Literature DB >> 15484214

Validation of the postoperative nomogram for 12-year sarcoma-specific mortality.

Fritz C Eilber1, Murray F Brennan, Frederick R Eilber, Sarah M Dry, Samuel Singer, Michael W Kattan.   

Abstract

BACKGROUND: On the basis of a prospectively followed cohort of adult patients with primary soft tissue sarcoma (STS) who were treated at Memorial Sloan-Kettering Cancer Center (MSKCC; New York, NY), a nomogram for predicting sarcoma-specific mortality was developed. Although this nomogram was found to be accurate by internal validation tests, it had not been validated in an external patient cohort, and thus its universal applicability remained unproven.
METHODS: Between 1975 and 2002, 1167 adult patients (age > or = 16 years) underwent treatment for primary STS at the University of California-Los Angeles (UCLA; Los Angeles, CA). All patients treated with an ifosfamide-based chemotherapy protocol (n = 238) were excluded from the current analysis. The remaining 929 patients constituted the population on which the validation study was performed. The nomogram validation process comprised two activities. First, the extent of discrimination was quantified using the concordance index. Second, the level of calibration was assessed by grouping patients with respect to their nomogram-predicted mortality probabilities and then comparing group means with observed Kaplan-Meier estimates of disease-specific survival.
RESULTS: With median follow-up intervals of 48 months for all patients and 60 months for surviving patients, the 5-year and 10-year disease-specific survival rates were 77% (95% confidence interval [CI], 74-80%) and 71% (95% CI, 67-75%), respectively. Application of the nomogram to the UCLA data set yielded a concordance index of 0.76, and the observed correspondence between predicted and actual outcomes suggested a high level of calibration.
CONCLUSIONS: In the current study, the MSKCC Sarcoma Nomogram was found to provide accurate survival predictions when it was applied to an external cohort of patients who were treated at UCLA. (c) 2004 American Cancer Society

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Year:  2004        PMID: 15484214     DOI: 10.1002/cncr.20570

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


  33 in total

Review 1.  Principles in Management of Soft Tissue Sarcoma.

Authors:  Aimee M Crago; Murray F Brennan
Journal:  Adv Surg       Date:  2015-05-05

2.  Sarcoma: primary retroperitoneal sarcoma-predicting survival.

Authors:  Murray F Brennan
Journal:  Nat Rev Clin Oncol       Date:  2013-05-07       Impact factor: 66.675

Review 3.  Of mice and men: opportunities to use genetically engineered mouse models of synovial sarcoma for preclinical cancer therapeutic evaluation.

Authors:  Kevin B Jones; Malay Haldar; Joshua D Schiffman; Lisa Cannon-Albright; Stephen L Lessnick; Sunil Sharma; Mario R Capecchi; R Lor Randall
Journal:  Cancer Control       Date:  2011-07       Impact factor: 3.302

4.  Lessons learned from the study of 10,000 patients with soft tissue sarcoma.

Authors:  Murray F Brennan; Cristina R Antonescu; Nicole Moraco; Samuel Singer
Journal:  Ann Surg       Date:  2014-09       Impact factor: 12.969

5.  Soft tissue sarcoma across the age spectrum: a population-based study from the Surveillance Epidemiology and End Results database.

Authors:  Andrea Ferrari; Iyad Sultan; Tseng Tien Huang; Carlos Rodriguez-Galindo; Ahmad Shehadeh; Cristina Meazza; Kirsten K Ness; Michela Casanova; Sheri L Spunt
Journal:  Pediatr Blood Cancer       Date:  2011-07-25       Impact factor: 3.167

6.  Aggressive Surgical Approach for Treatment of Primary and Recurrent Retroperitoneal Soft Tissue Sarcoma.

Authors:  Antonio Chiappa; Emilio Bertani; Gabriella Pravettoni; Andrew Paul Zbar; Diego Foschi; Giuseppe Spinoglio; Bernardo Bonanni; Gianluca Polvani; Federico Ambrogi; Maria Laura Cossu; Carlo Ferrari; Marco Venturino; Cristiano Crosta; Luca Bocciolone; Roberto Biffi
Journal:  Indian J Surg       Date:  2018-01-31       Impact factor: 0.656

7.  Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients.

Authors:  Jan C Peeken; Tatyana Goldberg; Christoph Knie; Basil Komboz; Michael Bernhofer; Francesco Pasa; Kerstin A Kessel; Pouya D Tafti; Burkhard Rost; Fridtjof Nüsslin; Andreas E Braun; Stephanie E Combs
Journal:  Strahlenther Onkol       Date:  2018-03-20       Impact factor: 3.621

8.  Histology-based Classification Predicts Pattern of Recurrence and Improves Risk Stratification in Primary Retroperitoneal Sarcoma.

Authors:  Marcus C B Tan; Murray F Brennan; Deborah Kuk; Narasimhan P Agaram; Cristina R Antonescu; Li-Xuan Qin; Nicole Moraco; Aimee M Crago; Samuel Singer
Journal:  Ann Surg       Date:  2016-03       Impact factor: 12.969

9.  Quantitative F18-fluorodeoxyglucose positron emission tomography accurately characterizes peripheral nerve sheath tumors as malignant or benign.

Authors:  Matthias R Benz; Johannes Czernin; Sarah M Dry; William D Tap; Martin S Allen-Auerbach; David Elashoff; Michael E Phelps; Wolfgang A Weber; Fritz C Eilber
Journal:  Cancer       Date:  2010-01-15       Impact factor: 6.860

10.  A synovial sarcoma-specific preoperative nomogram supports a survival benefit to ifosfamide-based chemotherapy and improves risk stratification for patients.

Authors:  Robert J Canter; Li-Xuan Qin; Robert G Maki; Murray F Brennan; Marc Ladanyi; Samuel Singer
Journal:  Clin Cancer Res       Date:  2008-12-15       Impact factor: 12.531

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