Clinical Applications of Cell‐Based Approaches in Alveolar Bone Augmentation: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Cell-based approaches, utilizing adult mesenchymal stem cells (MSCs), are reported to overcome the limitations of conventional bone augmentation procedures. PURPOSE: The study aims to systematically review the available evidence on the characteristics and clinical effectiveness of cell-based ridge augmentation, socket preservation, and sinus-floor augmentation, compared to current evidence-based methods in human adult patients. MATERIALS AND METHODS: MEDLINE, EMBASE, and CENTRAL databases were searched for related literature. Both observational and experimental studies reporting outcomes of "tissue engineered" or "cell-based" augmentation in ≥5 adult patients alone, or in comparison with non-cell-based (conventional) augmentation methods, were eligible for inclusion. Primary outcome was histomorphometric analysis of new bone formation. Effectiveness of cell-based augmentation was evaluated based on outcomes of controlled studies. RESULTS: Twenty-seven eligible studies were identified. Of these, 15 included a control group (8 randomized controlled trials [RCTs]), and were judged to be at a moderate-to-high risk of bias. Most studies reported the combined use of cultured autologous MSCs with an osteoconductive bone substitute (BS) scaffold. Iliac bone marrow and mandibular periosteum were frequently reported sources of MSCs. In vitro culture of MSCs took between 12 days and 1.5 months. A range of autogenous, allogeneic, xenogeneic, and alloplastic scaffolds was identified. Bovine bone mineral scaffold was frequently reported with favorable outcomes, while polylactic-polyglycolic acid copolymer (PLGA) scaffold resulted in graft failure in three studies. The combination of MSCs and BS resulted in outcomes similar to autogenous bone (AB) and BS. Three RCTs and one controlled trial reported significantly greater bone formation in cell-based than conventionally grafted sites after 3 to 8 months. CONCLUSIONS: Based on limited controlled evidence at a moderate-to-high risk of bias, cell-based approaches are comparable, if not superior, to current evidence-based bone grafting methods, with a significant advantage of avoiding AB harvesting. Future clinical trials should additionally evaluate patient-based outcomes and the time-/cost-effectiveness of these approaches.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".