Symptom burden at the end of life for neuroendocrine tumors: A population-based analysis of patient-reported outcomes.
Bibliographic record
Abstract
297 Background: How to best support neuroendocrine tumor (NET) patients remains unclear. While the peri-diagnostic period has been investigated, there is no data regarding symptoms at the end of life, when suboptimal symptom control may be particularly burdensome. This study examined symptom trajectories and factors associated with high symptom burden in NET at the end of life. Methods: We conducted a population-based retrospective cohort study of NET diagnosed from 2004-2015, who died between 2007-2016. Prospectively collected patient-reported Edmonton Symptom Assessment System scores were linked to provincial administrative datasets. Moderate-to-severe symptom scores in the 6 months prior to death were presented by 2-week intervals. Multivariable Poisson regression identified factors associated with moderate-to-severe symptoms scores. Results: Among 677 decedents, 2,579 symptom assessments prior to death were analyzed. Overall, moderate-to-severe scores were most commonly reported for tiredness (86%), wellbeing (81%), lack of appetite (75%), and drowsiness (68%) at any time. This proportion changed over time, progressively increasing closer to death: 56.8% to 83.9% tiredness, 50.5% to 73.1% wellbeing, 40.9% to 80.6% lack of appetite, and 41.5% to 68.8% drowsiness. The increase was steeper in the 8 weeks before death for lack of appetite, drowsiness, and shortness of breath. On multivariate analyses, the risk of moderate-to-severe symptoms was significantly higher in the last 2 months prior to death and with shorter survival from diagnosis (< 6 months). Women reported a higher burden of anxiety, nausea, and pain than men. There was no association between symptom burden and age or primary tumor site. Conclusions: NET patients suffer a high symptom burden at the end of life, not previously described. The proportion of moderate-to-severe symptoms increases steeply as death nears, highlighting an opportunity for improved management. Combined with identified factors associated with moderate-to-severe symptom, this information is important to improve patient-centred and personalized supportive care for NET at the end of life.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".