Objective To evaluate the clinical application value of four inflammatory indices [monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR)] in predicting postoperative mortality risk in patients with Siewert type Ⅱ esophagogastric junction adenocarcinoma, and to explore the predictive performance of four inflammatory indices. Methods This retrospective study collected clinical data from 310 patients with Siewert typeⅡ esophagogastric junction adenocarcinoma who were admitted to the Second Hospital of Lanzhou University between October 2016 and March 2023, and met the inclusion and exclusion criteria. Univariate analysis was used to initially screen variables related to postoperative mortality risk. The variance inflation factor (VIF) analysis was performed to assess multicollinearity issues, and multivariate regression analysis was used to further reveal the independent effects of key variables on postoperative mortality risk. The performance of the predictive models was evaluated using receive operatior characteristic curves and Kaplan-Meier survival analysis, and the effects of different inflammatory indices on patient survival were explored. Finally, machine learning methods such as Light GBM, random forest, support vector machine (SVM), and XGBoost were used to evaluate the predictive performance of the four inflammatory indices. Results The four inflammatory indices were significantly associated with postoperative mortality risk in patients with Siewert type Ⅱ esophagogastric junction adenocarcinoma (MLR: HR=2.6884, 95% CI 1.4559 to 4.9642, P=0.002; PLR: HR=1.0022, 95% CI1.0001 to 1.0043, P=0.041; SII: HR=1.0003, 95% CI1.0001 to 1.0006, P=0.002; NLR: HR=1.0697, 95% CI 1.0277 to 1.1134, P=0.001). Machine learning model results showed that NLR had the best performance in the random forest model, with an AUC of 0.863 in the training set and an AUC of 0.834 in the test set. Conclusion Preoperative clinical indicators, especially the NLR inflammatory factor, are of significant importance in predicting the postoperative mortality risk of patients with Siewert typeⅡ esophagogastric junction adenocarcinoma.
ObjectiveTo analyze the factors affecting the prognosis of patients with primary tracheal malignancy, and establish a nomogram model for prediction its prognosis.MethodsA total of 557 patients diagnosed with primary tracheal malignancy from 1975 to 2016 in the Surveillance, Epidemiology, and End Results Data were collected. The factors affecting the overall survival rate of primary tracheal malignancy were screened and modeled by univariate and multivariate Cox regression analysis. The nomogram prediction model was performed by R 3.6.2 software. Using the C-index, calibration curves and receiver operating characteristic (ROC) curve to evaluate the consistency and predictive ability of the nomogram prediction model.ResultsThe median survival time of 557 patients with primary tracheal malignancy was 21 months, and overall survival rates of the 1-year, 3-year and 5-year were 59.1%±2.1%, 42.5%±2.1%, and 35.4%±2.2%. Univariate and multivariate Cox regression analysis showed that age, histology, surgery, radiotherapy, tumor size, tumor extension and the range of lymph node involvement were independent risk factors affecting the prognosis of patients with primary tracheal malignancy (P<0.05). Based on the above 7 risk factors to establish the nomogram prediction model, the C-index was 0.775 (95%CI 0.751-0.799). The calibration curve showed that the prediction model established in this study had a good agreement with the actual survival rate of the 1 year, 3 year and 5 years. The area under curve of 1-year, 3-year and 5-year predicting overall survival rates was 0.837, 0.827 and 0.836, which showed that the model had a high predictive power.ConclusionThe nomogram prediction model established in this study has a good predictive ability, high discrimination and accuracy, and high clinical value. It is useful for the screening of high-risk groups and the formulation of personalized diagnosis and treatment plans, and can be used as an evaluation tool for prognostic monitoring of patients with primary tracheal malignancy.
Objectives
To evaluate the effect of preoperative body mass index (BMI) on the perioperative and long-term results in esophageal squamous cell cancer patients.
Method
We retrospectively analyzed the clinical data of 503 patients with esophageal cancer between January 2001 and December 2009. There were 268 males and 235 females with the median age of 57 years ranging from 32-88 years. The associations between preoperative BMI and clinic patholo-gical characteristics were assessed by using the χ2 or Fisher's exact test. Survival analysis was performed by Kaplan-Meier curves with log-rank tests.
ResultsThe 1-year, 3-year, 5-year, and 10-year overall survival rate for the entire cohort of patients was 64.0%, 49.0%, 43.0%, and 41.0% respectively. The occurance rates of weight loss, lymph node metastases, and poorly differentiated tumorigenesis represented statistically higher in patients with BMI≤18.5 kg/m2 than those in the patients with BMI>18.5 kg/m2 (P=0.026, P=0.006, P=0.048). For the cohort, the Kaplan-Meier survival analysis showed a significant trend toward a decreased survival in esophageal cancer patients with underweight (P=0.001). No statistical difference in overall complication, anastomotic leakage, and pulmonary complication rate was detected among the different BMI classes(P=0.162, P=0.590, P=0.376). Univariate and multivariate analysis showed that the drinking status, pathological stage, and underweight were the independent prognostic factors.
ConclusionsAfter esophagectomy, BMI is not associated with the incidence of postoperative complications in patients. Patients with underweight are usually diagnosed with advanced stage, therefore tend to have poorer survivals than those with normal or over-weight.
In order to achieve the automatic identification of liver cancer cells in the blood, the present study adopted a principal component analysis (PCA) and back propagation (BP) algorithm of feedforward neural networks to identify white blood cells and red blood cells in mice and human liver cancer cells, HepG2. The present paper shows the process in which PCA was carried out after obtaining spectral data by fiber confocal back-scattering spectrograph, selecting the first two principal components as spectral features, and establishing a neural network pattern recognition model with two input layer nodes, eleven hidden layer nodes and three output nodes. In order to verify whether the model would give accurate identification of cells, we chose 195 object data to train the model with 150 sets of data as training set and 45 sets as test set. According to the results, the overall recognition accuracy of the three cells was above 90% with the average relative deviation only 4.36%. The results showed that PCA+BP algorithm could automatically identify liver cancer cells from erythrocyte and white blood cells, which will provide a useful tool for the study of metastasis and biological metabolism characteristics of liver cancer.
Objective
To compare lymph node sampling (LN-S) and lobe-specific lymph node dissection (L-SLD) in the clinical efficacy and safety for early-stage non-small cell lung cancer (NSCLC).
Methods
PubMed, Medline, EMbase, Web of Science and The Cochrane Library databases were searched up to March 2017 for English language studies. We collected randomized controlled trials (RCTs) and cohort studies (CS) which used the systematic mediastinal lymph node dissection (SMLD) and LN-S or L-SLD for the treatment of NSCLC. Direct meta-analysis was performed using RevMan 5.3 software and indirect meta-analysis with ITC software after two researchers screened the literature, extracted the data and evaluated the risk of bias independently.
Results
A total of 18 articles were included (4 RCTs and 14 CS, and 10 714 patients). Meta-analysis results showed that in the CS, compared with the the SMLD group, overall survival increased in the L-SLD group (HR=0.99, 95%CI 0.78 to 1.25, P=0.92), and overall survival decreased in the LN-S group with significant difference in CS (HR=1.43, 95%CI 1.17 to 1.75, P=0.000 4), but was not statistically significant in RCT (P=0.35). In terms of disease-free survival, there was no significant difference between the SMLD group and the LN-S group (HR=1.25, 95%CI 0.90, 1.62, P=0.10) as well as the L-SLD group (HR=1.15, 95%CI 0.92 to 1.43, P=0.23) in the CS. There was no significant difference in the local recurrence rate or distant metastasis rate between the non-systematic lymph node dissection (NSMLD) and SMLD in CS and RCTs (CS: P=0.43, P=0.39; RCT: P=0.43, P=0.10). There was no significant difference in the postoperative complications between NSMLD and SMLD in the CS (OR=0.79, 95%CI0.58 to 1.09, P=0.15) and RCTs (OR=0.36, 95%CI 0.09 to 1.45, P=0.15). Indirect meta-analysis showed that risk of death decreased by 31% and risk of recurrence by 35% in the L-SLD group compared with the LN-S group (HR=0.69, 95% CI 0.51 to 0.95, P=0.46; HR=0.65, 95% CI 0.65 to 1.30, P=0.72), but the difference was not statistically significant.
Conclusion
For early-stage NSCLC, L-SLD is not statistically different from SMLD in terms of survival; however, the overall survival of LN-S is lower than that of systematic lymphadenectomy. Indirect meta-analysis shows that L-SLD reduces the risk of death and recurrence risk compared with LN-S. There is no evidence to support both direct comparison of the prognosis of LN-S and L-SLD, therefore further prospective studies are still needed to verify.
ObjectiveTo systematically review the postoperative recovery of lung function in patients with early stage non-small cell lung cancer (NSCLC) after different operation, such as lobectomy versus segmentectomy and video-assisted thoracoscopic surgery (VATS) versus traditional open chest surgery.MethodsClinical studies about effect of different surgical methods on lung function in patients with early NSCLC were searched from PubMed, EMbase, The Cochrane Library, CBM and CNKI databases from inception to October 1st, 2016. Two researchers independently screened literature, extracted data and evaluated the risk of bias of included studies, and then meta-analysis was conducted by RevMan 5.3 and MetaAnalyst software.ResultsA total of 25 studies involving 2 924 patients were included. The results of meta-analysis showed that: compared with lobectomy group, one-second rate difference (ΔFEV1%) (MD=–0.03, 95%CI –0.03 to –0.03, P<0.001) and predictive value of forced vital capacity difference (ΔFVC%) (MD=–0.09, 95%CI –0.11 to –0.06, P<0.001) of preoperative to postoperative in segmentectomy group were higher. However, there was no significant difference between two groups in first second forced expiratory volume difference (ΔFEV1) (MD=0.01, 95%CI –0.10 to 0.11, P=0.92). Compared with thoracotomy group, VATS group had lower ΔFEV1 (MD=–0.19, 95%CI –0.27 to –0.10, P<0.0001), ΔFVC (MD=–0.20, 95%CI –0.37 to –0.03, P=0.02), ΔFEV1% (MD=–0.03, 95%CI –0.06 to –0.01, P<0.001) of preoperative to postoperative (≤3 months), and maximum minute ventilation (ΔMVV) (MD=–5.59, 95%CI –10.38 to –1.52, P=0.008) of preoperative to postoperative (≥6 months). However, there were no statistically significant differences in difference of carbon monoxide diffusion rate (ΔDLCO%) (MD=–0.04, 95%CI –0.09 to 0.02, P=0.16), ΔFEV1% (MD=–0.02, 95%CI –0.06 to 0.02, P=0.32) and ΔFEV1 (MD=1.13, 95%CI –0.92 to 3.18, P=0.28).ConclusionThe protective effect of segmentectomy on postoperative pulmonary function is better than that of lobectomy. VATS has a protective effect on the ventilation function within 3 months and 6 months after surgery. Due to limited quantity and quality of included studies, the above conclusions are needed to be validated by more high quality studies.
Objective
To introduce a simple preoperative risk score for esophageal cancer (PRSEC) and its relationship with the prognosis of patients who underwent resection of esophageal carcinoma.
Methods
We retrospectively analyzed the clinical data of 498 patients receiving resection of esophageal carcinoma between 2005 and 2015 in our hospital. They were divided into three groups (PRSEC1, PRSEC2 and PRSEC3 groups) according to the results of PRSEC (revised cardiac risk index, model for end-stage liver disease score and pulmonary function test). Their overall survival (OS) and disease-free survival (DFS) were measured to find the relationship between the PRSEC and prognosis of patients.
Results
The mortality, morbidity, DFS and OS were correlative with the PRSEC. Therefore the PRSEC can be used to predict the short-term outcome. The patients with score 2 or 3 had higher risk of mortality and morbidity than those with score 1. In addition, the DFS and OS of patients with higher score were shorter (P<0.001).
Conclusion
The PRSEC is easy and efficient and can predict the morbidity, mortality, and long-term outcomes for the patients with resection of esophageal carcinoma.
