| Literature DB >> 33497314 |
Marta Ligero1, Alonso Garcia-Ruiz1, Cristina Viaplana1, Guillermo Villacampa1, Maria V Raciti1, Jaid Landa1, Ignacio Matos1, Juan Martin-Liberal1, Maria Ochoa-de-Olza1, Cinta Hierro1, Joaquin Mateo1, Macarena Gonzalez1, Rafael Morales-Barrera1, Cristina Suarez1, Jordi Rodon1, Elena Elez1, Irene Braña1, Eva Muñoz-Couselo1, Ana Oaknin1, Roberta Fasani1, Paolo Nuciforo1, Debora Gil1, Carlota Rubio-Perez1, Joan Seoane1, Enriqueta Felip1, Manuel Escobar1, Josep Tabernero1, Joan Carles1, Rodrigo Dienstmann1, Elena Garralda1, Raquel Perez-Lopez1.
Abstract
Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.Entities:
Year: 2021 PMID: 33497314 DOI: 10.1148/radiol.2021200928
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105