Symptom burden among head and neck cancer patients in the first year after diagnosis: Association with primary treatment modality
Bibliographic record
Abstract
PURPOSE: Head and neck cancer (HNC) and its treatment affects quality of life, with significant symptom burden. The main objectives of this study were to examine symptom trajectories of HNC patients by treatment and to identify factors associated with high ESAS scores. METHODS AND MATERIALS: We conducted a retrospective cohort study in patients diagnosed with HNC in Ontario, Canada from 2007 to 2015 using linked health administrative databases. The primary outcome was a monthly patient self-reported moderate-to-severe (≥4) symptom score in the year following diagnosis. Multivariable Modified Poisson regression analyses with robust variance were used to investigate factors associated with moderate-to-severe scores. RESULTS: Of 13,827 HNC patients identified, 4793 had ≥1 ESAS assessment within 12 months of cancer diagnosis. Overall, 60% (n = 2708) and 65% (n = 2903) of patients reported moderate-to-severe pain and poor appetite, respectively. The proportion of patients reporting a score ≥4 increased significantly during treatment and was most pronounced for those who received chemoradiation (CRT). On multivariable analysis, patients who were female (Relative Risk (RR) 1.15, 95% CI 1.08-1.23, received CRT, had a higher comorbidity burden (RR 1.31, 1.23-1.39), and had a diagnosis of oropharyngeal (1.10, 1.02-1.19), or oral cavity cancer (1.31, 1.19-1.45), were at an increased risk of reporting severe pain scores (p < 0.01 for all). CONCLUSION: The majority of HNC patients report high pain scores, with symptom burden highest during the treatment phase, and especially for patients who received radiation or chemoradiation. This large study highlights the need for proactive symptom management during the HNC patients' cancer journey.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".