Assessment of Cancer Therapy-Induced Oral Mucositis Using a Patient-Reported Oral Mucositis Experience Questionnaire
Bibliographic record
Abstract
OBJECTIVES: Treatment of oral mucositis (OM) is challenging. In order to develop and test useful treatment approaches, the development of reliable, reproducible and simpler methods than are currently available for assessment of OM is important. A Patient-Reported Oral Mucositis Symptom (PROMS) scale was assessed in patients with head and neck cancer to determine if the patient-reported OM experience, as determined by using the PROMS scale, correlate with OM assessed by clinician-based scoring tools. MATERIALS AND METHODS: Fifty patients with head and neck cancer and undergoing radiotherapy consented to participate. They were examined before cancer treatment and twice weekly during 6-7 weeks of therapy and once 4-6 weeks after therapy. Signs of OM were evaluated using the 3 clinician-based scoring tools; NCI-CTCAE v.3, the OMAS criteria and the Total VAS-OMAS. The participants' OM experiences were recorded using PROMS-questionnaires consisting of 10 questions on a visual analogue scale. Spearman rank correlation test were applied between the PROMS scale values and the clinician-determined scores. Repeated measures mixed linear models were applied to appraise the strengths of correlation at the different time points throughout the observation period. RESULTS: Thirty-three participants completed all stages of the study. The participant experience of OM using the PROMS scale demonstrates good correlations (Spearman's Rho 0.65-0.78, p<0.001) with the clinician-determined scores on the group level over all time points and poor to good correlations (Spearman's Rho -0.12-0.70, p<0.001) on the group level at different time points during and after therapy. When mouth opening was problematic, i.e. during the 6th and 7th week after commencing cancer treatment, the Spearman's Rho varied between 0.19 and 0.70 (p<0.001). CONCLUSION: Patient experience of OM, as reported by the PROMS scale may be a feasible substitute for clinical assessment in situations where patients cannot endure oral examinations.
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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) | 0.001 | 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".