Preoperative neutrophil-lymphocyte ratio predicts the risk of microvascular invasion in hepatocellular carcinoma: A meta-analysis

Preoperative prediction and risk assessment of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.

Significant association between high neutrophil-lymphocyte ratio and poor prognosis in patients with hepatocellular carcinoma: a systematic review and meta-analysis

Objective

Whether neutrophil-lymphocyte ratio (NLR) is an applicative predictor of poor prognosis in patients with hepatocellular carcinoma (HCC) remains controversial. In response to the current conflicting data, this meta-analysis was conducted to gain a comprehensive and systematic understanding of prognostic value of NLR in HCC.

Methods

Several English databases, including PubMed, EMBASE, and the Cochrane Library, with an update date of February 25, 2023, were systematically searched. We set the inclusion criteria to include randomized controlled trial (RCT) studies that reported the prognostic value of serum NLR levels in patients with HCC receiving treatment. Both the combined ratio (OR) and the diagnosis ratio (DOR) were used to assess the prognostic performance of NLR. Additionally, we completed the risk of bias assessment by Cochrane Risk of Bias Assessment Tool.

Results

This meta-analysis ultimately included 16 studies with a total of 4654 patients with HCC. The results showed that high baseline NLR was significantly associated with poor prognosis or recurrence of HCC. The sensitivity of 0.67 (95% confidence interval [CI]. 0.59-0.73); specificity of 0.723 (95% CI: 0.64-0.78) and DOR of 5.0 (95% CI: 4.0-7.0) were pooled estimated from patient-based analyses. Subsequently, the combined positive likelihood ratio (PLR) and negative likelihood ratio (NLHR) were calculated with the results of 2.4 (95% CI: 1.9-3.0) and 0.46 (95% CI: 0.39-0.56), respectively. In addition, area under the curve (AUC) of the summary receiver operating characteristic (SROC) reflecting prognostic accuracy was calculated to be 0.75 (95% CI: 0.71-0.78). The results of subgroup analysis suggested that high NLR was an effective predictive factor of poor prognosis in HCC in mainland China as well as in the northern region.

Conclusion

Our findings suggest that high baseline NLR is an excellent predictor of poor prognosis or relapse in patients with HCC, especially those from high-incidence East Asian populations.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023440640.

The prognostic utility of preoperative neutrophil-to-lymphocyte ratio (NLR) in patients with colorectal liver metastasis: a systematic review and meta-analysis

The neutrophil-to-lymphocyte ratio is used to reflect body's inflammatory status with prognostic value in different cancers. We aimed to investigate the influence of preoperative NLR in the prognosis of CRLM patients receiving surgery using meta-analysis. Data in Cochrane Library, PubMed, Embase, and Web of Science databases created before October 2022 were recruited. Meta-analysis was carried out with RevMan 5.3 and Stata16 software, and the primary outcome indicators included overall survival (OS), and secondary outcome indicators included disease-free survival (DFS) and relapse-free survival (RFS). The pooled risk ratio (HR) and 95% confidence interval (CI) for each outcome indicator were determined using random-effects models or fixed-effects models. The pooled odds ratio (OR) and corresponding 95% confidence intervals (CI) for NLR and clinicopathological characteristics were determined with a fixed-effects model. 18 papers published between 2008 and 2022 (3184 patients in total) were included. The pooled analysis found that high preoperative NLR was correlated with poor OS (multivariate HR = 1.83, 95% CI = 1.61-2.08, p < 0.01), DFS (multivariate HR = 1.78, 95% CI = 1.16-2.71, p < 0.01) and RFS (multivariate HR = 1.46, 95% CI = 1.15-1.85, p < 0.01), but NLR was not related to clinicopathological features of CRLM patients correlation. In conclusion, NLR is an independent risk factor for poor prognosis in patients with CRLM. More large-scale clinical researches are required in the future to demonstrate the inclusion of preoperative NLR as a prognostic indicator for CRLM patients to guide postoperative adjuvant chemotherapy.

Analysis of Biochemical and Inflammatory Markers for Predicting COVID-19 Severity: Insights From a Tertiary Healthcare Institution of Eastern India

Background Coronavirus disease-19 (COVID-19) patients often deteriorate rapidly based on viral infection-related inflammation and the subsequent cytokine storm. The clinical symptoms were found to be inconsistent with laboratory findings. There is a need to develop biochemical severity score to closely monitor COVID-19 patients. Methods This study was conducted in the department of biochemistry at All India Institute of Medical Sciences (AIIMS) Bhubaneswar in collaboration with the intensive care unit. Laboratory data of 7,395 patients diagnosed with COVID-19 during the first three waves of the pandemic were analyzed. The serum high sensitivity high-sensitivity C-reactive protein (hs-CRP, immuno-turbidity method), lactate dehydrogenase (LDH, modified Wacker et al. method), and liver enzymes (kinetic-UV method) were estimated by fully automated chemistry analyzer. Serum ferritin and interleukin-6 (IL-6) were measured by one-step immunoassay using chemiluminescence technology. Three models were used in logistic regression to check for the predictive potential of biochemical parameters, and a COVID-19 biochemical severity score was calculated using a non-linear regression algorithm. Results The receiver operating characteristic curve found age, urea, uric acid, CRP, ferritin, IL6, and LDH with the highest odds of predicting ICU admission for COVID-19 patients. COVID-19 biochemical severity scores higher than 0.775 were highly predictive (odds ratio of 5.925) of ICU admission (AUC=0.740, p<0.001) as compared to any other individual parameter. For the validation, 30% of the total dataset was used as testing data (n=2095) with a sensitivity of 68.3%, specificity of 74.5%, and odds ratio of 6.304. Conclusion Age, urea, uric acid, ferritin, IL6, LDH, and CRP-based predictive probability algorithm calculating COVID-19 severity was found to be highly predictive of ICU admission for COVID-19 patients.

Role of Plasma methylated SEPT9 for Predicting Microvascular Invasion and Tumor Proliferation in Hepatocellular Carcinoma

Background: Methylated SEPT9 (mSEPT9) has a role in the occurrence and development of hepatocellular carcinoma (HCC). Here, we studied the significance of plasma mSEPT9 for predicting prognosis-associated pathological parameters in patients with HCC. Methods: We retrospectively analyzed data from 205 subjects, including 111 HCC patients, 53 patients with at-risk liver disease (ARD) and 41 healthy donors (HDs). Analysis of plasma mSEPT9 was performed using methylation-specific polymerase chain reaction. Levels of mSEPT9 among different groups were compared using a nonparametric Mann-Whitney U test or a one-way ANOVA test. Correlations between pretreatment plasma mSEPT9 and clinicopathological characteristics were analyzed using the Chi-square. Univariate and multivariate analyses were used to identify factors related to microvascular invasion (MVI). Performance of variables for MVI prediction was evaluated by receiver operating characteristics curve. Results: A specific increase of plasma mSEPT9 in HCC was found when compared with ARD and HDs (HCC vs ARD, P  =  1.1  ×  10^-5 and HCC vs HDs, P  =  3.7  ×  10^-10). Pretreatment plasma mSEPT9 was significantly correlated tumor number (P  =  .004), tumor size (P  =  4.6  ×  10^-5), MVI (P  =  .002) and Barcelona Clinic Liver Cancer stage (P  =  .012). Levels of plasma mSEPT9 correlated significantly with Ki67 expression in tumor (r  =  0.356, P  =  1.3  ×  10^-4). Univariate and multivariate analyses showed that plasma mSEPT9 and serum protein induced by vitamin K absence or antagonist-II (PIVKA-II) were independent predictors for MVI. A combination of these 2 markers exhibited a larger areas under the curve (areas under the curve [AUC]  =  0.72) than mSEPT9 or PIVKA alone (AUC  =  0.67 and 0.65), especially in early-stage HCC. Conclusions: Plasma mSEPT9 is a promising noninvasive biomarker for predicting MVI and tumor proliferation in HCC. Integration plasma mSEPT9 detection into clinical settings might facilitate the patient management.

Long-term risk and predictors of cerebrovascular events following sepsis hospitalization: A systematic review and meta-analysis

Background

Long-term risk and predictors of cerebrovascular events following sepsis hospitalization have not been clearly elucidated. We aim to determine the association between surviving sepsis hospitalization and cerebrovascular complications in adult sepsis survivors.

Method

We searched MEDLINE, Embase, Scopus, Web of Sciences, Cochrane library, and Google scholar for studies published from the inception of each database until 31 August 2022.

Results

Of 8,601 screened citations, 12 observational studies involving 829,506 participants were analyzed. Surviving sepsis hospitalization was associated with a significantly higher ischemic stroke [adjusted hazard ratio (aHR) 1.45 (95% CI, 1.23-1.71), I ² = 96], and hemorrhagic stroke [aHR 2.22 (95% CI, 1.11-4.42), I ² = 96] at maximum follow-up compared to non-sepsis hospital or population control. The increased risk was robust to several sensitivity analyses. Factors that were significantly associated with increased hazards of stroke were: advanced age, male gender, diabetes mellitus, hypertension, coronary artery disease, chronic heart failure, chronic kidney disease, chronic obstruction pulmonary disease, and new-onset atrial fibrillation. Only diabetes mellites [aHR 1.80 (95% CI, 1.12-2.91)], hypertension [aHR 2.2 (95% CI, 2.03-2.52)], coronary artery disease [HR 1.64 (95% CI, 1.49-1.80)], and new-onset atrial fibrillation [aHR 1.80 (95% CI, 1.42-2.28)], were associated with > 50% increase in hazards.

Conclusion

Our findings showed a significant association between sepsis and a subsequent risk of cerebrovascular events. The risk of cerebrovascular events can be predicated by patient and sepsis-related baseline variables. New therapeutic strategies are needed for the high-risk patients.

A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy

INTRODUCTION

Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim of this study was to develop a deep learning prognostic prediction model by incorporating a new factor of MVI area to the other independent risk factors.

METHODS

Consecutive patients with HCC who underwent R0 liver resection from January to December 2016 at the Eastern Hepatobiliary Surgery Hospital were included in this retrospective study. For patients with MVI detected on resected specimens, they were divided into two groups according to the size of the maximal MVI area: the small-MVI group and the large-MVI group.

RESULTS

Of 193 patients who had MVI in the 337 HCC patients, 130 patients formed the training cohort and 63 patients formed the validation cohort. The large-MVI group of patients had worse overall survival (OS) when compared with the small-MVI group (p = 0.009). A deep learning model was developed based on the following independent risk factors found in this study: MVI stage, maximal MVI area, presence/absence of cirrhosis, and maximal tumor diameter. The areas under the receiver operating characteristic of the deep learning model for the 1-, 3-, and 5-year predictions of OS were 80.65, 74.04, and 79.44, respectively, which outperformed the traditional COX proportional hazards model.

CONCLUSION

The deep learning model, by incorporating the maximal MVI area as an additional prognostic factor to the other previously known independent risk factors, predicted more accurately postoperative long-term OS for HCC patients with MVI after R0 liver resection.

Melanoma survivors are at increased risk for second primary keratinocyte carcinoma

BACKGROUND

Recent large cohorts have reported that melanoma survivors are at risk of developing second keratinocyte carcinoma (KC). However, the detailed proportion and risk are still unknown. We aimed to comprehensively analyze the risk of developing keratinocyte carcinoma after primary melanoma.

METHODS

We conducted systematic literature research in PubMed, Embase, Web of Science, and Cochrane Library published prior to September 13, 2021. Proportion and standardized incidence ratios (SIR) with its corresponding 95% confidence interval (CI) were pooled for assessing the risk.

RESULTS

A total of 15 studies encompassing 168,286 patients were included in our analysis. The pooled proportions of melanoma survivors that developed a subsequent basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and KC were 4.11% (95% CI, 1.32-6.90), 2.54% (95% CI, 1.78-3.31), and 5.45% (95% CI, 3.06-7.84), respectively. The risks of developing a second BCC, SCC, and KC in melanoma survivors were 5.3-fold (SIR 5.30; 95% CI, 4.87-5.77), 2.6-fold (SIR 2.58; 95% CI, 1.33-5.04), and 6.2-fold (SIR 6.17; 95% CI, 3.66-10.39) increased in comparison with the general population. Both fixed effects and random effects models were applied in conducting meta-analysis and reached a consistent conclusion.

CONCLUSIONS

Our results indicated melanoma survivors are at elevated risk of experiencing second primary BCC and SCC, which suggested the significance of surveillance for second primary KC and efforts for prevention in patients with a history of melanoma.

Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma

Objective

To forecast the onset of microvascular invasion (MVI) in patients with hepatoma by evaluating the preoperative aspartate aminotransferase-to-platelet ratio index (APRI), alpha-fetoprotein (AFP), neutrophil-to-lymphocyte ratio (NLR), and other clinicopathological data.

Methods

In this study, we retrospectively analysed the clinical data of 62 patients who received radical surgery for hepa toma from 2019 to 2021. Patients were separated into the MVI-negative group and the MVI-positive group according to the postoperative pathological diagnosis. The relationships between MVI and NLR, APRI, AFP, tumor size, and other clinical data were assessed using the univariate analysis, receiver operating characteristic (ROC) curve, least absolute shrinkage and selection operator (LASSO) analysis, and logistic analysis.

Results

The ROC curve determined that the cutoff values of NLR, platelet-to-lymphocyte ratio (PLR), and APRI were 1.520, 98, and 0.275, respectively. The univariate analysis showed that the MVI-positive result was associated with five factors: tumor size (χ² = 10.620, p = 0.001), AFP (χ² = 10.524, p = 0.001), Edmondson grade (χ² = 20.736, p < 0.001), NLR (χ² = 8.744, p = 0.003), and APRI (χ² = 4.849, p = 0.028). The LASSO analysis indicated that the risk factors were the number of tumors, PLR, APRI, NLR, AFP, Edmondson grade, and tumor size. The multivariate logistic regression analysis showed that NLR ≥ 1.520 (OR 11.119, p = 0.006), APRI ≥ 0.275 (OR 12.515, p = 0.009), AFP ≥ 200 μg/mL (OR 7.823, p = 0.016), and tumor size > 3 cm (OR 7.689, p = 0.022) were independent risk factors for MVI in patients with hepatoma.

Conclusion

Preoperative NLR, APRI, AFP, and tumor size are reliable indicators for predicting the appearance of MVI in patients with hepatoma and are of great value in making detailed and reliable treatment protocols for these patients before surgery.

Diagnostic Accuracy of Artificial Intelligence Based on Imaging Data for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Background

The presence of microvascular invasion (MVI) is considered an independent prognostic factor associated with early recurrence and poor survival in hepatocellular carcinoma (HCC) patients after resection. Artificial intelligence (AI), mainly consisting of non-deep learning algorithms (NDLAs) and deep learning algorithms (DLAs), has been widely used for MVI prediction in medical imaging.

Aim

To assess the diagnostic accuracy of AI algorithms for non-invasive, preoperative prediction of MVI based on imaging data.

Methods

Original studies reporting AI algorithms for non-invasive, preoperative prediction of MVI based on quantitative imaging data were identified in the databases PubMed, Embase, and Web of Science. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) scale. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated using a random-effects model with 95% CIs. A summary receiver operating characteristic curve and the area under the curve (AUC) were generated to assess the diagnostic accuracy of the deep learning and non-deep learning models. In the non-deep learning group, we further performed meta-regression and subgroup analyses to identify the source of heterogeneity.

Results

Data from 16 included studies with 4,759 cases were available for meta-analysis. Four studies on deep learning models, 12 studies on non-deep learning models, and two studies compared the efficiency of the two types. For predictive performance of deep learning models, the pooled sensitivity, specificity, PLR, NLR, and AUC values were 0.84 [0.75–0.90], 0.84 [0.77–0.89], 5.14 [3.53–7.48], 0.2 [0.12–0.31], and 0.90 [0.87–0.93]; and for non-deep learning models, they were 0.77 [0.71–0.82], 0.77 [0.73–0.80], 3.30 [2.83–3.84], 0.30 [0.24–0.38], and 0.82 [0.79–0.85], respectively. Subgroup analyses showed a significant difference between the single tumor subgroup and the multiple tumor subgroup in the pooled sensitivity, NLR, and AUC.

Conclusion

This meta-analysis demonstrates the high diagnostic accuracy of non-deep learning and deep learning methods for MVI status prediction and their promising potential for clinical decision-making. Deep learning models perform better than non-deep learning models in terms of the accuracy of MVI prediction, methodology, and cost-effectiveness.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php? RecordID=260891, ID:CRD42021260891.

Using Systemic Inflammatory Markers to Predict Microvascular Invasion Before Surgery in Patients With Hepatocellular Carcinoma

Background

Mounting studies reveal the relationship between inflammatory markers and post-therapy prognosis. Yet, the role of the systemic inflammatory indices in preoperative microvascular invasion (MVI) prediction for hepatocellular carcinoma (HCC) remains unclear.

Patients and Methods

In this study, data of 1,058 cases of patients with HCC treated in the First Affiliated Hospital of Sun Yat-sen University from February 2002 to May 2018 were collected. Inflammatory factors related to MVI diagnosis in patients with HCC were selected by least absolute shrinkage and selection operator (LASSO) regression analysis and were integrated into an “Inflammatory Score.” A prognostic nomogram model was established by combining the inflammatory score and other independent factors determined by multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive efficacy of the model.

Results

Sixteen inflammatory factors, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, etc., were selected by LASSO regression analysis to establish an inflammatory score. Multivariate logistic regression analysis showed that inflammatory score (OR = 2.14, 95% CI: 1.63–2.88, p < 0.001), alpha fetoprotein (OR = 2.02, 95% CI: 1.46–2.82, p < 0.001), and tumor size (OR = 2.37, 95% CI: 1.70–3.30, p < 0.001) were independent factors for MVI. These three factors were then used to establish a nomogram for MVI prediction. The AUC for the training and validation group was 0.72 (95% CI: 0.68–0.76) and 0.72 (95% CI: 0.66–0.78), respectively.

Conclusion

These findings indicated that the model drawn in this study has a high predictive value which is capable to assist the diagnosis of MVI in patients with HCC.

Usefulness of neutrophil-to-lymphocyte ratio (NLR) as a prognostic predictor after treatment of hepatocellular carcinoma." Review article

The neutrophil-to-lymphocyte ratio (NLR) is an inflammatory marker which has been investigated as a prognostic indicator in post-therapeutic recurrence and survival of patients with HCC. Our aim was to review all studies that assessed the prognostic value of pre-treatment NLR in predicting patient survival, cancer recurrence, and graft survival in patients undergoing various therapies for HCC. We searched the database of PubMed and Google Scholar to review all studies that have the word "NLR" and the word "HCC." We included all studies that assessed pre-treatment NLR as a prognostic factor in predicting outcomes in HCC patients. We excluded studies that assessed the correlation between post-treatment NLR or dynamic changes in NLR after treatment and HCC outcomes in an effort to minimize the confounding effect of each treatment on NLR. We reviewed 123 studies that studied the correlation between pre-treatment NLR and patient survival, 72 studies that evaluated the correlation between pre-treatment NLR and tumor recurrence, 21 studies that evaluated the correlation between NLR and tumor behavior, and 4 studies that assessed the correlation between NLR and graft survival. We found a remarkable heterogeneity between the methods of the studies, which is likely responsible for the differences in outcomes. The majority of the studies suggested a correlation between higher levels of pre-treatment NLR and poor outcomes. We concluded that NLR is a reliable and inexpensive biomarker and should be incorporated into other prognostic models to help determine outcomes following HCC treatment.

A Combination of Blood Lymphocytes and AST Levels Distinguishes Patients with Small Hepatocellular Carcinomas from Non-cancer Patients

PURPOSE

HCC patients typically present at an advanced tumor stage, in which surgical therapies cannot be used. Screening ultrasound exams can increase the numbers of patients diagnosed with small tumors, but are often not used in patients at risk for HCC. We evaluated clinically available and cheap potential blood tests as biomarkers for screening patients at risk for HCC.

METHODS

A comparison was made of commonly used blood count and liver function parameters in a group of patients (n = 101) with small HCCs (≤ 3 cm) or without HCC (n = 275), who presented for liver transplantation in our institute.

RESULTS

Significant differences were found for blood lymphocytes and AST levels. This 2-parameter combination was found to be significantly different between patients with small HCCs versus no HCC. Using the combination of lymphocytes and AST levels to dichotomize the HCC patients, only blood levels of alpha-fetoprotein among the tumor characteristics were found to be significantly different among the 2 HCC groups, as well as levels of blood total bilirubin, ALKP, and PLR ratio. The results were confirmed using a separate smaller cohort of non-transplanted small size HCC patients.

CONCLUSION

The combination of elevated blood levels of lymphocyte counts and AST levels holds promise for screening of patients with chronic liver disease who are at risk for HCC.

Prognostic Significance of Microvascular Invasion in Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis

BACKGROUND The incidence, pathogenesis, and prognostic effect of microvascular invasion on pancreatic ductal adenocarcinoma (PDAC) remain controversial. This study aimed to summarize the incidence, pathogenesis, role in clinical management, recurrence, and prognostic significance of microvascular invasion in PDAC. MATERIAL AND METHODS A literature review and meta-analysis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Systematic literature searches were conducted using PubMed and Google Scholar up to February 2021. RESULTS Seventeen studies were included in the meta-analysis. The incidence of microvascular invasion was 49.0% (95% confidence interval [CI], 43.8-54.5%) among PDAC patients who underwent surgery. The weighted multivariate Cox proportional hazards model hazard ratio for disease-free survival of 8 studies was 1.78 (95% CI 1.53-2.08, P<0.001), and there was no statistically significant difference between the subgroups (P=0.477). The hazard ratio for overall survival of 14 studies was 1.49 (95% CI 1.27-1.74, P<0.001), and there was no statistically significant difference between the subgroups (P=0.676). CONCLUSIONS Microvascular invasion occurred in nearly half of PDAC patients after surgery and was closely related to disease-free and overall survival. Understanding the role of microvascular invasion in PDAC will help provide more personalized and effective preoperative or postoperative strategies to achieve better survival outcomes.

Prognostic role of plasma level of angiopoietin-1, angiopoietin-2, and vascular endothelial growth factor in hepatocellular carcinoma

BACKGROUND

Most hepatocellular carcinomas (HCCs) are hypervascular, with characteristic features of hepatic arterial supply to the tumor. The factors involved in tumor angiogenesis include angiopoietin-1 (Ang-1), angiopoietin-2 (Ang-2), and vascular endothelial growth factor (VEGF).

AIM

To investigate the profiles of plasma levels of angiogenesis markers in patients with HCC and evaluate their roles in predicting overall survival (OS) and progression-free survival (PFS).

METHODS

Plasma samples from 240 prospectively enrolled HCC patients in the very early to advanced stages were used to measure the levels of Ang-1, Ang-2, and VEGF. Their associations with clinical characteristics, OS, and PFS were analyzed.

RESULTS

The median plasma levels of Ang-1, Ang-2, and VEGF were 3216 pg/mL, 1684 pg/mL, and 26.5 pg/mL, respectively. The plasma level of Ang-2 showed a significant increase from early stage [Barcelona clinic liver cancer (BCLC) A] to intermediate (BCLC B) and advanced stage HCC (BCLC C/D), whereas Ang-1, VEGF, and alpha-fetoprotein (AFP) levels in the plasma did not show any such changes. Multivariable analysis, propensity score-matched analysis, and time-dependent receiver operating curve analysis revealed that Ang-2 levels had the highest predictive power for OS and PFS. Neither Ang-1 nor VEGF was significantly associated with OS or PFS. The neutrophil-to-lymphocyte ratio was an independent factor for OS and PFS.

CONCLUSION

The plasma levels of Ang-2 correlated with liver function, tumor stage, and tumor invasiveness, showing better performance in predicting OS and PFS than AFP, Ang-1, or VEGF.

Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters

PURPOSE

Microvascular invasion (MVI) is a critical determinant of the early recurrence and poor prognosis of patients with hepatocellular carcinoma (HCC). Prediction of MVI status is clinically significant for the decision of treatment strategies and the assessment of patient's prognosis. A deep learning (DL) model was developed to predict the MVI status and grade in HCC patients based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical parameters.

METHODS

HCC patients with pathologically confirmed MVI status from January to December 2016 were enrolled and preoperative DCE-MRI of these patients were collected in this study. Then they were randomly divided into the training and testing cohorts. A DL model with eight conventional neural network (CNN) branches for eight MRI sequences was built to predict the presence of MVI, and further combined with clinical parameters for better prediction.

RESULTS

Among 601 HCC patients, 376 patients were pathologically MVI absent, and 225 patients were MVI present. To predict the presence of MVI, the DL model based only on images achieved an area under curve (AUC) of 0.915 in the testing cohort as compared to the radiomics model with an AUC of 0.731. The DL combined with clinical parameters (DLC) model yielded the best predictive performance with an AUC of 0.931. For the MVI-grade stratification, the DLC models achieved an overall accuracy of 0.793. Survival analysis demonstrated that the patients with DLC-predicted MVI status were associated with the poor overall survival (OS) and recurrence-free survival (RFS). Further investigation showed that hepatectomy with the wide resection margin contributes to better OS and RFS in the DLC-predicted MVI present patients.

CONCLUSION

The proposed DLC model can provide a non-invasive approach to evaluate MVI before surgery, which can help surgeons make decisions of surgical strategies and assess patient's prognosis.

Value of gadoxetic acid-enhanced MRI for microvascular invasion of small hepatocellular carcinoma: a retrospective study

Background

The objective of this study was to analyze the accuracy of gadolinium–ethoxybenzyl–diethylenetriamine penta–acetic acid enhanced magnetic resonance imaging (Gd–EOB–DTPA–MRI) for predicting microvascular invasion (MVI) in patients with small hepatocellular carcinoma (sHCC) preoperatively.

Methods

A total of 60 sHCC patients performed with preoperative Gd–EOB–DTPA–MRI in the Harbin Medical University Cancer Hospital from October 2018 to October 2019 were involved in the study. Univariate and multivariate analyses were performed by chi–square test and logistic regression analysis. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of Gd–EOB–DTPA–MRI were performed by receiver operating characteristic (ROC) curves.

Results

Univariate analysis indicated that alanine aminotransferase (≥ 39.00U/L), poorly differentiated pathology, and imaging features including grim enhancement, capsule enhancement, arterial halo sign and hepatobiliary features (tumor highly uptake, halo sign, spicule sign and brush sign) were associated with the occurrence of MVI (p < 0.05). Multivariate analysis revealed that rim enhancement and hepatobiliary spicule sign were independent predictors of MVI (p < 0.05). The area under the ROC curve was 0.917 (95% confidence interval 0.838–0.996), and the sensitivity was 94.74%.

Conclusions

The morphologies of hepatobiliary phase imaging, especially the spicule sign, showed high accuracy in diagnosing MVI of sHCC. Rim enhancement played a significant role in diagnosing MVI of sHCC.

A Nomogram Estimation for the Risk of Microvascular Invasion in Hepatocellular Carcinoma Patients Meeting the Milan Criteria

OBJECTIVE

We aimed to develop and validate a nomogram for preoperatively estimating the risk of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the Milan criteria.

METHODS

The clinical data of 312 HCC patients who underwent liver surgery at the xxx from Jan 2017 to Dec 2019 were retrospectively collected. Then, the study population was categorized into the training and validation group based on the date of surgery. To identify risk factors related to MVI, we conducted a series of logistic regression analyses. By combining these risk factors, a nomogram was then established. We further clarified the usability of our model through the area under the ROC curve (AUC), decision curve analysis (DCA), and calibration curve.

RESULTS

Pathological examination revealed MVI in 108 patients with HCC (34.6%). Three independent predictors were identified: level of alpha-fetoprotein (AFP) exceeds 194 ng/mL (OR = 2.20, 95% CI: 1.13-4.31, p = 0.021), size of tumor (OR = 1.59; 95% CI: 1.18-2.12; P < 0.001) and number of tumors (OR = 3.37, 95% CI: 1.64-7.28, p < 0.001). A nomogram was subsequently built with an AUC of 0.73 and 0.74 respectively in the training cohort and validation cohort. The calibration curve showed a relatively high consistency between predicted probability and observed outcomes. Besides, the DCA revealed that the model was clinically beneficial for preoperatively predicting MVI in HCC.

CONCLUSIONS

A model for evaluating the risk of MVI HCC patients was developed and validated. The model could provide clinicians with a relatively reliable basis for optimizing treatment decisions.

Association of inflammatory markers with the severity of COVID-19: A meta-analysis

Objectives

Studies reported associations of inflammatory markers with the severity of COVID-19, but conclusions were inconsistent. We aimed to provide an overview of the association of inflammatory markers with the severity of COVID-19.

Methods

We searched PubMed, Embase, Cochrane Library, Wanfang and China National Knowledge Infrastructure (CNKI) database until March 20, 2020. Weighted mean difference (WMD) and 95% confidence intervals (CIs) were pooled using random or fixed-effects models.

Results

A total of 16 studies comprising 3962 patients with COVID-19 were included in our analysis. Random-effect results demonstrated that patients with COVID-19 in the nonsevere group had lower levels for CRP (WMD = −41.78 mg/l, 95% CI = [−52.43, −31.13], P < 0.001), PCT (WMD = −0.13 ng/ml, 95% CI = [−0.20, −0.05], P < 0.001), IL-6 (WMD = −21.32 ng/l, 95% CI = [−28.34, −14.31], P < 0.001), ESR (WMD = −8 mm/h, 95% CI = [−14, −2], P = 0.005), SAA (WMD = −43.35 μg/ml, 95% CI = [−80.85, −5.85], P = 0.020) and serum ferritin (WMD = −398.80 mg/l, 95% CI = [−625.89, −171.71], P < 0.001), compared with those in the severe group. Moreover, survivors had a lower level of IL-6 than non-survivors (WMD = −4.80 ng/ml, 95% CI = [−5.87, −3.73], P < 0.001). These results were consistent through sensitivity analysis and publication bias assessment.

Conclusions

The meta-analysis highlights the association of inflammatory markers with the severity of COVID-19. Measurement of inflammatory markers might assist clinicians to monitor and evaluate the severity and prognosis of COVID-19.

Laparoscopic versus open gastrectomy for gastric cancer

Background

Compared with open gastrectomy (OG), laparoscopic gastrectomy (LG) for gastric cancer has achieved rapid development and popularities in the past decades. However, lack of comprehensive analysis in long-term oncological outcomes such as recurrence and mortality hinder its full support as a valid procedure. Therefore, there are still debates on whether one of these options is superior.

Aim

To evaluate the primary and secondary outcomes of laparoscopic versus open gastrectomy for gastric cancer patients

Methods

Two authors independently extracted study data. Risk ratio (RR) with 95% confidence interval (CI) was calculated for binary outcomes, mean difference (MD) or the standardized mean difference (SMD) with 95% CI for continuous outcomes, and the hazard ratio (HR) for time-to-event outcomes. Review Manager 5.3 and STATA software were used for the meta-analysis.

Results

Seventeen randomized controlled trials (RCTs) involving 5204 participants were included in this meta-analysis. There were no differences in the primary outcomes including the number of lymph nodes harvested during operation, severe complications, short-term and long-term recurrence, and mortality. As for secondary outcomes, compared with the OG group, longer operative time was required for patients in the LG group (MD = 58.80 min, 95% CI = [45.80, 71.81], P < 0.001), but there were less intraoperative blood loss (MD = − 54.93 ml, 95% CI = [− 81.60, − 28.26], P < 0.001), less analgesic administration (frequency: MD = − 1.73, 95% CI = [− 2.21, − 1.24], P < 0.001; duration: MD = − 1.26 days, 95% CI = [− 1.40, − 1.12], P < 0.001), shorter hospital stay (MD = − 1.37 days, 95% CI = [− 2.05, − 0.70], P < 0.001), shorter time to first flatus (MD = − 0.58 days, 95% CI = [− 0.79, − 0.37], P < 0.001), ambulation (MD = − 0.50 days, 95% CI = [− 0.90, − 0.09], P = 0.02) and oral intake (MD = − 0.64 days, 95% CI = [− 1.24, − 0.03], P < 0.04), and less total complications (RR = 0.81, 95% CI = [0.71, 0.93], P = 0.003) in the OG group. There was no difference in blood transfusions (number, quantity) between these two groups. Subgroup analysis, sensitivity analysis, and the adjustment of Duval’s trim and fill methods for publication bias did not change the conclusions.

Conclusion

LG was comparable to OG in the primary outcomes and had some advantages in secondary outcomes for gastric cancer patients. LG is superior to OG for gastric cancer patients.

The Prognostic Role of a Combined Fibrinogen and Neutrophil-to-Lymphocyte Ratio Score in Patients with Resectable Hepatocellular Carcinoma: A Retrospective Study

Background

Inflammation and activation of the coagulation cascades have a role in the pathogenesis of malignancy, including hepatocellular carcinoma (HCC). This retrospective study aimed to investigate the prognostic role of the combined fibrinogen and neutrophil-to-lymphocyte ratio (F-NLR) in patients with resectable HCC.

Material/Methods

This retrospective study included 292 patients with HCC who underwent surgical resection. The receiver operating characteristic (ROC) curve was used to determine the cut-off value of preoperative fibrinogen (Fib) levels and the neutrophil-to-lymphocyte ratio (NLR). The. Hyperfibrinogenemia was >3.35 g/L, and an increased NLR was ≥2.47. The F-NLR was calculated for all patients. Kaplan-Meier survival curves, univariate analysis, multivariate analysis, and subgroup analysis were used to identify independent prognostic factors for overall survival (OS) and disease-free survival (DFS). The receiver operating characteristic (ROC) curve analysis of the F-NLR score and OS, according to the Barcelona Clinic Liver Cancer (BCLC) stage, was performed.

Results

Increased F-NLR scores were significantly associated with the presence of tumor thrombus (P=0.001), larger tumor diameter (P<0.001), vascular invasion (P<0.001), and increased BCLC stage (P<0.001). Multivariate analysis showed that the F-NLR score was an independent predictor of OS (P<0.001) and DFS (P=0.002). The prognostic role of F-NLR was significant for BCLC stage 0–I (P=0.004; P<0.001) and BCLC stage II–III (P=0.026; P=0.005) for OS and DFS, respectively.

Conclusions

In patients with resectable HCC, the combined F-NLR score, a new indicator of systemic inflammation, was an independent prognostic indicator.

Nomogram based on inflammatory indices for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma

Objective

To establish nomogram based on inflammatory indices for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC).

Methods

A cohort of 422 patients with HCC or ICC hospitalized at Xiangya Hospital between January 2014 and December 2018 was included in the study. Univariate and multivariate analysis was performed to identify the independent differential factors. Through combining these independent differential factors, a nomogram was established for differential diagnosis between ICC and HCC. The accuracy of nomogram was evaluated by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). The results were validated using a prospective study on 98 consecutive patients operated on from January 2019 to November 2019 at the same institution.

Results

Sex (OR = 9.001, 95% CI: 3.268‐24.792, P < .001), hepatitis (OR = 0.323, 95% CI: 0.121‐0.860, P = .024), alpha‐fetoprotein (AFP) (OR = 0.997, 95% CI: 0.995‐1.000, P = .046), carbohydrate antigen 19‐9 (CA199) (OR = 1.016, 95% CI: 1.007‐1.025, P < .001), and aspartate transaminase‐to‐neutrophil ratio index (ANRI) (OR = 0.904, 95% CI: 0.843‐0.969, P = .004) were the independent differential factors for ICC. Nomogram was established with well‐fitted calibration curves through incorporating these 5 factors. Comparing model 1 including gender, hepatitis, AFP, and CA199 (C index = 0.903, 95% CI: 0.849‐0.957) and model 2 enrolling AFP and CA199 (C index = 0.850, 95% CI: 0.791‐0.908), the nomogram showed a better discrimination between ICC and HCC, with a C index of 0.920 (95% CI, 0.872‐0.968). The results were consistent in the validation cohort. DCA also confirmed the conclusion.

Conclusion

A nomogram was established for the differential diagnosis between ICC and HCC preoperatively, and better therapeutic choice would be made if it was applied in clinical practice.

Nomogram For Preoperative Prediction Of Microvascular Invasion Risk In Hepatocellular Carcinoma

Objective

To preoperatively predict the microvascular invasion (MVI) risk in hepatocellular carcinoma (HCC) using nomogram.

Methods

A retrospective cohort of 513 patients with HCC hospitalized at Xiangya Hospital between January 2014 and December 2018 was included in the study. Univariate and multivariate analysis was performed to identify the independent risk factors for MVI. Based on the independent risk factors, nomogram was established to preoperatively predict the MVI risk in HCC. The accuracy of nomogram was evaluated by using receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).

Results

Tumor size (OR=1.17, 95% CI: 1.11–1.23, p<0.001), preoperative AFP level greater than 155 ng/mL (OR=1.65, 95% CI: 1.13–2.39, p=0.008) and NLR (OR=1.14, 95% CI: 1.00–1.29, p=0.042) were the independent risk factors for MVI. Incorporating these 3 factors, nomogram was established with the concordance index of 0.71 (95% CI, 0.66–0.75) and well-fitted calibration curves. DCA confirmed that using this nomogram added more benefit compared with the measures that treat all patients or treat none patients. At the cutoff value of predicted probability ≥0.44, the model demonstrated sensitivity of 61.64%, specificity of 71.53%, positive predictive value (PPV) of 64.13%, and negative predictive value (NPV) of 69.31%.

Conclusion

Nomogram was established for preoperative prediction of the MVI risk in HCC patients, and better therapeutic choice will be made if it was applied in clinical practice.