TY - JOUR
T1 - A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors
AU - Ligero, Marta
AU - Garcia-Ruiz, Alonso
AU - Viaplana, Cristina
AU - Villacampa, Guillermo
AU - Raciti, Maria V.
AU - Landa, Jaid
AU - Matos, Ignacio
AU - Martin-Liberal, Juan
AU - Ochoa-De-Olza, Maria
AU - Hierro, Cinta
AU - Mateo, Joaquin
AU - Gonzalez, Macarena
AU - Morales-Barrera, Rafael
AU - Suarez, Cristina
AU - Rodon, Jordi
AU - Elez, Elena
AU - Braña, Irene
AU - Muñoz-Couselo, Eva
AU - Oaknin, Ana
AU - Fasani, Roberta
AU - Nuciforo, Paolo
AU - Gil, Debora
AU - Rubio-Perez, Carlota
AU - Seoane, Joan
AU - Felip, Enriqueta
AU - Escobar, Manuel
AU - Tabernero, Josep
AU - Carles, Joan
AU - Dienstmann, Rodrigo
AU - Garralda, Elena
AU - Perez-Lopez, Raquel
N1 - Publisher Copyright:
© RSNA, 2021
PY - 2021/4
Y1 - 2021/4
N2 - 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 6 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years 6 12; 37 men) and 47 patients (cohort 3: mean age, 64 years 6 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years 6 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.
AB - 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 6 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years 6 12; 37 men) and 47 patients (cohort 3: mean age, 64 years 6 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years 6 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.
UR - http://www.scopus.com/inward/record.url?scp=85103474148&partnerID=8YFLogxK
U2 - 10.1148/RADIOL.2021200928
DO - 10.1148/RADIOL.2021200928
M3 - Article
C2 - 33497314
AN - SCOPUS:85103474148
SN - 0033-8419
VL - 299
SP - 109
EP - 119
JO - Radiology
JF - Radiology
IS - 1
ER -