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Medicine

A Prospective study of Outcomes in Sporadic versus Hereditary breast cancer

Study purpose

The primary aims of the POSH study are to determine whether:

Study design

The Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) is a large, prospective cohort study. This design was chosen to minimise ascertainment bias, facilitate identification of controls that could be matched for all potential confounding factors and ensure accurate contemporaneous data collection.

Inclusion/exclusion criteria

All women diagnosed with invasive breast cancer aged 40 years or younger during the recruitment period in each centre were eligible to participate. In addition women aged 41-50 who had a known BRCA1 or BRCA2 gene mutation and were diagnosed with invasive breast cancer within the study period, were also eligible. This population was specifically chosen to maximise the number of BRCA1 and BRCA2 mutation carriers in the cohort. Women were excluded if they had a previous invasive malignancy (with the exception of non-melanomatous skin cancer), would not be available for follow up or who refused consent to retain diagnostic and follow up data.

Ethics approval

This study received approval from the South and West Multi-centre Research Ethics Committee (MREC 00/6/69)

Recruitment complete

We completed recruitment of 3000 cases by 31st December 2008 and continue follow up annually as funding allows.

How We Use Your Data

Data for this study is held securely by study staff who work at University of Southampton and University Hospital Southampton NHS Foundation Trust. During the study we have collected some data from your study team about you, which when combined with other data, could potentially identify you.

Of course, all of the data submitted to us is treated confidentially. Any identifiable information will strictly not be shared with anyone outside the trial team, aside from NHS Digital. When you kindly consented to being involved in this research, this organisation was called the NHS Information Centre, they have since changed their name. The study team share your NHS number with NHS Digital and they use it to link to health and mortality datasets that they hold in order to provide us with information about your current health status.

NHS Digital link data they hold with data from the Office of National Statistics (for patients in England and Wales) and from the National Records of Scotland (for patients from Scotland), regarding any patients who have sadly died. The study team will then be informed and given the date and cause of that death. Linking with NHS Digital enables us to get information about participants, even if your treating hospital has lost contact with you.

Your participation is voluntary and we very much hope that you will continue to participate in our research and let us use your data. However, you are free to withdraw at any time and without giving a reason. A decision to withdraw at any time will not affect the standard of care you receive. There are several options if you choose to withdraw:

  1. Complete withdrawal: We will attempt no further contact. No further visits will be scheduled and no additional data will be collected about you from the point of your withdrawal. Note, it will not be possible to remove data that we have previously collected and processed from our analyses.
  2. Partial withdrawal: The information you have given us up to today will be used in our analysis but there will be no more visits and only information from your patient notes in hospital will be collected going forward.

As the study already has had substantial results and publications we will not be able to destroy any data we hold about you up until your withdrawal. However, your data has been de-identified so you can be assured that you will not be personally identified in any reports, presentations or publications. If you would like to obtain a copy of the published results, please ask your doctor.

If you wish to either withdraw completely or partially, or have any other enquiries relating to participation, please contact Southampton Clinical Trials Unit on ctu@soton.ac.uk or 023 8120 5154.

Publications

Eccles D, Gerty S, Simmonds P, Hammond V, Ennis S, Altman DG, et al. Prospective study of outcomes in sporadic versus hereditary breast cancer (POSH): Study protocol. BMC Cancer.

Tapper W, Hammond V, Gerty S, Ennis S, Simmonds P, Collins A, et al. The influence of genetic variation in 30 selected genes on the clinical characteristics of early onset breast cancer. Breast Cancer Res. 2008;10(6).144.

Shaw EC, Hanby AM, Wheeler K, Shaaban AM, Poller D, Barton S, et al. Observer agreement comparing the use of virtual slides with glass slides in the pathology review component of the POSH breast cancer cohort study. J Clin Pathol. 2012;65(5):403-8.

Copson E, Eccles B, Maishman T, Gerty S, Stanton L, Cutress RI, et al. Prospective observational study of breast cancer treatment outcomes for UK women aged 18-40 years at diagnosis: The POSH study. J Natl Cancer Inst. 2013;105(13):978-88.

Rafiq S, Tapper W, Collins A, Khan S, Politopoulos I, Gerty S, et al. Identification of inherited genetic variations influencing prognosis in early-onset breast cancer. CANCER RES. 2013;73(6):1883-91.

Upstill-Goddard R, Eccles D, Ennis S, Rafiq S, Tapper W, Fliege J, et al. Support Vector Machine Classifier for Estrogen Receptor Positive and Negative Early-Onset Breast Cancer. PLoS ONE. 2013;8(7)

Copson E, Maishman T, Gerty S, Eccles B, Stanton L, Cutress RI, et al. Ethnicity and outcome of young breast cancer patients in the United Kingdom: The POSH study. BR J CANCER. 2014;110(1):230-41.

Rafiq S, Khan S, Tapper W, Collins A, Upstill-Goddard R, Gerty S, et al. A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. PLoS ONE. 2014;9(12).

Copson ER, Cutress RI, Maishman T, Eccles BK, Gerty S, Stanton L, et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26(1):101-12.

Couch FJ, Hart SN, Sharma P, Toland AE, Wang X, Miron P, et al. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer. J Clin Oncol. 2015;33(4):304-11.

Eccles BK, Copson ER, Cutress RI, Maishman T, Altman DG, Simmonds P, et al. Family history and outcome of young patients with breast cancer in the UK (POSH study). Br J Surg. 2015;102(8):924-35.

Fagerholm R, Schmidt MK, Khan S, Rafiq S, Tapper W, Aittomaki K, et al. The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients. Oncotarget. 2015;6(10):7390-407.

Khan S, Fagerholm R, Rafiq S, Tapper W, Aittomaki K, Liu J, et al. Polymorphism at 19q13.41 Predicts Breast Cancer Survival Specifically after Endocrine Therapy. Clin Cancer Res. 2015

Smyth C, Spakulova I, Cotton-Barratt O, Rafiq S, Tapper W, Upstill-Goddard R, et al. Quantifying the cumulative effect of low-penetrance genetic variants on breast cancer risk. Mol Genet Genomic Med. 2015;3(3):182-8.

Maishman T, Copson E, Stanton L, Gerty S, Dicks E, Durcan L, et al. An evaluation of the prognostic model PREDICT using the POSH cohort of women aged 40 years at breast cancer diagnosis. Br J Cancer. 2015;112(6):983-91.

Saladores P, Murdter T, Eccles D, Chowbay B, Zgheib NK, Winter S, et al. Tamoxifen metabolism predicts drug concentrations and outcome in premenopausal patients with early breast cancer. Pharmacogenomics J. 2015;15(1):84-94.

Eccles DM, Li N, Handwerker R, Maishman T, Copson ER, Durcan LT, et al. Genetic testing in a cohort of young patients with HER2-amplified breast cancer. Annals of Oncology 2016;27(3):467-73.

Maishman T, Cutress RI, Hernandez A, Gerty S, Copson ER, Durcan L, et al. Local Recurrence and Breast Oncological Surgery in Young Women With Breast Cancer: The POSH Observational Cohort Study. Annals of Surgery 2017: 266 ( 1): 165–172

McGeehan RE, Cockram LA, Littlewood DTJ, Keatley K, Eccles DM, An Q. Deep sequencing reveals the mitochondrial DNA variation landscapes of breast-to-brain metastasis blood samples. Mitochondrial DNA Part A. 2017:1-11.

Kadalayil L, Khan S, Nevanlinna H, Fasching PA, Couch FJ, Hopper JL, et al. Germline variation in ADAMTSL1 is associated with prognosis following breast cancer treatment in young women. Nat Commun. 2017;8(1):1632.

Copson ER, Maishman TC, Tapper WJ, Cutress RI, Greville-Heygate S, Altman DG, et al…..Eccles DM. Germline BRCA mutation and outcome in young-onset breast cancer (POSH): a prospective cohort study. Lancet Oncol. 2018;19(2):169-80.

Eccles DM, Copson ER. Genetic testing for young women with breast cancer–Authors' reply. Lancet Oncol. 2018;19(4):e183.

Zeidan B, Manousopoulou A, Garay-Baquero DJ, White CH, Larkin SE, Potter KN, et al. Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study. Breast Cancer Res. 2018;20(1):19.

Khan S, Fagerholm R, Kadalayil L, Tapper W, Aittomäki K, Liu J, et al. Meta-analysis of three genome-wide association studies identifies two loci that predict survival and treatment outcome in breast cancer. Oncotarget. 2018;9(3):4249.

Additional publications including data from the POSH study

Eccles D, Tapper W. The influence of common polymorphisms on breast cancer. Cancer Treat Res. 2010;155:15-32.

Wilson JRF, Bateman AC, Hanson H, An Q, Evans G, Rahman N, et al. A novel HER2-positive breast cancer phenotype arising from germline TP53 mutations. J Med Genet. 2010;47(11):771-4.

Evans DG, Howell A, Ward D, Lalloo F, Jones JL, Eccles DM. Prevalence of BRCA1 and BRCA2 mutations in triple negative breast cancer. J Med Genet. 2011;48(8):520-2.

Stevens KN, Vachon CM, Lee AM, Slager S, Lesnick T, Olswold C, et al. Common breast cancer susceptibility loci are associated with triple-negative breast cancer. CANCER RES. 2011;71(19):6240-9.

Haiman CA, Chen GK, Vachon CM, Canzian F, Dunning A, Millikan RC, et al. A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor negative breast cancer. Nat Genet. 2011;43(12):1210-4.

Yang XR, Chang-Claude J, Goode EL, Couch FJ, Nevanlinna H, Milne RL, et al. Associations of breast cancer risk factors with tumor subtypes: A pooled analysis from the breast cancer association consortium studies. J Natl Cancer Inst. 2011;103(3):250-63.

Couch FJ, Gaudet MM, Antoniou AC, Ramus SJ, Kuchenbaecker KB, Soucy P, et al. Common variants at the 19p13.1 and ZNF365 loci are associated with ER subtypes of breast cancer and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev. 2012;21(4):645-57.

Ghoussaini M, Fletcher O, Michailidou K, Turnbull C, Schmidt MK, Dicks E, et al. Genome-wide association analysis identifies three new breast cancer susceptibility loci. Nat Genet. 2012;44(3):312-8.

Kirchhoff T, Offit K, Gaudet MM, Pharoah PDP, Easton DF, Antoniou AC, et al. Breast cancer risk and 6q22.33: Combined results from breast cancer association consortium and consortium

Robertson L, Hanson H, Seal S, Warren-Perry M, Hughes D, Howell I, et al. BRCA1 testing should be offered to individuals with triple-negative breast cancer diagnosed below 50 years. BR J CANCER. 2012;106(6):1234-8.

Siddiq A, Couch FJ, Chen GK, Lindström S, Eccles D, Millikan RC, et al. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11. Hum Mol Genet. 2012;21(24):5373-84.

Stevens KN, Fredericksen Z, Vachon CM, Wang X, Margolin S, Lindblom A, et al. 19p13.1 Is a triple-negative-specific breast cancer susceptibility locus. CANCER RES. 2012;72(7):1795-803.

Thompson ER, Gorringe KL, Choong DYH, Eccles DM, Mitchell G, Campbell IG. Analysis of KLLN as a high-penetrance breast cancer predisposition gene. Breast Cancer Res Treat. 2012;134(2):543-7.

Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, et al. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet. 2013;45(4):371-84.

Garcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN, et al. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat Genet. 2013;45(4):392-8.

Ruark E, Snape K, Humburg P, Loveday C, Bajrami I, Brough R, et al. Mosaic PPM1D mutations are associated with predisposition to breast and ovarian cancer. Nature. 2013;493(7432):406-10.

Upstill-Goddard R, Eccles D, Fliege J, Collins A. Machine learning approaches for the discovery of gene-gene interactions in disease data. Brief Bioinform. 2013;14(2):251-60.

Evans DG, Thomas S, Caunt J, Roberts L, Howell A, Wilson M, et al. Mammographic surveillance in women aged 35-39 at enhanced familial risk of breast cancer (FH02). Fam Cancer. 2014;13(1):13-21.

Li J, Lindström LS, Foo JN, Rafiq S, Schmidt MK, Pharoah PDP, et al. 2q36.3 is associated with prognosis for oestrogen receptor-negative breast cancer patients treated with chemotherapy. Nat Commun. 2014;5.

Moore KM, Thomas GJ, Duffy SW, Warwick J, Gabe R, Chou P, et al. Therapeutic targeting of integrin αvβ6 in breast cancer. J Natl Cancer Inst. 2014;106(8).

Purrington KS, Slager S, Eccles D, Yannoukakos D, Fasching PA, Miron P, et al. Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer. Carcinogenesis. 2014;35(5):1012-9.

Guo Q, Schmidt MK, Kraft P, Canisius S, Chen C, Khan S, et al. Identification of novel genetic markers of breast cancer survival. J Natl Cancer Inst. 2015;107(5).

Lei J, Rudolph A, Moysich KB, Rafiq S, Behrens S, Goode EL, et al. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy. Breast Cancer Res. 2015;17:18.

Pirie A, Guo Q, Kraft P, Canisius S, Eccles DM, Rahman N, et al. Common germline polymorphisms associated with breast cancer-specific survival. Breast Cancer Res. 2015;17(1):58.

Abubakar M, Orr N, Daley F, Coulson P, Ali HR, Blows F, et al. Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups. Breast Cancer Res. 2016;18(1):104.

Couch FJ, Kuchenbaecker KB, Michailidou K, Mendoza-Fandino GA, Nord S, Lilyquist J, et al. Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer. Nat Commun. 2016;7:11375-.

Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types. Cancer Discov. 2016;6(9):1052-67.

Purrington KS, Visscher DW, Wang C, Yannoukakos D, Hamann U, Nevanlinna H, et al. Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes. Breast Cancer Res Treat. 2016;157(1):117-31.

Schroth W, Winter S, Mürdter T, Schaeffeler E, Eccles D, Eccles B, et al. Improved prediction of endoxifen metabolism by CYP2D6 genotype in breast cancer patients treated with tamoxifen. Frontiers in pharmacology. 2017;8:582.

Milne RL, Kuchenbaecker KB, Michailidou K, Beesley J, Kar S, Lindström S, et al. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer. Nat Genet. 2017;49(12):1767.

Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92.

Guo Q, Burgess S, Turman C, Bolla MK, Wang Q, Lush M, et al. Body mass index and breast cancer survival: a Mendelian randomization analysis. International journal of epidemiology. 2017;46(6):1814-22.

Candido Dos Reis FJ, Wishart GC, Dicks EM, Greenberg D, Rashbass J, Schmidt MK, et al. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation. Breast Cancer Res. 2017;19(1):58.

Copson ER, Maishman TC, Tapper WJ, Cutress RI, Greville-Heygate S, Altman DG, et al…..Eccles DM. Germline BRCA mutation and outcome in young-onset breast cancer (POSH): a prospective cohort study. Lancet Oncol. 2018;19(2):169-80.

Eccles DM, Copson ER. Genetic testing for young women with breast cancer–Authors' reply. Lancet Oncol. 2018;19(4):e183.

Zeidan B, Manousopoulou A, Garay-Baquero DJ, White CH, Larkin SE, Potter KN, et al. Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study. Breast Cancer Res. 2018;20(1):19.

Khan S, Fagerholm R, Kadalayil L, Tapper W, Aittomäki K, Liu J, et al. Meta-analysis of three genome-wide association studies identifies two loci that predict survival and treatment outcome in breast cancer. Oncotarget. 2018;9(3):4249.

Horne HN, Oh H, Sherman ME, Palakal M, Hewitt SM, Schmidt MK, et al. E-cadherin breast tumor expression, risk factors and survival: Pooled analysis of 5,933 cases from 12 studies in the Breast Cancer Association Consortium. Sci Rep. 2018;8.

Weigelt B, Bi R, Kumar R, Blecua P, Mandelker DL, Geyer FC, et al. The landscape of somatic genetic alterations in breast cancers from ATM germline mutation carriers. Journal of the National Cancer Institute. 2018.: 110 (9): 1030-1034.

The following sources of funding have been important for the setting up and continuation of the POSH study:

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