ABSTRACT
BACKGROUND: Most terminally ill cancer patients prefer to die at home, but a majority die in institutional settings. Research questions about this discrepancy have not been fully answered. This study applies artificial intelligence and machine learning techniques to explore the complex network of factors and the cause-effect relationships affecting the place of death, with the ultimate aim of developing policies favouring home-based end-of-life care. METHODS: A data mining algorithm and a causal probabilistic model for data analysis were developed with information derived from expert knowledge that was merged with data from 116 deceased cancer patients in southern Switzerland. This data set was obtained via a retrospective clinical chart review. RESULTS: Dependencies of disease and treatment-related decisions demonstrate an influence on the place of death of 13%. Anticancer treatment in advanced disease prevents or delays communication about the end of life between oncologists, patients and families. Unknown preferences for the place of death represent a great barrier to a home death. A further barrier is the limited availability of family caregivers for terminal home care. The family's preference for the last place of care has a high impact on the place of death of 51%, while the influence of the patient's preference is low, at 14%. Approximately one-third of family systems can be empowered by health care professionals to provide home care through open end-of-life communication and good symptom management. Such intervention has an influence on the place of death of 17%. If families express a convincing preference for home care, the involvement of a specialist palliative home care service can increase the probability of home deaths by 24%. CONCLUSION: Concerning death at home, open communication about death and dying is essential. Furthermore, for the patient preference for home care to be respected, the family's decision for the last place of care seems to be key. The early initiation of family-centred palliative care and the provision of specialist palliative home care for patients who wish to die at home are suggested.
Subject(s)
Attitude to Death , Neoplasms/mortality , Neoplasms/psychology , Terminal Care/methods , Terminal Care/psychology , Terminally Ill/psychology , Adult , Aged , Aged, 80 and over , Artificial Intelligence , Data Interpretation, Statistical , Data Mining , Female , Home Care Services , Hospitalization , Humans , Machine Learning , Male , Middle Aged , Models, Statistical , Patient Satisfaction , Probability , Switzerland/epidemiology , Young AdultABSTRACT
Hepatocellular carcinoma (HCC) is the most frequent primary hepatic cancer. Pathological features can define the biological behavior and prognosis. Medullary-like HCC is a very rare variant that has been described only twice in literature. In the present study, we report the case of a non-cirrhotic 72-year-old man, who presented two HCC lesions on routine screening for hepatitis C virus liver disease. Radiological imaging and biopsy showed two different subtypes: one classic HCC, which was treated with chemoembolization, and a second PET/CT-positive carcinoma with a PET/CT-positive metastatic coeliac lymph node, which was resected laparoscopically with a left lateral sectionectomy and extended lymphadenectomy. Histopathology revealed a medullary-like HCC; lymph node analysis confirmed the metastatic nature of the PET/CT-positive coeliac node and showed an incidental B-cell lymphoma in the hepatic pedicle lymph nodes. To the best of our knowledge this is the third case of medullary-like HCC described in the literature, and the first associated to a concomitant typical HCC.