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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.


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 < 0.001; AUC: 0.730 versus 0.644, p < 0.001. The calibration curves showed excellent agreement between the predicted and actual EM-DMFS. The nomogram can stratify patients into three risk groups with distinct EM-DMFS (2-year DMFS: 96.8% versus 90.1% versus 80.3%, p < 0.001). A validation cohort supported the results. The three identified risk groups are correlated with the efficacy of different treatment regimens.

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 LL 

PROVIDER: S-EPMC7758560 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

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.

Zhang Lu-Lu LL   Xu Fei F   He Wen-Ting WT   Huang Meng-Yao MY   Song Di D   Li Yi-Yang YY   Deng Qi-Ling QL   Huang Yong-Shi YS   Wang Ting T   Shao Jian-Yong JY  

Therapeutic advances in medical oncology 20201221


<h4>Background</h4>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).<h4>Methods</h4>From 2009 to 2015, a total of 9461 patients with NPC (training cohort: <i>n</i> = 7096; validation cohort: <i>n</i> = 2365) were identified from an institutional big-data research platform. EMM was defined as time to metastasis within 2 years after t  ...[more]

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