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Start Over Author "Tom Maishman" Journal breast cancer research
2 results on '"Tom Maishman"'

1. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation

Author

Francisco J. Candido dos Reis, Gordon C. Wishart, Ed M. Dicks, David Greenberg, Jem Rashbass, Marjanka K. Schmidt, Alexandra J. van den Broek, Ian O. Ellis, Andrew Green, Emad Rakha, Tom Maishman, Diana M. Eccles, and Paul D. P. Pharoah

Subjects
Breast cancer, Prognosis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in ‘step’ changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Methods Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. Results In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. Conclusions The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer.

Published
2017
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2. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

Author

Chen-Yang Shen, Keun-Young Yoo, Kazuo Tajima, Georgia Chenevix-Trench, Qin Wang, William J. Tapper, Kristiina Aittomäki, Douglas F. Easton, Anne Lise Børresen-Dale, Ann Smeets, Hidemi Ito, Heli Nevanlinna, Kamila Czene, Sabine C. Linn, Soo Hwang Teo, Tom Maishman, Ursula Eilber, Robert Luben, Jolanta Lissowska, Cheng Har Yip, Keitaro Matsuo, Sue K. Park, Sandrine Tchatchou, Lothar Haeberle, Anja Rudolph, Sajjad Rafiq, Ellen L. Goode, Nur Aishah Taib, Arto Mannermaa, Keith Humphreys, Sabine Behrens, Silje Nord, Javier Benitez, Alison M. Dunning, Irene L. Andrulis, Jaana M. Hartikainen, Sandra Alexandra J van den Broek, Joe Dennis, Gord Glendon, Taru A. Muranen, Arif B. Ekici, Veli-Matti Kosma, Madeleine M.A. Tilanus-Linthorst, Annika Lindblom, Emily Hallberg, Vessela N. Kristensen, Diana Eccles, Maartje J. Hooning, Sten Cornelissen, Stephen J. Chanock, Paul P.D. Pharoah, Diana Torres, Carolien H.M. van Deurzen, Jingmei Li, Celine M. Vachon, Pei-Ei Wu, Jenny Chang-Claude, Fergus J. Couch, Hans-Ulrich Ulmer, Jieping Lei, Sigrid Hatse, Vesa Kataja, Ute Hamann, Sara Margolin, Daehee Kang, Marjanka K. Schmidt, Hans Wildiers, Lara Sucheston, Janet E. Olson, Mitul Shah, Matthias W. Beckmann, Manjeet K. Bolla, Ji Yeob Choi, Per Hall, Carl Blomqvist, Thomas Rüdiger, Gwo Fuang Ho, Jonine D. Figueroa, Julia A. Knight, Petra Seibold, Chia-Ni Hsiung, Ming-Feng Hou, Hiroji Iwata, Diether Lambrechts, Kelly-Anne Phillips, Grethe I. Grenaker Alnæs, Peter A. Fasching, Montserrat Garcia-Closas, Kirsten B. Moysich, Agnes Jager, Pharoah, Paul [0000-0001-8494-732X], Dennis, Joe [0000-0003-4591-1214], Wang, Jean [0000-0002-9139-0627], Luben, Robert [0000-0002-5088-6343], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], Apollo - University of Cambridge Repository, Medical Oncology, Clinical Genetics, Pathology, and Surgery

Subjects
Oncology, medicine.medical_treatment, Estrogen receptor, 32 Biomedical and Clinical Sciences, Genome-wide association study, Kaplan-Meier Estimate, 0302 clinical medicine, Medizinische Fakultät, Surgical oncology, Antineoplastic Combined Chemotherapy Protocols, 2.1 Biological and endogenous factors, Prospective cohort study, health care economics and organizations, Cancer, 2 Aetiology, Medicine(all), 0303 health sciences, Interleukin-12 Subunit p40, Hazard ratio, Genomics, Middle Aged, Prognosis, Tumor Burden, 3. Good health, 3204 Immunology, Treatment Outcome, Receptors, Estrogen, 030220 oncology & carcinogenesis, Female, 4.2 Evaluation of markers and technologies, Signal Transduction, Research Article, Adult, medicine.medical_specialty, Breast Neoplasms, Single-nucleotide polymorphism, Protein Serine-Threonine Kinases, Polymorphism, Single Nucleotide, Immunomodulation, 03 medical and health sciences, Breast cancer, SDG 3 - Good Health and Well-being, Internal medicine, Breast Cancer, Genetics, Biomarkers, Tumor, medicine, Humans, ddc:610, Neoplasm Staging, 030304 developmental biology, Chemotherapy, business.industry, Receptor, Transforming Growth Factor-beta Type II, 3211 Oncology and Carcinogenesis, medicine.disease, Cancer research, Neoplasm Grading, 4 Detection, screening and diagnosis, business, Receptors, Transforming Growth Factor beta
Abstract

Introduction Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy). Methods We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast cancer-specific survival (BCSS). Heterogeneity according to chemotherapy or ER status was evaluated with the log-likelihood ratio test. Results Three independent SNPs in TGFBR2 and IL12B were associated with OS (P C) (per allele hazard ratio (HR) 1.54 (95% confidence interval (CI) 1.22 to 1.95), P = 3.08 × 10−4) was not found in ER-negative patients without chemotherapy or ER-positive patients with chemotherapy (P for interaction A) with poorer OS (HR 1.50 (95% CI 1.21 to 1.86), P = 1.81 × 10−4), and rs2853694 (A > C) with improved OS (HR 0.73 (95% CI 0.61 to 0.87), P = 3.67 × 10−4). Similar associations were observed with BCSS. Association with TGFBR2 rs1367610 but not IL12B variants replicated using BCAC Asian samples and the independent Prospective Study of Outcomes in Sporadic versus Hereditary Breast Cancer Study and yielded a combined HR of 1.57 ((95% CI 1.28 to 1.94), P = 2.05 × 10−5) without study heterogeneity. Conclusions TGFBR2 variants may have prognostic and predictive value in ER-negative breast cancer patients treated with adjuvant chemotherapy. Our findings provide further insights into the development of immunotherapeutic targets for ER-negative breast cancer.

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