Response evaluation for immunotherapy through semi-automatic software based on RECIST 1.1, irRC, and iRECIST criteria: comparison with subjective assessment

Lai, Ying‐Chieh; Chang, Wen‐Cheng; Chen, Chun‐Bing; Wang, Chi-Liang; Lin, Yu-Fen; Ho, M.; Cheng, Ching‐Yi; Huang, Pei-Wei; Hsu, Chao‐Wei; Lin, Gigin

doi:10.1177/0284185119887588

Cited by 12 publications

(6 citation statements)

References 25 publications

(31 reference statements)

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“…Analyses conducted by the FDA applying iRECIST suggest a low impact on response rates. 10 Similar pooled analyses of trials which used irRECIST also confirm some impact on response rates but did not impact to a significant degree the interpretation of progression-free survival (PFS) 11 or overall survival (OS). 12 Given the potential importance of pseudoprogression on outcome, we sought to investigate the frequency of uptake of iRECIST by clinical trial sponsors in the years after the guideline was published.…”

Section: Introductionmentioning

confidence: 83%

iRECIST and atypical patterns of response to immuno-oncology drugs

Ramon-Patino

Schmid

Lau

et al. 2022

J Immunother Cancer

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With the advent of immunotherapy as one of the keystones of the treatment of our patients with cancer, a number of atypical patterns of response to these agents has been identified. These include pseudoprogression, where the tumor initially shows objective growth before decreasing in size, and hyperprogression, hypothesized to be a drug-induced acceleration of the tumor burden. Despite it being >10 years since the first immune-oncology drug was approved, neither the biology behind these paradoxical responses has been well understood, nor their incidence, identification criteria, predictive biomarkers, or clinical impact have been fully described. Immune-based Response Evaluation Criteria in Solid Tumors (iRECIST) guidelines have been published as a revision to the RECIST V.1.1 criteria for use in trials of immunotherapeutics, and the iRECIST subcommittee (of the RECIST Working Group) is working on elucidating these aspects, with data sharing a current major challenge to move forward with this unmet need in immuno-oncology.

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Section: Introductionmentioning

confidence: 83%

iRECIST and atypical patterns of response to immuno-oncology drugs

Ramon-Patino

Schmid

Lau

et al. 2022

J Immunother Cancer

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“…Various software tools with different degrees of automation have been introduced to minimize misinterpretations [ 12 , 13 ]. Concepts of fully automated approaches including image interpretation and segmentation have been proposed [ 14 , 15 ] but have not been implemented in clinical trials so far.…”

Section: Introductionmentioning

confidence: 99%

Tumor Response Evaluation Using iRECIST: Feasibility and Reliability of Manual Versus Software-Assisted Assessments

Ristow,

Well,

Wiese

et al. 2024

Cancers

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Objectives: To compare the feasibility and reliability of manual versus software-assisted assessments of computed tomography scans according to iRECIST in patients undergoing immune-based cancer treatment. Methods: Computed tomography scans of 30 tumor patients undergoing cancer treatment were evaluated by four independent radiologists at baseline (BL) and two follow-ups (FU), resulting in a total of 360 tumor assessments (120 each at BL/FU1/FU2). After image interpretation, tumor burden and response status were either calculated manually or semi-automatically as defined by software, respectively. The reading time, calculated sum of longest diameter (SLD), and tumor response (e.g., “iStable Disease”) were determined for each assessment. After complete data collection, a consensus reading among the four readers was performed to establish a reference standard for the correct response assignments. The reading times, error rates, and inter-reader agreement on SLDs were statistically compared between the manual versus software-assisted approaches. Results: The reading time was significantly longer for the manual versus software-assisted assessments at both follow-ups (median [interquartile range] FU1: 4.00 min [2.17 min] vs. 2.50 min [1.00 min]; FU2: 3.75 min [1.88 min] vs. 2.00 min [1.50 min]; both p < 0.001). Regarding reliability, 2.5% of all the response assessments were incorrect at FU1 (3.3% manual; 0% software-assisted), which increased to 5.8% at FU2 (10% manual; 1.7% software-assisted), demonstrating higher error rates for manual readings. Quantitative SLD inter-reader agreement was inferior for the manual compared to the software-assisted assessments at both FUs (FU1: ICC = 0.91 vs. 0.93; FU2: ICC = 0.75 vs. 0.86). Conclusions: Software-assisted assessments may facilitate the iRECIST response evaluation of cancer patients in clinical routine by decreasing the reading time and reducing response misclassifications.

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“…1 3 Pseudoprogression has been reported in 2.8%-15.8% of patients in recent trials of anti-cytotoxic T-lymphocyte antigen 4 (CTLA4)/anti-PD-1 ICIs. [5][6][7] Following reports of pseudoprogression with ICIs, immune-response criteria were developed. 3 First, immune-related response criteria (irRC) were developed on the basis of WHO criteria, using bidimensional measurements.…”

Section: Introductionmentioning

confidence: 99%

Comparison of tumor assessments using RECIST 1.1 and irRECIST, and association with overall survival

Manitz¹,

D’Angelo

Apolo

et al. 2022

J Immunother Cancer

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BackgroundPatients treated with immune checkpoint inhibitors (ICIs) may experience pseudoprogression, which can be classified as progressive disease (PD) by Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1 and could lead to inappropriate treatment discontinuation. Immune-response criteria were developed to better capture novel response patterns seen with ICIs.MethodsWe pooled data from 1765 patients with 12 types of advanced solid tumors treated with avelumab (an anti-programmed death ligand 1 (PD-L1) monoclonal antibody) monotherapy in the JAVELIN Solid Tumor and JAVELIN Merkel 200 trials, conducted a comparative analysis of tumor assessments by investigators according to RECIST 1.1 and immune-related RECIST (irRECIST), and evaluated the correlation between progression-free survival (PFS) and overall survival (OS).ResultsIn total, 147 patients (8.3%) had a best overall response (BOR) of PD by RECIST 1.1 but had immune-related disease control by irRECIST (defined as immune-related BOR (irBOR) of immune-related stable disease or better). This discordance was seen irrespective of PD-L1 status and observed across all tumor types. Overall, PFS and immune-related PFS showed similar imputed rank correlations with OS.ConclusionsThe use of irRECIST identified a subset of patients with a BOR of PD by RECIST 1.1 but an irBOR of immune-related disease control by irRECIST with a distinctive survival curve, thereby providing more clinically relevant information than RECIST 1.1 alone. However, as a surrogate endpoint for OS in the whole population, immune-related PFS by irRECIST did not show improved predictive value compared with PFS by RECIST 1.1.

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Response evaluation for immunotherapy through semi-automatic software based on RECIST 1.1, irRC, and iRECIST criteria: comparison with subjective assessment

Cited by 12 publications

References 25 publications

iRECIST and atypical patterns of response to immuno-oncology drugs

iRECIST and atypical patterns of response to immuno-oncology drugs

Tumor Response Evaluation Using iRECIST: Feasibility and Reliability of Manual Versus Software-Assisted Assessments

Comparison of tumor assessments using RECIST 1.1 and irRECIST, and association with overall survival

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