Efficacy and safety of AiDi injection in treating primary liver cancer: A systematic review on 70 randomized controlled trials

Efficacy and safety of AiDi injection in treating primary liver cancer: A systematic review on 70 randomized controlled trials | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Efficacy and safety of AiDi injection in treating primary liver cancer: A systematic review on 70 randomized controlled trials Zhengyu Duan, Xiuli Mo, Lanxu Jia, Haoyuan Li, Xiaonan Liang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7287067/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Background AiDi injection (ADI) has been widely used for primary liver cancer (PLC) and numerous clinical trials in China have been conducted to compare the efficacy of ADI with other treatments for PLC. Objective This study aimed to conduct a systematic review and meta-analysis to comprehensively evaluate ADI for PLC. Methods PubMed, Web of Science, the Cochrane Library, CNKI and WanFang Database were searched to select randomized controlled trials (RCTs) that evaluated ADI for PLC with outcomes including disease control rate (DCR), objective response rate (ORR), quality of life (QoL), serious adverse events (SAEs). The RoB2 tool was used to assess RCTs. Meta-analysis was performed to compute the overall effect sizes using odds ratio (OR) with 95% confidence intervals (CIs). Subgroup and sensitivity analyses, meta-regression, and publication bias were also conducted. The strength of evidence was assessed using with the GRADE method. Results This study included 70 RCTs involving 5283 PLC patients. The overall RoB of RCTs was assessed as some concerns. The effect size of OR was 2.86 (95% CI [2.41, 3.40]) with statistical significance (P < 0.00001) and insignificant heterogeneity (I 2 = 0%, P = 0.69) on DCR. The effect sizes were significant differences (P < 0.00001) with insignificant heterogeneity (P ≥ 0.14) on ORR, QoL, and SAEs. Moreover, subgroup and sensitivity analyses, and meta-regression showed consistent results. Most publication bias analyses showed insignificant differences. The evidence strength was rated as moderate. Conclusion ADI combination therapy demonstrated significant efficacy and safety in PLC patients. Nevertheless, further strong evidence through more high-quality RCTs is warranted to support findings. Biological sciences/Cancer Health sciences/Diseases Health sciences/Gastroenterology Health sciences/Medical research Health sciences/Oncology primary liver cancer randomized controlled trials systematic review AiDi injection efficacy safety Figures Figure 1 Figure 2 Figure 3 Highlights 1. This study employed comprehensive systermatic review and meta-analysis to evaluate AiDi injection (ADI) for primary liver cancer (PLC) on 70 RCTs. 2. ADI combination therapy was found to be more efficacy and safety for adult patients with PLC. 3. This study included the largest RCTs and provided the most reliable evidence of ADI against PLC. Significance of this study What is already known on this subject? AiDi injection (ADI) played an important role in the treatment of primary liver cancer (PLC). Although six meta-analyses on ADI against PLC were available, there are obvious limitations of the methodology and tools employed in these studies. Moreover, some new randomized controlled trials (RCTs) have been conducted and published after these meta-analyses published. Thus, a comprehensive study to apply more rigorous methods to evaluate all eligible RCTs is warranted according to the PRISMA-2020 statement. What are the new findings? This study was the first critical systermatic review to provide a comprehensive quality appraisal of 70 RCTs with 5283 patients investigating ADI for the treatment of adults with PLC. This latest evidence shown that ADI combination therapy was efficacy and safety for PLC patient. The overall quality of 70 RCTs evaluated with the Risk of Bias 2 tool (RoB2) was assessed to be some concerns. How might it impact clinical practice in the foreseeable future? The ADI combination therapy demonstrated significantly efficacy and safety for adult patients with PLC. However, more high-quality RCTs with larger sample sizes, and longer follow-up periods are still warranted to strengthen the evidence of ADI in treating PLC in further study. 1. Introduction Primary liver cancer (PLC), predominantly comprising hepatocellular carcinoma, intrahepatic cholangio carcinoma, and mixed carcinoma, is characterized by high incidence and mortality rates [ 1 ] . As one of the most prevalent malignant tumors globally, particularly in China, PLC ranks third in cancer-related mortality [ 2 ] . PLC represents a significant public health burden, with approximately 370,000 new cases diagnosed annually, and an estimated 326,000 deaths each year in China [ 3 ] . PLC in its early stages often presents no symptoms or only non-specific symptoms, progresses rapidly, and by the time of diagnosis, 60% of patients have reached at an advanced stage [ 4 ] , leaving limited treatment options [ 5 ] . Current conventional treatments mainly includes transcatheter arterial chemoembolization (TACE), radio-frequency ablation, radiation therapy, and molecular targeted therapy [ 6 ] . However, these therapies are associated with certain side effects, such as fatigue, nausea, hair loss and others. Meanwhile, traditional Chinese medicines (TCM) is widely used in China for cancers. There is more and more evidence that TCM combined with conventional therapies is effective in treating liver cancer [ 7 ] . Many clinical trials of PLC treatments have shown that TCM injections, such as AiDi injection (ADI) [ 8 ] , compound Kushen injection [ 9 ] , Kanglaite injection [ 10 ] , and Kangai injection [ 11 ] , can improve treatment effectiveness and reduce adverse reactions for various cancers. ADI, one combination formula and prescription, was approved (drug approval number: Z52020236) by China National Medical Products Administration (NMPA) as a TCM that demonstrated a potential clinical therapeutic effect in treating PLC [ 7 ] and is included in the standard of pharmacopoeia [ 12 ] . It is composed of four Chinese medicines: Blister beetle ( Mylabris phalerata Pallas, Meloidae , Banmao in Chinese pinyin), Astragalus Root ( Astragalus membranaceus (Fisch.) Bge., Fabaceae , Huangqi in Chinese pinyin), Ginseng ( Panax ginseng C.A.Mey., Araliaceae , Renshen in Chinese pinyin), Eleuthero ( Eleutherococcus senticosus (Rupr. & Maxim.) Maxim., Araliaceae , Ciwujia in Chinese pinyin) and it has been widely used in clinical practice for PLC [ 13 ] . The preliminary literature search found that there were hundreds of clinical trials and six systematic reviews to evaluate ADI for PLC. All these six systematic reviews conducted meta-analysis of randomized controlled trials (RCTs) to compare Chinese herbal injections including ADI with TACE. However, these six systematic reviews did not provide justification for selecting a random-effects model and a fixed-effect model, assess adequately the heterogeneity of the included studies, perform meta-regression analysis, select the Risk of Bias 2 tool [ 14 ] to evaluate the quality of included RCTs, and apply the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach [ 15 ] to assess the evidence strength of meta-analysis. The first [ 16 ] included 16 RCTs, the second [ 17 ] included 21 RCTs, the third [ 18 ] included 20 RCTs, the fourth [ 19 ] included 19 RCTs, the fifth [ 20 ] included 33 RCTs, and the last one [ 21 ] included 24 RCTs published up to 2019. Additional RCTs have since been published [ 22 – 25 ] that require to be included and evaluated after 2019. Thus, a study is needed to conduct a comprehensive systematic review and meta-analysis following the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) [ 26 ] statement to compare the efficacy and safety of ADI for adult patients with PLC. 2. Methods 2.1. Study design This study was registered with PROSPERO with the registration number CRD42024599944 and conducted according to the PRISMA guidelines. Table S1 in the Supplementary material provides the PRISMA 2020 checklist [ 26 ] . 2.2. Database search and retrieval strategies Clinical trials were comprehensively searched from PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI) Database, and WanFang Database with a search window from database inception to June 1, 2024. The search focused on two key concepts: Primary liver cancer, Aidi injection were identified to search relevant clinical trials. Search terms included ‘Primary liver cancer’, ‘Aidi injection’, ‘Liver neoplasms’, ‘Hepatic neoplasms’, ‘Hepatic neoplasm’, ‘Liver neoplasm’, ‘Yuanfaxingganai’, ‘Ganai’, ‘Aidizhusheye’, ‘Randomized controlled trial’. Table S2 summarizes the specific search strategy for each database. 2.3. PICOS criteria for RCTs selection All relevant records were managed and organized using EndNote software. After duplicate records were excluded, potentially eligible clinical trials were independently reviewed by reading full-text articles. Potential clinical studies with full-text were included based on the following PICOS criteria: Participants were adults of at least 18 years of age suffering from PLC that was diagnosed with medical criteria including pathological, histological, and/or cytological examinations; Interventions had to include ADI that was used as ADI monotherapy, or ADI combination therapy (ADI was prescribed based on the controls); Controls mainly involved the TACE, radiotherapy, chemotherapy, other drug therapies, or their combination therapies; Outcome measures included the clinical efficacy and safety data. Clinical efficacy data included DCR (disease control rate, complete remission (CR) + partial remission (PR) + disease stability (SD)) and ORR (objective response rate, CR + PR) [ 6 ] , in which patients were divided into the following categories: CR, complete disappearance of visible lesions for more than one month; PR, at least a 50% reduction in the size of a single lesion or a combined product of the two largest perpendicular diameters of two largest lesions reduced by more than 50%; SD, no significant change in the condition for at least 4 weeks, and the estimated increase in tumor size < 25%, and decrease < 50%, the appearance of new lesions or an estimated increase in the size of existing lesions ≥ 25%. Quality of life (QoL) included both improvement and stabilization. The efficacy data also included survival rates, and cellular immune function profiles (such as CD3 + T cells, CD4 + T cells). Clinical safety data included specific adverse events (AEs) such as leukopenia, and serious adverse events (SAEs) that were defined as AEs with grade > II. DCR, ORR, QoL, and SAEs were defined as the primary outcomes, survival rate, cellular immune function, and specific AEs were defined as the secondary outcomes. Studies were required to be clinical randomized controlled trials (RCTs). The exclusion criteria included: Patients with other primary tumors; ADI was not used for patients with PLC in clinical trials; ADI was used for all patients with PLC in clinical trials; clinical trials were not RCTs. 2.4. Information extraction Two researchers (DZY and JYL) independently read the titles and abstracts of the literature, and screened out obviously irrelevant literatures, reviews, pharmacological experiments, etc. If it was a controlled trial, the full text was read to determine whether it met the inclusion criteria. In case of disagreement, discussions or consultation with a third party (MXL and JLX) could be conducted. The extracted contents included: Basic information of the included studies, including the number of authors, publication year; Basic characteristics of the research subjects, including the number of people in the treatment group and the control group, gender composition, average age, specific details such as the dosage and course of the intervention measures and drugs; Outcome including DCR, ORR, QoL, SAEs, cellular immune function, and survival rate. 2.5. Quality assessment of included RCTs The risk of bias (RoB) of included RCTs was independently evaluated with the Cochrane collaboration’s RoB tool 2 (RoB2) [ 14 ] . RoB was assessed based on the following five domains: the randomization process; deviations from intended interventions; missing outcome data; measurement of the outcome; and selection of the reported result. The RoB of each domain was assessed as ‘low’, ‘high’, or ‘some concerns’. The RoB of an RCT was assessed to be ‘low’ when all five domains were rated as ‘low’. The RoB of an RCT was assessed to be ‘high’ when at least one domain was rated as ‘high’. Otherwise, RCTs were assessed to be ‘some concerns’. 2.6. Statistical analysis and evidence synthesis A meta-analysis on a random-effects model [ 27 ] was conducted to synthesize the outcome data from all eligible RCTs. The overall effect size was estimated with odds ratio (OR) and 95% confidence intervals (CIs) for binary data, and mean difference (MD) and 95% CIs for continuous data. OR was calculated as the ratio of the odds of an event occurring in one group to the odds of the event occurring in another group. MD was one of the numbers that indicates the degree of difference between the values of each variable. When OR is far from 1 or MD is far from 0, it means that there is a significant association between the variables being studied. Heterogeneity among RCTs was measured with the I-square (I 2 ) and chi-square (χ 2 ). The possible differences among all RCTs were assessed with adequate essential analysis including subgroup and sensitivity analyses, and meta-regression analyses based on RCT characteristics including the TNM stage of PLC (II-IV, or not reported), sample sizes, ADI dosages, courses of treatment, levels of RoB (some concerns, or high), details of randomization, publication years, No. of the author, mean age of patients, ratio of male to female patients, and controls. The differences between the subgroups were evaluated with the chi-square test for subgroups. Publication bias was evaluated with funnel plots, Begg’s test [ 28 ] , and Egger’s test [ 29 ] . The trim-and-fill method [ 30 ] was also used for correcting funnel plot asymmetry in the case of high risk of publication bias. Meta-regression analysis was performed on the 4 primary outcomes. Additionally the GRADE approach [ 15 ] was also applied to assess the overall evidence strength as ‘high’, ‘moderate’, ‘low’, or ‘very low’ for primary outcomes. RevMan 5.4.1 was selected to draw forest plots. Other operations are performed using the ‘metafor’ [ 31 ] package of R software. A result with a P-value less than 0.05 was considered statistically significant. 3. Result 3.1. Characteristics of 70 included RCTs Initially, 452 records were identified through database search (Fig. 1). Eventually, 70 RCTs that met the previous PICOS criteria were included for data extraction and evidence synthesis. These 70 RCTs included 5283 adult patients with PLC, andTable S3 summarized the basic characteristics of RCTs. 2651 PLC patients were randomly assigned to the ADI group and 2582 PLC patients assigned to the control group. These 70 RCTs with 5283 participants were published between 2003 and 2022, with sample sizes ranging from 15 to 80, follow-up periods ranged from 90 to 1050 days, and ADI dose ranging from 50 ml to 100 ml, including 30 studies equal to 50 ml and 40 items ranging from 50 to 100 ml. Among the included studies, 48 RCTs compared ADI with TACE, and 22 reported ADI with chemotherapy, radiotherapy, or other conventional treatments. Additionally, 50 RCTs reported DCR and ORR, 25 RCTs reported QoL, 12 RCTs reported SAEs, and17 reported changes in CD3 + T cells, 19 reported changes in CD4 + T cells, 14 reported changes in CD8 + T cells, and 19 reported changes in CD4 + /CD8 + ratio. 12 reported 0.5-year survival rates, 14 reported 1-year survival rates, 12 reported 2-year survival rates, and 9 RCTs reported leukopenia. 3.2. Some concerns of RCTs In the randomization process, 13 RCTs used the random number table method, 1 used the stratified randomization method, 37 RCTs only mentioned randomization, and the remaining 21 RCTs did not mention random grouping. In deviations from intended interventions, none of the RCTs mentioned blinding. In missing outcome data, 4 RCTs reported loss to follow-up. In measurement of the outcome, 5 RCTs did not report quality of life improvement or stabilization. In selection of the reported result, 30 RCTs conducted selective result reporting. Althoughall RCTs reported the criteria for patients with PLC, none described the effect of blinding, allocation concealment, and withdrawal’s impact on outcomes. The RoB (Fig. 2 and Fig. S1 ) showed some concerns about the overall quality of included RCTs. 3.3. Significant efficacy estimates of ADI for PLC 3.3.1. Evaluation of therapeutic efficacy The overall effect size (Fig. 3) on DCR of OR = 2.86 with 95% CI [2.41, 3.40] and P < 0.00001 indicated that ADI combination therapy was more efficacious than controls (TACE alone and other treatments) in treating PLC. There was no statistical heterogeneity among the studies (I 2 = 0%, P = 0.69). Meanwhile, the meta-analysis showed that ADI combination therapy could significantly improve the ORR (Fig. S2 ) of patients with PLC based on the results (OR = 2.12, 95% CI [1.84, 2.45], P < 0.00001). There was no statistical heterogeneity among the studies (I 2 = 0%, P = 0.98). These significant results showed that ADI could significantly improve the clinical efficacy, which indicated the efficacy of ADI for PLC. 3.3.2. Quality of life The overall effect size on QoL (Fig. S3) of OR = 3.89, 95% CI [3.08, 4.90], P < 0.00001 indicated that ADI combination therapy could significantly improve and stabilize QoL in PLC patients. There was no statistical heterogeneity among the studies (I 2 = 0%, P = 0.99). The results indicate that ADI can significantly improve and stabilize the QoL of PLC patients. 3.3.3. Survival rates The results showed that the significant effect size of the OR was 1.84 (95% CI [1.30, 2.58]; P = 0.0005) for 0.5-year survival rate (Fig. S4), with no significant heterogeneity (I 2 = 0%, P = 0.99). For 1-year survival rate (Fig. S5), the significant effect size of the OR was 2.05 (95% CI [1.59, 2.64]; P < 0.0001), with no significant heterogeneity (I 2 = 0%, P = 0.56). For 2-year survival rate (Fig. S6), the significant effect size of the OR was 1.83 (95% CI [1.39, 2.42]; P < 0.0001), with no significant heterogeneity (I 2 = 0%, P = 0.99). These results indicate that ADI significantly improves patient survival rates and there is no significant heterogeneity, which suggests that ADI can improve the survival rate in PLC patients. 3.3.4. Cellular immune function The results showed that the significant effect size of the MD was 10.71 (95% CI [8.03, 13.39]; P < 0.00001) for CD3 + T cells (Fig. S7) with significant heterogeneity (I 2 = 96%, P < 0.00001). For CD4 + T cells (Fig. S8), the significant effect size of the MD was 7.51 (95% CI [5.70, 9.31]; P < 0.00001) with significant heterogeneity (I 2 = 94%, P < 0.00001). There was no statistically significant difference between the ADI combined treatment group and the conventional treatment group in CD8 + T cells (Fig. S9) (P = 0.33). For CD4 + /CD8 + ratio (Fig. S10), the significant effect size of the MD was 0.28 (95% CI [0.22, 0.35]; P < 0.00001) with significant heterogeneity (I 2 = 89%, P < 0.00001). These results show that ADI may improve the cellular immune function in PLC patients. 3.4. More safety of ADI for PLC 3.4.1. Serious adverse events The overall effect size of OR = 0.21 with 95% CI [0.12, 0.36] showed that ADI could significantly (P < 0.00001) reduce the incidence of SAEs (Fig. S11). Additionally, the study showed insignificant heterogeneity (I 2 = 31%, P = 0.14). These results showed that ADI was safer than controls in treating adult patients with PLC. 3.4.2. Leukopenia The overall effect size of OR = 0.36 with a 95% CI [0.20, 0.65] indicated that ADI could significantly reduce the incidence of leukopenia (Fig. S12) (P = 0.0007). Additionally, the study showed insignificant heterogeneity (I 2 = 0%, P = 0.87). These results showed that ADI was safe for PLC patients. 3.5. Consistent efficacy from subgroup and sensitivity analysis In terms of four primary outcomes, subgroup and sensitivity analyses were conducted in 27 subgroups (Table. 1) based on the TNM staging of PLC (II-IV or not reported), sample size ( 50ml), RoB (with some concerns or high), detailed information on randomization (only mentioned randomization or reported specific randomization methods or not mentioned), publication year (2003–2012 or 2013–2022), number of authors (1, 2, 3 or > 3), ADI treatment duration (> 28 days or ≤ 28 days), mean age of patients (> 55, ≤ 55 or not mentioned), ratio of male to female patients (≥ 2, 0.05) except for the subgroups of ADI dosages (P = 0.02) on DCR. The results showed that ADI was significant effective and safe in PLC patient treatment. These significant and consistent results from different subgroups and sensitivity analyses suggested that results from this meta-analysis were robust and consistent. 3.6. Robust efficacy from meta-regression The P values of all features were greater than 0.05 (Table S4 to S7) for Meta-regression, which suggested that the basic features extracted in the included literature were not the source of heterogeneity. 3.7. Insignificant publication bias No significant publication bias was detected for the three primary outcomes (Table 2 ). In terms of DCR, Egger’s test (P = 0.0003) and Begg’s test (P = 0.0007) indicated that there may be significant publication bias. Although trim-and-fill method found 14 missing RCTs (Fig. S13), the adjusted significant results (2.50 [2.13, 2.94]) with the insignificant heterogeneity (I 2 = 0.6%, P = 0.46) still suggested the significant efficacy. The adjusted results were similar and consistent with the overall efficacy size from meta-analysis. In terms of ORR, Egger’s test indicated that there may be significant publication bias (P = 0.0011) and 1 missing RCT with the trim-and-fill method (Fig. S14). However, the adjusted significant results (2.10 [1.82, 2.42]) with the insignificant heterogeneity (I 2 = 0.00%, P = 0.94) still suggested that the efficacy remained significant. In terms of QoL and SAEs, both Egger’s test and Begg’s test did not indicate significant publication bias (P>0.05). There may be 3 missing studies on QoL (Fig. S15) and 4 missing studies on SAEs (Fig. S16) based on the trim-and-fill method, but the adjusted results were still significant differences without significant heterogeneity. These results still support the significant efficacy and safety of ADI in treating PLC patients. Overall, all three methods indicated potential publication bias on DCR and no significant publication bias on ORR, QoL, and SAEs. Table 2 Publication bias analysis on four primary outcomes. Outcome Egger’s regression test Begg’s rank correlation test Trim-and-fill method t P z P Left Right OR (adj) OR P (adj) I 2 (%) P (het adj) DCR 3.94 0.000 3.37 0.001 14 0 2.50 [2.13, 2.94] 2.86 [2.41, 3.40] < 0.0001 0.6 0.463 ORR 3.48 0.001 1.37 0.170 1 0 2.10 [1.82, 2.42] 2.12 [1.84, 2.45] < 0.0001 0.0 0.944 QoL -0.34 0.736 0.02 0.981 0 3 4.06 [3.25, 5.07] 3.90 [3.09, 4.92] < 0.0001 0.0 0.986 SAEs -0.51 0.163 -0.89 0.373 0 4 0.33 [0.17, 0.61] 0.21 [0.12, 0.36] 0.0004 56.2 0.003 adj: adjusted; het: heterogeneity. Publication bias analyses were conducted on the effect estimates from the meta-analysis on a random-effects model. 3.8. Moderate evidence strength Table 3 shows the evidence strength assessment with the GRADE approach [ 15 ] . The 43 included RCTs assessed as 'high risk' for RoB weakened the strength of evidence. Three statistical methods indicated possible publication bias for DCR which could also decrease the evidence strength of DCR. Inconsistency, indirectness, imprecision did not decrease evidence strength. Thus, the overall evidence of this meta-analysis was ‘moderate’. Table 3 Moderate evidence strength with the GRADE approach. Outcome Evidence assessment Evidence strength No. of RCTs Risk of bias Inconsistency Indirectness Imprecision Publication bias DCR 50 serious ↓ not serious not serious not serious serious ↓ ㊉㊉〇〇 ORR 50 serious ↓ not serious not serious not serious none ㊉㊉㊉〇 QoL 25 serious ↓ not serious not serious not serious none ㊉㊉㊉〇 SAEs 12 serious ↓ not serious not serious not serious none ㊉㊉㊉〇 4. Discussions 4.1. Reliable of this study This study presents the first PRISMA-compliant meta-analysis to comprehensively assess the efficacy and safety of ADI against common therapies including radiotherapy, chemotherapy and conventional drugs for the treatment of adults with PLC based on 70 eligible RCTs published. Significant efficacy of ADI was demonstrated in terms of DCR, ORR, QoL, survival rates and cellular immune function. The insignificant heterogeneity was observed for all efficacy estimates. Meanwhile, the results of the safety assessment (OR < 1 with P < 0.05) also found that ADI was safe for patients with PLC on outcome measures of SAEs and specific AEs. Adequate subgroup and sensitivity analysis on different characteristics including sample size, publication year, patient age, control group treatment plan and dosages of ADI also supported the significant efficacious estimates of ADI. Moreover, there was no significant result for most publication bias analyses. ADI combination therapy is of significance in improving efficacy and safety for the treatment of patients with PLC. Moreover, the overall evidence strength of this meta-analysis was moderate with the GRADE approach. Therefore, these findings and evidence suggested that ADI has significant efficacy and safety in treating PLC patients. 4.2. Strengths of this study Adequate subgroup and sensitivity analyses were performed in terms of primary outcomes based on 27 subgroups. At the same time, the effect sizes with significant differences in SAEs, leukopenia were provided reliable evidence for the safety evaluation of ADI. This study used funnel plots, Egger’s test and Begg’s test to evaluate the publication bias in terms of four primary outcomes. The results showed that there may be significant publication bias in DCR, and there were missing studies in all four results with the trim-and-fill method. Nevertheless, the adjustment results were stable with no significant heterogeneity. ADI still shows significant efficacy and safety in PLC patients. The study demonstrates significant efficacy of ADI in the treatment of PLC patients in terms of DCR and ORR, which is consistent with the results of the six previously included studies [ 16 – 21 ] . In addition, the OR value of QoL in this study was 3.89 (95% CI [3.08, 4.90]), which was higher than the highest OR value of 3.47 (2.70, 4.46) computed from previous studies [ 19 ] . RCTs published after 2019 [ 22 – 25 ] strengthened the evidence base for ADI in adult PLC treatment. 4.3. Limitations of this study Three limitations warrant consideration: First, although both Chinese and English databases were searched, all included RCTs originated exclusively from Chinese studies. The average sample size was small, and some RCTs reported vague information about the specific conditions of patients. Most follow-up periods were also too short to assess the long-term effect of ADI on PLC. Second, 37 RCTs and 18 RCTs were assessed as being of some concerns or high risk due to the randomization process. Only 15 of the 70 RCTs reported specific randomization methods. These weaknesses lead to bias in selection and implementation, reducing the strength of evidence. Thirdly, pharmacological mechanisms remain unaddressed. The Shennong Bencao Jing ( Shennong's Classic of Materia Medica ) elaborates: the Four Natures theory (‘cold’, ‘cool’, ‘hot’, and ‘warm’) is a one of the core concepts in TCM, determining the efficacy and applicable scope of medicinal herbs. There are four herbs in ADI, in which Chinese blistering beetle belongs to the ‘hot’ category, other three herbs (Milkvetch Root, Ginseng, and Acanthopanax senticosus) belong to the ‘ warm ’ category [ 32 ] . Medicinal herbs with ‘hot’ and ‘warm’ can contributing to enhanced immune function, increased metabolic activity, and mild regulatory effects [ 33 ] . Their specific mechanisms and signaling pathways require further research and elucidation. Therefore, more high-quality, well-designed, larger sample size, and longer follow-up RCTs are needed in further studies to verify the beneficial effects of ADI in PLC treatment and improve the strength of evidence for ADI in PLC treatment. 5. Conclusion The ADI combination therapy demonstrated significantly efficacy and safety for PLC patient. However, more RCTs of high quality with large sample sizes, and longer follow up periods are still warranted to update the evidence of ADI in treating PLC in further study. Declarations Acknowledgments We thank all authors who kindly provided additional information and data regarding their studies, for this meta-analysis. Author contributions Concept and design: Yongliang Jia, Shuiling Jin Preliminary literature search: Zhengyu Duan, Yongliang Jia Literature search and examination: Zhengyu Duan, Xiuli Mo, Lanxu Jia Data extraction and examination: Zhengyu Duan, Xiuli Mo, Lanxu Jia Acquisition, analysis, or interpretation of data: Zhengyu Duan, Yongliang Jia,Haoyuan Li, Xiaonan Liang Statistical analysis: Zhengyu Duan, Yongliang Jia, Xiaonan Liang Obtained funding: Yongliang Jia Administrative, technical, or material support: Shuiling Jin, Yongliang Jia Drafting of the manuscript: Zhengyu Duan, Yongliang Jia Critical revision of the manuscript for important intellectual content: Zhengyu Duan, Yongliang Jia, Shuiling Jin Discussing impact of the results and how to articulate: Yongliang Jia, Zhengyu Duan Zhengyu Duan and Yongliang Jia had full access to all the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Conflict of Interest Disclosures. The authors declare that they have no known competing financial interests or personal Conflict of Interest Disclosures. relationships that could have appeared to influence the work reported in this paper. Funding Part of the work of YLJ was financially supported by the Henan Institute of Medical and Pharmacological Sciences (Grant No. 2025BP0102), and the Wuxi ShenNongCao Medical Technology Co., Ltd. (Grant No. 24110002/509). Data availability The data that support the findings of this study are available from the corresponding author Yongliang Jia upon reasonable request. ORCID Zhengyu Duan: https://orcid.org/0009-0004-5481-607X Xiuli Mo: https://orcid.org/0009-0003-6674-5101 Lanxu Jia: https://orcid.org/0009-0005-9699-2773 Haoyuan Li: https://orcid.org/0009-0009-7658-312X Xiaonan Liang: https://orcid.org/0000-0002-6017-2184 Shuiling Jin: https://orcid.org/0000-0001-7330-7140 Yongliang Jia: https://orcid.org/0000-0002-4981-9282 Ethical approval This study did not need ethical approval because all the work was developed using published data. References Witt-Kehati, D.; Fridkin, A.; Alaluf, M.B.; Zemel, R.; Shlomai, A. Inhibition of pMAPK14 Overcomes Resistance to Sorafenib in Hepatoma Cells with Hepatitis B Virus. Transl Oncol . 11(2). 511-517, doi: 10.1016/j.tranon.2018.02.015 (2018). Dai, X.; Pi, G.; Yang, S.L.; Chen, G.G.; Liu, L.P.; Dong, H.H. Association of PD-L1 and HIF-1α Coexpression with Poor Prognosis in Hepatocellular Carcinoma. Transl Oncol . 11(2). 559-566.doi: 10.1016/j.tranon.2018.02.014 (2018). Jin, Z.; Zhang, Q.; Zhu, H.; Teng, G. 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Meta-analysis of clinical efficacy and safety of compound Kushen injection combined with hepatic arterial chemoembolization in the treatment of primary liver cancer. J Li-Shizhen Tradit Chin Med . 33(03). 767-770. (2022). Sun, D.; Yang, Z.; Long, F.; Wei, X.; Tang, D. Meta-analysis of the efficacy of KangLaiTe injection combined with transhepatic arterial chemoembolization in the treatment of advanced liver cancer. Chin J Hepatol . 36(02). 363-368. (2020). Ma, X.; He, X.; Li, H.; Wei, S.; Zou, Y.; Zhao, Y. Meta-analysis of Kangai injection combined with TACE in the treatment of primary liver cancer. Chin Tradit Pat Med . 41(07). 1564-1572. (2019). Zhang, N.; Tian, Y. Effect of Aidi injection on liver function after partial resection of hepatocellular carcinoma. Clin Med Eng . 31(04). 453-454. (2024). Lan, H. Study on the optimal formulation and synergistic mechanism of Aidi injection for anti-liver cancer. (2021). Sterne, J.A.C.; Savović, J.; Page, M.J. et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ . 366. l4898. doi: 10.1136/bmj.l4898 (2019). Guyatt, G.H.; Oxman, A.D.; Vist, G.E. et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ . 336(7650). 924-926.doi: 10.1136/bmj.39489.470347.AD (2008). Yuan, W.; Qiao, B.; Chang, J.; Zou, L.; Zhang, R. Systematic evaluation of Aidi injection combined with chemotherapy in the treatment of primary hepatocellular carcinoma. Med J West Chin . 25(01). 144-148. (2010). Gong, X.; Yang, Q.; Wang, X.; Xu, Y.; Huang, J. A randomized controlled meta-analysis of Aidi injection combined with transcatheter arterial chemoembolization in the treatment of primary liver cancer. Chin J Tradit Chin Med Pharm . 28(05). 1627-1632. (2013). Zhou, X.; Xie, R.; Xu, J. A meta-analysis of the literature on Aidi injection for interventional therapy of hepatocellular carcinoma. (2014). Yang, Y.; He, X.; Jian, X. et al. Systematic evaluation of Aidi injection combined with hepatic artery embolization chemotherapy in the treatment of primary liver cancer. Eval Anal Drug Use Hosp China . 16(12). 1588-1593. doi: 10.14009/j.issn.1672-2124.2016.12.002 (2016). Zheng, J.; Zhang, D.; Wu, J.; Liu, S.; Zhang, B. Meta-analysis of Aidi injection in adjuvant treatment of liver cancer. Chin J Pharmacoepidemiol. 26(08). 540-546. doi: 10.19960/j.cnki.issn1005-0698.2017.08.006 (2017). Liu, L.; Liang, J.; Deng, X. Effects of Aidi Injection with Western Medical Therapies on Quality of Life for Patients with Primary Liver Cancer:A Systematic Review and Meta-Analysis. Chin J Integr Med . 25(10). 785-790. (2019). Yi, A.; Li, W.; Liu, J. Effect of Aidi injection combined with 5-fluorouracil on immune function in patients with hepatitis B-associated liver cancer. Oncol Prog. 20(07). 691-694. (2022). Yin, J.; Yang, S. Effect of hepatic arterial chemoembolization combined with Aidi injection in the treatment of primary liver cancer and its effect on serum basic fibroblast growth factor level. Henan Med Res . 29(34). 6457-6459. (2020) Liu, D.; Zhang, G.; Shen, Z et al. Effect of Aidi injection combined with hepatic arterial chemoembolization on the clinical efficacy, vascular growth factor and cellular immune function of patients with primary liver cancer. J Hainan Med Univ . 25(23). 1770-1775. doi: 10.13210/j.cnki.jhmu.20191118.001 (2019). Tang, X. Aidi injection combined with radiofrequency ablation in the study of vascular growth factor and lymphocyte subsets in patients with primary liver cancer. Med J Liaoning. 35(03). 64-66. (2021). Hutton, B.; Salanti, G.; Caldwell, D.M. et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med . 162(11). 777-784. doi: 10.7326/m14-2385 (2015). Page, M.J.; McKenzie, J.E.; Bossuyt, P.M. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ . 372. n71. doi: 10.1136/bmj.n71 (2021). Begg, C.B, Mazumdar, M. Operating characteristics of a rank correlation test for publication bias. BIOMETRICS . 50(4). 1088-1101. (1994). Egger, M.; Davey, S.G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ . 315(7109). 629-634. doi: 10.1136/bmj.315.7109.629 (1997). Duval, S.; Tweedie, R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. BIOMETRICS . 56(2). 455-463. doi:10.1111/j.0006-341x.2000.00455.x (2000). Viechtbauer, W. Conducting Meta-Analyses in R with the metafor Package. J Stat Softw . 36(3). 1 - 48. doi: 10.18637/jss.v036.i03 (2010). Wang, Y.; Kuang, H.; Su, F. et al. Clinical value of four natures of traditional Chinese medicine and its relationship with five flavors. Chin Tradit Herb Drugs . 54(04). 1329-1341. (2023). Li, Q.; Liu, H.; Jin, J. et al. Traditional Chinese Medicine Properties and Microcalorimetry: BioScience Evaluation. Med Research . 1. 103-121. doi: https://doi.org/10.1002/mdr2.70002 (2025). Table 1 Table 1. Subgroup and sensitivity analyses based on different characteristics of 70 RCTs. Characteristics Subgroups No. of RCTs No. of participants OR χ 2 (Chi 2 , df, P) 95% CI Z P (effect) I 2 (%) P (het) DCR All RCTs 50 3739 2.86 [2.41, 3.40] 12.00 < 0.00001 0 0.69 TNM stage Ⅱ-Ⅳ 21 1801 2.70 1.27, 1, 0.26 [2.09, 3.49] 7.59 < 0.00001 0 0.74 NR 29 1938 3.30 [2.61, 4.16] 9.99 < 0.00001 0 0.95 Sample size ≥ 60 40 3268 3.01 0.03, 1, 0.86 [2.49, 3.64] 11.41 < 0.00001 0 0.80 < 60 10 471 2.88 [1.88, 4.43] 4.83 < 0.00001 0 0.90 ADI dosage 50mg 27 2099 3.65 5.09, 1, 0.02 [2.87, 4.64] 10.55 50mg 23 1640 2.45 [1.91, 3.14] 7.07 < 0.00001 0 0.83 No. of author 1 17 1178 3.34 2.56, 3, 0.46 [2.51, 4.45] 8.30 < 0.00001 0 0.67 2 11 798 2.37 [1.64, 3.43] 4.60 3 16 1314 2.61 [1.97, 3.46] 6.65 < 0.00001 0 0.73 Risk of bias Some concerns 36 2480 3.21 1.72, 1, 0.19 [2.62, 3.93] 11.25 < 0.00001 0 0.89 High 14 1259 2.47 [1.78, 3.45] 5.35 < 0.00001 0 0.78 Randomization Specific 13 949 2.75 0.41,2, 0.81 [1.99, 3.81] 6.09 < 0.00001 0 0.78 Mentioned 22 1483 3.16 [2.41, 4.13] 8.43 < 0.00001 0 0.84 NR 15 1307 2.99 [2.18, 4.11] 6.76 < 0.00001 0 0.55 Publication year 2003-2012 30 2118 2.94 0.06, 1, 0.81 [2.35, 3.67] 9.42 < 0.00001 0 0.72 2013-2022 20 1621 3.07 [2.33, 4.03] 8.04 < 0.00001 0 0.91 Follow-up ≤ 28d 17 1168 2.79 0.30, 1, 0.58 [2.06, 3.77] 6.65 28d 33 2571 3.09 [2.50, 3.82] 10.47 55 14 1339 2.42 1.46, 2, 0.48 [1.72, 3.41] 5.04 < 0.00001 9 0.35 < 55 17 1216 3.07 [2.27, 4.16] 7.26 < 0.00001 13 0.31 Not mentioned 19 1184 3.12 [2.33, 4.18] 7.65 < 0.00001 0 0.95 Male/female ≥ 2 26 1670 3.01 0.34, 2, 0.84 [2.35, 3.85] 8.70 < 0.00001 0 0.92 < 2 23 1935 2.93 [2.32, 3.70] 9.01 < 0.00001 20 0.20 Not mentioned 1 134 2.27 [0.92, 5.64] 1.77 0.08 Controls TACE 30 2129 3.16 0.81, 1, 0.37 [2.51, 3.99] 9.76 < 0.00001 0 0.99 Other 20 1610 2.64 [1.93, 3.62] 6.03 < 0.00001 31 0.09 ORR All RCTs 50 3739 2.12 [1.84, 2.45] 10.32 < 0.00001 0 0.98 TNM stage Ⅱ-Ⅳ 21 1801 2.01 0.54, 1, 0.46 [1.64, 2.47] 6.71 < 0.00001 0 0.96 NR 29 1938 2.24 [1.83, 2.74] 7.86 < 0.00001 0 0.86 Sample size ≥ 60 40 3268 2.17 0.54, 1, 0.46 [1.86, 2.54] 9.84 < 0.00001 0 0.98 < 60 10 471 1.86 [1.26, 2.74] 3.14 0.002 0 0.64 ADI dosage 50mg 27 2099 2.12 0.00, 1, 0.97 [1.75, 2.57] 7.67 50mg 23 1640 2.13 [1.72, 2.65] 6.89 < 0.00001 0 0.96 No. of author 1 17 1178 2.17 0.27, 3, 0.97 [1.66, 1.82] 5.70 < 0.00001 3 0.41 2 11 798 2.02 [1.48, 2.74] 4.48 < 0.00001 0 0.76 3 6 449 2.29 [1.55, 3.38] 4.15 3 16 1314 2.11 [1.65, 2.70] 5.97 < 0.00001 0 0.99 Risk of bias Some concerns 36 2480 2.10 0.27, 3, 0.97 [1.75, 2.51] 8.10 < 0.00001 0 0.77 High 14 1259 2.18 [1.71,2.77] 6.38 < 0.00001 0 1.00 Randomization Specific 13 949 2.45 4.39, 2, 0.11 [1.84, 3.26] 6.12 < 0.00001 0 0.55 Mentioned 22 1483 1.77 [1.42, 2.22] 5.05 < 0.00001 0 0.99 Not mentioned 15 1307 2.40 [1.87, 3.08] 6.91 < 0.00001 0 0.93 Publication year 2003—2012 30 2118 2.02 0.68, 1, 0.41 [1.66, 2.44] 7.12 < 0.00001 0 0.96 2013—2022 20 1621 2.28 [1.84, 2.82] 7.50 < 0.00001 0 0.83 Follow-up ≤ 28d 17 1168 2.09 0.03, 1, 0.87 [1.61, 2.72] 5.49 28d 33 2571 2.15 [1.81, 2.55] 8.71 55 14 1339 2.20 0.26, 2, 0.88 [1.74, 2.77] 6.66 < 0.00001 0 0.70 < 55 17 1216 2.15 [1.67, 2.77] 5.90 < 0.00001 0 1.00 Not mentioned 19 1184 2.01 [1.55, 2.61] 5.26 < 0.00001 0 0.59 Male/female ≥ 2 26 1670 2.00 0.61, 2, 0.74 [1.61, 2.48] 6.29 < 0.00001 0 0.95 < 2 23 1935 2.22 [1.83, 2.71] 7.92 < 0.00001 0 0.82 Not mentioned 1 134 2.36 [1.10, 5.05] 2.21 0.03 Controls TACE 30 2129 1.88 3.88, 1, 0.05 [1.56, 2.27] 6.58 < 0.00001 0 1.00 Other 20 1610 2.52 [2.02, 3.14] 8.20 < 0.00001 0 0.65 QoL All RCTs 25 1702 3.89 [3.08, 4.90] 11.48 < 0.00001 0 0.99 TNM stage Ⅱ-Ⅳ 11 870 3.98 0.04, 1, 0.84 [2.88, 5.49] 8.42 < 0.00001 0 0.81 NR 14 832 3.79 [2.71, 5.30] 7.82 < 0.00001 0 0.98 Sample size ≥ 60 19 1435 4.07 0.92,1, 0.34 [3.17, 5.23] 11.00 < 0.00001 0 0.97 < 60 6 267 2.94 [1.59, 5.44] 3.43 0.0006 0 0.97 ADI dosage 50mg 9 646 3.60 0.26, 1, 0.61 [2.46, 5.25] 6.61 50mg 16 1056 4.07 [3.04, 5.46] 9.40 < 0.00001 0 0.99 No. of author 1 7 470 3.55 0.57, 3, 0.90 [2.29, 5.51] 5.65 < 0.00001 0 0.70 2 7 477 4.25 [2.67, 6.74] 6.13 3 8 574 4.09 [2.80, 5.96] 7.31 < 0.00001 0 0.75 Risk of bias Some concerns 18 1133 3.72 0.29, 1, 0.59 [2.80, 4.94] 9.04 < 0.00001 0 0.92 High 7 569 4.25 [2.85, 6.33] 7.10 < 0.00001 0 0.99 Randomization Specific 2 96 3.26 2.13, 2, 0.34 [1.13, 9.44] 2.18 0.03 0 0.64 Mentioned 17 1106 3.46 [2.58, 4.64] 8.27 < 0.00001 0 0.99 Not mentioned 6 500 4.96 [3.32, 7.42] 7.81 < 0.00001 0 0.83 Publication year 2003-2012 22 1527 3.99 0.49, 1, 0.48 [3.13, 5.09] 11.15 < 0.00001 0 0.98 2013-2022 3 175 3.00 [1.40, 6.42] 2.82 0.005 0 0.95 Follow-up ≤ 28d 8 515 3.50 0.26, 1, 0.61 [2.21, 5.56] 5.33 28d 17 1187 4.03 [3.08, 5.26] 10.19 55 6 576 6.82 0.85, 2, 0.65 [2.51, 5.29] 6.82 < 0.00001 0 0.75 < 55 6 367 6.00 [2.87, 7.96] 6.00 < 0.00001 0 0.84 Not mentioned 12 717 6.74 [2.50, 5.31] 6.74 < 0.00001 0 0.94 Male/female ≥ 2 18 1202 3.82 0.18, 1, 0.67 [2.92, 5.01] 9.75 < 0.00001 0 1.00 < 2 5 422 4.34 [2.58, 7.28] 5.56 < 0.00001 11 0.35 Controls TACE 20 1401 3.59 2.13, 1, 0.14 [2.78, 4.63] 9.03 < 0.00001 0 1.00 Other 5 301 5.66 [3.25, 9.87] 6.11 < 0.00001 0 0.67 OR: Odds ratio; CI: Confidence interval; het: Heterogeneity; DCR: Disease control rate; RCT: Randomized controlled trial; TNM: Tumor Node Metastasis; NR: not report; TACE: transcatheter arterial chemoembolization; ADI: AiDi Injection; ORR: Objective response rate; SAEs: Serious adverse events; QoL: Quality of life. 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10:15:29","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":946230,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3ForestplotoftheDCR.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/44b78e656d6a64d8f562be0d.png"},{"id":91846034,"identity":"3607f15d-f9e9-41ad-854d-8a039a45c680","added_by":"auto","created_at":"2025-09-22 10:15:29","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":447521,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1Databasesearchandstudyselection.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/cff112173690dc4a2cb1bd72.png"},{"id":91846025,"identity":"83740847-7658-4baa-8e78-3c82333eb965","added_by":"auto","created_at":"2025-09-22 10:15:29","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":41930,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2RiskofbiasofincludedRCTswiththeRoB2tool.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/76b0aed11330ce1fb51e72c0.png"},{"id":91847997,"identity":"76a4717f-c3db-4523-a2cd-8f5e54a51e50","added_by":"auto","created_at":"2025-09-22 10:31:29","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":125810,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure3ForestplotoftheDCR.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/65b82915bbbc8431179bd9f7.png"},{"id":91847998,"identity":"3cfc5754-c88f-4aa3-b5fa-ab8cc47c9940","added_by":"auto","created_at":"2025-09-22 10:31:29","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":184664,"visible":true,"origin":"","legend":"","description":"","filename":"d1a760f1c8764265afe7c59ea813b3801structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/7302313681a96395bc7933d3.xml"},{"id":91846039,"identity":"7166dcc4-382e-45d8-b965-ed5016768c87","added_by":"auto","created_at":"2025-09-22 10:15:29","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":197915,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/fa55b2717e32820a48ef05c5.html"},{"id":91847574,"identity":"338abd9b-ae6b-48ca-b309-c298a697457d","added_by":"auto","created_at":"2025-09-22 10:23:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6893782,"visible":true,"origin":"","legend":"\u003cp\u003eDatabase search and study selection.\u003c/p\u003e","description":"","filename":"Figure1Databasesearchandstudyselection.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/71e1fac17fb1faab284d68f4.png"},{"id":91847573,"identity":"458aabd4-6810-43ed-be7c-ff1a4681fd2b","added_by":"auto","created_at":"2025-09-22 10:23:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":398300,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias of included RCTs with the Cochrane RoB2 tool.\u003c/p\u003e","description":"","filename":"Figure2RiskofbiasofincludedRCTswiththeRoB2tool.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/b361541f9add1c10547b078e.png"},{"id":91846021,"identity":"b78154e1-05c2-42b2-af29-371a6a9f9f21","added_by":"auto","created_at":"2025-09-22 10:15:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":946230,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the DCR.\u003c/p\u003e","description":"","filename":"Figure3ForestplotoftheDCR.png","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/bf6b5fbac58626fd402deb1d.png"},{"id":97724630,"identity":"5ba42b47-01c0-49c1-ad73-85273dc5ffaf","added_by":"auto","created_at":"2025-12-08 16:12:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10099056,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/2eccd979-87da-4dca-9a29-d61f86c955bc.pdf"},{"id":91846032,"identity":"00528cf2-6fb7-424d-b0ca-a25ee737502c","added_by":"auto","created_at":"2025-09-22 10:15:29","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4436265,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary20250807.docx","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/e23dcc6b12371264a880e50d.docx"},{"id":91847995,"identity":"01df730e-faea-49c5-9ce1-022edf90d1f4","added_by":"auto","created_at":"2025-09-22 10:31:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24963,"visible":true,"origin":"","legend":"","description":"","filename":"PRISMAchecklist20250807.docx","url":"https://assets-eu.researchsquare.com/files/rs-7287067/v1/8f073d554a1ae0a7aedcebf9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Efficacy and safety of AiDi injection in treating primary liver cancer: A systematic review on 70 randomized controlled trials","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1. This study employed comprehensive systermatic review and meta-analysis to evaluate AiDi injection (ADI) for primary liver cancer (PLC) on 70 RCTs.\u003c/p\u003e\u003cp\u003e2. ADI combination therapy was found to be more efficacy and safety for adult patients with PLC.\u003c/p\u003e\u003cp\u003e3. This study included the largest RCTs and provided the most reliable evidence of ADI against PLC.\u003c/p\u003e"},{"header":"Significance of this study","content":"\u003cp\u003e\u003cstrong\u003eWhat is already known on this subject?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAiDi injection (ADI)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eplayed an important role in the\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003etreatment of primary liver cancer (PLC). Although six meta-analyses on ADI against PLC were available, there are obvious limitations of the methodology and tools employed in these studies. Moreover, some new randomized controlled trials (RCTs) have been conducted and published after these meta-analyses published. Thus, a comprehensive study to apply more rigorous methods to evaluate all eligible RCTs is warranted according to the PRISMA-2020 statement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat are the new findings?\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThis study was the first critical systermatic review to provide a comprehensive quality appraisal of 70 RCTs with 5283 patients investigating ADI for the treatment of adults with PLC.\u003c/li\u003e\n \u003cli\u003eThis latest evidence shown that ADI combination therapy was efficacy and safety for PLC patient.\u003c/li\u003e\n \u003cli\u003eThe overall quality of 70 RCTs evaluated with the Risk of Bias 2 tool (RoB2) was assessed to be some concerns.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHow might it impact clinical practice in the foreseeable future?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ADI combination therapy demonstrated significantly efficacy and safety for adult patients with PLC. However, more high-quality RCTs with larger sample sizes, and longer follow-up periods are still warranted to strengthen the evidence of ADI in treating PLC in further study.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003ePrimary liver cancer (PLC), predominantly comprising hepatocellular carcinoma, intrahepatic cholangio carcinoma, and mixed carcinoma, is characterized by high incidence and mortality rates \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. As one of the most prevalent malignant tumors globally, particularly in China, PLC ranks third in cancer-related mortality \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. PLC represents a significant public health burden, with approximately 370,000 new cases diagnosed annually, and an estimated 326,000 deaths each year in China \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePLC in its early stages often presents no symptoms or only non-specific symptoms, progresses rapidly, and by the time of diagnosis, 60% of patients have reached at an advanced stage \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, leaving limited treatment options \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Current conventional treatments mainly includes transcatheter arterial chemoembolization (TACE), radio-frequency ablation, radiation therapy, and molecular targeted therapy \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. However, these therapies are associated with certain side effects, such as fatigue, nausea, hair loss and others.\u003c/p\u003e\u003cp\u003eMeanwhile, traditional Chinese medicines (TCM) is widely used in China for cancers. There is more and more evidence that TCM combined with conventional therapies is effective in treating liver cancer \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Many clinical trials of PLC treatments have shown that TCM injections, such as AiDi injection (ADI) \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, compound Kushen injection \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, Kanglaite injection \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, and Kangai injection \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, can improve treatment effectiveness and reduce adverse reactions for various cancers. ADI, one combination formula and prescription, was approved (drug approval number: Z52020236) by China National Medical Products Administration (NMPA) as a TCM that demonstrated a potential clinical therapeutic effect in treating PLC \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e and is included in the standard of pharmacopoeia \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. It is composed of four Chinese medicines: Blister beetle (\u003cem\u003eMylabris phalerata Pallas, Meloidae\u003c/em\u003e, Banmao in Chinese pinyin), Astragalus Root (\u003cem\u003eAstragalus membranaceus (Fisch.) Bge., Fabaceae\u003c/em\u003e, Huangqi in Chinese pinyin), Ginseng (\u003cem\u003ePanax ginseng C.A.Mey., Araliaceae\u003c/em\u003e, Renshen in Chinese pinyin), Eleuthero (\u003cem\u003eEleutherococcus senticosus (Rupr. \u0026amp; Maxim.) Maxim., Araliaceae\u003c/em\u003e, Ciwujia in Chinese pinyin) and it has been widely used in clinical practice for PLC \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe preliminary literature search found that there were hundreds of clinical trials and six systematic reviews to evaluate ADI for PLC. All these six systematic reviews conducted meta-analysis of randomized controlled trials (RCTs) to compare Chinese herbal injections including ADI with TACE. However, these six systematic reviews did not provide justification for selecting a random-effects model and a fixed-effect model, assess adequately the heterogeneity of the included studies, perform meta-regression analysis, select the Risk of Bias 2 tool \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e to evaluate the quality of included RCTs, and apply the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e to assess the evidence strength of meta-analysis. The first \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e included 16 RCTs, the second \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e included 21 RCTs, the third \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e included 20 RCTs, the fourth \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e included 19 RCTs, the fifth \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e included 33 RCTs, and the last one \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e included 24 RCTs published up to 2019. Additional RCTs have since been published \u003csup\u003e[\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e that require to be included and evaluated after 2019. Thus, a study is needed to conduct a comprehensive systematic review and meta-analysis following the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e statement to compare the efficacy and safety of ADI for adult patients with PLC.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study design\u003c/h2\u003e\u003cp\u003e This study was registered with PROSPERO with the registration number CRD42024599944 and conducted according to the PRISMA guidelines. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in the Supplementary material provides the PRISMA 2020 checklist \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Database search and retrieval strategies\u003c/h2\u003e\u003cp\u003eClinical trials were comprehensively searched from PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI) Database, and WanFang Database with a search window from database inception to June 1, 2024. The search focused on two key concepts: Primary liver cancer, Aidi injection were identified to search relevant clinical trials. Search terms included \u0026lsquo;Primary liver cancer\u0026rsquo;, \u0026lsquo;Aidi injection\u0026rsquo;, \u0026lsquo;Liver neoplasms\u0026rsquo;, \u0026lsquo;Hepatic neoplasms\u0026rsquo;, \u0026lsquo;Hepatic neoplasm\u0026rsquo;, \u0026lsquo;Liver neoplasm\u0026rsquo;, \u0026lsquo;Yuanfaxingganai\u0026rsquo;, \u0026lsquo;Ganai\u0026rsquo;, \u0026lsquo;Aidizhusheye\u0026rsquo;, \u0026lsquo;Randomized controlled trial\u0026rsquo;. Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e summarizes the specific search strategy for each database.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. PICOS criteria for RCTs selection\u003c/h2\u003e\u003cp\u003eAll relevant records were managed and organized using EndNote software. After duplicate records were excluded, potentially eligible clinical trials were independently reviewed by reading full-text articles. Potential clinical studies with full-text were included based on the following PICOS criteria: Participants were adults of at least 18 years of age suffering from PLC that was diagnosed with medical criteria including pathological, histological, and/or cytological examinations; Interventions had to include ADI that was used as ADI monotherapy, or ADI combination therapy (ADI was prescribed based on the controls); Controls mainly involved the TACE, radiotherapy, chemotherapy, other drug therapies, or their combination therapies; Outcome measures included the clinical efficacy and safety data. Clinical efficacy data included DCR (disease control rate, complete remission (CR)\u0026thinsp;+\u0026thinsp;partial remission (PR)\u0026thinsp;+\u0026thinsp;disease stability (SD)) and ORR (objective response rate, CR\u0026thinsp;+\u0026thinsp;PR) \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, in which patients were divided into the following categories: CR, complete disappearance of visible lesions for more than one month; PR, at least a 50% reduction in the size of a single lesion or a combined product of the two largest perpendicular diameters of two largest lesions reduced by more than 50%; SD, no significant change in the condition for at least 4 weeks, and the estimated increase in tumor size\u0026thinsp;\u0026lt;\u0026thinsp;25%, and decrease\u0026thinsp;\u0026lt;\u0026thinsp;50%, the appearance of new lesions or an estimated increase in the size of existing lesions\u0026thinsp;\u0026ge;\u0026thinsp;25%. Quality of life (QoL) included both improvement and stabilization. The efficacy data also included survival rates, and cellular immune function profiles (such as CD3\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells, CD4\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells). Clinical safety data included specific adverse events (AEs) such as leukopenia, and serious adverse events (SAEs) that were defined as AEs with grade\u0026thinsp;\u0026gt;\u0026thinsp;II. DCR, ORR, QoL, and SAEs were defined as the primary outcomes, survival rate, cellular immune function, and specific AEs were defined as the secondary outcomes. Studies were required to be clinical randomized controlled trials (RCTs). The exclusion criteria included: Patients with other primary tumors; ADI was not used for patients with PLC in clinical trials; ADI was used for all patients with PLC in clinical trials; clinical trials were not RCTs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Information extraction\u003c/h2\u003e\u003cp\u003eTwo researchers (DZY and JYL) independently read the titles and abstracts of the literature, and screened out obviously irrelevant literatures, reviews, pharmacological experiments, etc. If it was a controlled trial, the full text was read to determine whether it met the inclusion criteria. In case of disagreement, discussions or consultation with a third party (MXL and JLX) could be conducted. The extracted contents included: Basic information of the included studies, including the number of authors, publication year; Basic characteristics of the research subjects, including the number of people in the treatment group and the control group, gender composition, average age, specific details such as the dosage and course of the intervention measures and drugs; Outcome including DCR, ORR, QoL, SAEs, cellular immune function, and survival rate.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Quality assessment of included RCTs\u003c/h2\u003e\u003cp\u003eThe risk of bias (RoB) of included RCTs was independently evaluated with the Cochrane collaboration\u0026rsquo;s RoB tool 2 (RoB2) \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. RoB was assessed based on the following five domains: the randomization process; deviations from intended interventions; missing outcome data; measurement of the outcome; and selection of the reported result. The RoB of each domain was assessed as \u0026lsquo;low\u0026rsquo;, \u0026lsquo;high\u0026rsquo;, or \u0026lsquo;some concerns\u0026rsquo;. The RoB of an RCT was assessed to be \u0026lsquo;low\u0026rsquo; when all five domains were rated as \u0026lsquo;low\u0026rsquo;. The RoB of an RCT was assessed to be \u0026lsquo;high\u0026rsquo; when at least one domain was rated as \u0026lsquo;high\u0026rsquo;. Otherwise, RCTs were assessed to be \u0026lsquo;some concerns\u0026rsquo;.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Statistical analysis and evidence synthesis\u003c/h2\u003e\u003cp\u003eA meta-analysis on a random-effects model \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e was conducted to synthesize the outcome data from all eligible RCTs. The overall effect size was estimated with odds ratio (OR) and 95% confidence intervals (CIs) for binary data, and mean difference (MD) and 95% CIs for continuous data. OR was calculated as the ratio of the odds of an event occurring in one group to the odds of the event occurring in another group. MD was one of the numbers that indicates the degree of difference between the values of each variable. When OR is far from 1 or MD is far from 0, it means that there is a significant association between the variables being studied. Heterogeneity among RCTs was measured with the I-square (I\u003csup\u003e2\u003c/sup\u003e) and chi-square (χ\u003csup\u003e2\u003c/sup\u003e). The possible differences among all RCTs were assessed with adequate essential analysis including subgroup and sensitivity analyses, and meta-regression analyses based on RCT characteristics including the TNM stage of PLC (II-IV, or not reported), sample sizes, ADI dosages, courses of treatment, levels of RoB (some concerns, or high), details of randomization, publication years, No. of the author, mean age of patients, ratio of male to female patients, and controls. The differences between the subgroups were evaluated with the chi-square test for subgroups. Publication bias was evaluated with funnel plots, Begg\u0026rsquo;s test \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, and Egger\u0026rsquo;s test \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. The trim-and-fill method \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e was also used for correcting funnel plot asymmetry in the case of high risk of publication bias. Meta-regression analysis was performed on the 4 primary outcomes. Additionally the GRADE approach \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e was also applied to assess the overall evidence strength as \u0026lsquo;high\u0026rsquo;, \u0026lsquo;moderate\u0026rsquo;, \u0026lsquo;low\u0026rsquo;, or \u0026lsquo;very low\u0026rsquo; for primary outcomes. RevMan 5.4.1 was selected to draw forest plots. Other operations are performed using the \u0026lsquo;metafor\u0026rsquo; \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e package of R software. A result with a P-value less than 0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Characteristics of 70 included RCTs\u003c/h2\u003e\u003cp\u003eInitially, 452 records were identified through database search (Fig.\u0026nbsp;1). Eventually, 70 RCTs that met the previous PICOS criteria were included for data extraction and evidence synthesis. These 70 RCTs included 5283 adult patients with PLC, andTable S3 summarized the basic characteristics of RCTs. 2651 PLC patients were randomly assigned to the ADI group and 2582 PLC patients assigned to the control group. These 70 RCTs with 5283 participants were published between 2003 and 2022, with sample sizes ranging from 15 to 80, follow-up periods ranged from 90 to 1050 days, and ADI dose ranging from 50 ml to 100 ml, including 30 studies equal to 50 ml and 40 items ranging from 50 to 100 ml. Among the included studies, 48 RCTs compared ADI with TACE, and 22 reported ADI with chemotherapy, radiotherapy, or other conventional treatments. Additionally, 50 RCTs reported DCR and ORR, 25 RCTs reported QoL, 12 RCTs reported SAEs, and17 reported changes in CD3\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells, 19 reported changes in CD4\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells, 14 reported changes in CD8\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells, and 19 reported changes in CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003e ratio. 12 reported 0.5-year survival rates, 14 reported 1-year survival rates, 12 reported 2-year survival rates, and 9 RCTs reported leukopenia.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Some concerns of RCTs\u003c/h2\u003e\u003cp\u003eIn the randomization process, 13 RCTs used the random number table method, 1 used the stratified randomization method, 37 RCTs only mentioned randomization, and the remaining 21 RCTs did not mention random grouping. In deviations from intended interventions, none of the RCTs mentioned blinding. In missing outcome data, 4 RCTs reported loss to follow-up. In measurement of the outcome, 5 RCTs did not report quality of life improvement or stabilization. In selection of the reported result, 30 RCTs conducted selective result reporting. Althoughall RCTs reported the criteria for patients with PLC, none described the effect of blinding, allocation concealment, and withdrawal\u0026rsquo;s impact on outcomes. The RoB (Fig.\u0026nbsp;2 and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) showed some concerns about the overall quality of included RCTs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Significant efficacy estimates of ADI for PLC\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1. Evaluation of therapeutic efficacy\u003c/h2\u003e\u003cp\u003eThe overall effect size (Fig.\u0026nbsp;3) on DCR of OR\u0026thinsp;=\u0026thinsp;2.86 with 95% CI [2.41, 3.40] and P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001 indicated that ADI combination therapy was more efficacious than controls (TACE alone and other treatments) in treating PLC. There was no statistical heterogeneity among the studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.69). Meanwhile, the meta-analysis showed that ADI combination therapy could significantly improve the ORR (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) of patients with PLC based on the results (OR\u0026thinsp;=\u0026thinsp;2.12, 95% CI [1.84, 2.45], P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). There was no statistical heterogeneity among the studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.98). These significant results showed that ADI could significantly improve the clinical efficacy, which indicated the efficacy of ADI for PLC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2. Quality of life\u003c/h2\u003e\u003cp\u003eThe overall effect size on QoL (Fig. S3) of OR\u0026thinsp;=\u0026thinsp;3.89, 95% CI [3.08, 4.90], P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001 indicated that ADI combination therapy could significantly improve and stabilize QoL in PLC patients. There was no statistical heterogeneity among the studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.99). The results indicate that ADI can significantly improve and stabilize the QoL of PLC patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3. Survival rates\u003c/h2\u003e\u003cp\u003eThe results showed that the significant effect size of the OR was 1.84 (95% CI [1.30, 2.58]; P\u0026thinsp;=\u0026thinsp;0.0005) for 0.5-year survival rate (Fig. S4), with no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.99). For 1-year survival rate (Fig. S5), the significant effect size of the OR was 2.05 (95% CI [1.59, 2.64]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.56). For 2-year survival rate (Fig. S6), the significant effect size of the OR was 1.83 (95% CI [1.39, 2.42]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.99). These results indicate that ADI significantly improves patient survival rates and there is no significant heterogeneity, which suggests that ADI can improve the survival rate in PLC patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.3.4. Cellular immune function\u003c/h2\u003e\u003cp\u003eThe results showed that the significant effect size of the MD was 10.71 (95% CI [8.03, 13.39]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) for CD3\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells (Fig. S7) with significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;96%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). For CD4\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells (Fig. S8), the significant effect size of the MD was 7.51 (95% CI [5.70, 9.31]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) with significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;94%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). There was no statistically significant difference between the ADI combined treatment group and the conventional treatment group in CD8\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eT\u003c/em\u003e cells (Fig. S9) (P\u0026thinsp;=\u0026thinsp;0.33). For CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003e ratio (Fig. S10), the significant effect size of the MD was 0.28 (95% CI [0.22, 0.35]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) with significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;89%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). These results show that ADI may improve the cellular immune function in PLC patients.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.4. More safety of ADI for PLC\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.4.1. Serious adverse events\u003c/h2\u003e\u003cp\u003eThe overall effect size of OR\u0026thinsp;=\u0026thinsp;0.21 with 95% CI [0.12, 0.36] showed that ADI could significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) reduce the incidence of SAEs (Fig. S11). Additionally, the study showed insignificant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;31%, P\u0026thinsp;=\u0026thinsp;0.14). These results showed that ADI was safer than controls in treating adult patients with PLC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.4.2. Leukopenia\u003c/h2\u003e\u003cp\u003eThe overall effect size of OR\u0026thinsp;=\u0026thinsp;0.36 with a 95% CI [0.20, 0.65] indicated that ADI could significantly reduce the incidence of leukopenia (Fig. S12) (P\u0026thinsp;=\u0026thinsp;0.0007). Additionally, the study showed insignificant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.87). These results showed that ADI was safe for PLC patients.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Consistent efficacy from subgroup and sensitivity analysis\u003c/h2\u003e\u003cp\u003eIn terms of four primary outcomes, subgroup and sensitivity analyses were conducted in 27 subgroups (Table. 1) based on the TNM staging of PLC (II-IV or not reported), sample size (\u0026lt;\u0026thinsp;60 or \u0026ge;\u0026thinsp;60), ADI dose (50ml or \u0026gt;\u0026thinsp;50ml), RoB (with some concerns or high), detailed information on randomization (only mentioned randomization or reported specific randomization methods or not mentioned), publication year (2003\u0026ndash;2012 or 2013\u0026ndash;2022), number of authors (1, 2, 3 or \u0026gt;\u0026thinsp;3), ADI treatment duration (\u0026gt;\u0026thinsp;28 days or \u0026le;\u0026thinsp;28 days), mean age of patients (\u0026gt;\u0026thinsp;55, \u0026le; 55 or not mentioned), ratio of male to female patients (\u0026ge;\u0026thinsp;2, \u0026lt;2 or not mentioned), and control strategy (TACE or other). There were no significant differences in DCR, ORR, QoL and SAEs among all subgroups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) except for the subgroups of ADI dosages (P\u0026thinsp;=\u0026thinsp;0.02) on DCR. The results showed that ADI was significant effective and safe in PLC patient treatment. These significant and consistent results from different subgroups and sensitivity analyses suggested that results from this meta-analysis were robust and consistent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.6. Robust efficacy from meta-regression\u003c/h2\u003e\u003cp\u003eThe P values of all features were greater than 0.05 (Table S4 to S7) for Meta-regression, which suggested that the basic features extracted in the included literature were not the source of heterogeneity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.7. Insignificant publication bias\u003c/h2\u003e\u003cp\u003eNo significant publication bias was detected for the three primary outcomes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of DCR, Egger\u0026rsquo;s test (P\u0026thinsp;=\u0026thinsp;0.0003) and Begg\u0026rsquo;s test (P\u0026thinsp;=\u0026thinsp;0.0007) indicated that there may be significant publication bias. Although trim-and-fill method found 14 missing RCTs (Fig. S13), the adjusted significant results (2.50 [2.13, 2.94]) with the insignificant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.6%, P\u0026thinsp;=\u0026thinsp;0.46) still suggested the significant efficacy. The adjusted results were similar and consistent with the overall efficacy size from meta-analysis. In terms of ORR, Egger\u0026rsquo;s test indicated that there may be significant publication bias (P\u0026thinsp;=\u0026thinsp;0.0011) and 1 missing RCT with the trim-and-fill method (Fig. S14). However, the adjusted significant results (2.10 [1.82, 2.42]) with the insignificant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.00%, P\u0026thinsp;=\u0026thinsp;0.94) still suggested that the efficacy remained significant. In terms of QoL and SAEs, both Egger\u0026rsquo;s test and Begg\u0026rsquo;s test did not indicate significant publication bias (P\u0026gt;0.05). There may be 3 missing studies on QoL (Fig. S15) and 4 missing studies on SAEs (Fig. S16) based on the trim-and-fill method, but the adjusted results were still significant differences without significant heterogeneity. These results still support the significant efficacy and safety of ADI in treating PLC patients. Overall, all three methods indicated potential publication bias on DCR and no significant publication bias on ORR, QoL, and SAEs.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePublication bias analysis on four primary outcomes.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eEgger\u0026rsquo;s regression test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eBegg\u0026rsquo;s rank correlation test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"7\" nameend=\"c14\" namest=\"c8\"\u003e\u003cp\u003eTrim-and-fill method\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ez\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eOR (adj)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eP (adj)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eP (het adj)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDCR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2.50 [2.13, 2.94]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e2.86 [2.41, 3.40]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0.463\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eORR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2.10 [1.82, 2.42]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e2.12 [1.84, 2.45]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQoL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e4.06 [3.25, 5.07]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e3.90 [3.09, 4.92]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0.986\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAEs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.373\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.33 [0.17, 0.61]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.21 [0.12, 0.36]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e56.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"14\"\u003eadj: adjusted; het: heterogeneity. Publication bias analyses were conducted on the effect estimates from the meta-analysis on a random-effects model.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e3.8. Moderate evidence strength\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the evidence strength assessment with the GRADE approach \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The 43 included RCTs assessed as 'high risk' for RoB weakened the strength of evidence. Three statistical methods indicated possible publication bias for DCR which could also decrease the evidence strength of DCR. Inconsistency, indirectness, imprecision did not decrease evidence strength. Thus, the overall evidence of this meta-analysis was \u0026lsquo;moderate\u0026rsquo;.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModerate evidence strength with the GRADE approach.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eEvidence assessment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eEvidence strength\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo. of RCTs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRisk of bias\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInconsistency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIndirectness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eImprecision\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePublication bias\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDCR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eserious \u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eserious \u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e㊉㊉〇〇\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eORR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eserious \u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003enone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e㊉㊉㊉〇\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQoL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eserious \u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003enone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e㊉㊉㊉〇\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAEs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eserious \u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003enot serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003enone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e㊉㊉㊉〇\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Reliable of this study\u003c/h2\u003e\u003cp\u003eThis study presents the first PRISMA-compliant meta-analysis to comprehensively assess the efficacy and safety of ADI against common therapies including radiotherapy, chemotherapy and conventional drugs for the treatment of adults with PLC based on 70 eligible RCTs published. Significant efficacy of ADI was demonstrated in terms of DCR, ORR, QoL, survival rates and cellular immune function. The insignificant heterogeneity was observed for all efficacy estimates. Meanwhile, the results of the safety assessment (OR\u0026thinsp;\u0026lt;\u0026thinsp;1 with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) also found that ADI was safe for patients with PLC on outcome measures of SAEs and specific AEs. Adequate subgroup and sensitivity analysis on different characteristics including sample size, publication year, patient age, control group treatment plan and dosages of ADI also supported the significant efficacious estimates of ADI. Moreover, there was no significant result for most publication bias analyses. ADI combination therapy is of significance in improving efficacy and safety for the treatment of patients with PLC. Moreover, the overall evidence strength of this meta-analysis was moderate with the GRADE approach. Therefore, these findings and evidence suggested that ADI has significant efficacy and safety in treating PLC patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Strengths of this study\u003c/h2\u003e\u003cp\u003eAdequate subgroup and sensitivity analyses were performed in terms of primary outcomes based on 27 subgroups. At the same time, the effect sizes with significant differences in SAEs, leukopenia were provided reliable evidence for the safety evaluation of ADI. This study used funnel plots, Egger\u0026rsquo;s test and Begg\u0026rsquo;s test to evaluate the publication bias in terms of four primary outcomes. The results showed that there may be significant publication bias in DCR, and there were missing studies in all four results with the trim-and-fill method. Nevertheless, the adjustment results were stable with no significant heterogeneity. ADI still shows significant efficacy and safety in PLC patients. The study demonstrates significant efficacy of ADI in the treatment of PLC patients in terms of DCR and ORR, which is consistent with the results of the six previously included studies \u003csup\u003e[\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. In addition, the OR value of QoL in this study was 3.89 (95% CI [3.08, 4.90]), which was higher than the highest OR value of 3.47 (2.70, 4.46) computed from previous studies \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. RCTs published after 2019 \u003csup\u003e[\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e strengthened the evidence base for ADI in adult PLC treatment.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Limitations of this study\u003c/h2\u003e\u003cp\u003eThree limitations warrant consideration: First, although both Chinese and English databases were searched, all included RCTs originated exclusively from Chinese studies. The average sample size was small, and some RCTs reported vague information about the specific conditions of patients. Most follow-up periods were also too short to assess the long-term effect of ADI on PLC. Second, 37 RCTs and 18 RCTs were assessed as being of some concerns or high risk due to the randomization process. Only 15 of the 70 RCTs reported specific randomization methods. These weaknesses lead to bias in selection and implementation, reducing the strength of evidence. Thirdly, pharmacological mechanisms remain unaddressed. The \u003cem\u003eShennong Bencao Jing\u003c/em\u003e (\u003cem\u003eShennong's Classic of Materia Medica\u003c/em\u003e) elaborates: the Four Natures theory (\u0026lsquo;cold\u0026rsquo;, \u0026lsquo;cool\u0026rsquo;, \u0026lsquo;hot\u0026rsquo;, and \u0026lsquo;warm\u0026rsquo;) is a one of the core concepts in TCM, determining the efficacy and applicable scope of medicinal herbs. There are four herbs in ADI, in which Chinese blistering beetle belongs to the \u0026lsquo;hot\u0026rsquo; category, other three herbs (Milkvetch Root, Ginseng, and Acanthopanax senticosus) belong to the \u003cb\u003e\u0026lsquo;\u003c/b\u003ewarm\u003cb\u003e\u0026rsquo;\u003c/b\u003e category \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Medicinal herbs with \u0026lsquo;hot\u0026rsquo; and \u0026lsquo;warm\u0026rsquo; can contributing to enhanced immune function, increased metabolic activity, and mild regulatory effects \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Their specific mechanisms and signaling pathways require further research and elucidation. Therefore, more high-quality, well-designed, larger sample size, and longer follow-up RCTs are needed in further studies to verify the beneficial effects of ADI in PLC treatment and improve the strength of evidence for ADI in PLC treatment.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe ADI combination therapy demonstrated significantly efficacy and safety for PLC patient. However, more RCTs of high quality with large sample sizes, and longer follow up periods are still warranted to update the evidence of ADI in treating PLC in further study.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all authors who kindly provided additional information and data regarding their studies, for this meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConcept and design: Yongliang Jia, Shuiling Jin\u003c/p\u003e\n\u003cp\u003ePreliminary literature search: Zhengyu Duan, Yongliang Jia\u003c/p\u003e\n\u003cp\u003eLiterature search and examination: Zhengyu Duan, Xiuli Mo, Lanxu Jia\u003c/p\u003e\n\u003cp\u003eData extraction and examination: Zhengyu Duan, Xiuli Mo, Lanxu Jia\u003c/p\u003e\n\u003cp\u003eAcquisition, analysis, or interpretation of data: Zhengyu Duan, Yongliang Jia,Haoyuan Li, Xiaonan Liang\u003c/p\u003e\n\u003cp\u003eStatistical analysis: Zhengyu Duan, Yongliang Jia, Xiaonan Liang\u003c/p\u003e\n\u003cp\u003eObtained funding: Yongliang Jia\u003c/p\u003e\n\u003cp\u003eAdministrative, technical, or material support: Shuiling Jin, Yongliang Jia\u003c/p\u003e\n\u003cp\u003eDrafting of the manuscript: Zhengyu Duan, Yongliang Jia\u003c/p\u003e\n\u003cp\u003eCritical revision of the manuscript for important intellectual content: Zhengyu Duan, Yongliang Jia, Shuiling Jin\u003c/p\u003e\n\u003cp\u003eDiscussing impact of the results and how to articulate: Yongliang Jia, Zhengyu Duan\u003c/p\u003e\n\u003cp\u003eZhengyu Duan and Yongliang Jia had full access to all the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosures.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal Conflict of Interest Disclosures. relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePart of the work of YLJ was financially supported by the Henan Institute of Medical and Pharmacological Sciences (Grant No. 2025BP0102), and the Wuxi ShenNongCao Medical Technology Co., Ltd. (Grant No. 24110002/509).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author Yongliang Jia upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORCID\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhengyu Duan: https://orcid.org/0009-0004-5481-607X\u003c/p\u003e\n\u003cp\u003eXiuli Mo: https://orcid.org/0009-0003-6674-5101\u003c/p\u003e\n\u003cp\u003eLanxu Jia: https://orcid.org/0009-0005-9699-2773\u003c/p\u003e\n\u003cp\u003eHaoyuan Li: https://orcid.org/0009-0009-7658-312X\u003c/p\u003e\n\u003cp\u003eXiaonan Liang: https://orcid.org/0000-0002-6017-2184\u003c/p\u003e\n\u003cp\u003eShuiling Jin: https://orcid.org/0000-0001-7330-7140\u003c/p\u003e\n\u003cp\u003eYongliang Jia: https://orcid.org/0000-0002-4981-9282\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not need ethical approval because all the work was developed using published data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWitt-Kehati, D.; Fridkin, A.; Alaluf, M.B.; Zemel, R.; Shlomai, A. 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(1994).\u003c/li\u003e\n\u003cli\u003eEgger, M.; Davey, S.G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. \u003cem\u003eBMJ\u003c/em\u003e. 315(7109). 629-634. doi: 10.1136/bmj.315.7109.629 (1997).\u003c/li\u003e\n\u003cli\u003eDuval, S.; Tweedie, R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. \u003cem\u003eBIOMETRICS\u003c/em\u003e. 56(2). 455-463. doi:10.1111/j.0006-341x.2000.00455.x (2000).\u003c/li\u003e\n\u003cli\u003eViechtbauer, W. Conducting Meta-Analyses in R with the metafor Package. \u003cem\u003eJ Stat Softw\u003c/em\u003e. 36(3). 1 - 48. doi: 10.18637/jss.v036.i03 (2010).\u003c/li\u003e\n\u003cli\u003eWang, Y.; Kuang, H.; Su, F. et al. Clinical value of four natures of traditional Chinese medicine and its relationship with five flavors. \u003cem\u003eChin Tradit Herb Drugs\u003c/em\u003e. 54(04). 1329-1341. (2023).\u003c/li\u003e\n\u003cli\u003eLi, Q.; Liu, H.; Jin, J. et al. Traditional Chinese Medicine Properties and Microcalorimetry: BioScience Evaluation. \u003cem\u003eMed Research\u003c/em\u003e. 1. 103-121. doi: https://doi.org/10.1002/mdr2.70002 (2025).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Subgroup and sensitivity analyses based on different characteristics of 70 RCTs.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSubgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003eNo. of RCTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003eNo. of participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(Chi\u003csup\u003e2\u003c/sup\u003e, df, P)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003eZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003eP (effect)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003eP (het)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eDCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eAll RCTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e3739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.86\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.41, 3.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e12.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eⅡ-Ⅳ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.70\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e1.27, 1, 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.09, 3.49]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.61,\u0026nbsp;4.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e3268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.03, 1, 0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.49,\u0026nbsp;3.64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e11.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.80\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.88,\u0026nbsp;4.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.90\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eADI dosage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e5.09, 1, 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.87,\u0026nbsp;4.64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e10.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt;\u0026nbsp;50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.91,\u0026nbsp;3.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eNo. of author\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e2.56, 3, 0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.51,\u0026nbsp;4.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.64,\u0026nbsp;3.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.60\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.75,\u0026nbsp;5.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.97,\u0026nbsp;3.46]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRisk of bias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSome concerns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e1.72, 1, 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.62,\u0026nbsp;3.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e11.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.78,\u0026nbsp;3.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRandomization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSpecific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.41,2, 0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.99,\u0026nbsp;3.81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eMentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.41,\u0026nbsp;4.13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.18,\u0026nbsp;4.11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003ePublication year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2003-2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.06, 1, 0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.35,\u0026nbsp;3.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2013-2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.33,\u0026nbsp;4.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eFollow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026le; 28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.30, 1, 0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.06,\u0026nbsp;3.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.50,\u0026nbsp;3.82]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e10.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMean age of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e1.46, 2, 0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.72,\u0026nbsp;3.41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.27,\u0026nbsp;4.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.33,\u0026nbsp;4.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMale/female\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.34, 2, 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.35,\u0026nbsp;3.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.70\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.32,\u0026nbsp;3.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[0.92,\u0026nbsp;5.64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eControls\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eTACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.81, 1, 0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.51,\u0026nbsp;3.99]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.93,\u0026nbsp;3.62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eORR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eAll RCTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e3739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.84,\u0026nbsp;2.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e10.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eⅡ-Ⅳ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.54, 1, 0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.64,\u0026nbsp;2.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.83,\u0026nbsp;2.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e3268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.54, 1, 0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.86,\u0026nbsp;2.54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.26,\u0026nbsp;2.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eADI dosage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.00, 1, 0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.75,\u0026nbsp;2.57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt;\u0026nbsp;50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.72,\u0026nbsp;2.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eNo. of author\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.27, 3, 0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.66,\u0026nbsp;1.82]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.70\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.48,\u0026nbsp;2.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.55,\u0026nbsp;3.38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.65,\u0026nbsp;2.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRisk of bias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSome concerns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.27, 3, 0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.75,\u0026nbsp;2.51]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.71,2.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRandomization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSpecific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e4.39, 2, 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.84,\u0026nbsp;3.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eMentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.42,\u0026nbsp;2.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.40\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.87,\u0026nbsp;3.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003ePublication year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2003\u0026mdash;2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.68, 1, 0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.66,\u0026nbsp;2.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2013\u0026mdash;2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.84,\u0026nbsp;2.82]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eFollow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026le; 28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.03, 1, 0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.61,\u0026nbsp;2.72]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt;\u0026nbsp;28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.81,\u0026nbsp;2.55]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMean age of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt;\u0026nbsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.26, 2, 0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.74,\u0026nbsp;2.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.70\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.67,\u0026nbsp;2.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.90\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.55,\u0026nbsp;2.61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.61, 2, 0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.61,\u0026nbsp;2.48]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.83,\u0026nbsp;2.71]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.82\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.10,\u0026nbsp;5.05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eTACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e2129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e3.88, 1, 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.56,\u0026nbsp;2.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.02,\u0026nbsp;3.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.65\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eQoL\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eAll RCTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.08,\u0026nbsp;4.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e11.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eⅡ-Ⅳ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.04, 1, 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.88,\u0026nbsp;5.49]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.71,\u0026nbsp;5.30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.92,1, 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.17,\u0026nbsp;5.23]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e11.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.59,\u0026nbsp;5.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eADI dosage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.60\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.26, 1, 0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.46,\u0026nbsp;5.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt;\u0026nbsp;50mg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.04,\u0026nbsp;5.46]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.40\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eNo. of author\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.57, 3, 0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.29,\u0026nbsp;5.51]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.70\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.67,\u0026nbsp;6.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.54,\u0026nbsp;6.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.80,\u0026nbsp;5.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRisk of bias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSome concerns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.29, 1, 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.80,\u0026nbsp;4.94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.85, 6.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eRandomization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eSpecific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e2.13, 2, 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.13, 9.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eMentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.58,\u0026nbsp;4.64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e8.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eNot mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.32,\u0026nbsp;7.42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003ePublication year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2003-2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.49, 1, 0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.13,\u0026nbsp;5.09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e11.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e2013-2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[1.40,\u0026nbsp;6.42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eFollow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026le; 28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.26, 1, 0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.21,\u0026nbsp;5.56]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 28d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.08,\u0026nbsp;5.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e10.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMean age of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026gt; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.85, 2, 0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.51,\u0026nbsp;5.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026lt; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.87,\u0026nbsp;7.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n 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style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.50,\u0026nbsp;5.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eMale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003e\u0026ge; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e0.18, 1, 0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.92,\u0026nbsp;5.01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n 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style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eTACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e1401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e2.13, 1, 0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[2.78,\u0026nbsp;4.63]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e9.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9677%;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.3871%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.8602%;\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e5.66\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.70968%;\"\u003e\n \u003cp\u003e[3.25,\u0026nbsp;9.87]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.5914%;\"\u003e\n \u003cp\u003e6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.49462%;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.63441%;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds ratio; CI: Confidence interval; het: Heterogeneity; DCR: Disease control rate; RCT: Randomized controlled trial; TNM: Tumor Node Metastasis; NR: not report; TACE: transcatheter arterial chemoembolization; ADI: AiDi Injection; ORR: Objective response rate; SAEs: Serious adverse events; QoL: Quality of life.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"primary liver cancer, randomized controlled trials, systematic review, AiDi injection, efficacy, safety","lastPublishedDoi":"10.21203/rs.3.rs-7287067/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7287067/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cdiv id=\"ASec1\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eBackground\u003c/div\u003e\u003cp\u003eAiDi injection (ADI) has been widely used for primary liver cancer (PLC) and numerous clinical trials in China have been conducted to compare the efficacy of ADI with other treatments for PLC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"ASec2\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eObjective\u003c/div\u003e\u003cp\u003eThis study aimed to conduct a systematic review and meta-analysis to comprehensively evaluate ADI for PLC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"ASec3\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eMethods\u003c/div\u003e\u003cp\u003ePubMed, Web of Science, the Cochrane Library, CNKI and WanFang Database were searched to select randomized controlled trials (RCTs) that evaluated ADI for PLC with outcomes including disease control rate (DCR), objective response rate (ORR), quality of life (QoL), serious adverse events (SAEs). The RoB2 tool was used to assess RCTs. Meta-analysis was performed to compute the overall effect sizes using odds ratio (OR) with 95% confidence intervals (CIs). Subgroup and sensitivity analyses, meta-regression, and publication bias were also conducted. The strength of evidence was assessed using with the GRADE method.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"ASec4\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eResults\u003c/div\u003e\u003cp\u003eThis study included 70 RCTs involving 5283 PLC patients. The overall RoB of RCTs was assessed as some concerns. The effect size of OR was 2.86 (95% CI [2.41, 3.40]) with statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) and insignificant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, P\u0026thinsp;=\u0026thinsp;0.69) on DCR. The effect sizes were significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) with insignificant heterogeneity (P\u0026thinsp;\u0026ge;\u0026thinsp;0.14) on ORR, QoL, and SAEs. Moreover, subgroup and sensitivity analyses, and meta-regression showed consistent results. Most publication bias analyses showed insignificant differences. The evidence strength was rated as moderate.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"ASec5\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eConclusion\u003c/div\u003e\u003cp\u003eADI combination therapy demonstrated significant efficacy and safety in PLC patients. Nevertheless, further strong evidence through more high-quality RCTs is warranted to support findings.\u003c/p\u003e\u003c/div\u003e","manuscriptTitle":"Efficacy and safety of AiDi injection in treating primary liver cancer: A systematic review on 70 randomized controlled trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 10:15:24","doi":"10.21203/rs.3.rs-7287067/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-24T12:58:58+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"253673836584006720259406430806699891637","date":"2025-10-24T05:21:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T16:22:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334561368391342457842300180625251625199","date":"2025-10-21T00:37:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-06T19:41:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293493936137836462974643831318779605878","date":"2025-09-12T10:09:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-12T00:40:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T08:56:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-21T18:39:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-15T08:56:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-15T08:52:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a81c6e92-212f-4560-a7f4-b5a5b26722ba","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54850465,"name":"Biological sciences/Cancer"},{"id":54850466,"name":"Health sciences/Diseases"},{"id":54850467,"name":"Health sciences/Gastroenterology"},{"id":54850468,"name":"Health sciences/Medical research"},{"id":54850469,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-12-08T16:09:40+00:00","versionOfRecord":{"articleIdentity":"rs-7287067","link":"https://doi.org/10.1038/s41598-025-31271-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-05 15:58:06","publishedOnDateReadable":"December 5th, 2025"},"versionCreatedAt":"2025-09-22 10:15:24","video":"","vorDoi":"10.1038/s41598-025-31271-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-31271-z","workflowStages":[]},"version":"v1","identity":"rs-7287067","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7287067","identity":"rs-7287067","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}