Radiology workflow for RECIST assessment in clinical trials: Can we reconcile time-efficiency and quality?

Beaumont, Hubert; Bertrand, Anne Sophie; Klifa, Catherine; Patriti, Sebastien; Cippolini, S.; Lovera, Christine; Iannessi, Antoine

doi:10.1016/j.ejrad.2019.07.030

Cited by 12 publications

(5 citation statements)

References 20 publications

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“…Our study gives encouraging results regarding the ability of some trained technologists to perform measurements according to RECIST 1.1 criteria during CT oncology follow-up with good identification of disease progression and excellent intra-observer reproducibility. Our results complement the study of Beaumont et al 28 , who showed in a cohort of 23 patients that the involvement of a specialized technician with specific computer tools required few corrections by radiologists (13%) and saved significant time for radiologists.…”

Section: Discussionsupporting

confidence: 90%

Evaluation of the capability and reproducibility of RECIST 1.1. measurements by technologists in breast cancer follow-up: a pilot study

Gouel,

Callonnec,

Levêque

et al. 2023

Sci Rep

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The evaluation of tumor follow-up according to RECIST 1.1 has become essential in clinical practice given its role in therapeutic decision making. At the same time, radiologists are facing an increase in activity while facing a shortage. Radiographic technologists could contribute to the follow-up of these measures, but no studies have evaluated their ability to perform them. Ninety breast cancer patients were performed three CT follow-ups between September 2017 and August 2021. 270 follow-up treatment CT scans were analyzed including 445 target lesions. The rate of agreement of classifications RECIST 1.1 between five technologists and radiologists yielded moderate (k value between 0.47 and 0.52) and substantial (k value = 0.62 and k = 0.67) agreement values. 112 CT were classified as progressive disease (PD) by the radiologists, and 414 new lesions were identified. The analysis showed a percentage of strict agreement of progressive disease classification between reader-technologists and radiologists ranging from substantial to almost perfect agreement (range 73–97%). Analysis of intra-observer agreement was strong at almost perfect (k > 0.78) for 3 technologists. These results are encouraging regarding the ability of selected technologists to perform measurements according to RECIST 1.1 criteria by CT scan with good identification of disease progression.

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Section: Discussionsupporting

confidence: 90%

Evaluation of the capability and reproducibility of RECIST 1.1. measurements by technologists in breast cancer follow-up: a pilot study

Gouel,

Callonnec,

Levêque

et al. 2023

Sci Rep

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“…During the follow-up, the patients received both image evaluation, such as ultrasound, computed tomography, or magnetic resonance imaging and biochemical markers, such as CA-125 (the abbreviation of cancer antigen 125, carcinoma antigen 125, or carbohydrate antigen 125) examinations. The evaluation of image finding was based on Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1 [127][128][129]. Criteria of progression or recurrence were based on findings of clinical symptoms or signs accompanied with image findings and tumor markers described elsewhere [41,130,131].…”

Section: Assessmentsmentioning

confidence: 99%

Comparing Paclitaxel–Carboplatin with Paclitaxel–Cisplatin as the Front-Line Chemotherapy for Patients with FIGO IIIC Serous-Type Tubo-Ovarian Cancer

Huang

Chen

Lee

et al. 2020

IJERPH

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The use of weekly chemotherapy for the treatment of patients with advanced-stage serous-type epithelial Tubo-ovarian cancer (ETOC), and primary peritoneal serous carcinoma (PPSC) is acceptable as the front-line postoperative chemotherapy after primary cytoreductive surgery (PCS). The main component of dose-dense chemotherapy is weekly paclitaxel (80 mg/m2), but it would be interesting to know what is the difference between combination of triweekly cisplatin (20 mg/m2) or triweekly carboplatin (carboplatin area under the curve 5-7 mg/mL per min [AUC 5-7]) in the dose-dense paclitaxel regimen. Therefore, we compared the outcomes of women with Gynecology and Obstetrics (FIGO) stage IIIC ETOC and PPSC treated with PCS and a subsequent combination of dose-dense weekly paclitaxel and triweekly cisplatin (paclitaxel–cisplatin) or triweekly carboplatin using AUC 5 (paclitaxel–carboplatin). Between January 2010 and December 2016, 40 women with International Federation of Gynecology and Obstetrics (FIGO) stage IIIC EOC, FTC, or PPSC were enrolled, including 18 treated with paclitaxel–cisplatin and the remaining 22 treated with paclitaxel–carboplatin. There were no statistically significant differences in disease characteristics of patients between two groups. Outcomes in paclitaxel–cisplatin group seemed to be little better than those in paclitaxel–carboplatin (median progression-free survival [PFS] 30 versus 25 months as well as median overall survival [OS] 58.5 versus 55.0 months); however, neither reached a statistically significant difference. In terms of adverse events (AEs), patients in paclitaxel–carboplatin group had more AEs, with a higher risk of neutropenia and grade 3/4 neutropenia, and the need for a longer period to complete the front-line chemotherapy, and the latter was associated with worse outcome for patients. We found that a period between the first-time chemotherapy to the last dose (6 cycles) of chemotherapy >21 weeks was associated with a worse prognosis in patients compared to that ≤21 weeks, with hazard ratio (HR) of 81.24 for PFS and 9.57 for OS. As predicted, suboptimal debulking surgery (>1 cm) also contributed to a worse outcome than optimal debulking surgery (≤1 cm) with HR of 14.38 for PFS and 11.83 for OS. Based on the aforementioned findings, both regimens were feasible and effective, but maximal efforts should be made to achieve optimal debulking surgery and following the on-schedule administration of dose-dense weekly paclitaxel plus triweekly platinum compounds. Randomized trials validating the findings are warranted.

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“…Multiple commercial products are currently available to assist in radiologic interpretation, standardized response assessment, and data management of imaging performed as part of an oncology clinical trial. Implementation of electronic case report forms during RECIST 1.1 interpretation was previously found to reduce nonconformity errors by 10-fold (43). Artificial intelligence is increasingly embedded within many of these platforms, including automation for tumor measurement, target and nontarget location labeling, tumor localization at follow-up, and response assessment categorization.…”

Section: Limitations and Futurementioning

confidence: 99%

A Primer on RECIST 1.1 for Oncologic Imaging in Clinical Drug Trials

Ruchalski¹,

Braschi‐Amirfarzan²,

Douek³

et al. 2021

Radiology: Imaging Cancer

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M easuring changes in tumor size with imaging can help determine if patients are responding to therapy, as well as if and when disease progression occurs. In the clinical trial setting, there is blending of patient care and scientific discovery. Quantification of radiologic changes in tumor size extends beyond contributing to individual patient treatment decisions. It can also provide a method to perform statistical analyses and attain regulatory drug approval of promising investigational therapeutic agents by objective clinical trial endpoints. Image-based treatment outcome measures are commonly used to assess if treatments are effective and, in the past few decades, have played an increasing role in the regulatory drug approval of a growing number of oncologic therapies. Therefore, it is imperative that the imaging community understands the application of these rule-based response criteria during image interpretation and how reported findings inform clinical trial results. Oncology Innovation: Drug Development ProcessThe drug discovery and approval paradigm is a very timeand resource-intensive process. For U.S. Food and Drug Administration (FDA) approval of one therapy, typically anywhere between 5000 to 10 000 initial compounds are rigorously investigated in a structured process that usually takes more than $1 billion and 10 years to complete (2-4). Beyond the initial concept and basic drug development, promising agents must undergo extensive preclinical evaluation and endure multiple phases of clinical trials to ensure safety and efficacy. Preclinical testing is performed both in This copy is for personal use only. To order printed copies, contact reprints@rsna.org Drug discovery and approval in oncology is mediated by the use of imaging to evaluate drug efficacy in clinical trials. Imaging is performed while patients receive therapy to evaluate their response to treatment. Response criteria, specifically Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), are standardized and can be used at different time points to classify response into the categories of complete response, partial response, stable disease, or disease progression. At the trial level, categorical responses for all patients are summated into image-based trial endpoints. These outcome measures, including objective response rate (ORR) and progression-free survival (PFS), are characteristics that can be derived from imaging and can be used as surrogates for overall survival (OS). Similar to OS, ORR and PFS describe the efficacy of a drug. U.S. Food and Drug Administration (FDA) regulatory approval requires therapies to demonstrate direct evidence of clinical benefit, such as improved OS. However, multiple programs have been created to expedite drug approval for life-threatening illnesses, including advanced cancer. ORR and PFS have been accepted by the FDA as adequate predictors of OS on which to base drug approval decisions, thus substantially shortening the time and cost of drug development (1). Use of imaging surrogate marke...

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Radiology workflow for RECIST assessment in clinical trials: Can we reconcile time-efficiency and quality?

Abstract: Iannessi b a Median Technologies. 1800 route des crêtes, les deux arcs-Bat B. Sciences Department,

Cited by 12 publications

References 20 publications

Evaluation of the capability and reproducibility of RECIST 1.1. measurements by technologists in breast cancer follow-up: a pilot study

Evaluation of the capability and reproducibility of RECIST 1.1. measurements by technologists in breast cancer follow-up: a pilot study

Comparing Paclitaxel–Carboplatin with Paclitaxel–Cisplatin as the Front-Line Chemotherapy for Patients with FIGO IIIC Serous-Type Tubo-Ovarian Cancer

A Primer on RECIST 1.1 for Oncologic Imaging in Clinical Drug Trials

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