Significance of site‐specific radiation dose and technique for success of implant‐based prosthetic rehabilitation in irradiated head and neck cancer patients—A cohort study
Bibliographic record
Abstract
BACKGROUND: Radiotherapy aggravates implant-based prosthetic rehabilitation in patients with head and neck cancer. PURPOSE: To evaluate the impact of radiation dose at implant and parotid gland site for prosthetic rehabilitation. MATERIAL AND METHODS: The retrospective study includes 121 irradiated head and neck cancer patients with 751 inserted implants. Radiation doses on implant bed and parotid gland site were recorded by 3-dimensional modulated radiation plans. Implant success was clinically and radiographically evaluated according to modified Albrektsson criteria and compared to treatment- and patient-specific data. RESULTS: Implant overall survival after 5 years was 92.4% with an implant success rate of 74.9%. Main reasons for implant failure were marginal bone resorption (20.9%), implant not in situ or unloaded (9.6%) and peri-implantitis (7.5%). A mean radiation dose of 62.6 Gy was applied with a mean parotid dose of 35 Gy. Modulating radiation techniques went along with lower grades of xerostomia (p < 0.001). At implant site mean doses of 57.5, 42.0, and 32.3 Gy were recorded for oral, oropharyngeal, and hypopharyngeal/laryngeal carcinoma, respectively. Implant success inversely correlated to radiation dose at implant site. Strong predictors for implant failure in uni- and multivariate analysis were implant-specific dose >50 Gy (HR 7.9), parotid dose >30 Gy (HR 2.3), bone (HR 14.5) and soft tissue (HR 4.5) transplants, bad oral hygiene (HR 3.8), nonmodulated radiation treatment planning (HR 14.5), and nontelescopic prosthetics (HR 5.2). CONCLUSION: Radiotherapy impedes implant success in a dose-dependent manner at implant site. Modern radiation techniques effectively reduce xerostomia favoring implant-based prosthetic rehabilitation. Implantation in bone grafts is more critical and telescopic-retained overdentures should be preferred.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".