Dataset Information

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer.

ABSTRACT:

Background

This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.

Methods

We performed a retrospective analysis of 541 patients diagnosed with lung cancer between January 2016 and December 2017 at the Pneumology Department of Dazhou Central Hospital. Serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA153, CA199, CA724, cytokeratin 19 fragment (CYFRA), and neuron-specific enolase (NSE) levels were quantified in each patient at the time of lung cancer diagnosis. Metastasis was confirmed by computed tomography, and/or positron emission tomography, and/or surgery or other necessary methods. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the performance of the model.

Results

Of the 541 patients eligible for final analysis, 253 were detected with metastasis and 288 were detected without metastasis. Compared with those in nonmetastatic patients, the serum CEA, CA125, CA199, CA153, CYFRA, and NSE levels were notably higher in metastatic patients (P < .05). The ROC curve demonstrated that the CEA-CA125-CA199-CA153-CYFRA-NSE-CA724 combination based on the cut-off value had an optimal area under the curve and specificity in assessing tumor metastasis. The decision tree model is a convenient and valuable tool for guiding the appropriate application of our model to assess metastasis in lung cancer patients.

Conclusions

Our study suggested that the nomogram of the regression model is valuable for assessing tumor metastasis in newly diagnosed lung cancer patients before traditional standard methods are used. These findings could aid in the evaluation of metastasis in the clinic.

SUBMITTER: Wang J

PROVIDER: S-EPMC7402813 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Publications

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer.

Wang Jiasi J Chu Yanpeng Y Li Jie J Zeng Fanwei F Wu Min M Wang Tingjie T Sun Liangli L Chen Qianlai Q Wang Pingxi P Zhang Xiuqin X Zeng Fanxin F

Cancer medicine 20200614 15

<h4>Background</h4>This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.<h4>Methods</h4>We performed a retrospective analysis of 541 patients diagnosed with lung cancer between January 2016 and December 2017 at the Pneumology Department of Dazhou Central Hospital. Serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA153, CA199, CA724, cytokeratin 19 fragment (CYFRA), and neuron-specific e ...[more]

PMID: 32536037

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Dataset Information

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer.

Background

Methods

Results

Conclusions

Publications

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer.

Similar Datasets

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