Should dexamethasone be standard in the prophylaxis of pain flare after palliative radiotherapy for bone metastases?—a debate
Bibliographic record
Abstract
Pain flare is a well-recognized side-effect of palliative radiotherapy for the treatment of painful bone metastases, with recent randomized data showing incidence rates up to 35%. The impact of pain flare has been associated with worsening immobility, anxiety, depression and quality of life. The use of dexamethasone has recently been supported as an effective option in reducing radiation-induced pain flare based on the NCIC Clinical Trials Group (NCIC CTG) Symptom Control 23 (SC.23) randomized double-blind placebo-controlled trial. Despite this, conflicting opinions exist, and standard clinical use of dexamethasone to prevent pain flare continues to be debated among clinicians. Given this controversy, two sides of the debate are presented. Although consensus has not been achieved, the choice to use dexamethasone in the prophylactic setting to reduce pain flare incidence should be a shared decision between the oncologist and patient. Factors including symptom burden, comorbidities, performance status, quality of life and radiation dose and fractionation should be taken into account on an individualized level.
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 | 0.030 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".