Compliance to Therapy—Elderly Head and Neck Carcinoma Patients
Bibliographic record
Abstract
BACKGROUND: Treatment compliance of elderly patients to intensive multi-modality cancer therapy can be challenging and has not been adequately addressed in developing countries. The present study evaluated compliance of elderly head and neck carcinomas patients to cancer-directed therapy. METHODS: Forty-seven elderly HNSCC patients were evaluated in the present study. Patients were assessed as per stage and site of disease, general condition, performance status, and any pre-existing co-morbidities. Compliance was defined as patients who were able to complete cancer therapy as intended at primary clinic. Non-compliance to therapy was stratified as early, mid- and late-course non-compliance. Statistical analysis was done using STATA 9.1 software, chi-square/Fischer's exact test to see strength of association between two categorical variables that could possibly affect compliance in elderly patients. RESULTS: Sixty-eight per cent of elderly patients were subjected to radical treatment, majority (42/47) presented in loco-regionally advanced stage (III-IV), most common site of malignancy was oropharynx (21/47). Sixty-two per cent of elderly HNSCC patients were compliance to cancer therapy. Median overall treatment time for patients subjected to radical radiation therapy was 52 (range 47-99) days, and for radical surgery and adjuvant radiotherapy was 109 (95-190) days. Compliance to therapy for elderly HNSCC patients was not significantly associated with advanced stage, poor general condition, intent of treatment or presence of co-morbidity. As regards to non-compliance, majority (14/18) of elderly patients showed mid-course treatment non-compliance. CONCLUSIONS: Nearly two-thirds of elderly head and neck carcinoma patients were compliant to cancer-directed therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".