Nomogram for predicting the survival of patients with small cell carcinoma of the esophagus

Qie, Shuo; Wang, Xuefeng; Ran, Yu-Ge; Liu, Miao-Ling; Cui, Guimin; Shi, Hongyun

doi:10.1097/md.0000000000025427

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Moreover, expression of PD-L1 in TIICs was an independent and significant predictor of OS. This result is in line with other pulmonary and extrapulmonary squamous cell carcinoma studies that have previously reported that expression of PD-L1 is correlated with better prognoses 53 , 54 . We also evaluated the prognostic significance of CD8 + TILs.…”

Section: Discussionsupporting

confidence: 92%

Patterns and prognostic values of programmed cell death-ligand 1 expression and CD8+ T-cell infiltration in small cell carcinoma of the esophagus: a retrospective analysis of 34 years of National Cancer Center data in China

Zhang¹,

Zhang²,

Xue

et al. 2023

International Journal of Surgery

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Background: Small cell carcinoma of the esophagus (SCCE) is an extremely rare and highly aggressive neuroendocrine malignancy with a strikingly poor prognosis. Given the great clinical successes of checkpoint immunotherapies, we explored the expression profile and clinical significance of programmed cell death-ligand 1 (PD-L1) and CD8 + T cell in SCCE for the first time. Materials and methods: Tumor-infiltrating immune cells (TIICs) and tumor cells in postoperative, whole tumor sections from 147 SCCE patients were stained for PD-LI expression. We also evaluated each patient’s Combined Positive Score (CPS). Multiplex immunofluorescence staining (CD3, CD20, CD68, and PD-L1) was introduced to clarify the location of PD-L1. CD8 density was analyzed by digital imaging and analysis of entire slides. Clinical outcomes were tested for correlations with both PD-L1 expression and CD8 density. Results: No patients had PD-L1 expressed in their tumor cells. PD-L1 + expression in TIICs was detected in 65 patients (44.2%) and 42 (28.6%) exhibited CPS positivity. Multiplex immunofluorescence staining demonstrated that most of the PD-L1 was expressed on the CD68 + monocytes/macrophages. PD-L1 expression in the TIICs and CPS was found to be correlated with paraffin block age, tumor length, macroscopic type, T stage, and increased overall survival (OS). Expression of PD-L1 in TIICs showed significantly prolonged relapse-free survival (RFS). Increasing CD8 densities were associated with increased PD-L1 expression ( P trend <0.0001). Multivariate regression confirmed that PD-L1 in TIICs and CD8 states were independent predictors of OS, and CD8 status were found to be independently predictive of RFS. A stratification based on PD-L1 and CD8 status was also significantly associated with both OS and RFS. Conclusion: Expression of PD-L1 was only detected in TIICs from approximately half of the patients with SCCEs. In SCCEs, PD-L1 and CD8 status are novel prognostic biomarkers and may inform the implementation of risk-related therapeutic strategies. SCCEs with higher CD8 infiltration also had higher expression of PD-L1, suggesting the development of resistance against adaptive immunity. These findings support the assertion that PD-L1/programmed cell death 1 inhibitors should be investigated in this rare malignancy.

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Section: Discussionsupporting

confidence: 92%

Patterns and prognostic values of programmed cell death-ligand 1 expression and CD8+ T-cell infiltration in small cell carcinoma of the esophagus: a retrospective analysis of 34 years of National Cancer Center data in China

Zhang¹,

Zhang²,

Xue

et al. 2023

International Journal of Surgery

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“…In the evaluation of the established prediction model, predicting survivals of multiple-site EPSCCs throughout the body also has good performance (Figure 2), compared to the nomograms of seven single-site EPSCC studies, whose AUCs range from 0.656 to 0.75 (41)(42)(43)(44)(45)(46)(47). It may be because of the same pathological nature, the large sample size, and the merits of the decision tree-based algorithm.…”

Section: Discussionmentioning

confidence: 99%

“…There is still no survival model able to predict EPSCC throughout the body. There are only seven nomograms constructed on single-organ small-scale data (41)(42)(43)(44)(45)(46)(47).…”

Section: Discussionmentioning

confidence: 99%

An online tool for survival prediction of extrapulmonary small cell carcinoma with random forest

Zhang

2023

Front. Oncol.

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PurposeExtrapulmonary small cell carcinoma (EPSCC) is rare, and its knowledge is mainly extrapolated from small cell lung carcinoma. Reliable survival prediction tools are lacking.MethodsA total of 3,921 cases of EPSCC were collected from the Surveillance Epidemiology and End Results (SEER) database, which form the training and internal validation cohorts of the survival prediction model. The endpoint was an overall survival of 0.5–5 years. Internal validation performances of machine learning algorithms were compared, and the best model was selected. External validation (n = 68) was performed to evaluate the generalization ability of the selected model.ResultsAmong machine learning algorithms, the random forest model performs best on internal validation, whose area under the curve (AUC) is 0.736–0.800. The net benefit is higher than the TNM classification in decision curve analysis. The AUC of this model on the external validation cohort is 0.739–0.811. This model was then deployed online as a free, publicly available prediction tool of EPSCC (http://42.192.80.13:4399/).ConclusionThis study provides an excellent online survival prediction tool for EPSCC with machine learning and large-scale data. Age, TNM stages, and surgery (including potential performance status information) are the most critical factors for the prediction model.

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Development and validation of a prognostic nomogram model for Chinese patients with primary small cell carcinoma of the esophagus

Zhang¹,

Huang²,

Ku³

et al. 2021

WJCC

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BACKGROUND Primary small cell carcinoma of the esophagus (PSCE) is a highly invasive malignant tumor with a poor prognosis compared with esophageal squamous cell carcinoma. Due to the limited samples size and the short follow-up time, there are few reports on elucidating the prognosis of PSCE, especially on the establishment and validation of a survival prediction nomogram model covering general information, pathological factors and specific biological proteins of PSCE patients. AIM To establish an effective nomogram to predict the overall survival (OS) probability for PSCE patients in China. METHODS The nomogram was based on a retrospective study of 256 PSCE patients. Univariate analysis and multivariate Cox proportional hazards regression analysis were used to examine the prognostic factors associated with PSCE, and establish the model for predicting 1-, 3-, and 5-year OS based on the Akaike information criterion. Discrimination and validation were assessed by the concordance index (C-index) and calibration curve and decision curve analysis (DCA). Histology type, age, tumor invasion depth, lymph node invasion, detectable metastasis, chromogranin A, and neuronal cell adhesion molecule 56 were integrated into the model. RESULTS The C-index was prognostically superior to the 7 th tumor node metastasis (TNM) staging in the primary cohort [0.659 (95%CI: 0.607-0.712) vs 0.591 (95%CI: 0.517-0.666), P = 0.033] and in the validation cohort [0.700 (95%CI: 0.622-0.778) vs 0.605 (95%CI: 0.490-0.721), P = 0.041]. Good calibration curves were observed for the prediction probabilities of 1-, 3-, and 5-year OS in both cohorts. DCA analysis showed that our nomogram model had a higher overall net benefit compared to the 7 th TNM staging . CONCLUSION Our nomogram can be used to predict the survival probability of PSCE patients, which can help clinicians to make individualized survival predictions.

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Nomogram for predicting the survival of patients with small cell carcinoma of the esophagus

Cited by 4 publications

References 21 publications

Patterns and prognostic values of programmed cell death-ligand 1 expression and CD8+ T-cell infiltration in small cell carcinoma of the esophagus: a retrospective analysis of 34 years of National Cancer Center data in China

Patterns and prognostic values of programmed cell death-ligand 1 expression and CD8+ T-cell infiltration in small cell carcinoma of the esophagus: a retrospective analysis of 34 years of National Cancer Center data in China

An online tool for survival prediction of extrapulmonary small cell carcinoma with random forest

Development and validation of a prognostic nomogram model for Chinese patients with primary small cell carcinoma of the esophagus

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