Variability in assessing treatment response: metastatic colorectal cancer as a paradigm.
OBJECTIVE
The cutoff values currently used to categorize tumor response to therapy are neither biologically based nor tailored for measurement reproducibility with contemporary imaging modalities. Sources and magnitudes of discordance in response assessment in metastatic colorectal cancer (mCRC) are unknown.


METHODS
A subset of patients' CT images of chest, abdomen, and pelvis were randomly chosen from a multicenter clinical trial evaluating insulin-like growth factor receptor type 1-targeted therapy in mCRC. Using Response Evaluation Criteria in Solid Tumors (RECIST), three radiologists selected target lesions and measured "uni" (maximal diameter), "bi" (product of maximal diameter and maximal perpendicular diameter), and "vol" (volume) on baseline and 6-week posttherapy scans in the following ways: (i) each radiologist independently selected and measured target lesions and (ii) one radiologist's target lesions were blindly remeasured by the others. Variability in relative change of tumor measurements was analyzed using linear mixed effects models.


RESULTS
Three radiologists independently selected 138, 101, and 146 metastatic target lesions in the liver, lungs, lymph nodes, and other organs (e.g., peritoneal cavity) in 29 patients. Of 198 target lesions total, 33% were selected by all three, 28% by two, and 39% by one radiologist. With independent selection, the variability in relative change of tumor measurements was 11% (uni), 19% (bi), and 22% (vol), respectively. When measuring the same lesions, the corresponding numbers were 8%, 14%, and 12%.


CONCLUSIONS
The relatively low variability in change of mCRC measurements suggests that response criteria could be modified to allow more accurate and sensitive CT assessment of anticancer therapy efficacy.
Authors' Affiliations: Department of Radiology, Columbia University Medical Center; bz2166@cumc.columbia.edu.
Binsheng
B
Zhao
Mailman School of Public Health, Columbia University, New York, New York; and.
Shing M
SM
Lee
Authors' Affiliations: Department of Radiology, Columbia University Medical Center;
Hyun-Ju
HJ
Lee
Authors' Affiliations: Department of Radiology, Columbia University Medical Center;
Yongqiang
Y
Tan
Authors' Affiliations: Department of Radiology, Columbia University Medical Center;
Jing
J
Qi
Authors' Affiliations: Department of Radiology, Columbia University Medical Center;
Thorsten
T
Persigehl
Department of Imaging, Merck Research Laboratory, West Point, Pennsylvania.
David P
DP
Mozley
Authors' Affiliations: Department of Radiology, Columbia University Medical Center;
Lawrence H
LH
Schwartz
D000368:Aged; D000369:Aged, 80 and over; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000628:therapy*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods / Q000592:standards; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D009367:Neoplasm Staging; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000592:standards; D016896:Treatment Outcome