Monte Carlo Investigations for Relative Efficiency of Stratified Random Sampling Scheme for Estimation of Relative Risk in Case-Control Studies

Monte Carlo Investigations have been widely used in Sample Surveys in Comparing the efficiency of various methods when exact mathematical comparisons are not possible. In this paper the same has been used for comparing the efficiency of Stratified Random Sampling with respect to Simple Random Sampling for estimation of Relative Risk in Case-Control Studies. The data used relate to a Case Control study on peptic ulcer. On the basis of Monte Carlo Investigations on 50 samples of size 10–20 (Cases and Controls), it has been observed that there is considerable gain in efficiency in using Stratified Random Sampling over Simple Random Sampling. The sensitivity of the results with the change in Sample Size has also been investigated.     

Association Testing of Clustered Rare Causal Variants in Case-Control Studies

Biological evidence suggests that multiple causal variants in a gene may cluster physically. Variants within the same protein functional domain or gene regulatory element would locate in close proximity on the DNA sequence. However, spatial information of variants is usually not used in current rare variant association analyses. We here propose a clustering method (abbreviated as “CLUSTER”), which is extended from the adaptive combination of P-values. Our method combines the association signals of variants that are more likely to be causal. Furthermore, the statistic incorporates the spatial information of variants. With extensive simulations, we show that our method outperforms several commonly-used methods in many scenarios. To demonstrate its use in real data analyses, we also apply this CLUSTER test to the Dallas Heart Study data. CLUSTER is among the best methods when the effects of causal variants are all in the same direction. As variants located in close proximity are more likely to have similar impact on disease risk, CLUSTER is recommended for association testing of clustered rare causal variants in case-control studies.     

Mitochondrial DNA as a Risk Factor for False Positives in Case-Control Association Studies

<正>During the last decade,hundreds of studies have been published examining whether significant associations exist between mitochondrial DNA(mt DNA)variants and/or haplogroups(clades)and particular diseases(generally common/complex diseases)(Fig.1).However,several authors have gathered evidence indicating a high incidence of false positive findings in mt DNA case-control association studies.     

Risk Factors for Invasive Cryptococcus neoformans Diseases: A Case-Control Study

Background

Cryptococcus neoformans is a ubiquitous environmental fungus that can cause life-threatening meningitis and fungemia, often in the presence of acquired immunodeficiency syndrome (AIDS), liver cirrhosis, diabetes mellitus, or other medical conditions. To distinguish risk factors from comorbidities, we performed a hospital-based, density-sampled, matched case-control study.

Methods

All new-onset cryptococcal meningitis cases and cryptococcemia cases at a university hospital in Taiwan from 2002–2010 were retrospectively identified from the computerized inpatient registry and were included in this study. Controls were selected from those hospitalized patients not experiencing cryptococcal meningitis or cryptococcemia. Controls and cases were matched by admission date, age, and gender. Conditional logistic regression was used to analyze the risk factors.

Results

A total of 101 patients with cryptococcal meningitis (266 controls) and 47 patients with cryptococcemia (188 controls), of whom 32 patients had both cryptococcal meningitis and cryptococcemia, were included in this study. Multivariate regression analysis showed that AIDS (adjusted odds ratio [aOR] = 181.4; p < 0.001), decompensated liver cirrhosis (aOR = 8.5; p = 0.008), and cell-mediated immunity (CMI)-suppressive regimens without calcineurin inhibitors (CAs) (aOR = 15.9; p < 0.001) were independent risk factors for cryptococcal meningitis. Moreover, AIDS (aOR = 216.3, p < 0.001), decompensated liver cirrhosis (aOR = 23.8; p < 0.001), CMI-suppressive regimens without CAs (aOR = 7.3; p = 0.034), and autoimmune diseases (aOR = 9.3; p = 0.038) were independent risk factors for developing cryptococcemia. On the other hand, diabetes mellitus and other medical conditions were not found to be risk factors for cryptococcal meningitis or cryptococcemia.

Conclusions

The findings confirm AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CAs, and autoimmune diseases are risk factors for invasive C. neoformans diseases.     

Weighted Score Tests Implementing Model-Averaging Schemes in Detection of Rare Variants in Case-Control Studies

Multi-locus effect modeling is a powerful approach for detection of genes influencing a complex disease. Especially for rare variants, we need to analyze multiple variants together to achieve adequate power for detection. In this paper, we propose several parsimonious branching model techniques to assess the joint effect of a group of rare variants in a case-control study. These models implement a data reduction strategy within a likelihood framework and use a weighted score test to assess the statistical significance of the effect of the group of variants on the disease. The primary advantage of the proposed approach is that it performs model-averaging over a substantially smaller set of models supported by the data and thus gains power to detect multi-locus effects. We illustrate these proposed approaches on simulated and real data and study their performance compared to several existing rare variant detection approaches. The primary goal of this paper is to assess if there is any gain in power to detect association by averaging over a number of models instead of selecting the best model. Extensive simulations and real data application demonstrate the advantage the proposed approach in presence of causal variants with opposite directional effects along with a moderate number of null variants in linkage disequilibrium.     

On Estimation of Relative Risk in Case Control Studies

An estimator of relative risk in a case control study has been proposed in terms of observed cell frequencies and the probability of disease. The bias of the usual estimator i.e odds ratio as compared to the new estimator has been workedout. The expression of Mean Square Error of proposed estimator has been derived in situations where probability of disease is exactly known and when it is estimated through an independent survey. It has been observed that there is a serious error using odds ratio as an estimate of relative risk when probability of disease is not negligible. In such situations the proposed estimator can be used with advantage.     

Three ADIPOR1 Polymorphisms and Cancer Risk: A Meta-Analysis of Case-Control Studies

Background

Studies have come to conflicting conclusions about whether polymorphisms in the adiponectin receptor 1 gene (ADIPOR1) are associated with cancer risk. To help resolve this question, we meta-analyzed case-control studies in the literature.

Methods

PubMed, EMBASE, Cochrane Library, the Chinese Biological Medical Database and the Chinese National Knowledge Infrastructure Database were systematically searched to identify all case-control studies published through February 2015 examining any ADIPOR1 polymorphisms and risk of any type of cancer. Pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated.

Results

A total of 13 case-control studies involving 5,750 cases and 6,762 controls were analyzed. Analysis of the entire study population revealed a significant association between rs1342387(G/A) and overall cancer risk using a homozygous model (OR 0.82, 95%CI 0.72 to 0.94), heterozygous model (OR 0.84, 95%CI 0.76 to 0.93), dominant model (OR 0.85, 95%CI 0.75 to 0.97) and allele contrast model (OR 0.88, 95%CI 0.80 to 0.97). However, subgroup analysis showed that this association was significant only for Asians in the case of colorectal cancer. No significant associations were found between rs12733285(C/T) or rs7539542(C/G) and cancer risk, either in analyses of the entire study population or in analyses of subgroups.

Conclusions

Our meta-analysis suggests that the ADIPOR1 rs1342387(G/A) polymorphism, but not rs12733285(C/T) or rs7539542(C/G), may be associated with cancer risk, especially risk of colorectal cancer in Asians. Large, well-designed studies are needed to verify our findings.     

Univariate Dose-Response Models in Case-Control Studies

For modelling dose-response relationships in case-control studies the multiplicative logistic regression model, assuming the relative risk to be an exponential function of the dose, is widely known. If the relative risk is assumed to be a linear function of the dose, several authors (see e.g. BERRY (1980)) have proposed an additive (linear) model. This model has a better fit with the data if such a linear relation holds. Confidence limits for the relative risk derived from the information matrix, however, appear to be rather inaccurate. Therefore, use of the ‘standard’ logistic model in two different ways was studied: extension with a quadratic term or a logarithmic transformation of the dose. By applying the methods both to an empirical data set and in a simulation experiment, it is shown that appropriate transformation (often logarithmic) of the dosage and then applying the ‘standard’ logistic model is an useful approach if a linear dose-response relationship holds.     

流行病学研究中的嵌套病例对照研究

自从1975年由Thomas提出以来，嵌套病例对照研究（nested case-control study）方法在流行病学和生存分析的研究中应用日益广泛，近几年来，随机点过程理论的发展促进了这一方法中的理论问题的解决，从而为这一方法的进一步研究奠定了理论基础，本文综述近年来嵌套病例对照研究方法的新进展，指出目前仍待研究的一些问题，并就一种特殊情况给出了Mantel-Haenszel型推断方法。     

Estimation of Relative Risk in Case Control Studies Through Logistic Regression Analysis

Multiple logistic regression analysis is used to estimate the relative risk in case control studies. The estimators obtained are valid when disease is rare. In this paper an estimator of relative risk in a case control study has been proposed using logistic regression results when the incidence of disease is not small. The bias of the usual estimator through logistic regression as compared to the new estimator has been worked out. The expression of Mean Square Error of proposed estimator has been derived in situations when the incidence of disease is known exactly as well as when estimated through an independent survey. It has been observed that there is a significant bias using the conventional estimator of relative risk when incidence of disease is high. In such situations the proposed estimator can be used with advantage.     

Genetic Polymorphisms of XRCC1 and Leukemia Risk: A Meta-Analysis of 19 Case-Control Studies

Objective

Three common X-ray repair cross-complementing groups 1 (XRCC1) polymorphisms, Arg399Gln, Arg194Trp, and Arg280His, have been reported to be implicated in the development of leukemia. However, previous results from different studies were inconsistent. Consequently, we performed a meta-analysis in order to accurately evaluate the association between XRCC1 Arg399Gln, Arg194Trp, and Arg280His polymorphisms and leukemia risk.

Methods

Through computerized searching of PubMed, ISI Web of Knowledge, Cochrane, EBSCO, and OpenGrey databases, and manually searching relevant references, a total of 19 studies with 3387 cases and 6168 controls for Arg399Gln (G>A) polymorphism, 12 studies with 2043 cases and 4550 controls for Arg194Trp (C>T), and 6 studies with 1445 cases and 1905 controls for Arg280His (G>A) were collected to perform meta-analysis and stratified analysis to explore the associations between these variants and leukemia susceptibility. Based on three genetic models, the codominant model, dominant model and recessive model, odds ratios (ORs) as well as their 95% confidence intervals (CIs) were used to evaluate the association strength between XRCC1 genotypes and leukemia risk.

Results

With respect to overall leukemia susceptibility, no association was detected. In stratified analyses by tumor type, Arg399Gln was associated with higher acute lymphoblastic leukemia (ALL) risk (AA vs. GG, OR  =  1.50, 95% CI: 1.11-2.02; AA+GA vs. GG, OR  =  1.35, 95% CI: 1.02-1.78). Additionally, Arg399Gln, Arg194Trp, and Arg280His may influence the susceptibilities of some leukemia type and race populations.

Conclusion

This meta-analysis indicates these three polymorphisms of XRCC1 do not associate with overall leukemia risks but could be associated with the risks for some specific subgroups.     

Relative Efficiency of the Case-Control to the Cohort Design in Epidemiology

In deriving the efficiency of the stratified to the simple random sample design in survey research, the critical link between the designs is the population analysis of variance. Analogously, the efficiency of the case-control to the cohort design in epidemiologic research can be derived using Bayes' theorem as the essential connection between the designs. Prior information on the odds of the disease is also required. A numerical example using data from Fleiss' text is used to illustrate the result.     

Association between TGFBR1 Polymorphisms and Cancer Risk: A Meta-Analysis of 35 Case-Control Studies

Background

Numerous epidemiological studies have evaluated the association between TGFBR1 polymorphisms and the risk of cancer, however, the results remain inconclusive. To derive a more precise estimation of the relation, we conducted a comprehensive meta-analysis of all available case-control studies relating the TGFBR1*6A and IVS7+24G>A polymorphisms of the TGFBR1 gene to the risk of cancer.

Methods

Eligible studies were identified by search of electronic databases. Overall and subgroup analyses were performed. Odds ratio (OR) and 95% confidence interval (CI) were applied to assess the associations between TGFBR1*6A and IVS7+24G>A polymorphisms and cancer risk.

Results

A total of 35 studies were identified, 32 with 19,767 cases and 18,516 controls for TGFBR1*6A polymorphism and 12 with 4,195 cases and 4,383 controls for IVS7+24G>A polymorphism. For TGFBR1*6A, significantly elevated cancer risk was found in all genetic models (dominant OR = 1.11, 95% CI = 1.04∼1.18; recessive: OR = 1.36, 95% CI = 1.11∼1.66; additive: OR = 1.13, 95% CI = 1.05∼1.20). In subgroup analysis based on cancer type, increased cancer risk was found in ovarian and breast cancer. For IVS7+24G>A, significant correlation with overall cancer risk (dominant: OR = 1.39, 95% CI = 1.15∼1.67; recessive: OR = 2.23, 95% CI = 1.26∼3.92; additive: OR = 1.43, 95% CI = 1.14∼1.80) was found, especially in Asian population. In the subgroup analysis stratified by cancer type, significant association was found in breast and colorectal cancer.

Conclusions

Our investigations demonstrate that TGFBR1*6A and IVS7+24G>A polymorphisms of TGFBR1 are associated with the susceptibility of cancer, and further functional research should be performed to explain the inconsistent results in different ethnicities and cancer types.     

Fish Intake and Ovarian Cancer Risk: A Meta-Analysis of 15 Case-Control and Cohort Studies

Background

Previous epidemiological studies have shown that fish consumption may modify the risk of ovarian cancer. However, these studies yielded controversial results. The present meta-analysis was undertaken to evaluate the relationship between fish intake and ovarian cancer risk.

Methods

A literature search was carried out using Pubmed, Embase, and Cochrane Library Central database for all relevant studies up to August 2013. We pooled the relative risks (RR) from individual studies using fixed-effect or random-effect model, and carried out heterogeneity and publication bias analyses.

Results

A total of 15 (ten case–control, and five cohort) studies were included in the present meta-analysis, representing data for 889,033 female subjects and 6,087 ovarian cancer cases. We found that total fish intake was not significantly associated with the risk of ovarian cancer among cohort studies (RR = 1.04 95% CI [0.89, 1.22]) as well as case–control studies (RR = 0.90, 95% CI [0.73,1.12]). There was no evidence of publication bias as suggested by Begg''s test (P = 0.55) and Egger''s test(P = 0.29).

Conclusions

The present meta-analysis showed that total fish consumption was not significantly associated with the risk of ovarian cancer. Further analysis on different fish species and food preparation methods should be conducted in future studies.     

Association between microRNA Polymorphisms and Cancer Risk Based on the Findings of 66 Case-Control Studies

MicroRNAs (miRNAs) are small non-coding RNA molecules, which participate in diverse biological processes and may regulate tumor suppressor genes or oncogenes. Single nucleotide polymorphisms (SNPs) in miRNA may contribute to diverse functional consequences, including cancer development, by altering miRNA expression. Numerous studies have shown the association between miRNA SNPs and cancer risk; however, the results are generally debatable and inconclusive, mainly due to limited statistical power. To assess the relationship between the five most common SNPs (miR-146a rs2910164, miR-196a2 rs11614913, miR-499 rs3746444, miR-149 rs2292832, and miR-27a rs895919) and the risk cancer development, we performed a meta-analysis of 66 published case-control studies. Crude odds ratios at 95% confidence intervals were used to investigate the strength of the association. No association was observed between rs2910164 and cancer risk in the overall group. However, in stratified analysis, we found that either the rs2910164 C allele or the CC genotype was protective against bladder cancer, prostate cancer, cervical cancer, and colorectal cancer, whereas it was a risk factor for papillary thyroid carcinoma and squamous cell carcinoma of the head and neck (SCCHN). Further, rs11614913 was found to be significantly associated with decreased cancer risk, in particular, for bladder cancer, gastric cancer, and SCCHN. For miR-499, a significant association was found between the rs3746444 polymorphism and cancer risk in pooled analysis. In subgroup analysis, similar results were mainly observed for breast cancer. Finally, no association was found between rs2292832 and rs895919 polymorphisms and cancer risk in the overall group and in stratified analysis. In summary, miR-196a2 rs11614913, miR-146a rs2910164, and miR-499 rs3746444 are risk factors for cancer development, whereas mir-149 rs2292832 and miR-27a rs895919 are not associated with cancer risk.     

Vitamin C Intake and Pancreatic Cancer Risk: A Meta-Analysis of Published Case-Control and Cohort Studies

Background

Observational studies inconsistently reported the relationship between vitamin C intake and risk of pancreatic cancer. We conducted a meta-analysis of published case-control and cohort studies to quantify the association.

Methods

Potentially eligible studies were found on PubMed and EMBASE databases through May 31, 2015. A random-effects model was assigned to compute summary point estimates with corresponding 95% confidence intervals (CIs). Subgroup and meta-regression analyses were also performed to explore sources of heterogeneity.

Results

Our final analyses included 20 observational studies comprising nearly 5 thousand cases of pancreatic cancer. When comparing the highest with the lowest categories of vitamin C intake, the summary odds ratio/relative risk for case-control studies (14 studies), cohort studies (6 studies) and all studies combined was 0.58 (95% CI: 0.52–0.66), 0.93 (95% CI: 0.78–1.11) and 0.66 (95% CI: 0.58–0.75), respectively. The difference in the findings between case-control and cohort studies was statistically significant (P < .001). Possible publication bias was shown in the meta-analysis of case-control studies.

Conclusion

There is insufficient evidence to conclude any relationship between vitamin C intake and risk of pancreatic cancer. The strong inverse association observed in case-control studies may be affected by biases (eg, recall and selection biases) that particularly affect case-control studies and/or potential publication bias. Future prospective studies of vitamin C intake and pancreatic cancer are needed.     

Association of GSTM1 Null Allele with Prostate Cancer Risk: Evidence from 36 Case-Control Studies

Background

Glutathione S-transferase M1 (GSTM1) is thought to be involved in detoxifying several carcinogens and may play a vital role in tumorigenesis. Numerous studies have evaluated the association between GSTM1 null/present polymorphism and risk of prostate cancer (PCa). However, the results remain inconsistent. To derive a more precise estimation, we performed a meta-analysis.

Methodology/Principal Findings

A comprehensive search was conducted to identify all eligible case-control studies. We used odds ratios (ORs) with 95% confidence intervals (CIs) to assess the strength of the association. The overall association was significant (OR = 1.28, 95% CI: 1.11–1.48, P = 0.001). Moreover, subgroup analyses showed GSTM1 null genotype significantly associated with PCa risk among Asians (OR = 1.35, 95% CI: 1.03–1.78, P = 0.03) but not among Caucasians (OR = 1.12, 95% CI: 0.96–1.31, P = 0.16). In addition, we did not find that smoking modified the genotype effect on the risk of PCa.

Conclusions/Significance

The present meta-analysis suggested that GSTM1 null allele was a low-penetrant risk factor for PCa among Asians.     

稀土元素对生物机体剂量效应的研究

综述了稀土元素对生物机体的剂量效应,包括稀土对生物体生长发育、内分泌系统、体内分布及其引发的疾病、细胞毒性及抗诱变、抗癌等影响,以期为稀土在生物学领域的进一步应用提供参考.     

Association between the XRCC1 Polymorphisms and Thyroid Cancer Risk: A Meta-Analysis from Case-Control Studies

Background

The previous published data on the association between the X-ray repair cross-conplementation group 1 (XRCC1) polymorphisms and thyroid cancer risk remained controversial. Hence, we performed a meta-analysis on all available studies that provided 1729 cases and 3774 controls (from 11 studies) for XRCC1 Arg399Gln, 1040 cases and 2487 controls for Arg194Trp (from 7 studies), and 1432 cases and 3356 controls for Arg280His (from 8 studies).

Methodology/Principal Findings

PubMed, CNKI, and EMBASE database were searched to identify relevant studies. Overall, no significant association was found between XRCC1 Arg399Gln (recessive model: OR = 0.95, 95% CI = 0.77–1.15; dominant model: OR = 0.89, 95% CI = 0.75–1.05; homozygote model: OR = 0.92, 95% CI = 0.69–1.23; Heterozygote model: OR = 0.91, 95% CI = 0.80–1.03; additive model: OR = 0.93, 95% CI = 0.81–1.07), Arg194Trp (recessive model: OR = 1.41, 95% CI = 0.62–3.23; dominant model: OR = 1.01, 95% CI = 0.77–1.34; homozygote model: OR = 1.42, 95% CI = 0.55–3.67; Heterozygote model: OR = 1.03, 95% CI = 0.85–1.26; additive model: OR = 1.08, 95% CI = 0.81–1.42), and Arg280His (recessive model: OR = 1.08, 95% CI = 0.56–2.10; dominant model: OR = 1.01, 95% CI = 0.84–1.22; homozygote model: OR = 1.00, 95% CI = 0.51–1.96; Heterozygote model: OR = 1.04, 95% CI = 0.75–1.42; additive model: OR = 1.03, 95% CI = 0.86–1.23) and thyroid cancer risk when all the eligible studies were pooled into the meta-analysis. In the further stratified and sensitivity analyses, significant association was still not found in these three genetic polymorphisms.

Conclusions/Significance

In summary, this meta-analysis indicates that XRCC1 Arg399Gln, Arg280His, and Arg194Trp are not associated with thyroid cancer.