[The relationship between the comprehensive blood inflammation indexes and stage I pneumoconiosis and its combined lung infections].

Objective: To analyze the comprehensive blood inflammation index of the patients with stage I pneumoconiosis complicated with pulmonary infection, and to explore its value in predicting the patients' disease. Methods: In September 2023, 83 patients with stage I pneumoconiosis who were treated in Tianjin Occupational Diseases Precaution and Therapeutic Hospital from November 2021 to August 2023 were selected and divided into non-infected group (56 cases) and infected group (27 cases) according to whether they were combined with lung infection. Workers with a history of dust exposure but diagnosed without pneumoconiosis during the same period were selected as the control group (65 cases) . By referring to medical records and collecting clinical data such as gender, age, occupational history, past medical history, hematology testing, the differences in the comprehensive blood inflammation indexes among the three groups were compared, ROC curve was drawn, and the relationship between comprehensive blood inflammation indexes and stage I pneumoconiosis and its combined lung infection was analyzed. Results: There were significtant differences in the number of neutrophils (N) , the number of lymphocytes (L) , the number of monocytes (M) , C-reactive protein (CRP) , the neutrophil to lymphocyte ratio (NLR) , the monocyte to lymphocyte ratio (MLR) , the platelet to lymphocyte ratio (PLR) , the systemic immune-inflammatory index (SII) , the systemic inflammation response index (SIRI) , the aggregate index of systemic inflammation (AISI) , the derived neutrophil to lymphocyte ratio (dNLR) , the neutrophil to lymphocyte and platelet ratio (NLPR) , and the C-reactive protein to lymphocyte ratio (CLR) (P<0.05) . Compared with the control group, MLR, SIRI and AISI in the non-infected group were significantly increased (P<0.05) . NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR, CLR were significantly increased (P<0.05) . Compared with the non-infected group, NLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR were significantly increased in the infected group (P<0.05) . ROC analysis showed that NLR, MLR, PLR, SII, SIRI and AISI had a certain predictive capability for stage I pneumoconiosis (P<0.05) , among which MLR had the highest efficacy, with an AUC of 0.791 (95% CI: 0.710-0.873) , the cut-off value was 0.18, the sensitivity was 71.4%, and the specificity was 78.5%. NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR all had a certain predictive capability forstage I pneumoconiosis combined lung infection (P<0.05) , among which CLR had the highest efficacy, with an AUC of 0.904 (95%CI: 0.824~0.985) , the cut-off value was 5.33, sensitivity was 77.8%, specificity was 98.2%. Conclusion: The comprehensive blood inflammation index may be an auxiliary predictor of stage I pneumoconiosis and its combined lung infections.

Clinical significance of systemic inflammation response index and platelet-lymphocyte ratio in patients with adenocarcinoma of the esophagogastric junction and upper gastric cancer.

Background: Tumor immunity plays an important role in assessing the tumor progression. The purpose of this study was to investigate the prognostic value of combined systemic inflammation response index (SIRI) and platelet-lymphocyte ratio (PLR) of gastroesophageal junction cancer (AEG) and upper gastric cancer (UGC) patients. Methods: In this retrospective study, patients from 2003 to 2014 were divided into training and validation sets. The prognostic accuracy of each variable was compared using time-independent ROC analysis. The scoring system was calculated by cut-off values of SIRI and PLR in 5-year. Kaplan-Meier and Log-rank tests were used to analyze overall survival (OS). Chi-square test was used to analyze the association between clinical characteristics and the scoring system. Univariate and multivariate analyses based on the competitive risk regression model were used to analyze independent predictors of death due to AGC and UGC. R software was used to construct the Nomogram model of risk assessment. Results: Patients with SIRI-PLR = 2 had worse survival time than those with 0 and 1 (P < 0.001) and more suitable for postoperative adjuvant chemotherapy (P = 0.002). High PLR patients were more suitable for proximal gastrectomy (P = 0.049). SIRI-PLR were independent predictors in training set (P < 0.001), which could be combined with age, pTNM stage and postoperative chemotherapy to construct Nomogram for predicting OS. Conclusions: Preoperative SIRI-PLR score was an independent predictor for patients with AEG and UGC. The Nomogram model constructed by age, SIRI-PLR, pTNM stage and postoperative chemotherapy can correctly predict the prognosis of patients.