Patient-Reported Symptoms and Direct Health Care Costs in Head and Neck Cancer
Bibliographic record
Abstract
Importance: Head and neck cancer (HNC) and its associated treatments are associated with substantial functional, psychological, and financial consequences. Patient-reported outcome measures (PROMs) play a crucial role in capturing the full impact of disease. Understanding how PROMs are associated with health care costs is critical for cancer care planning; however, the association of health care expenditure and PROMs is yet to be clarified. Objective: To assess the association between Edmonton Symptom Assessment System (ESAS) scores and direct health care costs incurred in 30 days for adult patients with HNC. Design, Setting, and Participants: This cohort study used linked administrative datasets from Ontario, Canada, of adult patients who received a diagnosis of HNC between January 1, 2007, and December 31, 2022. Included patients had at least 1 ESAS assessment completed from the date of diagnosis to the date of death or January 31, 2023. Coprimary exposures were the highest individual symptom score (h-ESAS, from 0 to 10) and the sum total of the individual scores of the 9 symptoms (t-ESAS, from 0-90). Multivariable negative binomial regression models using a generalized estimating equation approach under an exchangeable correlation structure were used to assess the association between each primary exposure and 30-day costs, accounting for patient age, sex, immigration status, socioeconomic status, cancer type, and recent cancer-directed treatment modality, updated to each ESAS assessment date. Data analysis was performed from September 2024 to February 2025. Main Outcomes and Measures: A 30-day cost-capturing window was defined around each ESAS assessment date to comprise a 7-day interval before this date and a 22-day interval after this date. Direct health care costs incurred during this 30-day window were estimated using a patient-level case-costing algorithm adjusted to 2023 Canadian dollars. Results: The total sample population was 16 544 adult patients with HNC (mean [SD] age at diagnosis, 63.7 [11.5] y; 12 526 [75.7%] male individuals ) and their 90 025 ESAS assessments completed since the date of diagnosis. Each 1-point increase in h-ESAS was associated with a 22% increase in 30-day costs (rate ratio [RR], 1.22; 95% CI, 1.21-1.22). Likewise, relative costs increased progressively with higher t-ESAS scores, peaking among patients with scores of 71 to 80 (RR, 4.82; 95% CI, 4.32-5.39). Conclusions and Relevance: This cohort study found that both h-ESAS and t-ESAS were significantly associated with 30-day costs. These findings highlight the potential role of PROMs in cost-mitigation strategies for HNC care.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".