Literature DB >> 22952219

RECIST: no longer the sharpest tool in the oncology clinical trials toolbox---point.

Manish R Sharma1, Michael L Maitland, Mark J Ratain.   

Abstract

Although "response" has been an attractive term for oncologists and patients, oncologists really want to know which therapy to start for a given patient and when to discontinue that therapy in favor of an alternative. In efficacy trials, cancer therapeutics have conventionally been assessed by endpoints that are based on the categorical Response Evaluation Criteria In Solid Tumors (RECIST) system. In this article, we make the case for a new paradigm in which therapeutics are assessed on a continuous scale by evidence of efficacy, using a variety of quantitative tools that take advantage of technologic innovations and increasing understanding of cancer biology. The new paradigm relies on randomized comparisons between investigational arms and control arms, as historical controls are unavailable or unreliable for these quantitative measures. We discuss multiple limitations of RECIST, including its overemphasis on tumor regression, concerns about the accuracy of tumor measurements and the validity of comparisons with historical controls, and its inadequacy in disease settings in which tumor measurements on cross-sectional imaging are difficult or uninformative. We discuss how the new paradigm overcomes these limitations and provides a framework for answering the key questions of the oncologist and improving patient outcomes.

Entities:  

Mesh:

Year:  2012        PMID: 22952219     DOI: 10.1158/0008-5472.CAN-12-0058

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  38 in total

Review 1.  Bringing Model-Based Prediction to Oncology Clinical Practice: A Review of Pharmacometrics Principles and Applications.

Authors:  Núria Buil-Bruna; José-María López-Picazo; Salvador Martín-Algarra; Iñaki F Trocóniz
Journal:  Oncologist       Date:  2015-12-14

Review 2.  Pulmonary imaging after stereotactic radiotherapy-does RECIST still apply?

Authors:  Sarah A Mattonen; Aaron D Ward; David A Palma
Journal:  Br J Radiol       Date:  2016-06-20       Impact factor: 3.039

Review 3.  Computed tomography imaging assessment of postexternal beam radiation changes of the liver.

Authors:  Michael Lock; Ashkan A Malayeri; Omar Y Mian; Nina A Mayr; Joseph M Herman; Simon S Lo
Journal:  Future Oncol       Date:  2016-08-31       Impact factor: 3.404

4.  Circulating tumor DNA as an early marker of therapeutic response in patients with metastatic colorectal cancer.

Authors:  J Tie; I Kinde; Y Wang; H L Wong; J Roebert; M Christie; M Tacey; R Wong; M Singh; C S Karapetis; J Desai; B Tran; R L Strausberg; L A Diaz; N Papadopoulos; K W Kinzler; B Vogelstein; P Gibbs
Journal:  Ann Oncol       Date:  2015-04-07       Impact factor: 32.976

5.  Taking a Measured Approach to Toxicity Data in Phase I Oncology Clinical Trials.

Authors:  Manish R Sharma; Mark J Ratain
Journal:  Clin Cancer Res       Date:  2015-10-14       Impact factor: 12.531

6.  Quantifying local tumor morphological changes with Jacobian map for prediction of pathologic tumor response to chemo-radiotherapy in locally advanced esophageal cancer.

Authors:  Sadegh Riyahi; Wookjin Choi; Chia-Ju Liu; Hualiang Zhong; Abraham J Wu; James G Mechalakos; Wei Lu
Journal:  Phys Med Biol       Date:  2018-07-19       Impact factor: 3.609

7.  FDG-Avid Focal Liver Reaction From Proton Therapy in a Patient With Primary Esophageal Adenocarcinoma.

Authors:  Hena S Ahmed; Austin R Pantel; James M Metz; John P Plastaras; Michael D Farwell
Journal:  Clin Nucl Med       Date:  2018-05       Impact factor: 7.794

8.  Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy.

Authors:  Gopichandh Danala; Theresa Thai; Camille C Gunderson; Katherine M Moxley; Kathleen Moore; Robert S Mannel; Hong Liu; Bin Zheng; Yuchen Qiu
Journal:  Acad Radiol       Date:  2017-05-26       Impact factor: 3.173

9.  A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration.

Authors:  Maxine Tan; Zheng Li; Yuchen Qiu; Scott D McMeekin; Theresa C Thai; Kai Ding; Kathleen N Moore; Hong Liu; Bin Zheng
Journal:  IEEE Trans Med Imaging       Date:  2015-08-27       Impact factor: 10.048

10.  Predicting responsiveness to sorafenib: can the determination of FGF3/FGF4 amplifications enrich for clinical benefit?

Authors:  James J Harding; Ghassan K Abou-Alfa
Journal:  Hepatobiliary Surg Nutr       Date:  2014-08       Impact factor: 7.293

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