Abstract
Background
The aim of this study was to investigate the association between cyclooxygenase-2 (COX-2) rs689466 (–1195 G>A) polymorphism and susceptibility to head and neck squamous cell carcinoma (HNSCC) by performing a meta-analysis.
Material/Methods
PubMed and Embase were searched for relevant cohort and case-control studies up to 13 March 2015. After data extraction and methodological quality assessment for eligible studies, the overall, subgroup, sensitivity, and cumulative meta-analyses were conducted using the Comprehensive Meta-Analysis software (version 2.2).
Results
Finally, 5 case-control studies involving 1564 HNSCC patients and 2346 healthy controls were included. For overall population, the results of 3 genetic models showed significant association, while the other 2 presented negative association [A vs. G: OR=0.97–1.09, 95%CI=0.97–1.09; AA vs. GG: OR=1.26, 95%CI=1.01–1.57; AA vs. GA: OR=1.21, 95%CI=1.01–1.45); AA vs. (GG+GA): OR=1.20, 95%CI=1.01–1.43; (AA+GA) vs. GG: OR=0.98, 95%CI=0.84–1.15]. Publication bias was not assessed due to the limited number of included studies.
Conclusions
This meta-analysis indicated that COX-2 rs689466 polymorphism might be associated with increased susceptibility to HNSCC. We also suggest performing more relevant studies in order to enlarge the sample size and obtain more precise results.
MeSH Keywords: Cyclooxygenase 2; Head and Neck Neoplasms; Meta-Analysis; Mouth Neoplasms; Polymorphism, Genetic
Background
Head and neck squamous cell carcinoma (HNSCC), mainly including the oral cavity squamous cell carcinoma (OSCC), oropharynx squamous cell carcinoma (OPSCC), pharynx squamous cell carcinoma (PSCC), and larynx squamous cell carcinoma (LSCC), is one of the most common cancers worldwide [1,2]. Considering the special location and great importance of the head and neck, seeking risk factors associated with HNSCC susceptibility and developing effective strategies to prevent this disease is a significant task. Human papillomavirus (HPV) infection, tooth loss, cigarette smoking, periodontal diseases, and alcohol drinking are commonly accepted risk factors of developing HNSCC [2–7]. Genetic factors also play important roles during the onset and development of HNSCC [8–10], and the cyclooxygenase-2 (COX-2) gene has been reported to be one of those relevant genes [11].
The human COX-2 gene, is 8.3 kb in size, also named the prostaglandin-endoperoxide synthase 2 (PTGS2), is located on chromosome 1q25.2-q25.3; it contains 10 exons and 9 introns and produces an mRNA of 4.6 kb [12]. Published meta-analyses indicated the COX-2 gene plays a vital role in tumor development, metastasis, and inflammation [13–17]. Enhanced biosynthesis of inflammation-promoting prostaglandins via Cox-2 catalysis, resulting in elevated DNA damage, may be the mechanism of the carcinogenesis effects of this gene. [18] The rs689466 polymorphism (–1195 G>A) is one of the most widely investigated Cox-2 polymorphisms. In 2008, a case-control study including 377 OSCC patients and 442 healthy controls found COX-2–1195 G>A polymorphism was a potential genetic risk of OSCC [19]. However, this positive result was not supported in the following case-control study by Peters et al. in 2009 [20]. This situation with different studies showing controversial results is less convincing; therefore, a meta-analysis was necessary to pool evidence for providing a more precise and less uncertain result [21]. Therefore, we conducted this meta-analysis to investigate the association between COX-2 rs689466 polymorphism and HNSCC susceptibility.
Material and Methods
We carried out this meta-analysis according to the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) statement [22].
Eligible criteria
A case-control or cohort study would be included if it met all the following criteria: (1) the theme was the association between COX-2 rs689466 polymorphism and human HNSCC susceptibility; (2) the patients were identified as HNSCC, OPSCC, OSCC, PSCC, or LSCC pathologically; (3) the controls were healthy volunteers or cancer-free population; (4) the frequency of genotypes in case and control groups were reported or could be calculated from reported data; (5) the publication language was English or Chinese, and the full text could be obtained.
Search strategy
A comprehensive electronic database search in PubMed and Embase was conducted up to 13 March, 2015 by 2 authors independently. The search term was as follows: [(carcinoma OR cancer OR tumor OR neoplasm) AND (head and neck OR oral OR pharyngeal OR oropharynx OR laryngeal OR laryngopharyngeal OR mouth OR tongue) AND (polymorphism OR mutation OR variant OR haplotype) AND (cyclooxygenase-2 OR COX-2 OR PTGs2)]. Moreover, the bibliographies of recent reviews and included studies were retrieved manually.
Data extraction
Two authors independently selected studies and then extracted data from included studies, any disagreements were resolved by discussion. The extracted data were as follow: surname of the first author, publication year, study locations (country), ethnicity of included population, source of control, smoking status, alcohol consumption, sample sizes, frequency of genotype distribution, HPV status, genotyping method, and Hardy-Weinberg equilibrium (HWE) for controls (p>0.05 of control was considered as in accordance with HWE).
Methodological quality assessment
Two authors independently assessed the study methodological quality using the Newcastle-Ottawa scale (NOS) [21,23–26], and the detailed items was clearly described by Leng et al. [27].
Data analysis
The odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were chosen as effect size. The A vs. G, AA vs. GG, AA vs. GA, AA vs. (GG+GA), and (AA+GA) vs. GG genetic models were used to present the strength of associations between COX-2 rs689466 polymorphism and HNSCC susceptibility. Firstly, the Cochran’s Q and I2 test [28] were used to explore the heterogeneity among the involved studies. An I2 no more than 50% along with corresponding p>0.10 indicates an acceptable heterogeneity and the fixed-effects model was used; otherwise, we used the random-effects model. We performed subgroup analyses according to ethnicity, smoking status, alcohol consumption, and type of study design. Since all included studies conformed to HWE and no HPV-positive patients were involved, no subgroup analysis according to HWE and HPV status was performed. The sensitivity analysis was also carried out to investigate the robustness of overall results. The cumulative meta-analysis was conducted to observe the trend with sample size enlarged. Because only 5 studies were included in our analyses, publication bias was not assessed. All analyses were carried out using the Comprehensive Meta-Analysis software (version 2.2) [23].
Results
Study characteristics
The electronic searching identified 44 studies from PubMed and 296 studies from Embase, and finally 5 case-control studies involving 1564 HNSCC patients and 2346 healthy controls were included [19,20,29–31]. Figure 1 shows the selection process.
Figure 1.
Flow chart from identification of eligible studies to final inclusion.
Of them, 3 studies were conducted in China [19,30,31], 1 in the Netherlands [20], and 1 in India [29]; 2 studies exclusively included OSCC patients [19,29], and 1 study [31] reported data for all HNSCC patients, OSCC, and LSCC patients respectively; 1 study [29] focused on smokers and the smoking status of the other 4 studies were mixed; 1 study did not report the alcohol consumption, and the other 4 studies were mixed. All studies conformed to HWE and involved no HPV patients. The methodological quality of all the included studies was high, and the score ranged from 7 to 8. Table 1 presents the main characteristics.
Table 1.
Characteristics of included studies in the meta-analysis.
| Study | Country (Ethnicity) | Form of disease | Sample size (Ca/Co) | Genotyping method | Genotype distribution (Ca/Co) | P for HWE | Smoking status | Alcohol status | NOS | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| GG | GA | AA | |||||||||
| Chiang 2008 | China (Asian) | OSCC | 368/441 | PCR-RFLP | 80/114 | 187/235 | 101/92 | 0.17 | Mixed | Mixed | 7 |
| Peters 2009 | Netherlands (Caucasian) | HNSCC | 431/438 | PCR | 275/260 | 134/163 | 22/15 | 0.08 | Mixed | Mixed | 7 |
| Mittal 2010 | India (Asian) | OSCC | 193/137 | PCR-RFLP | 3/5 | 57/32 | 133/100 | 0.24 | Smokers | Unclear | 8 |
| Chang 2013 | China (Asian) | HNSCC | 313/295 | Taqman | 93/90 | 146/148 | 74/57 | 0.78 | Mixed | Mixed | 8 |
| Niu 2014 | China (Asian) | HSNCC | 259/1035 | Taqman | 61/222 | 126/542 | 72/271 | 0.11 | Mixed | Mixed | 7 |
| OSCC | 149/1035 | Taqman | 44/222 | 80/542 | 25/271 | 0.11 | Mixed | Mixed | |||
| LSCC | 90/1035 | Taqman | 17/222 | 46/542 | 27/271 | 0.11 | Mixed | Mixed | |||
Ca/Co – Case/Control; HNSCC – head and neck squamous cell carcinoma; OSCC – oral cavity squamous cell carcinoma; LSCC – larynx squamous cell carcinoma; HWE – Hardy-Weinberg equilibrium; Mixed – smokers and non-smokers; NOS – Newcastle-Ottawa scale.
Meta-analysis
Table 2 presents results of overall and subgroup analyses. Overall, the meta-analysis showed significantly increased risk in 3 genetic models: AA vs. GG (OR=1.26, 95%CI=1.01–1.57, Figure 2), AA vs. GA (OR=1.21, 95%CI=1.01–1.45), AA vs. (GG+GA) (OR=1.20, 95%CI=1.01–1.43). When stratified by smoking status, a significantly increased risk was also found in these 3 genetic models (AA vs. GG, AA vs. GA, and AA vs. (GG+GA)) in mixed populations. When stratified by ethnicity, only the allele genetic model showed an increased risk, with marginal significance in Asians population (OR=1.12, 95%CI=1.00–1.25). The other results of overall and subgroup population all revealed non-significant association.
Table 2.
Results of overall and subgroups analyses of pooled ORs and 95% CIs.
| Overall and subgroups | No. of studies | Heterogeneity (I2/p) | Effect model | OR(95%CI) |
|---|---|---|---|---|
| A vs. G | ||||
| Overall | 5 | 7%/0.37 | Fixed | 1.08 (0.97–1.09) |
| Smoker (mixed) | 4 | 21%/0.28 | Fixed | 1.09 (0.98–1.21) |
| Smoker (yes) | 1 | NA | NA | 0.93 (0.61–1.42) |
| Asians | 4 | 0%/0.56 | Fixed | 1.12 (1.00–1.25) |
| Caucasian | 1 | NA | NA | 0.92 (0.73–1.16) |
| OSCC | 3 | 80%/<0.10 | Random | 1.01 (0.87–1.16) |
| LSCC | 1 | NA | NA | 0.96 (0.72–1.32) |
| AA vs. GG | ||||
| Overall | 5 | 0%/0.46 | Fixed | 1.26 (1.01–1.57) |
| Smoker (mixed) | 4 | 0%/0.39 | Fixed | 1.24 (1.00–1.55) |
| Smoker (yes) | 1 | NA | NA | 2.22 (0.52–2.49) |
| Asians | 4 | 14%/0.32 | Fixed | 1.25 (0.99–1.57) |
| Caucasian | 1 | NA | NA | 1.39 (0.70–2.73) |
| OSCC | 3 | 86%/<0.10 | Random | 1.07 (0.40–2.86) |
| LSCC | 1 | NA | NA | 1.30 (0.69–2.45) |
| AA vs. GA | ||||
| Overall | 5 | 28%/0.23 | Fixed | 1.21 (1.01–1.45) |
| Smoker (mixed) | 4 | 0%/0.68 | Fixed | 1.30 (1.07–1.58) |
| Smoker (yes) | 1 | NA | NA | 0.75 (0.45–1.24) |
| Asians | 4 | 30%/0.23 | Fixed | 1.17 (0.97–1.42) |
| Caucasian | 1 | NA | NA | 1.78 (0.89–3.57) |
| OSCC | 3 | 76%/<0.10 | Random | 0.88 (0.53–1.48) |
| LSCC | 1 | NA | NA | 1.17 (0.71–1.93) |
| AA vs. (GG+GA) | ||||
| Overall | 5 | 12%/0.34 | Fixed | 1.20 (1.01–1.43) |
| Smoker (mixed) | 4 | 0%/0.61 | Fixed | 1.27 (1.06–1.53) |
| Smoker (yes) | 1 | NA | NA | 0.82 (0.51–1.33) |
| Asians | 4 | 26%/0.26 | Fixed | 1.18 (0.99–1.41) |
| Caucasian | 1 | NA | NA | 1.52 (0.78–2.96) |
| OSCC | 3 | 83%/<0.10 | Random | 0.89 (0.50–1.58) |
| LSCC | 1 | NA | NA | 1.21 (0.75–1.94) |
| (AA+GA) vs. GG | ||||
| Overall | 5 | 28%/0.23 | Fixed | 0.98 (0.84–1.15) |
| Smoker (mixed) | 4 | 27%/0.25 | Fixed | 0.97 (0.83–1.14) |
| Smoker (yes) | 1 | NA | NA | 2.40 (0.56–10.21) |
| Asians | 4 | 13%/0.33 | Fixed | 1.07 (0.88–1.29) |
| Caucasian | 1 | NA | NA | 0.83 (0.63–1.09) |
| OSCC | 3 | 75%/<0.10 | Random | 1.03 (0.57–1.88) |
| LSCC | 1 | NA | NA | 1.17 (0.68–2.03) |
OSCC – oral cavity squamous cell carcinoma; LSCC – larynx squamous cell carcinoma; NA – not available.
Figure 2.
Forest plot for AA vs. GG comparison (fixed effect model).
Because all included studies conformed to HWE and involved no HPV-positive patients, no subgroup analysis according to HWE or HPV status was performed. When omitting each included study sequentially, the results of sensitivity analyses all showed the overall results were unstable (Figure 3 for AA vs. GG). The results of cumulative analyses by publication year also failed to detect a significant change (Figure 4 for AA vs. GG).
Figure 3.
Sensitivity forest plot for AA vs. GG comparison (fixed effect model).
Figure 4.
Cumulative forest plot for AA vs. GG comparison (fixed effect model).
Publication bias
Because only 5 case-control studies were included [32], publication bias was not assessed.
Discussion
Head and neck carcinogenesis is a complex and multi-step process, with which dysregulation involving many oncogenes and/or tumor suppressor genes have been considered as associated [33]. COX-2 is considered to be relevant in inflammation and cancer via being upregulated by cytokines, growth factors, and tumor promoters. Various nuclear regulatory factors such as NF-κB and c-myb are located in the promoter region of COX-2, hence its expression is transcriptionally regulated [29,34]. Different published studies reported consistent results that COX-2 is overexpressed in multiple cancers, including HNSCC and premalignant lesions [35–37], suggesting its important role in tumor development and dissemination [38]. There are some studies evaluating the effects of single-nucleotide polymorphism (SNPs) in COX-2 gene on the predisposition of HNSCC. In this meta-analysis, we investigated the association between COX-2 rs689466 polymorphism and HNSCC susceptibility based on 5 case-control studies. All studies were confirmed to be consistent with HWE and the results of 5 genetic models showed that COX-2 rs689466 polymorphism might be associated with increased susceptibility of HNSCC; however, the ORs were not large and not all the genetic models showed significant association.
As smoking and alcohol consumption are well accepted risk factors of HNSCC [5], we extracted the smoking and alcohol status of included population. Because the alcohol consumption was unclear in 1 study and mixed in the other 4 studies, we only conducted a subgroup analysis of smoking status. Only 1 study investigated exclusively the smokers [29], and the other 4 studies both included smokers and non-smokers but did not reported relevant data separately; hence, we did not extract more information about smoking status from included studies. The results of the mixed smoking status subgroup were similar to overall population, while a non-significant association was shown for smokers. We also considered the influence of different ethnicities and performed a subgroup analysis according to the ethnicity; the results showed a non-significant increasing trend for both Asians and whites. The subgroup analysis based on different cancer sites was also considered in this meta-analysis and yielded similar results as ethnicity for OSCC and LSCC.
For the overall population, the heterogeneity of all genetic models was good and only the fixed-effects model was used to pool data. Acceptable heterogeneity was revealed in all the subgroup analyses except for the OSCC subgroup. The reason why obvious heterogeneity emerged in the OSCC group is hard to explain with the obtained information, and real statistical heterogeneity is a possible explanation. Moreover, the small sample size may have been a source of heterogeneity, since only 5 case-control studies involving 1564 HNSCC patients and 2346 healthy controls were included. Other potential sources include mixed smoking status, different detection technology, or concomitant diseases, which need to be examined in further research.
Our study is the first meta-analysis on this topic, and more details should be investigated in the future. Firstly, many confirmed risk factors, such as periodontal diseases, tooth loss, and HPV infection [3–7], of HNSCC are necessary to report in the study and should be adjusted so we can judge whether the polymorphism is a risk factor or just a marker. Secondly, only 5 studies were included and the results were not consistent in the 5 genetic models, and this may indicate that the sample size was too small and further relevant studies are needed. The results of sensitivity and cumulative analyses also support that more studies are needed. Thirdly, if the COX-2 rs689466 polymorphism is a risk factor for HNSCC, the mechanism needs to be explored. If the COX-2 rs689466 polymorphism is only a marker of other risk factors, the role that this polymorphism plays and the associated risk factors should be determined.
Some limitations in this meta-analysis should be pointed out. Obviously, the sample size is small. Although we did our best to search for more eligible studies, only 4 single-center and 1 multiple-center case-control studies met the inclusion criteria. The small sample size might influence the statistic power and provide a biased result. Because we lacked enough studies, the publication bias was not assessed. Hence, we could not examine the existence of publication bias through qualitative or quantitative detection. Due to the restricted accessibility and language barriers, we did not search databases in other languages (e.g. Russian, Japanese, French, or German) for relevant studies; accordingly, certain eligible studies were possibly not included in this work. Secondly, since the included population consisted of Asians and whites only, the result of this meta-analysis might not be reasonably extended to other ethnicities. As we know, different ethnicity may possess its own genetic background by which the onset, development, or outcome of certain diseases could be influenced. Thirdly, the results of five genetic models did not converge and the sensitivity analyses indicated unstable results. This might be partially explained by the absence of sufficient sample size, on which a conclusive result depends. On the other hand, this also suggests relevant studies should be conducted in the future.
Conclusions
Our meta-analysis indicated that COX-2 rs689466 polymorphism might be associated with increased susceptibility to HNSCC. In the future, 3 points should be taken into consideration: relevant studies reporting more details should be performed for further investigation; whether COX-2 rs689466 polymorphism is a risk factor or just a marker needs to be verified; and the underlying mechanisms of COX-2 rs689466 polymorphism’s effects on HNSCC onset, development, or outcome need to be investigated.
Footnotes
Conflict of interest
The authors declare that they have no conflict of interest.
Source of support: This research was supported (in part) by the Nature Science Foundation of Hubei Province (2012FFB03902) and the Evidence-based Medicine Nursery Fund of Taihe Hospital (EBM2014006) without commercial or not-for-profit sectors. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding was received for this study
References
- 1.Galli P, Cadoni G, Volante M, et al. A case-control study on the combined effects of p53 and p73 polymorphisms on head and neck cancer risk in an Italian population. BMC Cancer. 2009;9:137. doi: 10.1186/1471-2407-9-137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Zeng XT, Leng WD, Zhang C, et al. Meta-analysis on the association between toothbrushing and head and neck cancer. Oral Oncol. 2015;51:446–51. doi: 10.1016/j.oraloncology.2015.02.095. [DOI] [PubMed] [Google Scholar]
- 3.Zygogianni AG, Kyrgias G, Karakitsos P, et al. Oral squamous cell cancer: Early detection and the role of alcohol and smoking. Head and Neck Oncology. 2011;3:2. doi: 10.1186/1758-3284-3-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Abogunrin S, Di Tanna GL, Keeping S, et al. Prevalence of human papillomavirus in head and neck cancers in European populations: a meta-analysis. BMC Cancer. 2014;14:968. doi: 10.1186/1471-2407-14-968. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Galbiatti AL, Padovani-Junior JA, Maniglia JV, et al. Head and neck cancer: causes, prevention and treatment. Braz J Otorhinolaryngol. 2013;79:239–47. doi: 10.5935/1808-8694.20130041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Zeng XT, Deng AP, Li C, et al. Periodontal disease and risk of head and neck cancer: a meta-analysis of observational studies. PLoS One. 2013;8:e79017. doi: 10.1371/journal.pone.0079017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Zeng XT, Luo W, Huang W, et al. Tooth loss and head and neck cancer: a meta-analysis of observational studies. PLoS One. 2013;8:e79074. doi: 10.1371/journal.pone.0079074. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Taniyama Y, Takeuchi S, Kuroda Y. Genetic polymorphisms and oral cancer. J UOEH. 2010;32:221–36. doi: 10.7888/juoeh.32.221. [DOI] [PubMed] [Google Scholar]
- 9.Verisqa F, Johan C. Association between gene polymorphisms with oral squamous cell carcinoma risk and survival in multiple ethnicities: A systematic review. International Journal of Oral and Maxillofacial Surgery. 2013;42:1283. [Google Scholar]
- 10.Brunotto M, Zarate AM, Bono A, et al. Risk genes in head and neck cancer: a systematic review and meta-analysis of last 5 years. Oral Oncol. 2014;50:178–88. doi: 10.1016/j.oraloncology.2013.12.007. [DOI] [PubMed] [Google Scholar]
- 11.Rakesh N, Nagesh KS, Iyengar AR, Patil DB. Inflammation in oral cancer and role of COX-2: A review. Research Journal of Pharmaceutical, Biological and Chemical Sciences. 2014;5:319–29. [Google Scholar]
- 12.Fritsche E, Baek SJ, King LM, et al. Functional characterization of cyclooxygenase-2 polymorphisms. J Pharmacol Exp Ther. 2001;299:468–76. [PubMed] [Google Scholar]
- 13.Jiang L, Weng H, Chen MY, et al. Association between cyclooxygenase-2 gene polymorphisms and risk of periodontitis: a meta-analysis involving 5653 individuals. Mol Biol Rep. 2014;41:4795–801. doi: 10.1007/s11033-014-3350-z. [DOI] [PubMed] [Google Scholar]
- 14.Dai ZJ, Shao YP, Ma XB, et al. Association of the three common SNPs of cyclooxygenase-2 gene (rs20417, rs689466, and rs5275) with the susceptibility of breast cancer: an updated meta-analysis involving 34,590 subjects. Dis Markers. 2014;2014:484729. doi: 10.1155/2014/484729. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wang XF, Huang MZ, Zhang XW, et al. COX-2-765G>C polymorphism increases the risk of cancer: a meta-analysis. PLoS One. 2013;8:e73213. doi: 10.1371/journal.pone.0073213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Tang Z, Nie ZL, Pan Y, et al. The Cox-2–1195 G > A polymorphism and cancer risk: A meta-analysis of 25 case-control studies. Mutagenesis. 2011;26:729–34. doi: 10.1093/mutage/ger040. [DOI] [PubMed] [Google Scholar]
- 17.Zhu W, Wei BB, Shan X, Liu P. −765G>C and 8473T>C polymorphisms of COX-2 and cancer risk: A meta-analysis based on 33 case-control studies. Mol Biol Rep. 2010;37:277–88. doi: 10.1007/s11033-009-9685-1. [DOI] [PubMed] [Google Scholar]
- 18.Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420:860–67. doi: 10.1038/nature01322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Chiang SL, Chen PH, Lee CH, et al. Up-regulation of inflammatory signalings by areca nut extract and role of cyclooxygenase-2–1195G>a polymorphism reveal risk of oral cancer. Cancer Res. 2008;68:8489–98. doi: 10.1158/0008-5472.CAN-08-0823. [DOI] [PubMed] [Google Scholar]
- 20.Peters WH, Lacko M, Te Morsche RH, et al. COX-2 polymorphisms and the risk for head and neck cancer in white patients. Head Neck. 2009;31:938–43. doi: 10.1002/hed.21058. [DOI] [PubMed] [Google Scholar]
- 21.Zeng X, Zhang Y, Kwong JS, et al. The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline: a systematic review. J Evid Based Med. 2015;8:2–10. doi: 10.1111/jebm.12141. [DOI] [PubMed] [Google Scholar]
- 22.Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12. doi: 10.1001/jama.283.15.2008. [DOI] [PubMed] [Google Scholar]
- 23.Yan Y, Weng H, Shen ZH, et al. Association between interleukin-4 gene –590 c/t, –33 c/t, and 70-base-pair polymorphisms and periodontitis susceptibility: a meta-analysis. J Periodontol. 2014;85:e354–62. doi: 10.1902/jop.2014.140317. [DOI] [PubMed] [Google Scholar]
- 24.Wu L, Wang Z, Zhu J, et al. Nut consumption and risk of cancer and type 2 diabetes: a systematic review and meta-analysis. Nutr Rev. 2015;73:409–25. doi: 10.1093/nutrit/nuv006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wu L, Zhu J, Prokop LJ, Murad MH. Pharmacologic therapy of diabetes and overall cancer risk and mortality: A meta-analysis of 265 studies. Sci Rep. 2015;5:10147. doi: 10.1038/srep10147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Wu L, Jiang Z, Li C, Shu M. Prediction of heart rate variability on cardiac sudden death in heart failure patients: A systematic review. Int J Cardiol. 2014;174:857–60. doi: 10.1016/j.ijcard.2014.04.176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Leng WD, He MN, Chen QL, et al. Vascular endothelial growth factor (VEGF) gene polymorphisms and risk of head and neck cancer: a meta-analysis involving 2,444 individuals. Mol Biol Rep. 2013;40:5987–92. doi: 10.1007/s11033-013-2708-y. [DOI] [PubMed] [Google Scholar]
- 28.Coory MD. Comment on: Heterogeneity in meta-analysis should be expected and appropriately quantified. Int J Epidemiol. 2010;39:932. doi: 10.1093/ije/dyp157. ; author reply 933. [DOI] [PubMed] [Google Scholar]
- 29.Mittal M, Kapoor V, Mohanti BK, Das SN. Functional variants of COX-2 and risk of tobacco-related oral squamous cell carcinoma in high-risk Asian Indians. Oral Oncol. 2010;46:622–26. doi: 10.1016/j.oraloncology.2010.06.002. [DOI] [PubMed] [Google Scholar]
- 30.Chang JS, Lo HI, Wong TY, et al. Investigating the association between oral hygiene and head and neck cancer. Oral Oncol. 2013;49:1010–17. doi: 10.1016/j.oraloncology.2013.07.004. [DOI] [PubMed] [Google Scholar]
- 31.Niu Y, Yuan H, Shen M, et al. Association between cyclooxygenase-2 gene polymorphisms and head and neck squamous cell carcinoma risk. J Craniofac Surg. 2014;25:333–37. doi: 10.1097/SCS.0000000000000372. [DOI] [PubMed] [Google Scholar]
- 32.Green S. Cochrane handbook for systematic reviews of interventions version 5.1. 0 [updated March 2011] The Cochrane Collaboration; 2011. [Google Scholar]
- 33.Tsai WC, Tsai ST, Ko JY, et al. The mRNA profile of genes in betel quid chewing oral cancer patients. Oral Oncol. 2004;40:418–26. doi: 10.1016/j.oraloncology.2003.09.015. [DOI] [PubMed] [Google Scholar]
- 34.Gasparini G, Longo R, Sarmiento R, Morabito A. Inhibitors of cyclo-oxygenase 2: a new class of anticancer agents? Lancet Oncol. 2003;4:605–15. doi: 10.1016/s1470-2045(03)01220-8. [DOI] [PubMed] [Google Scholar]
- 35.Pandey M, Prakash O, Santhi WS, et al. Overexpression of COX-2 gene in oral cancer is independent of stage of disease and degree of differentiation. Int J Oral Maxillofac Surg. 2008;37:379–83. doi: 10.1016/j.ijom.2008.01.004. [DOI] [PubMed] [Google Scholar]
- 36.Wang Z. The role of COX-2 in oral cancer development, and chemoprevention/treatment of oral cancer by selective COX-2 inhibitors. Curr Pharm Des. 2005;11:1771–77. doi: 10.2174/1381612053764887. [DOI] [PubMed] [Google Scholar]
- 37.Banerjee AG, Gopalakrishnan VK, Bhattacharya I, Vishwanatha JK. Deregulated cyclooxygenase-2 expression in oral premalignant tissues. Mol Cancer Ther. 2002;1:1265–71. [PubMed] [Google Scholar]
- 38.Kapoor V, Singh A, Dey S, et al. Circulating cycloxygenase-2 in patients with tobacco-related intraoral squamous cell carcinoma and evaluation of its peptide inhibitors as potential antitumor agent. J Canc Res Clin Oncol. 2010;136:1795–804. doi: 10.1007/s00432-010-0837-4. [DOI] [PMC free article] [PubMed] [Google Scholar]