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51. The role of oral hygiene in head and neck cancer: results from International Head and Neck Cancer Epidemiology (INHANCE) consortium

Author

Hashim, D., Sartori, S., Brennan, P., Curado, M.P., Wünsch-Filho, V., Divaris, K., Olshan, A.F., Zevallos, J.P., Winn, D.M., Franceschi, S., Castellsagué, X., Lissowska, J., Rudnai, P., Matsuo, K., Morgenstern, H., Chen, C., Vaughan, T.L., Hofmann, J.N., D'Souza, G., Haddad, R.I., Wu, H., Lee, Y.-C., Hashibe, M., Vecchia, C.La, and Boffetta, P.

Published
2016
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52. Significance of histologic pattern of carcinoma and sarcoma components on survival outcomes of uterine carcinosarcoma

Author

Matsuo, K., Takazawa, Y., Ross, M.S., Elishaev, E., Podzielinski, I., Yunokawa, M., Sheridan, T.B., Bush, S.H., Klobocista, M.M., Blake, E.A., Takano, T., Matsuzaki, S., Baba, T., Satoh, S., Shida, M., Nishikawa, T., Ikeda, Y., Adachi, S., Yokoyama, T., Takekuma, M., Fujiwara, K., Hazama, Y., Kadogami, D., Moffitt, M.N., Takeuchi, S., Nishimura, M., Iwasaki, K., Ushioda, N., Johnson, M.S., Yoshida, M., Hakam, A., Li, S.W., Richmond, A.M., Machida, H., Mhawech-Fauceglia, P., Ueda, Y., Yoshino, K., Yamaguchi, K., Oishi, T., Kajiwara, H., Hasegawa, K., Yasuda, M., Kawana, K., Suda, K., Miyake, T.M., Moriya, T., Yuba, Y., Morgan, T., Fukagawa, T., Wakatsuki, A., Sugiyama, T., Pejovic, T., Nagano, T., Shimoya, K., Andoh, M., Shiki, Y., Enomoto, T., Sasaki, T., Mikami, M., Shimada, M., Konishi, I., Kimura, T., Post, M.D., Shahzad, M.M., Im, D.D., Yoshida, H., Omatsu, K., Ueland, F.R., Kelley, J.L., Karabakhtsian, R.G., and Roman, L.D.

Published
2016
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54. Enhancing laser beam performance by interfering intense laser beamlets

Author

Morace, A., Iwata, N., Sentoku, Y., Mima, K., Arikawa, Y., Yogo, A., Andreev, A., Tosaki, S., Vaisseau, X., Abe, Y., Kojima, S., Sakata, S., Hata, M., Lee, S., Matsuo, K., Kamitsukasa, N., Norimatsu, T., Kawanaka, J., Tokita, S., Miyanaga, N., Shiraga, H., Sakawa, Y., Nakai, M., Nishimura, H., Azechi, H., Fujioka, S., and Kodama, R.

Published
2019
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56. Geodetic measurements and quantitative evaluation for reduced gravitational redshift uncertainty of optical frequency standards

Author

Ichikawa, R., Hachisu, H., Sekido, M., Ido, T., Hiraoka, Y., Harima, E., Fukaya, S., Matsuo, K., Nakashima, M., Hattori, A., Aoyama, Y., Fukuda, Y., Imanishi, Y., Honda, R., and Kazama, T.

Abstract

The National Institute of Information and Communications Technology (NICT) has developed a Sr optical lattice clock and optical ion clocks employing In+and Ca+. The centimeter-level uncertainty of site elevation is the cause of 10^(-18)-level frequency uncertainties of optical frequency standards. It is significantly important to understand frequency changes caused by solid-earth tides that often range from 10 to 20 cm in amplitude, by oceanic tidal loading, crustal deformations due to earthquakes, and ground movements with groundwater changes for the stable operation of optical atomic clocks.NICT and partners including the Geospatial Information Authority of Japan (GSI) have been jointly conducting leveling surveys and relative gravimeter observations at NICT’s headquarters in Koganei. These observations reduce the contribution of gravitational redshift to the total uncertainty of the optical lattice clock to the 10^(-19)level. With the support of National Institute of Polar Research (NIPR), absolute gravity measurements were performed in August 2019 and May 2022 to evaluate the effects of the 2011 off the Pacific coast of Tohoku Earthquake on postseismic crustal movement. The obtained absolute gravity change between the two periods was -43.8 μGal, which matches the trend of GNSS vertical movement obtained by GSI. We have introduced a Micro-g LaCoste’s gPhoneX gravimeter for continuous gravity measurements nearby the optical clocks in the end of 2021 and have started to investigate the temporal variation of the ground water level in Koganei. We will present preliminary results of these geodetic measurements., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Published
2023
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60. Association of vegetable and fruit intake with gastric cancer risk among Japanese: a pooled analysis of four cohort studies

Author

Sasazuki, Shizuka, Tsugane, Shoichiro, Inoue, Manami, Iwasaki, Motoki, Otani, Tetsuya, Sawada, Norie, Shimazu, Taichi, Yamaji, Taiki, Tsuji, Ichiro, Tsubono, Yoshitaka, Nishino, Yoshikazu, Tamakoshi, Akiko, Matsuo, Keitaro, Ito, Hidemi, Wakai, Kenji, Nagata, Chisato, Mizoue, Tetsuya, Tanaka, Keitaro, Shimazu, T., Wakai, K., Tamakoshi, A., Tsuji, I., Tanaka, K., Matsuo, K., Nagata, C., Mizoue, T., Inoue, M., Tsugane, S., and Sasazuki, S.

Published
2014
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61. Lobar analysis of collapsibility indices to assess functional lung volumes in COPD patients

Author

Kitano M, Iwano S, Hashimoto N, Matsuo K, Hasegawa Y, and Naganawa S

Subjects
Diseases of the respiratory system, RC705-779
Abstract

Mariko Kitano,1 Shingo Iwano,1 Naozumi Hashimoto,2 Keiji Matsuo,3 Yoshinori Hasegawa,2 Shinji Naganawa1 1Department of Radiology, 2Department of Respiratory Medicine, Graduate School of Medicine, Nagoya University, Nagoya, Aichi, Japan; 3Department of Radiology, Ichinomiya Municipal Hospital, Ichinomiya, Aichi, Japan Background: We investigated correlations between lung volume collapsibility indices and pulmonary function test (PFT) results and assessed lobar differences in chronic obstructive pulmonary disease (COPD) patients, using paired inspiratory and expiratory three dimensional (3D) computed tomography (CT) images. Methods: We retrospectively assessed 28 COPD patients who underwent paired inspiratory and expiratory CT and PFT exams on the same day. A computer-aided diagnostic system calculated total lobar volume and emphysematous lobar volume (ELV). Normal lobar volume (NLV) was determined by subtracting ELV from total lobar volume, both for inspiratory phase (NLVI) and for expiratory phase (NLVE). We also determined lobar collapsibility indices: NLV collapsibility ratio (NLVCR) (%) = (1 - NLVE/NLVI) × 100%. Associations between lobar volumes and PFT results, and collapsibility indices and PFT results were determined by Pearson correlation analysis. Results: NLVCR values were significantly correlated with PFT results. Forced expiratory volume in 1 second, measured as percent of predicted results (FEV1%P) was significantly correlated with NLVCR values for the lower lobes (P

Published
2014

64. EP.06B.04 Aging Alteration of Biomarkers and Its Prognostic Role in Elderly Lung Cancer Patients Treated with Adjuvant S-1 Chemotherapy

Author

Soh, J., Yamamoto, H., Okumura, N., Suzuki, H., Nakata, M., Fujiwara, T., Genma, K., Sano, I., Fujinaga, T., Kataoka, M., Terazaki, Y., Fujimoto, N., Kataoka, K., Kosaka, S., Yamashita, M., Inokawa, H., Inoue, M., Nakamura, H., Yamashita, Y., Takahashi, Y., Torigoe, H., Sato, H., Tomida, S., Hotta, K., Yoshioka, H., Morita, S., Matsuo, K., Sakamoto, J., Date, H., and Toyooka, S.

Published
2024
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65. Lessons learned from the INHANCE consortium: An overview of recent results on head and neck cancer

Author

Bravi, F, Lee, Y, Hashibe, M, Boffetta, P, Conway, D, Ferraroni, M, La Vecchia, C, Edefonti, V, Agudo, A, Ahrens, W, Benhamou, S, Boccia, S, Brennan, P, Brenner, H, Cadoni, G, Canova, C, Chen, C, Chuang, S, Curado, M, Dal Maso, L, Daudt, A, D'Souza, G, Fabianova, E, Fernandez, L, Franceschi, S, Garavello, W, Gillison, M, Gross, N, Hayes, R, Healy, C, Herrero, R, Holcatova, I, Kelsey, K, Kjaerheim, K, Koifman, R, Lagiou, P, Lazarus, P, Levi, F, Li, G, Lissowska, J, Luce, D, Macfarlane, G, Mates, D, Matsuo, K, Mcclean, M, Menezes, A, Menvielle, G, Morgenstern, H, Moyses, R, Moysich, K, Muscat, J, Negri, E, Olshan, A, Pandics, T, Polesel, J, Purdue, M, Radoi, L, Ramroth, H, Richiardi, L, Schantz, S, Schwartz, S, Serraino, D, Shangina, O, Smith, E, Sturgis, E, Swiatkowska, B, Thomson, P, Toporcov, T, Vaughan, T, Vilensky, M, Winn, D, Wunsch-Filho, V, Yu, G, Zevallos, J, Zhang, Z, Zheng, T, Znaor, A, Bravi F., Lee Y. -C. A., Hashibe M., Boffetta P., Conway D. I., Ferraroni M., La Vecchia C., Edefonti V., Agudo A., Ahrens W., Benhamou S., Boccia S., Brennan P., Brenner H., Cadoni G., Canova C., Chen C., Chuang S. -C., Curado M. P., Dal Maso L., Daudt A. W., D'Souza G., Fabianova E., Fernandez L., Franceschi S., Garavello W., Gillison M., Gross N. D., Hayes R. B., Healy C., Herrero R., Holcatova I., Kelsey K., Kjaerheim K., Koifman R., Lagiou P., Lazarus P., Levi F., Li G., Lissowska J., Luce D., Macfarlane G. J., Mates D., Matsuo K., McClean M., Menezes A., Menvielle G., Morgenstern H., Moyses R. A., Moysich K., Muscat J., Negri E., Olshan A. F., Pandics T., Polesel J., Purdue M. P., Radoi L., Ramroth H., Richiardi L., Schantz S., Schwartz S. M., Serraino D., Shangina O., Smith E., Sturgis E. M., Swiatkowska B., Thomson P., Toporcov T. N., Vaughan T. L., Vilensky M., Winn D. M., Wunsch-Filho V., Yu G. -P., Zevallos J. P., Zhang Z. -F., Zheng T., Znaor A., Bravi, F, Lee, Y, Hashibe, M, Boffetta, P, Conway, D, Ferraroni, M, La Vecchia, C, Edefonti, V, Agudo, A, Ahrens, W, Benhamou, S, Boccia, S, Brennan, P, Brenner, H, Cadoni, G, Canova, C, Chen, C, Chuang, S, Curado, M, Dal Maso, L, Daudt, A, D'Souza, G, Fabianova, E, Fernandez, L, Franceschi, S, Garavello, W, Gillison, M, Gross, N, Hayes, R, Healy, C, Herrero, R, Holcatova, I, Kelsey, K, Kjaerheim, K, Koifman, R, Lagiou, P, Lazarus, P, Levi, F, Li, G, Lissowska, J, Luce, D, Macfarlane, G, Mates, D, Matsuo, K, Mcclean, M, Menezes, A, Menvielle, G, Morgenstern, H, Moyses, R, Moysich, K, Muscat, J, Negri, E, Olshan, A, Pandics, T, Polesel, J, Purdue, M, Radoi, L, Ramroth, H, Richiardi, L, Schantz, S, Schwartz, S, Serraino, D, Shangina, O, Smith, E, Sturgis, E, Swiatkowska, B, Thomson, P, Toporcov, T, Vaughan, T, Vilensky, M, Winn, D, Wunsch-Filho, V, Yu, G, Zevallos, J, Zhang, Z, Zheng, T, Znaor, A, Bravi F., Lee Y. -C. A., Hashibe M., Boffetta P., Conway D. I., Ferraroni M., La Vecchia C., Edefonti V., Agudo A., Ahrens W., Benhamou S., Boccia S., Brennan P., Brenner H., Cadoni G., Canova C., Chen C., Chuang S. -C., Curado M. P., Dal Maso L., Daudt A. W., D'Souza G., Fabianova E., Fernandez L., Franceschi S., Garavello W., Gillison M., Gross N. D., Hayes R. B., Healy C., Herrero R., Holcatova I., Kelsey K., Kjaerheim K., Koifman R., Lagiou P., Lazarus P., Levi F., Li G., Lissowska J., Luce D., Macfarlane G. J., Mates D., Matsuo K., McClean M., Menezes A., Menvielle G., Morgenstern H., Moyses R. A., Moysich K., Muscat J., Negri E., Olshan A. F., Pandics T., Polesel J., Purdue M. P., Radoi L., Ramroth H., Richiardi L., Schantz S., Schwartz S. M., Serraino D., Shangina O., Smith E., Sturgis E. M., Swiatkowska B., Thomson P., Toporcov T. N., Vaughan T. L., Vilensky M., Winn D. M., Wunsch-Filho V., Yu G. -P., Zevallos J. P., Zhang Z. -F., Zheng T., and Znaor A.

Abstract

Objective: To summarize the latest evidence on head and neck cancer epidemiology from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. Subjects and Methods: INHANCE was established in 2004 to elucidate the etiology of head and neck cancer through pooled analyses of individual-level data on a large scale. We summarize results from recent INHANCE-based publications updating our 2015 overview. Results: Seventeen papers were published between 2015 and May 2020. These studies further define the nature of risks associated with tobacco and alcohol, and occupational exposures on head and neck cancer. The beneficial effects on incidence of head and neck cancer were identified for good oral health, endogenous and exogenous hormonal factors, and selected aspects of diet related to fruit and vegetables. INHANCE has begun to develop risk prediction models and to pool follow-up data on their studies, finding that ~30% of cases had cancer recurrence and 9% second primary cancers, with overall- and disease-specific 5-year-survival of 51% and 57%, respectively. Conclusions: The number and importance of INHANCE scientific findings provides further evidence of the advantages of large-scale internationally collaborative projects and will support the development of prevention strategies.

Published
2021

68. DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis

Author

Md Mahmudur Rahman, Matsuo, K., Matsuzaki, S., and Purushotham, S.

Subjects
General Medicine
Abstract

Competing Risk Analysis (CRA) aims at the correct estimation of the marginal probability of occurrence of an event in the presence of competing events. Many of the statistical approaches developed for CRA are limited by strong assumptions about the underlying stochastic processes. To overcome these issues and to handle censoring, machine learning approaches for CRA have designed specialized cost functions. However, these approaches are not generalizable, and are computationally expensive. This paper formulates CRA as a cause-specific regression problem and proposes DeepPseudo models, which use simple and effective feed-forward deep neural networks, to predict the cumulative incidence function (CIF) using Aalen-Johansen estimator-based pseudo values. DeepPseudo models capture the time-varying covariate effect on CIF while handling the censored observations. We show how DeepPseudo models can address co-variate dependent censoring by using modified pseudo values. Experiments on real and synthetic datasets demonstrate that our proposed models obtain promising and statistically significant results compared to the state-of-the-art CRA approaches. Furthermore, we show that explainable methods such as Layer-wise Relevance Propagation can be used to interpret the predictions of our DeepPseudo models.

Published
2021

76. The Application of Grid Computing to Real-Time Functional MRI Analysis

Author

Bagarinao, E., Sarmenta, L., Tanaka, Y., Matsuo, K., Nakai, T., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cao, Jiannong, editor, Yang, Laurence T., editor, Guo, Minyi, editor, and Lau, Francis, editor

Published
2005
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79. Abstract No. 123 Impact of ablation margin on local tumor progression after radiofrequency ablation for lung metastases from colorectal carcinoma: supplementary analysis of phase II trial (MLCSG-0802)

Author

Hasegawa, T., primary, Takaki, H., additional, Kodama, H., additional, Matsuo, K., additional, Yamanaka, T., additional, Nakatsuka, A., additional, Inaba, Y., additional, Gobara, H., additional, Hayashi, S., additional, Takao, M., additional, and Yamakado, K., additional

Published
2022
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80. OP0112 THE EVER-LARGEST ASIAN GWAS FOR SYSTEMIC SCLEROSIS AND TRANS-POPULATION META-ANALYSIS IDENTIFIED SEVEN NOVEL LOCI AND A CANDIDATE CAUSAL SNP IN A CIS-REGULATORY ELEMENT OF THE FCGR REGION

Author

Ishikawa, Y., primary, Tanaka, N., additional, Asano, Y., additional, Kodera, M., additional, Shirai, Y., additional, Akahoshi, M., additional, Hasegawa, M., additional, Matsushita, T., additional, Kazuyoshi, S., additional, Motegi, S., additional, Yoshifuji, H., additional, Yoshizaki, A., additional, Kohmoto, T., additional, Takagi, K., additional, Oka, A., additional, Kanda, M., additional, Tanaka, Y., additional, Ito, Y., additional, Nakano, K., additional, Kasamatsu, H., additional, Utsunomiya, A., additional, Sekiguchi, A., additional, Niro, H., additional, Jinnin, M., additional, Makino, K., additional, Makino, T., additional, Ihn, H., additional, Yamamoto, M., additional, Suzuki, C., additional, Takahashi, H., additional, Nishida, E., additional, Morita, A., additional, Yamamoto, T., additional, Fujimoto, M., additional, Kondo, Y., additional, Goto, D., additional, Sumida, T., additional, Ayuzawa, N., additional, Yanagida, H., additional, Horita, T., additional, Atsumi, T., additional, Endo, H., additional, Shima, Y., additional, Kumanogoh, A., additional, Hirata, J., additional, Otomo, N., additional, Suetsugu, H., additional, Koike, Y., additional, Tomizuka, K., additional, Yoshino, S., additional, Liu, X., additional, Ito, S., additional, Hikino, K., additional, Suzuki, A., additional, Momozawa, Y., additional, Ikegawa, S., additional, Ishikawa, O., additional, Takehara, K., additional, Torii, T., additional, Sato, S., additional, Okada, Y., additional, Mimori, T., additional, Matsuda, F., additional, Matsuda, K., additional, Imoto, I., additional, Matsuo, K., additional, Kuwana, M., additional, Kawaguchi, Y., additional, Ohmura, K., additional, and Terao, C., additional

Published
2022
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81. Alcohol drinking and head and neck cancer risk: the joint effect of intensity and duration

Author

Di Credico, G, Polesel, J, Dal Maso, L, Pauli, F, Torelli, N, Luce, D, Radoi, L, Matsuo, K, Serraino, D, Brennan, P, Holcatova, I, Ahrens, W, Lagiou, P, Canova, C, Richiardi, L, Healy, C, Kjaerheim, K, Conway, D, Macfarlane, G, Thomson, P, Agudo, A, Znaor, A, Franceschi, S, Herrero, R, Toporcov, T, Moyses, R, Muscat, J, Negri, E, Vilensky, M, Fernandez, L, Curado, M, Menezes, A, Daudt, A, Koifman, R, Wunsch-Filho, V, Olshan, A, Zevallos, J, Sturgis, E, Li, G, Levi, F, Zhang, Z, Morgenstern, H, Smith, E, Lazarus, P, La Vecchia, C, Garavello, W, Chen, C, Schwartz, S, Zheng, T, Vaughan, T, Kelsey, K, Mcclean, M, Benhamou, S, Hayes, R, Purdue, M, Gillison, M, Schantz, S, Yu, G, Chuang, S, Boffetta, P, Hashibe, M, Yuan-Chin, A, Edefonti, V, Di Credico G., Polesel J., Dal Maso L., Pauli F., Torelli N., Luce D., Radoi L., Matsuo K., Serraino D., Brennan P., Holcatova I., Ahrens W., Lagiou P., Canova C., Richiardi L., Healy C. M., Kjaerheim K., Conway D. I., Macfarlane G. J., Thomson P., Agudo A., Znaor A., Franceschi S., Herrero R., Toporcov T. N., Moyses R. A., Muscat J., Negri E., Vilensky M., Fernandez L., Curado M. P., Menezes A., Daudt A. W., Koifman R., Wunsch-Filho V., Olshan A. F., Zevallos J. P., Sturgis E. M., Li G., Levi F., Zhang Z. -F., Morgenstern H., Smith E., Lazarus P., La Vecchia C., Garavello W., Chen C., Schwartz S. M., Zheng T., Vaughan T. L., Kelsey K., McClean M., Benhamou S., Hayes R. B., Purdue M. P., Gillison M., Schantz S., Yu G. -P., Chuang S. -C., Boffetta P., Hashibe M., Yuan-Chin A. L., Edefonti V., Di Credico, G, Polesel, J, Dal Maso, L, Pauli, F, Torelli, N, Luce, D, Radoi, L, Matsuo, K, Serraino, D, Brennan, P, Holcatova, I, Ahrens, W, Lagiou, P, Canova, C, Richiardi, L, Healy, C, Kjaerheim, K, Conway, D, Macfarlane, G, Thomson, P, Agudo, A, Znaor, A, Franceschi, S, Herrero, R, Toporcov, T, Moyses, R, Muscat, J, Negri, E, Vilensky, M, Fernandez, L, Curado, M, Menezes, A, Daudt, A, Koifman, R, Wunsch-Filho, V, Olshan, A, Zevallos, J, Sturgis, E, Li, G, Levi, F, Zhang, Z, Morgenstern, H, Smith, E, Lazarus, P, La Vecchia, C, Garavello, W, Chen, C, Schwartz, S, Zheng, T, Vaughan, T, Kelsey, K, Mcclean, M, Benhamou, S, Hayes, R, Purdue, M, Gillison, M, Schantz, S, Yu, G, Chuang, S, Boffetta, P, Hashibe, M, Yuan-Chin, A, Edefonti, V, Di Credico G., Polesel J., Dal Maso L., Pauli F., Torelli N., Luce D., Radoi L., Matsuo K., Serraino D., Brennan P., Holcatova I., Ahrens W., Lagiou P., Canova C., Richiardi L., Healy C. M., Kjaerheim K., Conway D. I., Macfarlane G. J., Thomson P., Agudo A., Znaor A., Franceschi S., Herrero R., Toporcov T. N., Moyses R. A., Muscat J., Negri E., Vilensky M., Fernandez L., Curado M. P., Menezes A., Daudt A. W., Koifman R., Wunsch-Filho V., Olshan A. F., Zevallos J. P., Sturgis E. M., Li G., Levi F., Zhang Z. -F., Morgenstern H., Smith E., Lazarus P., La Vecchia C., Garavello W., Chen C., Schwartz S. M., Zheng T., Vaughan T. L., Kelsey K., McClean M., Benhamou S., Hayes R. B., Purdue M. P., Gillison M., Schantz S., Yu G. -P., Chuang S. -C., Boffetta P., Hashibe M., Yuan-Chin A. L., and Edefonti V.

Abstract

Background: Alcohol is a well-established risk factor for head and neck cancer (HNC). This study aims to explore the effect of alcohol intensity and duration, as joint continuous exposures, on HNC risk. Methods: Data from 26 case-control studies in the INHANCE Consortium were used, including never and current drinkers who drunk ≤10 drinks/day for ≤54 years (24234 controls, 4085 oral cavity, 3359 oropharyngeal, 983 hypopharyngeal and 3340 laryngeal cancers). The dose-response relationship between the risk and the joint exposure to drinking intensity and duration was investigated through bivariate regression spline models, adjusting for potential confounders, including tobacco smoking. Results: For all subsites, cancer risk steeply increased with increasing drinks/day, with no appreciable threshold effect at lower intensities. For each intensity level, the risk of oral cavity, hypopharyngeal and laryngeal cancers did not vary according to years of drinking, suggesting no effect of duration. For oropharyngeal cancer, the risk increased with durations up to 28 years, flattening thereafter. The risk peaked at the higher levels of intensity and duration for all subsites (odds ratio = 7.95 for oral cavity, 12.86 for oropharynx, 24.96 for hypopharynx and 6.60 for larynx). Conclusions: Present results further encourage the reduction of alcohol intensity to mitigate HNC risk.

Published
2020

82. High Prediagnosis Inflammation-Related Risk Score Associated with Decreased Ovarian Cancer Survival

Author

Brieger, KK, Phung, MT, Mukherjee, B, Bakulski, KM, Anton-Culver, H, Bandera, E, Bowtell, DDL, Cramer, DW, DeFazio, A, Doherty, JA, Fereday, S, Fortner, RT, Gentry-Maharaj, A, Goode, EL, Goodman, MT, Harris, HR, Matsuo, K, Menon, U, Modugno, F, Moysich, KB, Qin, B, Ramus, SJ, Risch, HA, Rossing, MA, Schildkraut, JM, Trabert, B, Vierkant, RA, Winham, SJ, Wentzensen, N, Wu, AH, Ziogas, A, Khoja, L, Cho, KR, McLean, K, Richardson, J, Grout, B, Chase, A, Deurloo, CM, Odunsi, K, Nelson, BH, Brenton, JD, Terry, KL, Pharoah, PDP, Berchuck, A, Hanley, GE, Webb, PM, Pike, MC, Pearce, CL, Brieger, KK, Phung, MT, Mukherjee, B, Bakulski, KM, Anton-Culver, H, Bandera, E, Bowtell, DDL, Cramer, DW, DeFazio, A, Doherty, JA, Fereday, S, Fortner, RT, Gentry-Maharaj, A, Goode, EL, Goodman, MT, Harris, HR, Matsuo, K, Menon, U, Modugno, F, Moysich, KB, Qin, B, Ramus, SJ, Risch, HA, Rossing, MA, Schildkraut, JM, Trabert, B, Vierkant, RA, Winham, SJ, Wentzensen, N, Wu, AH, Ziogas, A, Khoja, L, Cho, KR, McLean, K, Richardson, J, Grout, B, Chase, A, Deurloo, CM, Odunsi, K, Nelson, BH, Brenton, JD, Terry, KL, Pharoah, PDP, Berchuck, A, Hanley, GE, Webb, PM, Pike, MC, and Pearce, CL

Abstract

BACKGROUND: There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects. METHODS: This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data. RESULTS: There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03-1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11-1.54). CONCLUSIONS: A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival. IMPACT: Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Published
2022

83. Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk.

Author

Dareng, EO, Tyrer, JP, Barnes, DR, Jones, MR, Yang, X, Aben, KKH, Adank, MA, Agata, S, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Aravantinos, G, Arun, BK, Augustinsson, A, Balmaña, J, Bandera, EV, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Bjorge, L, Black, A, Bogdanova, NV, Bonanni, B, Borg, A, Brenton, JD, Budzilowska, A, Butzow, R, Buys, SS, Cai, H, Caligo, MA, Campbell, I, Cannioto, R, Cassingham, H, Chang-Claude, J, Chanock, SJ, Chen, K, Chiew, Y-E, Chung, WK, Claes, KBM, Colonna, S, GEMO Study Collaborators, GC-HBOC Study Collaborators, EMBRACE Collaborators, Cook, LS, Couch, FJ, Daly, MB, Dao, F, Davies, E, de la Hoya, M, de Putter, R, Dennis, J, DePersia, A, Devilee, P, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dörk, T, du Bois, A, Dürst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, RT, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, OPAL Study Group, AOCS Group, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Høgdall, E, Høgdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, KConFab Investigators, HEBON Investigators, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, B-G, Kjaer, SK, Komenaka, I, Kupryjanczyk, J, Kurian, AW, Kwong, A, Lambrechts, D, Larson, MC, Lazaro, C, Le, ND, Leslie, G, Lester, J, Lesueur, F, Levine, DA, Li, L, Li, J, Loud, JT, Lu, KH, Lubiński, J, Mai, PL, Manoukian, S, Marks, JR, Matsuno, RK, Matsuo, K, May, T, McGuffog, L, McLaughlin, JR, McNeish, IA, Mebirouk, N, Menon, U, Miller, A, Milne, RL, Minlikeeva, A, Modugno, F, Montagna, M, Moysich, KB, Munro, E, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Yie, JNY, Nielsen, HR, Nielsen, FC, Nikitina-Zake, L, Odunsi, K, Offit, K, Olah, E, Olbrecht, S, Olopade, OI, Olson, SH, Olsson, H, Osorio, A, Papi, L, Park, SK, Parsons, MT, Pathak, H, Pedersen, IS, Peixoto, A, Pejovic, T, Perez-Segura, P, Permuth, JB, Peshkin, B, Peterlongo, P, Piskorz, A, Prokofyeva, D, Radice, P, Rantala, J, Riggan, MJ, Risch, HA, Rodriguez-Antona, C, Ross, E, Rossing, MA, Runnebaum, I, Sandler, DP, Santamariña, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, OCAC Consortium, CIMBA Consortium, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Van Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, Y-L, Wu, AH, Yan, L, Yannoukakos, D, Zavaglia, KM, Zheng, W, Ziogas, A, Zorn, KK, Kleibl, Z, Easton, D, Lawrenson, K, DeFazio, A, Sellers, TA, Ramus, SJ, Pearce, CL, Monteiro, AN, Cunningham, J, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, Pharoah, PDP, Dareng, EO, Tyrer, JP, Barnes, DR, Jones, MR, Yang, X, Aben, KKH, Adank, MA, Agata, S, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Aravantinos, G, Arun, BK, Augustinsson, A, Balmaña, J, Bandera, EV, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Bjorge, L, Black, A, Bogdanova, NV, Bonanni, B, Borg, A, Brenton, JD, Budzilowska, A, Butzow, R, Buys, SS, Cai, H, Caligo, MA, Campbell, I, Cannioto, R, Cassingham, H, Chang-Claude, J, Chanock, SJ, Chen, K, Chiew, Y-E, Chung, WK, Claes, KBM, Colonna, S, GEMO Study Collaborators, GC-HBOC Study Collaborators, EMBRACE Collaborators, Cook, LS, Couch, FJ, Daly, MB, Dao, F, Davies, E, de la Hoya, M, de Putter, R, Dennis, J, DePersia, A, Devilee, P, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dörk, T, du Bois, A, Dürst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, RT, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, OPAL Study Group, AOCS Group, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Høgdall, E, Høgdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, KConFab Investigators, HEBON Investigators, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, B-G, Kjaer, SK, Komenaka, I, Kupryjanczyk, J, Kurian, AW, Kwong, A, Lambrechts, D, Larson, MC, Lazaro, C, Le, ND, Leslie, G, Lester, J, Lesueur, F, Levine, DA, Li, L, Li, J, Loud, JT, Lu, KH, Lubiński, J, Mai, PL, Manoukian, S, Marks, JR, Matsuno, RK, Matsuo, K, May, T, McGuffog, L, McLaughlin, JR, McNeish, IA, Mebirouk, N, Menon, U, Miller, A, Milne, RL, Minlikeeva, A, Modugno, F, Montagna, M, Moysich, KB, Munro, E, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Yie, JNY, Nielsen, HR, Nielsen, FC, Nikitina-Zake, L, Odunsi, K, Offit, K, Olah, E, Olbrecht, S, Olopade, OI, Olson, SH, Olsson, H, Osorio, A, Papi, L, Park, SK, Parsons, MT, Pathak, H, Pedersen, IS, Peixoto, A, Pejovic, T, Perez-Segura, P, Permuth, JB, Peshkin, B, Peterlongo, P, Piskorz, A, Prokofyeva, D, Radice, P, Rantala, J, Riggan, MJ, Risch, HA, Rodriguez-Antona, C, Ross, E, Rossing, MA, Runnebaum, I, Sandler, DP, Santamariña, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, OCAC Consortium, CIMBA Consortium, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Van Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, Y-L, Wu, AH, Yan, L, Yannoukakos, D, Zavaglia, KM, Zheng, W, Ziogas, A, Zorn, KK, Kleibl, Z, Easton, D, Lawrenson, K, DeFazio, A, Sellers, TA, Ramus, SJ, Pearce, CL, Monteiro, AN, Cunningham, J, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, and Pharoah, PDP

Published
2022

84. Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Author

Dareng, EO, Tyrer, JP, Barnes, DR, Jones, MR, Yang, X, Aben, KKH, Adank, MA, Agata, S, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Aravantinos, G, Arun, BK, Augustinsson, A, Balmana, J, Bandera, E, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Bjorge, L, Black, A, Bogdanova, N, Bonanni, B, Borg, A, Brenton, JD, Budzilowska, A, Butzow, R, Buys, SS, Cai, H, Caligo, MA, Campbell, I, Cannioto, R, Cassingham, H, Chang-Claude, J, Chanock, SJ, Chen, K, Chiew, Y-E, Chung, WK, Claes, KBM, Colonna, S, Cook, LS, Couch, FJ, Daly, MB, Dao, F, Davies, E, de la Hoya, M, de Putter, R, Dennis, J, DePersia, A, Devilee, P, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dork, T, du Bois, A, Durst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, R, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, Group, OS, AOCSGroup, Hahnen, E, Haiman, CA, Hakansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, B-G, Kjaer, SK, Komenaka, I, Kupryjanczyk, J, Kurian, AW, Kwong, A, Lambrechts, D, Larson, MC, Lazaro, C, Le, ND, Leslie, G, Lester, J, Lesueur, F, Levine, DA, Li, L, Li, J, Loud, JT, Lu, KH, Mai, PL, Manoukian, S, Marks, JR, KimMatsuno, R, Matsuo, K, May, T, McGuffog, L, McLaughlin, JR, McNeish, IA, Mebirouk, N, Menon, U, Miller, A, Milne, RL, Minlikeeva, A, Modugno, F, Montagna, M, Moysich, KB, Munro, E, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Yie, JNY, Nielsen, HR, Nielsen, FC, Nikitina-Zake, L, Odunsi, K, Offit, K, Olah, E, Olbrecht, S, Olopade, O, Olson, SH, Olsson, H, Osorio, A, Papi, L, Park, SK, Parsons, MT, Pathak, H, Pedersen, IS, Peixoto, A, Pejovic, T, Perez-Segura, P, Permuth, JB, Peshkin, B, Peterlongo, P, Piskorz, A, Prokofyeva, D, Radice, P, Rantala, J, Riggan, MJ, Risch, HA, Rodriguez-Antona, C, Ross, E, Rossing, MA, Runnebaum, I, Sandler, DP, Santamarina, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, BethTerry, M, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, Y-L, Wu, AH, Yan, L, Yannoukakos, D, Zavaglia, KM, Zheng, W, Ziogas, A, Zorn, KK, Kleibl, Z, Easton, D, Lawrenson, K, DeFazio, A, Sellers, TA, Ramus, SJ, Pearce, CL, Monteiro, AN, Cunningham, J, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, Pharoah, PDP, Dareng, EO, Tyrer, JP, Barnes, DR, Jones, MR, Yang, X, Aben, KKH, Adank, MA, Agata, S, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Aravantinos, G, Arun, BK, Augustinsson, A, Balmana, J, Bandera, E, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Bjorge, L, Black, A, Bogdanova, N, Bonanni, B, Borg, A, Brenton, JD, Budzilowska, A, Butzow, R, Buys, SS, Cai, H, Caligo, MA, Campbell, I, Cannioto, R, Cassingham, H, Chang-Claude, J, Chanock, SJ, Chen, K, Chiew, Y-E, Chung, WK, Claes, KBM, Colonna, S, Cook, LS, Couch, FJ, Daly, MB, Dao, F, Davies, E, de la Hoya, M, de Putter, R, Dennis, J, DePersia, A, Devilee, P, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dork, T, du Bois, A, Durst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, R, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, Group, OS, AOCSGroup, Hahnen, E, Haiman, CA, Hakansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, B-G, Kjaer, SK, Komenaka, I, Kupryjanczyk, J, Kurian, AW, Kwong, A, Lambrechts, D, Larson, MC, Lazaro, C, Le, ND, Leslie, G, Lester, J, Lesueur, F, Levine, DA, Li, L, Li, J, Loud, JT, Lu, KH, Mai, PL, Manoukian, S, Marks, JR, KimMatsuno, R, Matsuo, K, May, T, McGuffog, L, McLaughlin, JR, McNeish, IA, Mebirouk, N, Menon, U, Miller, A, Milne, RL, Minlikeeva, A, Modugno, F, Montagna, M, Moysich, KB, Munro, E, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Yie, JNY, Nielsen, HR, Nielsen, FC, Nikitina-Zake, L, Odunsi, K, Offit, K, Olah, E, Olbrecht, S, Olopade, O, Olson, SH, Olsson, H, Osorio, A, Papi, L, Park, SK, Parsons, MT, Pathak, H, Pedersen, IS, Peixoto, A, Pejovic, T, Perez-Segura, P, Permuth, JB, Peshkin, B, Peterlongo, P, Piskorz, A, Prokofyeva, D, Radice, P, Rantala, J, Riggan, MJ, Risch, HA, Rodriguez-Antona, C, Ross, E, Rossing, MA, Runnebaum, I, Sandler, DP, Santamarina, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, BethTerry, M, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, Y-L, Wu, AH, Yan, L, Yannoukakos, D, Zavaglia, KM, Zheng, W, Ziogas, A, Zorn, KK, Kleibl, Z, Easton, D, Lawrenson, K, DeFazio, A, Sellers, TA, Ramus, SJ, Pearce, CL, Monteiro, AN, Cunningham, J, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, and Pharoah, PDP

Abstract

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Published
2022

85. Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Author

Grootes, I, Keeman, R, Blows, FM, Milne, RL, Giles, GG, Swerdlow, AJ, Fasching, PA, Abubakar, M, Andrulis, IL, Anton-Culver, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Bonanni, B, Briceno, I, Burwinkel, B, Camp, NJ, Castelao, JE, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Ernst, K, Evans, DG, Figueroa, JD, Fink, V, Floris, G, Fox, S, Gabrielson, M, Gago-Dominguez, M, Garcia-Saenz, JA, Gonzalez-Neira, A, Haeberle, L, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hartman, M, Hein, A, Hooning, MJ, Hou, M-F, Howell, SJ, Ito, H, Jakubowska, A, Janni, W, John, EM, Jung, A, Kang, D, Kristensen, VN, Kwong, A, Lambrechts, D, Li, J, Manoochehri, M, Margolin, S, Matsuo, K, Taib, NAM, Mulligan, AM, Nevanlinna, H, Newman, WG, Offit, K, Osorio, A, Park, SK, Park-Simon, T-W, Patel, A, Presneau, N, Pylkas, K, Rack, B, Radice, P, Rennert, G, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schochter, F, Schoemaker, MJ, Shen, C-Y, Shibli, R, Sinn, P, Tapper, WJ, Tawfiq, E, Teo, SH, Teras, LR, Torres, D, Vachon, CM, van Deurzen, CHM, Wendt, C, Williams, JA, Winqvist, R, Elwood, M, Schmidt, MK, Pharoah, PDP, Grootes, I, Keeman, R, Blows, FM, Milne, RL, Giles, GG, Swerdlow, AJ, Fasching, PA, Abubakar, M, Andrulis, IL, Anton-Culver, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Bonanni, B, Briceno, I, Burwinkel, B, Camp, NJ, Castelao, JE, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Ernst, K, Evans, DG, Figueroa, JD, Fink, V, Floris, G, Fox, S, Gabrielson, M, Gago-Dominguez, M, Garcia-Saenz, JA, Gonzalez-Neira, A, Haeberle, L, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hartman, M, Hein, A, Hooning, MJ, Hou, M-F, Howell, SJ, Ito, H, Jakubowska, A, Janni, W, John, EM, Jung, A, Kang, D, Kristensen, VN, Kwong, A, Lambrechts, D, Li, J, Manoochehri, M, Margolin, S, Matsuo, K, Taib, NAM, Mulligan, AM, Nevanlinna, H, Newman, WG, Offit, K, Osorio, A, Park, SK, Park-Simon, T-W, Patel, A, Presneau, N, Pylkas, K, Rack, B, Radice, P, Rennert, G, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schochter, F, Schoemaker, MJ, Shen, C-Y, Shibli, R, Sinn, P, Tapper, WJ, Tawfiq, E, Teo, SH, Teras, LR, Torres, D, Vachon, CM, van Deurzen, CHM, Wendt, C, Williams, JA, Winqvist, R, Elwood, M, Schmidt, MK, and Pharoah, PDP

Abstract

BACKGROUND: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Published
2022

90. Menstrual and reproductive factors, and hormonal contraception use: associations with non-Hodgkin lymphoma in a pooled analysis of InterLymph case–control studies

Author

Kane, E.V., Roman, E., Becker, N., Bernstein, L., Boffetta, P., Bracci, P.M., Cerhan, J.R., Chiu, B. C. -H., Cocco, P., Costas, L., Foretova, L., Holly, E.A., La Vecchia, C., Matsuo, K., Maynadie, M., Sanjose, S., Spinelli, J.J., Staines, A., Talamini, R., Wang, S.S., Zhang, Y., Zheng, T., and Kricker, A.

Published
2012
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94. Single systemic administration of Ag85B of mycobacteria DNA inhibits allergic airway inflammation in a mouse model of asthma

Author

Karamatsu K, Matsuo K, Inada H, Tsujimura Y, Shiogama Y, Matsubara A, Kawano M, and Yasutomi Y

Subjects
Immunologic diseases. Allergy, RC581-607
Abstract

Katsuo Karamatsu,1,2 Kazuhiro Matsuo,3 Hiroyasu Inada,4 Yusuke Tsujimura,1 Yumiko Shiogama,1,2 Akihiro Matsubara,1,2 Mitsuo Kawano,5 Yasuhiro Yasutomi1,21Laboratory of Immunoregulation and Vaccine Research, Tsukuba Primate Research Center, National Institute of Biomedical Innovation, Tsukuba, 2Division of Immunoregulation, Department of Molecular and Experimental Medicine, Mie University Graduate School of Medicine, Tsu, 3Department of Research and Development, Japan BCG Laboratory, Tokyo, 4Department of Pathology, Suzuka University of Medical Science, Suzuka, 5Department of Microbiology and Molecular Genetics, Mie University Graduate School of Medicine, Tsu, JapanAbstract: The immune responses of T-helper (Th) and T-regulatory cells are thought to play a crucial role in the pathogenesis of allergic airway inflammation observed in asthma. The correction of immune response by these cells should be considered in the prevention and treatment of asthma. Native antigen 85B (Ag85B) of mycobacteria, which cross-reacts among mycobacteria species, may play an important biological role in host–pathogen interaction since it elicits various immune responses by activation of Th cells. The current study investigated the antiallergic inflammatory effects of DNA administration of Ag85B from Mycobacterium kansasii in a mouse model of asthma. Immunization of BALB/c mice with alum-adsorbed ovalbumin followed by aspiration with aerosolized ovalbumin resulted in the development of allergic airway inflammation. Administration of Ag85B DNA before the aerosolized ovalbumin challenge protected the mice from subsequent induction of allergic airway inflammation. Serum and bronchoalveolar lavage immunoglobulin E levels, extent of eosinophil infiltration, and levels of Th2-type cytokines in Ag85B DNA-administered mice were significantly lower than those in control plasmid-immunized mice, and levels of Th1- and T-regulatory-type cytokines were enhanced by Ag85B administration. The results of this study provide evidence for the potential utility of Ag85B DNA inoculation as a novel approach for the treatment of asthma.Keywords: immunotherapy, asthma, Ag85B, mycobacteria, allergy

Published
2012

96. Risk factors for head and neck cancer in more and less developed countries: Analysis from the INHANCE consortium

Author

Goyal, N. Hennessy, M. Lehman, E. Lin, W. Agudo, A. Ahrens, W. Boccia, S. Brennan, P. Brenner, H. Cadoni, G. Canova, C. Chen, C. Conway, D. Curado, M. Dal Maso, L. Daudt, A.W. Edefonti, V. Fabianova, E. Fernandez, L. Franceschi, S. Garavello, W. Gillison, M. Hayes, R.B. Healy, C. Herrero, R. Holcatova, I. Kanda, J.L. Kelsey, K. Hansen, B. Koifman, R. Lagiou, P. La Vecchia, C. Levi, F. Li, G. Lissowska, J. Mendoza López, R. Luce, D. Macfarlane, G. Mates, D. Matsuo, K. McClean, M. Menezes, A. Menvielle, G. Morgenstern, H. Moysich, K. Negri, E. Olshan, A.F. Pandics, T. Polesel, J. Purdue, M. Radoi, L. Ramroth, H. Richiardi, L. Schantz, S. Schwartz, S.M. Serraino, D. Shangina, O. Smith, E. Sturgis, E.M. Świątkowska, B. Thomson, P. Vaughan, T.L. Vilensky, M. Winn, D.M. Wunsch-Filho, V. Yu, G.-P. Zevallos, J.P. Zhang, Z.-F. Zheng, T. Znaor, A. Boffetta, P. Hashibe, M. Lee, Y.-C.A. Muscat, J.E.

Abstract

Objective: We analyzed the pooled case-control data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium to compare cigarette smoking and alcohol consumption risk factors for head and neck cancer between less developed and more developed countries. Subjects and Methods: The location of each study was categorized as either a less developed or more developed country. We compared the risk of overall head and neck cancer and cancer of specific anatomic subsites associated with cigarette smoking and alcohol consumption. Additionally, age and sex distribution between categories was compared. Results: The odds ratios for head and neck cancer sites associated with smoking duration differed between less developed and more developed countries. Smoking greater than 20 years conferred a higher risk for oral cavity and laryngeal cancer in more developed countries, whereas the risk was greater for oropharynx and hypopharynx cancer in less developed countries. Alcohol consumed for more than 20 years conferred a higher risk for oropharynx, hypopharynx, and larynx cancer in less developed countries. The proportion of cases that were young (

Published
2022

98. Objective assessment of skin rejuvenation using near-infrared 1064-nm neodymium: YAG laser in Asians

Author

Tanaka Y, Matsuo K, and Yuzuriha S

Subjects
Dermatology, RL1-803
Abstract

Yohei Tanaka1,2, Kiyoshi Matsuo1, Shunsuke Yuzuriha11Department of Plastic and Reconstructive Surgery, Shinshu University School of Medicine, Matsumoto, Japan; 2Clinica Tanaka Plastic and Reconstructive Surgery and Anti-aging Center, Matsumoto, JapanBackground: We reported previously that near-infrared (NIR) irradiation provides long-lasting stimulation of elastin, and is efficient for skin rejuvenation. Many studies have indicated the efficacy of various types of laser, but did not include sufficiently objective evaluation. Therefore, we evaluated the efficacy of NIR laser treatment not only subjectively but also objectively.Methods: Fifty Japanese patients were treated with a NIR 1064-nm neodymium: YAG laser. Objective computer assessments were performed by Canfield VISIA Complexion Analysis for improvement of dilated pores, skin texture, and wrinkles. The volunteers then provided subjective assessments. Histological evaluations of elastin were performed by Victoria blue staining up to 90 days post-treatment in four Japanese volunteers.Results: Mean pretreatment percentiles of dilated pores, skin texture, and wrinkles were 51.08 ± 24.82, 54.7 ± 26.33, and 58.02 ± 28.61, respectively. Mean post-treatment percentiles of dilated pores, skin texture, and wrinkles were 53.58 ± 23.89, 58.58 ± 24.44, and 62.2 ± 25.39, respectively. All objective computer assessments evaluated by percentiles in dilated pores, skin texture, and wrinkles showed significant improvement after NIR laser treatment. Ninety-six percent, 100%, and 98% of volunteers reported satisfaction with the improvement of dilated pores, skin texture, and wrinkles, respectively. NIR laser treatment appeared to increase the amount of elastin at day 30, which then decreased slightly but was still elevated at day 90 compared with nonirradiated controls on day 0. Thickening of the epidermis was detected on day 30, and epidermal smoothness persisted for up to 90 days. No treatment-related adverse events were observed.Conclusions: NIR irradiation increased elastin in the dermis, and achieved skin rejuvenation. The results indicated that NIR irradiation provides safe and effective long-term stimulation of elastin, which is beneficial for improving dilated pores, skin texture, and wrinkles.Keywords: near-infrared laser, elastin, skin rejuvenation, objective assessment

Published
2011

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