Identification and management of cancer cachexia in patients: Assessment of healthcare providers' knowledge and practice gaps
Bibliographic record
Abstract
BACKGROUND: Cancer cachexia negatively impacts patient outcomes, quality of life and survival. Identification and management of cancer cachexia remains challenging to healthcare professionals (HCPs). The aim of this assessment was to identify current gaps in HCPs' knowledge and practice for identifying and managing adults with cancer-related cachexia. Results may guide development of new educational programmes to close identified gaps and improve outcomes of cancer patients. METHODS: An international assessment was conducted using a mixed-methods approach including focus group interviews with subject matter experts and an electronic survey of practising HCP. The assessment was led by the Society on Sarcopenia, Cachexia and Wasting Disorders (SCWD) and was supported by in-country collaborating organizations. RESULTS: A quantitative survey of 58 multiple-choice questions was completed by physicians, nurses dietitians and other oncology HCP (N = 2375). Of all respondents, 23.7% lacked confidence in their ability to provide care for patients with cancer cachexia. Patients with gastrointestinal, head and neck, pulmonary cancers and leukaemia/lymphoma were reported as those at highest risk for cachexia. Only 29.1% of respondents recognized a key criterion of cancer cachexia as >5% weight loss from baseline, but many (14.4%) did not utilize a standardized definition of cancer cachexia. Despite this, most clinicians (>84%) were able to identify causes of weight loss-reduced oral intake, progressive disease, side effects of therapy and disease-related inflammation. Of all respondents, 52.7% indicated newly diagnosed patients with cancer should be screened for weight loss. In practice, 61.9% reported that patient weight was systematically tracked over time, but only 1125 (47.4%) reported they weigh their cancer patients at each visit. Treatment of cachexia focused on increasing the patient's nutritional intake by oral nutritional supplements (64.2%), energy and protein fortified foods (60.3%) and counselling by a dietitian (57.1%). Whereas many respondents (37.3%) considered cachexia inevitable, most (79.2%) believed that an interprofessional team approach could improve care and that use of standardized tools is critical. CONCLUSIONS: Findings from this international assessment highlight the challenges associated with the care of patients with cancer cachexia, opportunities for interventions to improve patient outcomes and areas of variance in care that would benefit from further analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".