Literature DB >> 19820504

Semiquantitative visual approach to scoring lung cancer treatment response using computed tomography: a pilot study.

Ronald H Gottlieb1, Prasanna Kumar, Peter Loud, Donald Klippenstein, Cheryl Raczyk, Wei Tan, Jenny Lu, Nithya Ramnath.   

Abstract

OBJECTIVE: Our objective was to compare a newly developed semiquantitative visual scoring (SVS) method with the current standard, the Response Evaluation Criteria in Solid Tumors (RECIST) method, in the categorization of treatment response and reader agreement for patients with metastatic lung cancer followed by computed tomography.
MATERIALS AND METHODS: The 18 subjects (5 women and 13 men; mean age, 62.8 years) were from an institutional review board-approved phase 2 study that evaluated a second-line chemotherapy regimen for metastatic (stages III and IV) non-small cell lung cancer. Four radiologists, blinded to the patient outcome and each other's reads, evaluated the change in the patients' tumor burden from the baseline to the first restaging computed tomographic scan using either the RECIST or the SVS method. We compared the numbers of patients placed into the partial response, the stable disease (SD), and the progressive disease (PD) categories (Fisher exact test) and observer agreement (kappa statistic).
RESULTS: Requiring the concordance of 3 of the 4 readers resulted in the RECIST placing 17 (100%) of 17 patients in the SD category compared with the SVS placing 9 (60%) of 15 patients in the partial response, 5 (33%) of the 15 patients in the SD, and 1 (6.7%) of the 15 patients in the PD categories (P < 0.0001). Interobserver agreement was higher among the readers using the SVS method (kappa, 0.54; P < 0.0001) compared with that of the readers using the RECIST method (kappa, -0.01; P = 0.5378).
CONCLUSIONS: Using the SVS method, the readers more finely discriminated between the patient response categories with superior agreement compared with the RECIST method, which could potentially result in large differences in early treatment decisions for advanced lung cancer.

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Year:  2009        PMID: 19820504     DOI: 10.1097/RCT.0b013e3181963b14

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  2 in total

1.  Joint confidence region estimation of L-moment ratios with an extension to right censored data.

Authors:  Dongliang Wang; Alan D Hutson
Journal:  J Appl Stat       Date:  2013       Impact factor: 1.404

2.  Quantified visual scoring of metastatic melanoma patient treatment response using computed tomography: improving on the current standard.

Authors:  Ronald H Gottlieb; Elizabeth Krupinski; Pavani Chalasani; Lee Cranmer
Journal:  J Digit Imaging       Date:  2012-04       Impact factor: 4.056

  2 in total

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