Characteristics of Orthodontic Treatment in Cancer Survivors: A Systematic Review
Bibliographic record
Abstract
Background: Survival rates of cancer patients have increased globally and across age groups. Challenges arising from craniofacial growth-development disturbances and dental abnormalities might warrant modifications to standard orthodontic pathways of care. Objective: The aim of this study was to systematically summarize and critically assess the available literature regarding the characteristics of orthodontic treatment in cancer survivors. Materials and Methods: A systematic search was conducted in seven databases for studies on malignant tumor survivors having undergone orthodontic intervention with fixed appliances following cancer treatment up to August 2023. The outcomes of interest included quantitative data regarding various characteristics of orthodontic treatment and the post-treatment period. The risk of bias was assessed individually with the Newcastle-Ottawa scale. Results: Out of 347 records, 4 cohort studies were eventually included in the qualitative synthesis. Leukemia was the most common malignancy type, with treatment involving mainly chemotherapy and/or radiotherapy. The duration of orthodontic treatment in cancer survivors varied. Occlusal results, quality of life, and satisfaction were comparable to healthy peers. However, in some survivors’ groups, treatment was shorter and the final results were compromised. Root resorption and oral mucositis were reported among the treated cancer survivors. Reduced occlusal outcome stability during the retention period was also reported. Conclusions: Overall, the duration of orthodontic treatment varied among cancer survivors. The occlusal results achieved were similar to those of their healthy peers, though potentially less stable. Patient-reported outcomes did not differ significantly between cancer survivors and healthy individuals treated orthodontically.
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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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".