Enhancing Outpatient Symptom Management in Patients With Head and Neck Cancer
Bibliographic record
Abstract
IMPORTANCE: Patients with head and neck cancer manage a variety of symptoms at home on an outpatient basis. Clinician review alone often leaves patient symptoms undetected and untreated. Standardized symptom assessment using patient-reported outcomes (PROs) has been shown in randomized clinical trials to improve symptom detection and overall survival, although translation into real-world settings remains a challenge. OBJECTIVE: To better understand how patients with head and neck cancer cope with cancer-related symptoms and to examine their perspectives on standardized symptom assessment. DESIGN, PARTICIPANTS, AND SETTING: This was a qualitative analysis using semistructured interviews of patients with head and neck cancer and their caregivers from November 2, 2020, to April 16, 2021, at a regional tertiary center in Canada. Purposive sampling was used to recruit a varied group of participants (cancer subsite, treatment received, sociodemographic factors). Drawing on the Supportive Care Framework, a thematic approach was used to analyze the data. Data analysis was performed from November 2, 2020, to August 2, 2021. MAIN OUTCOMES AND MEASURES: Patient perception of ambulatory symptom management and standardized symptom assessment. RESULTS: Among 20 participants (median [range] age, 59.5 [33-74] years; 9 [45%] female; 13 [65%] White individuals), 4 themes were identified: (1) timely physical symptom management, (2) information as a tool for symptom management, (3) barriers to psychosocial support, and (4) external factors magnifying symptom burden. Participants' perceptions of standardized symptom assessment varied. Some individuals described the symptom monitoring process as facilitating self-reflection and symptom detection. Others felt disempowered by the process, particularly when symptom scores were inconsistently reviewed or acted on. CONCLUSIONS AND RELEVANCE: This qualitative analysis provides a novel description of head and neck cancer symptom management from the patient perspective. The 4 identified themes and accompanying recommendations serve as guides for enhanced symptom monitoring.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".