8 research outputs found

    A prognostic index for operable, node-negative breast cancer

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    Clinical data and samples from patients diagnosed, more than 10 years previously, with operable node-negative breast cancer (participants in the Scottish Adjuvant Tamoxifen trial), were revisited, Cases with two distinct categories of outcome were selected; more than 10 years disease-free survival ('good outcome') or distant relapse within 6 years of diagnosis ('poor outcome'). An initial set of cases was analysed for a range of putative prognostic markers and a prognostic index, distinguishing the two outcome categories, was calculated. This index was then validated by testing its predictive power on a second, independent set of cases. A combination of histological grade plus immunochemical staining for BCL-2, p27 and Cyclin D 1, generated a useful prognostic index for tamoxifen-treated patients but not for those treated by surgery alone, The value of the index was confirmed in a second set of tamoxifen-treated, early stage breast cancers. Over-all, it correctly predicted good and poor outcome in 79 and 74% of cases, respectively (odds ratio 11.0). Other markers assessed added little to prediction of outcome. In the case of molecular assays, sensitivity and reliability were compromised by the age of the tissue specimens and the variability of fixation protocols. In selecting patients for adjuvant systemic chemotherapy, the proposed index improves considerably on current international guidelines and matches the performance reported for 'gene-expression signature' analysis. (C) 2004 Cancer Research UK.</p

    Molecular test algorithms for breast tumours

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    In order to advise the Federal Government on all matters related to personalised medicine in oncology, including the reimbursement of molecular tests, the Commission of Personalized Medicine (ComPerMed) has applied, for the breast tumours, the same methodology as previously applied for the digestive tumours. Meaning, the different molecular tests, represented in the shape of algorithms, are annotated with test levels — which aim to reflect their relevance based on current available data and to define the reimbursement — and are documented with recent literature, guidelines and a brief technical&nbsp;description.</p
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