Feasibility of Assessing Patient Health Benefits and Incurred Costs Resulting from Early Dysphagia Intervention during and Immediately after Chemoradiotherapy for Head-and-Neck Cancer
Bibliographic record
Abstract
Background: Resource limitations affect the intensity of speech–language pathology (SLP) dysphagia interventions for patients with head-and-neck cancer (HNC). The objective of the present study was to assess the feasibility of a prospective clinical trial that would evaluate the effects on health and patient costs of early SLP dysphagia intervention for HNC patients planned for curative concurrent chemoradiotherapy (CCRT). Methods: Patients with HNC planned for curative CCRT were consecutively recruited and received dysphagia-specific intervention before, during, and for 3 months after treatment. Swallowing function, body mass index, health-related quality of life (QOL), and out-of-pocket costs were measured before CCRT, at weeks 2 and 5 during CCRT, and at 1 and 3 months after CCRT. Actuarial percutaneous endoscopic gastrostomy (PEG) removal rates and body mass index in the study patients and in a time-, age-, and disease-matched cohort were compared. Results: The study enrolled 21 patients (mean age: 54 years; 19 men). The study was feasible, having a 95% accrual rate, 10% attrition, and near completion of all outcomes. Compared with the control cohort, patients receiving dysphagia intervention trended toward a higher rate of PEG removal at 3 months after CCRT [61% (32%–78%) vs. 53% (23%–71%), p = 0.23]. During CCRT, monthly pharmaceutical costs ranged between $239 and $348, with work loss in the range of 18–30 days for patients and 8–12 days for caregivers. Conclusions: We demonstrated the feasibility of comparing health and economic outcomes in patients receiving and not receiving early SLP dysphagia intervention. These preliminary findings suggest that early SLP dysphagia intervention for HNC patients might reduce PEG dependency despite worsening health. Findings also highlight effects on financial security for these patients and their caregivers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".