The predictive power of C-reactive protein- lymphocyte ratio for in-hospital mortality after colorectal cancer surgery

Using preoperative C-reactive protein levels to predict anastomotic leaks and other complications after elective colorectal surgery: A systematic review and meta-analysis

AIM

While postoperative C-reactive protein (CRP) is used routinely as an early indicator of anastomotic leak (AL), preoperative CRP remains to be established as a potential predictor of AL for elective colorectal surgery. The aim of this systematic review and meta-analysis is to examine the association between preoperative CRP and postoperative complications including AL.

METHOD

MEDLINE, EMBASE, Web of Science, PubMed, Cochrane Library and CINAHL databases were searched. Studies with reported preoperative CRP values and short-term surgical outcomes after elective colorectal surgery were included. An inverse variance random effects meta-analysis was performed for all meta-analysed outcomes to determine if patients with or without complications and AL differed in their preoperative CRP levels. Risk of bias was assessed with MINORS and certainty of evidence with GRADE.

RESULTS

From 1945 citations, 23 studies evaluating 7147 patients were included. Patients experiencing postoperative infective complications had significantly greater preoperative CRP values [eight studies, n = 2421 patients, mean difference (MD) 8.0, 95% CI 3.77-12.23, p < 0.01]. A significant interaction was observed with subgroup analysis based on whether patients were undergoing surgery for inflammatory bowel disease (X2 = 8.99, p < 0.01). Preoperative CRP values were not significantly different between patients experiencing and not experiencing AL (seven studies, n = 3317, MD 2.15, 95% CI -2.35 to 6.66, p = 0.35), nor were they different between patients experiencing and not experiencing overall postoperative morbidity (nine studies, n = 2958, MD 4.54, 95% CI -2.55 to 11.62, p = 0.31) after elective colorectal surgery.

CONCLUSION

Higher preoperative CRP levels are associated with increased rates of overall infective complications, but not with AL alone or with overall morbidity in patients undergoing elective colorectal surgery.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

The predictive power of C-reactive protein- lymphocyte ratio for in-hospital mortality after colorectal cancer surgery

BACKGROUND

The relation between immunity, inflammation, and tumor development and progression has been emphasized in colorectal cancer widely and the prognosis is linked to the inflammatory reaction of the host as well as the biological behavior of the tumor.

AIM

In this study, we aimed to find out the predictive power of C-reactive protein- lymphocyte ratio (CLR) for in-hospital mortality after colorectal surgery.

METHODS AND RESULTS

A series of 388 CRC patients were enrolled in the present retrospective study which was conducted in a tertiary state Hospital in Ankara, Turkey. In-hospital mortality was the main outcome to evaluate the predictive power of inflammatory markers, while the other outcomes that would be evaluated as separate variables were LOS in hospital and LOS in ICU. In this study, there were 260 males and 128 females, and the mean age was 60.9. The in-hospital mortality rate was 3.4% (n = 13) and age, APACHE II score and Charlson comorbidity index score were related to in-hospital mortality statistically. The mean LOS in the hospital was 13.9 days and LOS in ICU was 4.5 days. The CRP levels and the CLR levels were higher both in the preoperative and postoperative periods in the mortality (+) group and the difference was significant statistically (P = .008/ .002 and .004/ <.001, respectively). CLR in the postoperative period had the best predictive power with AUC: 0.876.

CONCLUSION

In conclusion, within the context of our study there appears to be a relationship between CLR, as measured on day 2 postoperatively, and in-hospital mortality. It is observed to be more effective than NLR, ALC, and CRP.