We describe the outcomes in cancer patients during the initial outbreak of the COVID-19 in Europe from the retrospective, multi-center observational OnCovid study. We identified 204 cancer patients from eight centers in the United Kingdom, Italy, and Spain aged >18 (mean = 69) and diagnosed with COVID-19 between 26 February and 1 April 2020. A total of 127 (62%) were male, 184 (91%) had a diagnosis of solid malignancy, and 103 (51%) had non-metastatic disease. A total of 161 (79%) had >1 co-morbidity. A total of 141 (69%) patients had >1 COVID-19 complication. A total of 36 (19%) were escalated to high-dependency or intensive care. A total of 59 (29%) died, 53 (26%) were discharged, and 92 (45%) were in-hospital survivors. Mortality was higher in patients aged >65 (36% vs. 16%), in those with >2 co-morbidities (40% vs. 18%) and developing >1 complication from COVID-19 (38% vs. 4%, p = 0.004). Multi-variable analyses confirmed age > 65 and >2 co-morbidities to predict for patient mortality independent of tumor stage, active malignancy, or anticancer therapy. During the early outbreak of SARS-CoV-2 infection in Europe co-morbid burden and advancing age predicted for adverse disease course in cancer patients. The ongoing OnCovid study will allow us to compare risks and outcomes in cancer patients between the initial and later stages of the COVID-19 pandemic.

Background: Despite the increasing number of ICU admissions among patients with solid tumours, there is a lack of tools with which to identify patients who may benefit from critical support. We aim to characterize the clinical profile and outcomes of patients with solid malignancies admitted to the ICU. Methods: Retrospective observational study of patients with cancer non-electively admitted to the ICU of the Hospital Clinic of Barcelona (Spain) between January 2019 and December 2019. Data regarding patient and neoplasm characteristics, ICU admission features and outcomes were collected from medical records. Results: 97 ICU admissions of 84 patients were analysed. Lung cancer (22.6%) was the most frequent neoplasm. Most of the patients had metastatic disease (79.5%) and were receiving oncological treatment (75%). The main reason for ICU admission was respiratory failure (38%). Intra-ICU and in-hospital mortality rates were 9.4% and 24%, respectively. Mortality rates at 1, 3 and 6 months were 19.6%, 36.1% and 53.6%. Liver metastasis, gastrointestinal cancer, hypoalbuminemia, elevated basal C-reactive protein, ECOG-PS greater than 2 at ICU admission, admission from ward and an APACHE II score over 14 were related to higher mortality. Functional status was severely affected at discharge, and oncological treatment was definitively discontinued in 40% of the patients. Conclusion: Medium-term mortality and functional deterioration of patients with solid cancers non-electively admitted to the ICU are high. Surrogate markers of cachexia, liver metastasis and poor ECOG-PS at ICU admission are risk factors for mortality.

Background: In a patient-centred model of care, referral to early palliative care (EPC) depends on both the prognosis and the complexity of care needs. The PALCOM scale is a 5-domain multidimensional assessment tool developed to identify the level of complexity of palliative care needs of cancer patients. The aim of this study was to validate the PALCOM scale. Patient and methods: We conducted a prospective cohort study of cancer patients to compare the PALCOM scale and expert empirical assessment (EA) of the complexity of palliative care needs. The EA had to categorise patients according to their complexity, considering that medium to high levels required priority attention from specialist EPC teams, while those with low levels could be managed by non-specialist teams. Systematically collected multidimensional variables were recorded in an electronic report form and stratified by level of complexity and rating system (PALCOM scale versus EA). The correlation rank (Kendall’s tau test) and accuracy test (F1-score) between the two rating systems were analysed. ROC curve analysis was used to determine the predictive power of the PALCOM scale. Results: A total of 283 advanced cancer patients were included. There were no significant differences in the frequency of the levels of complexity between the EA and the PALCOM scale (low 22.3–23.7%; medium 57.2–59.0%; high 20.5–17.3%). The prevalence of high symptom burden, severe pain, functional impairment, socio-familial risk, existential/spiritual problems, 6-month mortality and in-hospital death was significantly higher (p < 0.001) at the high complexity levels in both scoring systems. Comparative analysis showed a high correlation rank and accuracy between the two scoring systems (Kendall’s tau test 0.81, F1 score 0.84). The predictive ability of the PALCOM scale was confirmed by an area under the curve in the ROC analysis of 0.907 for high and 0.902 for low complexity. Conclusions: In a patient-centred care model, the identification of complexity is a key point to appropriate referral and management of shared care with EPC teams. The PALCOM scale is a high precision tool for determining the level of complexity of palliative care needs.

Introduction: Identifying the complexity of palliative care needs is a key aspect of referral to specialized multidisciplinary early palliative care (EPC) teams. The PALCOM scale is an instrument consisting of five multidimensional assessment domains developed in 2018 and validated in 2023 to identify the level of complexity in patients with advanced cancer. (1) Objectives: The main objective of this study was to determine the degree of instability (likelihood of level change or death), health resource consumption and the survival of patients according to the level of palliative complexity assigned at the baseline visit during a 6-month follow-up. (2) Method: An observational, prospective, multicenter study was conducted using pooled data from the development and validation cohort of the PALCOM scale. The main outcome variables were as follows: (a) instability ratio (IR), defined as the probability of level change or death; (b) emergency department visits; (c) days of hospitalization; (d) hospital death; (e) survival. All the variables were analyzed monthly according to the level of complexity assigned at the baseline visit. (3) Results: A total of 607 patients with advanced cancer were enrolled. According to the PALCOM scale, 20% of patients were classified as low complexity, 50% as medium and 30% as high complexity. The overall IR was 45% in the low complexity group, 68% in the medium complexity group and 78% in the high complexity group (p < 0.001). No significant differences in mean monthly emergency department visits (0.2 visits/ patient/month) were observed between the different levels of complexity. The mean number of days spent in hospital per month was 1.5 in the low complexity group, 1.8 in the medium complexity group and 3.2 in the high complexity group (p < 0.001). The likelihood of in-hospital death was significantly higher in the high complexity group (29%) compared to the medium (16%) and low (8%) complexity groups (p < 0.001). Six-month survival was significantly lower in the high complexity group (24%) compared to the medium (37%) and low (57%) complexity groups (p < 0.001). Conclusion: According to the PALCOM scale, more complex cases are associated with greater instability and use of hospital resources and lower survival. The data also confirm that the PALCOM scale is a consistent and useful tool for describing complexity profiles, targeting referrals to the EPC and managing the intensity of shared care.

Immune checkpoint inhibitors (ICI) have revolutionized the landscape of cancer treatment. Although several studies have shown that ICIs have a better safety profile than chemotherapy, some patients develop immune-related adverse events (irAEs), which require specialized and multidisciplinary management. Since ICI indications are rapidly increasing, it is crucial that clinicians involved in cancer care learn to identify irAEs and manage them properly. Here, we report a case series of 23 patients with severe irAEs requiring hospitalization over a period of 12 months and seize the opportunity to review and update different general features related to irAEs along with the management of the most frequent severe irAEs in our series.