Blood biomarkers as predictors of pathological lymph node metastasis in clinical stage T1N0 esophageal squamous cell carcinoma

Radiomics-clinical nomogram for preoperative lymph node metastasis prediction in esophageal carcinoma

OBJECTIVES

This research aimed to develop a radiomics-clinical nomogram based on enhanced thin-section CT radiomics and clinical features for the purpose of predicting the presence or absence of metastasis in lymph nodes among patients with resectable esophageal squamous cell carcinoma (ESCC).

METHODS

This study examined the data of 256 patients with ESCC, including 140 cases with lymph node metastasis. Clinical information was gathered for each case, and radiomics features were derived from thin-section contrast-enhanced CT with the help of a 3D slicer. To validate risk factors that are independent of the clinical and radiomics models, least absolute shrinkage and selection operator logistic regression analysis was used. A nomogram pattern was constructed based on the radiomics features and clinical characteristics. The receiver operating characteristic curve and Brier Score were used to evaluate the model's discriminatory ability, the calibration plot to evaluate the model's calibration, and the decision curve analysis to evaluate the model's clinical utility. The confusion matrix was used to evaluate the applicability of the model. To evaluate the efficacy of the model, 1000 rounds of 5-fold cross-validation were conducted.

RESULTS

The clinical model identified esophageal wall thickness and clinical T (cT) stage as independent risk factors, whereas the radiomics pattern was built based on 4 radiomics features chosen at random. Area under the curve (AUC) values of 0.684 and 0.701 are observed for the radiomics approach and clinical model, respectively. The AUC of nomogram combining radiomics and clinical features was 0.711. The calibration plot showed good agreement between the incidence of lymph node metastasis predicted by the nomogram and the actual probability of occurrence. The nomogram model displayed acceptable levels of performance. After 1000 rounds of 5-fold cross-validation, the AUC and Brier score had median values of 0.702 (IQR: 0.65, 7.49) and 0.21 (IQR: 0.20, 0.23), respectively. High-risk patients (risk point >110) were found to have an increased risk of lymph node metastasis [odds ratio (OR) = 5.15, 95% CI, 2.95-8.99] based on the risk categorization.

CONCLUSION

A successful preoperative prediction performance for metastasis to the lymph nodes among patients with ESCC was demonstrated by the nomogram that incorporated CT radiomics, wall thickness, and cT stage.

ADVANCES IN KNOWLEDGE

This study demonstrates a novel radiomics-clinical nomogram for lymph node metastasis prediction in ESCC, which helps physicians determine lymph node status preoperatively.

Prognostic factors for esophageal squamous cell carcinoma without pathological lymph node metastasis after neoadjuvant therapy and surgery

BACKGROUND

Pathological lymph node metastasis (LNM) following multimodal therapy is an important indicator of poor prognosis in patients with esophageal cancer. However, a significant number of patients without LNM are still at high risk for recurrence.

METHODS

We assessed prognostic factors in 143 patients without pathological LNM who were diagnosed with locally advanced esophageal squamous cell carcinoma (ESCC) and underwent neoadjuvant chemotherapy (NAC) or chemoradiotherapy (NACRT), followed by surgery.

RESULTS

Using univariate and multivariate analyses of recurrence-free survival, carcinoembryonic antigen (CEA) levels (hazard ratio [HR]: 2.17, 95% confidence interval [CI]: 1.12-4.23, and p = 0.02) and neutrophil-to-lymphocyte ratio (NLR) (HR: 1.22, 95% CI: 1.04-1.43, and p = 0.02) were significant independent covariates. Furthermore, pretherapeutic LNM (HR: 1.94, 95% CI: 1.003-3.76, and p = 0.049), NACRT (HR: 3.29, 95% CI: 1.30-8.33, and p = 0.01), poorly differentiated tumors (HR: 2.52, 95% CI: 1.28-4.98, and p = 0.01), and lymphovascular invasion (LVI) (HR: 2.78, 95% CI: 1.27-6.09, and p = 0.01) were also significant independent covariates. The recurrence rates among patients with 0/1, 2, 3, and 4/5 poor prognostic factors were significantly different (5.0%, 25.0%, 35.7%, and 53.8%, respectively; p = 0.001); the survival rates were stratified among these prognostic groups.

CONCLUSIONS

Pretherapeutic CEA and NLR levels, pretherapeutic LNM, NACRT, poorly differentiated tumors, and LVI were significantly correlated with survivals in patients without pathological LNM after neoadjuvant therapy and surgery. Postoperative therapy should be considered in patients with ESCC with several indicators of recurrence, even in those without pathological LNM who underwent surgery following neoadjuvant therapy.

Eosinophil Levels, Neutrophil-Lymphocyte Ratio, and Platelet-Lymphocyte Ratio in the Cytokine Storm Period of Patients with COVID-19

BACKGROUND

In the early stages of the COVID-19 pandemic, elevated inflammatory cytokine levels, particularly interleukin-6 (IL-6), were detected in patients with cytokine storm (CS).

AIMS

This study aimed to investigate levels, diagnostic usefulness, and optimal cutoff values of monocyte, eosinophil, neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) in CS of patients with COVID-19 and also to identify risk factors for mortality.

METHODS

Seventy-six patients with COVID-19 who developed CS and randomly chosen 150 COVID-19 patients who had no CS during their stay in the hospital were included in the study.

RESULTS

Lymphocytes and eosinophil levels remained lower in the CS group. Patients with low lymphocyte levels had a higher risk for mortality (OR: 1.92). Neutrophil, D-dimer, ferritin, IL-6, NLR, and PLR were higher in the CS group. High levels of neutrophil, ferritin, D-dimer, and NLR and a history of coronary artery disease (CAD) and diabetes mellitus (DM) were identified as independent risk factors for mortality.

CONCLUSION

In the light of the obtained results, COVID-19 patients with a decrease in lymphocyte levels and an increase in NLR and D-dimer levels and a history of CAD and DM have a higher risk of cytokine storm and mortality.