Dataset Information

Development and Validation of Web-Based Nomograms to Precisely Predict Survival Outcomes of Non-metastatic Nasopharyngeal Carcinoma in an Endemic Area.

ABSTRACT:

Purpose

This study aimed to develop web-based nomograms to precisely predict survival outcomes in patients with non-metastatic nasopharyngeal carcinoma (NPC) in an endemic area.

Materials and methods

A total of 10,126 patients who underwent radical intensity-modulated radiotherapy at Sun Yat-sen University Cancer Center (SYSUCC) from 2009 to 2015 were analyzed. We assigned patients into a training cohort (SYSUCC-A, n=6,751) and an internal validation cohort (SYSUCC-B, n=3,375) based on computer-generated random numbers. Patients collected from Wuzhou Red Cross Hospital (WZRCH) between 2012 and 2015 were used as the independent external validation cohort (WZRCH, n=450). Concordance index (C-index) was used to determine predictive accuracy and discriminative ability for the nomogram. The web-based clinicopathologic prediction models for predicting survival were based on Cox regression.

Results

The C-indexes for SYSUCC-A, SYSUCC-B, and WZRCH cohorts for the established nomograms to predict 3-year overall survival (OS) was 0.736, 0.715, and 0.691. Additionally, C-indexes to predict 3-year distant metastasis-free survival (DMFS) was 0.717, 0.706, and 0.686, disease-free survival (DFS) was 0.713, 0.697, and 0.656, local relapse-free survival was 0.695, 0.684, and 0.652, and regional relapse-free survival was 0.672, 0.650, and 0.616. The calibration plots showed great agreement between nomogram-predicted 3-year survival outcomes and actual 3-year survival outcomes. Moreover, C-indexes of the nomograms for OS, DMFS, and DFS were significantly superior than TNM stage (p< 0.001 for all).

Conclusion

These user-friendly nomograms can precisely predict survival endpoints in patients with non-metastatic NPC. They may serve as a useful tool for providing patient counseling and help physicians to make individual follow-up plans.

SUBMITTER: Yao JJ

PROVIDER: S-EPMC8291181 | biostudies-literature |

REPOSITORIES: biostudies-literature

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