To evaluate whether urinary iodine concentration (UIC) can predict goiter among school-age children, and to assess the association between UIC and goiter prevalence.We searched the MEDLINE, EMBASE, Cochrane Library (Cochrane Database of Systematic Reviews), Web of Science, CNKI, VIP, and Wan Fang databases for relevant reports in both English and Chinese up to August 25, 2016. The mean differences (MD) and 95% confidence intervals (CI) were calculated for the UIC and goiter prevalence assessments. Pooled odds ratios and 95% CIs were used to compare the prevalences of goiter in the different UIC groups.We identified 11 case-control studies, and found that children with goiter had lower UIC values, compared to children without goiter . An increased risk of goiter was associated with UIC values of < 20 μg/L or > 200 μg/L.The results of our meta-analysis suggest that lower UIC values were associated with an increased risk of goiter, and that iodine deficiency may lead to an increased risk of goiter. Furthermore, we observed U-shaped relationships between UIC and the prevalence of goiter, which suggests that both severe iodine deficiency and excessive iodine intake may lead to increased risks of goiter. Goiter remains an important public health concern, especially in developing countries –3. DurinThe measurement of urinary iodine concentration (UIC) in casual urine specimens is recommended for monitoring iodine status . In addiAs goiter formation reflects chronic iodine deficiency or excess, it can be used as a baseline assessment of a region’s iodine status , and goiThe present meta-analysis aimed to evaluate the evidence regarding whether UIC could predict goiter among school-age children, and to assess the goiter prevalences in different UIC groups.The present meta-analysis was performed according to the PRISMA guidelines  and the The inclusion criteria were studies that: (a) assessed and reported UIC among school-age children with and without goiter, (b) compared the prevalences of goiter in different UIC groups based on the WHO categories, (c) used a case-control or cohort design, and (d) evaluated school-age children (6–18 years old). We excluded studies that did not fulfill the inclusion criteria, and also excluded conference abstracts and animal experimental studies.The following data were extracted from the included studies: (a) first author, (b) publication and study year, (c) study location, (d) study design, (e) sample size and number of goiter cases, (f) UIC values from children with and without goiter, and (g) the prevalences of goiter in the different UIC groups . The extracted data were entered into an Excel file and Review Manager software by two of the authors.The quality of the included studies was assessed using the Newcastle-Ottawa Scale .Meta-analyses were used to provide overall estimates of UIC among children with and without goiter, and to compare the prevalences of goiter in the different UIC groups. The mean differences (MD) and 95% confidence intervals (CI) were calculated for the UIC and goiter prevalence data. The assumption of heterogeneity was assessed, and heterogeneity was considered present at a p-value of <0.1. To compare the prevalences of goiter in the different UIC groups, we calculated the pooled odds ratios (ORs) and 95% CIs. All analyses were performed using Review Manager software (version 5.3), and differences were considered statistically significant at p-values of <0.05.Our literature search identified 560 potentially relevant reports that were published up to August 25, 2016, and we also identified five other studies from the reports’ reference lists. However, we excluded 116 reports because of duplication, 316 reports because they were unrelated to the aim of this meta-analysis, and 122 reports for failing to fulfill the inclusion criteria after a review of the full text . A total of 11 studies fulfilled our inclusion criteria and were included in the meta-analysis . The selThe basic characteristics of the 11 included studies are shown in Eight studies –22, 26 r2 value of 99%, which confirmed that significant heterogeneity was present. Possible explanations for the heterogeneity include the studies evaluating different races and ethnicities, the different sample sizes, differences in the laboratory tests for determining UIC, and the possible effects of regional economic and cultural differences.As shown in 2 = 99%; p < 0.05).The pooled results from the comparison of UIC between children with and without goiter are shown in We observed a U-shaped association between the UIC values and the prevalence of goiter. The pooled results for these comparison revealed increasing risks of goiter at both high UIC values (>200 μg/L) and low UIC values (<20 μg/L): <20 μg/L vs. >20 μg/L , <50 μg/L vs. >50 μg/L , <100 μg/L vs. >100 μg/L , <200 μg/L vs. >200 μg/L , and <300 μg/L vs. >300 μg/L .Iodine is an essential micronutrient that is required to synthesize thyroid hormones, and universal salt iodization is considered an appropriate method for iodine fortification in developed countries . HoweverWe evaluated 11 case-control studies in the present meta-analysis, and found that children with goiter had significantly lower UIC values, compared to children without goiter, which indicates that lower UIC values were associated with an increased risk of goiter. Furthermore, as UIC is a reliable indicator for assessing population-level iodine status, it appears that iodine deficiency may lead to an increased risk of goiter. Similarly, an epidemical study has suggested that approximately 2.2 billion people live in areas with iodine deficiency and 30–70% of these people have goiter , 23, 31.Based on the strong relationship between iodine status and goiter formation, it is important to evaluate the relationship between iodine status and goiter prevalence. Thus, we compared the prevalences of goiter among the different UIC groups based on the WHO classifications. This analysis revealed a U-shaped association between UIC and goiter prevalence, with higher prevalences observed at UIC values of <20 μg/L and >200 μg/L. Therefore, it appears that both severe iodine deficiency and excessive iodine intake may increase the risk of goiter, and this finding is consistent with the WHO recommended range for adequate iodine intake (100–199 μg/L).Our meta-analysis has several strengths. First, most of the previous studies have focused on adults, rather than children. However, children are more sensitive to iodine deficiency or excess, and goiter or thyroid nodules are more frequently malignant during childhood, compared to during adulthood  , 33. SecOur meta-analysis also has several limitations. First, we did not have access to thyroid volume data, although thyroid gland inspection and palpation has been endorsed as part of the WHO criteria . Thus, wS1 Table(DOC)Click here for additional data file.S2 Table(XLS)Click here for additional data file.


NOD2 (nucleotide-binding oligomerisation domain containing 2), an intracellular sensor of bacteria-derived muramyl dipeptide, was the first genetic association discovered in CD and remains one of the strongest associations  is a common form of chronic inflammatory bowel disease (IBD) affecting 21–294 per 100,000 in European populations . It arisciations . The mecntestine . The thrntestine .Several environmental factors have been postulated in CD, but the most consistent epidemiological evidence points to a clear risk associated with cigarette smoking. Two meta-analyses reveal that current smokers are up to twice as likely to develop CD as non-smokers (OR = 1.8–2.0) . CigaretNOD2 mRNA expression leading to the impairment of NOD2 functioning in intestinal epithelial cells . This is the first comprehensive systematic review and meta-analysis of the interaction between NOD2 and cigarette smoking in CD. Whilst it is clear that smoking and NOD2 variants increase the risk of CD independently, there is conflicting evidence for their interaction with some studies suggesting a positive interaction, a negative interaction or no interaction. The discordant findings could be explained by the fact that the majority of previous NOD2/smoking studies were underpowered to detect an interaction. Based on a large literature review and meta-analysis, the authors conclude that only one of the three known CD risk variants in NOD2 (1007fs) shows an interaction with smoking exposure and more importantly, this interaction is negative. They subsequently explore this relationship in more detail in a case series of 627 patients which confirms the negative interaction. They suggest this is due to the inverse relationship between NOD2 prevalence (increased in younger patients with CD) and smoking exposure (increased in older patients with CD) with increasing age of onset. It is important to point out that the authors could not restrict their analysis to individual age groups and hence, they were not able to adjust age as a confounder. However, a similar significant negative interaction between smoking and NOD2 was demonstrated in a previous study by NOD2 polymorphism is smaller than expected under a multiplicative model.NOD2 variant carriers would be higher than in those with wild-type NOD2 (The complexity of identifying gene-environment interactions for Crohn's disease should be acknowledged. It is important to understand the design of the studies and the methodical implications of grouping multiple genetic variants into a single analysis. Helbig et al. were the first to use a case-only design to explore statistical interaction and the current meta-analysis adopted a similar design. A multiplicative interaction as demonstrated here does not indicate which group is at a higher absolute risk from the environmental exposure; case-only studies cannot be used to assess for additive interactions, and it remains possible that the absolute risk of smoking in ype NOD2 .NOD2 and smoking are associated with ileal CD and furthermore, ileal and colonic CD have been shown to be in part genetically-determined phenotypes (The similar results obtained from the two quoted studies are intriguing and point to the importance of assessing genetic and environmental factors in sub-phenotypes of CD. In addition to age, disease location, disease behaviour and other subphenotypes may influence gene-environment interactions. Both enotypes .Further epidemiological and functional studies are needed to fully explore the mechanistic gene-environment interactions in patients with CD. They need to be adequately powered to assess SNP-specific interactions. The current meta-analysis provides a platform for further research in the field of precision medicine which will enable clinicians to develop personalised recommendations for individuals at high risk of developing CD.The authors declared no conflicts of interest.


The contribution of genetic variants in RhoA and ROCK1 genes towards prostate cancer risk has not been reported before. We genotyped six potentially functional genetic variants in a case-control study of 1699 subjects. Overall, we found rs2410 mutant allele and rs2269736 wild allele were risk factors for prostate cancer. Individuals carrying more than two risk alleles were exposed to hazard of prostate cancer. In addition, we demonstrated that the risk of biochemical recurrence might be linked with clinico-pathological characteristics and also genetic factors. Unfortunately, no associations were observed between all polymorphisms and clinico-pathological characteristics. Moreover, no genotype was found as significant independent prognostic predictor for biochemical recurrence survival in Multivariate Cox regression analysis after Bonferroni correction. Our study is the first to clarify the relations of genetic variants of RhoA and ROCK1 genes with development, progression and prognosis of prostate cancer. These variants may be promising novel biomarkers to facilitate clinical treatment decision-making. Prostate cancer (PCa) is a multifactorial and complex disease . In the Small guanosine triphosphate hydrolases (GTPase) of the Ras homology (Rho) family work as molecular switches in a wide variety of signal transduction pathways that regulate diverse cellular functions . RhoA, aMany lines of evidence have proved that RhoA/ROCK1 signaling pathway participates in PCa pathogenesis. Somlyo AV and colleagues stated that invasiveness of human PCa was facilitated by the Rho/ROCK1 pathway and inhibition of RhoA or its interacting protein ROCK1 might diminish motility of PCa cells . SimilarHowever, the contribution of genetic variants in RhoA and ROCK1 genes towards the risk of PCa has not been reported. Given the significant role of RhoA and ROCK1 in the development of PCa, we conceived genetic variants in RhoA/ROCK1 signaling pathway as appropriate biomarkers of PCa. To verify this hypothesis, we selected six potentially functional single nucleotide polymorphisms (SNPs) in RhoA and ROCK1 genes to detect whether these genetic variants could forecast progression and recurrence of PCa.P = 0.002 and P = 0.040, respectively). Moreover, in comparison with the controls, a significantly higher proportion of the PCa patients had family history of cancer (P < 0.001). Among cases, 498 (60.0%) patients were in the localized stage and 332 (40.0%) patients were in the advanced stage. The percent of subjects in Gleason score < 7, = 7 and > 7 subgroups was 28.1%, 36.4% and 35.5%, respectively. Furthermore, 58.2% of 830 patients had a PSA level greater than 20 ng/ml, whereas, 20.7% and 21.1% patients had a level between 10 ng/ml to 20 ng/ml and less than 20 ng/ml, respectively.The demographic characteristics and the clinical information of 830 PCa patients and 869 controls were summarized in Table P > 0.05). Overall, the single loci analysis only demonstrated that the genotype frequency of RhoA rs2269736 was crucially different between the cases and controls (P < 0.001). Moreover, for RhoA rs2269736, multivariate logistic regression analysis also revealed that the genotype and allele distributions were remarkably different between cases and controls in the heterozygote model , the homozygote model , the dominant model  and the allele comparison . Additionally, multivariate logistic regression analysis indicated that individuals carrying RhoA rs2410 CC genotype had a significantly higher incidence of PCa than those carrying AA genotype. However, such conclusion in RhoA rs2410 was not established with Bonferroni correction. Unfortunately, P value was adjusted as 0.05/3 with Bonferroni correction, and no positive relationships with PCa risk were detected in RhoA rs2410, RhoA rs2625955, ROCK1 rs11874761, ROCK1 rs35996865 and ROCK1 rs8089974.Genotype distributions and allele frequencies of these polymorphisms in cases and controls were listed in Table Considering latent combined effects from different variants or genotypes and potential interactions of RhoA gene polymorphism on the risk of PCa, we combined these two tSNPs based on the numbers of risk alleles . As shown in Table P value was adjusted as 0.05/9 with Bonferroni correction, such conclusions were also tenable.We then conducted combined genotype analysis to further probe underlying combined effects in the development of PCa. The outcomes of combined genotype analysis were outlined in Table P value adjusted as 0.05/3, such conclusions were invalid in some subgroups of particular genes.Although not all genetic variants in RhoA and ROCK1 genes were proved to be related to overall risk of PCa, we further conducted subgroup analysis stratified by age, smoke status, Pack-years of smoking, drink status, tea drinking, family history of cancer, hypertension and diabetes. All results of stratification analysis were summarized in Similarly, we performed stratified analysis to survey the relationship between the numbers of risk alleles and PCa susceptibility Table . As a reWe further conducted stratified analysis among PCa patients according to some disease-related clinical features including clinical stage, Gleason score and PSA level. Regrettably, no statistical evidence was explored for any interactions between single SNPs or combined genotypes with PCa risk .In order to seek possible effects of RhoA/ROCK1 polymorphisms on PCa prognosis, we conducted analysis of BCR in a cohort of 289 patients who accepted radical prostatectomy. All clinico-pathological characteristics of study populations were shown in P value adjusted as 0.05/3, the relationship between rs35996865 and BCR was invalid.Kaplan-Meier curves were used to study biochemical recurrence-free survival across known risk factors for BCR. As expected, the risk of BCR was greatly linked with clinico-pathological characteristics . GeneralP = 0.030). Simultaneously, we combined rs2269736 with rs35996865 and observed meaningful difference between BCR survival of patients with number of risk allele. The results revealed individuals with more risk alleles had poorer prognoses. Unfortunately, the results were insignificant after Bonferroni correction.We further performed multivariate Cox proportional hazard analysis for BCR of PCa patients. Table Recently, the RhoA/ROCK1 signaling pathway has received considerable attention for its involvement in tumor formation and progression. To date, the level of RhoA expression was proved to increase in skin, gastric, testicular cancer and so on –24. LikeIn this study, we observed subjects carrying mutant C allele of rs2410 were liable to develop PCa while those with mutant G allele of rs2269736 and mutant T allele of rs35996865 were relatively safe. Some possible explanations may account for these results. Angiogenesis is regarded as one of the hallmarks of tumor initiation and progression, which depends on the homeostatic balance between pro-angiogenic and anti-angiogenic factors . Tumor cFurthermore, we combined genotypes of two polymorphism loci in RhoA and observed a protective effect of CCGG genotype. Theoretically, subjects carrying CCAA joint genotype were apt to suffer from PCa while those with AAGG genotype were safest. However, we only perceived that AAGG joint genotype had a boundary protective effect. We supposed that different genetic variations had discrepant capacities or powers to affect PCa susceptibility. Apparently, rs2269736 mutant allele had stronger protective effect than rs2410 wild allele. Besides, relatively small sample size in each joint genotype could not be overlooked. To reduce interference of small sample size, we combined risk alleles and found only individuals with 3 or 4 risk alleles were at high risk of PCa. We conjectured that individuals with 1 or 2 rs2410 risk alleles carried rs2269736 mutant alleles at the same time, which counteracted risk effect of rs2410 mutant alleles and further caused those people with less than 2 risk alleles were not associated with increased hazard of PCa. We thought these outcomes were consistent with results of joint genotype analysis. Combined analysis may provide a more comprehensive prediction of genetic susceptibility. Nevertheless, it is universally accepted that PCa is a complex malignancy arose from multifactor. Results of further subgroup analysis suggested that single loci polymorphisms and the combined effect were more pronounced in some specific population groups, which indicated that genetic effects on PCa susceptibility may be interfered by age, physical condition and environment exposure. Further study with larger sample size should be conducted to draw more convinced conclusion.As we mentioned above, the RhoA/ROCK signaling pathway was closely related with MVD, angiogenesis and VEGF. Bono AV and his colleagues declared that MVD counts were associated with PCa progression and might potentially predict outcome in patients undergoing RP . AnotherCampa M et al. reported identification of functional membrane androgen receptors (mAR) and found its activation could induce rapid actin cytoskeleton reorganization and increased secretion of PSA. Recently, their research team indicated that RhoA and ROCK1 were major mAR effectors adjusting actin reorganization and apoptosis in PCa cells . AccordiP value as 0.05. Though, no statistical significance was detected in some new findings with Bonferroni correction, further studies with larger sample size were required to confirm such results.Remarkably, Bonferroni correction was utilized in our study. As strict correction method, it is one of the most important methods used to address false discovery rates resulting from multiple testing. The Bonferroni correction acts as conservative method and adjusts the value of alpha according to the number of tests performed. Moreover, truly significant differences may be deemed non-significant because of type II errors . AccordiTaken together, the results in our present study provided new insight into genetic variants in RhoA/ROCK1 signaling pathway and their function in prostate cancer. We believed our findings were helpful to clinical diagnosis and prediction of prostate cancer. Also, our study gave rise to the idea that meaningful SNPs in RhoA/ROCK1 pathway and some combined genotypes might be favorable biomarkers for PCa prognosis, which guided clinicians to formulate individualized therapy regimen. However, some limitations of this study should be noted. Firstly, to apply new markers in the clinical practice needs complicated steps and diverse validation analyses. More studies on expression and activity of the RhoA/ROCK1 pathway in subjects with different genotypes are indispensible. Secondly, our findings merit further evaluation in larger series of PCa patients from different regions, taking into account that prostate cancer is a heterogeneous illness with multiple confounders. Moreover, Bonferroni correction was utilized in our study. Though, no statistical significance was detected in some genotypes or subgroups with Bonferroni correction, further studies with larger sample size were required to confirm such results. Last but not the least, lack of detailed data of survival and other risk factors from patients limits further in-depth investigation.To sum up, to our knowledge, the current study firstly provided evidences to certify genetic variants in the RhoA/ROCK1 pathway, especially rs2269736 and combined risk alleles may be promising novel predictors to forecast development, progression and prognosis of prostate cancer. Undoubtedly, the conclusions may broaden our horizons in the biological basis of carcinogenesis of prostate cancer and be beneficial to offer patients reasonable treatment.We prospectively recruited 830 patients with histopathologically confirmed PCa and a group of 869 cancer free controls who sought routine outpatient care between September 2003 and January 2013 from The First Hospital of Nanjing Medical University, Nanjing, China. All these subjects were genetically unrelated Han Chinese. All controls had no history of other cancers and were matched on age to the cases. Before recruitment, a standard questionnaire was administered through face-to-face interviews by well-trained interviewers to collect demographic data, clinical data and related factors. The definitions of subgroups were described in our previous paper . The cli2 = 1), only one SNP was selected for genotyping. Genomic DNA was extracted from the peripheral blood by proteinase K digestion and phenol–chloroform extraction. Before genotyping, we conducted DNA quality control and made sure that all DNA samples were qualified. Genotyping was performed with the TaqMan SNP Genotyping Assay using the 384-well ABI 7900HT real-time PCR system . The tSNPs information, sequences of primers and probes of each SNP were available as requested. Negative controls were included in each plate to ensure accuracy of the genotyping. Two investigators conducted genotyping independently in a blinded manner. Finally, about 10% of the DNA samples were randomly chose for repeated genotyping for confirmation, and the results were 100% concordant.We chose 3 potentially functional tSNPs in RhoA gene  and 3 tSNPs in ROCK1 gene  according to HapMap data  and the Haploview 4.2 software  . All sel2 and r2 value for linkage disequilibrium (LD) between the two polymorphisms were estimated by the Haploview software version 4.2. The Bonferroni correction is one of the most frequently-used methods, and aims to address false discovery rates caused by multiple testing. Accordingly, all P values were Bonferroni corrected, and statistical significance was set at P < 0.01667  or P < 0.00556 . All statistical tests were two-sided. All the statistical analyses were performed with the Stata software  or SPSS version 17.0 for Windows .Deviation of genotype distribution from the Hardy–Weinberg equilibrium (HWE) for all polymorphisms among the controls was tested by a goodness-of-fit chi-square test. Differences in the distributions of demographic characteristics, selected variables, and frequencies of genotypes between cases and controls were analyzed using the Student's t-test (for continuous variables) or chi-square test . The associations between polymorphisms and risk of PCa were estimated by computing odds ratios (ORs) and 95% confidence intervals (CIs) from unconditional logistic regression analysis with the adjustment for possible confounders. Biochemical recurrence was defined as a rise in serum PSA level 0.2 ng/ml after RP. To study BCR-free survival, time was calculated from date of RP to date of BCR or last follow up. The different recurrence times according to demographic characteristics, clinical features, and RhoA/ROCK1 polymorphisms were evaluated by Kaplan–Meier method and compared by the log-rank test. Univariate and multivariate analyses were performed using Cox proportional hazard models to determine the association between polymorphisms and PCa biochemical recurrence and to estimate adjusted Hazard Ratios (HRs) and 95% CIs with adjustment for possible confounders. D


LINC00673 rs11655237 C>T polymorphism to be associated with the susceptibility of several malignant tumors. However, the association between this polymorphism and neuroblastoma susceptibility is not clear. We genotyped LINC00673 rs11655237 C>T in 393 neuroblastoma patients in comparison with 812 age-, gender-, and ethnicity-matched healthy controls. We found a significant association between the LINC00673 rs11655237 C>T polymorphism and neuroblastoma risk (TT compared with CC: adjusted odds ratio (OR) =1.80, 95% confidence interval (CI) =1.06–3.06, P=0.029; TT/CT compared with CC: adjusted OR =1.31, 95% CI =1.02–1.67, P=0.033; and T compared with C: adjusted OR =1.29, 95% CI =1.06–1.58, P=0.013). Furthermore, stratified analysis indicated that the rs11655237 T allele carriers were associated with increased neuroblastoma risk for patients with tumor originating from the adrenal gland  and International Neuroblastoma Staging System (INSS) stage IV disease . In conclusion, we verified that the LINC00673 rs11655237 C>T polymorphism might be associated with neuroblastoma susceptibility. Prospective studies with a large sample size and different ethnicities are needed to validate our findings.Neuroblastoma, which accounts for approximately 10% of all pediatric cancer-related deaths, has become a therapeutic challenge and global burden attributed to poor outcomes and mortality rates of its high-risk form. Previous genome-wide association studies (GWASs) identified the  Neuroblastoma, originating from the developing sympathetic nervous system, is the most common extracranial tumor of infancy and childhood. The median age at diagnosis is approximately 18 months  and contLINC00673 rs11655237 C>T  polymorphism at 17q25.1 region to be significantly associated with the risk of pancreatic cancer [LINC00673 [LINC00673 forms a target site for miR-1231 binding, which weakens the tumor suppressing function of LINC00673 in an allele-specific manner and thus endows pancreatic cancer with susceptibility [LINC00673 has been identified to be associated with non-small-cell lung cancer (NSCLC) [LINC00673 rs11655237 appears to be implicated in the development of broad-spectrum tumors and also involved in cell homeostasis maintenance. However, the association between neuroblastoma susceptibility and LINC00673 rs11655237, is not yet reported.Previous genome-wide association studies (GWASs) of pancreatic ductal adenocarcinoma have identified a long intergenic non-coding RNA (lincRNA) c cancer . It was INC00673 . Furthertibility . Moreove (NSCLC) , gastric (NSCLC) , tongue  (NSCLC) , and breLINC00673 rs11655237 C>T polymorphism on neuroblastoma susceptibility, we performed a hospital-based case–control study using data from a Chinese Han population composed of 393 neuroblastoma cases and 812 age-, gender-, ethnicity-matched cancer-free controls.To comprehensively evaluate and provide new insights into the impact of The subjects included were described in our previous studies –20. A toLINC00673 rs11655237 C>T polymorphism was carried out in a 384-well plate using TaqMan Real-Time PCR method as described elsewhere [DNA samples were extracted as previously described . Brieflylsewhere –24. For P-values <0.05 were considered as statistically significant. All statistical analyses were two-sided and were calculated by SAS software .Comparison of the differences in the demographic and genotypic information between neuroblastoma cases and controls was performed by chi-square test. Hardy–Weinberg equilibrium for controls was analyzed by goodness-of-fit chi-square test. To estimate the strength of association between rs11655237 C>T polymorphism and neuroblastoma risk, unconditional univariate and multivariate logistic regression analyses were conducted and adjusted for age and gender, while odds ratios (ORs) and 95% confidence intervals (CIs) were used. Further stratified analysis was performed by age, gender, the International Neuroblastoma Staging System (INSS) clinical stages , and tumP=0.229, P=0.484, P=0.437) and gender  for Guangdong, Henan, and combined subjects, respectively. According to the INSS criteria, 69 (17.56%), 93 (23.66%), 68 (17.30%), 143 (36.39%), and 11 (2.80%) patients were diagnosed with clinical stages I, II, III, IV, and 4s disease, respectively. With respect to tumor sites, 153 (38.93%) neuroblastomas occurred in the adrenal glands, 87 (22.14%) in retroperitoneal regions, 109 (27.74%) in the mediastinum, and 36 (9.16%) in other regions.The demographic characteristics of the included participants are summarized in Supplementary Table S1. No statistically significant differences were observed between neuroblastoma cases and controls regarding age , especially mutated-type homozygote carriers , were significantly associated with an increased risk of neuroblastoma when compared with wild-type homozygote carriers.The P=0.021). Furthermore, we also found that the carriers of the CT/TT genotypes had a significantly increased risk of INSS clinical stage IV disease  when compared with the carriers of the CC genotype.Next, the included participants were stratified by age, gender, tumor sites, and INSS stages. We further estimated the effects of the variant genotype of the rs11655237 C>T polymorphism on the neuroblastoma risk amongst the different strata . We founLINC00673 rs11655237 C>T polymorphism with neuroblastoma susceptibility in 393 patients and 812 cancer-free controls. Our results revealed that the rs11655237 T allele significantly increased the risk of neuroblastoma. In addition, stratified analysis showed that the rs11655237 C>T polymorphism increased the risk of adrenal gland and clinical stage IV neuroblastoma. The results from the present study suggested that the rs11655237 T allele was positively associated with neuroblastoma and could confer neuroblastoma susceptibility.In this hospital-based case–control study, we evaluated the association of the GWAS-identified H19 [KCNQ1OT1 [MALAT1 [HOTAIR [COLDAIR [XIST [PTENP1 [Described as the largest subclass in the non-coding transcriptome in humans, lincRNAs are non-coding transcripts longer than 200 nts. In the past decade, the roles of lincRNAs in human disorders, including tumors, have attracted a lot of attention ,27. lincH19  and KCNQKCNQ1OT1 ), metast [MALAT1 , HOTAIR  [HOTAIR , and COL[COLDAIR ), X inacIR [XIST ), dereguIR [XIST , and pse [PTENP1 ). TherefLINC00673 is located at 17q24.3, which is a chromosome region recently documented to have a high frequency of loss of heterozygosity [LINC00673 rs11655237 variant, a germline C>T transition, can lead to a decrease in the level of LINC00673 in cells, which may trigger SRC-ERK oncogenic signaling, while attenuating STAT1-dependent anti-oncogenic signaling. Consistent with these functional discoveries, researchers have observed significantly decreased pancreatic ductal adenocarcinoma susceptibility in the rs11655237 C allele carriers when compared with the rs116552337 T allele carriers [LINC00673 has been proven to be associated with susceptibility, progression, and outcome of other malignancies as either a tumor suppressor or promoter. Shi et al. [LINC00673 can promote tumor proliferation through LSD1 interaction and repression of Neurocalcin δ in NSCLC, which implied LINC00673 as an oncogene in NSCLC. For the first time, Ma et al. [LINC00673 promoted NSCLC metastasis by binding with EZH2 that resulted in epigenetic silencing of HOXA5. The latter is a tumor suppressor gene that inhibits NSCLC cell metastasis via regulating cytoskeletal remodeling. Lu et al. [LINC00673 regulated NSCLC proliferation, invasion, migration, and even epithelial–mesenchymal transition by sponging miR-150-5p. A study by Abdul-Rahman et al. [LINC00673 levels were modulated by hormone signaling and inversely associated with breast cancer survival. Huang et al. [LINC00673 was significantly up-regulated in gastric cancer. LINC00673 overexpression induced cell proliferation and invasion and inhibited cell apoptosis. Research conducted by Yu et al. [LINC00673 was highly expressed in a significant proportion of human tongue squamous cell carcinoma samples and associated with poor prognosis.zygosity , and is zygosity . Furthercarriers ,38. Intri et al.  found tha et al.  showed tg et al.  reportedLINC00673 and malignancies. Therefore, it would be interesting to examine the role of LINC00673 in neuroblastoma. With such purpose, we conducted the current study in the Chinese Han population. The current study has several important strengths. To the best of our knowledge, this is the first investigation to validate the association of neuroblastoma susceptibility with GWAS-identified polymorphism within LINC00673. The identification of LINC00673 as an antitumor factor in neuroblastoma was based on discoveries in GWASs in several tumors. Although our findings showed that the association between rs11655237 and neuroblastoma susceptibility were obtained in Chinese Han populations and are consistent with previous reports in other malignancies, further studies on this and other tumors in a different ethnic group would be beneficial. In addition, it has been suggested that rs11655237 might have a potential role in the regulation of gene expression via an enhancer, promoter, or silencer mechanism [in vivo experimental settings.Taken together, these findings shed light on an important functional interaction between echanism . TherefoLINC00673 and neuroblastoma, we included only 393 neuroblastoma cases and 812 cancer-free controls. The relative small sample size may limit the statistical power. Replication studies from other centers with a larger sample size are encouraged to confirm the association. Second, only one polymorphism of the newly identified LINC00673 was investigated in the current study. More polymorphisms, especially the potentially functional polymorphisms not yet contained in previous GWASs, remain to be explored. Third, due to the design of the retrospective study, information bias and selection bias might be unavoidable. Because of the lack of information on dietary intake, living environmental factors, and parental exposures, only frequency matching of neuroblastoma cases and controls by age and gender could be used to reduce these biases. Fourth, in vitro and in vivo experiments should be performed to interrogate mechanism(s) underlying the association in the future. Finally, although recruited from two centers, including residents in Southern and Northern China, participants were all Han Chinese, so the results should be cautiously extrapolated to other ethnic groups.Several limitations should be addressed in the present study. First, although it was the first study on the association between LINC00673 rs11655237 C>T polymorphism was significantly associated with neuroblastoma susceptibility in the Chinese Han population, especially for children with neuroblastoma of the adrenal gland region and clinical stage IV. In the future, well-designed prospective studies with larger sample size including different ethnic populations, detailed information  and functional studies should be performed to strengthen our findings.In conclusion, our results verified that the


Objective: Previous studies have reported that rs523349 (V89L) and rs9282858 (A49T) polymorphisms in the gene 5α-reductase II (SRD5A2) are associated with the risk of benign prostatic hyperplasia (BPH), but different opinions have emerged. In view of distinct discrepancies among those findings, we performed this meta-analysis to ascertain a more accurate association between SRD5A2 rs523349 and rs9282858 polymorphisms and the risk of BPH.Methods: Studies investigating the association between SRD5A2 rs523349 and rs9282858 polymorphisms and susceptibility to BPH were searched from the databases of PubMed, Embase, Wanfang, and Chinese National Knowledge Infrastructure (CNKI).The strength of correlation was assessed by crude odds ratios (ORs) with their corresponding 95% confidence intervals (95% CIs). Moreover, subgroup analysis was conducted to further ascertain such relationship and investigate sources of heterogeneity.Results:SRD5A2 rs9282858 (A49T) polymorphism showed a significant correlation with increased BPH susceptibility under allele T vs.allele A genetic model  in total analysis, and stratification analysis by ethnicity also revealed a similar association in Caucasian group under the same contrast. SRD5A2 rs523349 (V89L) polymorphism showed no significant role in BPH occurrence in total analysis, but its reducing and increasing effects on the disease risk were reflected in Caucasian and other-ethnicity subgroups, respectively, after stratification analysis by ethnicity.Conclusion: In conclusion, SRD5A2 rs9282858 polymorphism may elevate the susceptibility to BPH, while the polymorphism rs523349 may exert different influences on the disease in people of different ethnic lines. Benign prostatic hyperplasia (BPH) is one of the most common diseases in men over 60 years old in western world  gene  polymorphism increased the SRD5A2 enzyme activity by about 5-fold, whereas the rs523349 (V89L) polymorphism was associated with approximately 40% lower SRD5A2 activity , have been suggested to be involved in the occurrence of BPH  in BPH susceptibility, this meta-analysis incorporating a total of 1,865 cases and 1,424 controls was carried out.SRD5A2 rs523349 and/or rs9282858 polymorphisms on risk of BPH using search terms as follows: “SRD5A2” or “5α-reductase type 2,” “BPH” or “benign prostatic hyperplasia,” and “polymorphism” or “variant” or “variation” or “SNP.” Bibliographies of all pertinent articles were also manually checked for other relevant articles.An extensive literature search was performed in PubMed, Embase, Wanfang, and Chinese National Knowledge Infrastructure (CNKI) databases to identify studies examining the impact of SRD5A2 polymorphisms or BPH; and (3) abstract, reviews, case reports, and comments. When overlapping data were contained in more than one publication, the one with the largest number of objects was selected.Eligible studies should accord with the following criteria: (1) containing original data; (2) published in English or Chinese language; (3) including sufficient data on genotype and/or allele distribution in cases and controls; and (4) with a case-control design. Studies were excluded for the following reasons: (1) with no control subjects; (2) not about P-value for Hardy-Weinberg Equilibrium (HWE) in controls. Any discrepancies over recorded information were resolved through discussion between the two authors until a final consensus was reached.Two authors independently reviewed the included studies and extracted essential data from them. The collected information included: first author's name, publication year, country, ethnicity, source of control, studied polymorphism(s), genotyping method, sample size, genotype and/or allele distribution in both case and control groups, and SRD5A2 rs523349 and rs9282858 polymorphisms on BPH risk. Whether genotype distribution in control group was in accordance with HWE expectation was determined by Chi-square test. Significance of summary ORs was examined using Z test. Heterogeneity between studies was assessed with Chi-Square based Q-statistical test. P-value smaller than 0.05 in Q test indicated significant heterogeneity, and random-effects model was applied for OR estimation in this case; otherwise, fixed-effects model was utilized. For SRD5A2 rs523349 (V89L) polymorphism, this meta-analysis examined the association between allele L and BPH risk compared with that for allele V (L vs. V), homozygote LL was contrasted with VV (LL vs. VV), heterozygote VL was contrasted with VV (VL vs. VV); meanwhile, dominant (LL + VL vs. VV) and recessive (LL vs. VL+VV) models were also used, so was rs9282858 (A49T). Moreover, subgroup analysis was conducted to further ascertain such relationship and investigate sources of heterogeneity. The effect of single studies on overall estimates was evaluated using one-way sensitivity analysis for studied polymorphism(s) on which more than 5 studies concerned. In addition, Begg's funnel plot and Egger's linear regression test were performed for inspecting potential publication bias among included studies, the number of which was more than 5. All P-values were two-sided, with P < 0.05 suggesting statistical significance.STATA software version 12.0 was used to conduct all data syntheses in this meta-analysis. Crude odds ratios (ORs) with their corresponding 95% confidence intervals (95% CIs) were calculated to evaluate the effects of SRD5A2 polymorphisms, 5 were drug dose researches, 2 were duplicate reports, and another 2 contained insufficient data. As a result, 1,865 cases and 1,424 controls were included in the present meta-analysis  polymorphism, an increased BPH risk was observed under allele T vs. allele A genetic contrast in total analysis  polymorphism and BPH observed in the total analysis  polymorphism, no significant relationship was detected with BPH risk in total analysis. However, after the subgroup analysis by ethnicity, a positive association there between was revealed in other-ethnicity group under LL vs. VV   polymorphism under LL vs. VV+VL and VL vs. VV contrasts in total analysis, so the random-effects model was employed for ORs calculation in these cases while the fixed-effects model was chosen for the other three comparisons. As for the possible source of such heterogeneity, we found the significance was totally removed after subgroup analysis by ethnicity, thus indicating ethnicity might account for a part of the origin.According to SRD5A2 rs9282858 (A49T) polymorphism due to the absence of significant heterogeneity under all genetic models.The fixed-effects model was used to calculate pooled ORs for SRD5A2 rs9282858 polymorphism was less than 5, such analysis was not performed.The reliability of our results was determined using sensitivity analysis. Since the number of included studies for SRD5A2 rs523349 polymorphism, no significant change in pooled ORs was detected after removal any one of individual studies, thus demonstrating that our results were robust (data not shown).During the sensitivity examination of study on SRD5A2 rs523349 (V89L) polymorphism in view of the number of included studies. The funnel plots did not show any significant asymmetry , manifesting the absence of significant publication bias.The publication bias was explored using Begg's funnel plot and Egger's tests only for SRD5A2 gene, and their correlation with susceptibility to prostate cancer were reported previously  the studied people belonged to different ethnicities; (2) selection criteria for study subjects varied among different studies, so basic characteristics such as age period and lifestyles might be statistically different; (3) not all studies obtained their results after adjustment of conflicting factors, thus possibly causing biased conclusions; and (4) some studies only had a relatively small number of participants, causing reduced statistical power of final results.SRD5A2 (rs523349 and rs9282858) polymorphisms and the risk of BPH. This meta-analysis, including a total of 1,865 cases and 1,424 controls, was strictly implemented from literature search to data syntheses. According to pooled ORs, SRD5A2 rs9282858 (A49T) polymorphism increased the BPH risk under allele T vs. allele A contrast in total analysis as well as in Caucasian subgroup after stratified analysis by ethnicity. The rs523349 (V89L) polymorphism displayed no significant correlation with the disease susceptibility in total analysis; in stratified analysis based on ethnicity, it reduced the risk in Caucasian group under LL+VL vs. VV and VL vs. VV contrast while increased the disease risk in other-ethnicity group under LL vs. VV, LL vs. VV+VL and allele L vs. allele V genetic models.To our knowledge, this is the first meta-analysis comprehensively performed to assess the relationship between The present study had certain advantages in itself, like a relatively large sample size. However, there still were some limitations to be noted when applying our findings, since meta-analysis is a secondary analysis  polymorphism may be a risk factor for BPH occurrence, especially in Caucasians; while the rs523349 (V89L) polymorphism may present different effects on the disease onset in people of different ethnic lines.All in all, the present meta-analysis suggests that Future studies should consider the mentioned limitations, such as selection of objects, adjustment of interfering factors and large sample size for their designing of studies. Larger-scale and better-designed studies should be conducted to verify our findings.XTZ and XHW designed this study; XJS and HW searched databases and collected full-text papers; SL and TZL extracted and analyzed data; XTZ, XJS, and SL wrote the manuscript, TZL reviewed the manuscript.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. The reviewer KP and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


GSTP1 gene polymorphism with the outcomes and toxicities of treatments in breast cancer. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for the association of GSTP1 polymorphism with tumour response and toxicities, and the hazard ratios (HRs) and 95% CIs were calculated for the association between GSTP1 polymorphism and overall survival (OS). The statistical analysis showed that the GSTP1 polymorphism was not associated with tumour response or OS. A significant increase in the incidence of toxicities was observed , especially in the chemotherapy ± surgery group . Our results indicate that the GSTP1 polymorphism may be associated with increased toxicity, especially in patients treated with chemotherapy ± surgery.This study aimed to investigate the association of the  Breast cancer in 2012 was both the most common cancer worldwide, with 1.7 million new cases, and the leading cause of cancer-related deaths in women –5. InterGSTP1 gene, a member of the GST family, is located on chromosome 11q13, which contains 7 exons and 6 introns. Genetic polymorphisms involving an adenine to guanine transition (rs1695) at codon 105 in exon 5 of the GSTP1 gene results in amino acid substitution from isoleucine to valine . This substitution decreases the enzymatic activity of glutathione-S-transferase P1 (GSTP1) and alters the pharmacokinetics of cyclophosphamide, which may influence treatment outcomes and toxicity for breast cancer [Glutathione S-transferases (GSTs) are a superfamily of phase-II metabolic enzymes that play a key role in cellular resistance mechanisms . GSTs deGSTP1 (A313G) gene polymorphism with treatment response, prognosis, and toxicities for breast cancer [GSTP1 (A313G) polymorphism on treatment outcomes and toxicities in patients with breast cancer.Studies have investigated the associations of the t cancer –41. HoweGSTP1,” “breast cancer,” “breast carcinoma,” and “breast neoplasm.” Studies were manually filtered without language restrictions. Additional studies were identified by screening references and relevant reviews.PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure were searched for relevant studies up to August 29th, 2016, by using the following terms: “glutathione S-transferase,” “glutathione S-transferase P1,” “GSTP1 and treatment outcomes, as well as toxicities after radiotherapy and/or chemotherapy; (3) treatment outcomes including tumour response and overall survival (OS), with toxicities including all adverse effects; and (4) provision of adequate data for calculation of both odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (CIs).Studies were included if they met the following criteria: (1) inclusion of patients who were treated for breast cancer; (2) evaluation of associations between The following items were gathered independently from all eligible studies by two investigators (JM and YL): first author's name, year of publication, country, number of patients, genotyping methods, median follow-up, treatment protocols, treatment outcomes, and toxicities. Any disagreements were resolved through discussion and consensus.The risk of bias was assessed by reviewers independently using a modified Ottawa classification for observational studies . Any disGSTP1 and tumour response and toxicities based on raw data. Cox proportional HRs and 95% CIs for OS were also calculated using the most adjusted HR in each study. In this meta-analysis, we examined the association of variant genotypes of GSTP1 polymorphism with treatment outcome and toxicities.The responses were estimated according to Response Evaluation Criteria in Solid Tumors, including complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). Patients with CR and PR were categorized as the responder group, and patients with SD and PD were categorized as the non-responder group. Toxicities were defined as all adverse effects that occurred after treatment with chemotherapy and/or radiotherapy. ORs with 95% CIs were used to evaluate the association between Q test with a significance level of P < 0.05. The I2 statistic was used to test the heterogeneity among the included studies [The heterogeneity was assessed using the  studies . A fixed studies . Otherwi studies .P values were 2-sided and P < 0.05 was considered statistically significant.Subgroup analysis was carried out based on ethnicity, sample size, and therapeutic method. Ethnic subgroups consisted of three groups: East Asian (Chinese and Japanese), South Asian (Indian and Bangladeshi), and mixed descent . Sample size was divided into a large group (≥ 100 cases) and a small group (< 100 cases). Therapeutic methods included chemotherapy ± surgery, radiotherapy ± surgery, and chemotherapy + radiotherapy ± surgery. Potential publication bias was assessed using a Funnel plot  and EggeA total of 831 potentially relevant publications were systematically identified. Of them, 784 studies were excluded because they were reviews, letters, comments, or irrelevant studies. An additional study was excluded because data were not provided, and the authors could not be reached . AnotherGSTP1 polymorphism with tumour response, OS, and toxicities, respectively. The meta-analysis was conducted using a fixed-effect model when P > 0.05 for the Q test, which indicated a lack of heterogeneity among studies; otherwise, a random-effect model was used.Tables GSTP1 polymorphism and tumour response . Publication bias was observed in the Funnel plot and Egger's test , but not for other models .There was no significant association between the GSTP1 polymorphism was associated with OS in the dominant genetic model , but not other genetic models , as shown in Table vs. AA, P = 0.365; and GG vs. AA, P = 0.719).The vs. AA OR = 1.45, 95% CI 1.04–2.01, P = 0.028, Figure vs. AA OR = 1.47, 95% CI 1.03–2.10, P = 0.036, Figure P = 0.006, Figure P = 0.011, Figure P = 0.058). Publication bias was observed in the Funnel plot and Egger's test for the genetic models  There was no publication bias in other models .Pooled results showed that there was a significant increase of toxicities , but this association was not found when the sample size was small, or with any ethnicity subgroup. In addition, no associations between GSTP1 polymorphism and OS were found in either large or small sample sizes. The estimated results showed that there was an increased incidence of toxicities after chemotherapy ± surgery in three genetic models: GA vs. AA , recessive model , and allele model , chemotherapeutic agents, breast cancer subtypes , and TNM staging status—were not strictly described in some studies. Therefore, these factors could not be stratified into subgroups with great detail. Furthermore, the major sources of heterogeneity where not detected, except for subgroup analysis by ethnicity, sample size, and therapeutic method. Second, publication bias existed in this meta-analysis. This may be due to the absence of some negative trials, which may lead to overestimate the treatment effects.GSTP1 polymorphism may be associated with increased incidence of toxicities, especially in patients treated with chemotherapy ± surgery. Nevertheless, no significant associations were found between the GSTP1 polymorphism and tumour response or OS.In conclusion, our meta-analysis suggests that


This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities. Malignant neoplasm, or cancer, is one of the most prevalent chronic diseases, which develops as a result of a somatic mutation. Advancing from this theory, a personalized medicine is currently gaining traction for the diagnosis and treatment of cancer , and sucWith the advances in genetic technologies, the subjects of analyses in studies aiming to discover disease-related genomes have changed into chromosomal abnormalities, allelic heterogeneity, and single nucleotide polymorphisms (SNPs). According to these changes, linkage analysis studies, genetic association studies (GTAS), and genome-wide association studies (GWAS) has been currently ongoing ,3.However, a phenomenon known as the “winner’s curse,” which is characterized by low replicability of results, has been appearing in follow-up studies on genes that were previously associated with a particular disease through genome-wide epidemiology studies -6. PopulThis review introduces the process of a genome-wide meta-analysis (GWMA), which involves a meta-analysis of findings of GWAS that investigate the SNPs associated with a particular disease . ParticuThe general procedures of a GWMA introduced by previous studies ,12-17 coHere, we present the study by Song et al. , which eThe search for GWAS articles involves different sources and keywords from those used for a search of general systematic reviews. We recommend the use of data sources on the organized tables by Casado-Vela et al. , RamasamWe recommend the use of the flow chart suggested by Sagoo et al.  for the The sets of information extracted from the selected GWAS articles are needed for the evaluation of the validity of each article in the next step. Items for evaluating the validity of GWAS articles have been suggested by Attia et al. , de BakkIf the quality of each of the selected genetic epidemiology studies must be assessed, the assessment checklist provided as supplementary data in the study by Thakkinstian et al.  or the c2, 2pq, and q2, respectively, where p²+2pq+q²=1. Using this equation, we can predict the frequency of a genotype with a known allele frequency.One critical aspect of validity assessment for GWMA findings is the satisfaction of HWE assumption. HWE states that the frequencies of genes and genotypes remain in equilibrium over generations under limited conditions . For exaThe subjects of HWE testing depend on the study design. In a cohort study or cross-sectional study, HWE should be tested on the entire study population. On the other hand, HWE is only tested on the control group in a case-control study because the case group may not confirm to the HWE if the genotype is associated with a disease. Studies that deviate from the HWE should be excluded from step 4, and their meanings should be investigated in step 5 through a sensitivity analysis.The most popular test to verify the HWE is the chi-squared test , a statiFor HWE analysis of case-control studies in the STATA software, genotypic counts of the case and control groups should be listed following the <genhwcci> command. For example, in In a C/T polymorphism where C is dominant and T is recessive, there are five possible types of genetic models: dominant (CC+CT vs. TT), recessive (CC vs. CT+TT), homozygote contrast (CC vs. TT), heterozygote contrast (CC vs. CT), and allelic contrast (C vs. T) .Add the frequencies for the case and control groups of each article according to each model before performing the meta-analyses. For example, in the study by Han et al. , multiplFor a frequency-based meta-analysis on STATA, use the <metan> command. Refer to Shim et al.  for creaIf heterogeneity is present, difference of race should be first considered ,29, as dIf heterogeneity is determined to persist, a random effect model may be applied ,34. HoweTwo features that distinguish GWMA from the intervention meta-analyses are that GWMA uses HWE to verify the validity of a study and performs meta-analyses according to the five possible types of genetic models.If individual patient data, as opposed to the findings of the selected literature, are used, the STATA <metagen> command may be used . FurtherCurrently, genome-wide epidemiology is evolving into system epidemiology using multi-omics, including proteomics, metabolomics, and epigenomics, in pursuit of precision medicine ,38,39. A


Existing evidence of the association between statin use and non-melanoma skin cancer (NMSC) risk has been inconsistent.To maximize statistical power to synthesize prospective evidence on this relationship.PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and ClinicalTrial.gov were systematically searched up to December 11, 2016. A random-effects meta-analysis was conducted to calculate summary estimates.Our meta-analysis of 14 randomized controlled trials (RCTs) including 63,157 subjects showed no significant association between statin use and NMSC risk . However, meta-analysis of four observational studies including 1,528,215 participants showed significantly increased risk of NMSC among statin users compared to non-users . Furthermore, ever using lipophilic statins  or lower-potency statins , as well as usage of any statin longer than one year  were significantly associated with increased NMSC risk based on observational studies.Evidence from observational studies supported an association between statin use and increased NMSC risk. This finding should be interpreted with caution due to modest number of included studies, possible between-study heterogeneity and inherent limitations of observational studies. Non-melanoma skin cancer (NMSC), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) of the skin, is the most common cancer in the United States , 2. StatAmong the 6,420 citations retrieved from the electronic databases, a total of seven reports that covered 14 RCTs including 63,157 subjects and 1,211 NMSC events , 16, 17,2 = 59.9%; P for heterogeneity = 0.02). However, the meta-analysis of observational studies revealed a significant association. Statin users have a higher risk of NMSC than non-users  .Meta-analysis of RCTs did not show a significant association between statin use and NMSC risk . None of the subgroup analyses detected a significant association based on RCTs (P > 0.05). However, subgroup analyses of observational studies revealed significantly increased risks of NMSC among ever-users of lipophilic statins  or statins with lower potency , compared to never-users. Additionally, users of statins for more than one year had significantly higher NMSC risk than never-users .The results of subgroup analyses are shown in Table Our meta-analysis of four prospective observational studies involving 1,528,215 participants and 55,793 NMSC cases suggested a significant and positive association between statins and NMSC risk. However, our meta-analysis of 14 RCTs with 63,157 participants and 1,211 NMSC events did not observe such an association. This may be due to the fact that RCTs usually have shorter follow-up period of time than observational studies and an increased risk of rare events (e.g. cancers) may not be detected during a relatively short duration. Besides, cancer events are not the primary endpoints of the RCTs for statins. Therefore, observational studies may have some advantage of examining a long-term drug-safety issue.One previous meta-analysis evaluated statins and all-cancer risk, among which only four RCTs were related to NMSC, and their pooled results indicated a significant association between statins and increased NMSC risk . AnotherMelanoma, SCC, and BCC are three major types of skin cancer. The underlying mechanisms of melanoma and non-melanoma skin cancers (SCC and BCC) are not the same. In terms of melanoma, which is the most serious type of skin cancer, most randomized controlled trials and observational studies published so far showed non-significant association between statin use and melanoma risk . RecentlWe still lack substantial understanding of the biological mechanisms by which statins affect cancer risk, and whether specific properties of statins make any difference in this process. Some studies have indicated that the immunomodulatory effects of statins may be responsible for its potential carcinogenic actions. A statin-induced increase in CD4+CD25+ regulatory T cells (Tregs) may impair the host antitumor immune response through suppressing the tumor specific effector T cell response, which may lead to an increased risk of cancer . NotablyOur findings should be interpreted with caution due to the modest number of studies we were able to include, possible between-study heterogeneity, as well as the residual confounding inherent in observational studies. Due to the unavailability of original data, we could not conduct meta-analysis separately for BCC and SCC. We also could not estimate dose-response effects as available data were too heterogeneous to pool.In conclusion, our meta-analysis of observational studies supported an association between statin use and increased NMSC risk. In future, ongoing post-marketing surveillance and long-term follow-up studies of RCTs could provide ongoing monitoring of new NMSC cases that may be related to the use of statins. More prospective studies with large sample sizes could be conducted to further evaluate the association between statins and NMSC risk. In addition, basic research on cholesterol metabolism and tumor formation is needed to explore underlying mechanisms.This meta-analysis was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines .ClinicalTrials.gov registry to identify all prospective evidence . References list from all relevant review articles, meta-analysis, and the identified articles were manually checked. The following terms were used for literature search: ((hydroxymethylglutaryl coenzyme A reductase inhibitor) OR (hydroxymethylglutaryl-coa reductase inhibitors) OR (HMG-CoA reductase inhibitors) OR (statins) OR (atorvastatin) OR (fluvastatin) OR (lovastatin) OR (mevastatin) OR (pravastatin) OR (pitavastatin) OR (rosuvastatin) OR (simvastatin) OR (cerivastatin)) AND ((melanoma) OR (non-melanoma) OR (nonmelanoma) OR  OR (squamous cell carcinoma) OR (cancer) OR (neoplasms) OR (neoplasm) OR (skin cancer)).We conducted a comprehensive and systematical literature search in PubMed, EMBASE, Web of science, Cochrane Central Register of Controlled Trials (CENTRAL), and Both randomized controlled trials and prospective observational studies (cohort study and nested case-control study) were considered. Included studies should meet the following criteria: (1) Published and unpublished RCTs of statins that reported NMSC cases as adverse events ; (2) Cohort or nested case-control studies that examined the association between statin use and NMSC incidence; (3) All study participants were adults aged ≥ 18 years. NMSC cases referred only to SCC and BCC in this meta-analysis. Retrospective case-control studies were excluded as they were subjected to various biases. Also, to minimize bias, we used safety data from only the original trials rather than prolonged post-trial follow-up (if available), as the majority of all subjects received open-label lipid-lowering treatment during the latter. Studies did not provide sufficient information or failed to meet eligibility criteria were also excluded.ClinicalTrials.gov registry website. Study characteristics including first author’s name, publication/report year, trial name, study design, study location, sample size, study length, type of statins, exposure and outcome assessment, as well as population characteristics including age, sex and race of the study population in each included study were also extracted.Two reviewers (K.Y. and A.M.) independently performed the study selection, data extraction, and quality assessment. Numbers of NMSC cases were extracted from randomized trials and adjusted risk ratios were extracted from observational studies for data synthesis. As two included RCTs did not report NMSC events in the manuscript (JUPITER and AURORA) , 16, theThe quality of randomized trials was evaluated by Cochrane Risk of Bias (RoB) Tool . We used2 statistics were used to assess between-study heterogeneity. Additionally, subgroup analyses were separately performed for RCTs and observational studies to explore the source of heterogeneity, based on: (1) category of statins ; (2) potency of statins ; and (3) duration of statin use . Publication bias was examined using Begg’s and Egger’s tests. All statistical analyses were performed with STATA version 14.2. Two-sided α ≤ 0.05 was the significance level.We used the random-effects model (DerSimonian and Laird inverse variance method) to estimate summary relative risk (RR) with a 95% confidence interval (95% CI). I


Cancer is a leading cause of death among people living with HIV/AIDS (PLWHA). We conducted a systematic review and meta-analysis to evaluate prevalence of cancer risk factors among Chinese PLWHA based on 102 articles. Random effects meta-analysis was used to calculate the summary prevalence estimate (sPrev) and 95% confidence interval (CI) for each cancer risk factor by demographic group. Overall, the sPrev for each risk factor among Chinese PLWHA was: 41.1% (95% CI: 35.3–46.9%) for current smoking; 30.3% (95% CI: 23.3–37.4%) for current alcohol consumption; 24.4% (95% CI: 14.7–30.2%) for overweight and obesity; 12.5% (95% CI: 10.6–14.3%) for hepatitis B virus infection; 29.1% (95% CI: 23.6–34.5%) for hepatitis C virus infection; 33.9% (95% CI: 24.3–43.5%) for high-risk human papillomavirus infection from cervical samples and 78.6% (95% CI: 69.4–87.7%) from anal samples; 2.7% (95% CI: 0.7–4.7%) for Epstein-Barr virus (EBV) immunoglobulin M (IgM) positivity, 94.7% (95% CI: 90.7–98.8%) for EBV IgG positivity and 25.6% (95% CI: 12.4–38.8%) for EBV DNA positivity; 14.9% (95% CI: 12.4–17.4%) for human herpes virus 8 infection. The prevalence of major cancer risk factors was high among PLWHA in China, suggesting an urgent need for interventions to reduce cancer risk in this high-risk group. For PLWHA, cancer is now one of the leading causes of death with higher incidence of both AIDS-defining cancers (ADCs) and non-AIDS-defining cancers (NADCs) compared with the general population8. In particular, NADCs have shown increasing incidence and account for a rising proportion of all cancers in this population4. China has implemented HAART nationally since 2003. In a Chinese cohort, substantially elevated standardized incidence ratios of NADCS and ADCs were observed, and cancers occurred at a younger age for PLWHA compared to the general population9. Accumulated evidence suggests that HIV-induced immunodeficiency and prevalent risk factors other than HIV infection independently contribute to the increased cancer risk among PLWHA11. The major risk factors associated with leading causes of cancer deaths include tobacco use , alcohol consumption , overweight/obesity , and viral infections 13. Numerous independent studies have reported prevalence of cancer risk factors among PLWHA in China. However, the researches vary in time and geographic areas, and do not provide a comprehensive overview of cancer risk factors epidemics for PLWHA in China. We conducted a meta-analysis among PLWHA in China to describe the prevalence of major cancer risk factors including tobacco smoking, alcohol consumption, overweight and obesity, and cancer-related viral infections such as hepatitis B virus (HBV), hepatitis C virus (HCV), human papillomavirus (HPV), Epstein-Barr virus (EBV) and human herpes virus 8 (HHV8). Prevalence estimates among Chinese PLWHA were compared with the general population or uninfected comparison groups from the same study when available.Highly active antiretroviral therapy (HAART) or combination antiretroviral therapy (cART) has drastically reduced mortality in people living with HIV/AIDS (PLWHA)115. One additional study with unique data on HIV uninfected population was included for comparison analysis116.The process of selection of publications and the numbers of articles for each cancer risk factor are presented in Table 101, 2 retrospective cohort studies79 and 1 intervention trial36 were included. Most studies (99) were based in clinics or hospitals for PLWHA recruitment, 2 were population-based73 and 1 study sampled was recruited from jail75. The 102 eligible studies covered 20 provinces and 4 municipalities in China. The median sample size for PLWHA was 295 [interquartile range (IQR): 178–551]. Seventy-five articles reported the median or mean age, and the median of the median or mean age was 37.2(IQR: 34.0–41.0). Of the 95 articles reporting gender distribution, the median proportion of male was 72.6% (IQR: 61.3–86.9%). Of the 16 articles reporting the proportions of MSM, the median was 79.1% (IQR: 63.9–100.0%). Of the 23 articles reporting the proportions of IDU, the median was 74.8% (IQR: 40.4–100.0%). Of 26 articles reporting the proportions on ART, the median was 67.5% (IQR: 45.3–100.0%).Table Table , I2 = 96.0%) in PLWHA based on the meta-analysis of 21 studies. The sPrev of current smoking was 63.2% (95% CI: 39.7–86.8%) for male PLWHA and was 3.4% (95% CI: 2.2–4.6%) for females, based on the 5 studies with gender-specific prevalence. Overall, the sPrev of ever and former smoking was 51.9% (95% CI: 42.8–61.1%) based on 5 studies and 13.9% (95% CI: 0.3–27.6%) based on 3 studies, respectively  based on the meta-analysis of 25 studies. Gender-specific estimates showed that the sPrev of current alcohol consumption was 26.9%  in male PLWHA based on 5 studies and was 3.3%  in females based on 3 studies. MSM presented a current drinking sPrev of 35.7% (95% CI: 18.9–52.5%) based on 3 studies while IDUs presented a current drinking sPrev of 13.1% (95% CI: 8.3–17.9%) based on 2 studies. Overall, the sPrev of ever and former alcohol drinking was 64.3% (95% CI: 60.8–67.7%) and 17.8% (95% CI: 3.6–32.0%), respectively (Table P = 0.004)  among PLWHA, with a sPrev of 24.4%  , 10.4%  and 13.4%  in overall, female and male groups, respectively. The highest sPrev of HBsAg was among IDUs  (Table P = 0.013) . Male PLWHA showed a sPrev of 47.1%  based on 15 studies, while female PLWHA had a sPrev of 29.9%  based on 16 studies. The highest HCV prevalence was found in IDU group with a sPrev of 83.4%   and 33.9% , respectively. For anal samples, the sPrev among male PLWHA of any type of HPV was 78.6% , and the sPrev of high-risk type was 52.1% . Similar sPrev was observed among HIV positive MSM . IgG was tested in 2 studies, and the sPrev in overall, female and male groups was 94.7% , 92.5%  and 96.8% , respectively. DNA from peripheral blood was tested in 2 studies, and the overall sPrev was 25.6% . One study reported the prevalence of 27.1% (95% CI: 16.7–37.6%) in female and 34.2% (95% CI: 27.4–41.0%) in male PLWHA for EBV DNA positivity  was tested in 4 studies and the sPrev was 2.7% , 12.1% , 17.7%  and 16.3% , respectively. The highest serum HHV8 prevalence was among MSM  . For serum antibody, the sPrev in overall, female, male and IDU groups was 14.9%  and males (63.2% vs. 55.4%), alcohol consumption among males (26.9% vs. 30.2%), overweight and obesity (22.4% vs. 25.8%), and HCV infection among IDUs (83.4% vs. 93.0%).We recalculated each sPrevP-value for Egger test was 0.028, P-value for Begg test was 0.057), the overall sPrev of alcohol consumption , the overall sPrev of HBV infection , and the sPrev of HCV infection overall , in females , and in males .In our meta-analysis, substantial publication bias was significantly observed by the Egger test and/or the Begg test in estimating the overall sPrev of smoking 119 while MSM showed slightly higher sPrev (35.7%) and IDUs showed significantly lower estimate (13.1%). As group I carcinogens defined by IARC, tobacco smoking and alcohol consumption are not only associated with a series of human cancers, but also with other important chronic diseases. Based on our summarized estimates, the high prevalence of tobacco and alcohol use especially among male PLWHA suggested the need for an effective and more targeted intervention in smoking and drinking behaviors as well as a close observation of their roles in HIV and cancer disease progression to reduce morbidity and to improve quality of life in this aging population with prolonged life expectancy.For such two modifiable behavioral risk factors as tobacco and alcohol use, Chinese PLWHA showed high prevalence of tobacco smoking and alcohol drinking overall and especially among males. For example, the smoking prevalence is 53.3% for general Chinese men126, shown by the results from both meta-analyses and independent studies. By demographic group, 10.4–13.4% of PLWHA were HBsAg positive, and 29.1–47.1% were HCV antibody positive. Moreover, the highest prevalence of HBV (32.8%) and HCV (83.4%) infection were both found in IDUs, probably due to the shared transmission route with HIV. For female PLWHA, the sPrev of both any type of HPV (42.0%) and high-risk type of HPV (33.9%) from cervical samples were higher than the prevalence in Chinese general population aged 15–60 years123. Moreover, we found that in anal samples collected from male PLWHA, the HPV prevalence was very high no matter whether they were MSM or not. These observations call attention since HPV infection is also a risk factor for anal cancer. The high seropositivity of EBV-IgG was close to the prevalence reported earlier in the Chinese general population (97.6%)125. Although the latter statistic might be limited to experimental conditions and in need of update, it is believed that EBV infection is very common among adults127. Moreover, several studies suggested higher detection rate of EBV DNA among HIV-infected subjects compared to HIV-negatives, suggesting potentially more active viral application in immune-suppressed population129. Last but not least, the overall seroprevalence of HHV8 infection was 14.9%, higher than the prevalence in the Chinese general population126, with the highest prevalence found in MSM .The prevalence of cancer-related viral infections, including HBV, HCV, HPV, EBV and HHV8 infection, are significantly higher in PLWHA than in general Chinese population119. This is similar with the observations in western countries that the obesity prevalence was lower in HIV population118. We need to further observe the change in weights in PLWHA to have a better understanding and balance in control of both the HIV wasting syndrome and risk for obesity-related cancers and chronic diseases.The overall prevalence of overweight and obesity among PLWHA was 22.4% (95% CI: 14.7–30.2%), lower than the prevalence of 42.6% in Chinese general population118, which, consistent with our analysis, also observed higher prevalence of cancer risk factors among PLWHA than the general population. However, the prevalence level seems to be different between PLWHA in western countries and in China. Compared with PLWHA in western countries, PLWHA in China seemed to have higher prevalence in alcohol consumption (30.3% versus 24.0%), HCV (29.1–47.1% versus 23.0–28.0%) and HBV (10.4–13.4% versus 4.0–5.0%) infection, but lower prevalence in smoking (41.1% versus 54.0%), overweight and obesity (22.4% versus 53.0%) and HPV infection . Thus, the spectrum of cancers among PLWHA in China might be different from that in western countries and further investigations and interventions might be targeted to different high-risk groups.A meta-analysis was recently published on prevalence of risk factors for NADCs among PLWHA in western high-income countriesI2 values larger than 90%. This was expected since heterogeneity could be found in almost all ‘overall’ groups, because we could not know the proportion of genders or behavioral characteristics in these study populations across publications. So was the case in ‘male’ groups, which could have different proportions of heterosexual male, MSM and IDU. Meanwhile, extensive heterogeneity still existed in specific demographic groups such as female, MSMs and IDUs. This could be attributable to many potential factors including study design, sampling method, geographical regions, study period, age, ethnicity, the definition or method of measurement for risk factors, differences in CD4+ and the length of time in ART, etc130. Insufficient number of studies has limited our further stratification analysis. However, random effects models were used to minimize the impact of heterogeneity on precision and provided rational approximations of pooled prevalence estimates in our meta-analyses. Sources of heterogeneity should be further explored in the future with more research for specific subgroups.Substantial heterogeneity across subgroups was significantly observed with 132. The association between behavioral changes such as smoking and alcohol consumption and severity of HIV patients might lead to underestimation of prevalence of cancer risk factors among PLWHA.Several limitations in our study should be noted. First, there might be some information bias since the methods for measuring these risk factors might vary across studies. Most (69.2%) studies did not give a clear definition of smoking habits  or did not have a precise measurement for smoking dose or frequency, while only 50% of studies presented the range of time (past 30 days or a day) for current alcohol drinking. Although we tried to extract information from reference studies using standardized definitions, misclassification might still exist since not every study gave a clear definition for each risk factor. Also, the testable HPV subtypes varied across studies, and therefore, underestimation of HPV prevalence might have occurred in studies with fewer testable HPV subtypes. Second, the representativeness of our meta-analyses is compromised since it covered 24 but not all 31 provinces or municipalities in China, underscoring the need for expanded research and surveillance efforts on cancer risk factors among PLWHA all over the country. Third, comparability was not considered across different sources of data due to time lags among studies. Some risk factors may present a temporal trend, some may not. For those with an increasing or decreasing trend, it may have compromised the comparison. Fourth, as prevalence estimates of cancer risk factors can vary with characteristics including age, lack of matching for age and other factors also limited the validity of the comparisons between PLWHA and the general population. However, consistent results were still observed when stratified roughly by age where possible , Wanfang Data and Chinese Scientific Journals Fulltext Database (CQVIP). Using the Medical Subject Headings (MeSH) terms ‘China’ or ‘Taiwan’ with ‘HIV,’ ‘HIV Infections’ or ‘Acquired Immunodeficiency Syndrome’, the search also included MeSH terms for the specific cancer risk factors as follows: smoking (‘Smoking’ or ‘Tobacco Products’ or ‘Tobacco’ or ‘Tobacco Use’), alcohol consumption (‘Alcohol Drinking’ or ‘Alcoholism’ or ‘Alcoholic Intoxication’), overweight or obesity (‘Overweight’ or ‘Obesity’ or ‘Body Mass Index’ or ‘Body Weight’), HBV (‘Hepatitis B’), HCV (‘Hepatitis C’), HPV (‘Papillomavirus Infections’ or ‘Papillomaviridae’), EBV (‘Epstein-Barr Virus Infections’), and HHV8 . We also searched those MeSH terms and their abbreviations of each risk factor under the condition of ‘all fields’ in each database. Due to the large number of studies published on HBV and HCV infections among PLWHA in China, we restricted published data from January 1, 2013 to February 29, 2016 in order to use the latest published prevalence of HBV and HCV infections. For other cancer risk factors, data published from database inception to February 29, 2016 were included in the analyses.One author (Jin Z-Y) identified relevant articles, excluding those with unrelated titles and abstracts before obtaining full-text references. Two independent authors (Jin Z-Y and Liu X) conducted full-text review. Cross-sectional, case-control, prospective or retrospective cohort and intervention trial studies were included. Studies with sample size greater than 100 were considered to have a sufficiently stable prevalence estimate to be qualified for inclusion in the study. Studies lacking original data for the numerator or denominator of the prevalence estimate were excluded. If information from one study had been published for more than once, we chose the publication with more detailed information such as prevalence estimates stratified by specific demographic groups, studies with a larger sample size, or those most recently updated.Data were extracted and organized using Microsoft Excel . For each risk factor, the number of PLWHA with known status was recorded as the denominator and the number of positive subjects was recorded as the numerator. The participants with unknown status were excluded from the calculation. If an article contained more than one of the mentioned risk factors, we kept all of them. If the PLWHA were stratified into different groups such as females, males, men who have sex with men (MSM) or injection drug users (IDU), we included data from each subgroup for prevalence estimate. The definitions of smoking and drinking status including “ever/never”, “former/current” were based on the descriptions in the original studies when a clear definition is not available. We also extracted prevalence estimates for HIV uninfected comparison groups if data were available from the same study. Other information including the first author’s name, year of publication, study site, original study design, sampling frame, calendar years of research, major information for participants including the mean or median age, percentage of males, MSM, IDU, treatment with antiretroviral therapy (ART), and the measurement of risk factors were also extracted.119. For HBV and HCV infections, prevalence estimates were obtained from a national serosurvey in 2006, of which participants were local residents aged 1–59 years (the median age was in the range from 15 to 59 years for HBV and in the range from 15 to 20 years for HCV) living in 31 provinces with 160 DSPs121. For HPV infection, prevalence estimates were acquired from a nationwide investigation of female subjects aged 15–60 years in 37 Chinese cities in 2012, a review (age ranging from 15 to 59 years) and a population-based study among men aged 25–65 years (the median age was 43 years)124. For EBV infection, the prevalence estimate was extracted from a 1989 study by Liu125. For HHV8 infection, the prevalence estimate was from a systematic review and meta-analysis published in 2012126.We also extracted prevalence estimates for cancer risk factors among the general population from the most representative surveys. For tobacco smoking, alcohol consumption, overweight and obesity, prevalence estimates were extracted from a national survey, which was carried out in Chinese adults (aged 18 years and over with the median age in the range from 45 to 49 years) at 162 disease surveillance points (DSPs) from 31 provinces in 2010P < 0.1 refers to statistically significant heterogeneity) and I2 values140. Random effects models were used because of significant heterogeneity across subgroups142. DerSimonian and Laird method (D-L) was applied to estimate the summary prevalence estimate (sPrev) and its 95% confidence interval (CI) for each risk factor143. If only one study was presented for the specific subgroup, we showed the single prevalence and its 95% CI. In sensitivity analyses, each sPrev was recalculated excluding studies evaluated as having higher potential for bias. Lastly, we performed a publication bias test when the meta-analysis included more than 10 studies145. Publication bias was assessed through the Egger weighted regression and Begg rank correlation method 147. All the analyses were conducted by Stata 12.0 (Stata Corp LP).PLWHA were stratified into overall, female, male, MSM, and IDU demographic groups when such subgroups were available. The ‘Overall’ group represents PLWHA not restricted by gender or HIV transmission category . Similarly, the ‘male’ group implies that PLWHA were not restricted by HIV transmission category. A meta-analysis of prevalence was performed for each risk factor by demographic group if there was more than one study included. Heterogeneity tests across subgroups were examined by Q-test (Supplementary Information