Neuropathic and nociceptive pain in head and neck cancer patients receiving radiation therapy
Bibliographic record
Abstract
BACKGROUND: Pain is common in head and neck cancer (HNC) patients and may be attributed to the malignancy and/or cancer treatment. Pain mechanisms and patient report of pain in HNC are expected to include both nociceptive and neuropathic components. The purpose of this study was to assess the trajectory of orofacial and other pain during and following treatment, using patient reports of neuropathic pain and nociceptive pain and pain impact. METHODS: 124 consecutive HNC patients receiving radiation therapy (RT) (95 men, 29 women; mean age: 54.7 +/- 12.3 years) participated in a patient-reported outcome (PRO) assessment. Patients completed the McGill Pain Questionnaire three times during therapy and 3 months following study entry. RESULTS: The majority of patients related their pain to the tumor and/or cancer treatment. Whereas 59% reported their pain to be less severe than they expected, 29% were not satisfied with their level of pain despite pain management during cancer therapy. Worst pain was 3.0 +/- 1.3 on a 0- to 5-point verbal descriptor scale. Pain intensity was present at entry, highest at 2-week follow-up, declining towards the end of treatment and persisting at 3-month follow-up. The most common neuropathic pain descriptors chosen were aching (20%) and burning (27%); nociceptive words chosen were dull (22%), sore (32%), tender (35%), and throbbing (23%), and affective/evaluative descriptors were tiring (25%) and annoying (41%). 57% of patients reported continuous pain, and combined continuous and intermittent pain was reported by 79% of patients. DISCUSSION: This study provides evidence that patients with HNC experience nociceptive and neuropathic pain during RT despite ongoing pain management. The affective and evaluative descriptors chosen for head and neck pain indicate considerable impact on quality of life even with low to moderate levels of pain intensity. These findings suggest that clinicians should consider contemporary management for both nociceptive and neuropathic pain in head and neck cancer patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".