Abstract 2888
Background
In various types of solid tumor, pathological microscopic features can be used as prognostic biomarkers. We intended to develop a pathological microscopic features (PMFs) pattern for individual survival assessment in patients with nasopharyngeal carcinoma (NPC).
Methods
We retrospectively included 1229 patients with NPC who had received radical radiotherapy with/without chemotherapy. The PMFs differently digitized were extracted using the software QuPath (version 0.1.2.Queen’s University Belfast, Belfast, Northern Ireland, UK) in the training cohort (Guangzhou training cohort, n = 739) to bulid a pathological feature classifier using a penalized regression model. The prognostic accuracy of the pathological feature classifier was validated in the internal validation cohort (Guangzhou validation cohort, n = 316) and one external validation cohort (Chenzhou validation cohort, n=170).The primary end point was progression-free survival (PFS) and distant metastasis-free survival (DMFS).
Results
We found 143 PMFs in the H&E image of NPC with the whole slide image (WSI) scanning. In the training cohort a pathological micromarker of survival risk in NPC (PMSRN) that consisted of 14 PMFs was generated to classify patients into high-risk and low-risk groups. Patients with high-risk scores in the training cohort had shorter PFS (HR 2.16, 1.61 -2.89; p = 0.000), and DMFS (HR 1.87, 1.27 -2.75; p = 0.001) than patients with low-risk scores. We developed a nomogram based on the PMSRN and other variables that predicted an individual’s survival risk and the c-index of this nomogram (C-index=0.759, 95% CI: 0.717 -0.801) was equal to other nomograms. Furthermore, among patients with high-risk scores in the combined training and internal cohorts, ICT had better PFS to those who received CCRT alone (p = 0.033), whereas those with low-risk scores ICT had similar PFS to CCRT alone (p = 0.363). These results were validated in the internal external validation cohort.
Conclusions
The PMSRN is a reliable prognostic tool for survival risk in NPC patients and might be able to predict which patients need to receive ICT or not. It might guide treatment decisions for NPC patients.
Clinical trial identification
ChiECRCT20190034.
Editorial acknowledgement
Legal entity responsible for the study
Sun Yet-sen University Cancer Center.
Funding
National Natural Science Foundation of China.
Disclosure
All authors have declared no conflicts of interest.
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