Patients' views about causes and preferences for the management of cancer-related fatigue—a case for non-congruence with the physicians?

Purpose: Cancer-related fatigue (CRF) is frequently overlooked. Adherence to treatment guidelines may be related to the patient's views about illness. This study aimed at exploring patients' views about CRF and determining whether they are congruent with best practice treatments. Methods: Data were collected in 160 consecutive patients hospitalized in a supportive care setting. Biological, clinical, and psychological variables were assessed using validated questionnaires. Patients were also asked to complete the Brief Fatigue Inventory (BFI) and a questionnaire investigating their main symptoms and views about CRF and its management. Results: Patients were mainly men (60%); median age was 66years. Various cancer diagnoses were represented; 17.5% had primary local diseases, 40% local recurrences, and 42.5% metastatic diseases. The majority of the patients experienced moderate or severe CRF (76.3%) on the BFI. Fatigue was the most frequently reported symptom (87.5%). Only anxiety, depression, and dimensions of quality of life were significantly related with CRF. Two thirds of the patients associated CRF with cancer-related morbidities. As for the best treatments, patients first stressed control of adverse effects. Over half of the patients were reluctant to report fatigue, mainly because they considered fatigue as an unavoidable side effect, but also because they feared a change towards less active/aggressive treatments. Conclusion: Patients mostly consider that CRF must be tolerated. Guidelines emphasize activity enhancement strategies as beneficial. The patients' preferences for rest rather than activity may be related to their high level of fatigue, which leads them to disregard activity as a possible treatmen

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Patients' views about causes and preferences for the management of cancer-related fatigue-a case for non-congruence with the physicians?

Cancer-related fatigue (CRF) is frequently overlooked. Adherence to treatment guidelines may be related to the patient's views about illness. This study aimed at exploring patients' views about CRF and determining whether they are congruent with best practice treatments

Children living with HIV in Europe: do migrants have worse treatment outcomes?

International audienceTo assess the effect of migrant status on treatment outcomes among children living with HIV in Europe

Make EU trade with Brazil sustainable

Brazil, home to one of the planet's last great forests, is currently in trade negotiations with its second largest trading partner, the European Union (EU). We urge the EU to seize this critical opportunity to ensure that Brazil protects human rights and the environment