Lymph Node Ratio Improves Prediction of Overall Survival in Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy: A National Cancer Database Analysis

Is postoperative adjuvant radiotherapy necessary for patients with esophageal cancer after neoadjuvant chemoradiotherapy? An analysis based on the SEER database

OBJECTIVES

To evaluate the outcomes of adjuvant radiotherapy in patients with esophageal cancer (EC) who underwent esophagectomy following neoadjuvant chemoradiotherapy (NCRT).

METHODS

The data of EC patients who received adjuvant therapy after NCRT between 2004 to 2019 was retrieved from the SEER database. The patients were split into the adjuvant radiotherapy with or without chemotherapy (RT±CT) and the adjuvant chemotherapy (CT) groups. The process of propensity score matching (PSM) was employed.

RESULTS

Following PSM, 157 patients in total were recruited in each treatment group. There were no significant variations in either overall survival (OS) or cancer-specific survival (CSS) between the RT±CT and CT groups (median OS: 28 months versus. 51 months, p=0.063; median CSS: 31 months versus. 52 months, p=0.16). Within the CT group, patients with ypI/II or cI/II tumor stage, positive lymph node ratio (LNR) ≤0.1, and tumor size ≥50 mm (p<0.05) had higher OS compared to the RT±CT groups. Among patients with cT3-4 tumors in N-stage downstaging group, the OS and CSS were significantly greater for those underwent RT±CT as opposed to the CT group (5-year OS:56.6% versus 19.4%, p=0.042; 5-year CSS:67.9% versus. 19.4%, p=0.023). Multivariate Cox regression analysis identified the tumor histology grade as an independent prognostic factor of OS and CSS.

CONCLUSION

Radiotherapy-based adjuvant therapy does not significantly improve the prognosis of EC patients after NCRT, although it may provide a survival benefit for patients with cT3-4 tumors in N-stage downstaging.

Association of Lymph Nodes Positive Rate With the Risk of Recurrence in Patients With Stage T1 Papillary Thyroid Cancer

The incidence of lymph node metastasis in papillary thyroid carcinoma (PTC) is common and a significant risk factor for local recurrence; however, its impact on recurrence patterns among low-risk patients remains uncertain. We aimed to elucidate the effect of metastatic lymph node on recurrence type. The medical records of 1209 patients with stage T1 PTC who underwent unilateral thyroidectomy with ipsilateral central lymph node dissection were retrospectively analyzed. The study first identified risk factors for different types of recurrence and then categorized patients as high or low risk based on their lymph node positive ratio (LNPR). The diagnostic accuracy of LNPR in predicting recurrence was compared using receiver operating characteristic (ROC) curve analysis, while differences in recurrence-free survival were assessed using the Kaplan-Meier method. During follow-up, a total of 502 (41.5%) patients had central lymph node metastasis and 52 (4.3%) patients experienced recurrence. Notably, LNPR was significantly higher in relapsed patients compared to nonrelapsed patients, with mean values of 0.45 and 0.23, respectively (P < .001). The recurrence rate of residual thyroid did not differ significantly across different T stages (P = .679), N stages (P = .415), or LNPR risk groups (P = .175). However, the recurrence rate of lymph nodes showed a significant correlation with LNPR (P < .001). The area under the ROC curves for LNPR risk stratification at 5 and 10 years were approximately 0.691 and 0.634, respectively, both of which outperformed N stage. The findings underscore the significance of LNPR's reliability as a prognostic indicator for local lymph node recurrence in patients diagnosed with T1 stage PTC.

Prognostic value of lymph node ratio in patients with non-metastatic cervical cancer treated with radical hysterectomy: A population-based study

BACKGROUND

The lymph node ratio (LNR) is an emerging prognostic biomarker in multiple malignancies. This study aimed to explore the prognostic role of LNR in patients with non-metastatic cervical cancer undergoing radical hysterectomy.

METHODS

Data were extracted from the SEER 17 registry. Univariate and multivariate Cox analyses were performed to identify the prognostic factors associated with cancer-specific survival (CSS). A nomogram was constructed to predict the 5-year and 10-year CSS. Survival analyses stratified by the status of LNR and different adjuvant treatments were performed using the Kaplan-Meier method.

RESULTS

A total of 8128 female patients with non-metastatic cervical cancer who underwent radical hysterectomy and regional node examination (≥8) were enrolled. Of these, 1269 (15.6%) were confirmed as lymph node-positive. Cox regression analyses showed that age, race, tumor size, tumor grade, histology, and LNR were significant factors affecting CSS. A nomogram was developed for predicting the 5-year and 10-year CSS, which showed good discrimination and calibration. Patients without lymph node involvement had inferior CSS with adjuvant treatments compared to those who did not receive further treatment. In patients with LNR ≤10%, only those receiving adjuvant radiotherapy had a trend of better CSS. In patients with an LNR between 10% and 30% and more than 30%, concurrent radiochemotherapy (CCRT) proved to be the best treatment.

CONCLUSIONS

LNR is an independent prognostic factor in patients with non-metastatic cervical cancer undergoing radical hysterectomy. For patients with negative lymph nodes, no further treatment is recommended. Patients with positive lymph nodes could benefit more from CCRT.

Online tools to predict individualised survival for primary oesophageal cancer patients with and without pathological complete response after neoadjuvant therapy followed by oesophagectomy: development and external validation of two independent nomograms

OBJECTIVE

This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy.

DESIGN

Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models.

RESULTS

In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.

CONCLUSIONS

The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.

A new lymph node ratio-based staging system for rectosigmoid cancer: a retrospective study with external validation

BACKGROUND

This study evaluated the clinical value of a new American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging prediction model based on lymph node ratio (LNR) in rectosigmoid cancer (RSC).

METHODS

The analysis included 1444 patients with nonmetastatic RSC diagnosed pathologically between 2010 and 2016 who were collected from the National Cancer Institute Surveillance, Epidemiology, and Results database. The AJCC N-stage was redefined according to the LNR cutoff point, and the ability of the new staging system to predict prognosis was compared with that of the AJCC TNM staging system. Data from 739 patients from our hospital were used for external validation.

RESULTS

According to the number of examined lymph nodes and LNR, the N stage was divided into five groups (LNR0-5). The 5-year OS of patients divided according to the new T lymph node ratio M (TLNRM) staging into stage I (T1LNR1, T1LNR2), IIA (T1LNR3, T2LNR1, T2LNR2, T2LNR3, T1LNR4, T3LNR1), IIB (T2LNR4), IIC (T3LNR2, T4a LNR1, T1LNR5), IIIA (T3LNR3, T2LNR5, T4b LNR1, T4a LNR2, T3LNR4), IIIB (T3LNR5, T4a LNR3, T4a LNR4, T4b LNR2), and IIIC (T4b LNR3, T4a LNR5, T4b LNR4, T4b LNR5) was significantly different ( P <0.05). Decision curve analysis showed that the net income of the new TLNRM staging system for different decision thresholds was higher than the prediction line of the traditional eighth TNM staging system. The smaller Akaike information criterion and Bayesian information suggested that the new staging system had a higher sensitivity for predicting prognosis than the traditional staging system. TLNRM II and III patients benefited from adjuvant chemotherapy, while adjuvant chemotherapy did not improve the prognosis of TNM II patients. These findings were confirmed by the external validation data.

CONCLUSION

The new TLNRM staging system was superior to the eighth edition AJCC staging system for staging and predicting the prognosis of patients with RSC and may become an effective tool in clinical practice.

The minimum number of examined lymph nodes was 24 for optimal survival of pathological T2-4 gastric cancer: a multi-center, hospital-based study covering 20 years of data

INTRODUCTION

The current National Comprehensive Cancer Network (NCCN) guidelines recommend that at least 16 lymph nodes should be examined for gastric cancer patients to reduce staging migration. However, there is still debate regarding the optimal management of examined lymph nodes (ELNs) for gastric cancer patients. In this study, we aimed to develop and test the minimum number of ELNs that should be retrieved during gastrectomy for optimal survival in patients with gastric cancer.

METHODS

We used the restricted cubic spline (RCS) to identify the optimal threshold of ELNs that should be retrieved during gastrectomy based on the China National Cancer Center Gastric Cancer (NCCGC) database. Northwest cohort, which sourced from the highest gastric cancer incidence areas in China, was used to verify the optimal cutoff value. Survival analysis was performed via Kaplan-Meier estimates and Cox proportional hazards models.

RESULTS

In this study, 12,670 gastrectomy patients were included in the NCCGC cohort and 4941 patients in the Northwest cohort. During 1999-2019, the average number of ELNs increased from 17.88 to 34.45 nodes in the NCCGC cohort, while the number of positive lymph nodes remained stable (5-6 nodes). The RCS model showed a U-curved association between ELNs and the risk of all-cause mortality, and the optimal threshold of ELNs was 24 [Hazard ratio (HR) = 1.00]. The ELN ≥ 24 group had a better overall survival (OS) than the ELN < 24 group clearly (P = 0.003), however, with respect to the threshold of 16 ELNs, there was no significantly difference between the two groups (P = 0.101). In the multivariate analysis, ELN ≥ 24 group was associated with improved survival outcomes in total gastrectomy patients [HR = 0.787, 95% confidence interval (CI): 0.711-0.870, P < 0.001], as well as the subgroup analysis of T2 patients (HR = 0.621, 95%CI: 0.399-0.966, P = 0.035), T3 patients (HR = 0.787, 95%CI: 0.659-0.940, P = 0.008) and T4 patients (HR = 0.775, 95%CI: 0.675-0.888, P < 0.001).

CONCLUSION

In conclusion, the minimum number of ELNs for optimal survival of gastric cancer with pathological T2-4 was 24.

GNB1 promotes hepatocellular carcinoma progression by targeting BAG2 to activate P38/MAPK signaling

G-proteins are intracellular partners of G-protein-coupled receptors. As a member of the G-protein family, GNB1 has been shown to play a pro-cancer role in lung cancer and breast cancer. However, the biological function and detailed mechanisms of GNB1 in hepatocellular carcinoma progression are unclear. In this study, we investigated the effects of GNB1 and its possible mechanism of action in hepatocellular carcinoma (HCC). The clinical significance of GNB1 was evaluated in a large cohort of HCC patients, showing that GNB1 was overexpressed in HCC compared to adjacent normal liver tissues, and increased GNB1 expression was associated with poor prognosis. We also demonstrated that GNB1 enhances cell proliferation, colony formation, and cell migration and invasion in vitro and promotes the epithelial-to-mesenchymal transition process in HCC cells. Tumor xenograft model assay confirmed the oncogenic role of GNB1 in tumorigenicity in nude mice. Activation of P38 signaling was found in the GNB1 overexpressed HCC cells. Further intervention of P38 confirmed it as an important signaling pathway for the oncogenic role of GNB1 in HCC. Moreover, co-immunoprecipitation followed by liquid chromatograph-mass spectrometry identified that GNB1 exerted oncogenic functions via the interaction of BAG2 and activated P38 signaling pathway. Together, our results reveal that GNB1 plays a pivotal oncogenic role in HCC by promoting the P38 pathway via cooperating with BAG2. GNB1 may serve as a prognostic biomarker for patients with HCC.

The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy

Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the evaluation of efficacy after NAT for EC lacks accurate and uniform criteria. Radiomics is a multi-parameter quantitative approach for developing medical imaging in the era of precision medicine and has provided a novel view of medical images. As a non-invasive image analysis method, radiomics is an inevitable trend in NAT efficacy prediction and prognosis classification of EC by analyzing the high-throughput imaging features of lesions extracted from medical images. In this literature review, we discuss the definition and workflow of radiomics, the advances in efficacy prediction after NAT, and the current application of radiomics for predicting efficacy after NAT.

A retrospective cohort study on the association between early coagulation disorder and short-term all-cause mortality of critically ill patients with congestive heart failure

Purpose

Coagulation disorder in congestive heart failure (CHF) has been well-documented. The prognostic value of a composite coagulation disorder score, which combines the absolute platelet count, international normalized ratio (INR), and activated partial thromboplastin time (APTT), has not been assessed in CHF. The present study endeavored to explore the association between the coagulation disorder score and adverse outcomes of critically ill patients with CHF.

Methods

Patients diagnosed with CHF in the Medical Information Mart for Intensive Care III (MIMIC-III) database were included in the present retrospective cohort study. The coagulation disorder score was calculated according to the abnormalities of the absolute platelet count, INR, and APTT within 24 h after intensive care unit admission. The primary outcomes were the short-term all-cause mortality, including 30-, 90-day and in-hospital mortalities. The Kaplan-Meier (K-M) survival curve and the Cox proportional hazard model were performed to assess the correlation between coagulation disorder score and outcome events.

Results

A total of 6,895 patients were enrolled in this study and divided into four groups according to the coagulation disorder score. K-M survival curve preliminarily indicated that subjects with higher coagulation disorder score presented lower survival rate and shorter survival time. After adjustment for potential confounders, the multivariate Cox analysis further illustrated that elevated coagulation disorder score as a quartile variable was significantly associated with increased all-cause mortality (quartile 4 vs. quartile 1, 30-day: HR [95% CI], 1.98 [1.50, 2.62], 90-day: HR [95% CI], 1.88 [1.49, 2.37], in-hospital: HR [95%CI], 1.93 [1.42, 2.61]).

Conclusion

In critically ill patients with CHF, ones with high coagulation disorder score tend to be worse clinical prognosis, which would be a promising biomarker and helpful for the management of CHF patients.

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Background

The prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram’s precision was verified by the C-index, calibration curves, and AUC. Kaplan–Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram.

Results

Compared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan–Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC.

Conclusion

We analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.