Publication date: August 2017
Source:Oral Oncology, Volume 71
Author(s): Dan Ou, Pierre Blanchard, Silvia Rosellini, Antonin Levy, France Nguyen, Ralph T.H. Leijenaar, Ingrid Garberis, Philippe Gorphe, François Bidault, Charles Ferté, Charlotte Robert, Odile Casiraghi, Jean-Yves Scoazec, Philippe Lambin, Stephane Temam, Eric Deutsch, Yungan Tao
ObjectivesTo explore prognostic and predictive value of radiomics in patients with locally advanced head and neck squamous cell carcinomas (LAHNSCC) treated with concurrent chemoradiotherapy (CRT) or bioradiotherapy (BRT).Materials and MethodsData of 120 patients (CRT vs. BRT matched 2:1) were retrospectively analyzed. A total of 544 radiomics features of the primary tumor were extracted from radiotherapy planning computed tomography scans. Cox proportional hazards models were used to examine the association between survival and radiomics features with false discovery rate correction. The discriminatory performance was evaluated using receiver operating characteristic curve analysis.ResultsMultivariate analysis showed a 24-feature based signature significantly predicted for OS (HR=0.3, P=0.02) and progression-free survival (PFS) (HR=0.3, P=0.01). Combining the radiomics signature with p16 status showed a significant improvement of prognostic performance compared with p16 (AUC=0.78vs. AUC=0.64 at 5years, P=0.01) or radiomics signature (AUC=0.78vs. AUC=0.67, P=0.01) alone. When patients were stratified according to this combination, OS and PFS were significantly different according to the 4 sub-types (p16+ with low/high signature score; p16− with low/high signature score) (P<0.001). Patients with high signature score significantly benefited from CRT (vs. BRT) in terms of OS (P=0.004), while no benefit from CRT in patients with low signature score.ConclusionOur analysis suggests an added value of radiomics features as prognostic and predictive biomarker in HNSCC treated with CRT/BRT. Moreover, the radiomics signature provided additional information to HPV/p16 status to further stratify patients. External validation of such findings is mandatory given the risk of overfitting.
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