervention study, data were collected concerning adult patients with cancer who died between February 2014 and February 2015 (pre-PCP period) or between November 2015 and November 2016 (post-PCP period). We collected information on diagnostic procedures, anticancer treatments and other medical interventions during the last three months of life.Results: We included 424 patients in the pre-PCP period and 426 in the post-PCP period. No differences were found for the percentage of patients for whom laboratory tests (85% vs 85%, p=0.795) or radiological procedures (85% vs 82%, p=0.246) were performed. The percentage of patients who received anticancer treatment or other medical interventions was lower in the post-PCP period (40% vs 22%, pConclusions: Implementation of a PCP resulted in fewer medical interventions, including anticancer treatments, in the last three months of life. Implementation of the PCP may have created awareness among physicians of patients’ impending death, thereby supporting caregivers and patients to make appropriate decisions about medical treatment at the end of life.Trial registration number: Netherlands Trial Register; clinical trial number: NL 4400 (NTR4597); date registrated: 2014-04-27

Objective: This prospective study aimed to evaluate the performance of the ‘Surprise Question’ (SQ) ‘Would I be surprised if this patient died in the next 12 months?’ in predicting survival of 12, 6, 3 and 1 month(s), respectively, in hospitalised patients with cancer. Methods: In three hospitals, physicians were asked to answer SQs for 12/6/3/1 month(s) for inpatients with cancer. Sensitivity, specificity, positive and negative predictive values were calculated. Results: A total of 783 patients were included, of whom 51% died in the 12-month period after inclusion. Sensitivity of the SQ predicting death within 12 months was 0.79, specificity was 0.66, the positive predictive value was 0.71 and the negative predictive value was 0.75. When the SQ concerned a shorter survival period, sensitivities and positive predictive values decreased, whereas specificities and negative predictive values increased. In multivariable logistic regression analysis, the SQ was significantly associated with mortality (OR 3.93, 95% CI 2.70–5.71, p < 0.01). Conclusions: The 12-month SQ predicts death in patients with cancer admitted to the hospital reasonably well. Shortening the timeframe decreases sensitivities and increases specificities. The four surprise questions may help to identify patients for whom palliative care is indicated.

OBJECTIVE For patients who are discharged to go home after a hospitalisation, timely and adequately informing their general practitioner is important for continuity of care, especially at the end of life. We studied the quality of the hospital discharge letter for patients who were hospitalised in their last year of life. METHODS A retrospective medical record review was performed. Included patients had been admitted to the hospital during the period 1 January to 1 July 2017 and had died within a year after discharge. RESULTS Data were collected from records of 108 patients with cancer or other diseases. For 57 patients (53%), the discharge letter included information that related to their limited life expectancy (e.g., agreements about treatment limitations), whereas the patient's limited life expectancy was addressed in the medical record in 76 cases (70%). We found related information in discharge letters for 36 patients (66%) who died

Context: Early integration of oncology and palliative care has been recommended to improve patient outcomes at the end of life. A standardized Palliative Care Pathway, consisting of a structured electronic medical checklist, may support such integration. Objectives: We studied the effect of implementation of a Palliative Care Pathway on patients’ place of death and advance care planning. Methods: We conducted a prospective pre- and postimplementation study of adult patients with cancer from a single hospital who died between February 2014 and February 2015 (pre-implementation period) or between November 2015 and November 2016 (post-implementation period). Results: We included 424 patients in the pre- and 426 in the post-implementation period. The pathway was started for 236 patients (55%) in the post-implementation period, on average 33 days (IQR 12-73 days) before death. 74% and 77% of the patients died outside hospital in the pre- and post-implementation period, respectively (P = 0.360). When the PCP was initiated, 83% died outside hospital. Bad-news conversations (75% and 62%, P < 0.001) and preferred place of death (47% and 32%, P < 0.001) were more often documented in the pre-implementation period, whereas a DNR-code was more often documented during the post-implementation period (79% and 89%, P < 0.001). Conclusions: Implementation of a Palliative Care Pathway had no overall positive effect on place of death and several aspects of advance care planning. Start of a Palliative Care Pathway in the last months of life may be too late to improve end-of-life care. Future research should focus on strategies enabling earlier start of palliative care interventions.

CONTEXT: Palliative care aims to support patients' spiritual needs with the intention of promoting their spiritual well-being (SWB), an important dimension of quality of life. SWB is one of the less-studied dimensions of QoL, particularly in a secular country such as the Netherlands.OBJECTIVES: In this study we aimed to get a better understanding of SWB in Dutch patients with advanced cancer. We therefore examined its prominence and associated factors.METHODS: We used the baseline data of a cohort study on experienced quality of care and quality of life (eQuiPe study), which included 1,103 patients with advanced cancer. In addition to sociodemographic and religious/spiritual characteristics, study measures comprised the SWB subscales Meaning, Peace, and Faith of the revised FACIT-Sp-12, spiritual problems and needs (PNPCsv), quality of life (EORTC-QLQ-C30) and satisfaction with healthcare professionals' interpersonal skills (INPATSAT-32).RESULTS: On average, patients experienced quite a bit of Meaning (8.9, SD 2.3), a little bit to somewhat Peace (6.8, SD 2.7), and very low levels of Faith (2.9, SD 3.7). Two-thirds (71%) of patients reported one or more spiritual problems, for which the majority (54%) wanted to receive attention. In the final multivariable models, only a few factors were associated with SWB, such as greater spiritual needs with lower levels of Meaning and Peace.CONCLUSION: Dutch patients with advanced cancer experience medium to low levels of Meaning, Peace, and Faith. More attention for their SWB is warranted.

Background: Early palliative care team consultation has been shown to reduce costs of hospital care. The objective of this study was to investigate the association between palliative care team (PCT) consultation and the content and costs of hospital care in patients with advanced cancer. Material and Methods: A prospective, observational study was conducted in 12 Dutch hospitals. Patients with advanced cancer and an estimated life expectancy of less than 1 year were included. We compared hospital care during 3 months of follow-up for patients with and without PCT involvement. Propensity score matching was used to estimate the effect of PCTs on costs of hospital care. Additionally, gamma regression models were estimated to assess predictors of hospital costs. Results: We included 535 patients of whom 126 received PCT consultation. Patients with PCT had a worse life expectancy (life expectancy

132 Background: Advance care planning is necessary for cancer patients who are in their last year of life. We developed a clinical model to predict 1-year mortality for patients with advanced cancer. Methods: Patients with advanced cancer and no curatively aimed treatment options were included in a prospective multicenter observational study involving six hospitals in the Netherlands (June-November 2017). Using cox regression, a model was developed with candidate predictors as identified in literature: surprise question (SQ), clinical characteristics (age, sex, primary tumor, metastases, WHO performance status, food intake, weight loss, pain, comorbidity, dyspnea, and fatigue), and laboratory values (serum albumin, hemoglobin, and C-reactive protein). The primary outcome was all-cause 1-year mortality. Discriminative ability was measured using the c-statistic and assessed using internal-external validation by study hospital. Results: Of 867 patients (median age 66 years, male 47%), 362 (42%) died within 1-year follow-up. Three models were developed: model 1: SQ; model 2: SQ + clinical characteristics; model 3: SQ + clinical characteristics + laboratory values. Predictors included in the most expansive model 3 were: SQ ‘no’ (ref: ‘yes’; HR 3.43, 95% CI 2.57-4.58), age per 10 years (HR 1.07, 95% CI 0.97-1.18), primary tumor-site (ref: prostate, breast, or thyroid; HR 1.35, 95% CI 1.01-1.82), visceral metastases (HR 1.32, 95% CI 1.05-1.65), brain metastases (HR 1.54, 95% CI 1.07-2.22), WHO performance status 1 (ref: 0; HR 1.03, 95% CI 0.76-1.41), WHO performance status 2+ (ref: 0; HR 1.50, 95% CI 1.04-2.15), any weight loss (ref: none; HR 1.09, 95% CI 0.86-1.38), pain score (HR 1.03, 95% CI 0.98-1.09); dyspnea grade 1 (ref: 0; HR 1.20, 95% CI 0.94-1.54), dyspnea grade 2+ (ref: 0; HR 1.33, 95% CI 0.93-1.91), C-reactive protein (HR 1.15, 95% CI 1.04-1.27), and serum albumin (HR 0.97, 95% CI 0.95-1.00). The pooled c-statistic at internal-external validation was 0.69 for model 1, 0.76 for model 2, and 0.78 for model 3. Conclusions: A model that combines the SQ with easily available clinical characteristics (with or without laboratory values) is more accurate in predicting 1-year mortality in patients with advanced cancer than the SQ alone.

17 Background: Awareness is growing that palliative care is an important part in the hospital. It is aimed to improve the quality of life of patients and their relatives in the end-stage of a disease by a multidimensional approach. Prior to the development and implementation of a digital Care Pathway for Palliative Care, we wanted to map the palliative care process during the last hospitalization prior to death of patients with malignancies. Methods: We studied the medical files of patients who died in the period 1 July 2011 – 1 July 2012 within six months after having been admitted to the Department of Oncology and Lung diseases in a general hospital. A checklist was used to collect data about the patients’ diagnosis; the care that was provided during their last stay in the hospital; and about characteristics of the dying process. Results: In total 149 medical records were examined. Most of the patients (78%) were admitted because of complications or progression of the disease. During their last hospitalization, 90% of the patients underwent radiologic tests and 97% underwent blood tests. Furthermore, 38% of the patients received chemotherapy. Of all patients, 55% died during their last stay in the hospital. Medical files contained limited information about the care process: 18% contained information about provision of information to the general practitioner (GP) during admission, 78% contained reports of bad-news conversations. In 36%, the patient’s preference concerning their place of death was unknown. Further, there was no optimal communication with the GP after the patient had died in the hospital; 87% of the GP’s were informed. Conclusions: Palliative care in the hospital was found to involve suboptimal communication on several important topics. A structured medical file to guide palliative care may contribute to improvement of the care process. We are now evaluating the effects of a digital Care Pathway for Palliative Care, that includes ‘marking’ of the palliative phase of a disease and supports adequate communication, advanced care planning, multidisciplinary cooperation and continuity of care.