Literature DB >> 21544817

A nomogram predicting the probability of primary breast cancer survival at 2- and 5-years using pathological and biological tumor parameters.

Chafika Mazouni1, Pascal Bonnier, Sylvie Romain, Pierre-Marie Martin.   

Abstract

PURPOSE: Our objective was to develop a nomogram to predict individual overall survival (OS) for primary breast cancer, based on pathological and biological tumor parameters.
METHODS: A retrospective study in a cohort of 180 patients with primary breast cancer was used to build the nomogram. Pathological factors and tumor proteases measured prospectively in primary tumors were used. A multivariate Cox proportional hazards model was used to explore the relationship with OS, and regression coefficients were used to build the nomogram. The nomogram was internally validated with 200 bootstrap re-samples.
RESULTS: The final variables included in the nomogram comprised tumor size (P = 0.04), nodal pathological status (P = 0.01), estrogen receptor status (P = 0.04), urokinase plasminogen activator inhibitor-1 (PAI-1; P = 0.02), thymidine kinase (P = 0.03), and cathepsin D (P = 0.004). The predictive accuracy of the nomogram at estimating the probability of OS, at both 2 and 5 years, was respectively 0.874 and 0.832 before and after calibration.
CONCLUSION: A nomogram to predict 2- and 5-year OS in BC, using histological and biological parameters was successfully developed. This prognostic tool should prove useful in decision-making and therapeutic research.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21544817     DOI: 10.1002/jso.21712

Source DB:  PubMed          Journal:  J Surg Oncol        ISSN: 0022-4790            Impact factor:   3.454


  8 in total

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2.  Prognosis and Genomic Landscape of Liver Metastasis in Patients With Breast Cancer.

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6.  A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

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7.  Prognostic role of high cathepsin D expression in breast cancer: a systematic review and meta-analysis.

Authors:  Junho Kang; Yeuni Yu; Seongdo Jeong; Hansong Lee; Hye Jin Heo; Jeong Jun Park; Hee Sam Na; Dai Sik Ko; Yun Hak Kim
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8.  A Nomogram for Distinction and Potential Prediction of Liver Metastasis in Breast Cancer Patients.

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  8 in total

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