The neutrophil-lymphocyte-ratio, platelet-lymphocyte-ratio, and monocyte-lymphocyte-ratio have been explored as a simple, inexpensive, and effective method for cancer prognosis. However, there are no studies that have investigated the comparative utility of these markers, in multiple cancers.The preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) guidelines were used to design this meta-analysis protocol. The final study will also be conducted under the PRISMA guidelines for systematic reviews and meta-analyses. The core bibliographic database search will be carried out by 2 reviewers working individually, with each conducting an initial screening based on titles and abstracts. The shortlisted articles will be selected for review and quantitative analysis, based on predefined inclusion and exclusion criteria. Study characteristics, relevant clinicopathological characteristics, and statistical data required for meta-analysis  will be extracted and compiled into a MS Excel datasheet. Meta-analysis will be performed, using a random-effects model, and the results (pooled HR and 95% CI) will be presented in the form of a forest plot. Publication bias will also be assessed by use of Egger bias indicator test and funnel plot symmetry. If statistical data from included studies is insufficient, a qualitative literature review will be pursued.PROSPERO registration: PROSPERO CRD42019121008. Inflammation and inflammatory markers, when associated with cancer have been shown to lead to a worse prognosis. Therefore, assessing the magnitude of inflammation in cancers may allow us to use it as a clinical prognostic marker. This magnitude of inflammation can be captured by the measurement of the neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and monocyte-lymphocyte ratio (MLR). As systemic alteration of inflammation leads to alteration in the peripheral blood leukocytes, NLR can act as a proxy measurement of the degree of inflammation in cancers.,5 Similarly, platelets release pro-inflammatory mediators, such as cytokines and chemokines, which exacerbate the inflammatory microenvironment in tumors, making PLR another viable measure of inflammation.,7 Monocytes have also been observed to have a key role in inflammation, also having been implicated in many inflammatory diseases, including atherosclerosis.Tumor microenvironment plays a critical role in tumorigenesis and cancer cell growth. Current methods for cancer prognosis in patients involves the use of molecular markers ,,11 which require complex and expensive assays for measurement and quantification ,13, while also generating a greater degree of patient discomfort (biopsy). Therefore, a great deal of research interest has been directed towards the use of PLR, NLR, and MLR as biomarkers for cancer prognosis.The measurement of NLR, PLR, and MLR is simple, rapid, and inexpensive, while simultaneously being associated with little to no patient discomfort, .,15 This abundance of literature has also led to the publication of multiple systematic review and meta-analysis studies regarding this topic.,17 However, no systematic review or meta-analysis study published till-date, has investigated;Multiple clinical studies have explored the use of PLR, NLR, and MLR, not only in cancers, but also as preoperative prognostic biomarkers.(1)The prognostic efficacy of PLR, NLR, and MLR in comparison to each other, with regards to cancer,(2)The difference in prognostic efficacy of PLR, NLR, and MLR, across various types of cancers. Similarly, Zhu et al focused on multiple inflammatory markers, with emphasis on PLR and NLR, but limited their study to ovarian cancer, while Zhang et al limited their analysis to colorectal cancer.Previous systematic-review and meta-analysis studies have only focused on a single cancer type, with no study conducting a comparative analysis of PLR, NLR, and MLR in cancer. Mellor et al recently published a systematic review and meta-analysis study, including all cancer types, but only focusing on NLR alone as the prognostic marker of choice.This proposed systematic review and meta-analysis study intends to amend this existing knowledge gap, and provide a better understanding of the utility of PLR, NLR, and MLR as prognostic markers in cancer, while simultaneously attempting to highlight the best marker , with respect to each type of cancer.22.1,21 The search strategy is designed to be expansive and exhaustive, with the bibliographic databases, EMBASE, MEDLINE, Science Direct, Scopus, and Web of Science, acting as sources of published literature. The literature search will be limited to the past decade (1998–2018) to maintain the relevance of the study to current scope of research regarding cancer prognosis. The search strategy will also allow for extraction of relevant literature from reference lists of shortlisted articles to further increase the robustness of the search. The search will be carried out based on “search strings” designed from subject-relevant “keywords”  guidelines.2.2After initial screening, the full-texts of articles will be subject to selection based on the following inclusion and exclusion criteria. The inclusion and exclusion criteria are based on previous similar systematic review and meta-analysis studies, and have been adopted to the specifications of this current proposed study.2.3(1)The studies must discuss the survival outcome of cancer patients based on PLR, NLR, and MLR levels.(2)The survival outcome must be presented in the form of hazard ratios (HR) and 95% confidence intervals (CI).(3)The survival outcome must be presented in the form of Kaplan–Meier (KM) curves, along with patient cohort information, for each treatment arm represented in the KM curves. .2.4(1)Conference abstracts, reviews, letters to the editor, and other nonclinical literature will not be considered for either systematic-review or meta-analyses.(2)Included studies must be clinical studies or involve patient samples. .(3)Unpublished, or non-peer-reviewed literature will be excluded.(4)Studies that do not focus on survival outcomes and prognosis aspects of PLR, NLR, and MLR in cancer patients.(5)If the sample size of each individual study if of low power, (sample size <10) they will be excluded.(6)There will be no limitations on the types of patients involved or clinicopathological parameters, as part of each included study. No limitations based on gender, age, ethnicity, location, follow-up period, duration of treatment or method of treatment will be placed, on the studies being included.2.5After selection of studies, based on the predefined inclusion and exclusion criteria, the full-texts will be subject to a data extraction process. Data extraction will follow a top-down approach, with the selected full-texts being combed for relevant patient and study data, individually, by 3 reviewers . A standardized, data extraction form will be prepared using Microsoft Excel, and will be utilized by the reviewers to extract the data. After individual data extraction has been performed by all 3 reviewers, the collected dataset of study information will be collated into a single database , which will be used to conduct further analyses.2.6The data items which will be extracted from the full-texts of studies, include;(1)Author names(2)Year of publication(3)Marker studied (4)Size of patient cohort(5)Diagnostic methods.(6)Follow-up period(7)Gender split of cohort(8)TNM staging split of cohort(9)Survival endpoint of each study (10)General features of each study After data extraction, all selected articles will be input into EndNote, to form a bibliographic database, to help in future data processing.2.7 This scale presents a “star system,” which assigns each of the 3 broad parameters of the study, 1 to 4 stars, in increasing order of quality. The 3 broad perspectives being assessed include, the selection of study groups in each individual study, the comparability of groups, and the ascertainment of exposure/outcome of interest for case–control/cohort studies.–27 This tool offers a simple and succinct, yet comprehensive analysis of the quality of each included study, and allows us to visualize it with clarity.The quality assessment of the studies was based on the standard, Newcastle–Ottawa scale for quality assessment of nonrandomized studies in meta-analysis.2.8 The software will be used to generate forest plots representing the meta-analysis results. The HR effect size metric, will be pooled across all included studies to determine the prognostic utility of PLR, NLR, and MLR in cancer. The HR effect size metric, indicates the survival probability of the patient cohort in each individual study, and the pooled HR will determine the likelihood of survival across all studies. The HRs of OS, DFS, and DSS, from each study, will be pooled separately, as each indicate a different type of survival endpoint. Similarly, meta-analysis on PLR, NLR, and MLR will be conducted individually, to assess the prognostic utility of each as a marker in cancer. The statistical significance  of PLR, NLR, and MLR, will also be assessed, based on the meta-analysis of HR values. Statistical significance allows us to verify whether the pooled results accept or reject the null hypothesis , while the effect size metric, informs us regarding the magnitude of the effect , which allows us to measure the prognostic utility of PLR, NLR, and MLR in cancer. All analyses will be carried out using the random-effects model, owing to the between study heterogeneity that is inherent when comparing individual studies and publications.The meta-analysis itself, will be conducted using the comprehensive meta-analysis software .2.9–34 The Higgins I2 statistic will be used as the primary method to determine heterogeneity, as it has a high power of detection of heterogeneity. However, I2 is not an infallible metric of heterogeneity, as it can provide biased results in small meta-analysis. Therefore for redundancy, we will use the Cochran’ Q and Tau2 parameters to assess heterogeneity alongside the I2 statistic.,38The heterogeneity between studies will be assessed based on 3 parameters.2.10The major meta-analysis subgroups for this study are studies which assessed PLR, NLR, and MLR. Analysis of other subgroups is contingent upon the availability of high-quality statistical data from included studies. If sufficient data is available, the 3 different survival endpoints, OS, DFS, and DSS will be analyzed separately, . For additional subgroup analysis, cancer type, location, ethnicity, and follow-up period will be considered.3,39–42 Publication bias is caused as a natural side effect of the publication process, wherein small studies and negative results are rarely published as part of peer-reviewed literature. Therefore, it is important to perform analysis of publication bias, so as to understand the results of the meta-analysis, in context to the bias existing within the study.,32Assessment of publication bias is integral for validating the results of any meta-analytic study. The symmetry of the funnel plot along the regression line will offer a simple method to assess the publication bias. The symmetry of the funnel plot is inversely related to the degree of publication bias in the study.Egger graphical bias indicator test will be used to construct a funnel plot.N test will allow us to adjust the funnel plot for small missing studies. This method allows for imputation of small studies in the plot, to more accurately assess the bias present.Orwin Fail-Safe  A positive result on this test indicates that the publication bias assessment is accurate.Begg and Mazumdar Rank Correlation test will be used to check correlation between ranks of effect sizes and their respective variances.4,47 Therefore, there is a requirement for a study that explores the overall picture of PLR, NLR, and MLR as prognostic markers, across all cancer types. The systematic review and meta-analysis format of study, in particular, allows us to pursue this goal, as the study is based on the collation of all published research in this field. This protocol will allow us to conduct such a study, in a precise manner while ensuring that the present research in this field is accurately represented in its results.PLR, NLR, and MLR have great potential for clinical use as prognostic markers in cancer. However, previous studies have been limited in scope to single cancer types. Furthermore, no study has performed any comparative assessment of the aforementioned markers. This limitation is not only observed in the individual clinical studies, but also in recent systematic reviews and meta-analysis.The tentative results of the proposed study should be able to inform us regarding the extent clinical significance of each prognostic marker in particular types of cancers. It will also indicate the areas, where further research is necessary, before clinical application of PLR, NLR, and MLR as cancer markers can be considered.Therefore, this study will have clinical relevance by suggesting the best markers across PLR, NLR, and MLR in each particular type of cancer, or even in the case of negative results, support and guide future research by highlighting areas where research is required for establishing PLR, NLR, and MLR as cancer markers.Cancer research is an ever-evolving field, and as more literature continues to be published, the protocol will also continue to be relevant in the future, as the study may require to be update to incorporate ongoing advancements in this field. Therefore, this protocol will allow for standardization of the process of conducting of an updated study, while also tangentially benefiting any future researchers conducting a systematic review or meta-analysis study regarding cancer biomarkers.4.1 A flow chart will be employed to outline the selection process .We would like to acknowledge the Meta-analysis concepts and applications workshop manual by Michael Borenstein for his guidelines on reporting Meta-analysis, subgroup analysis and publication bias, (RJ, CK, MRM, and SS contributed to the conceptualization, study design, search strategy, protocol development, and review by revising different versions. RJ, SB, SS, RN, KMG were involved in the supervision, ensured the absence of errors, and arbitrated in case of disagreement. CK, SS, MRM, KL engaged in the manuscript writing and analysis. All authors have read and approved the final version of the manuscript.Conceptualization: Chellan Kumarasamy, Madhav Madurantakam Royam, Rama Jayaraj.Data curation: Chellan Kumarasamy, Shanthi Sabarimurugan, Rama Jayaraj.Formal analysis: Chellan Kumarasamy, Shanthi Sabarimurugan, Madhav Madurantakam Royam, Rama Jayaraj.Investigation: Chellan Kumarasamy, Rama Jayaraj.Methodology: Chellan Kumarasamy, Kartik Lakhotiya, Suja Samiappan, Rama Jayaraj.Project administration: Shanthi Sabarimurugan, Gothandam K M, Rama Jayaraj.Resources: Madhav Madurantakam Royam, Suja Samiappan, Siddhartha Baxi, Rama Jayaraj.Software: Rama Jayaraj.Supervision: Siddhartha Baxi, Ramesh Nachimuthu, Gothandam K M, Rama Jayaraj.Validation: Kartik Lakhotiya, Ramesh Nachimuthu.Writing – original draft: Chellan Kumarasamy, Shanthi Sabarimurugan, Madhav Madurantakam Royam, Kartik Lakhotiya, Suja Samiappan, Ramesh Nachimuthu, Gothandam K M, Rama Jayaraj.Writing – review and editing: Chellan Kumarasamy, Shanthi Sabarimurugan, Madhav Madurantakam Royam, Kartik Lakhotiya, Suja Samiappan, Siddhartha Baxi, Ramesh Nachimuthu, Gothandam K M, Rama Jayaraj.Rama Jayaraj orcid: 0000-0002-2179-0510.


There is no published dose–response meta-analysis on the association between height and colorectal cancer risk (CRC) by sex and anatomical sub-site. We conducted a meta-analysis of prospective studies on the association between height and CRC risk with subgroup analysis and updated evidence on the association between body fatness and CRC risk.PubMed and several other databases were searched up to November 2016. A random effects model was used to calculate dose–response summary relative risks (RR’s).I² = 91%] per 5 cm increase in height, 1.02  per 5 kg increase in weight, 1.06  per 5 kg/m2 increase in BMI, 1.02  per 10 cm increase in waist circumference, 1.03  per 0.1 unit increase in waist to hip ratio. The significant association for height and CRC risk was similar in men and women. The significant association for BMI and CRC risk was stronger in men than in women.47 studies were included in the meta-analyses including 50,936 cases among 7,393,510 participants. The findings support the existing evidence regarding a positive association of height, general and abdominal body fatness and CRC risk. The summary RR were 1.04 [95% (CI)1.02–1.05, The positive association between height and risk of CRC suggests that life factors during childhood and early adulthood might play a role in CRC aetiology. Higher general and abdominal body fatness during adulthood are risk factors of CRC and these associations are stronger in men than in women.The online version of this article (doi:10.1007/s00394-017-1557-1) contains supplementary material, which is available to authorized users. Colorectal cancer (CRC) is the second most common cancer in women and the third most common cancer in men with 614,000 new cases diagnosed among women and 746,000 cases in men worldwide in 2012. It is a leading cause of cancer-related death, resulting in around 700,000 deaths worldwide [In the World Cancer Research Fund (WCRF)/American Institute for Cancer Research report from 2011, it was stated that the evidence that greater adult attained height increases colorectal cancer risk was convincing, based on the results from eight studies –11. In an = 24) [n = 13) [n = 6) [Adiposity is also an established risk factor for colorectal cancer, both as measured by body mass index (BMI) and waist circumference and waist-to-hip ratio. Although many studies have investigated the association between BMI and colorectal cancer , 14–40, n = 24) –51, wais[n = 13) , 53 and  [n = 6) , 49, 53 http://www.wcrf.org/int/research-we-fund/continuous-update-project-findings-reports/colorectal-bowel-cancer.PubMed, Embase, CABAbstracts, ISI Web of Science, BIOSIS, LILACS, Cochrane library, CINAHL, AMED, National Research Register and In Process Medline were searched for studies on anthropometric measures including BMI, height, weight, waist circumference and waist to hip ratio, and colorectal cancer risk up to December 2015. The specific search criteria and the review protocol can be found at: The search was restricted to cohort  studies which investigated the link between anthropometric measures and colorectal cancer risk and reported estimates of the relative risk (RR)  and 95% confidence intervals (CIs) for the exposures of interest , total number of cases and person years of follow-up. If there were multiple publications from the same study, the newest publication which included the largest number of cases was selected.From each publication, the following data were extracted: first author’s last name, year of publication, the study name, period of follow-up, sample size, age, sex, number of cases, country where the study was conducted, assessment method of exposure (self-reported vs measured), anthropometric measures, their quantities and their associated RRs and 95% CIs, and variables used in adjustment in the analysis. The update search and data extraction from January 2010 up to November 2016 was conducted by three authors  and was checked for accuracy by two authors .I² statistics were used to determine heterogeneity [I2 < 30%, moderate proportion by an I2 = 30–50%, and high proportion by an I2 ≥ 50%.The associations between height, weight, BMI, waist circumference and waist-to-hip ratio and colorectal, colon and rectal cancer were investigated using random effect models to calculate the summary RRs and 95% CIs to take into account heterogeneity across studies . Q and Iogeneity  and wereContinuous risk estimates were used directly when available in the articles, and for studies that only reported categorical data dose–response associations and 95% CIs were derived using generalized least-squares for trend estimation , which rThe mean or median values per category were used if provided in the articles, or the midpoint was calculated for studies that only reported a range by category. If the range of the highest or lowest category was open-ended, its width was assumed to be the same as the adjacent category. If the results were reported for men and women separately, they were combined using a fixed effects meta-analysis before being pooled with other studies.Small-study effects, such as publication bias, were assessed using funnel plots and Egger’s test .A potential nonlinear dose–response association between anthropometric measures and colorectal cancer risk was assessed by calculating restricted cubic splines for each study with more than three categories of exposure, using three fixed knots at 10, 50, and 90% through the total distribution of the reported measurements, and combined them using multivariate meta-analysis. Indication of non-linearity was tested using likelihood ratio test.p < 0.05 was considered statistically significant.For all analyses, the results of each paper with the most comprehensive adjustment for confounders were included. A two-tailed Stata version 12 software  was used.In total, 47 studies including 50,960 cases among 7,393,510 participants were included in the meta-analysis of anthropometric measures and colorectal, colon , and rectal cancer risk  and evidence of publication or small-study bias .Fourteen studies 84,095 cases) were included in the dose–response meta-analysis  cases we, 58–63. In stratified analysis the associations were similar in men and women and were stronger in studies in North America compared to studies in Europe. In addition, the associations tended to be stronger in studies in which height was measured than self-reported and in studies with less than 10 years of follow-up   Fig. b.I² = 87%, Pheterogeneity < 0.001) .Fourteen studies  were included in the dose–response meta-analysis , 64–67. In stratified analysis by sex and geographical location, the summary RR showed similar association in studies in men and women and stronger association in studies in North America than studies in Europe. No significant association was observed in studies in Asia including two studies Table .Pnonlinearity = 0.03, n = 9), showing a significant increased risk with increasing height .There was evidence of a significant non-linear association  and distal (1275 cases) colon cancer.I² = 76%, Pheterogeneity < 0.01). There was no evidence of publication bias .The summary RR for proximal colon cancer per an increase of 5 cm was 1.02 (95% CI 0.99–1.05)  .There was no evidence of a non-linear association . There was a significant evidence of publication bias .The summary RR for distal colon cancer per an increase of 5 cm was 1.01 (95% CI 1.00–1.01)  .There was an evidence of a significant non-linear association . There was evidence of a significant publication or small study bias .Fourteen studies  were included in the dose–response meta-analysis , 64–66. In stratified analysis, the summary RR showed a slightly stronger association in studies in men than in women and a stronger association in studies in North America than in studies in Asia and Europe Table .Pnonlinearity = 0.08, n = 9) .There was no evidence of a non-linear association (Four studies 2700 cases) were included in the meta-analysis , 27, 39.00 cases I² = 0%, Pheterogeneity = 0.58). There was no evidence of a publication or small study bias .of heterogeneity  . There was evidence of a significant publication or small study bias .Six studies 2143 cases) were included in the meta-analysis , 68–70. 43 cases In stratified analysis, the summary RR showed stronger associations in studies in women than in men and in studies conducted in Australia than in Europe Table .Pnonlinearity = 0.84, n = 3) .There was no significant evidence of a non-linear association  and distal (1083 cases) colon cancer.I² = 34%, Pheterogeneity = 0.22). There was no evidence of publication bias .The summary RR for proximal colon cancer per an increase of 5 kg was 1.02 (95% CI 1.00–1.04)  .There was no significant evidence of a non-linear association . There was no evidence of publication bias .The summary RR for distal colon cancer per an increase of 5 cm was 1.03 (95% CI 1.01–1.05)  .There was no significant evidence of a non-linear association  (Table Four studies 1186 cases) were included in the meta-analysis , 41, 45.186 casesIn stratified analysis by geographical location, positive significant association was observed in studies in Europe.Pnonlinearity = 0.29, n = 3) .There was no significant evidence of a non-linear association (2 was 1.06 (95% CI 1.04–1.07) . There was evidence of a publication or small study bias .Thirty-eight studies 84 859 cases) were included in the dose–response meta-analysis  cases we, 50, 51.Several differences in associations emerged in stratified analyses by study size, years of follow-up and in studies in which weight and height were self-assessed and in those in which they were measured, but none of them were statistically significant Table . The assPnonlinearity < 0.001, n = 29)  Fig. b. Colore2 was 1.07 (95% CI 1.05–1.08) . There was evidence of publication or small study bias .Forty two studies  were included in the dose–response meta-analysis , 69–83. In analysis stratified by sex and geographical location, the summary RR showed stronger associations in studies in men than women and stronger associations in studies in Asia and North America than studies in Europe Table .Pnonlinearity = 0.09, n = 33) .There was no statistical evidence of a non-linear association  and distal  colon cancer. There was evidence of significant positive association between BMI and both proximal and distal colon cancer risk, that was slightly stronger for distal than for proximal cancer.2 was 1.05 (95% CI 1.03–1.08) . There was no evidence of publication bias .The summary RR for proximal colon cancer per an increase of 5 kg/mIn stratified analysis by sex and geographical location, positive significant associations were stronger in men than in women and in studies conducted in Asia than in North America.Pnonlinearity = 0.14, n = 8) .There was no statistical evidence of a non-linear association (2 was 1.08 (95% CI 1.04–1.11) . There was no evidence of publication bias .The summary RR for distal colon cancer for an increase of 5 kg/mIn stratified analysis by sex and geographical location, positive significant associations were stronger in men than in women and in studies conducted in Asia than in Europe and North America.Pnonlinearity = 0.49, n = 8) .There was no statistical evidence of a non-linear association (2 was 1.02 (95% CI 1.01–1.03) . No evidence of publication or small study bias was detected .Thirty-six studies 73,186 cases) were included in the dose–response meta-analysis 6 cases w, 79, 80.In stratified analysis, the summary RR was statistically significant in men but not in women, and in studies in Asia and not in other geographic locations Table .Pnonlinearity<0.001, n = 28) . The curve shows that there is no evidence of association for BMI < 27.5 kg/m2, but increased risk for BMI values above this level.There was evidence of a non-linear association  .Ten studies 1 884 cases) were included in the dose–response meta-analysis , 27, 53. cases weIn stratified analysis, the positive associations were significant only in women and not in men, in studies conducted in Asia and North America and not in studies in Europe, and in studies with less years of follow-up < 10 years). In studies with measured or self-reported waist circumferences, the positive association was similar   Fig. b.I² = 72%, Pheterogeneity = < 0.001). There was evidence of publication bias .Eleven studies (4729 cases) were included in the dose–response meta-analysis , 53, 68.In stratified analysis by sex and geographic location, the positive significant associations were stronger in men than in women and in studies in Asia and North America compared to the studies conducted in Europe Table .Pnonlinearity = 0.001, n = 8). The curve shows increased risk of colon cancer with increasing waist circumference, with steeper associations at lower levels compared to higher levels of waist circumference .There was a significant evidence of non-linear association  and distal (1320 cases) colon cancer.There were significant positive associations of similar magnitude between waist circumference and both proximal and distal colon cancer.I² = 49.9%, Pheterogeneity = 0.09) .The summary RR for proximal colon cancer for an increase of 10 cm was 1.05 (95% CI 1.01–1.09). No heterogeneity was observed  .There was no statistical evidence of a non-linear association  .The summary RR for distal colon cancer per an increase of 10 cm was 1.06 (95% CI 1.02–1.11). No heterogeneity was observed  .There was no statistical evidence of a non-linear association . There was no evidence of publication bias .Eight studies 1980 cases) were included in the dose–response meta-analysis of waist circumference and rectal cancer , 45, 53.980 casesIn stratified analysis by sex, significant association was observed only in women and not in men. In stratified analysis by geographic location, the positive association was borderline significant in studies in Europe and not significant in studies conducted in North America Table .Pnonlinearity = 0.40, n = 6) .There was no evidence of non-linear association (Six studies 4 689 cases) were included in the dose–response meta-analysis of waist to hip ratio and colorectal cancer  cases we, 49, 53.I² =16%, Pheterogeneity =0.31). There was no evidence of publication bias .No heterogeneity was observed  .There was no statistical evidence of a non-linear association (Seven studies 3126 cases) were included in the dose–response meta-analysis of waist to hip ratio and colon cancer , 68, 84.26 cases I² =82%, Pheterogeneity < 0.001). There was no evidence of publication bias .High heterogeneity was observed  and the curve was approximately linear across the range of waist-to-hip ratio values .There was a significant evidence of non-linear association, showing colon cancer risk increased with increasing waist-to-hip-ratio  .Four studies were included in dose–response meta-analysis for proximal 1073 cases) and distal (932 cases) colon cancer. The summary RR for proximal colon cancer for an increase of 0.1 unit was 1.13 (1.00–1.28). High heterogeneity was observed .There was not enough studies to conduct non-linear analysis  .The summary RR for distal colon cancer for an increase of 0.1 unit was 1.17 (95% CI 1.01–1.35). High heterogeneity was observed .There was not enough studies to conduct non-linear analysis . There was no evidence of publication bias .Six studies 1510cases) were included in the dose–response meta-analysis of waist to hip ratio and rectal cancer risk , 49, 53.510cases In stratified analysis by sex, positive association was only significant in men and not in women. In stratified analysis by location, no significant association was observed Table .Pnonlinearity = 0.14, n = 3) .There was no statistical evidence of a non-linear association  and the risk of colorectal cancer, and all the anatomical localizations . Almost all positive associations were statistically significant.The strongest association for BMI was observed with distal colon cancer, showing 8% increased risk for an increase of 5 kg/m² of BMI. The trend of increasing colorectal cancer risk with greater BMI was stronger in men than in women.For waist circumference and waist to hip ratio, the strongest associations were observed with colon cancer, showing 5 and 16% increased risk per an increase of 10 cm of waist circumference and 0.1 increment of waist to hip ratio, respectively. Our results for an association between BMI and waist circumference and colorectal cancer risk are in agreement with the findings of two previous meta-analyses , 48.2 approximately. There was also evidence of non-linear association (P = 0.02) for BMI and colon cancer risk but the curve appeared approximately linear across the range of BMI values investigated. Furthermore, nonlinear associations were observed for abdominal fatness measures (waist circumference and waist to hip ratio) and colon cancer risk, with steeper associations at lower levels compared to higher levels of waist circumference. Several mechanisms are hypothesized to link obesity to colorectal cancer. Metabolic syndrome, elevated levels of insulin and insulin-like growth factors which inhibits apoptosis and modulates cell proliferation are suggested to play a role in the aetiology of colorectal cancer [We observed a nonlinear association between BMI and colorectal cancer risk. Colorectal cancer risk increased with BMI which appears to be stronger from BMI above 27 kg/ml cancer , 94–96. l cancer .This study has several advantages. It is based on large-scale prospective studies which minimize the probability of recall or selection bias, and also includes a large number of studies with relatively long follow-up and large number of cases that significantly increase the statistical power of the analysis. Moreover, the majority of the included studies in our meta-analysis were adjusted at least for age and other potential confounders such as alcohol consumption, smoking and physical activity.n = 27) rather than self-reported (n = 16).However, the current meta-analysis has some limitations which should be taken into account when interpreting the results. High heterogeneity was observed across studies, which would affect the reliability of the summary RR estimates and lead to less accurate results. We did not find an explanation for this heterogeneity as it persisted in most subgroup analyses. This high heterogeneity might be due to variations and differences in anthropometric measurements categories. Another limitation of this meta-analysis can be due to measurement errors in the assessment of anthropometric measures, although most of the studies reported measured BMI


Our results revealed no statistical association between current four polymorphism loci and cancer risks, suggesting that the attempt of applying HMGB1 variants as a therapeutic target or a prognosis predictor might still require a second thought. However, HMGB1 is deemed to play pleiotropic roles in cancers, we strongly call for large-scale studies with high evidence level to uncover the exact relationship between HMGB1 gene variants and cancer progression.The aim of the present study was to determine whether High mobility group box 1 (HMGB1) polymorphism was associated with cancer susceptibility. PubMed, Embase, and ISI Web of Science were extensively searched without language restriction. Data were extracted using a standardized data collection sheet after two reviewers scanned studies independently. The association between HMGB1 polymorphism and cancer risks was indicated as odds ratio (OR) along with its related 95% confidence interval (95%CI). Meta-analysis was conducted via RevMan 5.3 software. A total of ten studies comprising 4530 cases and 5167 controls were included in our study. Meta-analysis revealed no statistical association between  High mobility group box 1 (HMGB1), also known as HMG1 ,3. It isTill now, studies have correlated the HMGB1 protein to cancer progression, especially invasion and metastasis . In the in vitro, also preventing growth in in vivo tumor models [Intriguingly, HMGB1 may also function as a tumor suppressor. It has been found to increase the binding affinity of many sequence-specific transcription factors to their cognate DNA, such as p53, p73, the retinoblastoma protein (Rb), nuclear factor-κB (NF-κB), and the estrogen receptor . The over models ,23. CurrCancer development is a multistep progress. Chromosomal instability, which could be driven by complex genetic and physiological variations as well as environmental factors, is considered to be central to the pathogenesis of malignancies ,25. LossHMGB1 gene polymorphisms and cancer risks.Although flourishing numbers of researches have demonstrated that the existence of HMGB1 polymorphism made it possible for affecting the susceptibility , prognosThis systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines .We systemically searched PubMed, Embase, and ISI Web of Science (from their commencements to May 2018) with no language restrictions, for studies in humans of correlations between HMGB1 polymorphisms and cancer risks. The following terms were used for English online databases:  and (HMGB1 or high mobility group box 1 or HMG-1). To broaden our search, references of related reviews were also manually scrutinized.In this meta-analysis, publications were eligible if they fulfilled the following criteria: (i) case–control study or cohort study design; (ii) evaluated the association of the genetic polymorphisms of HMGB1 with the risk of cancer; (iii) displayed outcomes in the form of odds ratio (OR) with 95% confidence interval (95%CI) or provided sufficient genotypic and/or allelic information for estimating OR with 95%CI.The exclusion criteria included: (i) duplicated studies using the same population or overlapping database; (ii) non-human research; (iii) studies that were case reports, editorials, reviews, letters, and comments.The Newcastle–Ottawa Scale (NOS)  for asseStudy selection was achieved by two investigators independently based on the pre-decided inclusion criteria, any dispute was solved by discussion. Data from the selected studies were collected using a standard data collection sheet including first author and year of publication, SNP loci, country and ethnicity of participants, sample size, source of cases, number of cases and controls for each genotype, and Hardy–Weinberg equilibrium (HWE).Recessive model: if OR1 = OR3≠1 and OR2 = 1;Dominant model: if OR1 = OR2≠1 and OR3 = 1;Complete over-dominant model: if OR1 = 1, OR2 = 1/OR3≠1;Codominant model: if OR1 > OR2 > 1 and OR1 > OR3 > 1, or OR1 < OR2 < 1 and OR1 < OR3 < 1.Deviation from HWE was evaluated by using Chi-square test to assess goodness-of-fit in control subjects of each included study. The magnitude of association between HMGB1 polymorphisms and risk of cancer was expressed as OR along with the associated 95%CI. In order to avoid an inflated Type I error rate, we did not perform any prior assumptions about the genetic model of inherence in advance. The most plausible genetic model for HMGB1 polymorphisms in the risk of cancer was identified by a model-free approach recommended by Thakkinstian et al. . If A vaQ-statistical test and 2I test. The random-effect model and fixed-effect model were used for data combination in the presence  or absence of heterogeneity , respectively [After that the underlying genetic model was confirmed, the counts of each genotype were collapsed into two categories to obtain the merged results. The between-study heterogeneity was assessed using the ectively .In case of statistically significant heterogeneity across studies, subgroup analyses by ethnicity, type of cancer were performed to find the possible source of heterogeneity. The Leave-one-out sensitivity analysis was conducted by removing each study in turn and reassessing the resulting effect on the overall effect. Egger’s regression test and Begg’s rank correlation test  were useAn initial search yielded 239 potential citations, amongst which 64 from PubMed, 83 from Embase, and 92 from ISI Web of Science, respectively. Eighty citations were deleted because they were duplicates. After screening titles and abstracts, thirteen studies were selected and retrieved for full-text assessment based on predetermined inclusion criteria, amongst which one included unavailable data, one was conference abstract, and one was unrelated. Finally, a total of ten studies  were conrs1045411, rs1360485, rs1412125, rs2249825 polymorphism and risks of cancers, covering patients of lung cancer (LC) [As cer (LC) ,36, oralcer (LC) ,29, hepacer (LC) ,31, colocer (LC) , uterinecer (LC) , and BC cer (LC) ,35, amoncer (LC) ,28,30–36The risk of bias amongst studies was assessed using NOS scale . Studiesrs1360485 in HMGB1 and cancer risks, OR1 , OR2 , and OR3  were all statistically insignificant, which suggested no potential association between rs1360485 and risk of cancer. Null associations were also found for rs1412125 , rs2249825  polymorphisms and cancer risks. However, in terms of rs1045411, the estimated OR1  and OR2  were both statistically significant, whereas the estimated OR3  was insignificant, suggesting that the dominant model was the most plausible genetic model for meta-analysis. When using the dominant model, the counts of genotypes of CC and CT groups were combined together and compared with TT groups. Since there was moderate heterogeneity amongst included studies , the random-effect model was used for statistical analysis. The combined ORs showed that there was no statistically significant association between rs1045411 in HMGB1 gene and risk of cancer   .P=0.76), 1.10 , 0.54 , 0.63 , 0.57 , and 0.52  in LC, OSCC, HCC, CRC, UCC, and BC respectively  to low  and Egger’s test  also indicated no statistically significant publication bias.We also performed the leave-one-out sensitivity analysis, and found that Wang et al. study  might cors1045411, rs1360485, rs1412125, or rs2249825 polymorphisms and cancer risks. Thereafter, we went further by conducting subgroup analysis of rs1045411 based on cancer type and ethnicity stratification, which also indicated no correlations with cancer risks amongst all cancer types included except BC. No association was observed in the group of Hans or Caucasians.To the best of our knowledge, this is the first systemic review and meta-analysis performed to access the correlation between HMGB1 polymorphism and cancer occurrence. Our study revealed no correlations between HMGB1 HMGB1 is widely convinced as one of the most cancer-specific genes . As a mars1045411 polymorphism resides in the 3-flanking region, suggesting a role in mRNA stability as miRNAs can bind the 3′-UTR regions of mRNA transcripts and inhibit gene expression at the post-transcriptional level [miR-505 binding site, rs1045411 and rs1360485 3′-UTR region variants showed strong linkage and were synergistically involved in the etiopathogenesis [rs1045411 was connected with cancer risks in OR1 and 2 models in the current meta-analysis. We did not find statistically significant differences in cancer risks amongst carriers of this SNP variant compared with non-carriers, whether it was covered up by the counterbalance of its pleiotropic roles in cancer progression or reflected in diversified statistical strategies requires further investigation. However, there were trends toward an association with lower cancer susceptibility, which might become more apparent with a larger sample size.The al level . Meanwhiogenesis , which mrs1045411 in cancer susceptibility [rs1045411 and an increased risk of malignancies, which was likely owing to environmental, lifestyle, or dietary factors. Since rs1045411 polymorphism was closely correlated with an altered binding of miR-505-5P in the 3′-UTR of mRNA transcripts, HMGB1 gene polymorphisms could emerge as a crucial player in cancer development through a post-transcriptional mechanism. However, when all available studies were combined together, the pooled ORs showed no association between rs1045411 and risk of cancer in general , and the marginal overall effect is possibly due to limited number of studies included and number of subjects recruited in our selected studies. Therefore, we strongly call for additional studies with larger sample sizes and different ethnicities to confirm our findings.Of note, studies included led to highly discrepant findings, as five of which revealed a protective role of CC+CT genotypes of tibility , while ttibility . This mitibility ,32,34 inHMGB1 gene SNPs were found not related with risk of cancer based on the findings of our current meta-analysis, some of our included studies indicated that these SNPs could be associated with progression of cancer and overall survival outcomes. Wang et al. [rs1412125 showed a low risk of distant metastasis. Supic et al. [rs2249825 and rs3742305 polymorphisms might be associated with OSCC survival outcomes. Huang et al. [rs1360485 and rs2249825 were likely to progress to T2 stage tumor and lymph node metastasis. C allele in rs1412125 was found to be related with cancer progression, since Huang et al. reported that having one C allele increased the risk of pathologic grade 3 disease in HER2-enriched and triple-negative BC (TNBC). Furthermore, although multivariate analyses have demonstrated HMGB1 expression as an independent prognostic indicator of overall survival [Although g et al.  indicatec et al.  revealedg et al.  reportedsurvival ,48, the P<0.001) in this study, which might be confounding factors, as both of them were strikingly associated with the risk of HCC. Thus, the association between rs1045411 and risk of cancer could be overstated because of the higher percentages of smokers and alcohol drinkers in the case group than control group. After eliminating this study, reevaluation of the remaining studies still revealed no statistically significant correlations, suggesting the robustness of the results in this meta-analysis.According to the results of leave-one-out sensitivity analysis, research of Wang et al.  was founLimited to the few scanty studies, our present study does have its limitations. Besides discussed above, as nine out of ten studies were conducted in Asia, our findings may not be representative of the general population, not to mention samples of cases recruited in each cancer type. Moreover, the association between SNPs in HMGB1 and cancer risks may be affected by other confounders including smoking status, drinking status as well as gender and ages, but we are currently unable to perform further stratified analysis based on these confounding factors due to the incomplete raw data reported by included studies. Under such condition, large-scale studies, involving haplotype analysis as well as adjustments of potential confounding factors, are required to further elucidate the exact role of HMGB1 and its variants in cancer.rs1045411, rs1360485, rs1412125, or rs2249825 polymorphisms and cancer susceptibility, we went further by conducting subgroup analysis based on cancer type and ethnic groups of subjects, and revealed no statistical differences between rs1045411 polymorphism and cancer risk amongst LC, OSCC, HCC, CRC, and UCC. Subgroup analysis by ethnicity showed no association of rs1045411 and risk of cancer in Hans or Caucasians. Although our results appeared to be obscure statistically, which might postpone the potential application of HMGB1 as a therapeutic target as well as a prognosis predictor, reasonable confidence should be given to the null association between HMGB1 polymorphisms and risk of cancer. We strongly call for further investigations to lift the veil of the underlying mechanisms involved in the relationship between HMGB1 SNPs and cancer risk.Our current systemic review and meta-analysis mainly focussed on associations between HMGB1


PON1) gene is associated with coronary heart disease (CHD). However, it is still uncertain whether this polymorphism is associated with the plasma levels of oxidized low-density lipoprotein (Ox-LDL) and lipids. This meta-analysis is aimed to clarify the relationships between the rs662 polymorphism and plasma levels of Ox-LDL and lipids.Several meta-analyses have demonstrated that the rs662 polymorphism in Paraoxonase 1 gene  and 85 studies  were respectively identified for Ox-LDL association analysis and lipid association analysis. Standardized mean difference (SMD) was used to estimate the effects of the rs662 polymorphism on plasma Ox-LDL and lipid levels.P <  0.01), triglyceride (TG) , total cholesterol (TC)  and low-density lipoprotein cholesterol (LDL-C)  than the non-carriers.The carriers of the variant R allele had higher levels of Ox-LDL  contains supplementary material, which is available to authorized users. Coronary heart disease (CHD) is currently the leading cause of death in developed and some developing countries like China . CHD is In humans, PON has three isoforms: paraoxonase 1 (PON1), paraoxonase 2 (PON2) and paraoxonase 3 (PON3). Among them, PON1 is a calcium-dependent multifunctional enzyme that connects metabolisms of homocysteine (Hcy) and lipoproteins. First of all, PON1 plays a key role in Hcy metabolism by irreversibly catalyzing the conversion of homocysteine thiolactone (Hcy T) to Hcy. By detoxifying Hcy T, the PON1 would protect proteins against homocysteinylation, a potential risk factor for CHD . SecondlPON1 gene is located on the long arm of human chromosome 7 (7q21.3–22.1), and it contains 9 exons and 8 introns. There are several polymorphisms in the PON1 gene. The rs662 polymorphism  is located in exon 6 of the PON1 gene and formed by a transition from adenine (A) to guanine (G). Accordingly, the 192th genetic code is changed from CAA to CGA, resulting in the replacement of glutamine (Gln) by arginine (Arg) in the PON1 polypeptide. A large number of researches have investigated the associations of the rs662 polymorphism with plasma Ox-LDL and lipid levels. In some of these studies, the R allele of the rs662 polymorphism was reported to be associated with increased levels of Ox-LDL [The f Ox-LDL , 12, TG f Ox-LDL , 14, TC f Ox-LDL  and LDL-f Ox-LDL –17, and f Ox-LDL –20. Howesome 7 7q.3–22.1, f Ox-LDL . Hence, In this study, a systematic review and meta-analysis was performed based on previous publications to investigate the associations of the rs662 polymorphism with Ox-LDL and lipid levels. Our analysis results can provide an opportunity to unveil the interrelationships among the rs662 polymorphism, Ox-LDL, dyslipidemia and susceptibility to CHD.The articles published until September 2018 on the associations of the rs662 polymorphism with circulating Ox-LDL and lipid levels were identified. The languages of the articles were limited to English and Chinese. A comprehensive search was conducted and nine electronic databases were searched to identify all relevant articles. The databases were as follows: PubMed, Embase, Baidu Scholar, Google Scholar, Web of Science, Cochrane Library, Wanfang, CBM and CNKI. The following keywords were used: (“Paraoxonase 1” or “PON1”), (“Q192R” or “rs662” or “Gln192Arg”), (“polymorphism” or “mutation” or “variant”), (“Ox-LDL” or “oxidized low-density lipoprotein”) and (“plasma lipid” or “blood lipid” or “serum lipid”).The inclusion criteria for the meta-analysis are as follows: 1) studies which presented the genotype and allele frequencies of the rs662 polymorphism; 2) studies in which mean Ox-LDL and mean lipids with standard deviation (SD) or standard error (SE) according to the rs662 genotypes were available; 3) studies which reported at least one of the five variables, i.e., Ox-LDL, TG, TC, LDL-C and HDL-C. All references cited by the included articles were reviewed to check the published work which was not indexed by PubMed, Embase, Baidu Scholar, Google Scholar, Web of Science, Cochrane Library, Wanfang, CBM and CNKI. Reports with incomplete data, studies based on pedigree data, case reports, review articles, abstracts and animal studies were excluded from the meta-analysis. Pre-intervention data were used for interventional studies.Data were extracted from each study by using a structured data collection form and by two investigators independently according to the pre-specified selection criteria. Decisions were compared and disagreements about study selection were resolved by consensus or involving a third investigator. For the overlapping articles, only the publications that presented the most detailed information were included. In this meta-analysis, the data extracted from each of the included studies are as follows: first author, year of publication, age, ethnicity, gender, health status, type of study, lipid assay method, sample size, and mean with SD or SE according to the rs662 genotypes. If data in a study were unconvincing, we attempted to contact the corresponding or first author by e-mail or telephone.P-value of less than 0.05 for any test or model was considered to be statistically significant. The pooled standardized mean difference (SMD) with 95% confidence interval (CI) was used to assess the strength of the associations between the rs662 polymorphism and plasma levels of Ox-LDL and lipids. Random-effect model (DerSimonian-Laird method) was used to evaluate the results if heterogeneity among the included studies was significant (I2 > 50%). Otherwise, Fixed-effect model (Mantel-Haenszel method) was used [2-based Q-statistic, and Galbraith plots were used to detect the potential sources of heterogeneity. SMD values were recalculated after excluding the studies with heterogeneity. Subgroup analyses were performed according to gender, ethnicity and health status. Ethnic subgroup was defined as Caucasian, Asian, African, and the subjects of other ethnic origin. Health status was defined as CHD, T2DM and Hyperlipidemia. HWE was assessed by Fisher’s exact test. Publication bias was tested by Begg’s funnel plot and Egger’s test [Statistical analysis was performed using STATA version 12.0 . All the tests were two-sided and a was used . Heterogr’s test .Initial search of the databases yielded 2481 articles. Two thousand one hundred and eighty-five studies were excluded according to titles and abstracts. Then full-text articles were retrieved and assessed on the basis of the inclusion criteria. Forty studies were ineligible for the following reasons: 28 studies presented data for other polymorphisms, 4 studies had subjects overlapping with other publications, 5 studies were based on pedigree analysis, and 3 studies were treated with lipid-lowering drugs. In the end, 85 studies were selected for this meta-analysis  (Table P <  0.01) , TC  and LDL-C  than the non-carriers (Table P = 0.68) (Table P = 0.04) and LDL-C  than the non-carriers (Table P = 0.13) and HDL-C   was detected in the females, but not in the males. The significant associations of the rs662 polymorphism with higher levels of TG , TC  and LDL-C  were detected in Asians, but not in the other ethnicities. When health status was taken into account, the significant association of the rs662 polymorphism with higher levels of TG was detected in CHD patients and T2DM patients, but not in hyperlipidemia patients and healthy subjects; the significant association of the rs662 polymorphism with higher levels of TC  was only detected in healthy subjects, but not in CHD patients, T2DM patients and hyperlipidemia patients; furthermore, association of the rs662 polymorphism with higher levels of LDL-C was detected in T2DM patients and healthy subjects, but not in CHD patients and hyperlipidemia patients; continuously, association of the rs662 polymorphism with lower levels of HDL-C  was only detected in CHD patients, but not in T2DM patients, hyperlipidemia patients and healthy subjects . Two comparisons  were identified as the main contributors to the heterogeneity by using Galbraith plot. The SMD value and 95% CI  did not change substantially after excluding these outlier comparisons.In the Ox-LDL association analysis, there was significant heterogeneity in the analysis with all comparisons , TC , LDL-C  and HDL-C . Nine comparisons, 9 comparisons, 10 comparisons and 14 comparisons were respectively identified as the main contributors to the heterogeneity for TG, TC, LDL-C and HDL-C by using Galbraith plots. The SMD value and 95% CI of TG , LDL-C  and HDL-C  did not change substantially after excluding these outlier comparisons. However, The SMD values and 95% CIs of TC  changed significantly after excluding these outlier comparisons.In the lipids association analysis, there was significant heterogeneity in the total comparisons for TG . Thirdly, this meta-analysis only included the studies published in English and Chinese as it is very difficult to get the full papers published in various languages.The meta-analysis suggests that the rs662 polymorphism is significantly associated with abnormal levels of Ox-LDL and lipids, which may partly explain the significant association between the rs662 polymorphism and CHD.Additional file 1:The reference list for the studies included in the present meta-analysis. (DOCX 26 kb)Additional file 2:Table S1. Characteristics of the individual studies included in the meta-analysis of Ox-LDL levels and plasma lipid levels for the PON1 rs662 polymorphism; Table S2. Ox-LDL levels by the genotypes of the PON1 rs662 polymorphism; Table S3. Plasma lipid levels by the genotypes of the PON1 rs662 polymorphism. (DOC 649 kb)


Previous studies suggested an association between K121Q (rs1044498 C > A) in ecto-nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) gene and the risk of coronary heart disease (CHD), but the results have been inconsistent. In this study, we performed a meta-analysis of several trials to systematically summarize their potential association.Relevant articles were identified by searching electronic databases for studies published prior to March 2018. We carefully reviewed published studies on ENPP1 genetic polymorphism in relation to CHD susceptibility. The data extracted from selected high-quality studies were analyzed using STATA statistical software .Nine eligible studies which contained a combined total of 1547 CHD cases and 2213 healthy controls were chosen in the present meta-analysis. Our results indicated that K121Q strongly correlated with increased risk of CHD. The subgroup analysis on race, sample source, disease type, sex, age, and genotype showed that in Caucasians, K121Q strongly correlated with increased risk of CHD, but no difference was found in Chinese. Both single factor and multiple factor regression showed that race, sample origin, disease type, sex, age, and genotype were not the source of heterogeneity.Our meta-analysis revealed that the K121Q (rs1044498 C > A) in the ENPP1 gene is a risk factor for CHD. It is estimated that about 620,000 Americans have a new coronary attack annually and approximately 295,000 have a recurrent attack each year. In Europe, CHD is responsible for approximately 4 million deaths annually. Although the exact mechanisms involved in CHD are not completely understood, the increased incidence of CHD is attributed to a variety of environmental and genetic factors. Other important extrinsic risk factors, such as high blood cholesterol/pressure, smoking, diabetes, physical inactivity, obesity, poor diet, age, and medical history, are also indispensable factor for CHD.,8 In the past 2 decades, various genetic factors have been verified as significant contributors to the development of CHD. Recent findings support the view that ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) gene is associated with increased susceptibility to CHD in humans, and the mutations in ENPP1 gene are related to insulin resistance as well as idiopathic infantile arterial calcification.,11Coronary heart disease (CHD), also variously known as atherosclerotic heart disease, coronary artery disease, or ischemic heart disease, is the most common type of heart disease and the leading cause of death worldwide. The human ENPP1 gene is 80 kb in length and is located on chromosome 6q22-q23, consisting of 25 exons and 24 introns, and encoding a 925-amino acid protein with a molecular weight of 104.9 kDa.ENPP1 is expressed in multiple tissues, including muscle, capillary endothelium in the brain, fat, salivary duct epithelium, liver, adipose tissue, pancreas, chondrocytes, and kidneys. Elevated ENPP1 expression is found in adipose tissue, cultured skin fibroblasts, and skeletal muscle of insulin-resistant individuals, suggesting that over-expression of ENPP1 may be an early marker of insulin resistance in humans.,15 Insulin resistance is a critical risk factor in the development of type 2 diabetes mellitus, and is also related with obesity, dyslipidemia, hypertension, and coronary atherosclerosis. The underlying mechanisms appear to be related to ENPP1-mediated inhibition of insulin receptor tyrosine kinase activity, and overexpression of ENPP1 decreases the activity and cellular signaling of insulin receptor tyrosine kinase, inducing insulin resistance and contributing to the development of type 2 diabetes mellitus. Further, elevated ENPP1 expression promotes vascular inflammatory responses, inflammatory cytokine secretion, and left ventricular mass through stimulation of insulin like growth factor-1 receptors, which are abundantly expressed in the myocardium and then subsequently increase cardiovascular risk. Genetic researches also support that ENPP1 is a vital biomarker of insulin resistance, and ENPP1 genetic polymorphism may be correlated with type 2 diabetes mellitus, nephrovascular complications, and cardiovascular disease.,20 Recently, several studies have suggested the possibility that ENPP1 genetic polymorphisms are correlated with significantly elevated risk of CHD,,22 however, the results are inconsistent with the results of other studies.,24 In this study, we employ a meta-analysis based approach to summarize the relationship between CAD and ENPP1 K121Q (rs1044498 C > A), as a prelude to the development of novel strategies for prevention and treatment of CHD.ENPP1 is a type II transmembrane glycoprotein with extracellular pyrophosphatase and phosphodiesterase activities.22.1The databases such as Web of Science, CINAHL, PubMed, Cochrane Library, EMBASE, and Chinese Biomedical (CBM) were searched to identify case-control studies, which were published prior to March 2018. The combination of keywords and MeSH terms used for search strategy were: (“genetic polymorphism” or “SNP” or “variation” or “single nucleotide polymorphism” or “polymorphism” or “mutation” or “variant”) and  and . Additionally, a manual cross-reference search of the references of the relevant articles was performed to identify studies beside the computerized search.2.2ENPP1 K121Q (rs1044498 C > A); studies were case-control design; all patients were confirmed by the diagnostic criteria of CHD; studies supplying sufficient information on ENPP1 K121Q. The following studies were excluded: letters, reviews, case reports, conference abstracts, editorials, or expert opinions; studies in languages other than Chinese or English; studies on polymorphisms of ENPP1 not relevant to this study. In addition, we chose the most recent paper when multiple articles with same data were reported by the same author.All selected studies in this meta-analysis met the following inclusion criteria: studies reporting CHD and 2.3 Two researchers independently extract the document data and make the NOS quality evaluation. If the data extraction process or NOS quality evaluation is controversial, a number of researchers discussed and solve the controversial problems.The following data were extracted: first author, publication year, country, ethnicity, number of cases and controls, sex, age, genotype method, gene, and Newcastle-Ottawa Scale (NOS) score. NOS criteria was used by 2 coauthors to evaluate the methodological quality of the included studies.2.4ENPP1 K121Q and CHD based on the genotype frequencies in the 2 groups. Subgroup analysis by country, source of controls, disease, and genotype method was performed. Fixed-effect or random-effect model were applied to calculate pooled RRs. Statistical significance of pooled RRs was determined by Z test. The possibility of heterogeneity was evaluated using the Cochran's Q-statistic and I2 tests.P value <.05 or I2 > 50% meant obviously heterogeneity, and then a random-effect model was employed, otherwise a fixed-effect model was employed. Sensitivity analyses were performed to investigate potential source of the heterogeneity. Publication bias was also studied by visual inspection of funnel plots as well as Egger test.The unadjusted relative risks (RRs) and its corresponding 95% confidence interval (CI) was adopted to estimate the strength of the relation between the 33.1,24,28–31 The details of the study selection process are presented in Fig. A total of 62 relevant studies were identified in the initial search. Based on the inclusion and criteria, 53 articles were removed and 9 case-control studies were finally enrolled into this meta-analysis.3.2ENPP1 K121Q and CHD risk is provided in Table ENPP1 K121Q showed a significant correlation with the CHD risk  , while no such association was detected among Asian (P > .05)   in the dominant model  , but not with MS-PCR     Figs. B and 4B.5) Figs. C and 4C.3.3ENPP1 K121Q   Fig. .4ENPP1 gene and CHD risk has been investigated previously in multiple studies, while at the moment there is a heated debate, but no consensus of that issue. We performed this meta-analysis to provide a comprehensive evaluation of the relationship between ENPP1 K121Q and the risk of CHD by combining the data from previous studies and deriving reliable conclusions based on our statistical analysis. In the present meta-analysis, our results demonstrated that ENPP1 K121Q was responsible for a significantly increased risk of CHD, suggesting that the genetic polymorphism of ENPP1 could be helpful in predicting the pathogenesis of CHD. It was established that ENPP1 gene inhibited insulin receptor tyrosine kinase activity, and promoted insulin resistance. Insulin resistance was a vital factor in the etiology of cardiovascular diseases. Insulin resistance was widely accepted as largely contributed by genetic factors, and from this study, we also regarded ENPP1 genetic variant as one of the genetic factors, which might contribute to impaired sensitivity to insulin and then resulted in predisposition of individuals to CHD. The current meta-analysis mainly described the ENPP1 K121Q, which resulted in amino acid substitution to glutamine from lysine at codon 121. The ENPP1 Q variant had a stronger binding affinity to insulin receptor as well as decreased its auto-phosphorylation, compared with the K variant. It could be speculated that the ENPP1 K121 Q variant might increase cardiovascular risk for causing systemic insulin resistance as well as proatherogenic phenotypes. On the other hand, a direct mechanism related to CHD could also be involved due to the influence of the polymorphism on insulin-dependent endothelial function. From the above discussion, stronger binging of the K121Q variant to the insulin receptor at the cell membrane inhibited insulin signaling. In human endothelial cells harboring the K121Q variant, the consequences were serious because suppression of insulin receptor signaling potentially impacted synthesis and release of nitric oxide, and a powerful vasodilator whose decreased levels contributed to the development of atherosclerosis. Therefore, we hypothesized that the K121Q variants in the ENPP1 gene significantly might increase the susceptibility to CHD through its systemic effects and endothelial-specific effects, leading to insulin resistance and contributing to rapid progression of CHD. Consistent with our results, Shaker and Ismail showed in 60 unrelated patients suffering from their first MI and 60 unrelated controls, that the K121Q variant conferred a higher risk of early development of insulin resistance and patients showed significantly faster progression of acute myocardial infarction compared with the 121K allele. The present study clearly revealed that the occurrence of the ENPP1 K121Q polymorphism was significantly higher in CHD patients and the ENPP1 K121Q variant could be a clinically useful biomarker for population-based screening to identify high-risk individuals for their susceptibility to major cardiovascular events. Subgroup analysis by country showed a significant relation of K121Q polymorphism with CHD risk in Caucasian, but not in Asian. The results can be explained that individuals in different countries may have different genetic backgrounds and life-styles.The relationship between ENPP1 genetic polymorphism and CHD in our results.Limitations of the present study should be considered. Publication bias may result from the fact that unpublished data, as well as papers published in languages other than English and Chinese, were not included. Further, our meta-analysis division criteria of ethnic groups into “Caucasian,” or “Asian” may bias the results, without the detailed knowledge of the patients. Another limitation in our meta-analysis is the small sample size. Despite these limitations, we quantified and analyzed previous inconsistent results from previous studies in our meta-analysis. Besides, the number of years of publication, race, sample origin, disease, genotyping, male ratio, and average age were not heterogeneous factors in this study, which indicates a more credible conclusion of the relationship between ENPP1 K121Q confers a high risk of susceptibility to CHD and may be useful in early identification of at-risk CHD population, especially in Caucasian. These results indicated that ENPP1 genetic variation might be crucial in the occurrence of CHD and the genetic variant might be helpful in understanding the basic biology leading to insulin resistance. However, future studies including larger sample size and different ethnicities are also needed to confirm our findings and begin to develop therapeutic intervention strategies focused on ENPP1 K121Q.In conclusion, our results revealed that The authors would like to give our appreciation to the reviewers for their helpful comments.Conceptualization: Jia-Yin Di.Data curation: Jia-Yin Di.Formal analysis: Jia-Yin Di, Meng-Lu Dai.Funding acquisition: Meng-Lu Dai.Investigation: Meng-Lu Dai, Zong-Xin Zhang.Methodology: Zong-Xin Zhang.Project administration: Zong-Xin Zhang.


Conversely, EBV and HIV infections were significantly associated with higher risk of developing TGCTs . In conclusion, we found adequate evidence supporting an oncogenic effect of HIV and EBV on the human testis. Conversely, available data on HPV and TGCTs risk are conflicting and further studies are needed to draw firm conclusions. Finally, current evidence does not support an effect of CMV and Parvovirus B-19 on testicular carcinogenesis.The most represented histotype of testicular cancer is the testicular germ-cell tumor (TGCT), both seminoma and non-seminoma. The pathogenesis of this cancer is poorly known. A possible causal relationship between viral infections and TGCTs was firstly evoked almost 40 years ago and is still a subject of debate. In the recent past, different authors have argued about a possible role of specific viruses in the development of TGCTs including human papillomavirus (HPV), Epstein–Barr virus (EBV), cytomegalovirus (CMV), Parvovirus B-19, and human immunodeficiency virus (HIV). The aim of this present review was to summarize, for each virus considered, the available evidence on the impact of viral infections on the risk of developing TGCTs. The review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included all observational studies reported in English evaluating the correlations between viral infections  and TGCTs. The methodological quality of studies included in the meta-analysis was evaluated using a modified version of the “Newcastle–Ottawa Scale.” Meta-analyses were conducted using the “Generic inverse variance” method, where a pooled odds ratio (OR) was determined from the natural logarithm (LN) of the studies' individual OR [LN (OR)] and the 95% CI. A total of 20 studies  were included in the review. Meta-analysis showed an association with TGCTs only for some of the explored viruses. In particular, no association was found for HPV, CMV, and Parvovirus B-19 infection ( Testicular cancer (TC) is the most common solid tumor affecting males between 20 and 40 years old and accounting for approximately 1–1.5% of all cancers in men –5. It isMany risk factors have been proposed for TGCTs , 8 incluDespite the exposure to some viruses that have been certainly associated to other cancer types in males , few studies evaluated the possible implications of viral infection in the pathogenesis of TGCTs. Curiously, most of the viruses involved in sexually transmittable disorders have an age-related prevalence that coincides with that observed in TGCTs. Moreover, the characteristic long latency and persistence in the host of several viruses could induce a long-term dysregulation of the cell cycle able to induce the cancer development. Again, some studies demonstrated the prevalence of viral DNA/RNA directly in tissue specimens from testicular cancer –11. FinaIn this meta-analysis, we aimed to summarize the whole body of literature exploring the correlation between TGCTs and viral infections by HPV, HIV, cytomegalovirus (CMV), EBV, and Parvovirus B-19, with the purpose of clarifying the possible role of these viruses in the pathogenesis of this condition.This is a systematic review and meta-analysis of published data. The review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines .As this study was a systematic review and meta-analysis of published data, formal ethical approval was not required.Electronic databases  were searched until 1st February 2019 (without date restriction).Key search terms were as follows: virus OR viral infection OR viral disease OR human papillomavirus OR HPV OR Cytomegalovirus OR CMV OR Epstein–Barr virus OR EBV OR Parvovirus B19 OR human immunodeficiency virus OR HIV OR acquired immunodeficiency syndrome OR AIDS AND testicular cancer OR testicular neoplasm OR testicular tumor. The electronic search and the eligibility of the studies were independently assessed by two of the authors (AG and FM).We included all studies evaluating the correlations between viral infections  and TGCTs. All observational studies  reported in English were eligible. Testicular cancer was defined as the demonstration of testicular cancer cells at histopathological examination.Two authors (AG and AV) independently assessed the inclusion criteria and study selection. Disagreements were discussed with a third reviewer (CF).Data extraction was performed by five independent investigators . When studies involved a subgroup of patients considered negligible for the endpoints of meta-analysis , the authors provided only a qualitative data extraction. A manual search of reference lists of studies was performed to avoid missing relevant publications. One author (AV) reviewed the selection and data extraction process. The results were then compared, and any disagreement was discussed and resolved by consensus.sample representativeness,” “sampling technique,” “ascertainment of viral infection,” “quality of description of the population and confounders,” and “incomplete data on cancer histology” (Two reviewers (AV and AG) independently judged the methodological quality of studies included in the meta-analysis using a modified version of the “Newcastle–Ottawa Scale” . Qualitystology” . AccordiI2 statistics. The pooled estimates were reported graphically with Forest plots. Meta-analyses were conducted separately for each virus . Sources of statistical heterogeneity were investigated by subgroups and sensitivity analyses .Odds ratios (ORs) and proportions were calculated with MedCalc 18.5 . For meta-analysis, Review Manager (RevMan) Version 5.1  was used. Statistical analysis was conducted using the “Generic inverse variance” method, where a pooled OR was determined from the natural logarithm (LN) of the studies' individual OR [LN (OR)] and the 95% CI. The SE for the LN (OR) was calculated from the 95% CI using the formula: SE = [LN (upper CI limit) – LN (lower CI limit)]/3.92, according to the Cochrane Reviewers' handbook , 138 studies were excluded. Finally, a total of 25 studies were included in the present meta-analysis: 4 for HPV, 8 for EBV, 5 for CMV, 5 for Parvovirus B19, and 3 for HIV .in situ hybridization (ISH), one used fluorescent in situ hybridization (FISH), and one used immunofluorescent staining (IFS).Characteristics of included studies are summarized in In Sample representativeness: All but six studies . Sensitivity analysis did not provide statistical changes to aggregate results. Subgroup analysis was not feasible.Pooling of results did not show an association between HPV infection and TGCTs , with high degree of statistical heterogeneity (I2 = 84%). The exclusion of the study by Moss et al. from meta-analysis resulted in a significant association between EBV and TGCTs . Subgroup analysis based on the methods for EBV determination  found a significantly higher risk of TGCTs in those patients with a positive serology . The proportion of seminomas among EBV+ patients (at serology) with a diagnosis of TGCTs was 51.69% (95% CI 44.01–59.32%).Pooling of results did not show an association between EBV infection and TGCTs , with moderate statistical heterogeneity (I2 = 45%). The exclusion of the study by Akre et al. from the meta-analysis resulted in a significant association between CMV and TGCTs  and reduced the heterogeneity (I2 = 4%). The proportion of seminomas among CMV+ patients (at serology) with a diagnosis of TGCTs was 50.47% (95% CI 42.95–57.97%). Subgroup analysis was not feasible.Pooling of results did not show an association between CMV infection and TGCTs , with substantial statistical heterogeneity (I2 = 73%). The serial exclusion of each single study through sensitivity analysis as well as subgroup analysis did not modify the results of the primary analysis.Pooling of results did not show an association between Parvovirus B-19 infection and TGCTs , with low heterogeneity (I2 = 0%). The serial exclusion of each single study through sensitivity analysis did not modify the results of the primary analysis. The proportion of seminomas among HIV+ patients with a diagnosis of TGCTs was 75.17% (95% CI 69.01–80.66%).Pooling of results showed a significant association between HIV infection and TGCTs . Notably, there was high between-studies heterogeneity in terms of methodology, potentially limiting drawing firm conclusions from the data.The correlation between HPV infection and TGCTs was evaluated by four studies on 430 patients –18, 31. HPV is one of the most common sexually transmitted viruses . It is pNevertheless, concurrently with new insights about infertility causes and treatments , 50, we p = 0.05), the exclusion of a single study from meta-analysis (p = 0.004). Importantly, the study by Moss et al. (p < 0.00001), further confirming the association between history of EBV infection and TGCTs onset.The association between EBV infection and TGCTs was investigated by eight studies on 1,063 patients , 19–25. analysis  resulteds et al.  was at hEBV was the first virus shown to cause cancer in humans . BesidesRegarding EBV and TGCTs, there is an epidemiological correlation between these two entities. The incidence of infectious mononucleosis (including EBV-correlated orchitis) is higher in Europe and North America, similar to that of TGCTs. Interestingly, both infectious mononucleosis and TGCTs mainly occur in adolescents, suggesting that testicular differentiation is a factor increasing the susceptibility for both EBV infection and testicular carcinogenesis.  Moreoverp = 0.09), the exclusion of a single study (p = 0.009). Notably, the methodological quality of the study by Akre et al. . Additionally, subgroup and sensitivity analyses did not modify the results of the primary analysis, confirming their robustness. Parvovirus B-19 is the only parvovirus known to be pathogenic for humans  evaluated the correlation between Parvovirus B-19 infection and TGCTs , 27–30. r humans . The virr humans , 68. In r humans . In immur humans , 70. Ther humans . Howeverp < 0.00001). The results were robust and displayed a low statistical heterogeneity (I2 = 0%).Three studies, performed on 282,268 patients, evaluated the correlation between HIV infection and TGCTs –33, showThe correlation between HIV-induced immunodeficiency and increased cancer risk has long been known . In immuInterestingly, the majority of men dying of AIDS have hypospermatogenesis, spermatogenic arrest, or a Sertoli-cell-only testicular histology , 76. Thead hoc) in order to provide a methodological quality judgment for each study that may help readers in a proper interpretation of the study findings. However, our results are considerably limited by the small number of patients included in specific comparisons, heterogeneity in the study designs and methods, poor methodological quality of some studies (the majority were retrospective studies), and some concerns about the ascertainment of viral infection. In particular, while some studies used sensitive techniques to test viral infections, other studies, like those ones on HIV, based their results on the detection of serum antibodies. Moreover, only few studies reported the presence of other risk factors for the development of testicular cancer. Therefore, even if a relationship between specific viruses and testicular cancer was detected by the present meta-analysis, causation cannot be established.The present meta-analysis comprehensively evaluates the impact of viral infection on TGCTs risk. We planned sensitivity and subgroup analysis in order to reduce bias related to study heterogeneity. Moreover, we created a modified Newcastle–Ottawa scoring system (We found a possible correlation between specific viruses and testicular cancer, but the evidence was insufficient to establish causality. The correlation between HIV and increased risk of TGCTs is supported by good-quality evidence despite being based on serum antibody titers. Similarly, the evidence suggesting a link between EBV and TGCTs is fair.Regarding the correlation between CMV and TGCTs, available data are conflicting and further studies are needed to draw firm conclusions. Moreover, poor evidence supports the lack of correlation between Parvovirus B-19 and a meaningful risk of TGCTs. Finally, data about the possible relationship between HPV and TGCTs are inconsistent, but its oncogenic potential for male gonadal tissue cannot be excluded; thus, future good-quality studies are warranted.No datasets were generated or analyzed for this study.FM, UV, MG, AA, and GA performed the medline for article search. A manual search of reference lists of studies was performed to avoid missing relevant publications by FM. AG and AV independently assessed the inclusion criteria and study selection. Disagreements were discussed with the third reviewer CF. Data extraction was performed by two independent investigators AG and FM. AV reviewed the selection and data extraction process. The results were then compared, and any disagreement discussed and resolved by consensus of all authors. The draft was written by FM, AV, and AG.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


There is increasing evidence that inflammation-based biomarkers are associated with tumor microenvironment which plays important roles in cancer progression. A high lymphocyte-to-monocyte ratio (LMR), has been suggested to indicate favorable prognoses in various epithelial cancers. We performed a meta-analysis to quantify the prognostic value of LMR in advanced-stage epithelial cancers undergoing various treatment.We searched PubMed, EMBASE, Web of science and Cochrane Library up to July 2018 for relevant studies. We included studies assessing the prognostic impact of pretreatment LMR on clinical outcomes in patients with advanced-stage epithelial cancers. The primary outcome was overall survival (OS) and the secondary outcome was progression free survival (PFS). The summary hazard ratio (HR) and 95% confidence interval (CI) were calculated.P < 0.001) and PFS . The effect of LMR on OS was observed among various tumor types. A higher pretreatment LMR was associated with improved OS in chemotherapy , surgery  and combined therapy  in the subgroup analysis by different therapeutic strategies. The cut-off value for LMR was 3.0 (range = 2.35–5.46). Subgroup analysis according to the cut-off value showed a significant prognostic value of LMR on OS and PFS in both subgroups.A total of 8984 patients from 35 studies were included. A high pretreatment LMR was associated with favorable OS  contains supplementary material, which is available to authorized users. Cancer remains the most threatening disease to human health worldwide . AlthougCurrently, there is increasing evidence that inflammation-based biomarkers are associated with tumor microenvironment –16, whicNumerous studies have reported that the pretreatment LMR is associated with prognosis in various cancers –38. HoweThis meta-analysis was conducted in line with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement . StudiesThe identified studies were selected by two independent reviewers (Mao and Chen). First, the titles and abstracts were screened to assess study the eligibility, and then the full text was reviewed. Any disagreement was resolved by discussion or by a third reviewer (Duan) to reach a consensus. Studies meeting that met the following criteria were included: (1) Studies involving individuals with advanced-stage epithelial tumors and concerning the prognostic value of the pretreatment LMR. The definition of “advanced stage” was derived from the original research from which we extracted data. The timing of assessment of LMR was set at baseline before any treatment was initiated. 2) Studies providing the hazard ratio (HR) with a 95% confidence interval (CI) for overall survival (OS) or progression-free survival (PFS), or indirect information such as Kaplan–Meier curves used to estimate survival data on the basis of the methods previously described  Studies –42. (3) Two reviewers (Mao and Chen) independently carried out the data extraction from the eligible studies. The following information was recorded for each study: first author’s name, year of publication, research region, inclusion period, study design, number of patients, patient age, tumor type, tumor stage, treatment, cut-off value of LMR, time of LMR assessment, follow-up period, study endpoints, analysis of hazard ratios and adjustment variables. The individual HR (with the corresponding 95% CIs) in the studies was also extracted for OS and PFS to assess the therapeutic efficacy. The HRs were preferentially extracted from multivariate analyses. Any discrepancies between reviewers were resolved by consensus. As the previous studies reported , 43, 44,Q test and Higgins I-squared statistic were used to test the heterogeneity of different studies. A P value of less than 0.1 was considered significant. I2> 50% was deemed to show substantial heterogeneity [P less than 0.05.General data were analyzed using Statistical Package for Social Sciences (SPSS) software (version 21.0 for Windows). STATA 12.0 software  was used to conduct the meta-analysis. Cochran’s ogeneity . When thogeneity , 47. Wheogeneity . All staThe flow chart of the literature search is shown in Fig. These studies included a total of 8984 patients with a median age of 60.6 years and a median follow-up period of 26.8 months. Table P < 0.001). Given that the test for heterogeneity was significant , a random-effect model was used. Subgroup analyses were applied to explore potential sources of heterogeneity among several related clinical features for OS (Table I2 = 0%), lung cancer , pancreatic cancer , gastric cancer , nasopharyngeal carcinoma , renal cancer , cervical carcinoma , ovarian cancer , esophageal cancer  and head and neck cancer , but not breast cancer  and hepatocellular carcinoma . To be noted, the subgroup analysis by different therapeutic strategies indicated that a higher pretreatment LMR was associated with improved OS in chemotherapy , surgery , combined therapy  which consists of surgery and (neo)adjuvant therapy. The cut-off values of LMR in the studies ranged from 2.35 to 5.46. After stratifying the cut-off values of LMR into two subgroups, < 3.0 and ≥ 3.0, we noted that the level of statistical heterogeneity  was reduced, while the pooled HRs were not significantly altered. The reduction in statistical heterogeneity was also realized after adjusting research region , number of cases , therapeutic strategies  and follow-up period . Meanwhile, the subgroup analysis by publication year, initial inclusion period, median age, quality score and analysis of HR indicated that a high pretreatment LMR was consistently associated with superior OS.35 studies with 8984 individuals were included in the analysis of pretreatment LMR and OS. Figure P = 0.334; Egger’s test, P < 0.001). The adjusted random effects pooled HRs of 0.578 (95% CI 0.522–0.641), obtained using the trim-and-fill method, which was consistent with our primary analysis . Since the test for heterogeneity was significant , a random-effect model was used. Table I2 = 0%), cervical carcinoma , ovarian cancer  and esophageal cancer  but not lung cancer . A higher pretreatment LMR was proved to be associated with improved PFS in the subgroup analysis by different therapeutic strategies including chemotherapy  and combined therapy . The cut-off values of LMR ranged from 3.11 to 5.28 in different studies. The pooled HRs were not significantly altered by stratifying the cut-off values of LMR into 2 subgroups: ≤ 4.0 and > 4.0, which decreased the level of statistical heterogeneity  nonetheless. It was noted that the significant difference was altered in subgroup analysis by number of cases , therapeutic strategies , follow-up period , quality score  and analysis of hazard ratio . Sensitivity analysis further confirmed that omitting any single study did not significantly affect the pooled HRs, exhibiting good stability of PFS subset  and PFS . Furthermore, subgroup analyses were based on publication year, types of cancers, cut-off value, median age, initial inclusion period, research region, treatment, follow-up period, quality score and analysis of hazard ratio. The association between pretreatment LMR and OS remained mostly constant in various subgroups. Notably, the pooled HRs as well as 95% CI were statistically significant in the subgroups of therapeutic strategies, except for molecular targeted therapy, which may be attributed to the limited number of studies. Therefore, the study revealed that pretreatment LMR might serve as a discriminative indicator for the prognoses of patients who undergo different therapeutic strategies.To our best knowledge, this is the first meta-analysis to evaluate the association between LMR and outcomes of advanced epithelial cancer patients including the search results from 4 available databases online. We included 35 studies comprising 8984 patients with advanced epithelial tumors and found that a high pretreatment LMR was associated with favorable OS  overall survival, (B) overall survival adjusted with trim-and-fill methods.


IGF1) gene has been reported to affect cancer susceptibly in several studies. However, the results of the relevant studies are inconsistent. We conduct a current meta-analysis to investigate the association between rs1520220 and cancer susceptibly.The rs1520220 polymorphism in the insulin-like growth factor 1  were searched for studies regarding the relationship between rs1520220 and cancer susceptibly. Odds ratios (ORs) and the related 95% confidence intervals (CIs) were employed to assess the strength of the associations. A stratified analysis was performed according to cancer type, ethnicity, and quality score, and when results were obtained from no fewer than two studies, these results were pooled.p = 0.040; homozygote model OR = 1.22, 95%Cl = 1.01–1.47, p = 0.040; dominant model OR = 1.19, 95%Cl = 1.01–1.39, p = 0.033). No significantly association was detected in Caucasian populations. The analysis stratified by cancer type suggested that rs1520220 was not associated with susceptibility to breast cancer.There was no positive association between rs1520220 and overall cancer risk. However, the analysis stratified by ethnicity revealed that rs1520220 significantly increased cancer susceptibility in Asian populations  contains supplementary material, which is available to authorized users. The occurrence of cancer depends on both genetic and environmental factors , 2. ReleIGF1 SNPs affect plasma IGF1 levels and thus influence the risk of cancer [IGF1 is a growth factor that involves in many important biological and pathological processes , 9. The f cancer , 15.IGF1 gene which might lead to alternative splicing and a subsequent change in protein function [rs1520220 is located in intron 3 of function . It has function , 17. Howfunction –25. For function , but Li We searched for relevant studies in three databases: PubMed, Embase, and Web of Science. The search conditions limited the language to English and the data of publication prior to February 28, 2018. The following keywords were used: “IGF1 or IGF-1 or insulin-like growth factor 1 or rs1520220,” “cancer or tumor or carcinoma,” and “SNP or polymorphism or variant or mutation.” We also checked the references of the identified articles to ensure that we obtained all potentially relevant studies.The inclusion criteria of this meta-analysis are as follows: studies must (1) concern the relationship between rs1520220 and cancer susceptibility, (2) be case-control or cohort study, and (3) contain sufficient genotyping data to allow for the pooling of the results . The exclusion criteria are as follows: (1) when subjects of two studies overlap, the one containing fewer subjects was excluded, and (2) reviews and meta-analyses are excluded.The following information was extracted from the included studies by two authors independently: first author’s name, year of publication, country, cancer type, ethnicity, genotyping methods, control source, genotype distributions of cases and controls, and Hardy-Weinberg equilibrium (HWE) for controls. Disagreements were resolved via discussion.We assessed the quality of the included studies based on the following five factors : case soQ test and quantified by I2 [P > 0.1), the fixed-effects model was used [P values less than 0.05 were considered to indicate significant disequilibrium. Stratified analyses were conducted by ethnicity, cancer type, and quality score. Only results synthesized from no fewer than two studies are shown. Sensitivity analyses were performed via metainf command which investigates the influence of each individual study on the overall meta-analysis summary estimate by omitting each study in turn [We estimated the strengths of the associations using pooled ORs with corresponding 95% CIs. Five genetic models are employed: the allele model (C vs. G), the homozygote model (CC vs. GG), the heterozygote model (GC vs. GG), the dominant model (CC + GC vs. GG), and the recessive model (CC vs. GC + GG). The heterogeneity was evaluated using a ed by I2 . When hewas used . Otherwiwas used . Hardy-W in turn . Publica in turn , 32. AllWe obtained 2086 relevant articles through database searching after removing duplicates. Then, by screening the titles and abstracts, we excluded 1953 articles, and 133 articles remained. We read the full texts of these 133 articles and ultimately identified eight articles that meet the inclusion criteria . Thus, no significant association was detected in Caucasian populations  and head and neck cancer (HNC) susceptibility in women [IGF1 gene. It has been reported that rs35767 is significantly associated with increased susceptibility of childhood acute lymphoblastic leukemia (ALL) [Several tibility –39. Thesin women . The rs3ia (ALL)  and thatia (ALL) .IGF1 gene, and it has a minor allele frequency (MAF) about 10~ 40% in the populations included in the human 1000 Genomic Project phase 3 . After removing duplicate documents, 2086 related articles were initially obtained, which ensured the maximum possible recall rate. Through meta-analysis, we found that rs1520220 was not related to cancer susceptibility in the overall analysis based on the present epidemiology studies. Thus, in the analysis stratified by ethnicity, we revealed that rs1520220 increased cancer susceptibility in Asian populations.In this meta-analysis, we systematically searched for literature on IGF1 rs1520220 polymorphism on serum IGF1 are inconsistent [The present studies regarding the effect of nsistent , 18. In nsistent , and thinsistent . TherefoOur meta-analysis has several limitations. Firstly, we found that rs1520220 increased cancer susceptibility in Asians. The molecular mechanism via which the rs1520220 C allele increases plasma IGF1 levels and thus cancer risk remains unclear. Secondly, we did not consider potential external factors, such as gender, age, diet, and tobacco and alcohol intake habits or gene-gene interactions. Thirdly, the number of studies included in the meta-analysis is limited. We only included studies written in English, and important-related studies in other languages may have been overlooked.IGF1 rs1520220 is not significantly associated with overall cancer susceptibility. However, we did find that rs1520220 significantly increased cancer susceptibility in Asian populations. We also suggest that rs1520220 was not associated with susceptibility to breast cancer. There is a need for additional well-designed epidemiology and molecular biology studies to verify these conclusions and provide new insights into the role of SNPs in the etiology of cancer.The present meta-analysis showed that Additional file 1:Table S1. Quality score assessment. Table S2. Sensitivity analyses for IGF1 rs1520220 polymorphism and cancer susceptibility. Table S3. MAFs of IGF1 rs1520220 polymorphism in the populations from the 1000 Genomes Project Phase 3. (DOCX 30 kb)