Literature DB >> 20397778

Interobserver and intraobserver variability in the response evaluation of cancer therapy according to RECIST and WHO-criteria.

Chikako Suzuki1, Michael R Torkzad, Hans Jacobsson, Gunnar Aström, Anders Sundin, Thomas Hatschek, Hirofumi Fujii, Lennart Blomqvist.   

Abstract

BACKGROUND: Response Evaluation Criteria In Solid Tumors (RECIST) and WHO-criteria are used to evaluate treatment effects in clinical trials. The purpose of this study was to examine interobserver and intraobserver variations in radiological response assessment using these criteria.
MATERIAL AND METHODS: Thirty-nine patients were eligible. Each patient's series of CT images were reviewed. Each patient was classified into one of four categories according RECIST and WHO-criteria. To examine interobserver variation, response classifications were independently obtained by two radiologists. One radiologist repeated the procedure on two additional different occasions to examine intraobserver variation. Kappa statistics was applied to examine agreement.
RESULTS: Interobserver variation using RECIST and WHO-criteria were 0.53 (95% CI 0.33-0.72) and 0.60 (0.39-0.80), respectively. Response rates (RR) according to RECIST obtained by reader A and reader B were 33% and 21%, respectively. RR according to WHO-criteria obtained by reader A and reader B were 33% and 23% respectively. Intraobserver variation using RECIST and WHO-criteria ranged between 0.76-0.96 and 0.86-0.91, respectively.
CONCLUSION: Radiological tumor response evaluation according to RECIST and WHO-criteria are subject to considerable inter- and intraobserver variability. Efforts are necessary to reduce inconsistencies from current response evaluation criteria.

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Year:  2010        PMID: 20397778     DOI: 10.3109/02841861003705794

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  29 in total

1.  Imaging texture analysis for automated prediction of lung cancer recurrence after stereotactic radiotherapy.

Authors:  Sarah A Mattonen; Shyama Tetar; David A Palma; Alexander V Louie; Suresh Senan; Aaron D Ward
Journal:  J Med Imaging (Bellingham)       Date:  2015-11-12

2.  A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

Authors:  A B Spanier; N Caplan; J Sosna; B Acar; L Joskowicz
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-11-16       Impact factor: 2.924

3.  Interreader and inter-test agreement in assessing treatment response following transarterial embolization for hepatocellular carcinoma.

Authors:  Olivio F Donati; Richard Kinh Gian Do; Andreas M Hötker; Seth S Katz; Junting Zheng; Chaya S Moskowitz; Christopher Beattie; Karen T Brown
Journal:  Eur Radiol       Date:  2015-04-08       Impact factor: 5.315

Review 4.  Interventional Oncology in Hepatocellular Carcinoma: Progress Through Innovation.

Authors:  Lin Mu; Julius Chapiro; Jeremiah Stringam; Jean-François Geschwind
Journal:  Cancer J       Date:  2016 Nov/Dec       Impact factor: 3.360

5.  Three-dimensional Radiologic Assessment of Chemotherapy Response in Ewing Sarcoma Can Be Used to Predict Clinical Outcome.

Authors:  Maryam Aghighi; Justin Boe; Jarrett Rosenberg; Rie Von Eyben; Rakhee S Gawande; Philippe Petit; Tarsheen K Sethi; Jeremy Sharib; Neyssa M Marina; Steven G DuBois; Heike E Daldrup-Link
Journal:  Radiology       Date:  2016-03-16       Impact factor: 11.105

6.  Interobserver agreement of semi-automated and manual measurements of functional MRI metrics of treatment response in hepatocellular carcinoma.

Authors:  David Bonekamp; Susanne Bonekamp; Vivek Gowdra Halappa; Jean-Francois H Geschwind; John Eng; Celia Pamela Corona-Villalobos; Timothy M Pawlik; Ihab R Kamel
Journal:  Eur J Radiol       Date:  2013-12-03       Impact factor: 3.528

7.  Assessment of the response of hepatocellular carcinoma to interventional radiology treatments.

Authors:  Francesca Patella; Filippo Pesapane; Enrico Fumarola; Stefania Zannoni; Pietro Brambillasca; Ilaria Emili; Guido Costa; Victoria Anderson; Elliot B Levy; Gianpaolo Carrafiello; Bradford J Wood
Journal:  Future Oncol       Date:  2019-05-02       Impact factor: 3.404

8.  Semiautomatic volumetric tumor segmentation for hepatocellular carcinoma: comparison between C-arm cone beam computed tomography and MRI.

Authors:  Vania Tacher; MingDe Lin; Michael Chao; Lars Gjesteby; Nikhil Bhagat; Abdelkader Mahammedi; Roberto Ardon; Benoit Mory; Jean-François Geschwind
Journal:  Acad Radiol       Date:  2013-04       Impact factor: 3.173

9.  Unresectable hepatocellular carcinoma: MR imaging after intraarterial therapy. Part I. Identification and validation of volumetric functional response criteria.

Authors:  Susanne Bonekamp; Zhen Li; Jean-François H Geschwind; Vivek Gowdra Halappa; Celia Pamela Corona-Villalobos; Diane Reyes; Timothy M Pawlik; David Bonekamp; John Eng; Ihab R Kamel
Journal:  Radiology       Date:  2013-04-24       Impact factor: 11.105

10.  Identification of Discrete Prognostic Groups in Ewing Sarcoma.

Authors:  Erin E Karski; Elizabeth McIlvaine; Mark R Segal; Mark Krailo; Holcombe E Grier; Linda Granowetter; Richard B Womer; Paul A Meyers; Judy Felgenhauer; Neyssa Marina; Steven G DuBois
Journal:  Pediatr Blood Cancer       Date:  2015-08-10       Impact factor: 3.167

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