[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab
| Autor: | Damijan Valentinuzzi, Ivana Zagar, Robert Jeraj, Jens C. Eickhoff, U Simoncic, Nina Boc, Ziga Zupancic, Andrej Studen, Martina Vrankar, Valentina Ahac, Katja Skalic, Mojca Unk |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Oncology medicine.medical_specialty Multivariate statistics Lung Neoplasms Imaging biomarker medicine.medical_treatment R895-920 Pembrolizumab Antibodies Monoclonal Humanized 030218 nuclear medicine & medical imaging 03 medical and health sciences Medical physics. Medical radiology. Nuclear medicine 0302 clinical medicine Radiomics Fluorodeoxyglucose F18 Carcinoma Non-Small-Cell Lung Positron Emission Tomography Computed Tomography Internal medicine iradiomics Biomarkers Tumor medicine Humans Radiology Nuclear Medicine and imaging radiomics analysis Lung cancer Immune Checkpoint Inhibitors Response Evaluation Criteria in Solid Tumors Aged [18f]fdg pet/ct business.industry Hazard ratio Univariate Immunotherapy Middle Aged anti-pd-1 medicine.disease non-small-cell lung cancer 030220 oncology & carcinogenesis Female Radiopharmaceuticals business Research Article |
| Zdroj: | Radiology and Oncology, Vol 54, Iss 3, Pp 285-294 (2020) Radiology and Oncology |
| ISSN: | 1581-3207 |
| Popis: | Background Immune checkpoint inhibitors have changed the paradigm of cancer treatment; however, non-invasive biomarkers of response are still needed to identify candidates for non-responders. We aimed to investigate whether immunotherapy [18F]FDG PET radiomics signature (iRADIOMICS) predicts response of metastatic non-small-cell lung cancer (NSCLC) patients to pembrolizumab better than the current clinical standards. Patients and methods Thirty patients receiving pembrolizumab were scanned with [18F]FDG PET/CT at baseline, month 1 and 4. Associations of six robust primary tumour radiomics features with overall survival were analysed with Mann-Whitney U-test (MWU), Cox proportional hazards regression analysis, and ROC curve analysis. iRADIOMICS was constructed using univariate and multivariate logistic models of the most promising feature(s). Its predictive power was compared to PD-L1 tumour proportion score (TPS) and iRECIST using ROC curve analysis. Prediction accuracies were assessed with 5-fold cross validation. Results The most predictive were baseline radiomics features, e.g. Small Run Emphasis (MWU, p = 0.001; hazard ratio = 0.46, p = 0.007; AUC = 0.85 (95% CI 0.69–1.00)). Multivariate iRADIOMICS was found superior to the current standards in terms of predictive power and timewise with the following AUC (95% CI) and accuracy (standard deviation): iRADIOMICS (baseline), 0.90 (0.78–1.00), 78% (18%); PD-L1 TPS (baseline), 0.60 (0.37–0.83), 53% (18%); iRECIST (month 1), 0.79 (0.62–0.95), 76% (16%); iRECIST (month 4), 0.86 (0.72–1.00), 76% (17%). Conclusions Multivariate iRADIOMICS was identified as a promising imaging biomarker, which could improve management of metastatic NSCLC patients treated with pembrolizumab. The predicted non-responders could be offered other treatment options to improve their overall survival. |
| Databáze: | OpenAIRE |
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