NETWORK META-ANALYSIS OF ORAL AND MAXILLOFACIAL REGENERATION PROCEDURES

Background Regenerative dentistry is a novel speciality in dentistry that aims to regenerate the loss tissue. It involves deep understanding of cell and molecular biology to design dental therapies that aim to restore, repair, rejuvenate, and regenerate dental tissues. Its application in oral and maxillofacial regeneration procedures namely; alveolar ridge preservation, periodontal regeneration, maxillary sinus augmentation, soft tissue augmentation, root coverage procedures to name a few is wide and has become common through the use of wide range of stem cells, biomaterials and biologics. The question remains unanswered because of few clinical trials available for each procedure to regenerate loss tissue. There is a strong need of evidence for such therapies for specific clinical indications in oral and maxillofacial regeneration. Since traditional meta-analysis compares only two types of intervention, network meta-analysis has been used as most common method to compare multiple interventions from different clinical trials. Therefore, using this methodology our main aim was to determine the best performing biomaterials and biologics for oral and maxillofacial regeneration procedures. The specific objectives were; 1. to determine the most effective grafting/sealing biomaterial in maintaining horizontal and vertical dimensions after alveolar ridge preservation; 2. to determine the most effective grafting/sealing biomaterial for new bone formation after alveolar ridge preservation; 3. to determine the most effective biomaterial for soft tissue regeneration after tooth extraction; 4. to determine the most effective biomaterial for gingival recession treatment in adjunct to coronally advanced flap; 5. to determine the most effective dental implant abutment material; 6. to rank the different combinations of recombinant human-derived growth and differentiation factors with/without scaffold biomaterial in the treatment of periodontal intrabony defects, through network meta-analysis of pre-clinical studies; 7. to determine the best rank recombinant growth factor formulations agents through network meta-analysis of clinical studies; 8. to determine the effectiveness of biomaterials used in soft tissue augmentation procedures; 9. to determine the most effective biomaterial in increasing residual bone height after maxillary sinus lift procedures Methods The study protocols were recorded in the PROSPERO database, and a standard approach to searching for articles in various scientific databases was adopted. A patient/population, intervention, comparison and outcomes (PICO) format was used to form a research question for each specific objective in oral and maxillofacial regeneration procedures. A custom search strategy was developed for each set of objectives and specific outcomes that accurately represented the successful results of specific oral and maxillofacial regeneration procedures were chosen. The mean, standard deviation, type of interventions used in each treatment group, number of participants and blinding status were extracted. The risk of bias was evaluated for the studies included in the network meta-analysis. The analysis was conducted using STATA software and the methods recommended by Chaimani A and Salanti G. The findings were presented in the form of network plots, inconsistency plots, predictive intervals, SUCRA rankings, and multi-dimensional scale rankings based on feasibility. The ranking of biomaterials and biologics was calculated for each considered outcome, and a Bayesian method was used in the methodology. A Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist was followed to report the results of NMA. Results Specific objective 1: In this study, 88 randomized controlled trials were analyzed, including a total of 2805 patients and 3073 sockets. The biomaterials/biologics used were self-healing materials, xenografts, allografts, alloplasts, platelet concentrates, and combinations of these biomaterials. Xenografts and allografts, either alone or combined with bioactive agents, were found to be the most effective in preserving horizontal and vertical ridge dimensions. Platelet concentrates were shown to be the best in increasing the percentage of new bone formation. However, a previous network meta-analysis review that included six studies found that freeze-dried bone graft plus membrane was the most likely to be effective in reducing bone height remodeling. Meanwhile, autologous bone marrow was determined to be the most likely effective in terms of width remodeling. Specific objective 2: A total of 12 trials underwent both qualitative and quantitative analysis, which involved evaluating 312 sites. The results indicated that the use of autologous soft tissue grafts resulted in improved horizontal changes compared to resorbable membranes. Furthermore, when comparing crosslinked and non-crosslinked membranes, non-crosslinked membranes were found to be statistically superior, as confirmed by histomorphometric network meta-analysis. This study has no previous reviews to compare its specific objective 2. Specific objective 3: In the network meta-analysis (NMA), 11 studies were analyzed. The included studies had moderate levels of bias. The highest-ranking treatment for vertical buccal height was crosslinked collagen membranes with a SUCRA score of 81.8%. Autogenous soft tissue grafts ranked highest in horizontal width change with a SUCRA score of 89.1%, while the control group had the highest ranking in keratinized mucosa thickness with a SUCRA score of 85.8%. Specific objective 4: The best performers in enhancing KGW were CAF + connective tissue graft (CTG), CAF + platelet concentrate matrix (PCM), and acellular dermal matrix (ADM). In terms of improving the percentage of root coverage in gingival recession, the highest-ranking materials were CAF + collagen matrix (CM) + gingival fibroblasts (GF), CAF + ADM + platelet rich plasma (PRP), and CAF + ADM. These materials outperformed CAF alone. Specific objective 5: Of the 1437 studies identified, 18 relevant studies were included in the analysis. The total number of patients treated was 612, and 848 abutments were inserted. The network meta-analysis (NMA) found that zirconia abutments had a 83.3% probability of being ranked first in terms of plaque index (PI), 87.0% in bleeding on probing (BOP), and 65.0% in probing depth (PD) outcomes. These results indicate that zirconia abutments generally performed better than titanium and alumina abutments. Specific objective 6: 24 studies were included for qualitative analysis and 21 studies for quantitative analysis, published up until 2020. The combined total number of animals in the control and test groups was 162 and 339, respectively. The study duration ranged from 3 to 102 weeks. In the SUCRA rankings, rhBMP-2 was associated with the best performance for bone volume density. rhGDF-5/TCP had the best ranking in bone area (mm2), rhPDGF-BB/Equine in bone height (mm), rhBMP-2 in the percentage of new bone fill, rhBMP-2/ACS in new cementum formation, and rhGDF-5/b- TCP/PLGA in connective tissue attachment and junctional epithelium. Specific objective 7: This study considered 12 clinical studies for qualitative and quantitative analysis. The network meta-analysis found that the combination of rhFGF and hyaluronic acid had the highest ranking in terms of probing pocket depth (PPD) and clinical attachment level (CAL) outcomes. The combination of rhPDGF-BB and β-tricalcium phosphate was ranked highest in terms of percentage of bone filling. Furthermore, all bioactive agents showed better performance compared to control groups without rhGFs. Specific objective 8: In the majority of outcomes, connective tissue graft (CTG) performed the best. When it comes to increasing keratinized mucosa, free gingival graft (FGG) was found to be the best option. Both FGG and crosslinked collagen membranes (XCM) performed better in augmenting keratinized mucosa. As for increasing soft tissue in the buccal aspects, the best results were seen with vascularized connective tissue matrix (VCMX) compared to other matrices. Specific objective 9: 67 studies were eligible for a network meta-analysis (NMA). The study included 1955 patients who underwent 2405 sinus augmentation procedures. The biomaterials used were grouped into: autogenous bone (Auto), xenografts (XG), allografts (AG), alloplasts (AP), bioactive agents (Bio), hyaluronic acid (HA), and combinations of these. A statistically significant inconsistency factor (IF) was found in the entire loop of XG, AP, and Bio+AP. The highest ranked biomaterials for the residual bone height (RBH) of less than 4 mm were XG+AG, XG+AP, and Auto. Similarly, the biomaterials with the highest surface under the cumulative ranking curve (SUCRA) for RBH of 4 mm or more were Auto, Bio+XG, and XG+Auto. Conclusions The rankings of biomaterials can differ depending on the specific clinical outcomes being evaluated. Therefore, it is important to consider all confounding factors and utilize more robust NMA methods to achieve more reliable rankings. The availability of predictive intervals for the majority of research questions enables clinicians to select the most effective biomaterials for future clinical studies, which promotes informed decision-making and reduces costs for patients. However, new evidence continues to emerge through clinical trials and non-randomized studies. As a result, diverse methods such as multidimensional scale ranking, cluster plots for different outcomes, and predictive intervals should be employed when reporting the results of network meta-analyses.