Pain in head and neck cancer patients: the role of gender.
Bibliographic record
Abstract
PURPOSE: To assess the quality of life (QoL) following palliative radiotherapy (RT) in patients with painful bone metastases. METHODS: A literature search limited to English-written publications was carried out, through the Cochrane Central Register of Controlled Trials (November 2018), OvidSP and PubMedCentral (1940-November 2018) databases. Subject headings and keywords included "quality of life"(QoL), "bone metastases", "palliative therapy", "pain" and "radiotherapy". Original articles, literature reviews, trials and meta-analyses revealing alterations in QoL post-RT using ratified measuring tools were examined. Studies referring to other types of metastases (e.g. brain metastases), or to other types of palliative therapy (e.g. the use of bisphosphonates alone), or focusing only on pain, or even reporting QoL only before or only after the use of RT were excluded. RESULTS: Twenty four articles were selected from a total of 1360 articles. Seven trials proceeded to patients' randomization. The most commonly used tool to evaluate QoL was EORTC, followed by Brief Pain Inventory (BPI) and Edmonton Symptom Assessment System (ESAS) questionnaires. All studies showed improvement in symptoms and functional interference scores after RT. The QoL between responders (Rs) and non-responders (NRs) has been juxtaposed in 10 studies. Rs had a significant benefit in QoL in comparison with the NRs. DISCUSSION: Palliative radiotherapy in painful bone metastases improves Rs' QoL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".