Sanjay Shete

University of Texas MD Anderson Cancer Center, Houston, Texas, United States

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Publications (162)885.28 Total impact

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    ABSTRACT: Gliomas are the most common brain tumor, with several histological subtypes of various malignancy grade. The genetic contribution to familial glioma is not well understood. Using whole exome sequencing of 90 individuals from 55 families, we identified two families with mutations in POT1 (p.G95C, p.E450X), a member of the telomere shelterin complex, shared by both affected individuals in each family and predicted to impact DNA binding and TPP1 binding, respectively. Validation in a separate cohort of 264 individuals from 246 families identified an additional mutation in POT1 (p.D617Efs), also predicted to disrupt TPP1 binding. All families with POT1 mutations had affected members with oligodendroglioma, a specific subtype of glioma more sensitive to irradiation. These findings are important for understanding the origin of glioma and could have importance for the future diagnostics and treatment of glioma. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
    Journal of the National Cancer Institute. 01/2015; 107(1).
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    ABSTRACT: The underlying ethos of dbGaP is that access to these data by secondary data analysts facilitates advancement of science. NIH has required that genome-wide association study data be deposited in the Database of Genotypes and Phenotypes (dbGaP) since 2003. In 2013, a proposed updated policy extended this requirement to next-generation sequencing data. However, recent literature and anecdotal reports suggest lingering logistical and ethical concerns about subject identifiability, informed consent, publication embargo enforcement, and difficulty in accessing dbGaP data. We surveyed the International Genetic Epidemiology Society (IGES) membership about their experiences. One hundred and seventy five (175) individuals completed the survey, a response rate of 27%. Of respondents who received data from dbGaP (43%), only 32% perceived the application process as easy but most (75%) received data within five months. Remaining challenges include difficulty in identifying an institutional signing official and an overlong application process. Only 24% of respondents had contributed data to dbGaP. Of these, 31% reported local IRB restrictions on data release; an additional 15% had to reconsent study participants before depositing data. The majority of respondents (56%) disagreed that the publication embargo period was sufficient. In response, we recommend longer embargo periods and use of varied data-sharing models rather than a one-size-fits-all approach.
    International Journal of Environmental Research and Public Health 08/2014; 11:8383-8398. · 2.00 Impact Factor
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    ABSTRACT: Background: Smoking experimentation in Mexican American youth is problematic. In light of the research showing that preventing smoking experimentation is a valid strategy for smoking prevention, there is a need to identify Mexican American youth at high risk for experimentation. Methods: A prospective population-based cohort of 1179 adolescents of Mexican descent was followed for 5 years starting in 2005-06. Participants completed a baseline interview at a home visit followed by three telephone interviews at intervals of approximately 6 months and additional interviews at two home visits in 2008-09 and 2010-11. The primary end point of interest in this study was smoking experimentation. Information regarding social, cultural, and behavioral factors (e.g., acculturation, susceptibility to experimentation, home characteristics, household influences) was collected at baseline using validated questionnaires. Results: Age, sex, cognitive susceptibility, household smoking behavior, peer influence, neighborhood influence, acculturation, work characteristics, positive outcome expectations, family cohesion, degree of tension, ability to concentrate, and school discipline were found to be associated with smoking experimentation. In a validation dataset, the proposed risk prediction model had an AUC of 0.719 (95% confidence interval, 0.637 to 0.801) for predicting absolute risk for smoking experimentation within 1 year. Conclusions: The proposed risk prediction model is able to quantify the risk of smoking experimentation in Mexican American adolescents. Impact: Accurately identifying Mexican American adolescents who are at higher risk for smoking experimentation who can be intervened will substantially reduce the incidence of smoking and thereby subsequent health risks.
    07/2014;
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    ABSTRACT: Survival outcomes in patients with squamous cell carcinoma of the head and neck (HNSCC) vary by extent of disease, behavioral, and socioeconomic factors. We assessed the extent to which pre-treatment pain influences survival in 2340 newly diagnosed patients with HNSCC, adjusting for disease stage, symptoms, pain medications, comorbidities, smoking, alcohol consumption, age, sex, and race/ethnicity. Patients rated their pain at presentation to the cancer center (0= 'no pain' and 10= 'pain as bad as you can imagine'). Survival time was calculated from the date of diagnosis to the date of death of any cause or last follow-up. Five year overall survival was calculated for all the variables assessed in the study. Severe pain (>7) was most prevalent among those with oral cancer (20.4%; pharynx=18.8%; larynx=16.1%) and significantly varied by tumor stage, fatigue severity, smoking status, comorbid lung disease, and race (all p<0.05) across cancer diagnoses. Overall 5 year survival varied by pain for oral (severe pain=31% versus non-severe=52%; p<0.001) and pharyngeal cancer (severe pain=33%, versus non-severe=53%; p<0.001). Multivariable analyses showed that pain persisted as an independent prognostic factor for survival. Pain reported prior to treatment should be considered in understanding survival outcomes in HNSCC patients.
    The journal of pain : official journal of the American Pain Society. 07/2014;
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    ABSTRACT: Genome-wide association studies (GWAS) have mapped risk alleles for at least ten distinct cancers to a small region of 63,000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (ASSET) across six distinct cancers in 34,248 cases and 45,036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single nucleotide polymorphisms (SNPs): five in the TERT gene (region 1: rs7726159, P=2.10x10-39; region 3: rs2853677, P=3.30x10-36 and PConditional=2.36x10-8; region 4: rs2736098, P=3.87x10-12 and PConditional=5.19x10-6, region 5: rs13172201, P=0.041 and PConditional=2.04x10-6; and region 6: rs10069690, P=7.49x10-15 and PConditional=5.35x10-7) and one in the neighboring CLPTM1L gene (region 2: rs451360; P=1.90x10-18 and PConditional=7.06x10-16). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele specific effects on DNA methylation were seen for a subset of risk loci indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
    Human Molecular Genetics 07/2014; · 7.69 Impact Factor
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    Jian Wang, Robert Yu, Sanjay Shete
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    ABSTRACT: X-chromosome inactivation (XCI) is the process in which one of the two copies of the X-chromosome in females is randomly inactivated to achieve the dosage compensation of X-linked genes between males and females. That is, 50% of the cells have one allele inactive and the other 50% of the cells have the other allele inactive. However, studies have shown that skewed or nonrandom XCI is a biological plausibility wherein more than 75% of cells have the same allele inactive. Also, some of the X-chromosome genes escape XCI, i.e., both alleles are active in all cells. Current statistical tests for X-chromosome association studies can either account for random XCI (e.g., Clayton's approach) or escape from XCI (e.g., PLINK software). Because the true XCI process is unknown and differs across different regions on the X-chromosome, we proposed a unified approach of maximizing likelihood ratio over all biological possibilities: random XCI, skewed XCI, and escape from XCI. A permutation-based procedure was developed to assess the significance of the approach. We conducted simulation studies to compare the performance of the proposed approach with Clayton's approach and PLINK regression. The results showed that the proposed approach has higher powers in the scenarios where XCI is skewed while losing some power in scenarios where XCI is random or XCI is escaped, with well-controlled type I errors. We also applied the approach to the X-chromosomal genetic association study of head and neck cancer.
    Genetic Epidemiology 07/2014; · 4.02 Impact Factor
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    Rajesh Talluri, Jian Wang, Sanjay Shete
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    ABSTRACT: Several methods have been proposed to account for multiple comparisons in genetic association studies. However, investigators typically test each of the SNPs using multiple genetic models. Association testing using the Cochran-Armitage test for trend assuming an additive, dominant, or recessive genetic model, is commonly performed. Thus, each SNP is tested three times. Some investigators report the smallest p-value obtained from the three tests corresponding to the three genetic models, but such an approach inherently leads to inflated type 1 errors. Because of the small number of tests (three) and high correlation (functional dependence) among these tests, the procedures available for accounting for multiple tests are either too conservative or fail to meet the underlying assumptions (e.g., asymptotic multivariate normality or independence among the tests).
    BMC genetics. 06/2014; 15(1):75.
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    ABSTRACT: The aim was to determine the proportions and correlates of essential hypertension among children in a tertiary pediatric hypertension clinic.
    American journal of hypertension. 05/2014;
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    ABSTRACT: IntroductionThe genetic heritability for sensation-seeking tendencies ranges from 40 to 60%. Sensation-seeking behaviors typically manifest during adolescence and are associated with alcohol and cigarette experimentation in adolescents. Social disinhibition is an aspect of sensation-seeking that is closely tied to cigarette and alcohol experimentation.Methods We examined the contribution of candidate genes to social disinhibition among 1132 Mexican origin youth in Houston, Texas, adjusting for established demographic and psychosocial risk factors. Saliva samples were obtained at baseline in 2005–06, and social disinhibition and other psychosocial data were obtained in 2008–09. Participants were genotyped for 672 functional and tagging SNPs potentially related to sensation-seeking, risk-taking, smoking, and alcohol use.ResultsSix SNPs were significantly associated with social disinhibition scores, after controlling for false discovery and adjusting for population stratification and relevant demographic/psychosocial characteristics. Minor alleles for three of the SNPs (rs1998220 on OPRM1; rs9534511 on HTR2A; and rs4938056 on HTR3B) were associated with increased risk of social disinhibition, while minor alleles for the other three SNPs (rs1003921 on KCNC1; rs16116 downstream of NPY; and rs16870286 on LINC00518) exhibited a protective effect. Age, linguistic acculturation, thrill and adventure-seeking, and drug and alcohol-seeking were all significantly positively associated with increased risk of social disinhibition in a multivariable model (P < 0.001).Conclusions These results add to our knowledge of genetic risk factors for social disinhibition. Additional research is needed to verify whether these SNPs are associated with social disinhibition among youth of different ethnicities and nationalities, and to elucidate whether and how these SNPs functionally contribute to social disinhibition.
    Brain and Behavior. 05/2014;
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    ABSTRACT: Although familial susceptibility to glioma is known, the genetic basis for this susceptibility remains unidentified in the majority of glioma-specific families. An alternative approach to identifying such genes is to examine cancer pedigrees, which include glioma as one of several cancer phenotypes, to determine whether common chromosomal modifications might account for the familial aggregation of glioma and other cancers. Germline rearrangements in 146 glioma families (from the Gliogene Consortium; http://www.gliogene.org/) were examined using multiplex ligation-dependent probe amplification. These families all had at least 2 verified glioma cases and a third reported or verified glioma case in the same family or 2 glioma cases in the family with at least one family member affected with melanoma, colon, or breast cancer.The genomic areas covering TP53, CDKN2A, MLH1, and MSH2 were selected because these genes have been previously reported to be associated with cancer pedigrees known to include glioma. We detected a single structural rearrangement, a deletion of exons 1-6 in MSH2, in the proband of one family with 3 cases with glioma and one relative with colon cancer. Large deletions and duplications are rare events in familial glioma cases, even in families with a strong family history of cancers that may be involved in known cancer syndromes.
    Neuro-Oncology 04/2014; · 6.18 Impact Factor
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    Rajesh Talluri, Sanjay Shete
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    ABSTRACT: Graphical models are increasingly used in genetic analyses to take into account the complex relationships between genetic and nongenetic factors influencing the phenotypes. We propose a model for determining the network structure of quantitative traits while accounting for the correlated nature of the family-based samples using the kinship coefficient. The Gaussian graphical model of age, systolic blood pressure, diastolic blood pressure, hypertension, blood pressure medication use, and smoking status was derived for three time points using real data. We also explored binary sparse graphical models of single-nucleotide polymorphisms (SNPs), covariates, and quantitative traits for exploratory analysis of the data. We validated the applicability of this method by producing a network graph using 20 causal variants, 21 noncausal variants, and 6 binary and quantitative phenotypes using the simulated data. To improve the model's ability to identify associations between the causal variants and the phenotypes, we intend to conduct follow-up studies investigating how to use the relationships between SNPs and between SNPs and phenotypes when analyzing genome wide association data with multiple phenotypes.
    BMC proceedings 01/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S99.
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    ABSTRACT: We are now well into the sequencing era of genetic analysis, and methods to investigate rare variants associated with disease remain in high demand. Currently, the more common rare variant analysis methods are burden tests and variance component tests. This report introduces a burden test known as the modified replication based sum statistic and evaluates its performance, and the performance of other common burden and variance component tests under the setting of a small sample size (103 total cases and controls) using the Genetic Analysis Workshop 18 simulated data with complete knowledge of the simulation model. Specifically we look at the variable threshold sum statistic, replication-based sum statistics, the C-alpha, and sequence kernel association test. Using minor allele frequency thresholds of less than 0.05, we find that the modified replication based sum statistic is competitive with all methods and that using 103 individuals leads to all methods being vastly underpowered. Much larger sample sizes are needed to confidently find truly associated genes.
    BMC proceedings 01/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S13.
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    Jian Wang, Robert Yu, Sanjay Shete
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    ABSTRACT: Identifying genetic variants associated with complex diseases is an important task in genetic research. Although association studies based on unrelated individuals (ie, case-control genome-wide association studies) have successfully identified common single-nucleotide polymorphisms for many complex diseases, these studies are not so likely to identify rare genetic variants. In contrast, family-based association studies are particularly useful for identifying rare-variant associations. Recently, there has been some interest in employing multilevel models in family-based genetic association studies. However, the performance of such models in these studies, especially for longitudinal family-based sequence data, has not been fully investigated. Therefore, in this study, we investigated the performance of the multilevel model in the family-based genetic association analysis and compared it with the conventional family-based association test, by examining the powers and type I error rates of the 2 approaches using 3 data sets from the Genetic Analysis Workshop 18 simulated data: genome-wide association single-nucleotide polymorphism data, sequence data, and rare-variants-only data. Compared with the univariate family-based association test, the multilevel model had slightly higher power to identify most of the causal genetic variants using the genome-wide association single-nucleotide polymorphism data and sequence data. However, both approaches had low power to identify most of the causal single-nucleotide polymorphisms, especially those among the relatively rare genetic variants. Therefore, we suggest a unified method that combines both approaches and incorporates collapsing strategy, which may be more powerful than either approach alone for studying genetic associations using family-based data.
    BMC proceedings 01/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S30.
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    ABSTRACT: Because smoking has a profound impact on socioeconomic disparities in illness and death, it is crucial that vulnerable populations of smokers be targeted with treatment. The U.S. Public Health Service recommends that all patients be asked about their smoking at every visit and that smokers be given brief advice to quit and referred to treatment. Initiatives to facilitate these practices include the 5A's (ask, advise, assess, assist, arrange) and Ask-Advise-Refer (AAR). Unfortunately, primary care referrals are low, and most smokers referred fail to enroll. This study evaluated the efficacy of the Ask-Advise-Connect (AAC) approach to linking smokers with treatment in a large, safety net public healthcare system. The study design was a pair-matched group-randomized trial with two treatment arms. Ten safety net clinics in Houston TX. Clinics were randomized to AAC (n=5; intervention) or AAR (n=5; control). Licensed vocational nurses (LVNs) were trained to assess and record the smoking status of all patients at all visits in the electronic health record. Smokers were given brief advice to quit. In AAC, the names and phone numbers of smokers who agreed to be connected were sent electronically to the Texas quitline daily, and patients were proactively called by the quitline within 48 hours. In AAR, smokers were offered a quitline referral card and encouraged to call on their own. Data were collected between June 2010 and March 2012 and analyzed in 2012. The primary outcome was impact, defined here as the proportion of identified smokers that enrolled in treatment. The impact (proportion of identified smokers who enrolled in treatment) of AAC (14.7%) was significantly greater than the impact of AAR (0.5%), t(4)=14.61, p=0.0001, OR=32.10 (95% CI=16.60, 62.06). The AAC approach to aiding smoking cessation has tremendous potential to reduce tobacco-related health disparities. This study is registered at ISRCTN78799157.
    American journal of preventive medicine 12/2013; 45(6):737-41. · 4.24 Impact Factor
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    ABSTRACT: Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
    Genetic Epidemiology 11/2013; · 4.02 Impact Factor
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    ABSTRACT: We studied whether a melanoma survivor-centered intervention was more effective than materials available to the general public in increasing children's sun protection. In a randomized controlled trial, melanoma survivors (n = 340) who had a child ≤12 years received a targeted sun protection intervention (DVD and booklets) or standard education. Primary outcomes were children's sunburns, children's sun protection, and survivors' psychosocial factors at baseline and postintervention (1 and 4 months). The intervention increased children's sunscreen reapplication at 1 month (P = 0.002) and use of wide-brimmed hats at 4 months (P = 0.045). There were no effects on other behaviors or sunburns. The intervention improved survivors' hats/clothing self-efficacy at both follow-up assessments (P = 0.026, 0.009). At 4 months, the intervention improved survivors' clothing intentions (P = 0.029), knowledge (P = 0.010), and outcome expectations for hats (P = 0.002) and clothing (P = 0.037). Children's sun protection increased with survivors' intervention use. The intervention was less effective in survivors who were female or who had a family history, older children, or children with higher baseline sun protection scores. A melanoma survivor-centered sun protection intervention can improve some child and survivor outcomes. The intervention may be more effective in survivors who have younger children or less experience with sun protection. Intervention delivery must be enhanced to maximize use. This is the first study to examine a sun protection intervention for children of melanoma survivors. Findings will guide interventions for this important population at increased melanoma risk. Cancer Epidemiol Biomarkers Prev; 22(10); 1813-24. ©2013 AACR.
    Cancer Epidemiology Biomarkers &amp Prevention 10/2013; 22(10):1813-1824. · 4.56 Impact Factor
  • Cancer Epidemiology Biomarkers &amp Prevention 08/2013; 21(11_Supplement):04-4. · 4.56 Impact Factor
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    ABSTRACT: Symptom clusters, the multiple, co-occurring symptoms experienced by cancer patients, are debilitating and affects quality of life. We assessed if a panel of immune-response genes may underlie the co-occurrence of severe pain, depressed mood, and fatigue and help identify patients with severe versus non-severe symptom clusters. Symptoms were assessed at presentation, prior to cancer treatment in 599 newly diagnosed lung cancer patients. We applied cluster analyses to determine the patients with severe versus non-severe symptom clusters of pain, depressed mood, and fatigue. Two homogenous clusters were identified. One hundred sixteen patients (19 %) comprised the severe symptom cluster, reporting high intensity of pain, depressed mood, and fatigue and 183 (30 %) patients reported low intensity of these symptoms. Using Bayesian model averaging methodology, we found that of the 55 single nucleotide polymorphisms assessed, an additive effect of mutant alleles in endothelial nitric oxide synthase (-1474 T/A) (posterior probability of inclusion (PPI) = 0.78, odds ratio (OR) = 0.54, 95 % credible interval (CI) = (0.31, 0.93)); IL1B T-31C (PPI = 0.72, OR = 0.55, 95 % CI = (0.31, 0.97)); TNFR2 Met(196)Arg (PPI = 0.70, OR = 1.85, 95 % CI = (1.03, 3.36)); PTGS2 exon 10+837T > C (PPI = 0.69, OR = 0.54, 95 % CI = (0.28, 0.99)); and IL10RB Lys(47)Glu (PPI = 0.68; OR = 1.74; 95 % CI = (1.04, 2.92)) were predictive for symptom clusters. Genetic polymorphisms may facilitate identification of high-risk patients and development of individualized symptom therapies.
    Supportive Care in Cancer 07/2013; · 2.09 Impact Factor
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    ABSTRACT: Background:Most of the heritable risk of glioma is presently unaccounted for by mutations in known genes. In addition to rare inactivating germline mutations in TP53 causing glioma in the context of the Li-Fraumeni syndrome, polymorphic variation in TP53 may also contribute to the risk of developing glioma.Methods:To comprehensively evaluate the impact of variation in TP53 on risk, we analysed 23 tagSNPs and imputed 2377 unobserved genotypes in four series totaling 4147 glioma cases and 7435 controls.Results:The strongest validated association signal was shown by the imputed single-nucleotide polymorphism (SNP) rs78378222 (P=6.86 × 10(-24), minor allele frequency ∼0.013). Confirmatory genotyping confirmed the high quality of the imputation. The association between rs78378222 and risk was seen for both glioblastoma multiforme (GBM) and non-GBM tumours. We comprehensively examined the relationship between rs78378222 and overall survival in two of the case series totaling 1699 individuals. Despite employing statistical tests sensitive to the detection of differences in early survival, no association was shown.Conclusion:Our data provided strong validation of rs78378222 as a risk factor for glioma but do not support the tenet that the polymorphism being a clinically useful prognostic marker. Acquired TP53 inactivation is a common feature of glioma. As rs78378222 changes the polyadenylation signal of TP53 leading to impaired 3'-end processing of TP53 mRNA, the SNP has strong plausibility for being directly functional contributing to the aetiological basis of glioma.British Journal of Cancer advance online publication, 9 April 2013; doi:10.1038/bjc.2013.155 www.bjcancer.com.
    British Journal of Cancer 04/2013; · 5.08 Impact Factor
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    ABSTRACT: IMPORTANCE Several national health care-based smoking cessation initiatives have been recommended to facilitate the delivery of evidence-based treatments, such as quitline (telephone-based tobacco cessation services) assistance. The most notable examples are the 5 As (Ask, Advise, Assess, Assist, Arrange) and Ask. Advise. Refer. (AAR) programs. Unfortunately, rates of primary care referrals to quitlines are low, and most referred smokers fail to call for assistance. OBJECTIVE To evaluate a new approach-Ask-Advise-Connect (AAC)-designed to address barriers to linking smokers with treatment. DESIGN A pair-matched, 2-treatment-arm, group-randomized design in 10 family practice clinics in a single metropolitan area. Five clinics were randomized to the AAC (intervention) and 5 to the AAR (control) conditions. In both conditions, clinic staff were trained to assess and record the smoking status of all patients at all visits in the electronic health record, and smokers were given brief advice to quit. In the AAC clinics, the names and telephone numbers of smokers who agreed to be connected were sent electronically to the quitline daily, and patients were called proactively by the quitline within 48 hours. In the AAR clinics, smokers were offered a quitline referral card and encouraged to call on their own. All data were collected from February 8 through December 27, 2011. SETTING Ten clinics in Houston, Texas. PARTICIPANTS Smoking status assessments were completed for 42 277 patients; 2052 unique smokers were identified at AAC clinics, and 1611 smokers were identified at AAR clinics. INTERVENTIONS Linking smokers with quitline-delivered treatment. MAIN OUTCOME MEASURE Impact was based on the RE-AIM (Reach, Efficacy, Adoption, Implementation, and Maintenance) conceptual framework and defined as the proportion of all identified smokers who enrolled in treatment. RESULTS In the AAC clinics, 7.8% of all identified smokers enrolled in treatment vs 0.6% in the AAR clinics (t4 = 9.19 [P < .001]; odds ratio, 11.60 [95% CI, 5.53-24.32]), a 13-fold increase in the proportion of smokers enrolling in treatment. CONCLUSIONS AND RELEVANCE The system changes implemented in the AAC approach could be adopted broadly by other health care systems and have tremendous potential to reduce tobacco-related morbidity and mortality.
    JAMA Internal Medicine 02/2013; · 13.25 Impact Factor

Publication Stats

5k Citations
885.28 Total Impact Points

Institutions

  • 2002–2014
    • University of Texas MD Anderson Cancer Center
      • Department of Epidemiology
      Houston, Texas, United States
  • 2013
    • University of Texas at Austin
      Austin, Texas, United States
    • Tel Aviv University
      Tell Afif, Tel Aviv, Israel
  • 2012
    • Baylor College of Medicine
      • Dan L. Duncan Cancer Center
      Houston, TX, United States
  • 2010–2011
    • Institute of Cancer Research
      • Division of Genetics and Epidemiology
      London, ENG, United Kingdom
  • 2005–2011
    • University of Texas Health Science Center at Houston
      • Department of Internal Medicine
      Houston, Texas, United States
  • 2006–2010
    • University of Texas Medical School
      • Department of Internal Medicine
      Houston, TX, United States
  • 2008
    • Washington University in St. Louis
      San Luis, Missouri, United States
  • 2000
    • Case Western Reserve University
      • Department of Epidemiology and Biostatistics
      Cleveland, OH, United States