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566 results on '"Yu, J.-C."'

1. Density Estimation via Bayesian Inference Engines

Author

Wand, M. P. and Yu, J. C. F.

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We explain how effective automatic probability density function estimates can be constructed using contemporary Bayesian inference engines such as those based on no-U-turn sampling and expectation propagation. Extensive simulation studies demonstrate that the proposed density estimates have excellent comparative performance and scale well to very large sample sizes due to a binning strategy. Moreover, the approach is fully Bayesian and all estimates are accompanied by pointwise credible intervals. An accompanying package in the R language facilitates easy use of the new density estimates.

Published
2020

4. Fast and Accurate Binary Response Mixed Model Analysis via Expectation Propagation

Author

Hall, P., Johnstone, I. M., Ormerod, J. T., Wand, M. P., and Yu, J. C. F.

Subjects
Statistics - Methodology
Abstract

Expectation propagation is a general prescription for approximation of integrals in statistical inference problems. Its literature is mainly concerned with Bayesian inference scenarios. However, expectation propagation can also be used to approximate integrals arising in frequentist statistical inference. We focus on likelihood-based inference for binary response mixed models and show that fast and accurate quadrature-free inference can be realized for the probit link case with multivariate random effects and higher levels of nesting. The approach is supported by asymptotic theory in which expectation propagation is seen to provide consistent estimation of the exact likelihood surface. Numerical studies reveal the availability of fast, highly accurate and scalable methodology for binary mixed model analysis., Comment: 35 pages, 5 figures

Published
2018

5. FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium.

Author

Agarwal, D, Pineda, S, Michailidou, K, Herranz, J, Pita, G, Moreno, L, Alonso, M, Dennis, J, Wang, Q, Bolla, M, Meyer, K, Menéndez-Rodríguez, P, Hardisson, D, Mendiola, M, González-Neira, A, Lindblom, A, Margolin, S, Swerdlow, A, Orr, N, Jones, M, Matsuo, K, Ito, H, Iwata, H, Kondo, N, Hartman, M, Hui, M, Lim, W, Iau, P, Sawyer, E, Tomlinson, I, Kerin, M, Miller, N, Kang, D, Choi, J-Y, Park, S, Noh, D-Y, Hopper, J, Schmidt, D, Makalic, E, Southey, M, Teo, S, Yip, C, Sivanandan, K, Tay, W-T, Brauch, H, Brüning, T, Hamann, U, Dunning, A, Shah, M, Andrulis, I, Knight, J, Glendon, G, Tchatchou, S, Schmidt, M, Broeks, A, Rosenberg, E, vant Veer, L, Fasching, P, Renner, S, Ekici, A, Beckmann, M, Shen, C-Y, Hsiung, C-N, Yu, J-C, Hou, M-F, Blot, W, Cai, Q, Tseng, C-C, Van Den Berg, D, Stram, D, Cox, A, Brock, I, Reed, M, Muir, K, Lophatananon, A, Stewart-Brown, S, Siriwanarangsan, P, Zheng, W, Deming-Halverson, S, Shrubsole, M, Long, J, Shu, X-O, Lu, W, Gao, Y-T, Zhang, B, Radice, P, Peterlongo, P, Manoukian, S, Mariette, F, Sangrajrang, S, McKay, J, Couch, F, Toland, A, Yannoukakos, D, Fletcher, O, Johnson, N, dos Santos Silva, I, Peto, J, Marme, F, and Burwinkel, B

Subjects
Breast Neoplasms, Case-Control Studies, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Receptor, Fibroblast Growth Factor, Type 1, Receptor, Fibroblast Growth Factor, Type 2, Receptor, Fibroblast Growth Factor, Type 3, Receptor, Fibroblast Growth Factor, Type 4, Receptor, Fibroblast Growth Factor, Type 5
Abstract

BACKGROUND: Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. METHODS: Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. RESULTS: Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95% confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. CONCLUSION: Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2.

Published
2014

6. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author

Mueller, SH, Lai, AG, Valkovskaya, M, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Lush, M, Abu-Ful, Z, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baert, T, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Bonanni, B, Brenner, H, Brucker, SY, Buys, SS, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Chung, WK, Colonna, S, Cornelissen, S, Couch, FJ, Czene, K, Daly, MB, Devilee, P, Dork, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Evans, DG, Fasching, PA, Fletcher, O, Flyger, H, Gago-Dominguez, M, Gao, Y-T, Garcia-Closas, M, Garcia-Saenz, JA, Genkinger, J, Gentry-Maharaj, A, Grassmann, F, Guenel, P, Gundert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Harkness, EF, Harrington, PA, Hartikainen, JM, Hartman, M, Hein, A, Ho, W-K, Hooning, MJ, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Huo, D, Investigators, A, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jones, ME, Jung, A, Kaaks, R, Kang, D, Khusnutdinova, EK, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, Lambrechts, D, Le Marchand, L, Li, J, Linet, M, Lo, W-Y, Long, J, Lophatananon, A, Mannermaa, A, Manoochehri, M, Margolin, S, Matsuo, K, Mavroudis, D, Menon, U, Muir, K, Murphy, RA, Nevanlinna, H, Newman, WG, Niederacher, D, O'Brien, KM, Obi, N, Offit, K, Olopade, O, Olshan, AF, Olsson, H, Park, SK, Patel, A, Perou, CM, Peto, J, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rack, B, Radice, P, Ramachandran, D, Rashid, MU, Rennert, G, Romero, A, Ruddy, KJ, Ruebner, M, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneider, MO, Scott, C, Shah, M, Sharma, P, Shen, C-Y, Shu, X-O, Simard, J, Surowy, H, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Vachon, CM, Vijai, J, Weinberg, CR, Wendt, C, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Yang, XR, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Easton, DF, Hemingway, H, Hamann, U, Kuchenbaecker, KB, Mueller, SH, Lai, AG, Valkovskaya, M, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Lush, M, Abu-Ful, Z, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baert, T, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Bonanni, B, Brenner, H, Brucker, SY, Buys, SS, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Chung, WK, Colonna, S, Cornelissen, S, Couch, FJ, Czene, K, Daly, MB, Devilee, P, Dork, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Evans, DG, Fasching, PA, Fletcher, O, Flyger, H, Gago-Dominguez, M, Gao, Y-T, Garcia-Closas, M, Garcia-Saenz, JA, Genkinger, J, Gentry-Maharaj, A, Grassmann, F, Guenel, P, Gundert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Harkness, EF, Harrington, PA, Hartikainen, JM, Hartman, M, Hein, A, Ho, W-K, Hooning, MJ, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Huo, D, Investigators, A, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jones, ME, Jung, A, Kaaks, R, Kang, D, Khusnutdinova, EK, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, Lambrechts, D, Le Marchand, L, Li, J, Linet, M, Lo, W-Y, Long, J, Lophatananon, A, Mannermaa, A, Manoochehri, M, Margolin, S, Matsuo, K, Mavroudis, D, Menon, U, Muir, K, Murphy, RA, Nevanlinna, H, Newman, WG, Niederacher, D, O'Brien, KM, Obi, N, Offit, K, Olopade, O, Olshan, AF, Olsson, H, Park, SK, Patel, A, Perou, CM, Peto, J, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rack, B, Radice, P, Ramachandran, D, Rashid, MU, Rennert, G, Romero, A, Ruddy, KJ, Ruebner, M, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneider, MO, Scott, C, Shah, M, Sharma, P, Shen, C-Y, Shu, X-O, Simard, J, Surowy, H, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Vachon, CM, Vijai, J, Weinberg, CR, Wendt, C, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Yang, XR, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Easton, DF, Hemingway, H, Hamann, U, and Kuchenbaecker, KB

Abstract

BACKGROUND: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. METHODS: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. RESULTS: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. CONCLUSIONS: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.

Published
2023

7. 142P Effectiveness and safety of pegylated liposomal doxorubicin- cyclophosphamide vs. epirubicin-cyclophosphamide as adjuvant chemotherapy for stage I and II HER2-negative breast cancer: An interim analysis of phase II randomized trial

Author

Tseng, L-M., primary, Chen, F-M., additional, Chen, S-T., additional, Cheng, T-F., additional, Chao, T-Y., additional, Dai, M-S., additional, Kao, W-Y., additional, Chen, D-R., additional, Liu, L-C., additional, Wang, H.C., additional, Chang, H-T., additional, Wang, B.W., additional, Yu, J-C., additional, Chen, S.C., additional, Liao, K-H., additional, and Hou, M-F., additional

Published
2022
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9. A Novel Multifaceted Virtual Craniofacial Surgery Scheme Using Computer Vision

Author

Chowdhury, A. S., Bhandarkar, S. M., Tollner, E. W., Zhang, G., Yu, J. C., Ritter, E., 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, Liu, Yanxi, editor, Jiang, Tianzi, editor, and Zhang, Changshui, editor

Published
2005
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20. Breast cancer risk factors and survival by tumor subtype: Pooled analyses from the breast cancer association consortium.

Author

Morra A., Jung A.Y., Behrens S., Keeman R., Ahearn T.U., Anton-Culver H., Arndt V., Augustinsson A., Auvinen P.K., Beane Freeman L.E., Becher H., Beckmann M.W., Blomqvist C., Bojesen S.E., Bolla M.K., Brenner H., Briceno I., Brucker S.Y., Camp N.J., Campa D., Canzian F., Castelao J.E., Chanock S.J., Choi J.-Y., Clarke C.L., Couch F.J., Cox A., Cross S.S., Czene K., Dork T., Dunning A.M., Dwek M., Easton D.F., Eccles D.M., Egan K.M., Evans D.G., Fasching P.A., Flyger H., Gago-Dominguez M., Gapstur S.M., Garcia-Saenz J.A., Gaudet M.M., Giles G.G., Grip M., Guenel P., Haiman C.A., Hakansson N., Hall P., Hamann U., Han S.N., Hart S.N., Hartman M., Heyworth J.S., Hoppe R., Hopper J.L., Hunter D.J., Ito H., Jager A., Jakimovska M., Jakubowska A., Janni W., Kaaks R., Kang D., Kapoor P.M., Kitahara C.M., Koutros S., Kraft P., Kristensen V.N., Lacey J.V., Lambrechts D., Le Marchand L., Li J., Lindblom A., Lubi-Nski J., Lush M., Mannermaa A., Manoochehri M., Margolin S., Mariapun S., Matsuo K., Mavroudis D., Milne R.L., Muranen T.A., Newman W.G., Noh D.-Y., Nordestgaard B.G., Obi N., Olshan A.F., Olsson H., Park-Simon T.-W., Petridis C., Pharoah P.D.P., Plaseska-Karanfilska D., Presneau N., Rashid M.U., Rennert G., Rennert H.S., Rhenius V., Romero A., Saloustros E., Sawyer E.J., Schneeweiss A., Schwentner L., Scott C., Shah M., Shen C.-Y., Shu X.-O., Southey M.C., Stram D.O., Tamimi R.M., Tapper W., Tollenaar R.A.E.M., Tomlinson I., Torres D., Troester M.A., Therese Truong, Vachon C.M., Wang Q., Wang S.S., Williams J.A., Winqvist R., Wolk A., Wu A.H., Yoo K.-Y., Yu J.-C., Zheng W., Ziogas A., Yang X.R., Eliassen A.H., Holmes M.D., Garcia-Closas M., Teo S.H., Schmidt M.K., Chang-Claude J., Morra A., Jung A.Y., Behrens S., Keeman R., Ahearn T.U., Anton-Culver H., Arndt V., Augustinsson A., Auvinen P.K., Beane Freeman L.E., Becher H., Beckmann M.W., Blomqvist C., Bojesen S.E., Bolla M.K., Brenner H., Briceno I., Brucker S.Y., Camp N.J., Campa D., Canzian F., Castelao J.E., Chanock S.J., Choi J.-Y., Clarke C.L., Couch F.J., Cox A., Cross S.S., Czene K., Dork T., Dunning A.M., Dwek M., Easton D.F., Eccles D.M., Egan K.M., Evans D.G., Fasching P.A., Flyger H., Gago-Dominguez M., Gapstur S.M., Garcia-Saenz J.A., Gaudet M.M., Giles G.G., Grip M., Guenel P., Haiman C.A., Hakansson N., Hall P., Hamann U., Han S.N., Hart S.N., Hartman M., Heyworth J.S., Hoppe R., Hopper J.L., Hunter D.J., Ito H., Jager A., Jakimovska M., Jakubowska A., Janni W., Kaaks R., Kang D., Kapoor P.M., Kitahara C.M., Koutros S., Kraft P., Kristensen V.N., Lacey J.V., Lambrechts D., Le Marchand L., Li J., Lindblom A., Lubi-Nski J., Lush M., Mannermaa A., Manoochehri M., Margolin S., Mariapun S., Matsuo K., Mavroudis D., Milne R.L., Muranen T.A., Newman W.G., Noh D.-Y., Nordestgaard B.G., Obi N., Olshan A.F., Olsson H., Park-Simon T.-W., Petridis C., Pharoah P.D.P., Plaseska-Karanfilska D., Presneau N., Rashid M.U., Rennert G., Rennert H.S., Rhenius V., Romero A., Saloustros E., Sawyer E.J., Schneeweiss A., Schwentner L., Scott C., Shah M., Shen C.-Y., Shu X.-O., Southey M.C., Stram D.O., Tamimi R.M., Tapper W., Tollenaar R.A.E.M., Tomlinson I., Torres D., Troester M.A., Therese Truong, Vachon C.M., Wang Q., Wang S.S., Williams J.A., Winqvist R., Wolk A., Wu A.H., Yoo K.-Y., Yu J.-C., Zheng W., Ziogas A., Yang X.R., Eliassen A.H., Holmes M.D., Garcia-Closas M., Teo S.H., Schmidt M.K., and Chang-Claude J.

Abstract

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Method(s): We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer. specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Result(s): There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj > 0.30). The strongest associations were between all-cause mortality and BMI >=30 versus 18.5.25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age >=30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0.<5 years versus >=10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen.progestin therapy [0.61 (0.54.0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking. Conclusion(s): We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.Copyright © 2021 American Association for Cancer Research.

Published
2021

21. Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium

Author

Morra, A, Jung, AY, Behrens, S, Keeman, R, Ahearn, TU, Anton-Culver, H, Arndt, V, Augustinsson, A, Auvinen, PK, Freeman, LEB, Becher, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Brenner, H, Briceno, I, Brucker, SY, Camp, NJ, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Egan, KM, Evans, DG, Fasching, PA, Flyger, H, Gago-Dominguez, M, Gapstur, SM, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Grip, M, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Han, SN, Hart, SN, Hartman, M, Heyworth, JS, Hoppe, R, Hopper, JL, Hunter, DJ, Ito, H, Jager, A, Jakimovska, M, Jakubowska, A, Janni, W, Kaaks, R, Kang, D, Kapoor, PM, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Lacey, J, Lambrechts, D, Le Marchand, L, Li, J, Lindblom, A, Lush, M, Mannermaa, A, Manoochehri, M, Margolin, S, Mariapun, S, Matsuo, K, Mavroudis, D, Milne, RL, Muranen, TA, Newman, WG, Noh, D-Y, Nordestgaard, BG, Obi, N, Olshan, AF, Olsson, H, Park-Simon, T-W, Petridis, C, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rashid, MU, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schwentner, L, Scott, C, Shah, M, Shen, C-Y, Shu, X-O, Southey, MC, Stram, DO, Tamimi, RM, Tapper, W, Tollenaar, RAEM, Tomlinson, I, Torres, D, Troester, MA, Truong, T, Vachon, CM, Wang, Q, Wang, SS, Williams, JA, Winqvist, R, Wolk, A, Wu, AH, Yoo, K-Y, Yu, J-C, Zheng, W, Ziogas, A, Yang, XR, Eliassen, AH, Holmes, MD, Garcia-Closas, M, Teo, SH, Schmidt, MK, Chang-Claude, J, Morra, A, Jung, AY, Behrens, S, Keeman, R, Ahearn, TU, Anton-Culver, H, Arndt, V, Augustinsson, A, Auvinen, PK, Freeman, LEB, Becher, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Brenner, H, Briceno, I, Brucker, SY, Camp, NJ, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Egan, KM, Evans, DG, Fasching, PA, Flyger, H, Gago-Dominguez, M, Gapstur, SM, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Grip, M, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Han, SN, Hart, SN, Hartman, M, Heyworth, JS, Hoppe, R, Hopper, JL, Hunter, DJ, Ito, H, Jager, A, Jakimovska, M, Jakubowska, A, Janni, W, Kaaks, R, Kang, D, Kapoor, PM, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Lacey, J, Lambrechts, D, Le Marchand, L, Li, J, Lindblom, A, Lush, M, Mannermaa, A, Manoochehri, M, Margolin, S, Mariapun, S, Matsuo, K, Mavroudis, D, Milne, RL, Muranen, TA, Newman, WG, Noh, D-Y, Nordestgaard, BG, Obi, N, Olshan, AF, Olsson, H, Park-Simon, T-W, Petridis, C, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rashid, MU, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schwentner, L, Scott, C, Shah, M, Shen, C-Y, Shu, X-O, Southey, MC, Stram, DO, Tamimi, RM, Tapper, W, Tollenaar, RAEM, Tomlinson, I, Torres, D, Troester, MA, Truong, T, Vachon, CM, Wang, Q, Wang, SS, Williams, JA, Winqvist, R, Wolk, A, Wu, AH, Yoo, K-Y, Yu, J-C, Zheng, W, Ziogas, A, Yang, XR, Eliassen, AH, Holmes, MD, Garcia-Closas, M, Teo, SH, Schmidt, MK, and Chang-Claude, J

Abstract

BACKGROUND: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking. CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

Published
2021

22. Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

Author

Schweinsberg, M., Feldman, M., Staub, N., van den Akker, O.R., van Aert, R.C.M., van Assen, M.A.L.M., Liu, Y., Althoff, T., Heer, J., Kale, A., Mohamed, Z., Amireh, H., Venkatesh Prasad, V., Bernstein, A., Robinson, E., Snellman, K., Amy Sommer, S., Otner, S.M.G., Robinson, D., Madan, N., Silberzahn, R., Goldstein, P., Tierney, W., Murase, T., Mandl, B., Viganola, D., Strobl, C., Schaumans, C.B.C., Kelchtermans, S., Naseeb, C., Mason Garrison, S., Yarkoni, T., Richard Chan, C.S., Adie, P., Alaburda, P., Albers, C., Alspaugh, S., Alstott, J., Nelson, A.A., Ariño de la Rubia, E., Arzi, A., Bahník, Š., Baik, J., Winther Balling, L., Banker, S., AA Baranger, D., Barr, D.J., Barros-Rivera, B., Bauer, M., Blaise, E., Boelen, L., Bohle Carbonell, K., Briers, R.A., Burkhard, O., Canela, M.-A., Castrillo, L., Catlett, T., Chen, O., Clark, M., Cohn, B., Coppock, A., Cugueró-Escofet, N., Curran, P.G., Cyrus-Lai, W., Dai, D., Valentino Dalla Riva, G., Danielsson, H., Russo, R.D.F.S.M., de Silva, N., Derungs, C., Dondelinger, F., Duarte de Souza, C., Tyson Dube, B., Dubova, M., Mark Dunn, B., Adriaan Edelsbrunner, P., Finley, S., Fox, N., Gnambs, T., Gong, Y., Grand, E., Greenawalt, B., Han, D., Hanel, P.H.P., Hong, A.B., Hood, D., Hsueh, J., Huang, L., Hui, K.N., Hultman, K.A., Javaid, A., Ji Jiang, L., Jong, J., Kamdar, J., Kane, D., Kappler, G., Kaszubowski, E., Kavanagh, C.M., Khabsa, M., Kleinberg, B., Kouros, J., Krause, H., Krypotos, A.-M., Lavbič, D., Ling Lee, R., Leffel, T., Yang Lim, W., Liverani, S., Loh, B., Lønsmann, D., Wei Low, J., Lu, A., MacDonald, K., Madan, C.R., Hjorth Madsen, L., Maimone, C., Mangold, A., Marshall, A., Ester Matskewich, H., Mavon, K., McLain, K.L., McNamara, A.A., McNeill, M., Mertens, U., Miller, D., Moore, B., Moore, A., Nantz, E., Nasrullah, Z., Nejkovic, V., Nell, C.S., Arthur Nelson, A., Nilsonne, G., Nolan, R., O Brien, C.E., O Neill, P., O Shea, K., Olita, Toto, Otterbacher, J., Palsetia, D., Pereira, B., Pozdniakov, I., Protzko, J., Reyt, J.-N., Riddle, T., Akmal Ridhwan Omar Ali, A., Ropovik, I., Rosenberg, J.M., Rothen, S., Schulte-Mecklenbeck, M., Sharma, N., Shotwell, G., Skarzynski, M., Stedden, W., Stodden, V., Stoffel, M.A., Stoltzman, S., Subbaiah, S., Tatman, R., Thibodeau, P.H., Tomkins, S., Valdivia, A., Druijff-van de Woestijne, G.B., Viana, L., Villesèche, F., Duncan Wadsworth, W., Wanders, F., Watts, K., Wells, J.D., Whelpley, C.E., Won, A., Wu, L., Yip, A., Youngflesh, C., Yu, J.-C., Zandian, A., Zhang, L., Zibman, C., Luis Uhlmann, E., Schweinsberg, M., Feldman, M., Staub, N., van den Akker, O.R., van Aert, R.C.M., van Assen, M.A.L.M., Liu, Y., Althoff, T., Heer, J., Kale, A., Mohamed, Z., Amireh, H., Venkatesh Prasad, V., Bernstein, A., Robinson, E., Snellman, K., Amy Sommer, S., Otner, S.M.G., Robinson, D., Madan, N., Silberzahn, R., Goldstein, P., Tierney, W., Murase, T., Mandl, B., Viganola, D., Strobl, C., Schaumans, C.B.C., Kelchtermans, S., Naseeb, C., Mason Garrison, S., Yarkoni, T., Richard Chan, C.S., Adie, P., Alaburda, P., Albers, C., Alspaugh, S., Alstott, J., Nelson, A.A., Ariño de la Rubia, E., Arzi, A., Bahník, Š., Baik, J., Winther Balling, L., Banker, S., AA Baranger, D., Barr, D.J., Barros-Rivera, B., Bauer, M., Blaise, E., Boelen, L., Bohle Carbonell, K., Briers, R.A., Burkhard, O., Canela, M.-A., Castrillo, L., Catlett, T., Chen, O., Clark, M., Cohn, B., Coppock, A., Cugueró-Escofet, N., Curran, P.G., Cyrus-Lai, W., Dai, D., Valentino Dalla Riva, G., Danielsson, H., Russo, R.D.F.S.M., de Silva, N., Derungs, C., Dondelinger, F., Duarte de Souza, C., Tyson Dube, B., Dubova, M., Mark Dunn, B., Adriaan Edelsbrunner, P., Finley, S., Fox, N., Gnambs, T., Gong, Y., Grand, E., Greenawalt, B., Han, D., Hanel, P.H.P., Hong, A.B., Hood, D., Hsueh, J., Huang, L., Hui, K.N., Hultman, K.A., Javaid, A., Ji Jiang, L., Jong, J., Kamdar, J., Kane, D., Kappler, G., Kaszubowski, E., Kavanagh, C.M., Khabsa, M., Kleinberg, B., Kouros, J., Krause, H., Krypotos, A.-M., Lavbič, D., Ling Lee, R., Leffel, T., Yang Lim, W., Liverani, S., Loh, B., Lønsmann, D., Wei Low, J., Lu, A., MacDonald, K., Madan, C.R., Hjorth Madsen, L., Maimone, C., Mangold, A., Marshall, A., Ester Matskewich, H., Mavon, K., McLain, K.L., McNamara, A.A., McNeill, M., Mertens, U., Miller, D., Moore, B., Moore, A., Nantz, E., Nasrullah, Z., Nejkovic, V., Nell, C.S., Arthur Nelson, A., Nilsonne, G., Nolan, R., O Brien, C.E., O Neill, P., O Shea, K., Olita, Toto, Otterbacher, J., Palsetia, D., Pereira, B., Pozdniakov, I., Protzko, J., Reyt, J.-N., Riddle, T., Akmal Ridhwan Omar Ali, A., Ropovik, I., Rosenberg, J.M., Rothen, S., Schulte-Mecklenbeck, M., Sharma, N., Shotwell, G., Skarzynski, M., Stedden, W., Stodden, V., Stoffel, M.A., Stoltzman, S., Subbaiah, S., Tatman, R., Thibodeau, P.H., Tomkins, S., Valdivia, A., Druijff-van de Woestijne, G.B., Viana, L., Villesèche, F., Duncan Wadsworth, W., Wanders, F., Watts, K., Wells, J.D., Whelpley, C.E., Won, A., Wu, L., Yip, A., Youngflesh, C., Yu, J.-C., Zandian, A., Zhang, L., Zibman, C., and Luis Uhlmann, E.

Abstract

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.

Published
2021

27. Two truncating variants in FANCC and breast cancer risk.

Author

Gaudet M.M., Kaaks R., Kang D., Kwong A., Lambrechts D., Marchand L.L., Li J., Lindstrom S., Linet M., Lo W.-Y., Long J., Lophatananon A., Lubinski J., Manoochehri M., Manoukian S., Margolin S., Martinez E., Matsuo K., Mavroudis D., Meindl A., Menon U., Milne R.L., Mohd Taib N.A., Muir K., Mulligan A.M., Neuhausen S.L., Nevanlinna H., Neven P., Newman W.G., Offit K., Olopade O.I., Olshan A.F., Olson J.E., Olsson H., Park S.K., Park-Simon T.-W., Peto J., Plaseska-Karanfilska D., Pohl-Rescigno E., Presneau N., Rack B., Radice P., Rashid M.U., Rennert G., Rennert H.S., Romero A., Ruebner M., Saloustros E., Schmidt M.K., Schmutzler R.K., Schneider M.O., Schoemaker M.J., Scott C., Shen C.-Y., Shu X.-O., Simard J., Slager S., Smichkoska S., Southey M.C., Spinelli J.J., Stone J., Surowy H., Swerdlow A.J., Tamimi R.M., Tapper W.J., Teo S.H., Terry M.B., Toland A.E., Tollenaar R.A.E.M., Torres D., Torres-Mejia G., Troester M.A., Truong T., Tsugane S., Untch M., Vachon C.M., Ouweland A.M.W.V.D., Veen E.M.V., Vijai J., Wendt C., Wolk A., Yu J.-C., Zheng W., Ziogas A., Ziv E., Dunning A.M., Pharoah P.D.P., Schindler D., Devilee P., Easton D.F., Hopper J.L., Howell T., Huo D., Ito H., Iwasaki M., Jakubowska A., Janni W., John E.M., Dork T., Peterlongo P., Mannermaa A., Bolla M.K., Wang Q., Dennis J., Ahearn T., Andrulis I.L., Anton-Culver H., Arndt V., Aronson K.J., Augustinsson A., Freeman L.E.B., Beckmann M.W., Beeghly-Fadiel A., Behrens S., Bermisheva M., Blomqvist C., Bogdanova N.V., Bojesen S.E., Brauch H., Brenner H., Burwinkel B., Canzian F., Chan T.L., Chang-Claude J., Chanock S.J., Choi J.-Y., Christiansen H., Clarke C.L., Couch F.J., Czene K., Daly M.B., Dos-Santos-Silva I., Dwek M., Eccles D.M., Ekici A.B., Eriksson M., Evans D.G., Fasching P.A., Figueroa J., Flyger H., Fritschi L., Gabrielson M., Gago-Dominguez M., Gao C., Gapstur S.M., Garcia-Closas M., Garcia-Saenz J.A., Jung A., Giles G.G., Goldberg M.S., Goldgar D.E., Guenel P., Haeberle L., Haiman C.A., Hakansson N., Hall P., Hamann U., Hartman M., Hauke J., Hein A., Hillemanns P., Hogervorst F.B.L., Hooning M.J., Kapoor P.M., Khusnutdinova E., Kim S.-W., Kitahara C.M., Koutros S., Kraft P., Kristensen V.N., Gaudet M.M., Kaaks R., Kang D., Kwong A., Lambrechts D., Marchand L.L., Li J., Lindstrom S., Linet M., Lo W.-Y., Long J., Lophatananon A., Lubinski J., Manoochehri M., Manoukian S., Margolin S., Martinez E., Matsuo K., Mavroudis D., Meindl A., Menon U., Milne R.L., Mohd Taib N.A., Muir K., Mulligan A.M., Neuhausen S.L., Nevanlinna H., Neven P., Newman W.G., Offit K., Olopade O.I., Olshan A.F., Olson J.E., Olsson H., Park S.K., Park-Simon T.-W., Peto J., Plaseska-Karanfilska D., Pohl-Rescigno E., Presneau N., Rack B., Radice P., Rashid M.U., Rennert G., Rennert H.S., Romero A., Ruebner M., Saloustros E., Schmidt M.K., Schmutzler R.K., Schneider M.O., Schoemaker M.J., Scott C., Shen C.-Y., Shu X.-O., Simard J., Slager S., Smichkoska S., Southey M.C., Spinelli J.J., Stone J., Surowy H., Swerdlow A.J., Tamimi R.M., Tapper W.J., Teo S.H., Terry M.B., Toland A.E., Tollenaar R.A.E.M., Torres D., Torres-Mejia G., Troester M.A., Truong T., Tsugane S., Untch M., Vachon C.M., Ouweland A.M.W.V.D., Veen E.M.V., Vijai J., Wendt C., Wolk A., Yu J.-C., Zheng W., Ziogas A., Ziv E., Dunning A.M., Pharoah P.D.P., Schindler D., Devilee P., Easton D.F., Hopper J.L., Howell T., Huo D., Ito H., Iwasaki M., Jakubowska A., Janni W., John E.M., Dork T., Peterlongo P., Mannermaa A., Bolla M.K., Wang Q., Dennis J., Ahearn T., Andrulis I.L., Anton-Culver H., Arndt V., Aronson K.J., Augustinsson A., Freeman L.E.B., Beckmann M.W., Beeghly-Fadiel A., Behrens S., Bermisheva M., Blomqvist C., Bogdanova N.V., Bojesen S.E., Brauch H., Brenner H., Burwinkel B., Canzian F., Chan T.L., Chang-Claude J., Chanock S.J., Choi J.-Y., Christiansen H., Clarke C.L., Couch F.J., Czene K., Daly M.B., Dos-Santos-Silva I., Dwek M., Eccles D.M., Ekici A.B., Eriksson M., Evans D.G., Fasching P.A., Figueroa J., Flyger H., Fritschi L., Gabrielson M., Gago-Dominguez M., Gao C., Gapstur S.M., Garcia-Closas M., Garcia-Saenz J.A., Jung A., Giles G.G., Goldberg M.S., Goldgar D.E., Guenel P., Haeberle L., Haiman C.A., Hakansson N., Hall P., Hamann U., Hartman M., Hauke J., Hein A., Hillemanns P., Hogervorst F.B.L., Hooning M.J., Kapoor P.M., Khusnutdinova E., Kim S.-W., Kitahara C.M., Koutros S., Kraft P., and Kristensen V.N.

Abstract

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p=0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

Published
2020

43. Two truncating variants in FANCC and breast cancer risk

Author

Dork, T, Peterlongo, P, Mannermaa, A, Bolla, MK, Wang, Q, Dennis, J, Ahearn, T, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Augustinsson, A, Freeman, LEB, Beckmann, MW, Beeghly-Fadiel, A, Behrens, S, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Brauch, H, Brenner, H, Burwinkel, B, Canzian, F, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Christiansen, H, Clarke, CL, Couch, FJ, Czene, K, Daly, MB, dos-Santos-Silva, I, Dwek, M, Eccles, DM, Ekici, AB, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Flyger, H, Fritschisl, L, Gabrielson, M, Gago-Dominguez, M, Gao, C, Gapstur, SM, Garcia-Closas, M, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, Goldgar, DE, Guenel, P, Haeberle, L, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hartman, M, Hauke, J, Hein, A, Hillemanns, P, Hogervorst, FBL, Hooning, MJ, Hopper, JL, Howell, T, Huo, D, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jung, A, Kaaks, R, Kang, D, Kapoor, PM, Khusnutdinova, E, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kwon, A, Lambrechts, D, Le Marchand, L, Li, J, Lindstrom, S, Linet, M, Lo, W-Y, Long, J, Lophatananon, A, Lubinski, J, Manoochehri, M, Manoukian, S, Margolin, S, Martinez, E, Matsuo, K, Mavroudis, D, Meindl, A, Menon, U, Milne, RL, Taib, NAM, Muir, K, Mulligan, AM, Neuhausen, SL, Nevanlinna, H, Neven, P, Newman, WG, Offit, K, Olopade, O, Olshan, AF, Olson, JE, Olsson, H, Park, SK, Park-Simon, T-W, Peto, J, Plaseska-Karanfilska, D, Pohl-Rescigno, E, Presneau, N, Rack, B, Radice, P, Rashid, MU, Rennert, G, Rennert, HS, Romero, A, Ruebner, M, Saloustros, E, Schmidt, MK, Schmutzler, RK, Schneider, MO, Schoemaker, MJ, Scott, C, Shen, C-Y, Shu, X-O, Simard, J, Slager, S, Smichkoska, S, Southey, MC, Spinelli, JJ, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Teo, SH, Terry, MB, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Tsugane, S, Untch, M, Vachon, CM, van den Ouweland, AMW, van Veen, EM, Vijai, J, Wendt, C, Wolk, A, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Pharoah, PDP, Schindler, D, Devilee, P, Easton, DF, Balleine, R, Baxter, R, Braye, S, Carpenter, J, Dahlstrom, J, Forbes, J, Lee, CS, Marsh, D, Morey, A, Pathmanathan, N, Scott, R, Simpson, P, Spigelman, A, Wilcken, N, Yip, D, Zeps, N, Borresen-Dale, A-L, Alnaes, GIG, Sahlberg, KK, Ottestad, L, Karesen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebraten, O, Naume, B, Fossa, A, Kiserud, CE, Reinertsen, K, Helland, A, Riis, M, Geisler, J, Dork, T, Peterlongo, P, Mannermaa, A, Bolla, MK, Wang, Q, Dennis, J, Ahearn, T, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Augustinsson, A, Freeman, LEB, Beckmann, MW, Beeghly-Fadiel, A, Behrens, S, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Brauch, H, Brenner, H, Burwinkel, B, Canzian, F, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Christiansen, H, Clarke, CL, Couch, FJ, Czene, K, Daly, MB, dos-Santos-Silva, I, Dwek, M, Eccles, DM, Ekici, AB, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Flyger, H, Fritschisl, L, Gabrielson, M, Gago-Dominguez, M, Gao, C, Gapstur, SM, Garcia-Closas, M, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, Goldgar, DE, Guenel, P, Haeberle, L, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hartman, M, Hauke, J, Hein, A, Hillemanns, P, Hogervorst, FBL, Hooning, MJ, Hopper, JL, Howell, T, Huo, D, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jung, A, Kaaks, R, Kang, D, Kapoor, PM, Khusnutdinova, E, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kwon, A, Lambrechts, D, Le Marchand, L, Li, J, Lindstrom, S, Linet, M, Lo, W-Y, Long, J, Lophatananon, A, Lubinski, J, Manoochehri, M, Manoukian, S, Margolin, S, Martinez, E, Matsuo, K, Mavroudis, D, Meindl, A, Menon, U, Milne, RL, Taib, NAM, Muir, K, Mulligan, AM, Neuhausen, SL, Nevanlinna, H, Neven, P, Newman, WG, Offit, K, Olopade, O, Olshan, AF, Olson, JE, Olsson, H, Park, SK, Park-Simon, T-W, Peto, J, Plaseska-Karanfilska, D, Pohl-Rescigno, E, Presneau, N, Rack, B, Radice, P, Rashid, MU, Rennert, G, Rennert, HS, Romero, A, Ruebner, M, Saloustros, E, Schmidt, MK, Schmutzler, RK, Schneider, MO, Schoemaker, MJ, Scott, C, Shen, C-Y, Shu, X-O, Simard, J, Slager, S, Smichkoska, S, Southey, MC, Spinelli, JJ, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Teo, SH, Terry, MB, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Tsugane, S, Untch, M, Vachon, CM, van den Ouweland, AMW, van Veen, EM, Vijai, J, Wendt, C, Wolk, A, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Pharoah, PDP, Schindler, D, Devilee, P, Easton, DF, Balleine, R, Baxter, R, Braye, S, Carpenter, J, Dahlstrom, J, Forbes, J, Lee, CS, Marsh, D, Morey, A, Pathmanathan, N, Scott, R, Simpson, P, Spigelman, A, Wilcken, N, Yip, D, Zeps, N, Borresen-Dale, A-L, Alnaes, GIG, Sahlberg, KK, Ottestad, L, Karesen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebraten, O, Naume, B, Fossa, A, Kiserud, CE, Reinertsen, K, Helland, A, Riis, M, and Geisler, J

Abstract

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

Published
2019

45. Two-stage game-theoretic approach to supplier evaluation, selection, and order assignment.

Author

Yu, J. C. P., Wee, H. M., Jeng, S., and Daryanto, Y.

Subjects
SELECTION & appointment of arbitrators, EVALUATION, INDUSTRIALISTS, SUPPLY chain management, NASH equilibrium
Abstract

This study proposes a framework for supplier evaluation, selection, and assignment that incorporates a two-stage game-theoretic approach method. The objective is to provide manufacturers with insights to choose suitable suppliers for different manufacturing processes. The framework applies to the decision logic of multiple manufacturing processes. In the first stage, a non-cooperative game model is utilized for supplier evaluation and selection. The interactive behaviors between a manufacturer and some supplier candidates are modeled and analyzed so that the Supplier Evaluation Value (SEV) can be obtained using the Nash equilibrium. In the second stage, the SEVs become the input for the Shepley values calculation of each supplier under a cooperative game model. The Shapley values are utilized to create a set of limited supplier allocation. This paper provides managerial insights to verify the viability of the proposed approach for supplier selection and allocation. Thus, it enables Supply Chain Management (SCM) manager to optimize supplier evaluation, selection, and order assignment. [ABSTRACT FROM AUTHOR]

Published
2021
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