bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract A03: Risk prediction for gastric cancer using the GWAS-identified SNPs, Helicobacter pylori infection and lifestyle-related risk factors in a Japanese population
Authors: Ito Hidemi , Oze Isao , Matsuo Keitaro 
Published: May 2019

Abstract
Advances in molecular genetics have the potential to impact cancer prevention. However, the contribution of this information to determining the risk of cancer of the stomach at the population level in combination with biological and lifestyle-related factors has not been evaluated. Here, we established a risk prediction model of gastric cancer using genetic, biological, and lifestyle-related risk factors as a potential practical application in interventions for cancer prevention.
We conducted two independent age- and sex-matched case-control studies, the first for model derivation (697 cases and 1,372 controls) and the second (678 and 678) for external validation. Using the derivation study data, we developed a prediction model by fitting a conditional logistic regression model using the following predictors: age, ABCD classification defined by H.pylori infection and atrophic gastritis, smoking, fruit and vegetable intake, and selected GWAS-identified genotypes. Performance was assessed regarding discrimination (area under the curve, AUC), calibration (calibration plots and Hosmer-Lemeshow test) and reclassification (integrated discrimination improvement (IDI)).
We preliminarily found that a combination of rs229400, one of the GWAS-identified SNPs, H.Pylori infection, atrophic gastritis, smoking and fruit and vegetable intake provided high discriminatory accuracy and good calibration in both the derivation and validation studies, with AUCs of 0.78 (95% confidence intervals, 0.76-0.80) and 0.80 (0.77-0.82), respectively. The calibration plots of both studies stayed close to the ideal calibration line. IDI indices were 0.12 (p&lt;0.00001). We will establish a final model with selected GWAS-identified SNPs in addition to rs2294008, and the other predictors.
Citation Format: Hidemi Ito, Isao Oze, Keitaro Matsuo. Risk prediction for gastric cancer using the GWAS-identified SNPs, Helicobacter pylori infection and lifestyle-related risk factors in a Japanese population. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A03.
Abstract A13: Tooth loss, liver cancer incidence, and chronic liver disease mortality in the ATBC study
Authors: Yang Baiyu , Petrick Jessica L. , Abnet Christian C. , Graubard Barry I. , Weinstein Stephanie J. , Männistö Satu , Albanes Demetrius , McGlynn Katherine A. 
Published: May 2019

Abstract
Background: Periodontal disease, a common disorder of the tissue surrounding and supporting the teeth, is a major cause of tooth loss in adults. Periodontal infection by oral microorganisms may have systemic effects and has been associated with several types of cancer. However, its association with liver cancer has only been examined in two prospective studies, both of which had very small number of liver cancer cases (n &lt; 20).
Methods: We examined the association of tooth loss, as a proxy measure of periodontal infection, with primary liver cancer incidence and chronic liver disease mortality in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study, a prospective cohort of male Finnish smokers (n = 29,096). Number of permanent teeth lost was assessed at study baseline (1985-1988). We used Cox proportional hazards models to calculate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). As a sensitivity analysis, we conducted a nested case-control study to assess confounding by hepatitis B or C virus (HBV or HCV) infection and seropositivity of Helicobacter pylori.
Results: A total of 213 incident primary liver cancers occurred during a mean follow-up of 17 years. Having 11-31 permanent teeth lost was associated with a 42% higher risk of liver cancer (HR=1.42, 95% CI: 1.01-1.98), and having all 32 teeth lost was associated with a 45% higher risk of liver cancer (HR=1.45, 95% CI: 1.00-2.10), compared to having 0-10 teeth lost. In the sensitivity analysis, adjusting for Helicobacter pylori seropositivity yielded a modest attenuation of the effect estimate, whereas adjustment for HBV or HCV did not materially change the results. No consistent pattern was observed for liver disease mortality (n = 250 deaths).
Conclusions: In this study, greater number of teeth lost was associated with higher risk of primary liver cancer. Further investigations are warranted to clarify the role of periodontal infection in hepatocarcinogenesis and to determine the utility of tooth loss as a predictor of liver cancer development.
Citation Format: Baiyu Yang, Jessica L. Petrick, Christian C. Abnet, Barry I. Graubard, Stephanie J. Weinstein, Satu Männistö, Demetrius Albanes, Katherine A. McGlynn. Tooth loss, liver cancer incidence, and chronic liver disease mortality in the ATBC study. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A13.
Abstract A18: Using frailty models to improve familial cancer risk prediction
Authors: Huang Theodore , Braun Danielle , Gorfine Malka , Parmigiani Giovanni 
Published: May 2019

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR06) of the Conference Proceedings.
Citation Format: Theodore Huang, Danielle Braun, Malka Gorfine, Giovanni Parmigiani. Using frailty models to improve familial cancer risk prediction. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A18.
Abstract B21: The study of β-glucan on the release of nitric oxide by macrophages stimulated with lipopolysaccharide
Authors: Cho Kwang Keun 
Published: May 2019

Abstract
This research analyzed the effect of β-glucan that is expected to alleviate the production of the inflammatory mediator in a macrophagocyte, which was processed by the lipopolysaccharide (LPS) of Escherichia, a pathogen related to allergy. The incubated layer was used for a nitric oxide (NO) analysis. The DNA-binding activation of the small unit of NF-κB was measured using the ELISA-based kit. In the RAW264.7 cells that were vitalized by E.coli LPS, the β-glucan inhibited both the combatant and rendering phases of the inducible NO synthase (iNOS)-derived NO. β-glucan increased the expression of the heme oxygenase-1 (HO-1) in the cell that was stimulated by E.coli LPS, and the HO-1 activation was inhibited by the SnPP. This shows that the NO production induced by LPS is related to the inhibition effect of β-glucan. The phosphorylation of JNK and the p38 induced by the LPS were not influenced by the β-glucan, and the IκB-α decomposition was not influenced either. Instead, β-glucan remarkably inhibited the phosphorylation of the STAT1 that was induced by the E.coli LPS. Overall, the β-glucan inhibited the production of NO in the macrophagocyte that was vitalized by the E.coli LPS through the HO-1 induction and the STAT1 pathways inhibition in this research. As the host inflammation reaction control by β-glucan weakens the progress of the allergies, β-glucan can be used as an effective treatment method.
Note: This abstract was not presented at the conference.
Citation Format: Kwang Keun Cho, Sr. The study of β-glucan on the release of nitric oxide by macrophages stimulated with lipopolysaccharide. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B21.
Abstract B25: Association of variations in HLA-class II and other loci with susceptibility to EGFR-mutated lung adenocarcinoma
Authors: Shiraishi Kouya , Okada Yukinori , Takahashi Atsushi , Kamatani Yoichiro , Ashikawa Kyota , Momozawa Yukihide , Kunitoh Hideo , Matsumoto Shingo , Takano Atsushi , Shimizu Kimihiro , Goto Akiteru , Tsuta Koji , Watanabe Shun-ichi , Ohe Yuichiro , Watanabe Yukio , Goto Yasishi , Nokihara Hiroshi , Furuta Koh , Yoshida Akihiko , Goto Koichi , Hishida Tomoyuki , Tsuboi Masahiro , Tsuchihara Katsuya , Miyagi Yohei , Nakamura Haruhiko , Yokose Tomoyuki , Tanaka Katsuya , Nagashima Toshiteru , Ohtaki Yoichi , Maeda Daichi , Imai Kazuhiro , Minamiya Yoshihiro , Sakamoto Hiromi , Saito Akira , Shimada Yoko , Sunami Kuniko , Saito Motonobu , Yoshida Teruhiko , Yokota Jun , Matsuda Fumihiko , Matsuo Keitaro , Daigo Yataro , Kubo Michiaki , Kohno Takashi 
Published: May 2019

Abstract
Background: Lung adenocarcinoma (LADC) driven by somatic EGFR mutations is more prevalent in East Asians (30-50%) than in European/Americans (10-20%). Understanding the genetic factors underlying such LADC is required to elucidate disease etiology and to identify effective methods of prevention.
Methods: We investigate genetic factors underlying the risk of this disease by conducting a genome-wide association study, followed by two validation studies, in 3,173 Japanese patients with EGFR mutation-positive lung adenocarcinoma and 15,158 controls.
Results: Four loci, 5p15.33 (TERT), 6p21.3 (BTNL2, HLA-class II), 3q28 (TP63) and 17q24.2 (BPTF), previously shown to be strongly associated with overall lung adenocarcinoma risk in East Asians, were re-discovered as loci associated with a higher susceptibility to EGFR mutation-positive.
Citation Format: Kouya Shiraishi, Yukinori Okada, Atsushi Takahashi, Yoichiro Kamatani, Kyota Ashikawa, Yukihide Momozawa, Hideo Kunitoh, Shingo Matsumoto, Atsushi Takano, Kimihiro Shimizu, Akiteru Goto, Koji Tsuta, Shun-ichi Watanabe, Yuichiro Ohe, Yukio Watanabe, Yasishi Goto, Hiroshi Nokihara, Koh Furuta, Akihiko Yoshida, Koichi Goto, Tomoyuki Hishida, Masahiro Tsuboi, Katsuya Tsuchihara, Yohei Miyagi, Haruhiko Nakamura, Tomoyuki Yokose, Katsuya Tanaka, Toshiteru Nagashima, Yoichi Ohtaki, Daichi Maeda, Kazuhiro Imai, Yoshihiro Minamiya, Hiromi Sakamoto, Akira Saito, Yoko Shimada, Kuniko Sunami, Motonobu Saito, Teruhiko Yoshida, Jun Yokota, Fumihiko Matsuda, Keitaro Matsuo, Yataro Daigo, Michiaki Kubo, Takashi Kohno. Association of variations in HLA-class II and other loci with susceptibility to EGFR-mutated lung adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B25.
Abstract B26: Pre- and post-diagnostic use of nonsteroidal anti-inflammatory drugs and prostate cancer mortality among men diagnosed with prostate cancer in the NIH-AARP and PLCO cohorts
Authors: Zhou Cindy Ke , Daugherty Sarah E. , Black Amanda , Liao Linda M. , Freedman Neal D. , Abnet Christian C. , Pfeiffer Ruth , Cook Michael B. 
Published: May 2019

Abstract
Background: Prostate cancer is the second leading cause of cancer death in American men, but few modifiable risk factors have been established for prostate cancer progression and survival. Experimental studies have suggested that nonsteroidal anti-inflammatory drugs (NSAIDs) may improve prostate cancer survival through anti-thrombotic and anti-inflammation mechanisms. However, previous observational studies have shown mixed results. No study has examined over-the-counter non-aspirin NSAIDs in relation to prostate cancer survival. Few studies have assessed aspirin use before prostate cancer diagnosis in relation to prostate cancer survival, and whether any etiologically relevant time window of exposure exists remains unclear.
Methods: We assessed two cohorts of prostate cancer cases from two large prospective studies in the United States NIH-AARP Diet and Health Study and Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to investigate associations of aspirin and other nonselective non-aspirin NSAID use before and after prostate cancer diagnosis with prostate cancer-specific and all-cause mortality. Cox proportional hazards models with age as the time metric were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results across the two studies were meta-analyzed in a fixed effects model if consistent associations were observed.
Results: We did not find statistically significant associations of pre- or post-diagnostic NSAID use with prostate cancer-specific mortality. However, aspirin users versus nonusers five years or more before prostate cancer diagnosis had a 14% (95%CI=0.74 to 1.00) and a 16% (95%CI=0.78 to 0.89) reduced prostate cancer-specific and all-cause mortality when combining the two studies. Post-diagnostic occasional (less than once per day) and daily aspirin use were associated with 17% (95%CI=0.72 to 0.95) and 25% (95%CI=0.66 to 0.86) reductions in all-cause mortality independent of pre-diagnostic use, comparing with no use.
Conclusions: This analysis suggests a modest delayed survival benefit of aspirin use before prostate cancer diagnosis and highlights the importance of comorbidity prevention among prostate cancer survivors.
Citation Format: Cindy Ke Zhou, Sarah E. Daugherty, Amanda Black, Linda M. Liao, Neal D. Freedman, Christian C. Abnet, Ruth Pfeiffer, Michael B. Cook. Pre- and post-diagnostic use of nonsteroidal anti-inflammatory drugs and prostate cancer mortality among men diagnosed with prostate cancer in the NIH-AARP and PLCO cohorts. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B26.
Abstract B28: Clinicopathological features associated with late recurrence of gastric cancer
Authors: Park Ji Soo , Won Chu Ree , Son Taeil , Kim Hyoung-Il , Hyung Woo Jin , Noh Sung Hoon , Kim Tae Il 
Published: May 2019

Abstract
Background: Because most cases of cancer recurrence occur within 5 years, routine surveillance is also recommended for first five years. However, few patients experience late recurrence of disease, and the mechanism of late recurrence is not clearly revealed. The purpose of this study is to evaluate the clinicopathological features predicting the risk of late recurrence in gastric cancer patients.
Methods: From January 2006 to December 2013, we retrospectively reviewed 813 patients who were diagnosed and treated with gastric cancer in Yonsei cancer center.
Result: Among 226 patients who experienced recurrence of gastric cancer, 212 patients were diagnosed with recurrence within first five years from the curative resection of primary cancer, and 14 patients were diagnosed with recurrence of disease beyond 5 years. In comparison with early recurrence (≤ 5 years), the patients with late recurrence (&gt; 5 years) had primary disease of stage I/II (vs. stage III; HR, 4.5; 95% CI, 1.5-14.1; P=0.009), well or moderately differentiated histology (vs. poorly differentiated or signet ring cell; HR, 4.2; 95% CI, 1.4-13.1; P=0.013), and did not receive adjuvant chemotherapy (HR, 0.3; 95% CI, 0.1-0.9; P=0.028). All the 21 patients with HER2 positive gastric cancer experienced early recurrence.
Conclusion: Late recurrence of gastric cancer is possibly not influenced by advanced stage of primary disease. More attempts to find high risk groups for late recurrence of gastric cancer are needed.
Citation Format: Ji Soo Park, Chu Ree Won, Taeil Son, Hyoung-Il Kim, Woo Jin Hyung, Sung Hoon Noh, Tae Il Kim. Clinicopathological features associated with late recurrence of gastric cancer. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B28.
Abstract IA03: Requirements for a statistical prediction model to receive AJCC endorsement
Authors: Kattan Michael W. 
Published: May 2019

Abstract
The American Joint Committee on Cancer (AJCC) has recognizes the need for more personalized predictions than those delivered by cancer staging systems. In particular, the use of accurate risk models or calculators is seen as valuable. However, judging the quality and acceptability of a risk model is difficult. The AJCC Precision Medicine Core formed a committee to establish inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. They identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement. The criteria centered on performance metrics, implementation clarity, and clinical relevance. These criteria will be described.
Citation Format: Michael W. Kattan. Requirements for a statistical prediction model to receive AJCC endorsement. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA03.
Abstract IA05: Modeling genetic susceptibility to breast cancer
Authors: Antoniou Antonis C. 
Published: May 2019

Abstract
Several breast cancer genetic susceptibility variants have been identified to date. These include mutations in the high risk BRCA1 and BRCA2 genes, other rare genetic variants conferring intermediate to high risks (e.g. PALB2, CHEK2, ATM and others) and &gt;150 common alleles (SNPs) conferring low risks. The presentation will provide an overview of the latest developments and challenges in understanding the penetrance of mutations in BRCA1, BRCA2 and PALB2. Genetic counseling of women with BRCA1 and BRCA2 mutations currently relies on average cancer risk estimates obtained from retrospective penetrance studies. The talk will present penetrance estimates from ongoing prospective analyses, based on data from the International BRCA1/2 Carrier Cohort Study, the largest prospective cohort of BRCA1/2 mutation carriers that includes ~10,000 BRCA1/2 mutation carriers with follow-up information. The talk will also review the latest efforts and results from the Consortium of Investigators of Modifiers of BRCA1/2 to identify and characterise genetic modifiers of cancer risks for BRCA1 and BRCA2 mutation carriers and to provide individualized cancer risks for women with BRCA1 and BRCA2 mutations. Finally, the presentation will describe the efforts to develop a comprehensive risk prediction model for breast cancer, specifically the BOADICEA model that includes the explicit effects of mutations in BRCA1, BRCA2, PALB2, CHEK2, ATM, and of the common breast cancer susceptibility variants identified through genome-wide association studies.
Citation Format: Antonis C. Antoniou. Modeling genetic susceptibility to breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA05.
Abstract IA19: Can biomarkers be used to improve risk prediction models on lung cancer?
Authors: Johansson Mattias 
Published: May 2019

Abstract
Lung cancer kills over 1.6 million people every year, making it the chief cause of cancer death worldwide. The US National Lung Cancer Screening Trial (NLST) demonstrated in 2011 that screening with computed tomography (CT) scans could reduce lung cancer mortality by 20% and total mortality by 7%. As a result, the US Preventive Services Task Force (USPSTF) has recommended LDCT-screening for lung cancer in ever-smokers aged 55-80 years who have smoked 30 pack-years with no more than 15 years since quitting.
However, the NLST study also highlighted several important negative aspects of CT screening in terms of morbidity associated with over-diagnosis, treatment of benign nodules, and financial costs. The study also indicated important differences in the benefit of screening in different participant groups as defined by their underlying risk of lung cancer, highlighting the urgent need to improve and implement risk prediction models when identifying those individuals that are at high risk and most likely to benefit from lung cancer screening. Concurrently, multiple research groups, including ours, have explored the hypothesis that circulating biomarkers can capture information on risk that cannot be provided with questionnaires. In particular, we have evaluated the potential of improving upon the USPSTF lung cancer screening criteria using a small panel of selected tumour-related proteins, data on which will be presented during the conference.
Citation Format: Mattias Johansson. Can biomarkers be used to improve risk prediction models on lung cancer? [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA19.
Abstract IA20: Maximizing the impact of risk prediction models: Leveraging lessons learned from risk communication research
Authors: Klein. William MP 
Published: May 2019

Abstract
The most promising new medications are doomed to be ineffective if not adequately prescribed and taken as directed by patients, highlighting the grave importance of understanding the vicissitudes of human behavior. The same might be said of risk prediction tools. Irrespective of their quality and validity, the successful use and impact of such tools hinges firmly on a thorough understanding of human motivation, emotion, and cognition – the building blocks of human behavior and decision-making. In general, people desire to minimize loss, uncertainty, and ambiguity, and they hold defensive self-serving beliefs about their risk and risk factors, particularly when they compare themselves to other people. People also construe risk in terms of dimensions such as dread, absolute frequency, controllability, and intuition rather than objective likelihood, and fail to consider base rates when assessing risk (rendering their risk judgments non-Bayesian). They also endeavor to appear to themselves and others as rational actors, often leading to the paradoxical choice of non-dominant options, and are influenced – often beyond awareness – by incidental emotions and secondary motives such as managing existential anxiety when evaluating personal risk and making consequential decisions. People also vary greatly in how they use and comprehend numerical information and in the comfort with which they do so. Risk communication strategies have been developed to reduce the undesired consequences of these phenomena on risk perception and decision making, and in some cases can be implemented quite easily into the outward design of a risk prediction tool as well as the manner in which it is used in clinical practice.
Citation Format: William MP Klein. Maximizing the impact of risk prediction models: Leveraging lessons learned from risk communication research. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA20.