Impact on quality of life due to therapy-related oral complications in pediatric cancer patients: a scoping review
Bibliographic record
Abstract
Objectives: To systematically review the research literature on the relationship between Quality of Life (QoL) and cancer therapy-related oral side-effects in a pediatric population. Methods: A scoping review was conducted using 16 databases (research and grey literature), websites, reference lists, and key journals. Inclusion criteria included studies pertaining to children 0-20 years, in English or French, published from 2000 to 2011. Exclusion criteria included mixed population of adults and children and non-discrete disease categories. Data was independently charted by two reviewers. Results: A total of 1270 articles were identified through the initial search. A rigorous review of abstracts and full text reduced the sample to 82 articles, all of which were categorized through a data extraction process. Data analysis resulted in the following findings: Leukemia studies were predominant. The most common side-effect was mucositis; however, side-effects mostly co-occurred. Twenty-one articles dealt directly with the effect on QoL, citing impacts such as changes in taste, eating, drinking, sleep habits, voice and weight loss. Twenty-five articles examined the long-term effect of treatment on pediatric dentition, showing that resultant caries and malformed teeth can affect eating and speech. Conclusions: Preventive oral care before, during and after cancer therapy can decrease the oral side-effects and improve the QoL of the pediatric patient; however, few studies to date advance recommendations for QoL improvement. This study underscores the need for a dental oncology program in pediatric hospitals.
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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".