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Meta-analysis of animal experiments on osteogenic effects of trace element doped calcium phosphate ceramic/PLGA composites

  • Hongwei He , Meng Zhong , Panxianzhi Ni , Tun Yuan EMAIL logo , Jie Liang , Yujiang Fan and Xingdong Zhang
Published/Copyright: April 18, 2025
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Biomedical Engineering / Biomedizinische Technik
From the journal Biomedical Engineering / Biomedizinische Technik Volume 70 Issue 4

Abstract

Objectives

Investigate the impact of the components in element-doped calcium phosphate ceramic/PLGA composites on bone repair outcomes in animal experiments.

Methods

Computer search of CNKI, Wanfang, Pub Med, Web of science, and EMbase databases to collect related randomized controlled animal experimental studies. Using the SYRCLE Animal Experimental Bias Risk Assessment form to evaluate research quality. The outcome measures were statistically analyzed using the Rev Man 5.4 software.

Results

Included 11 randomized controlled animal studies. Meta-analysis showed that: (1) Element doping can promote the proliferation of osteoblasts in vitro. (2) Element doping can increase the activity of ALP in cells. (3) Element doping can increase bone volume fraction. (4) Element doping can increase trabecular number.

Conclusions

Trace element doping has been found to enhance the osteogenic effect of the composite material. The type of calcium phosphate ceramics may be a significant source of heterogeneity that influences the effectiveness of bone repair in vivo.

Keywords: bone repair; calcium phosphate ceramic; element doping; animal experiments; meta-analysis

Introduction

As a prevalent condition, bone defects resulting from trauma, bone disorders, tumors, and other bone diseases are increasingly becoming a widespread health concern [1], 2]. For instance, large cortical bone defects often lead to limb disability and severe dysfunction. Furthermore, femoral head necrosis in young patients caused by trauma, hormones, and other factors also has a high disability rate [3]. According to statistics, there are more than 1.5 million orthopedic surgeries performed in China every year, but over 3.5 million patients require bone transplantation [4]. Presently, autologous or allogeneic bone remains the primary source of bone transplantation in clinical practice, which has significant disadvantages, such as secondary surgery, limited bone availability, disease transmission, low osteogenic activity, and so on. Therefore, the treatment of some bone defects and osteonecrosis has not yielded satisfactory outcomes [5], [6], [7].

To address this challenges, artificial bone graft substitutes have gained increasing attention in the field of bone repair. Various artificial bone biomaterials, including organic polymers, metals, ceramics, and composite materials, have been developed for bone defect repair [8]. Among them, calcium phosphate ceramics are widely used due to their biocompatibility, bone conductivity, and lack of antigenicity, which make them similar to the inorganic phase composition of bone. Currently, 60 % of artificial bone replacement materials used in clinical practice are made of calcium phosphate ceramics [9]. Calcium phosphate bio-ceramics not only exhibit good biocompatibility but also have the ability to induce bone formation, making them highly suitable for bone repair. Hydroxyapatite (HA), tricalcium phosphate (TCP), and biphasic calcium phosphate (BCP) are commonly used calcium phosphate ceramics [10]. However, calcium phosphate ceramics still have some mechanical limitations, such as brittleness, especially when they are fabricated into porous structures for bone repair [11]. Thus, higher mechanical strength is required for calcium phosphate ceramics. The addition of reinforcing phases can improve the fracture toughness of dense calcium phosphate ceramics [12]. While porous calcium phosphate ceramics can be significantly enhanced by the growth of new bone, they need to be toughened and strengthened before the reconstructive bone is fully formed to perform their functions as soon as possible [13]. Thus, calcium phosphate ceramic matrix composites have emerged as a promising direction for the development of calcium phosphate bio-ceramics [14].

PLGA (poly (lactic-co-glycolic acid)) is commonly used to prepare scaffold materials for bone tissue engineering due to its favorable biocompatibility and degradation controllability. However, the acidic degradation products of PLGA can negatively affect cell activity and cause inflammation in the surrounding tissue. In recent years, research has focused on the use of PLGA/calcium phosphate ceramic composites [15], [16], [17]. The alkaline products generated during the degradation of calcium phosphate ceramics can partially neutralize the acidic degradation products of PLGA, reduce local inflammatory reactions, and enhance the fracture toughness and mechanical strength of the composite. Additionally, PLGA/calcium phosphate ceramic composites have demonstrated excellent bone conductivity and biocompatibility [18], 19].

In certain usage scenarios, the calcium phosphate ceramic/PLGA composite may still face some challenges, such as the presence of interface gaps between the material and surrounding tissues, excessive fibrous tissue proliferation leading to infection and inflammation issues, and difficulty controlling the degradation rate [20]. Numerous studies have confirmed that incorporating trace elements such as silicon (Si), zinc (Zn), magnesium (Mg) and strontium (Sr) into biomaterials can significantly enhance the osteogenesis of calcium phosphate materials, thereby improving their efficacy in bone tissue engineering and repair [21], [22], [23]. The use of biomaterials doped with multiple trace elements is considered a feasible method that can mimic the natural physiological extracellular environment [24]. In such cases, different elements play distinct roles in the process of bone regeneration, and the ability of functional coordination between multi-element doping and natural bone regeneration provides a novel strategy for biomaterial development [25].

Currently, there is a lack of clarity on the main factors that influence the bone repair effect of the element-doped PLGA/calcium phosphate ceramic composite in both in vivo and in vitro settings. This paper aims to investigate the impact of various components of the composite ceramic material on the bone repair process, including their effects on osteoblast activity in vitro and the rate of bone healing in vivo. With numerous ongoing animal experimental studies related to this novel material, our findings provide valuable insights and recommendations for interpreting the results of such experiments, as well as ideas for designing and optimizing future bone repair ceramic materials.

Methods

Search strategy

A comprehensive search was conducted in January 2023 across multiple databases including CNKI, Wanfang, Pub Med, Web of Science, and EMbase, to collect studies reporting the osteogenic effects of element-doped calcium-phosphorus ceramic/PLGA composites. The search terms used were based on bone repair headings and related free-text keywords such as elemental doping, PLGA, calcium-phosphorus ceramics, and calcium phosphate materials. PubMed is taken as an example of the retrieval strategy for English databases, while CNKI is taken as an example of the retrieval strategy for Chinese databases (Table 1).

Table 1:

Retrieval strategy for PubMed and CNKI database.

Databases Number Search terms
PubMed #1 Polylactic acid-polyglycolic acid copolymer [Mesh]
#2 PLGA[TIAB] OR (poly (lactic-co-glycolic acid) [TIAB])
#3 #1 OR #2
#4 Calcium phosphate ceramics [TIAB] OR calcium phosphate ceramic [TIAB] OR calcium phosphates [TIAB] OR hydroxyapatite [TIAB] OR hydroxyapatites [TIAB] OR HA [TIAB] OR HAP [TIAB] OR TCP [TIAB] OR CPC [TIAB] OR tricalcium phosphate [TIAB]
#5 Zn [TIAB] OR Mg [TIAB] OR Sr [TIAB] OR Si [TIAB] OR zinc [TIAB] OR magnesium [TIAB] OR strontium [TIAB] OR silicon [TIAB]
#6 #3 AND #4 AND #5
CNKI #1 (SU: calcium phosphate) OR (SU: calcium phosphate ceramics) OR (SU: tricalcium phosphate) OR (SU: hydroxyapatite) OR (SU: HA) OR (SU: CPC) OR (SU: BCP) OR (SU: TCP)
#2 (SU: PLGA) OR (SU: poly (lactic-co-glycolic acid))
#3 (SU: zinc) OR (SU: strontium) OR (SU: magnesium) OR (SU: silicon) OR (SU: Zn) OR (SU: Sr) OR (SU: Mg) OR (SU: Si)
#4 #1 AND #2 AND #3

  1. Use Chinese keywords during retrieval for CNKI.

Literature selection

Inclusion criteria

Study inclusion criteria were as follows: (1) randomized controlled animal experiments investigating the osteogenic effect of calcium-phosphorus ceramic/PLGA bone repair materials; (2) examining the impact of trace element doping on the osteogenic effect both in vitro or in vivo; (3) published in English or Chinese.

Duplicate records were removed, and two reviewers independently screened the titles and abstracts of the remaining records for potential eligibility. The full text of the potentially relevant studies was retrieved and assessed by the same two reviewers. Eligible studies had to meet the following criteria: (1) using 4-12-week-old Sprague-Dawley rats as animal models; (2) Outcome measures: the proliferation effect of BMSCs cells or MC3T3-E1 cells in vitro, alkaline phosphatase (ALP) activity and the healing rate of bone defects in vivo, including bone volume fraction (BV/TV) and number of trabeculae (Tb. N).

Exclusion criteria

The specific requirements for excluding studies are as follows: (1) studies that do not report the number of experimental animals used; (2) non-randomized controlled studies or studies with poor quality; (3) studies with incomplete or insufficient data that cannot be extracted; (4) repeated publications, reviews, conference proceedings, experience summaries, case reports, and other non-original research articles.

Data extraction

Two reviewers will conduct literature screening, data extraction, and cross-checking independently, and any discrepancies will be discussed and resolved. During literature screening, the reviewers will first read the titles and abstracts for preliminary screening. After excluding obviously unrelated literature, full-text double screening will be conducted to determine whether to include them. The main data extraction contents will include the name of the first author, country, year of publication, animal species, number of cases, age, type of doped elements, outcome indicators, and more.

Authenticity and quality evaluation

The quality evaluation and cross-checking of the included animal experiments using the SYRCLE assessment instrument was conducted by two independent evaluators.

Quantitative synthesis of the data

In this paper, the corresponding outcome variables’ data were organized into a table, and then the collected data were analyzed. Rev Man 5.4.1 and Stata 14.0 software was used for meta-analysis. The standardized mean difference (SMD) was calculated using Hedges’ g method with inverse-variance weighting, as the effect analysis statistic for continuous variables. And its 95 % confidence interval (CI) was provided. Heterogeneity adoption among included research results χ2 Inspection for analysis, while combining with I2 to quantitatively determine the magnitude of heterogeneity. If I2≤50 %, p≥0.1, it is considered that there is no significant heterogeneity among the studies, and fixed effect models are used for analysis; If I2>50 %, p<0.1, it is considered that there is significant heterogeneity among the studies, and a random effect model is used for analysis. If there is statistical heterogeneity between the results of each study, further analysis of the source of heterogeneity will be conducted.

Significant heterogeneity was treated using regression analysis and subgroup analysis, or only descriptive analysis. Sensitivity analysis was performed by excluding studies one by one to investigate the robustness of the results. Funnel plots were used to assessed the publication bias for primary outcome. When asymmetric funnel plots indicated publication bias, use Egger linear regression to quantitatively analyze publication bias.

Results

Search process

As shown in Figure 1, our literature retrieval strategy yielded 410 articles from various databases: CNKI (n=50), Wanfang database (n=138), PubMed (n=37), Embase (n=76), and Web of Science (n=109). Four duplicate documents were removed using EndNote literature management software, and 192 articles were excluded by title screening. Finally, 67 articles underwent full-text screening and 11 met the eligibility criteria.

Figure 1: Flow chart of literature retrieval.
Figure 1:

Flow chart of literature retrieval.

Study characteristics

A total of 11 articles were included in the study, comprising 77 control animals and 79 elemental doped animals [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36]. There were 12 element doping schemes included, with six studies using Mg element doping, two studies using Si element doping, one with Sr element doping, and three with Zn element doping, as detailed in Table 2.

Table 2:

Characteristics of the included studies.

Author Year Sample size Types of experiments Interventions Ceramic type Implantation time (week) Outcome measures
Go et al. [26] 2020 18/16 vivo Mg TCP 2/8 2/3
Liu et al. [27] 2021 9/9 vivo+vitro Mg HA 4/8 1/2/3/4
Ma et al. [28] 2015 / vitro Mg TCP / 1
Li et al. [29] 2022 8/8 vivo+vitro Zn TCP 4/8/12 1/2/3/4
Liang et al. [30] 2020 9/9 vivo+vitro Si CPC 4/12/24 1/3
Liang et al. [30] 2020 9/9 vivo+vitro Zn CPC 4/12/24 1/3
Xia et al. [31] 2021 3/3 vivo+vitro Mg HA 4/8 1/3/4
Zhong et al. [32] 2020 / vitro Sr CPC / 1/2
Qian et al. [33] 2020 4/4 vivo+vitro Zn CPC 4/8/16 1/3
Lee et al. [34] 2019 4/4 vitro Mg TCP / 1/2
Pei et al. [35] 2014 12/12 vivo+vitro Si HA 4/8/12 1
Liu et al. [36] 2022 3/3 vivo+vitro Mg TCP 4/8/10 1/3/4

  1. 1 is the proliferation of BMSCs or MC3T3-E1 cells in vitro, 2 is ALP activity, 3 is bone volume fraction (BV/TV), 4 is trabecular number (Tb. N).

Study quality evaluation

The included studies were evaluated using the SYRCLE Risk of Bias assessment tool, and the results are shown in Table 3. The generation of random sequence, baseline characteristics, allocation concealment, randomization of animal placement, double blind method, evaluation of random results and report of selective results do not have sufficient evidence to prove whether the evaluation criteria are met. However, all studies reported no incomplete data and were generally of medium quality. All experimental animals were randomly divided into groups, that is to first number the animals in order, and then use randomization tools to group them into an experimental group and a control group. No other sources of bias were found.

Table 3:

SYRCLE’ s risk of bias tool for animal studies.

Author Year 1 2 3 4 5 6 7 8 9 10
Go et al. [26] 2020 U Y Y U U U U N U Y
Liu et al. [27] 2021 U U Y U U U U N U Y
Ma et al. [28] 2015 U Y U Y U U U N U Y
Li et al. [29] 2022 U Y Y Y U U U N U Y
Liang et al. [30] 2020 U Y U U U U U N U Y
Xia et al. [31] 2021 U U U Y U U U N U Y
Zhong et al. [32] 2020 U U Y Y U U U N U Y
Qian et al. [33] 2020 U Y Y Y U U U N U Y
Lee et al. [34] 2019 U U Y U U U U N U Y
Pei et al. [35] 2014 U Y U U U U U N U Y
Liu et al. [36] 2022 U Y U U U U U N U Y

  1. Y as low risk of bias; N for high risk of bias; U for unclear.1 was generated for the sequence; 2 for baseline characteristics; 3 for allocation concealment; 4 for motility placement randomized; 5 for investigator blinding; 6 for randomized outcome assessment; 7 for the blinding of the testers; 8 for incomplete data reporting; 9 for the selectivity results presentation; 10 for other sources of bias.

Results of the meta-analysis

Meta-analysis of the effect of trace element doping on cell proliferation of BMSCs or MC3T3-E1 cells in vitro

A total of 10 articles, including 11 studies have reported the effect of element doping on cell proliferation of BMSCs or MC3T3-E1 cells in vitro [27], [28], [29], [30], [31], [32], [33], [34], [35], [36]. The heterogeneity between the 11 studies is very low, so a fixed effects model was used. The combined effect quantity is [SMD=1.07, 95 %CI: (0.54, 1.61), p<0.0001], as depicted in Figure 2A. These findings suggest that trace element doping may enhance cell proliferation in BMSCs or MC3T3-E1 cells, and the results have significant differences.

Figure 2: Meta-analysis of the effects of trace element doping on the cell experiments in vitro. (A) The cell proliferation profile of BMSCs or MC3T3-E1 cells in vitro. (B) The cell alkaline phosphatase (ALP) activity.
Figure 2:

Meta-analysis of the effects of trace element doping on the cell experiments in vitro. (A) The cell proliferation profile of BMSCs or MC3T3-E1 cells in vitro. (B) The cell alkaline phosphatase (ALP) activity.

Meta-analysis of cell alkaline phosphatase (ALP) activity

A total of five studies have reported the effect of element doping on cell ALP activity [26], 27], 29], 32], 34]. The meta-analysis revealed a fixed effect model yielding a combined effect size of [SMD=2.56, 95 %CI: (1.39, 3.73, p<0.0001], as depicted in Figure 2B. These findings suggest that trace element doping may enhance ALP activity in BMSCs or MC3T3-E1 cells, and the heterogeneity of research results is small.

Meta-analysis of the bone volume fraction (BV/TV) in vivo experiments

A total of eight studies have reported the effect of element doping on the bone volume fraction (BV/TV) in vivo experiments [26], 27], [29], [30], [31, 33], 36]. The meta-analysis revealed significant heterogeneity among the eight studies, with a combined effect size of [SMD=3.60, 95 %CI: (2.23, 4.97), p<0.00001], indicating that elemental doping can effectively promote bone healing in vivo, as illustrated in Figure 3A. To identify the possible sources of heterogeneity in the experimental bone healing rates, covariates such as the types of doped elements, ceramic types and implantation time were examined using meta-regression analysis, as shown in Supplementary Table S1. The results indicate that ceramic species may be the main source of heterogeneity.

Figure 3: The effects of trace element doping on the indicators of animal experiment. (A) Meta-analysis of bone volume fraction (BV/TV). (B) Subgroup analysis forest map of the effect of ceramic types on BV/TV. (C) Meta-analysis of the trabecular number (Tb. N).
Figure 3:

The effects of trace element doping on the indicators of animal experiment. (A) Meta-analysis of bone volume fraction (BV/TV). (B) Subgroup analysis forest map of the effect of ceramic types on BV/TV. (C) Meta-analysis of the trabecular number (Tb. N).

Subgroup analysis of bone healing rates was performed based on different ceramic types, and the findings suggest that the bone healing rate in the microelement-doped group was significantly higher than that in the control group, regardless of the type of ceramics employed, including HA, BCP, or CPC, as depicted in Figure 3B. Specifically, the subgroup analysis of ceramic types revealed that TCP significantly increased the bone healing rate, with a significantly higher effect size than that of the control group [SMD=4.21, 95 % CI: (1.49, 6.94), p<0.05]. The intra-group heterogeneity test I2=37 %, p=0.20, indicating a relatively low risk of heterogeneity. CPC also significantly increased the bone healing rate, with a statistically significant difference [SMD=2.16, 95 % CI: (1.08, 3.24), p<0.0001], the intra-group heterogeneity test I2=33 %, p=0.22, indicating a relatively low risk of heterogeneity. Similarly, HA significantly increased the bone healing rate, and there was also a significant difference [SMD=3.60, 95 % CI: (2.23, 4.97), p<0.00001], the intra-group heterogeneity test I2=41 %, p=0.19, indicating a relatively low risk of heterogeneity.

Meta-analysis of the trabecular number (Tb. N) in vivo experiments

A total of four studies have reported the effect of element doping on the trabecular number (Tb. N) [27], 29], 31], 36]. The meta-analysis revealed a random effect model yielding a combined effect size of [SMD=1.35, 95 %CI: (0.67, 2.03), p<0.0001], as depicted in Figure 3C. These results suggest that elemental doping is beneficial for increasing the number of bone trabeculae (Tb. N), and the heterogeneity of research results is small.

Sensitivity analysis

To ensure the stability and reliability of the meta-analysis results, sensitivity analysis was conducted on the effects of element doping on cell proliferation, ALP activity, bone volume fraction, and trabecular meshwork quantity. Exclude one study at a time from the included literature and merge other studies. The sensitivity analysis results indicate that the combined effect of element doping intervention on cell proliferation, ALP activity, bone volume fraction, and trabecular meshwork is not significantly affected by the sensitivity analysis, as shown in Figure 4A–D, indicating that the research results are relatively robust.

Figure 4: Sensitivity analysis and publication bias. (A) Sensitivity analysis of cell proliferation rate in vitro. (B) Sensitivity analysis of ALP activity. (C) Sensitivity analysis of bone volume fraction. (D) Sensitivity analysis of trabecular number. (E) Funnel diagram of osteogenic related cells proliferation rate in vitro. (F) Egger’s publication bias plot of osteogenic related cells proliferation rate in vitro.
Figure 4:

Sensitivity analysis and publication bias. (A) Sensitivity analysis of cell proliferation rate in vitro. (B) Sensitivity analysis of ALP activity. (C) Sensitivity analysis of bone volume fraction. (D) Sensitivity analysis of trabecular number. (E) Funnel diagram of osteogenic related cells proliferation rate in vitro. (F) Egger’s publication bias plot of osteogenic related cells proliferation rate in vitro.

Publication bias

The publication bias of the studies included in the evaluation outcome indicators. Draw a funnel map of the proliferation of BMSCs or MC3T3-E1 cells in vitro and find that there is asymmetry on both sides, indicating that there may be publication bias in the study, as shown in Figure 4E. The quantitative analysis of publication bias using Eggers linear regression method is shown in Supplementary Table S2 and Figure 4F. It can be seen that the p<0.05, indicating that there may be publication bias in the report of osteoblast proliferation rate in vitro in 11 studies. The number of studies involving the other three outcome indicators is less than 10, so no publication bias analysis of the outcome indicators will be conducted.

Discussion

Discussion of meta-analysis results

This article conducted a meta-analysis of 11 studies, using the results of in vitro cell experiments and in vivo bone implantation experiments as evaluation indicators to evaluate the osteogenic effect of calcium phosphate ceramic/PLGA composite doped with trace elements. The results suggest that doping trace elements can promote bone repair in rats. Compared to the control group, the doping group showed that the proliferation of BMSC or MC3T3-E1 cells was improved, and the activity of ALP in the cells was also increased. In the study of bone healing rate in vivo, significant heterogeneity was observed in the analysis of the effect of element doping on bone volume fraction. After conducting meta-regression analysis to examine heterogeneity from different perspectives, such as the type of doped elements, implantation time, and ceramic type, it was found that the type of calcium phosphate ceramics may be the main source of heterogeneity. Further subgroup analysis was conducted based on the type of calcium phosphate ceramics, and the results showed that the intra group heterogeneity of subgroup analysis was low. Therefore, it can be determined that the type of ceramics is likely the source of heterogeneity in bone volume fraction results. In addition, funnel chart and Eggers’ method are used to evaluate publication bias, we found that there may be some publication bias due to insufficient reporting of negative data included in the study.

In recent years, the composite of calcium phosphate ceramics and PLGA has gained widespread use in medicine, particularly in the realm of bone tissue engineering and repair, owing to its biodegradability [37]. Nonetheless, this composite material is not without its flaws. Its low biological activity, inadequate mechanical properties, inflammation response, and difficulty controlling degradation rate are significant drawbacks that need to be addressed [38], [39], [40]. As a potential solution, doping trace elements is deemed a viable method to enhance the biocompatibility and biological functionality of composite materials [41].

For composite materials of trace element-doped calcium phosphate ceramics/PLGA, each factor in their composition influences their bone repair effect. Some studies have shown that trace element doping has a significant impact on bone repair effectiveness [42], [43], [44]. However, our study found that, in addition to trace elements, the type of calcium phosphate ceramics also had a significant impact on the composite material’s bone repair effect. Evidence can also be found in clinical trials. In a clinical trial for the treatment of periodontal bone defects, BCP/PLGA demonstrated superior clinical efficacy compared to β-TCP at six months after surgery, specifically in the reduction of periodontal pockel depth and cemento-enamel junction levels [45]. Therefore, it is expected that further optimization of the structural composition of calcium phosphate ceramics will lead to better outcomes in bone defect repair in the future.

However, in addition to element doping and the type of calcium phosphate ceramics, there are other factors that may also influence the bone repair efficacy of the composite materials. Studies have shown that doping with different elements may lead to varying osteogenic effects. As an illustration, when it comes to Mg and Sr, in addition to their shared osteogenic potential, Mg ions can promote the migration of endothelial cells, while Sr ions can regulate the phenotype of macrophages to facilitate angiogenesis [46], [47], [48], [49]. Then, the dose effect of element doping is another possible factor. Studies have shown that magnesium oxide nanoparticles (nMgO) doped in calcium phosphate ceramic/PLGA composites exhibit a dose-dependent effect on the adhesion and proliferation of BMSCs, specifically enhancing these processes at low doses (200 μg/mL) and inhibiting them at high doses (>300 μg/mL) [50], [51], [52]. Moreover, the method of material preparation is also one of the heterogeneity risks. For example, in the 3D printing technology used for the fabrication of composite materials, compared to commonly used extrusion-based printing methods such as Fused Deposition Modeling (FDM), Low-Temperature Deposition Manufacturing (LMD) better achieves precise control over pore size and interconnectivity, as well as the preservation of material bioactivity, due to its low-temperature process and unique phase separation characteristics [53], [54], [55].

It should be noted that the limited number of standardized preclinical studies on trace element-doped composites may introduce above heterogeneity risks. This reflects a broader challenge in biomaterials research, where experimental protocols often vary significantly across laboratories. However, with more standardized research reports, the research methods and conclusions of this study will display more significant value, whose meta-analytical framework may provide a methodological roadmap for future studies adhering to standardized guidelines (e.g., ISO 10993), which could enhance cross-study comparability.

Anyhow, the implantation time, type of doped elements does not appear to be the critical factors affecting the bone repair effect. Instead, the type of calcium phosphate ceramics utilized may have the most significant impact on the bone repair effect of composite materials. If a more systematic study is needed on the impact of element doped composite materials on bone repair, it is recommended to first determine the type of calcium phosphate ceramic used, and then explore the impact of element doping. Moving forward, conducting more standardized animal experiments on element-doped calcium phosphate bioactive ceramic osteogenic materials is essential. These experiments can provide guidance for the controllable preparation and innovative design of element-doped calcium phosphate bioactive ceramic materials.

Article limitations

1. Some of the literature data were unavailable, and therefore were not included in the analysis. 2. Insufficient consideration was given to factors that lead to heterogeneity risks, such as the content and method of doping elements, which were not taken into account. 3. The outcome measures of the included literature demonstrated publication bias, possibly due to the small sample sizes of the studies. Thus, large samples and high-quality literature studies are necessary to obtain reliable study results. 4. Some studies lack a clear description of randomization methods in animal studies, which may affect the credibility of the experimental results. It is recommended that future studies adhere to standardized guidelines such as ARRIVE 2.0 to enhance the transparency of research methods [56].

Conclusions

The addition of trace elements can promote the proliferation of osteogenesis related cells and enhance bone healing rates. However, the use of different types of calcium phosphate ceramics may be a major source of heterogeneity leading to bone repair outcomes in vivo, and publication bias remains a concern. To obtain a better understanding of the impact of trace element doping, it is important to first define the specific type of calcium phosphate ceramics utilized.

Corresponding author: Tun Yuan, National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, Sichuan, 610064, China; College of Biomedical Engineering, Sichuan University, Chengdu, 610064, China; and Sichuan Testing Centre for Biomaterials and Medical Devices, Chengdu, Sichuan, 610064, China, E-mail:
Hongwei He and Meng Zhong contributed equally to this work.

Funding source: National Natural Science Foundation of China

Award Identifier / Grant number: No. 81902398 and No. 81371685

Funding source: the National key research and development programs of China

Award Identifier / Grant number: No. 2022YFC2405800

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: The authors acknowledge financial support from the National key research and development programs of China (No. 2022YFC2405800), National Natural Science Foundation of China (No. 81902398 and No. 81371685).

  7. Data availability: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/bmt-2024-0593).

Received: 2024-12-03
Accepted: 2025-04-04
Published Online: 2025-04-18
Published in Print: 2025-08-26

© 2025 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/bmt-2024-0593
Keywords for this article
bone repair; calcium phosphate ceramic; element doping; animal experiments; meta-analysis
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BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Design and optimization of a high-definition transcranial electrical stimulation device with envelope wave
  4. Free gas micro-/nano-bubble water: a novel dispersion system to prepare ultrasound imaging vehicles
  5. MEMS-based narrow-bandwidth magnetic field sensors: preliminary assessment of prototypes regarding coercivity, remanence, and sensitivity
  6. Novel low-cost approach to build large-scale flexible sensors for spatially distributed ground reaction force measurements
  7. Does helical plating for proximal humeral shaft fractures benefit bone healing? – an in silico analysis in fracture healing
  8. Meta-analysis of animal experiments on osteogenic effects of trace element doped calcium phosphate ceramic/PLGA composites
  9. Classification of anemic condition based on photoplethysmography signals and clinical dataset
  10. Improving the cleaning quality of tube lumen instruments by imaging analysis and deep learning techniques
  11. Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study
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