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Risk prediction of second primary malignancies in patients after rectal cancer: analysis based on SEER Program.


ABSTRACT:

Background

This study will focus on exploring the clinical characteristics of rectal cancer (RC) patients with Second Primary Malignancies (SPMs) and constructing a prognostic nomogram to provide clinical treatment decisions.

Methods

We determined the association between risk factors and overall survival (OS) while establishing a nomogram to forecast the further OS status of these patients via Cox regression analysis. Finally, we evaluated the performance of the prognostic nomogram to predict further OS status.

Results

Nine parameters were identified to establish the prognostic nomogram in this study, and, the C-index of the training set and validation set was 0.691 (95%CI, 0.662-0.720) and 0.731 (95%CI, 0.676-0.786), respectively. The calibration curve showed a high agreement between the predicted and actual results, and the receiver operating characteristic (ROC) curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improved the discrimination of SPMs' prognosis.

Conclusions

We systematically explored the clinical characteristics of SPMs after RC and constructed a satisfactory nomogram.

SUBMITTER: Sun YC 

PROVIDER: S-EPMC10568885 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Risk prediction of second primary malignancies in patients after rectal cancer: analysis based on SEER Program.

Sun Yong-Chao YC   Zhao Zi-Dan ZD   Yao Na N   Jiao Yu-Wen YW   Zhang Jia-Wen JW   Fu Yue Y   Shi Wei-Hai WH  

BMC gastroenterology 20231012 1


<h4>Background</h4>This study will focus on exploring the clinical characteristics of rectal cancer (RC) patients with Second Primary Malignancies (SPMs) and constructing a prognostic nomogram to provide clinical treatment decisions.<h4>Methods</h4>We determined the association between risk factors and overall survival (OS) while establishing a nomogram to forecast the further OS status of these patients via Cox regression analysis. Finally, we evaluated the performance of the prognostic nomogra  ...[more]

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