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The effect of sample size on polygenic hazard models for prostate cancer.
Karunamuni, Roshan A; Huynh-Le, Minh-Phuong; Fan, Chun C; Eeles, Rosalind A; Easton, Douglas F; Kote-Jarai, ZSofia; Amin Al Olama, Ali; Benlloch Garcia, Sara; Muir, Kenneth; Gronberg, Henrik; Wiklund, Fredrik; Aly, Markus; Schleutker, Johanna; Sipeky, Csilla; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokolorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Schöttker, Ben; Holleczek, Bernd; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula.
Affiliation
  • Karunamuni RA; Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA. rakarunamuni@health.ucsd.edu.
  • Huynh-Le MP; Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
  • Fan CC; Healthlytix, 4747 Executive Dr. Suite 820, San Diego, CA, USA.
  • Eeles RA; The Institute of Cancer Research, London, SM2 5NG, UK.
  • Easton DF; Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK.
  • Kote-Jarai Z; Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK.
  • Amin Al Olama A; The Institute of Cancer Research, London, SM2 5NG, UK.
  • Benlloch Garcia S; Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK.
  • Muir K; Department of Clinical Neurosciences, Stroke Research Group, R3, Box 83, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 0QQ, UK.
  • Gronberg H; Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK.
  • Wiklund F; Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
  • Aly M; Warwick Medical School, University of Warwick, Coventry, UK.
  • Schleutker J; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden.
  • Sipeky C; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden.
  • Tammela TLJ; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden.
  • Nordestgaard BG; Department of Molecular Medicine and Surgery, Karolinska Institute, SE-171 77, Stockholm, Sweden.
  • Key TJ; Department of Urology, Karolinska University Hospital, Stockholm, Sweden.
  • Travis RC; Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20014, Turku, Finland.
  • Neal DE; Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, PO Box 52, 20521, Turku, Finland.
  • Donovan JL; Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20014, Turku, Finland.
  • Hamdy FC; Faculty of Medicine and Health Technology, Prostate Cancer Research Center, Tampere University, FI-33014, Tampere, Finland.
  • Pharoah P; Department of Urology, Tampere University Hospital, Tampere, Finland.
  • Pashayan N; Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
  • Khaw KT; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, 2200, Copenhagen, Denmark.
  • Thibodeau SN; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.
  • McDonnell SK; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.
  • Schaid DJ; Nuffield Department of Surgical Sciences, University of Oxford, Room 6603, Level 6, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, UK.
  • Maier C; Department of Oncology, Box 279, Addenbrooke's Hospital, University of Cambridge, Hills Road, Cambridge, CB2 0QQ, UK.
  • Vogel W; Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK.
  • Luedeke M; School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.
  • Herkommer K; Nuffield Department of Surgical Sciences, University of Oxford, Oxford, OX1 2JD, UK.
  • Kibel AS; Faculty of Medical Science, John Radcliffe Hospital, University of Oxford, Oxford, UK.
  • Cybulski C; Department of Oncology, Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK.
  • Wokolorczyk D; Department of Oncology, Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK.
  • Kluzniak W; Department of Applied Health Research, University College London, London, UK.
  • Cannon-Albright L; Department of Applied Health Research, University College London, London, WC1E 7HB, UK.
  • Brenner H; Clinical Gerontology Unit, University of Cambridge, Cambridge, CB2 2QQ, UK.
  • Schöttker B; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA.
  • Holleczek B; Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, 55905, USA.
  • Park JY; Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, 55905, USA.
  • Sellers TA; Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany.
  • Lin HY; Institute for Human Genetics, University Hospital Ulm, 89075, Ulm, Germany.
  • Slavov C; Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany.
  • Kaneva R; Department of Urology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany.
  • Mitev V; Division of Urologic Surgery, Brigham and Womens Hospital, 75 Francis Street, Boston, MA, 02115, USA.
  • Batra J; Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland.
  • Clements JA; Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland.
  • Spurdle A; Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland.
  • Teixeira MR; George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, 84148, USA.
  • Paulo P; Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany.
Eur J Hum Genet ; 28(10): 1467-1475, 2020 10.
Article in En | MEDLINE | ID: mdl-32514134
We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Multifactorial Inheritance / Polymorphism, Single Nucleotide / Genome-Wide Association Study Type of study: Prognostic_studies Limits: Humans / Male Language: En Journal: Eur J Hum Genet Journal subject: GENETICA MEDICA Year: 2020 Document type: Article Affiliation country: United States Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Multifactorial Inheritance / Polymorphism, Single Nucleotide / Genome-Wide Association Study Type of study: Prognostic_studies Limits: Humans / Male Language: En Journal: Eur J Hum Genet Journal subject: GENETICA MEDICA Year: 2020 Document type: Article Affiliation country: United States Country of publication: United kingdom