Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Adult Aged Biomarkers, Tumor / genetics Follow-Up Studies Humans Male Middle Aged Models, Statistical Polymorphism, Single Nucleotide Predictive Value of Tests Prognosis Prostatic Neoplasms / epidemiology Risk Assessment / methods Risk Factors

Journal

Prostate cancer and prostatic diseases
ISSN: 1476-5608
Titre abrégé: Prostate Cancer Prostatic Dis
Pays: England
ID NLM: 9815755

Informations de publication

Date de publication:
06 2021
Historique:
received: 15 09 2020
accepted: 04 12 2020
revised: 10 11 2020
pubmed: 10 1 2021
medline: 19 1 2022
entrez: 9 1 2021
Statut: ppublish

Résumé

Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46). 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy. 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer. Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Sections du résumé

BACKGROUND
Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).
MATERIALS AND METHOD
180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS
166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS
Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Identifiants

DOI: 10.1038/s41391-020-00311-2 PMID: 33420416 PMC: PMC8157993
pubmed: 33420416
doi: 10.1038/s41391-020-00311-2
pii: 10.1038/s41391-020-00311-2
pmc: PMC8157993
mid: NIHMS1700848
doi:

Substances chimiques

Biomarkers, Tumor 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

532-541

Subventions

Organisme : NCI NIH HHS
ID : U10 CA037429
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA182883
Pays : United States
Organisme : NCI NIH HHS
ID : UG1 CA189974
Pays : United States
Organisme : NIBIB NIH HHS
ID : K08 EB026503
Pays : United States

Références

Seibert TM, Fan CC, Wang Y, Zuber V, Karunamuni R, Parsons JK, et al. Polygenic hazard score to guide screening for aggressive prostate cancer: Development and validation in large scale cohorts. BMJ. 2018;360:1–7.
Huynh-Le MP, Myklebust TÅ, Feng CH, Karunamuni R, Johannesen TB, Dale AM, et al. Age dependence of modern clinical risk groups for localized prostate cancer—a population-based study. Cancer. 2020;126:1691–9.
doi: 10.1002/cncr.32702
Pashayan N, Duffy SW, Chowdhury S, Dent T, Burton H, Neal DE, et al. Polygenic susceptibility to prostate and breast cancer: Implications for personalised screening. Br J Cancer. 2011;104:1656–63.
doi: 10.1038/bjc.2011.118
Witte JS. Personalized prostate cancer screening: improving PSA tests with genomic information. Sci Transl Med. 2010;2:1–5.
doi: 10.1126/scitranslmed.3001861
Chen H, Liu X, Brendler CB, Ankerst DP, Leach RJ, Goodman PJ, et al. Adding genetic risk score to family history identifies twice as many high-risk men for prostate cancer: Results from the prostate cancer prevention trial. Prostate. 2016;76:1120–9.
doi: 10.1002/pros.23200
Huynh-Le M-P, Fan CC, Karunamuni R, Thompson WK, Martinez ME, Eeles RA, et al. Polygenic hazard score is associated with prostate cancer in multi-ethnic populations. medRxiv. 2020:1–34.
Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al. Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci. Nat Genet. 2018;50:928–36.
doi: 10.1038/s41588-018-0142-8
Kote-Jarai Z, Easton DF, Stanford JL, Ostrander EA, Schleutker J, Ingles SA, et al. Multiple novel prostate cancer predisposition loci confirmed by an international study: The PRACTICAL consortium. Cancer Epidemiol Biomark Prev. 2008;17:2052–61.
doi: 10.1158/1055-9965.EPI-08-0317
Eeles RA, Olama AAAl, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M, et al. Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet. 2013;45:385–91.
doi: 10.1038/ng.2560
Tibshiranit BR. Regression shrinkage and selection via the Lasso. J R Stat Soc B. 1996:267–88.
Tibshirani R. The lasso method for variable selection in the cox model. Stat Med. 1997;16:385–95.
doi: 10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am J Hum Genet. 2019;104:21–34.
doi: 10.1016/j.ajhg.2018.11.002
Amos CI, Dennis J, Wang Z, Byun J, Schumacher FR, Gayther SA, et al. The oncoarray consortium: a network for understanding the genetic architecture of common cancers. Cancer Epidemiol Biomark Prev. 2017;26:126–35.
doi: 10.1158/1055-9965.EPI-16-0106
Eeles R. Prostate cancer genome-wide association study from 89,000 men using the OncoArray chip to identify novel prostate cancer susceptibility loci. J Clin Oncol. 2016;34:1525.
doi: 10.1200/JCO.2016.34.15_suppl.1525
Karunamuni RA, Huynh-Le MP, Fan CC, Eeles RA, Easton DF, Kote-Jarai ZsS, et al. The effect of sample size on polygenic hazard models for prostate cancer. Eur J Hum Genet. 2020. https://doi.org/10.1038/s41431-020-0664-2 .
Li Y, Byun J, Cai G, Xiao X, Han Y, Cornelis O, et al. FastPop: a rapid principal component derived method to infer intercontinental ancestry using genetic data. BMC Bioinforma. 2016;17:1–8.
doi: 10.1186/s12859-016-0965-1
Heller G. A measure of explained risk in the proportional hazards model. Biostatistics. 2012;13:315–25.
doi: 10.1093/biostatistics/kxr047
NCCN Clinical Practice Guidelines in Oncology. Prostate Cancer. Version 1.2019.
Therneau TM, Li H. Computing the Cox model for case cohort designs. Lifetime Data Anal. 1999;5:99–112.
doi: 10.1023/A:1009691327335
Huynh-Le M-P, Fan CC, Karunamuni R, Walsh EI, Turner EL, Lane JA, et al. A genetic risk score to personalize prostate cancer screening, applied to population data. Cancer Epidemiol Biomarkers Prev. 2020;29:1731–8.
doi: 10.1158/1055-9965.EPI-19-1527
Prostate Cancer Incidence Statistics Cancer Research UK. https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/prostate-cancer/incidence#heading-one . Accessed 23 Jul 2020.
Martin RM, Donovan JL, Turner EL, Metcalfe C, Young GJ, Walsh EI, et al. Effect of a low-intensity PSA-based screening intervention on prostate cancer mortality: the CAP randomized clinical trial. J Am Med Assoc. 2018;319:883–95.
doi: 10.1001/jama.2018.0154
Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, et al. ClinVar: Public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014;42:980–85.
doi: 10.1093/nar/gkt1113
Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. 2018;19:581–90.
doi: 10.1038/s41576-018-0018-x
Pashayan N, Duffy SW, Neal DE, Hamdy FC, Donovan JL, Martin RM, et al. Implications of polygenic risk-stratified screening for prostate cancer on overdiagnosis. Genet Med. 2015;17:789–95.
doi: 10.1038/gim.2014.192
Pashayan N, Pharoah PDP, Schleutker J, Talala K, Tammela TLJ, Määttänen L, et al. Reducing overdiagnosis by polygenic risk-stratified screening: findings from the Finnish section of the ERSPC. Br J Cancer. 2015;113:1086–93.
doi: 10.1038/bjc.2015.289
Wang TJ, Larson MG, Levy D, Benjamin EJ, Leip EP, Omland T, et al. Plasma natriuretic peptide levels and the risk of cardiovascular events and death. N Engl J Med. 2004;350:655–63.
doi: 10.1056/NEJMoa031994
Yang X, Leslie G, Gentry-Maharaj A, Ryan A, Intermaggio M, Lee A, et al. Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study. J Med Genet. 2018;55:546–54.
doi: 10.1136/jmedgenet-2018-105313
Yeh HC, Duncan BB, Schmidt MI, Wang NY, Brancati FL. Smoking, smoking cessation, and risk for type 2 diabetes mellitus: a cohort study. Ann Intern Med. 2010;152:10–7.
doi: 10.7326/0003-4819-152-1-201001050-00005
Ren S, Xu J, Zhou T, Jiang H, Chen H, Liu F, et al. Plateau effect of prostate cancer risk-associated SNPs in discriminating prostate biopsy outcomes. Prostate. 2013;73:1824–35.
doi: 10.1002/pros.22721
Forgetta V, Keller-baruch J, Forest M, Durand A, Bhatnagar S, Kemp JP, et al. Development of a polygenic risk score to improve screening for fracture risk: a genetic risk prediction study. PLoS Med. 2020;17:1–19.
doi: 10.1371/journal.pmed.1003152
Chen T-H, Chatterjee N, Landi MT, Shi J. A penalized regression framework for building polygenic risk models based on summary statistics from genome-wide association studies and incorporating external information. J Am Stat Assoc. 2020;1459:1–19.
Karunamuni R, Huynh-Le M-P, Fan CC, Thompson W, Eeles RA, Kote-Jarai Z, et al. African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer. International Journal of Cancer. 2021;148:99–105.
doi: 10.1002/ijc.33282
McNeish DM. Using Lasso for predictor selection and to assuage overfitting: a method long overlooked in behavioral sciences. Multivar Behav Res. 2015;50:471–84.
doi: 10.1080/00273171.2015.1036965

Auteurs

Roshan A Karunamuni (RA)

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA. rakarunamuni@health.ucsd.edu.
ORCID: 0000-0001-8723-8123

Minh-Phuong Huynh-Le (MP)

Radiation Oncology, George Washington University, Washington, DC, USA.
ORCID: 0000-0002-5025-4709

Chun C Fan (CC)

Center for Human Development, University of California San Diego, La Jolla, CA, USA.

Wesley Thompson (W)

Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA.

Rosalind A Eeles (RA)

The Institute of Cancer Research, London, SM2 5NG, UK.
Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK.
ORCID: 0000-0002-3698-6241

Zsofia Kote-Jarai (Z)

The Institute of Cancer Research, London, SM2 5NG, UK.

Kenneth Muir (K)

Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.
ORCID: 0000-0001-6429-988X

Artitaya Lophatananon (A)

Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.

Johanna Schleutker (J)

Institute of Biomedicine, University of Turku, Turku, Finland.
Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, PO Box 52, 20521, Turku, Finland.
ORCID: 0000-0002-1863-0305

Nora Pashayan (N)

Department of Applied Health Research, University College London, London, WC1E 7HB, UK.
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Worts Causeway, Cambridge, CB1 8RN, UK.

Jyotsna Batra (J)

Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, 4059, Australia.
Translational Research Institute, Brisbane, QLD, 4102, Australia.
ORCID: 0000-0003-4646-6247

Henrik Grönberg (H)

Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden.

Eleanor I Walsh (EI)

Bristol Medical School, Department of Population Health Sciences, University of Bristol, Bristol, UK.

Emma L Turner (EL)

Bristol Medical School, Department of Population Health Sciences, University of Bristol, Bristol, UK.

Athene Lane (A)

Bristol Medical School, Department of Population Health Sciences, University of Bristol, Bristol, UK.
MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Richard M Martin (RM)

Bristol Medical School, Department of Population Health Sciences, University of Bristol, Bristol, UK.
MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK.
ORCID: 0000-0002-7992-7719

David E Neal (DE)

Nuffield Department of Surgical Sciences, University of Oxford, Room 6603, Level 6, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, UK.
Department of Oncology, University of Cambridge, Box 279, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK.
Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK.

Jenny L Donovan (JL)

School of Social and Community Medicine, University of Bristol, Bristol, UK.

Freddie C Hamdy (FC)

Nuffield Department of Surgical Sciences, University of Oxford, Room 6603, Level 6, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, UK.
Faculty of Medical Science, University of Oxford, John Radcliffe Hospital, Oxford, UK.

Børge G Nordestgaard (BG)

Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, 2200, Copenhagen, Denmark.

Catherine M Tangen (CM)

SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Robert J MacInnis (RJ)

Cancer Epidemiology Division, Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC, 3004, Australia.
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Grattan Street, Parkville, VIC, 3010, Australia.

Alicja Wolk (A)

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, SE-171 77, Stockholm, Sweden.
Department of Surgical Sciences, Uppsala University, 75185, Uppsala, Sweden.

Demetrius Albanes (D)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.

Christopher A Haiman (CA)

Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90015, USA.

Ruth C Travis (RC)

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.

Janet L Stanford (JL)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109-1024, USA.
Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA.

Lorelei A Mucci (LA)

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.

Catharine M L West (CML)

Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, M13 9PL, UK.

Sune F Nielsen (SF)

Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, 2200, Copenhagen, Denmark.

Adam S Kibel (AS)

Division of Urologic Surgery, Brigham and Womens Hospital, 75 Francis Street, Boston, MA, 02115, USA.

Fredrik Wiklund (F)

Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden.
ORCID: 0000-0002-4623-0544

Olivier Cussenot (O)

Sorbonne Universite, GRC n°5, AP-HP, Tenon Hospital, 4 rue de la Chine, F-75020, Paris, France.
CeRePP, Tenon Hospital, F-75020, Paris, France.

Sonja I Berndt (SI)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.

Stella Koutros (S)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.

Karina Dalsgaard Sørensen (KD)

Department of Molecular Medicine, Aarhus University Hospital, Palle Juul-Jensen Boulevard 99, 8200, Aarhus, Denmark.
Department of Clinical Medicine, Aarhus University, DK-8200, Aarhus, Denmark.
ORCID: 0000-0002-4902-5490

Cezary Cybulski (C)

International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, 70-115, Szczecin, Poland.

Eli Marie Grindedal (EM)

Department of Medical Genetics, Oslo University Hospital, 0424, Oslo, Norway.

Jong Y Park (JY)

Department of Cancer Epidemiology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
ORCID: 0000-0002-6384-6447

Sue A Ingles (SA)

Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90015, USA.

Christiane Maier (C)

Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany.

Robert J Hamilton (RJ)

Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, ON, M5G 2M9, Canada.
Dept. of Surgery (Urology), University of Toronto, Toronto, ON, Canada.

Barry S Rosenstein (BS)

Department of Radiation Oncology and Department of Genetics and Genomic Sciences, Box 1236, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-5674, USA.

Ana Vega (A)

Fundación Pública Galega Medicina Xenómica, Santiago de Compostela, 15706, Spain.
Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, 15706, Spain.
Centro de Investigación en Red de Enfermedades Raras (CIBERER), Santiago De Compostela, Spain.

Manolis Kogevinas (M)

ISGlobal, Barcelona, Spain.
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.

Kathryn L Penney (KL)

Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, 02184, USA.

Manuel R Teixeira (MR)

Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), 4200-072, Porto, Portugal.
Biomedical Sciences Institute (ICBAS), University of Porto, 4050-313, Porto, Portugal.
Cancer Genetics Group, IPO-Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO-Porto), 4200-072, Porto, Portugal.
ORCID: 0000-0002-4896-5982

Hermann Brenner (H)

Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany.
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany.
Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, 69120, Heidelberg, Germany.

Esther M John (EM)

Departments of Epidemiology & Population Health and of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94304, USA.

Radka Kaneva (R)

Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, 2 Zdrave Str., 1431, Sofia, Bulgaria.

Christopher J Logothetis (CJ)

The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, 1515 Holcombe Blvd., Houston, TX, 77030, USA.

Susan L Neuhausen (SL)

Department of Population Sciences, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.

Azad Razack (A)

Department of Surgery, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia.

Lisa F Newcomb (LF)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109-1024, USA.
Department of Urology, University of Washington, 1959 NE Pacific Street, Box 356510, Seattle, WA, 98195, USA.

Marija Gamulin (M)

Division of Medical Oncology, Urogenital Unit, Department of Oncology, University Hospital Centre Zagreb, University of Zagreb, School of Medicine, 10000, Zagreb, Croatia.
ORCID: 0000-0003-2431-7910

Nawaid Usmani (N)

Department of Oncology, Cross Cancer Institute, University of Alberta, 11560 University Avenue, Edmonton, AB, T6G 1Z2, Canada.
Division of Radiation Oncology, Cross Cancer Institute, 11560 University Avenue, Edmonton, AB, T6G 1Z2, Canada.

Frank Claessens (F)

Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, KU, Leuven, BE-3000, Belgium.

Manuela Gago-Dominguez (M)

Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, Servicio Galego de Saúde, SERGAS, 15706, Santiago de Compostela, Spain.
University of California San Diego, Moores Cancer Center, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, 92093-0012, USA.

Paul A Townsend (PA)

Division of Cancer Sciences, Manchester Cancer Research Centre, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Health Innovation Manchester, Univeristy of Manchester, M13 9WL, Manchester, UK.

Monique J Roobol (MJ)

Department of Urology, Erasmus University Medical Center, 3015 CE, Rotterdam, The Netherlands.
ORCID: 0000-0001-6967-1708

Wei Zheng (W)

Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, 37232, USA.

Ian G Mills (IG)

Center for Cancer Research and Cell Biology, Queen's University of Belfast, Belfast, UK.

Ole A Andreassen (OA)

NORMENT, KG Jebsen Centre, Oslo University Hospital and University of Oslo, Oslo, Norway.
ORCID: 0000-0002-4461-3568

Anders M Dale (AM)

Department of Radiology, University of California San Diego, La Jolla, CA, USA.

Tyler M Seibert (TM)

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA. tseibert@ucsd.edu.
Department of Radiology, University of California San Diego, La Jolla, CA, USA. tseibert@ucsd.edu.
Department of Bioengineering, University of California San Diego, La Jolla, CA, USA. tseibert@ucsd.edu.
ORCID: 0000-0002-4089-7399

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Effectiveness of Virtual Yoga for Chronic Low Back Pain: A Randomized Clinical Trial.

Hallie Tankha, Devyn Gaskins, Amanda Shallcross et al.
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Facteurs biologiques › Marqueurs biologiques › Marqueurs biologiques tumoraux › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études de suivi › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Adulte d'âge moyen › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Modèles statistiques › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Polymorphisme génétique › Polymorphisme de nucléotide simple › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Méthodologie en recherche épidémiologique › Valeur prédictive des tests › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Diagnostic › Pronostic › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Maladies urogénitales › Tumeurs de l'appareil urogénital › Tumeurs de l'appareil génital mâle › Tumeurs de la prostate › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Risque › Appréciation des risques › Additional SNPs improve risk stratification of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Risque › Facteurs de risque › Additional SNPs improve risk stratification of...