Development and validation of a prognostic nomogram for the pre-treatment prediction of early metachronous metastasis in endemic nasopharyngeal carcinoma: a big-data intelligence platform-based analysis
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ABSTRACT: Background:
Early failure of cancer treatment generally indicates a poor prognosis. Here, we aim to develop and validate a pre-treatment nomogram to predict early metachronous metastasis (EMM) in nasopharyngeal carcinoma (NPC). Methods:
From 2009 to 2015, a total of 9461 patients with NPC (training cohort: n?=?7096; validation cohort: n?=?2365) were identified from an institutional big-data research platform. EMM was defined as time to metastasis within 2?years after treatment. Early metachronous distant metastasis-free survival (EM-DMFS) was the primary endpoint. A nomogram was established with the significant prognostic factors for EM-DMFS determined by multivariate Cox regression analyses in the training cohort. The Harrell Concordance Index (C-index), area under the receiver operator characteristic curve (AUC), and calibration curves were applied to evaluate this model. Results:
EMM account for 73.5% of the total metachronous metastasis rate and is associated with poor long-term survival in NPC. The final nomogram, which included six clinical variables, achieved satisfactory discriminative performance and significantly outperformed the traditional tumor–node–metastasis (TNM) classification for predicting EM-DMFS: C-index: 0.721 versus 0.638, p?Conclusion: Our established nomogram can reliably predict EMM in patients with NPC and might aid in formulating risk-adapted treatment decisions and personalized patient follow-up strategies.
SUBMITTER: Zhang L
PROVIDER: S-EPMC7758560 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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