Dataset Information

Proposal of a Nomogram for Predicting Survival in Patients with Siewert Type II Adenocarcinoma of the Esophagogastric Junction After Preoperative Radiation.

ABSTRACT:

Background

Preoperative radiotherapy tends to be more frequently used for patients with adenocarcinoma of the esophagogastric junction (AEG); however, the prognostic values of postoperative pathologic characteristics in these patients remain unclear. This study aimed to examine the outcomes in Siewert type II AEG patients receiving preoperative radiotherapy to identify the predictive factors for overall survival (OS).

Methods and results

A total of 1818 AEG patients undergoing preoperative radiotherapy were reviewed. Univariate analyses showed that age, sex, histology, tumor grade, positive lymph node (PLN), lymph node ratio, and log odds of positive lymph nodes (LODDS) were significantly correlated with OS; however, only age, grade, PLN, and LODDS were identified as independent risk factors in a multivariate regression model. Subsequently, patients were randomly grouped into training and validation cohorts (1:1 ratio), and the beta coefficients of these variables in the training set were used to generate the nomogram. The composite nomogram showed improved prognostic accuracy in the training, validation, and entire cohorts compared with that of TNM stage alone.

Conclusions

In conclusion, our proposed nomogram represents a promising tool for estimating OS in Siewert type II AEG patients after preoperative radiotherapy.

SUBMITTER: Liu F

PROVIDER: S-EPMC6456486 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Proposal of a Nomogram for Predicting Survival in Patients with Siewert Type II Adenocarcinoma of the Esophagogastric Junction After Preoperative Radiation.

Liu Feng F Zhou Rui R Jiang Funeng F Liu Guolong G Li Kangbao K Zhu Guodong G

Annals of surgical oncology 20190225 5

<h4>Background</h4>Preoperative radiotherapy tends to be more frequently used for patients with adenocarcinoma of the esophagogastric junction (AEG); however, the prognostic values of postoperative pathologic characteristics in these patients remain unclear. This study aimed to examine the outcomes in Siewert type II AEG patients receiving preoperative radiotherapy to identify the predictive factors for overall survival (OS).<h4>Methods and results</h4>A total of 1818 AEG patients undergoing pre ...[more]

PMID: 30805805

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Project description:PurposeWe developed and validated a CT-based radiomics nomogram to predict HER2 status in patients with adenocarcinoma of esophagogastric junction (AEG).MethodA total of 101 patients with HER2-positive (n=46) and HER2-negative (n=55) esophagogastric junction adenocarcinoma (AEG) were retrospectively analyzed. They were then randomly divided into a training cohort (n=70) and a verification cohort (n=31). The radiomics features were obtained from the portal phase of the CT enhanced scan. We used the least absolute shrinkage and selection operator (LASSO) logistic regression method to select the best radiomics features in the training cohort, combined them linearly, and used the radiomics signature formula to calculate the radiomics score (Rad-score) of each AEG patient. A multivariable logistic regression method was applied to develop a prediction model that incorporated the radiomics signature and independent risk predictors. The prediction performance of the nomogram was evaluated using the training and validation cohorts.ResultIn the training (P<0.001) and verification groups (P<0.001), the radiomics signature combined with seven radiomics features was significantly correlated with HER2 status. The nomogram composed of CT-reported T stage and radiomics signature showed very good predictive performance for HER2 status. The area under the curve (AUC) of the training cohort was 0.946 (95% CI: 0.919-0.973), and that of the validation group was 0.903 (95% CI: 0.847-0.959). The calibration curve of the radiomics nomogram showed a good degree of calibration. Decision-curve analysis revealed that the radiomics nomogram was useful.ConclusionThe nomogram CT-based radiomics signature combined with CT-reported T stage can better predict the HER2 status of AEG before surgery. It can be used as a non-invasive prediction tool for HER2 status and is expected to guide clinical treatment decisions in clinical practice, and it can assist in the formulation of individualized treatment plans.

Dataset Information

Proposal of a Nomogram for Predicting Survival in Patients with Siewert Type II Adenocarcinoma of the Esophagogastric Junction After Preoperative Radiation.

Background

Methods and results

Conclusions

Publications

Proposal of a Nomogram for Predicting Survival in Patients with Siewert Type II Adenocarcinoma of the Esophagogastric Junction After Preoperative Radiation.

Similar Datasets

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