Patterns of Symptoms Burden in Neuroendocrine Tumors: A Population-Based Analysis of Prospective Patient-Reported Outcomes
Bibliographic record
Abstract
BACKGROUND: How to best support patients with neuroendocrine tumors (NETs) remains unclear. Improving quality of care requires an understanding of symptom trajectories. Objective validated assessments of symptoms burden over the course of disease are lacking. This study examined patterns and risk factors of symptom burden in NETs, using patient-reported outcomes. SUBJECTS, MATERIALS, AND METHODS: A retrospective, population-based, observational cohort study of patients with NETs diagnosed from 2004 to 2015, who survived at least 1 year, was conducted. Prospectively collected patient-reported Edmonton Symptom Assessment System scores were linked to provincial administrative health data sets. Moderate-to-severe symptom scores were presented graphically for both the 1st year and 5 years following diagnosis. Multivariable Poisson regression identified factors associated with record of moderate-to-severe symptom scores during the 1st year after diagnosis. RESULTS: Among 2,721 included patients, 7,719 symptom assessments were recorded over 5 years following diagnosis. Moderate-to-severe scores were most frequent for tiredness (40%-51%), well-being (37%-49%), and anxiety (30%-40%). The proportion of moderate-to-severe symptoms was stable over time. Proportion of moderate-to-severe anxiety decreased by 10% within 6 months of diagnosis, followed by stability thereafter. Changes were below 5% for other symptoms. Similar patterns were observed for the 1st year after diagnosis. Primary tumor site, metastatic disease, younger age, higher comorbidity burden, lower socioeconomic status, and receipt of therapy within 30 days of assessment were independently associated with higher risk of elevated symptom burden. CONCLUSION: Patients with NETs have a high prevalence of moderate-to-severe patient-reported symptoms, with little change over time. Patients remain at risk of prolonged symptom burden following diagnosis, highlighting potential unmet needs. Combined with identified patient and disease factors associated with moderate-to-severe symptom scores, this information is important to support symptom management strategies to improve patient-centered care. IMPLICATIONS FOR PRACTICE: This study used population-level, prospectively collected, validated, patient-reported outcome measures to appraise the symptoms burden and trajectory of patients with neuroendocrine tumors (NETs) after diagnosis. It is the largest and most detailed analysis of patient-reported symptoms for NETs. Patients with NETs present a high burden of symptoms at diagnosis that persists up to 5 years later, highlighting unmet needs. Early and comprehensive symptom screening and management programs are needed. This information should serve to devise pathways and policies to better support patients, evaluate supportive interventions, and assess the effectiveness of symptom management at the provider, institutional, and system levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".