Nasopharyngeal cancer in non-endemic areas: Impact of treatment intensity within a large retrospective multicentre cohort

European Journal of Cancer ◽

10.1016/j.ejca.2021.09.005 ◽

2021 ◽

Vol 159 ◽

pp. 194-204

Author(s):

Paolo Bossi ◽

Annalisa Trama ◽

Alice Bernasconi ◽

Salvatore Grisanti ◽

Issa Mohamad ◽

...

Keyword(s):

Nasopharyngeal Cancer ◽

Treatment Intensity ◽

Endemic Areas ◽

Multicentre Cohort

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Nasopharyngeal Cancer in Non-Endemic Areas: Impact of Treatment Intensity within a Large Retrospective Multicenter Cohort

SSRN Electronic Journal ◽

10.2139/ssrn.3812378 ◽

2021 ◽

Author(s):

Paolo Bossi ◽

Annalisa Trama ◽

Alice Bernasconi ◽

Salvatore Grisanti ◽

Issa Mohamad ◽

...

Keyword(s):

Nasopharyngeal Cancer ◽

Treatment Intensity ◽

Multicenter Cohort ◽

Endemic Areas

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Baseline MRI-Radiomics Can Predict Overall Survival in Non-Endemic EBV-Related Nasopharyngeal Carcinoma Patients

Cancers ◽

10.3390/cancers12102958 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2958

Author(s):

Marco Bologna ◽

Valentina Corino ◽

Giuseppina Calareso ◽

Chiara Tenconi ◽

Salvatore Alfieri ◽

...

Keyword(s):

Overall Survival ◽

Clinical Features ◽

Cox Regression ◽

Nasopharyngeal Cancer ◽

Mri Imaging ◽

Prognostic Information ◽

Free Survival ◽

Clinical Endpoints ◽

Endemic Areas ◽

Magnetic Resonance Imaging Mri

Advanced stage nasopharyngeal cancer (NPC) shows highly variable treatment outcomes, suggesting the need for independent prognostic factors. This study aims at developing a magnetic resonance imaging (MRI)-based radiomic signature as a prognostic marker for different clinical endpoints in NPC patients from non-endemic areas. A total 136 patients with advanced NPC and available MRI imaging (T1-weighted and T2-weighted) were selected. For each patient, 2144 radiomic features were extracted from the main tumor and largest lymph node. A multivariate Cox regression model was trained on a subset of features to obtain a radiomic signature for overall survival (OS), which was also applied for the prognosis of other clinical endpoints. Validation was performed using 10-fold cross-validation. The added prognostic value of the radiomic features to clinical features and volume was also evaluated. The radiomics-based signature had good prognostic power for OS and loco-regional recurrence-free survival (LRFS), with C-index of 0.68 and 0.72, respectively. In all the cases, the addition of radiomics to clinical features improved the prognostic performance. Radiomic features can provide independent prognostic information in NPC patients from non-endemic areas.

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