RECIST criteria offer a simplified, conservative, extraction of imaging data for wide application in clinical trials

J · medicine forum Guru Joined: 29 Apr 2005 Posts: 612

http://imaging.cancer.gov/clinicaltrials/imaging/

Imaging Response Criteria

Since the year 2000, an international committee promulgated unified,
easily applicable criteria for measuring tumor response using X-ray, CT
and MRI which is known as Response Evaluation Criteria in Solid Tumors
(RECIST). The technique is recommended but not mandatory for NCI sponsored
trials and involves formalized rules for measurement of tumor target
lesions.

Guidelines and a RECIST Quick Reference for incorporating the procedure
are available online, and detailed explanations for application of the
method in clinical trials can be found at the European Organization for
Research and Treatment of Cancer (EORTC) RECIST Web page. NCI-funded
cooperative groups are encouraged, but not required, to use RECIST
criteria.

RECIST criteria are a voluntary, international standard, and are not an
NCI standard. They are based on a simplification of former methods (WHO,
ECOG) and based on measurable disease, i.e., the presence of at least one
measurable lesion.

RECIST criteria offer a simplified, conservative, extraction of imaging
data for wide application in clinical trials. They presume that linear
measures are an adequate substitute for 2-D methods and registers four
response categories:

* CR (complete response) = disappearance of all target lesions
* PR (partial response) = 30% decrease in the sum of the longest
diameter of target lesions
* PD (progressive disease) = 20% increase in the sum of the longest
diameter of target lesions
* SD (stable disease) = small changes that do not meet above criteria

Plans call for improving on RECIST methodology by developing and
validating clinical trial-acceptable methods and standards to incorporate:

* volumetric (3D) anatomical imaging
* dynamic contrast imaging
* functional (molecular) imaging

If successful, the use of medical image data as a surrogate endpoint in
clinical trials could lead to:

* Smaller clinical trials with fewer patients
* Earlier go/no decisions on drug compounds
* Faster regulatory approval for new drugs
* Earlier use in clinical care

Google