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How Does Target Lesion Selection Affect RECIST? A Computer Simulation Study
Teresa M Tareco Bucho1, Renaud L M Tissier, Kevin B W Groot Lipman
1From the Radiology Department (T.T.B., K.G.L., Z.B., T.D.L.N.-K., R.B.-T., S.T.), Biostatistics Unit (R.T.), and Thoracic Oncology (K.G.L.), Netherlands Cancer Institute, Amsterdam, the Netherlands; GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (T.T.B., K.G.L., Z.B., R.B.-T., S.T.); Institute for Advanced Biomedical Technologies, Gabriele d'Annunzio University of Chieti-Pescara, Italy (A.D.P.); Department of Innovative Technologies in Medicine and Dentistry, Gabriele d'Annunzio University of Chieti-Pescara, Italy (A.D.P.); Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland (T.D.L.N.-K.); Institute of Radiology and Nuclear Medicine, Stadtspital Zürich, Zurich, Switzerland (T.D.L.N.-K.); and Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark (R.B.-T.).
Objectives:
Response Evaluation Criteria in Solid Tumors (RECIST) is grounded on the assumption that target lesion selection is objective and representative of the change in total tumor burden (TTB) during therapy. A computer simulation model was designed to challenge this assumption, focusing on a particular aspect of subjectivity: target lesion selection.
Materials And Methods:
Disagreement among readers and the disagreement between individual reader measurements and TTB were analyzed as a function of the total number of lesions, affected organs, and lesion growth.
Results:
Disagreement rises when the number of lesions increases, when lesions are concentrated on a few organs, and when lesion growth borders the thresholds of progressive disease and partial response. There is an intrinsic methodological error in the estimation of TTB via RECIST 1.1, which depends on the number of lesions and their distributions. For example, for a fixed number of lesions at 5 and 15, distributed over a maximum of 4 organs, the error rates are observed to be 7.8% and 17.3%, respectively.
Conclusions:
Our results demonstrate that RECIST can deliver an accurate estimate of TTB in localized disease, but fails in cases of distal metastases and multiple organ involvement. This is worsened by the "selection of the largest lesions," which introduces a bias that makes it hardly possible to perform an accurate estimate of the TTB. Including more (if not all) lesions in the quantitative analysis of tumor burden is desirable.
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