The optimal duration of anticoagulation in patients with active cancer and venous thromboembolism (VTE) is unknown. Current clinical guidelines advocate anticoagulant therapy for 3–6 months and to continue anticoagulant therapy for as long as the cancer is active. However, an adequate systematic review on the rate of recurrent VTE after discontinuation of anticoagulant therapy has not been performed. For this systemic review and meta-analysis, we searched Embase.com, Medline (Ovid), Web of Science, Cochrane Library, and Google Scholar, from database inception to February 16, 2023, for studies on anticoagulant therapy in patients with cancer and the recurrence of venous thromboembolism after discontinuation of this therapy. We included randomised controlled trials and cohort studies published in English that reported on patients who met the following: cancer and a first VTE, completed at least 3 months of anticoagulant therapy, were followed after discontinuation of anticoagulant therapy, and with symptomatic recurrent VTE as an outcome during follow-up. Study-level data were requested from study authors. The primary outcome was the rate of recurrent VTE after discontinuation of anticoagulant therapy. A Bayesian random-effects meta-analysis was used to estimate the rate of recurrent VTE per 100 person-years for the pooled studies at different time intervals after discontinuation of anticoagulation therapy. We also calculated the cumulative VTE recurrence rate at different time intervals. Forest plots were mapped and the results were summarized by the median and 95% credible interval (CIs). This study was registered with PROSPERO, CRD42021249060. Of 3856 studies identified in our search, 33 studies were identified for inclusion. After requesting study-level data, 14 studies involving 1922 patients with cancer-associated thrombosis were included. The pooled rate of recurrent VTE per 100 person-years after discontinuation of anticoagulant therapy was 14.6 events (95% credible interval 6.5–22.8) in the first three months, decreasing to 1.1 events (95% CI 0.3–2.1) in year 2–3, and 2.2 events (95% CI 0.0–4.4) in year 3–5 after discontinuation of anticoagulant therapy. The cumulative VTE recurrence rate was 28.3% (95% CI 15.6–39.6%) at 1 year; 31.1% (95% CI 16.5–43.8%) at 2 years; 31.9% (95% CI 16.8–45.0%) at 3 years; and 35.0% (95% CI 16.8–47.4%) at 5 years after discontinuation of anticoagulant therapy. This meta-analysis demonstrates a high rate of recurrent VTE over time after discontinuation of anticoagulant therapy in patients with cancer-associated thrombosis. Our results support the current clinical guidelines to continue anticoagulant therapy in patients with active cancer. Erasmus MC.

To timely initiate advance care planning in patients with advanced cancer, physicians should identify patients with limited life expectancy. We aimed to identify predictors of mortality. To identify the relevant literature, we searched Embase, MEDLINE, Cochrane Central, Web of Science, and PubMed databases between January 2000–April 2020. Identified studies were assessed on risk-of-bias with a modified QUIPS tool. The main outcomes were predictors and prediction models of mortality within a period of 3–24 months. We included predictors that were studied in ≥2 cancer types in a meta-analysis using a fixed or random-effects model and summarized the discriminative ability of models. We included 68 studies (ranging from 42 to 66,112 patients), of which 24 were low risk-of-bias, and 39 were included in the meta-analysis. Using a fixed-effects model, the predictors of mortality were: the surprise question, performance status, cognitive impairment, (sub)cutaneous metastases, body mass index, comorbidity, serum albumin, and hemoglobin. Using a random-effects model, predictors were: disease stage IV (hazard ratio [HR] 7.58; 95% confidence interval [CI] 4.00–14.36), lung cancer (HR 2.51; 95% CI 1.24–5.06), ECOG performance status 1+ (HR 2.03; 95% CI 1.44–2.86) and 2+ (HR 4.06; 95% CI 2.36–6.98), age (HR 1.20; 95% CI 1.05–1.38), male sex (HR 1.24; 95% CI 1.14–1.36), and Charlson comorbidity score 3+ (HR 1.60; 95% CI 1.11–2.32). Thirteen studies reported on prediction models consisting of different sets of predictors with mostly moderate discriminative ability. To conclude, we identified reasonably accurate non-tumor specific predictors of mortality. Those predictors could guide in developing a more accurate prediction model and in selecting patients for advance care planning.

The quality of care of patients dying in the hospital is often judged as insufficient. This article describes the protocol of a study to assess the quality of care of the dying patient and the contribution of an intervention targeted on staff nurses of inpatient wards of a large university hospital in the Netherlands.

The aim of this study is to examine why patients are hospitalised in the last stage of life. 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. 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. 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.

Self-management of patients with advanced cancer is challenging. Although healthcare professionals may play a crucial role in supporting these patients, scant scientific attention has been paid to their perspectives. Therefore, we examined healthcare professionals' views on self-management and self-management support in this population. We conducted qualitative interviews with 27 purposively sampled medical specialists (n = 6), nurse specialists (n = 6), general practitioners (n = 8) and homecare/ hospice nurses (n = 7) in the Netherlands. Transcripts were analysed using thematic analysis. Healthcare professionals experienced self-management of patients with advanced cancer to be diverse, dynamic and challenging. They adopted instructive, collaborative and advisory roles in self-management support for this population. Whereas some professionals preferred or inclined towards one role, others indicated to switch roles, depending on the situation. Just like patients with advanced cancer, healthcare professionals differ in their views and approaches regarding self-management and self-management support in this population. Therefore, instructive, collaborative and advisory self-management support roles will all be useful under certain circumstances. Healthcare professionals can support self-management by being aware of their own views and communicating these clearly to their patients and colleagues. Education in self-management support should include self-reflection skills and discuss the relation between self-management and professional care.