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Introduction

Tooth extraction frequently results in notable alveolar bone loss, with a significant portion of bone resorption occurring within the first 3 to 6 months post-extraction, posing challenges for subsequent implant placement and aesthetic outcomes (1,2). This bone remodeling process is inevitable, characterized by horizontal and vertical bone reduction, particularly pronounced on the buccal side (3,4). Consequently, alveolar ridge preservation (ARP) techniques have become essential for minimizing bone loss and enhancing tissue regeneration. Recent clinical interest has focused on using high-concentration growth factors, such as concentrated growth factors (CGF) and plasma rich in growth factors (PRGF), which are derived from autologous blood and exhibit potent regenerative properties (5-7).

High-concentration growth factors such as CGF are advanced formulations of platelet concentrates designed to release growth factors more sustainably over time, closely mimicking natural healing mechanisms. These growth factors, including platelet-derived growth factor (PDGF), transforming growth factor-beta (TGF-β), vascular endothelial growth factor (VEGF), and insulin-like growth factor (IGF), play crucial roles in cell proliferation, angiogenesis and osteogenesis (8,9). CGF, in particular, is known for its dense fibrin matrix, which enhances tissue repair by supporting soft and hard tissue healing post-extraction. Fang et al (6) demonstrated that CGF can reduce postoperative complications such as pain and dry socket formation while promoting faster soft tissue regeneration. Growth factors such as TGF-β and VEGF also play pivotal roles in bone metabolism and regeneration. TGF-β is crucial in regulating the differentiation of mesenchymal stem cells into osteoblasts, promoting bone formation. However, its role can be complex, as it may have positive and negative effects on osteogenic differentiation depending on the context (8,10,11).

The clinical effectiveness of CGF in reducing alveolar bone resorption has been observed in multiple trials. For instance, Assadi et al (3) noted that CGF reduced bone loss in alveolar sockets and enhanced soft tissue preservation, facilitating improved outcomes in implant therapy. Similarly, Liu et al (5) found that CGF membranes, when used to seal extraction sockets, effectively maintained soft tissue healing rates. However, results on long-term bone preservation were mixed when compared with conventional collagen-based membranes. By contrast, the application of PRGF has also been explored extensively, with Farina et al (12) highlighting PRGF's role in early bone formation through enhanced cell differentiation and matrix formation. However, the benefits of the bone density and volume preservation were modest (12).

Comparative studies indicate varying efficacy levels between CGF and other biomaterials. For example, Stumbras et al (2) observed that bone substitutes, such as bovine-derived bone minerals combined with collagen membranes, achieved minimal horizontal bone resorption. In contrast, PRGF offered comparable benefits, particularly in vertical bone preservation (2). However, other trials have reported inconsistent results. Anitua et al (1) noted that while PRGF improved soft tissue healing and reduced inflammation post-extraction, it demonstrated limited impact on overall bone regeneration compared with control groups.

While using high-concentration growth factors in ARP offers promise, there is no consensus on optimal protocols. Farina et al (12) highlighted that CGF applications could reduce vertical and horizontal bone loss and enhance new bone formation in posterior tooth extractions. However, they emphasized that additional research is needed to establish consistent outcomes and explore the underlying mechanisms of action (12). Elayah et al (8) also advocated for CGF as a cost-effective, efficient option for ARP, recommending further studies to assess its full potential and applicability across various clinical scenarios.

While previous studies have demonstrated the general benefits of high-concentration growth factors, comprehensive meta-analyses that explore the variability in clinical outcomes, such as early bone formation, complication rates, and the influence of protocol differences, are needed. The present study provides new insights by employing precision interval analysis and cumulative sensitivity assessments to assess the reliability and range of outcomes associated with high-concentration growth factors.

Materials and methods

Study design

The present meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and meta-analyses (PRISMA) guidelines, which require the studies to be included no later than November 2024. This ensures a structured and transparent approach to the systematic review and synthesis of data (13).

Inclusion and exclusion criteria

Inclusion criteria were as follows: i) studies that assessed the effect of high-concentration growth factors (such as CGF and PRGF) on alveolar bone preservation during tooth extraction; ii) randomized controlled trials (RCTs) or controlled clinical trials that reported quantitative outcomes related to alveolar bone dimensions, including but not limited to alveolar ridge width, bone volume and socket width; iii) studies that provided sufficient statistical data to calculate standardized means differences (such as mean values, standard deviations, confidence intervals), and iv) studies published in English and peer-reviewed journals.

The exclusion criteria were as follows: i) studies that did not specifically focus on high-concentration growth factors for alveolar bone preservation (such as studies on other biomaterials or techniques), ii) observational studies, case series, case reports, reviews and studies without a control group, iii) studies lacking sufficient statistical data for meta-analysis, and iv) studies with severe methodological flaws or low quality based on the quality assessment criteria.

Data extraction process

In total, two reviewers independently conducted data extraction. Extracted data included study characteristics (such as author, year, sample size, population characteristics), details of the intervention (type of growth factor and application method), and primary outcomes such as changes in alveolar ridge width, bone volume and socket width. Secondary outcomes, such as soft tissue healing and probing depth, were also recorded when available. In cases where discrepancies occurred between the reviewers, a third reviewer was consulted to resolve disagreements. If consensus could not be reached, the study was excluded from the analysis to ensure consistency and reliability in the data extraction process.

Quality assessment

The quality of each included study was assessed using the Jadad Scale (14), a reliable tool specifically designed to evaluate the methodological rigor of RCTs. The Jadad Scale, or the Oxford Quality Scoring System, evaluates studies based on three key criteria: i) Randomization: Assessment of whether the study explicitly describes the randomization method and ensures its adequacy. Studies received points if they described both the process and adequacy of randomization, reducing selection bias. ii) Blinding: Evaluation of the implementation and description of blinding within the study. Studies that described an appropriate method of blinding received higher scores, as blinding minimizes detection and performance biases. iii) Withdrawals and dropouts: Consideration of whether the study reported the number and reasons for withdrawals or dropouts, providing transparency in handling incomplete outcome data and ensuring that the analysis accounts for all participants.

Each study received a Jadad score out of a maximum of 5 points, with higher scores reflecting better methodological quality and a lower risk of bias. This assessment allowed the authors to identify high-quality studies and contributed to the interpretation of results by considering the rigor of each study's design and implementation. The use of the Jadad Scale thus ensured a consistent and structured evaluation of study quality, supporting the overall robustness of the present meta-analysis.

Statistical analysis

Statistical analyses were performed using Comprehensive Meta-Analysis software v.3 (Biostat). A random-effects model was applied to estimate pooled effect sizes, presented as standardized differences in means. These models accounted for variations across study populations and methodologies. Instead of the I² statistic, the precision interval approach was used to evaluate heterogeneity, providing a range where the actual effect size is expected to fall across similar populations. This method was selected as it offers a more nuanced understanding of variability, giving insights into the range of actual effects rather than a single heterogeneity value (15). Publication bias was assessed using Begg and Mazumdar's rank correlation test and Egger's regression intercept. Both tests revealed no significant evidence of publication bias (P>0.05), indicating that selective reporting did not likely influence the results. Additionally, Duval and Tweedie's trim-and-fill method was applied to adjust for potentially missing studies, confirming that the pooled estimates remained stable even with hypothetical missing data. A sensitivity analysis was conducted by sequentially removing each study and recalculating the pooled effect size to ensure the robustness of the results. This analysis confirmed that no single study had an undue influence on the overall findings, enhancing the reliability of the conclusions of the present study. Classic and Orwin's fail-safe N tests were used to determine the number of unpublished studies required to negate the observed effects. These tests indicated a high degree of stability in the findings, demonstrating that a substantial number of studies would need to be missing to reduce the P-value to non-significant levels. A moderator analysis was conducted to explore potential effect modifiers, such as participant age, which may influence the efficacy of high-concentration growth factors on alveolar bone preservation. This analysis provided insights into whether specific study characteristics were associated with differences in effect sizes, aiding in the interpretation of heterogeneity across studies.

Results

Study selection

The study selection process was conducted according to PRISMA guidelines. A comprehensive literature search initially identified a total of 570 studies. After removing duplicates, 250 studies remained for the title and abstract screening. Of these, 229 studies were excluded for not meeting the inclusion criteria, such as inappropriate study design, lack of relevant outcome measures, or focus on interventions other than high-concentration growth factors. A full-text review was then conducted on 21 studies, from which 13 were further excluded due to methodological flaws or insufficient data. A total of 8 studies met the inclusion criteria and were included in the meta-analysis (Fig. 1). These studies are summarized in Table I, detailing sample size, interventions, control groups, primary outcomes and follow-up duration. The differences in outcomes presented in Table I reflect the variability in study designs, follow-up durations, and primary endpoints. For instance, while Assadi et al (3) and Liu et al (5) emphasized bone density and soft tissue healing, Farina et al (12) focused on early bone deposition. These variations highlight the heterogeneity in clinical protocols and intervention applications, which were accounted for using a random-effects model in the meta-analysis.

Figure 1 PRISMA 2020 flow diagram for systematic review and meta-analysis. The flow of study selection for a systematic review is depicted, illustrating the number of records identified, screened, assessed for eligibility, and included in the final synthesis. The sources of identified studies and tracks exclusions are highlighted at each stage, ending with eight studies included in the review.

Table I Study characteristics and outcomes of included trials on high-concentration growth factors in alveolar bone preservation. Summary of the characteristics and main outcomes of studies included in the meta-analysis and examination of the effects of high-concentration growth factors, such as PRGF and CGF, on alveolar bone preservation following tooth extraction. Study details include sample size, intervention type, control group, primary and secondary outcome measures, main results, and follow-up duration. Each study's design and specific findings are provided to facilitate comparison across trials.

Table I

Study characteristics and outcomes of included trials on high-concentration growth factors in alveolar bone preservation. Summary of the characteristics and main outcomes of studies included in the meta-analysis and examination of the effects of high-concentration growth factors, such as PRGF and CGF, on alveolar bone preservation following tooth extraction. Study details include sample size, intervention type, control group, primary and secondary outcome measures, main results, and follow-up duration. Each study's design and specific findings are provided to facilitate comparison across trials.

First author, year	Study design	Sample size	Intervention	Control group	Outcome measures	Main results	Follow-up duration	(Refs.)
Anitua et al, 2015	Randomized controlled trial	60	PRGF application in extraction socket	Blood clot	Bone regeneration, soft tissue healing	Improved bone regeneration and soft tissue healing with PRGF	10-12 weeks	(1)
Assadi et al, 2023	Randomized controlled trial	45	CGF application in alveolar socket post-extraction	Natural healing in opposite socket	Alveolar bone width, pain management	CGF reduced bone resorption and pain; improved soft tissue healing	2 months	(3)
Elayah et al, 2023	Randomized controlled trial	30	CGF in post-extraction socket	Natural healing in opposite socket	Bone height, bone density, socket surface area	Higher bone height and density with CGF	3 months	(8)
Fang et al, 2021	Randomized controlled clinical study	118	CGF in mandibular third molar extraction site	Serum in extraction socket	Pain, swelling, bone density, dry socket incidence	CGF reduced pain and dry socket incidence; improved bone density	24 weeks	(6)
Farina et al, 2012	Controlled clinical trial	28	PRGF in human extraction sockets	Spontaneous healing	Early bone deposition, tissue mineral content	No significant enhancement in early bone deposition with PRGF	4-10 weeks	(12)
Liu et al, 2022	Randomized controlled trial	22	CGF membrane for socket sealing in ARP	Bio-Gide collagen membrane	Soft tissue healing rate, bone resorption	CGF led to faster soft tissue healing but no significant bone resorption difference	6 months	(5)
Ma et al, 2021	Randomized controlled clinical trial	50	CGF application for alveolar ridge preservation	No intervention	Bone resorption, new bone formation	CGF reduced vertical and horizontal bone resorption	3 months	(16)
Stumbras et al, 2020	Randomized controlled clinical trial	40	PRGF in alveolar ridge preservation post-extraction	Spontaneous healing	Horizontal and vertical bone changes	PRGF reduced bone resorption, like bone substitute group	3 months	(2)

[i] PRGF, plasma rich in growth factors; CGF, concentrated growth factors; ARP, alveolar ridge preservation.

Meta-analysis outcomes

The random-effects model demonstrated a significant pooled effect size, with a standardized mean difference of 0.593 (standard error=0.178; 95% CI, 0.2443-0.942; Z=3.332; P<0.001) (Fig. 2). Heterogeneity was assessed using the Q statistic, yielding a value of 18.084 with 7 degrees of freedom (P=0.012), and an I² value of 61.3%, suggesting moderate to substantial heterogeneity among the included studies. The observed heterogeneity (I²=61.3%) indicates moderate to substantial variability, which is expected given the differences in study populations and intervention protocols. The tau-squared value was 0.143 (standard error=0.133), indicating variability in the effect size estimates beyond chance. A precision interval approach was used to assess heterogeneity further. The mean effect size was estimated at 0.59 (95% CI, 0.24-0.94), with the actual effect size in 95% of comparable populations expected to lie within -0.43 to 1.62. This broader range provides insights into variability across similar populations and supports the consistency of the positive effects of growth factor interventions on alveolar bone preservation across different settings (Fig. 3).

Figure 2 Forest plot of standardized differences in means for selected studies. The standardized difference in means for various outcomes across included studies is displayed. Each study's effect size and confidence interval are represented by a square and horizontal line, respectively, while the diamond at the bottom shows the overall effect estimate with its 95% CI. The outcomes measured include bone regeneration, ridge absorption and ridge width. Std diff, standard difference; CI, confidence interval.

Figure 3 Distribution of true effects in standardized differences. The distribution of true effects represents the variation in standardized mean differences, centered around the overall mean. The horizontal line indicates the estimated range of effects.

Sensitivity analysis

A sensitivity analysis was performed to evaluate the influence of individual studies on the overall effect size. When each study was sequentially removed, the standardized mean differences remained consistent, ranging from 0.489 (95% CI, 0.163-0.816; Z=2.935; P=0.003) to 0.672 (95% CI, 0.302-1.041; Z=3.562; P<0.001). This consistency indicates that no single study unduly influenced the pooled effect size, supporting the robustness of the findings (Fig. 4).

Figure 4 Forest plot with leave-one-out sensitivity analysis. The results of a leave-one-out sensitivity analysis are shown, where each study is sequentially removed to assess its impact on the overall effect size. Each row represents the recalculated effect size and confidence interval when a particular study is excluded, helping to identify influential studies. Std diff, standard difference; CI, confidence interval.

Both Classic and Orwin's fail-safe N tests were performed to further ensure the robustness of the findings. The Classic fail-safe N yielded a Z-value of 5.36805 with P<0.0001, indicating that 52,000 additional studies with null results would be required to bring the cumulative P-value above the alpha threshold of 0.05. This high fail-safe N supports the stability and reliability of the observed positive effect, confirming that unpublished studies with null findings are unlikely to overturn the results.

Methodological quality

The methodological quality of each included study was assessed using the Jadad Scale (Table II). This scale evaluates three critical components: i) Randomization, ii) blinding and iii) handling of withdrawals/dropouts. Out of a maximum score of 5, most studies scored 4, indicating moderate to high methodological quality. All studies appropriately reported randomization and withdrawals or dropouts, contributing to reliability in handling incomplete data. However, blinding was only partially implemented across studies, with all receiving a score of 1 in this category. Overall, the Jadad Scale assessment suggested that the studies included were of sufficient quality with minimal risk of bias.

Table II Assessment of publication bias in high-concentration growth factor studies for alveolar bone preservation. This table presents The Jadad Scale assessment is presented for each included study, evaluating methodological quality based on three criteria: i) Randomization (0-2 points), ii) blinding (0-2 points) and iii) withdrawals/dropouts (0-1 point). Each study's overall quality is reflected by the total Jadad score (0-5 points), with higher scores indicating lower risk of bias and greater methodological rigor.

Table II

Assessment of publication bias in high-concentration growth factor studies for alveolar bone preservation. This table presents The Jadad Scale assessment is presented for each included study, evaluating methodological quality based on three criteria: i) Randomization (0-2 points), ii) blinding (0-2 points) and iii) withdrawals/dropouts (0-1 point). Each study's overall quality is reflected by the total Jadad score (0-5 points), with higher scores indicating lower risk of bias and greater methodological rigor.

First author, year	Randomization (0-2)	Blinding (0-2)	Withdrawals/Dropouts (0-1)	Total Jadad score (0-5)	(Refs.)
Anitua et al, 2015	2	1	1	4	(1)
Assadi et al, 2023	2	1	1	4	(3)
Elayah et al, 2023	2	1	1	4	(8)
Fang et al, 2021	2	1	1	4	(6)
Farina et al, 2012	1	1	1	3	(12)
Liu et al, 2022	2	1	1	4	(5)
Ma et al, 2021	2	1	1	4	(16)
Stumbras et al, 2020	2	1	1	4	(2)

Publication bias

Publication bias was assessed through several methods to ensure the robustness of the results. The funnel plot appeared visually symmetrical, indicating no substantial publication bias (Fig. 5). Begg and Mazumdar's rank correlation test returned Kendall's tau values of -0.1429 (P=0.3105) without continuity correction and -0.1071 (P=0.3552) with continuity correction, both of which were not statistically significant. Egger's regression intercept was -0.9090 (95% CI, -5.3816-3.5636; P=0.6367), indicating no significant funnel plot asymmetry. These results suggest that publication bias is unlikely to have influenced the overall findings.

Figure 5 Funnel plot for publication bias assessment. Potential publication bias was evaluated by plotting the standard error against the standardized mean difference for each study. A symmetrical distribution of points around the pooled effect estimate at the bottom suggests low risk of bias, while asymmetry may indicate publication bias. Std diff, standard difference.

Furthermore, Duval and Tweedie's trim-and-fill method was applied to adjust for any hypothetical missing studies. This method did not trim any studies, as no missing studies were estimated, and the observed effect sizes remained consistent with the adjusted values. For the fixed-effects model, the point estimate was 0.614 (95% CI, 0.4122-0.815), and for the random-effects model, the point estimate was 0.593 (95% CI, 0.2443-0.942), with no adjustments needed. The Q value remained at 18.084, reinforcing the stability and reliability of the effect estimates without any detected publication bias.

Moderator analysis

Moderator analysis evaluated whether participant age influenced the standardized mean differences across studies. The regression analysis indicated no significant effect modification by age, suggesting that the positive effect of high-concentration growth factors was consistent across various age groups, enhancing the generalizability of the findings (Fig. 6).

Figure 6 Regression of age on standardized difference in means. The relationship between study participant age and the standardized difference in means for the primary outcome is illustrated. Each point represents an individual study, with the size indicating its weight in the analysis. The regression line suggests the trend of effect size variation across age. Std diff, standard difference.

Discussion

The present meta-analysis assessed the impact of high-concentration growth factors, such as PRGF and CGF, on alveolar bone preservation following tooth extraction. The pooled results from eight studies, with a combined sample size of 393 participants, demonstrated a significant positive effect of these growth factors in enhancing bone preservation. Sensitivity and cumulative analyses indicated the robustness and stability of these findings over time, with no single study unduly influencing the pooled effect size. Furthermore, publication bias assessments suggested minimal publication bias, including Begg's test, Egger's test, and Duval and Tweedie's trim-and-fill method. These findings support the beneficial impact of high-concentration growth factors in promoting alveolar bone preservation. The initial hypothesis anticipated consistent improvements in bone preservation and soft tissue healing with PRGF and CGF application. While the pooled effect size (SMD=0.593; P<0.001) confirmed this, certain studies, such as Farina et al (2012) (12), reported minimal early bone formation with PRGF. This discrepancy may be due to differences in the early bioactivity of PRGF compared to CGF or the timing of follow-up assessments. These findings underscore the importance of follow-up timing in evaluating bone regeneration.

The results of this meta-analysis align with and add to the growing body of literature supporting the use of PRGF and CGF in dental applications, particularly in alveolar ridge preservation. Previous individual studies, such as those by Assadi et al (3) and Fang et al (6), demonstrated that CGF significantly reduces alveolar bone loss and improves soft tissue healing after tooth extraction. Similarly, Anitua et al (1) reported enhanced bone regeneration and tissue healing with PRGF application, highlighting the effectiveness of growth factors in facilitating faster and more robust healing processes in extraction sites. These studies underscore the biological mechanisms of PRGF and CGF, which are rich in growth factors such as PDGF and transforming growth factor-beta (TGF-β). These factors stimulate cellular proliferation, angiogenesis, and osteogenesis, key bone and tissue regeneration processes.

However, there have been some inconsistencies across studies regarding the effectiveness of these interventions. For instance, Farina et al (12) found that PRGF did not significantly enhance bone deposition early, indicating outcome variability based on application method or patient characteristics. The present study provides quantitative confirmation that the pooled effects of PRGF and CGF consistently enhance bone preservation across varying follow-up durations, indicating robustness regardless of study-level differences in population characteristics.

CGFs have gained attention in recent years as a biologically potent and minimally invasive treatment to enhance tissue and bone regeneration in dental applications, including alveolar ridge preservation after tooth extraction. CGFs are derived from autologous blood through a specific centrifugation process, resulting in a fibrin-rich matrix with a high concentration of growth factors and cytokines. These biologically active components play critical roles in cellular processes essential for wound healing, angiogenesis and osteogenesis, thus contributing to improved clinical outcomes in bone preservation. The mechanisms by which CGFs exert their effects were explored to support the findings of the present meta-analysis. The unique centrifugation process was used to produce CGF, resulting in a dense fibrin matrix enriched with various growth factors, including PDGF. PDGF promotes cell migration, proliferation and differentiation, particularly of osteoblast, which are essential for new bone formation. It also stimulates the recruitment of mesenchymal stem cells to the extraction site, enhancing bone regeneration (8). Furthermore, TGF-β plays a vital role in collagen synthesis and extracellular matrix formation, crucial for stabilizing newly formed bone tissue. It also promotes the differentiation of osteoblasts and other bone-forming cells, which helps maintain alveolar ridge height and density (16,17). Besides, VEGF is a key driver of angiogenesis, forming new blood vessels, which improves blood flow and nutrient supply to the healing site. Enhanced vascularization supports cellular activities in bone regeneration, accelerating wound healing and reducing post-extraction complications such as dry sockets (1,6). In addition, the fibrin matrix in CGF acts as a three-dimensional scaffold, providing structural support and stability to the extraction socket. This matrix facilitates the gradual and sustained release of growth factors over time, closely mimicking the body's natural healing processes. The dense fibrin structure anchors cells in the extraction site and serves as a protective barrier that shields the wound from bacterial invasion, thereby reducing the risk of infection. The scaffold's mechanical properties also allow for the integration of osteoblasts and other bone-forming cells, which aids in new bone deposition and stabilizes the alveolar ridge (3). Furthermore, the growth factors in CGF have been shown to enhance the proliferation and differentiation of various cell types involved in bone healing, including osteoblasts, fibroblasts and endothelial cells. PDGF and TGF-β stimulate osteoblast activity, leading to increased production of bone matrix proteins, such as collagen, which forms the foundational structure of new bone.

Additionally, these factors promote the differentiation of mesenchymal stem cells into osteogenic lineages, further enhancing the regeneration of lost bone tissue. By accelerating these cellular processes, CGFs contribute to faster and more efficient alveolar ridge preservation (6). Moreover, CGFs contain anti-inflammatory cytokines, such as interleukin-4 (IL-4) and TGF-β, which help modulate the inflammatory response at the extraction site. Excessive inflammation can lead to delayed healing and increased bone resorption. The anti-inflammatory properties of CGF minimize inflammation, creating an optimal environment for bone and tissue regeneration. By reducing inflammation, CGFs also help mitigate postoperative pain and swelling, improving patient comfort and reducing complications (16). Finally, angiogenesis, the formation of new blood vessels, is critical for successful bone regeneration, as it ensures an adequate supply of oxygen and nutrients to the healing site. VEGF, a key component of CGF, stimulates angiogenesis within the extraction socket, promoting vascularization of the newly forming tissue. Enhanced blood vessel formation supports the survival and activity of osteoblasts and other cells involved in bone repair, thereby accelerating the healing process. Improved vascularization also facilitates soft tissue healing, contributing to the preservation of keratinized gingiva and the aesthetic outcome of the treatment (1,6,18,19).

The findings of the present meta-analysis are clinically relevant for several reasons. First, alveolar ridge preservation is critical for optimizing the success of subsequent implant placement and maintaining the aesthetic outcomes of dental procedures. Bone resorption following tooth extraction can complicate implant placement, requiring additional augmentation procedures, which may be costly and carry risks. By demonstrating that high-concentration growth factors can significantly reduce alveolar bone loss, this meta-analysis supports integrating PRGF and CGF as effective, minimally invasive options for ridge preservation.

The Jadad Scale assessment revealed that most studies scored 4 out of 5, indicating moderate to high methodological quality. While randomization and reporting of withdrawals were well-documented, blinding was consistently underreported across studies. This limitation may introduce performance and detection bias, especially in subjective outcomes such as pain assessment. However, the cumulative and sensitivity analyses confirmed that the overall findings remain robust despite these methodological differences, indicating that lower blinding scores do not disproportionately influence the positive effects of high-concentration growth factors on alveolar bone preservation. Despite variability in methodological rigor, the authors' precision interval approach estimated a range of true effects that underscore the robustness of high-concentration growth factor interventions across studies of varying quality. This consistency suggests that high-concentration growth factors improve bone preservation even when study designs differ in methodological rigor. Nonetheless, future studies could benefit from more rigorous implementation of blinding protocols to enhance reliability.

While the present study has several strengths, including rigorous adherence to PRISMA guidelines, comprehensive publication bias assessment, and cumulative and sensitivity analyses to evaluate the robustness of the findings, some limitations should be acknowledged. Furthermore, unlike previous studies, moderator analysis was applied to examine participant age as a potential effect modifier and found no significant age-related differences. This finding supports the generalizability of high-concentration growth factor effects across diverse age groups, reinforcing their clinical relevance for a broad patient population. One limitation is the moderate heterogeneity observed (I²=61.293%). This suggests some variability in study outcomes, potentially due to differences in study populations, intervention protocols, and follow-up durations. The precision interval analysis offered a range (-0.43 to 1.62) where the actual effect size may lie across comparable populations, providing a broader perspective on potential heterogeneity sources. However, variations in growth factor preparation methods, application techniques, and patient characteristics could contribute to outcome differences. Future studies may benefit from standardizing protocols to reduce heterogeneity and enhance the comparability of results. Another limitation is related to the Jadad Scale's focus on randomization and blinding, which may not fully capture the methodological rigor of these studies, mainly since blinding was inconsistently applied across the studies. Although the quality assessment revealed that most studies were of moderate to high quality, further refinement in assessing study quality, such as using a tool specifically tailored for non-pharmacological interventions, could provide additional insights. Finally, while publication bias was assessed using multiple methods, the relatively small number of studies (n=8) included in the meta-analysis may limit the power of these tests. Although Begg's test, Egger's test, and the trim-and-fill method did not indicate significant publication bias, future research with larger sample sizes may yield even more robust results.

Additionally, the fail-safe N value of 52,000 supports the robustness of these findings, suggesting that a substantial number of null-effect studies would be required to nullify the observed effects. Finally, the variability in study outcomes may also reflect differences between predicted and observed effects due to variations in growth factor preparation methods, application techniques, and follow-up periods. Standardizing these protocols minimizes variability and ensures comparable outcomes across future studies.

In conclusion, this meta-analysis proves that high-concentration growth factors, such as PRGF and CGF, enhance alveolar bone preservation following tooth extraction. The pooled results from eight studies consistently indicate positive effects on bone volume and width preservation, underscoring the potential of these growth factors to support effective bone regeneration in clinical settings. The findings were confirmed through cumulative and sensitivity analyses, demonstrating the stability and robustness of the pooled effect sizes despite some observed heterogeneity.

Using high-concentration growth factors represents a promising, minimally invasive strategy for promoting bone preservation and improving outcomes in dental surgeries, particularly for patients undergoing extractions and preparing for future implant placement. The present study provides novel evidence that confirms the robustness of interventions involving high-concentration growth factors across diverse settings. The findings of the present study also highlight the potential of precision interval analysis to guide future research by identifying ranges of clinical outcomes rather than single-point estimates. Future research should aim to standardize application protocols and evaluate the long-term impact of these growth factors on implant stability, bone quality, and patient satisfaction. Further studies are needed to explore their effectiveness across diverse patient populations, investigate cost-effectiveness, and examine potential synergistic effects with other biomaterials. These directions will help refine clinical practices and broaden the integration of growth factor therapies into routine dental and surgical care (20).

Acknowledgements

Not applicable.

Funding

Funding: No funding was received.

Availability of data and materials

The data generated in the present study may be requested from the corresponding author.

Authors' contributions

The manuscript was written and drafted by XS, YY, LL and WY. Additionally, they gathered and examined the data. XQ provided general supervision, made intellectual content revisions, and granted final publishing permission. QY acquired resources, edited the language, and conducted data analysis. XQ and XS created the study protocol and confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References