Preoperative inflammation-based scores predict early recurrence after lung cancer resection

Prognostic significance of systemic immune inflammatory index in NSCLC: a meta-analysis

Aim: The aim of this meta-analysis was to investigate the relationship between the baseline systemic immune inflammatory index (SII) and prognosis in patients with NSCLC. Materials & methods: The relation between pretreatment SII and overall survival, disease-free survival, cancer-specific survival, progression-free survival and recurrence-free survival in NSCLC patients was analyzed combined with hazard ratio and 95% CI. Results: The results showed that high SII was significantly correlated with overall survival and progression-free survival of NSCLC patients, but not with disease-free survival, cancer-specific survival and recurrence-free survival. Conclusion: The study suggests that a higher SII has association with worse prognosis in NSCLC patients. PROSPERO registration number: CRD42022336270.

Association between Preoperative C-Reactive Protein-to-Albumin Ratio and Mortality after Plastic and Reconstructive Surgery

Background: Prognostic markers have not been extensively studied in plastic and reconstructive surgery. Objective: We aimed to evaluate the prognostic value of preoperative C-reactive protein (CRP)-to-albumin ratio (CAR) in plastic and reconstructive surgery and to compare it with the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and modified Glasgow prognostic score (mGPS). Methods: From January 2011 to July 2019, we identified 2519 consecutive adult patients who were undergoing plastic and reconstructive surgery with available preoperative CRP and albumin levels. The receiver operating characteristic (ROC) curve was generated to evaluate predictability and estimate the threshold. The patients were divided according to this threshold, and the risk was compared. The primary outcome was one-year mortality, and the overall mortality was also analyzed. Results: The one-year mortality was 4.9%. The CAR showed an area under the ROC curve of 0.803, which was higher than those of NLR, PLR, and mGPS. According to the estimated threshold of 1.05, the patients were divided into two groups; 1585 (62.9%) were placed in the low group, and 934 (37.1%) were placed in the high group. After inverse probability weighting, the mortality rate during the first year after plastic and reconstructive surgery was significantly increased in the high group (1.3% vs. 10.9%; hazard ratio, 2.88; 95% confidence interval, 2.17-3.83; p < 0.001). Conclusions: In this study, high CAR was significantly associated with one-year mortality of patients after plastic and reconstructive surgery. Further studies are needed on prognostic markers in plastic and reconstructive surgery.

Prognostic evaluation of stage I lung adenocarcinoma based on systematic inflammatory response

BACKGROUND

This study aimed to construct an effective nomogram based on the clinical and laboratory characteristics to predict the prognosis of stage I lung adenocarcinoma with EGFR alteration.

METHODS

A retrospective study was performed of 913 eligible patients with EGFR alteration after surgery at Shanghai Pulmonary Hospital. The peripheral blood indicators were included in the nomogram. Calibration plots, concordance index, decision curve analysis, and X-tile software were used in this study. Recurrence-free survival (RFS) and overall survival were estimated by the Kaplan-Meier method and compared using the log-rank test.

RESULTS

Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio were independent risk factors for RFS. The calibration curves for RFS probabilities showed good agreement between the nomogram prediction and actual observation. Furthermore, the nomogram, including neutrophil to lymphocyte ratio and platelet to lymphocyte ratio had a higher concordance index (0.732, 95% confidence interval = 0.706 to 0.758) than that without neutrophil to lymphocyte ratio or platelet to lymphocyte ratio (0.713, 95% confidence interval = 0.686 to 0.740), and decision curve analysis plots showed that the nomogram with neutrophil to lymphocyte ratio and platelet to lymphocyte ratio had better clinical practicability. Additionally, the patients were divided into 2 groups according to cutoff values of risk points, and statistically significant differences in RFS and overall survival were observed between the high-risk and low-risk groups (P < .001).

CONCLUSIONS

High pretreatment levels of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio were strongly associated with a worse prognosis in stage I EGFR-altered lung adenocarcinomas. Besides, the proposed nomogram with neutrophil to lymphocyte ratio and platelet to lymphocyte ratio presented a better prediction ability for the survival of those patients.

Nomogram combining clinical and radiological characteristics for predicting the malignant probability of solitary pulmonary nodules measuring ≤ 2 cm

Background

At present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm.

Method

In this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA).

Result

A total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714-0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647-0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice.

Conclusion

We developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources.

Prognostic value of preoperative modified Glasgow prognostic score in surgical non-small cell lung cancer: A meta-analysis

Background and purpose

The predictive role of modified Glasgow prognostic score (mGPS) for long-term survival in several types of cancers has been well manifested. We supposed that preoperative mGPS might also be associated with long-term survival of operated non-small cell lung cancer (NSCLC) patients. The aim of this meta-analysis was to identify the prognostic value of preoperative mGPS in surgical NSCLC patients.

Methods

The PubMed, Web of Science, EMBASE and CNKI databases were searched for relevant studies up to November 7, 2022. The primary and secondary outcomes were overall survival (OS) and disease-free survival (DFS), respectively. The hazard ratios (HRs) and 95% confidence intervals (CIs) were combined.

Results

A total of 3,803 patients from 11 studies were enrolled and analyzed. The combined results demonstrated elevated preoperative mGPS was significantly related to poorer OS (HR = 2.11, 95% CI: 1.83-2.44, P < 0.001) and DFS (HR = 1.70, 95% CI: 1.42-2.03, P < 0.001). Subgroup analysis for the OS further identified the predictive role of elevated preoperative mGPS for worse OS in NSCLC.

Conclusion

Preoperative mGPS was significantly associated with prognosis in NSCLC and patients with elevated preoperative mGPS experienced poorer long-term survival.

Prognostic significance of preoperative C-reactive protein to albumin ratio in non-small cell lung cancer patients: A meta-analysis

Objective

We aimed to assess whether C-reactive protein to albumin ratio (CAR) is associated with the clinicopathology and prognosis of patients with non-small cell lung cancer (NSCLC) after surgery.

Methods

Several literature databases were searched for eligible studies in English and Chinese published before September 1, 2022, according to the inclusion and exclusion criteria. The pooled odds ratios (ORs) with 95% confidence interval (CI) were calculated to assess the association of CAR in lung cancer with clinicopathological characteristics including age, sex, smoking status, lymph node metastasis, and American Association of Cancer (AJCC) stage. The pooled hazard ratios (HRs) with 95% CI were calculated to assess the association of CAR with prognosis in lung cancer. Publication bias was assessed using Egger's test.

Results

Overall, 9 studies involving 3,359 NSCLC patients were included in this meta-analysis. The CAR was observed to be higher in males, smokers, and patients with lymph node metastasis and correlated with advanced AJCC stage but not with age. Moreover, a high CAR correlated with poor survival. No publication bias was observed in this meta-analysis.

Conclusions

CAR was observed to be a significant biomarker for prognosis and associated with clinicopathological characteristics in patients with NSCLC after surgery.

Prognostic value of pan-immune-inflammation value in colorectal cancer patients: A systematic review and meta-analysis

Background

The pan-immune-inflammation value (PIV) has been reported as a novel prognostic biomarker in multiple malignancies. The aim of this study is to investigate the prognostic value of the PIV in patients with colorectal cancer.

Methods

We comprehensively searched electronic databases including PubMed, Embase and Web of Science up to August 2022. The endpoints were survival outcomes. Hazard ratios (HRs) with 95% confidence intervals (CIs) for survival data were collected for analysis.

Results

Six studies including 1879 participants were included. A significant heterogeneity in the PIV cut-off value among studies was observed. The combined results indicated that patients in the high baseline PIV group had a worse overall survival (HR=2.09; 95%CI: 1.67-2.61; P<0.0001; I^{2 =} 7%) and progression-free survival (HR=1.82; 95%CI: 1.49-2.22; P<0.0001; I^{2 =} 15%). In addition, early PIV increase after treatment initiation was significantly associated with decreased overall survival (HR=1.79; 95%CI: 1.13-2.93; P=0.01; I^{2 =} 26%), and a trend toward poor progression-free survival (HR=2.00; 95%CI: 0.90-4.41; P=0.09; I^{2 =} 70%).

Conclusion

Based on existing evidence, the PIV could act as a valuable prognostic index in patients with colorectal cancer. However, the heterogeneity in the PIV cut-off value among studies should be considered when interpreting these findings.

Clinical significance of preoperative neutrophil‐lymphocyte ratio and platelet‐lymphocyte ratio in the prognosis of resected early‐stage patients with non‐small cell lung cancer: A meta‐analysis

BACKGROUND

Poor prognosis is linked to peripheral blood levels of preoperative platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) in many advanced cancers. Nevertheless, whether the correlation exists in resected early-stage cases with non-small cell lung cancer (NSCLC) stays controversial. Consequently, we performed a meta-analysis to explore the preoperative NLR and PLR's prognostic significance in early-stage patients with NSCLC undergoing curative surgery.

METHODS

Relevant studies that validated the link between preoperative NLR or PLR and survival results were found via the proceeding databases: PubMed, Embase, Cochrane Library, and Web of Science. The merged 95% confidence interval (CI) and hazard ratio (HR) was employed to validate the link between the NLR or PLR's index and overall survival (OS) and disease-free survival (DFS) in resected NSCLC cases. We used sensitivity and subgroup analyses to assess the studies' heterogeneity.

RESULTS

An overall of 21 studies were attributed to the meta-analysis. The findings indicated that great preoperative NLR was considerably correlated with poor DFS (HR = 1.58, 95% CI: 1.37-1.82, p < 0.001) and poor OS (HR = 1.51, 95% CI: 1.33-1.72, p < 0.001), respectively. Subgroup analyses were in line with the pooled findings. In aspect of PLR, raised PLR was indicative of inferior DFS (HR = 1.28, 95% CI: 1.04-1.58, p = 0.021) and OS (HR = 1.37, 95% CI: 1.18-1.60, p < 0.001). In the subgroup analyses between PLR and DFS, only subgroups with a sample size <300 (HR = 1.67, 95% CI: 1.15-2.43, p = 0.008) and TNM staging of mixed (I-II) (HR = 1.47, 95% CI: 1.04-2.07, p = 0.028) showed that the link between high PLR and poor DFS was significant.

CONCLUSIONS

Preoperative elevated NLR and PLR may act as prognostic biomarkers in resected early-stage NSCLC cases and are therefore valuable for guiding postoperative adjuvant treatment.

Radiomics with Artificial Intelligence for the Prediction of Early Recurrence in Patients with Clinical Stage IA Lung Cancer

BACKGROUND

We seek to explore the ability of computed tomography (CT)-based radiomics coupled with artificial intelligence (AI) to predict early recurrence (< 2 years after surgery) in patients with clinical stage 0-IA non-small cell lung cancer (c-stage 0-IA NSCLC).

PATIENTS AND METHODS

Data of 642 patients were collected for early recurrence and assigned to the derivation and validation cohorts at a ratio of 2:1. Using the AI software Beta Version (Fujifilm Corporation, Japan), 39 AI imaging factors, including 17 factors from the AI ground-glass nodule analysis and 22 radiomic features from nodule characterization analysis, were extracted.

RESULTS

Multivariate analysis showed that male sex (p = 0.016), solid part size (p < 0.001), CT value standard deviation (p = 0.038), solid part volume ratio (p = 0.016), and bronchus translucency (p = 0.007) were associated with recurrence-free survival (RFS). Receiver operating characteristics analysis showed that the area under the curve and optimal cutoff values relevant to recurrence were 0.707 and 1.49 cm for solid part size, and 0.710 and 22.9% for solid part volume ratio, respectively. The 5-year RFS rates for patients in the validation set with solid part size ≤ 1.49 cm and > 1.49 cm were 92.2% and 70.4% (p < 0.001), whereas those for patients with solid part volume ratios ≤ 22.9% and > 22.9% were 97.8% and 71.7% (p < 0.001), respectively.

CONCLUSIONS

CT-based radiomics coupled with AI contributes to the noninvasive prediction of early recurrence in patients with c-stage 0-IA NSCLC.

Systemic immune-inflammation index within the first postoperative hour as a predictor of severe postoperative complications in upper abdominal surgery: a retrospective single-center study

Background

Systemic pro-inflammatory factors play a critical role in mediating severe postoperative complications (SPCs) in upper abdominal surgery (UAS). The systemic immune-inflammation index (SII) has been identified as a new inflammatory marker in many occasions. The present study aims to determine the association between SII and the occurrence of SPCs after UAS.

Methods

Included in this study were 310 patients with upper abdominal tumors who received UAS and subsequently were transferred to the anesthesia intensive care unit between November 2020 and November 2021 in Nanjing Drum Hospital. SPCs, including postoperative pulmonary complications (PPCs), major adverse cardiac and cardiovascular events, postoperative infections and delirium, were recorded during the hospital stay. The clinical features of the patients with and without SPCs were compared by Student’s t-test or Fisher’s exact test as appropriate. Risk factors associated with SPC occurrence were evaluated by univariable and multivariable logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to establish a cut-off level of SII value to predict SPCs.

Results

Of the 310 patients receiving UAS, 103 patients (33.2%) presented at least one SPC, including PPCs (n = 62), adverse cardiovascular events (n = 22), postoperative infections (n = 51), and delirium (n = 5). Both preoperative SII and 1-h postoperative SII in patients with SPCs were significantly higher than those in patients without SPCs. Multivariate analysis showed that 1-h postoperative SII was an independent predictor for SPC occurrence (OR = 1.000, 95% CI 1.000–1.000, P = 0.007), together with postoperative C-reactive protein, postoperative arterial lactate, postoperative oxygenation-index and older age. The ROC curve showed that the optimal cutoff value of 1-h postoperative SII to predict SPCs was 754.6078 × 10⁹/L, with an 88.3% sensitivity and a 29% specificity. Multivariate analysis also confirmed that 1-h postoperative SII > 754.6078 × 10⁹/L was associated with increased SPC occurrence (OR = 2.656, 95% CI 1.311–5.381, P = 0.007).

Conclusion

Our findings demonstrated an association between the higher level of 1-h postoperative SII and SPCs, suggesting that 1-h postoperative SII, especially categorized 1-h postoperative SII using cutoff value, may be a useful tool for identifying patients at risk of developing SPCs.

The Relationship Between Systemic Immune Inflammatory Index and Prognosis of Patients With Non-Small Cell Lung Cancer: A Meta-Analysis and Systematic Review

Background

The relationship between systemic immune inflammation index (SII) and the prognosis of cancer has always been a subject of intense interest. However, the prognostic value of SII in non-small cell lung cancer (NSCLC) patients remains a controversial topic.

Objective

To evaluate the effect of SII index on prognosis of NSCLC.

Methods

We conducted a comprehensive search of PubMed, EMBASE, and the Cochrane Library databases to determine correlation between SII index, clinicopathological features, overall survival (OS), and progression-free survival (PFS). Odds ratio (ORs) and 95% confidence interval (CIs) were used to assess the connection between SII and clinicopathological parameters, and HRs and 95% CIs were used to assess the connection between SII and survival.

Results

Seventeen studies with 8,877 cases were included in the analysis. Compared with NSCLC patients with low SII level, patients with NSCLC with high SII level had a poor OS (HR = 1.75, 95% CI, 1.50–2.00; P < 0.001) and had a poor PFS (HR = 1.61, 95% CI, 1.25–1.96; P < 0.001). In addition, patients with higher pathological stage (II–III) had higher SII levels (OR = 2.32, 95% CI, 2.06–2.62; P < 0.001).

Conclusions

The SII index is a promising prognostic biomarker for NSCLC and may help clinicians choose appropriate NSCLC treatments.

Platelet‑to‑lymphocyte and neutrophil‑to‑lymphocyte ratios are associated with the efficacy of immunotherapy in stage III/IV non‑small cell lung cancer

Peripheral serological indicators are novel markers associated with prognosis in multiple malignant tumors. In the present study, platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were selected to construct a model that predicts long-term survival of patients with stage IIIB-IV non-small cell lung cancer (NSCLC) who received treatment with an anti-programmed cell death protein-1 (PD-1) monoclonal antibody. A total of 133 patients were eligible for the present retrospective study (January 2019-February 2021). The area under the receiver operating characteristic curve was used to compare the diagnostic value of PLR and NLR, and combined PLR and NLR. The objective response rate and disease control rate of each group were obtained and the differences were compared using the χ² test. The prognostic value of these indicators was assessed using the Kaplan-Meier method. Cox regression analysis was used to evaluate risk factors associated with long-term survival. Statistically significant parameters were included in the nomogram. Based on the median PLR and NLR values, the patients were divided into high PLR (H-PLR) (PLR >200.00, 67 patients) and low PLR (L-PLR) (PLR ≤200.00, 66 patients), and high NLR (H-NLR) (NLR >3.56, 65 patients) and low NLR (L-NLR) (NLR ≤3.56, 68 patients) groups. Immune-related adverse events (irAEs) occurred in 22 patients (16.5%) during the observation period, including 18 grade 2–3 irAEs and 4 grade 4 cases. H-NLR and H-PLR were associated with poor progression-free (PFS) and overall survival (OS) in the present study. NLR was an independent prognostic factor for PFS [hazard ratio (HR): 0.201, 95% confidence interval (CI): 0.060-0.670; P=0.009) and OS (HR: 0.413, 95% CI: 0.226-0.754; P=0.004) in this patient group. Therefore, NLR may be used in the prognostication of patients with stage IIIB-IV NSCLC treated with PD-1 inhibitors. These serological markers may be used in combination with established immunomarkers to help predict outcomes.

Prognostic value of pretreatment advanced lung cancer inflammation index in non-small cell lung cancer: a meta-analysis

Purpose To identify the prognostic value of pretreatment advanced lung cancer inflammation index (ALI) in non-small cell lung cancer (NSCLC) including surgical patients who were diagnosed with early stage. Methods The PubMed, EMBASE and Web of Science electronic databases were searched up to January 12, 2022 for relevant studies. The hazard ratios (HRs) with 95% confidence intervals (CIs) were combined to assess the association between pretreatment ALI and overall survival (OS) or progression-free survival (PFS) of NSCLC patients. All statistical analyses were conducted by STATA 12.0 software. Results A total of 14 studies involving 3607 participates were included. The pooled results indicated that lower pretreatment ALI was significantly related with poorer OS (HR =2.20, 95% CI: 1.46-3.33, P<0.001) and PFS (HR =1.78, 95% CI: 1.49-2.13, P<0.001). Besides, subgroup analysis also demonstrated that lower pretreatment ALI was associated with worse OS in surgical (P<0.001) and non-metastatic (P<0.001) patients and worse PFS of surgical (P<0.001) NSCLC patients. Conclusion Pretreatment ALI was a novel and reliable prognostic indicator in NSCLC and lower pretreatment ALI predicted worse survival including patients diagnosed with early stage. However, more prospective high-quality studies are still needed to verify above findings.

Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

To conduct better research in hepatocellular carcinoma resection, this paper used 3D machine learning and logistic regression algorithm to study the preoperative assistance of patients undergoing hepatectomy. In this study, the logistic regression model was analyzed to find the influencing factors for the survival and recurrence of patients. The clinical data of 50 HCC patients who underwent extensive hepatectomy (≥4 segments of the liver) admitted to our hospital from June 2020 to December 2020 were selected to calculate the liver volume, simulated surgical resection volume, residual liver volume, surgical margin, etc. The results showed that the simulated liver volume of 50 patients was 845.2 + 285.5 mL, and the actual liver volume of 50 patients was 826.3 ± 268.1 mL, and there was no significant difference between the two groups (t = 0.425; P > 0.05). Compared with the logistic regression model, the machine learning method has a better prediction effect, but the logistic regression model has better interpretability. The analysis of the relationship between the liver tumour and hepatic vessels in practical problems has specific clinical application value for accurately evaluating the volume of liver resection and surgical margin.