MASCC/ISOO clinical practice guidelines for the management of mucositis secondary to cancer therapy
Bibliographic record
Abstract
BACKGROUND: Mucositis is a significant toxicity of cancer therapy with numerous systemic sequelae. The goal of this systematic review was to update the Multinational Association of Supportive Care in Cancer and International Society of Oral Oncology (MASCC/ISOO) Clinical Practice Guidelines for the management of mucositis. METHODS: The literature was reviewed systematically to identify interventions for mucositis. Studies were rated according to the presence of major and minor flaws according to previously published criteria. The body of evidence for each intervention and in each treatment setting was assigned a level of evidence based on previously published criteria. Guidelines were developed based on the level of evidence, with 3 possible guideline determinations: recommendation, suggestion, or no guideline possible. RESULTS: The guideline covers evidence from 1197 publications related to oral or gastrointestinal mucositis. Thirteen new guidelines were developed for or against the use of various interventions in specific treatment settings, and 11 previous guidelines were confirmed after aa review of new evidence. Thirteen previously established guidelines were carried over because there was no new evidence for these interventions. CONCLUSIONS: The updated MASCC/ISOO Clinical Practice Guidelines for mucositis provide professional health caregivers with a clinical setting-specific, evidence-based tool to help with the management of mucositis in patients who have cancer.
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 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".