Dataset Information

Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy.

ABSTRACT:

Background

A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT.

Methods

We identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were randomly selected and designated as training data set, and the remaining patients (n=476) were defined as external validation set. Nomogram was established by the training set and validated by the validation set.

Results

According to the results of the multivariate analysis, a nomogram combined with age at diagnosis, sex, tumor location, yp-T stage, yp metastatic lymph node ratio stage (yp-mLNRS), and grade was developed. The C-index of the model was significantly higher than that of yp-TNM staging system (0.62, 95% CI, 0.58 to 0.66 vs 0.55, 95% CI, 0.51 to 0.60; p<0.001). Calibration plots of the nomogram showed that the probability of DSS rates optimally corresponded to the survival rates were observed.

Conclusion

The proposed nomogram resulted in more reliable DSS prediction for nMEC patients in general population, regardless of the patient's histological type. Upon validation, it will aid in individualized survival prediction and prove useful in clinical decision making in nMECs after pRT.

SUBMITTER: Xie K

PROVIDER: S-EPMC6152601 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy.

Xie Kenan K Liu Song S Liu Jianjun J

Cancer management and research 20180918

<h4>Background</h4>A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT.<h4>Methods</h4>We identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were ...[more]

PMID: 30271214

Similar Datasets

Project description:BackgroundImmunoscore, as a prognostic tool defined to quantify in situ immune cell infiltrates, appears to be superior to the TNM staging system. In esophageal squamous cell carcinoma (ESCC), no immunoscore has been established; however, in situ tumor immunology is recognized as highly important. Our study aimed to construct a comprehensive immunoprofile for ESCC.MethodsThe infiltration of four immune cell types (CD8+/CD4+/Foxp3+/CD33+ cells), the expression of both inhibitory (PD-1/PD-L1/Tim-3/LAG-3) and stimulatory checkpoints (OX-40/ICOS), and IDO1 were evaluated by IHC staining and multi-color immunofluorescence in two independent cohorts (95 patients in the primary cohort and 55 patients in the validation cohort). The association with patients' overall survival was analyzed by the Kaplan-Meier method and the Cox model. Nomogram-based immunoprofile was established using the independent prognostic variables. To determine its predictive accuracy and discriminatory capacity, the C-index and calibration curve were calculated.ResultsSignificant correlation of PD-L1 expression in tumor cells with PD-1+ T cell infiltration was found (P = 0.035), indicating the activation of the inhibitory PD-1/PD-L1 pathway in ESCC cases. More PD-L1+ ICs, Tim-3+ ICs and LAG-3+ ICs were found in the CD8-rich tumor microenvironment, which is in accordance with the feedback nature of immune system. After adjustment by TNM stage, four immune variables including the infiltration of CD8+/Foxp3+/CD33+ cells and the PD-L1 expression by tumor cells were selected to construct a prognostic nomogram. The calibration curves showed good accuracy of the nomogram for survival prediction. To overcome the complexity of applying a nomogram in a clinical setting, a simple immunoprofile was then established according to the points of each factor from the nomogram. Our immunoprofile model could separate same-stage patients into different risk subgroups, and showed superior accuracy for survival prediction than the TNM staging system based on the C-index calculation and ROC analysis.ConclusionsOur nomogram-based immunoprofile can provide more accurate prognosis prediction and is an important complement to the TNM staging system for operable ESCC patients.

Dataset Information

Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy.

Background

Methods

Results

Conclusion

Publications

Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets