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Published on: February 12, 2017
Implementing Real-World RECIST-based Tumor Response Assessment in Patients With Metastatic Non-small Cell Lung Cancer
Monika A Izano1, Nguyet Tran2, Alan Fu2
1Syapse, San Francisco, CA.
Background:
To accelerate drug approvals while maintaining scientific rigor in the evaluation of a therapeutic's efficacy and safety, the United States Food and Drug Administration now considers real-world data (RWD) to support New Drug Applications and expanded indications. Response Evaluation Criteria in Solid Tumors (RECIST) are the gold standard in clinical trials, but the derivation of RECIST-based treatment response from RWD is unproven. This study investigated the feasibility of implementing RECIST criteria in RWD by comparing lung cancer response assessments from RECIST-based measurement of lesions on archived radiologic films with results from medical oncologist and radiologist narratives recorded in electronic health records (EHR).
Materials And Methods:
Response to index treatment via different assessment approaches was compared among 30 metastatic non-small cell lung cancer (mNSCLC) patients receiving systemic treatment (index) after progression on a platinum or anti-PD(L)-1-containing regimen. Specifically, responses based on assessments documented in the medical oncologists' narratives were compared to a radiologist's assessments of archived images using RECIST v1.1 criteria. Each patient's best overall response was characterized as complete or partial (CR/PR), stable disease (SD), progressive disease (PD), or not evaluable (NE).
Results:
Similar distributions of best overall response and substantial concordance (77%) between medical oncologist-reported and radiologist re-assessed responses were observed. There were no instances of CR/PR to PD or PD to CR/PR discordance.
Conclusions:
Results suggest that accurate treatment responses, similar to RECIST, may be derived using RWD. Further validation and improvement of real-world response assessment are needed to develop a scalable real-world approach for response assessment.

