Literature DB >> 15495180

A tool for predicting breast carcinoma mortality in women who do not receive adjuvant therapy.

Michael W Kattan1, Dilip Giri, Katherine S Panageas, Amanda Hummer, Milicent Cranor, Kimberly J Van Zee, Clifford A Hudis, Larry Norton, Patrick I Borgen, Lee K Tan.   

Abstract

BACKGROUND: Among the several proposed risk classification schemes for predicting survival in women with breast carcinoma, one of the most commonly used is the Nottingham Prognostic Index (NPI). The goal of the current study was to use a continuous prognostic model (similar to those that have already been demonstrated to possess greater predictive accuracy than risk group-based models in other malignancies) to predict breast carcinoma mortality more accurately compared with the NPI.
METHODS: A total of 519 women who had been treated with mastectomy and axillary lymph node dissection at Memorial Sloan-Kettering Cancer Center (New York, NY) between 1976 and 1979 met the following requirements for study inclusion: confirmation of the presence of invasive mammary carcinoma, no receipt of neoadjuvant or adjuvant systemic therapy, no previous history of malignancy, and negative lymph node status as assessed on routine histopathologic examination. Paraffin blocks were available for 368 of the 519 eligible patients. All available axillary lymph node tissue blocks were subjected to enhanced pathologic analysis. The competing-risk method was used to predict disease-specific death, and the accuracy of the novel prognostic model that emerged from this process was evaluated using the concordance index. Jackknife and 10-fold cross-validation predictions yielded by this new model were compared with predictions yielded by the NPI.
RESULTS: Of the 348 women for whom complete data were available, 73 died of disease; the 15-year probability of breast carcinoma-related death was 20%. On the basis of these 348 cases, the authors developed a prognostic model that took patient age, disease multifocality, tumor size, tumor grade, lymphovascular invasion, and enhanced lymph node staining into account, and using competing-risks regression analysis, they found that this new model predicted disease-specific death more accurately compared with the NPI.
CONCLUSIONS: The authors have developed a model for predicting breast carcinoma-specific death with improved accuracy. This tool should be useful in counseling patients with regard to their specific need for adjuvant therapy. (c) 2004 American Cancer Society

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Year:  2004        PMID: 15495180     DOI: 10.1002/cncr.20635

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  7 in total

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Review 2.  Utilizing prognostic and predictive factors in breast cancer.

Authors:  Deepa S Subramaniam; Claudine Isaacs
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4.  Nomograms for Death from Pneumocystis jirovecii Pneumonia in HIV-Uninfected and HIV-Infected Patients.

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5.  Clinical validation of a model predicting the risk of preterm delivery.

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6.  Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index.

Authors:  J Mark Elwood; Essa Tawfiq; Sandar TinTin; Roger J Marshall; Tung M Phung; Ian Campbell; Vernon Harvey; Ross Lawrenson
Journal:  BMC Cancer       Date:  2018-09-17       Impact factor: 4.430

7.  Individualized Prediction of Breast Cancer Survival Using Flexible Parametric Survival Modeling: Analysis of a Hospital-Based National Clinical Cancer Registry.

Authors:  Donsuk Pongnikorn; Phichayut Phinyo; Jayanton Patumanond; Karnchana Daoprasert; Pachaya Phothong; Boonying Siribumrungwong
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  7 in total

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