Unknown

Dataset Information

0

Early risk-assessment of patients with nasopharyngeal carcinoma: the added prognostic value of MR-based radiomics.


ABSTRACT:

Objectives

To assess the additive prognostic value of MR-based radiomics in predicting progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC) METHODS: Patients newly diagnosed with non-metastatic NPC between June 2006 and October 2019 were retrospectively included and randomly grouped into training and test cohorts (7:3 ratio). Radiomic features (n=213) were extracted from T2-weighted and contrast-enhanced T1-weighted MRI. The patients were staged according to the 8th edition of American Joint Committee on Cancer Staging Manual. The least absolute shrinkage and selection operator was used to select the relevant radiomic features. Univariate and multivariate Cox proportional hazards analyses were conducted for PFS, yielding three different survival models (clinical, stage, and radiomic). The integrated time-dependent area under the curve (iAUC) for PFS was calculated and compared among different combinations of survival models, and the analysis of variance was used to compare the survival models. The prognostic performance of all models was validated using a test set with integrated Brier scores.

Results

This study included 81 patients (training cohort=57; test cohort=24), and the mean PFS was 57.5 ± 43.6 months. In the training cohort, the prognostic performances of survival models improved significantly with the addition of radiomics to the clinical (iAUC, 0.72-0.80; p=0.04), stage (iAUC, 0.70-0.79; p=0.001), and combined models (iAUC, 0.76-0.81; p<0.001). In the test cohort, the radiomics and combined survival models were robustly validated for their ability to predict PFS.

Conclusion

Integration of MR-based radiomic features with clinical and stage variables improved the prediction PFS in patients diagnosed with NPC.

SUBMITTER: Kim MJ 

PROVIDER: S-EPMC8319024 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC10689317 | biostudies-literature
| S-EPMC8683387 | biostudies-literature
| S-EPMC8803696 | biostudies-literature
| S-EPMC9364026 | biostudies-literature
| S-EPMC4637632 | biostudies-literature
| S-EPMC7506153 | biostudies-literature
| S-EPMC6639299 | biostudies-literature
| S-EPMC11365615 | biostudies-literature
| S-EPMC7068812 | biostudies-literature
| S-EPMC10514983 | biostudies-literature