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1. Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia

Author

Vijayakrishnan, J, Studd, J, Broderick, P, Kinnersley, B, Holroyd, A, Law, PJ, Kumar, R, Allan, JM, Harrison, CJ, Moorman, AV, Vora, A, Roman, E, Rachakonda, S, Kinsey, SE, Sheridan, E, Thompson, PD, Irving, JA, Koehler, R, Hoffmann, P, Nöthen, MM, Heilmann-Heimbach, S, Jöckel, KH, Easton, DF, Pharaoh, PDP, Dunning, AM, Peto, J, Canzian, F, Swerdlow, A, Eeles, RA, Kote-Jarai, Z, Muir, K, Pashayan, N, Greaves, M, Zimmerman, M, Bartram, CR, Schrappe, M, Stanulla, M, Hemminki, K, Houlston, RS, Henderson, BE, Haiman, CA, Benlloch, S, Schumacher, FR, Olama, AAA, Berndt, SI, Conti, DV, Wiklund, F, Chanock, S, Stevens, VL, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Schleutker, J, Albanes, D, Weinstein, S, Wolk, A, West, C, Mucci, L, Cancel-Tassin, G, Koutros, S, Sorensen, KD, Maehle, L, Neal, DE, Travis, RC, Hamilton, RJ, Ingles, SA, Rosenstein, B, Lu, YJ, Giles, GG, Kibel, AS, Vega, A, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, The PRACTICAL Consortium, and Claessens, Frank

Subjects
Male, Oncogene Proteins, Fusion, Glycosyltransferases, Prognosis, Polymorphism, Single Nucleotide, HLA Antigens, Risk Factors, Child, Preschool, Precursor B-Cell Lymphoblastic Leukemia-Lymphoma, Core Binding Factor Alpha 2 Subunit, Humans, Female, Genetic Predisposition to Disease, Child, Genome-Wide Association Study
Abstract

© 2018 The Author(s). Genome-wide association studies (GWAS) have advanced our understanding of susceptibility to B-cell precursor acute lymphoblastic leukemia (BCP-ALL); however, much of the heritable risk remains unidentified. Here, we perform a GWAS and conduct a meta-analysis with two existing GWAS, totaling 2442 cases and 14,609 controls. We identify risk loci for BCP-ALL at 8q24.21 (rs28665337, P = 3.86 × 10-9, odds ratio (OR) = 1.34) and for ETV6-RUNX1 fusion-positive BCP-ALL at 2q22.3 (rs17481869, P = 3.20 × 10-8, OR = 2.14). Our findings provide further insights into genetic susceptibility to ALL and its biology. ispartof: Nature Communications vol:9 issue:1 ispartof: location:England status: published

Published
2018

2. Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia (vol 9, 1340, 2018)

Author

Vijayakrishnan, J, Studd, J, Broderick, P, Kinnersley, B, Holroyd, A, Law, PJ, Kumar, R, Allan, JM, Harrison, CJ, Moorman, AV, Vora, A, Roman, E, Rachakonda, S, Kinsey, SE, Sheridan, E, Thompson, PD, Irving, JA, Koehler, R, Hoffmann, P, Noethen, MM, Heilmann-Heimbach, S, Joeckel, K-H, Easton, DF, Pharaoh, PDP, Dunning, AM, Peto, J, Canzian, F, Swerdlow, A, Eeles, RA, Kote-Jarai, Z, Muir, K, Pashayan, N, Henderson, BE, Haiman, CA, Benlloch, S, Schumacher, FR, Al Olama, AA, Berndt, SI, Conti, DV, Wiklund, F, Chanock, S, Stevens, VL, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Schleutker, J, Albanes, D, Weinstein, S, Wolk, A, West, C, Mucci, L, Cancel-Tassin, G, Koutros, S, Sorensen, KD, Maehle, L, Neal, DE, Travis, RC, Hamilton, RJ, Ingles, SA, Rosenstein, B, Lu, Y-J, Giles, GG, Kibel, AS, Vega, A, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, Cybulski, C, Nordestgaard, BG, Brenner, H, Maier, C, Kim, J, John, EM, Teixeira, MR, Neuhausen, SL, De Ruyck, K, Razack, A, Newcomb, LF, Lessel, D, Kaneva, R, Usmani, N, Claessens, F, Townsend, PA, Gago-Dominguez, M, Roobol, MJ, Menegaux, F, Greaves, M, Zimmerman, M, Bartram, CR, Schrappe, M, Stanulla, M, Hemminki, K, Houlston, RS, Vijayakrishnan, J, Studd, J, Broderick, P, Kinnersley, B, Holroyd, A, Law, PJ, Kumar, R, Allan, JM, Harrison, CJ, Moorman, AV, Vora, A, Roman, E, Rachakonda, S, Kinsey, SE, Sheridan, E, Thompson, PD, Irving, JA, Koehler, R, Hoffmann, P, Noethen, MM, Heilmann-Heimbach, S, Joeckel, K-H, Easton, DF, Pharaoh, PDP, Dunning, AM, Peto, J, Canzian, F, Swerdlow, A, Eeles, RA, Kote-Jarai, Z, Muir, K, Pashayan, N, Henderson, BE, Haiman, CA, Benlloch, S, Schumacher, FR, Al Olama, AA, Berndt, SI, Conti, DV, Wiklund, F, Chanock, S, Stevens, VL, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Schleutker, J, Albanes, D, Weinstein, S, Wolk, A, West, C, Mucci, L, Cancel-Tassin, G, Koutros, S, Sorensen, KD, Maehle, L, Neal, DE, Travis, RC, Hamilton, RJ, Ingles, SA, Rosenstein, B, Lu, Y-J, Giles, GG, Kibel, AS, Vega, A, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, Cybulski, C, Nordestgaard, BG, Brenner, H, Maier, C, Kim, J, John, EM, Teixeira, MR, Neuhausen, SL, De Ruyck, K, Razack, A, Newcomb, LF, Lessel, D, Kaneva, R, Usmani, N, Claessens, F, Townsend, PA, Gago-Dominguez, M, Roobol, MJ, Menegaux, F, Greaves, M, Zimmerman, M, Bartram, CR, Schrappe, M, Stanulla, M, Hemminki, K, and Houlston, RS

Abstract

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Published
2019

3. Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer (vol 138, pg 307, 2019)

Author

Bien, SA, Su, Y-R, Conti, DV, Harrison, TA, Qu, C, Guo, X, Lu, Y, Albanes, D, Auer, PL, Banbury, BL, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Caan, BJ, Campbell, PT, Carlson, CS, Chan, AT, Chang-Claude, J, Chen, S, Connolly, CM, Easton, DF, Feskens, EJM, Gallinger, S, Giles, GG, Gunter, MJ, Hampe, J, Huyghe, JR, Hoffmeister, M, Hudson, TJ, Jacobs, EJ, Jenkins, MA, Kampman, E, Kang, HM, Kuehn, T, Kury, S, Lejbkowicz, F, Le Marchand, L, Milne, RL, Li, L, Li, CI, Lindblom, A, Lindor, NM, Martin, V, McNeil, CE, Melas, M, Moreno, V, Newcomb, PA, Offit, K, Pharaoh, PDP, Potter, JD, Riboli, E, Rennert, G, Sala, N, Schafmayer, C, Scacheri, PC, Schmit, SL, Severi, G, Slattery, ML, Smith, JD, Trichopoulou, A, Tumino, R, Ulrich, CM, van Duijnhoven, FJB, Van Guelpen, B, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Casey, G, Nickerson, DA, Gruber, SB, Hsu, L, Zheng, W, Peters, U, Bien, SA, Su, Y-R, Conti, DV, Harrison, TA, Qu, C, Guo, X, Lu, Y, Albanes, D, Auer, PL, Banbury, BL, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Caan, BJ, Campbell, PT, Carlson, CS, Chan, AT, Chang-Claude, J, Chen, S, Connolly, CM, Easton, DF, Feskens, EJM, Gallinger, S, Giles, GG, Gunter, MJ, Hampe, J, Huyghe, JR, Hoffmeister, M, Hudson, TJ, Jacobs, EJ, Jenkins, MA, Kampman, E, Kang, HM, Kuehn, T, Kury, S, Lejbkowicz, F, Le Marchand, L, Milne, RL, Li, L, Li, CI, Lindblom, A, Lindor, NM, Martin, V, McNeil, CE, Melas, M, Moreno, V, Newcomb, PA, Offit, K, Pharaoh, PDP, Potter, JD, Riboli, E, Rennert, G, Sala, N, Schafmayer, C, Scacheri, PC, Schmit, SL, Severi, G, Slattery, ML, Smith, JD, Trichopoulou, A, Tumino, R, Ulrich, CM, van Duijnhoven, FJB, Van Guelpen, B, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Casey, G, Nickerson, DA, Gruber, SB, Hsu, L, Zheng, W, and Peters, U

Abstract

Every author has erroneously been assigned to the affiliation "62". The affiliation 62 belongs to the author Graham Casey.

Published
2019

4. Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer

Author

Bien, SA, Su, Y-R, Conti, DV, Harrison, TA, Qu, C, Guo, X, Lu, Y, Albanes, D, Auer, PL, Banbury, BL, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Caan, BJ, Campbell, PT, Carlson, CS, Chan, AT, Chang-Claude, J, Chen, S, Connolly, CM, Easton, DF, Feskens, EJM, Gallinger, S, Giles, GG, Gunter, MJ, Hampe, J, Huyghe, JR, Hoffmeister, M, Hudson, TJ, Jacobs, EJ, Jenkins, MA, Kampman, E, Kang, HM, Kuehn, T, Kury, S, Lejbkowicz, F, Le Marchand, L, Milne, RL, Li, L, Li, CI, Lindblom, A, Lindor, NM, Martin, V, McNeil, CE, Melas, M, Moreno, V, Newcomb, PA, Offit, K, Pharaoh, PDP, Potter, JD, Riboli, E, Rennert, G, Sala, N, Schafmayer, C, Scacheri, PC, Schmit, SL, Severi, G, Slattery, ML, Smith, JD, Trichopoulou, A, Tumino, R, Ulrich, CM, van Duijnhoven, FJB, Van Guelpen, B, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Casey, G, Nickerson, DA, Gruber, SB, Hsu, L, Zheng, W, Peters, U, Bien, SA, Su, Y-R, Conti, DV, Harrison, TA, Qu, C, Guo, X, Lu, Y, Albanes, D, Auer, PL, Banbury, BL, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Caan, BJ, Campbell, PT, Carlson, CS, Chan, AT, Chang-Claude, J, Chen, S, Connolly, CM, Easton, DF, Feskens, EJM, Gallinger, S, Giles, GG, Gunter, MJ, Hampe, J, Huyghe, JR, Hoffmeister, M, Hudson, TJ, Jacobs, EJ, Jenkins, MA, Kampman, E, Kang, HM, Kuehn, T, Kury, S, Lejbkowicz, F, Le Marchand, L, Milne, RL, Li, L, Li, CI, Lindblom, A, Lindor, NM, Martin, V, McNeil, CE, Melas, M, Moreno, V, Newcomb, PA, Offit, K, Pharaoh, PDP, Potter, JD, Riboli, E, Rennert, G, Sala, N, Schafmayer, C, Scacheri, PC, Schmit, SL, Severi, G, Slattery, ML, Smith, JD, Trichopoulou, A, Tumino, R, Ulrich, CM, van Duijnhoven, FJB, Van Guelpen, B, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Casey, G, Nickerson, DA, Gruber, SB, Hsu, L, Zheng, W, and Peters, U

Abstract

Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n = 169) and whole blood (n = 922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR ≤ 0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P = 2.2 × 10- 4, replication P = 0.01), and PYGL (discovery P = 2.3 × 10- 4, replication P = 6.7 × 10- 4). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight in

Published
2019

5. Correction to: Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer.

Author

Bien SA, Su YR, Conti DV, Harrison TA, Qu C, Guo X, Lu Y, Albanes D, Auer PL, Banbury BL, Berndt SI, Bézieau S, Brenner H, Buchanan DD, Caan BJ, Campbell PT, Carlson CS, Chan AT, Chang-Claude J, Chen S, Connolly CM, Easton DF, Feskens EJM, Gallinger S, Giles GG, Gunter MJ, Hampe J, Huyghe JR, Hoffmeister M, Hudson TJ, Jacobs EJ, Jenkins MA, Kampman E, Kang HM, Kühn T, Küry S, Lejbkowicz F, Le Marchand L, Milne RL, Li L, Li CI, Lindblom A, Lindor NM, Martín V, McNeil CE, Melas M, Moreno V, Newcomb PA, Offit K, Pharaoh PDP, Potter JD, Qu C, Riboli E, Rennert G, Sala N, Schafmayer C, Scacheri PC, Schmit SL, Severi G, Slattery ML, Smith JD, Trichopoulou A, Tumino R, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Weinstein SJ, White E, Wolk A, Woods MO, Wu AH, Abeçasis GR, Casey G, Nickerson DA, Gruber SB, Hsu L, Zheng W, and Peters U

Abstract

Every author has erroneously been assigned to the affiliation "62". The affiliation 62 belongs to the author Graham Casey.

Published
2019
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6. Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer.

Author

Bien SA, Su YR, Conti DV, Harrison TA, Qu C, Guo X, Lu Y, Albanes D, Auer PL, Banbury BL, Berndt SI, Bézieau S, Brenner H, Buchanan DD, Caan BJ, Campbell PT, Carlson CS, Chan AT, Chang-Claude J, Chen S, Connolly CM, Easton DF, Feskens EJM, Gallinger S, Giles GG, Gunter MJ, Hampe J, Huyghe JR, Hoffmeister M, Hudson TJ, Jacobs EJ, Jenkins MA, Kampman E, Kang HM, Kühn T, Küry S, Lejbkowicz F, Le Marchand L, Milne RL, Li L, Li CI, Lindblom A, Lindor NM, Martín V, McNeil CE, Melas M, Moreno V, Newcomb PA, Offit K, Pharaoh PDP, Potter JD, Qu C, Riboli E, Rennert G, Sala N, Schafmayer C, Scacheri PC, Schmit SL, Severi G, Slattery ML, Smith JD, Trichopoulou A, Tumino R, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Weinstein SJ, White E, Wolk A, Woods MO, Wu AH, Abecasis GR, Casey G, Nickerson DA, Gruber SB, Hsu L, Zheng W, and Peters U

Subjects
Case-Control Studies, Colorectal Neoplasms epidemiology, Gene Expression, Gene Expression Regulation, Neoplastic, Gene Frequency, Humans, Predictive Value of Tests, Prognosis, Risk Factors, Colorectal Neoplasms diagnosis, Colorectal Neoplasms genetics, Genetic Predisposition to Disease, Genome-Wide Association Study statistics & numerical data, Polymorphism, Single Nucleotide
Abstract

Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n = 169) and whole blood (n = 922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR ≤ 0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P = 2.2 × 10 - 4 , replication P = 0.01), and PYGL (discovery P = 2.3 × 10 - 4 , replication P = 6.7 × 10 - 4 ). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight into, risk loci.

Published
2019
Full Text
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7. Author Correction: Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia.

Author

Vijayakrishnan J, Studd J, Broderick P, Kinnersley B, Holroyd A, Law PJ, Kumar R, Allan JM, Harrison CJ, Moorman AV, Vora A, Roman E, Rachakonda S, Kinsey SE, Sheridan E, Thompson PD, Irving JA, Koehler R, Hoffmann P, Nöthen MM, Heilmann-Heimbach S, Jöckel KH, Easton DF, Pharaoh PDP, Dunning AM, Peto J, Canzian F, Swerdlow A, Eeles RA, Kote-Jarai Z, Muir K, Pashayan N, Greaves M, Zimmerman M, Bartram CR, Schrappe M, Stanulla M, Hemminki K, and Houlston RS

Abstract

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Published
2019
Full Text
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8. Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia.

Author

Vijayakrishnan J, Studd J, Broderick P, Kinnersley B, Holroyd A, Law PJ, Kumar R, Allan JM, Harrison CJ, Moorman AV, Vora A, Roman E, Rachakonda S, Kinsey SE, Sheridan E, Thompson PD, Irving JA, Koehler R, Hoffmann P, Nöthen MM, Heilmann-Heimbach S, Jöckel KH, Easton DF, Pharaoh PDP, Dunning AM, Peto J, Canzian F, Swerdlow A, Eeles RA, Kote-Jarai Z, Muir K, Pashayan N, Greaves M, Zimmerman M, Bartram CR, Schrappe M, Stanulla M, Hemminki K, and Houlston RS

Subjects
Child, Child, Preschool, Core Binding Factor Alpha 2 Subunit genetics, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Glycosyltransferases genetics, HLA Antigens genetics, Humans, Male, Oncogene Proteins, Fusion genetics, Polymorphism, Single Nucleotide, Precursor B-Cell Lymphoblastic Leukemia-Lymphoma immunology, Prognosis, Risk Factors, Precursor B-Cell Lymphoblastic Leukemia-Lymphoma genetics
Abstract

Genome-wide association studies (GWAS) have advanced our understanding of susceptibility to B-cell precursor acute lymphoblastic leukemia (BCP-ALL); however, much of the heritable risk remains unidentified. Here, we perform a GWAS and conduct a meta-analysis with two existing GWAS, totaling 2442 cases and 14,609 controls. We identify risk loci for BCP-ALL at 8q24.21 (rs28665337, P = 3.86 × 10 -9 , odds ratio (OR) = 1.34) and for ETV6-RUNX1 fusion-positive BCP-ALL at 2q22.3 (rs17481869, P = 3.20 × 10 -8 , OR = 2.14). Our findings provide further insights into genetic susceptibility to ALL and its biology.

Published
2018
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9. Accuracy of the online prognostication tools PREDICT and Adjuvant! for early-stage breast cancer patients younger than 50 years.

Author

Engelhardt EG, van den Broek AJ, Linn SC, Wishart GC, Rutgers EJT, van de Velde AO, Smit VTHBM, Voogd AC, Siesling S, Brinkhuis M, Seynaeve C, Westenend PJ, Stiggelbout AM, Tollenaar RAEM, van Leeuwen FE, van 't Veer LJ, Ravdin PM, Pharaoh PDP, and Schmidt MK

Subjects
Adult, Breast Neoplasms mortality, Chemotherapy, Adjuvant methods, Chemotherapy, Adjuvant mortality, Female, Humans, Middle Aged, Netherlands epidemiology, Prognosis, Receptors, Estrogen metabolism, Receptors, Progesterone metabolism, Sensitivity and Specificity, Severity of Illness Index, Young Adult, Breast Neoplasms drug therapy
Abstract

Importance: Online prognostication tools such as PREDICT and Adjuvant! are increasingly used in clinical practice by oncologists to inform patients and guide treatment decisions about adjuvant systemic therapy. However, their validity for young breast cancer patients is debated., Objective: To assess first, the prognostic accuracy of PREDICT's and Adjuvant! 10-year all-cause mortality, and second, its breast cancer-specific mortality estimates, in a large cohort of breast cancer patients diagnosed <50 years., Design: Hospital-based cohort., Setting: General and cancer hospitals., Participants: A consecutive series of 2710 patients without a prior history of cancer, diagnosed between 1990 and 2000 with unilateral stage I-III breast cancer aged <50 years., Main Outcome Measures: Calibration and discriminatory accuracy, measured with C-statistics, of estimated 10-year all-cause and breast cancer-specific mortality., Results: Overall, PREDICT's calibration for all-cause mortality was good (predicted versus observed) mean difference : -1.1% (95%CI: -3.2%-0.9%; P = 0.28). PREDICT tended to underestimate all-cause mortality in good prognosis subgroups (range mean difference : -2.9% to -4.8%), overestimated all-cause mortality in poor prognosis subgroups (range mean difference : 2.6%-9.4%) and underestimated survival in patients < 35 by -6.6%. Overall, PREDICT overestimated breast cancer-specific mortality by 3.2% (95%CI: 0.8%-5.6%; P = 0.007); and also overestimated it seemingly indiscriminately in numerous subgroups (range mean difference : 3.2%-14.1%). Calibration was poor in the cohort of patients with the lowest and those with the highest mortality probabilities. Discriminatory accuracy was moderate-to-good for all-cause mortality in PREDICT (0.71 [95%CI: 0.68 to 0.73]), and the results were similar for breast cancer-specific mortality. Adjuvant!'s calibration and discriminatory accuracy for both all-cause and breast cancer-specific mortality were in line with PREDICT's findings., Conclusions: Although imprecise at the extremes, PREDICT's estimates of 10-year all-cause mortality seem reasonably sound for breast cancer patients <50 years; Adjuvant! findings were similar. Prognostication tools should be used with caution due to the intrinsic variability of their estimates, and because the threshold to discuss adjuvant systemic treatment is low. Thus, seemingly insignificant mortality overestimations or underestimations of a few percentages can significantly impact treatment decision-making., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Published
2017
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