Nomogram Predicting the Likelihood of Parametrial Involvement in Early-Stage Cervical Cancer: Avoiding Unjustified Radical Hysterectomies

Development and validation of nomogram models for predicting overall survival and cancer-specific survival in gastric cancer patients with liver metastases: a cohort study based on the SEER database

OBJECTIVE

To establish nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of gastric cancer liver metastasis (GCLM) patients.

METHODS

Data from the Surveillance, Epidemiology, and End Results (SEER) database for 5,451 GCLM patients diagnosed between 2010 and 2015 were analyzed. The cohort was divided into a training set (3,815 cases) and an internal validation set (1,636 cases). External validation included 193 patients from the Fourth Hospital of Hebei Medical University and 171 patients from the People's Hospital of Shijiazhuang City, spanning 2016-2018. Multivariable Cox regression analysis identified eight independent prognostic factors for OS and CSS in GCLM patients, including age, histological type, grade, tumor size, surgery, chemotherapy, bone metastasis, and lung metastasis. Two nomogram models were developed based on these factors and evaluated using time-dependent receiver operating characteristic curve analysis, calibration curves, and decision curve analysis.

RESULTS

Internal validation showed that the nomogram models outperformed the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system in predicting 1-year, 2-year, and 3-year OS and CSS in GCLM patients (1-year OS: 0.801 vs. 0.593, P < 0.001; 1-year CSS: 0.807 vs. 0.598, P < 0.001; 2-year OS: 0.803 vs. 0.630, P < 0.001; 2-year CSS: 0.802 vs. 0.633, P < 0.001; 3-year OS: 0.824 vs. 0.691, P < 0.001; 3-year CSS: 0.839 vs. 0.692, P < 0.001).

CONCLUSION

This study developed and validated nomogram models using SEER database data to predict OS and CSS in GCLM patients. These models offer improved prognostic accuracy over traditional staging systems, aiding in clinical decision-making.

Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters

Objective

The purpose of this study was to evaluate the prognostic value of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with operable cervical cancer, and on this basis, combined with classical clinicopathological parameters to predict the recurrence of patients.

Methods

A total of 1580 patients with stage IA-IIA cervical cancer were randomly divided into training cohort (n=1054) and validation cohort (n=526) according to the predefined ratio of 2:1. In the training cohort, the receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of HALP score for predicting cervical cancer recurrence. On this basis, the independent related factors with cervical cancer recurrence were screened through univariate and multivariate Cox regression analysis, and then a nomogram model was further established. The internal and external validation of the model was carried out in the training cohort and the validation cohort respectively through the consistency index (C-index) and calibration curve.

Results

ROC curve and Youden index showed that the optimal threshold of HALP score for predicting cervical cancer recurrence was 39.50. Multivariate analysis confirmed that HALP score and some other classic clinicopathological parameters were independently associated with cervical cancer recurrence. Based on the results of multivariate analysis, a nomogram model for predicting cervical cancer recurrence was successfully constructed. The internal and external calibration curves showed that the fitting degree of the model was good, and the C-index (the C-index of the training cohort and the validation cohort were 0.862 and 0.847, respectively) showed that the prediction accuracy of the model proposed in this study was better than other similar models.

Conclusion

HALP score may be a novel predictor for predicting the cervical cancer recurrence. Nomogram model based on HALP score and classical clinicopathological parameters can better predict the recurrence of cervical cancer.

Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer

Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien-Dindo classification (CDC) has been applied in a variety of surgical fields. This study is designed to evaluate the complications after robot-assisted radical hysterectomy (RRH) for cervical cancer using CDC and further establish a prediction model. This is a study on the development of prediction model based on retrospective data. Patients with cervical cancer who received RRH treatment in our hospital from January 2016 to April 2019 were invited to participate in the study. The demographic data, laboratory and imaging examination results and postoperative complications were collected, and the logistic regression model was applied to analyze the risk factors possibly related to complications to establish a prediction model. 753 patients received RRH. The overall incidence of complications was 32.7%, most of which were grade I and grade II (accounting for 30.6%). The results of multivariate analysis showed that the preoperative neoadjuvant chemotherapy (OR = 1.693, 95%CI: 1.210-2.370, P = 0.002), preoperative ALT (OR = 1.028, 95%CI: 1.017-1.039, P < 0.001), preoperative urea nitrogen (OR = 0.868, 95%CI: 0.773-0.974, P = 0.016), preoperative total bilirubin (OR = 0.958, 95%CI: 0.925-0.993, P = 0.0.018), and preoperative albumin (OR = 0.937, 95%CI: 0.898-0.979, P = 0.003) were related to the occurrence of postoperative complications. The area under the curve (AUC) of receiver-operating characteristic (ROC) in the prediction model of RRH postoperative complications established based on these five factors was 0.827 with 95% CI of 0.794-0.860. In patients undergoing robot-assisted radical hysterectomy for cervical cancer, preoperative ALT level, urea nitrogen level, total bilirubin level, albumin level, and neoadjuvant chemotherapy were significantly related to the occurrence of postoperative complications. The regression prediction model established on this basis showed good prediction performance with certain clinical promotion and reference value.

What are the determinants of parametrial invasion in patients with early stage cervical cancer: A cross sectional study

Introduction

There was an increase in number of patients presented with early-stage cervical cancer (CC). Tumors with favorable pathological features might be candidates for less radical surgery.

Methods

We retrospectively reviewed 700 patients with histologically confirmed CC between January 2011 and March 2020. Chi-square, Fisher's exact tests and multivariate logistic regression analysis were used to assess relations between parametrial involvement (PI) and clinic-pathological variables.

Results

Total number of 132 patients with stage IA to IIA were eligible to participate. Squamous cell carcinoma was reported in 100 (75.8%) patients, adenocarcinoma and other tumor pathologies were found in 24(18.2%) and 8(6.1%), respectively. Considering the 2018 FIGO stage, 11 (8.4%) patients had IA, 111 (83%%) IB and 10 (7.6%) IIA. Nine patients (6.8%) had PI on permanent pathologic report. Univariate analysis demonstrated that following variables were statistically different between patients with and without PI: age ≥50, tumor size ≥ 3 cm, lower segment involvement, poorly differentiated pathology, deep stromal invasion, pelvic lymph node, lympho-vascular involvement and positive surgical margin (all p values < 0.05). Among these variables only tumor size ≥3 cm (OR: 2.1, 95% CI: 1.11–4.16, p value: 0.02), deep stromal invasion (OR: 2.2, 95% CI: 1.9–7.43, p value: 0.02) and positive surgical margin (OR: 5.1, 95% CI: 3.97–11.15, p value: 0.008) were independent risk factor of PI in multivariate analysis.

Conclusions

Early stage CC might be surgically approached in a more conservative manner if patients have tumor size <3 cm and do not have deep stromal invasion in conization.

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The parametrium was resected, in order to remove occult disease at the time of extirpation of the primary cervical lesion.

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This study revealed, tumor size, deep stromal invasion and surgical margin were independent risk factors for parametrial invasion.

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Selected patients in early stages of cervical cancer are possible candidates to undergo a more conservative approach.

Lymph Node Involvement in Early-Stage Cervical Cancer: Is Lymphangiogenesis a Risk Factor? Results from the MICROCOL Study

Simple Summary

The prognosis of cervical cancer is significantly influenced by lymph node involvement. The lymphatic system is the primary way of metastasis for cervical carcinoma, and lymph-vascular space invasion (LVSI) is considered the most important risk factor for pelvic lymph node metastasis (PLNM). Previous studies have not clarified the correlation between lymphangiogenesis and an increased risk of metastasis and tumor recurrence. The evaluation and identification of several markers of lymphangiogenesis may identify patients with high risk of PLNM. Our findings suggest that the lymphatic spread does not required the proliferation of new lymphatic endothelial cells. These results emphasize the importance of pre-existing peritumoral lymphatic vessels in the metastatic process in early cervical cancer.

Abstract

Background: In patients with cervical cancer, the presence of tumoral lymph-vascular space invasion (LVSI) is the main risk factor for pelvic lymph node metastasis (PLNM). The objective of this study was to evaluate the presence of several markers of lymphangiogenesis in early-stage cervical cancer and their correlation with PLNM and tumoral recurrence. Materials and Methods: Seventy-five patients with early-stage cervical carcinoma underwent sentinel lymph node (SLN) sampling in association with complete pelvic lymph node dissection. Primary tumors were stained with the following markers: Ki67, D2-40, CD31 and VEGF-C. A 3-year follow-up was performed to evaluate the disease-free survival. Results: Overall, 14 patients (18.6%) had PLNM. Positive LVSI was seen in 29 patients (38.6%). There was a significant correlation between LVSI evidenced by H/E staining and PLNM (p < 0.001). There was no correlation between high Ki67, CD31, D2-40, and VEGF-C staining with PLNM or tumor recurrence. Conclusions: Our data support that lymphatic spread does not require the proliferation of new lymphatic endothelial cells in early-stage cervical cancer. These results emphasize the importance of pre-existing peritumoral lymphatic vessels in the metastatic process in early cervical cancer. None of the markers of lymphangiogenesis and proliferation assessed in this study were predictive of PLNM or recurrence.