A nomogram based on liver stiffness predicts postoperative complications in patients with hepatocellular carcinoma

Current strategies for predicting post-hepatectomy liver failure and a new ultrasound-based nomogram

Liver cancer is associated with a few factors, such as viruses and alcohol consumption, and hepatectomy is an important treatment for patients with liver cancer. However, post-hepatectomy liver failure (PHLF) is the most serious complication and has a high mortality rate. Effective prediction of PHLF allows for the adjustment of clinical treatment strategies and is critical to the long-term prognosis of patients. Many factors have been associated with the development of PHLF, so there is an increasing interest in the development of predictive models for PHLF, such as nomograms that integrate intra-operative factors, imaging and biochemical characteristics of the patient. Ultrasound, as a simple and important examination method, plays an important role in predicting PHLF, especially the Nomogram established based on ultrasound measurements of liver stiffness and spleen area provides a more convenient way to predict the occurrence of PHLF.

Multicenter propensity score-matched analysis to compare perioperative morbidity after laparoscopic or robotic complex hepatectomy for solitary hepatocellular carcinoma

BACKGROUND

Postoperative complications are vital factors affecting the prognosis of patients with hepatocellular carcinoma (HCC), especially for complex hepatectomy. The present study aimed to compare perioperative complications between laparoscopic and robotic complex hepatectomy (LCH vs. RCH).

METHODS

Patients with solitary HCC after complex hepatectomy were collected from a multicenter database. Propensity score-matched (PSM) analysis was adopted to control confounding bias. Multivariable analysis was performed to determine the prognostic factors.

RESULTS

436 patients were included. After PSM, 43 patients were included in both the LCH and RCH groups. The results showed that compared to LCH, RCH had lower rates of blood loss and transfusion, and lower postoperative 30-day and major morbidity, and post-hepatectomy liver failure (PHLF) (all P < 0.05). Additionally, the length of hospital stay was shorter in the RCH group (P = 0.026). Multivariable analysis showed RCH is an independent protective factor for reducing the 30-day morbidity, major morbidity and PHLF.

CONCLUSION

RCH has advantages over LCH in the minimally invasive treatment of complex HCC, as it can reduce the incidence of postoperative morbidity. Therefore, RCH should be considered for patients with HCC who require complex hepatectomy.

Surgical Considerations in Portal Hypertension

This review provides an in-depth exploration of portal hypertension (PH) and its implications in various surgical procedures. The prevalence of clinically significant PH is 50% to 60% in compensated cirrhosis and 100% in decompensated cirrhosis. The feasibility and safety of hepatic and nonhepatic surgical procedures in patients with PH has been shown. Adequate preoperative risk assessment and optimization of PH are integral parts of patient assessment. The occurrence of adverse outcomes after surgery has decreased over time in this specific population, due to the development of techniques and improved perioperative multidisciplinary care.

Liver stiffness in hepatocellular carcinoma and chronic hepatitis patients: Hepatitis B virus infection and transaminases should be considered

BACKGROUND

Liver condition is a crucial prognostic factor for patients with hepatocellular carcinoma (HCC), but a convenient and comprehensive method to assess liver condition is lacking. Liver stiffness (LS) measured by two-dimensional shear wave elastography may help in assessing liver fibrosis and liver condition. Chronic hepatitis B (CHB) is an important risk factor for HCC progression, but LS was found to be less reliable in assessing liver fibrosis following hepatitis viral eradication. We hypothesize that the status of hepatitis virus infection would affect the accuracy of LS in assessing the liver condition.

AIM

To test the feasibility and impact factors of using LS to assess liver condition in patients with HCC and CHB.

METHODS

A total of 284 patients were retrospectively recruited and classified into two groups on the basis of serum CHB virus hepatitis B virus (HBV)-DNA levels [HBV-DNA ≥ 100.00 IU/mL as Pos group (n = 200) and < 100.00 IU/mL as Neg group (n = 84)]. Correlation analyses and receiver operating characteristic analyses were conducted to evaluate the relationship between LS and liver condition.

RESULTS

A significant correlation was found between LS and most of the parameters considered to have the ability to evaluate liver condition (P < 0.05). When alanine aminotransferase (ALT) concentrations were normal (≤ 40 U/L), LS was correlated with liver condition indices (P < 0.05), but the optimal cutoff of LS to identify a Child-Pugh score of 5 was higher in the Neg group (9.30 kPa) than the Pos group (7.40 kPa). When ALT levels were elevated (> 40 U/L), the correlations between LS and liver condition indices were not significant (P > 0.05).

CONCLUSION

LS was significantly correlated with most liver condition indices in patients with CHB and HCC. However, these correlations varied according to differences in HBV-DNA and transaminase concentrations.

Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography

BACKGROUND

Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions.

AIM

To develop a 2D-SWE-based predictive model for preoperative identification of HCC.

METHODS

A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms.

RESULTS

In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003).

CONCLUSION

2D-SWE's hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.

Effectiveness of homogenized nursing care intervention in postoperative bladder irrigation of urological system in primary hospitals-Taking the incidence of postoperative complications as an example: A retrospective study

To explore the effect of homogenized nursing interventions for bladder irrigation after urological surgery in primary hospitals, and to further analyze the incidence of postoperative complications according to the different nursing methods. The experiment selected 110 patients with urological disorders who underwent bladder irrigation, and the subjects were admitted to the hospital from January 2020 to October 2023. The subjects were chronologically divided into a control group and an experimental group, with the admission time of the control group being between between January 2020 and October 2022. The experimental group was admitted between October 2022 and October 2023. Conventional nursing care and homogenized nursing care were used respectively, and the intervention effect of homogenized nursing care was assessed by comparing the patients' psychological state indexes, vital characteristic indexes, and the incidence of various postoperative complications under the 2 interventions. None of the indicators were statistically significant before the nursing intervention. In the comparison of nursing satisfaction and clinical comfort, the experimental group's nursing satisfaction was 94.5% and clinical comfort was 90.9%, which was significantly higher than that of the control group. In the comparison of the incidence of postoperative complications, the incidence of urinary retention in the experimental group was 1.82%, which was significantly lower than that of the control group. In addition, the total incidence of complications in the experimental group was 1.82%, which proved that the homogenized nursing intervention was effective in reducing the complications after urinary bladder irrigation. In multifactorial logistic regression analysis, after homogenized nursing intervention. The relative risks of the 4 complications were 1.836, 1.445, 1.993, and 2.138, respectively, which were significantly lower than those of conventional nursing intervention. In the ROC analysis, the AUC values of the 4 complications were 0.832, 0.731, 0.746, and 0.723, respectively. proving the superiority of homogenized care in preventing postoperative complications. Homogenized nursing intervention can effectively reduce the incidence of postoperative complications in patients with urological postoperative bladder irrigation, improve patients' symptoms and prognosis, and improve the quality of care and patients' quality of life.

Development and validation of a nomogram to predict medication risk based on a knowledge, attitude and practice (KAP) survey of residents in Shanxi Province, China

Objective

Unsafe medication practices and medication errors are a major cause of harm in healthcare systems around the world. This study aimed to explore the factors that influence the risk of medication and provide medication risk evaluation model for adults in Shanxi province, China.

Methods

The data was obtained from the provincial questionnaire from May to December 2022, relying on the random distribution of questionnaires and online questionnaires by four hospitals in Shanxi Province. Multiple linear regression analysis was used to explore the factors affecting the KAP score of residents. Univariate and multivariate logistic regression was used to determine the independent risk factors, and the nomogram was verified by receiver operating characteristic curve, calibration and decision curve analysis.

Results

A total of 3,388 questionnaires were collected, including 3,272 valid questionnaires. The average scores of drugs KAP were 63.2 ± 23.04, 33.05 ± 9.60, 23.67 ± 6.75 and 33.16 ± 10.87, respectively. On the evaluation criteria of the questionnaire, knowledge was scored "fair", attitude and practice were scored "good". Sex, monthly income, place of residence, insurance status, education level, and employment were regarded as independent risk factors for medication and a nomogram was established by them.

Conclusion

Males, low-income, and low-educated people are important factors affecting the risk of medication. The application of the model can help residents understand the risk of their own medication behavior and reduce the harm of medication.

Development and validation of survival nomograms in elder triple-negative invasive ductal breast carcinoma patients

BACKGROUND

We aimed to develop a nomogram to predict the overall survival of elderly patients with Triple-negative invasive ductal breast carcinoma (TNIDC).

RESEARCH DESIGN AND METHODS

12165 elderly patients with nonmetastatic TNIDC were retrieved from the SEER database from 2010 to 2019 and were randomly assigned to training and validation cohorts. Stepwise Cox regression analysis was used to select variables for the nomogram based on the training cohort. Univariate and multivariate Cox analyses were used to calculate the correlation between variables and prognosis of the patients. Survival analysis was performed for high- and low-risk subgroups based on risk score.

RESULTS

Eleven predictive factors were identified to construct our nomograms. Compared with the TNM stage, the discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.741 (95% CI 0.728-0.754) against 0.708 (95% CI 0.694-0.721) and 0.765 (95% CI 0.747-0.783) against 0.725 (95% CI 0.705-0.744) for the training and validation cohorts, respectively. Differences in OS were also observed between the high- and low-risk groups (p < 0.001).

CONCLUSION

The proposed nomogram provides a convenient and reliable tool for individual evaluations for elderly patients with M0_stage TNIDC. However, the model may only for Americans.

Risk factors, prognostic factors, and nomograms for distant metastases in patients with gastroenteropancreatic neuroendocrine tumors: a population-based study

Background

Patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) have a poor prognosis for distant metastasis. Currently, there are no studies on predictive models for the risk of distant metastasis in GEP-NETs.

Methods

In this study, risk factors associated with metastasis in patients with GEP-NETs in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed by univariate and multivariate logistic regression, and a nomogram model for metastasis risk prediction was constructed. Prognostic factors associated with distant metastasis in patients with GEP-NETs were analyzed by univariate and multivariate Cox, and a nomogram model for prognostic prediction was constructed. Finally, the performance of the nomogram model predictions is validated by internal validation set and external validation set.

Results

A total of 9145 patients with GEP-NETs were enrolled in this study. Univariate and multivariate logistic analysis demonstrated that T stage, N stage, tumor size, primary site, and histologic types independent risk factors associated with distant metastasis in GEP-NETs patients (p value < 0.05). Univariate and multivariate Cox analyses demonstrated that age, histologic type, tumor size, N stage, and primary site surgery were independent factors associated with the prognosis of patients with GEP-NETs (p value < 0.05). The nomogram model constructed based on metastasis risk factors and prognostic factors can predict the occurrence of metastasis and patient prognosis of GEP-NETs very effectively in the internal training and validation sets as well as in the external validation set.

Conclusion

In conclusion, we constructed a new distant metastasis risk nomogram model and a new prognostic nomogram model for GEP-NETs patients, which provides a decision-making reference for individualized treatment of clinical patients.

Monocyte-to-High-Density Lipoprotein-Cholesterol Ratio Predicts Prognosis of Hepatocellular Carcinoma in Patients with Metabolic-Associated Fatty Liver Disease

Purpose

The incidence of non-B and non-C hepatocellular carcinoma (NBNC-HCC) is increasing globally. Metabolically associated fatty liver disease (MAFLD) has been a contributing factor to this rising trend in NBNC-HCC incidence. The monocyte-to-high-density lipoprotein-cholesterol ratio (MHR) is a new prognostic marker that connects systemic inflammation with disorders of lipid metabolism. Therefore, MHR may be a potential prognostic predictor of patients with MAFLD-related HCC (MAFLD-HCC). This study aims to investigate the relationship between the MHR and prognosis of patients with MAFLD-HCC and construct a novel prognostic prediction tool for MAFLD-HCC.

Patients and Methods

This retrospective study of patients with MAFLD-HCC included training (n = 112) and internal validation (n = 37) cohorts. Univariate and multivariate Cox proportional hazard regression analysis was conducted to identify independent risk factors of survival. A visual nomogram was constructed to assess the performance of the two groups. Furthermore, receiver operating characteristic (ROC) curves and calibration curves were used to verify the prognostic discriminative ability of this nomogram, even in the MHR, ALBI grade, and MHR-ALBI model.

Results

Univariate and multivariate analyses revealed that extrahepatic metastases, Vascular invasion, Barcelona staging B, C, D, elevated ALBI Grade 3, C-reactive protein (CRP), and MHR were independent risk factors for the prognosis of MAFLD-HCC. Moreover, calibration plots showed good discrimination and consistency when the significant factors were entered into the nomogram. Meanwhile, the MHR strongly correlated with the prognosis of cancer under a background of MAFLD-HCC, with a sensitivity of 88.89% and a specificity of 79.61%. Importantly, the performance of the MHR alone (AUC = 86.2) was not only superior to the ALBI grade (AUC = 63.8) but was comparable to the combination of MHR and ALBI (AUC = 88.5).

Conclusion

The novel nomogram demonstrated good value in predicting the overall survival of patients with MAFLD-HCC. The MHR may be a potential predictor of prognosis.

Pretreatment Non-Invasive Biomarkers as Predictors to Estimate Portal Vein Tumor Thrombosis (PVTT) Risk and Long-Term Survival in HBV-Related Hepatocellular Carcinoma Patients Without PVTT

Background

PVTT is a hallmark of advanced hepatocellular carcinoma (HCC). We aim to explore the influence of non-invasive biomarkers on the occurrence of PVTT and develop and validate models for predicting prognosis in HBV-related HCC patients without PVTT.

Methods

A total of 1026 HBV-related HCC patients without PVTT were enrolled, with 515 in the training cohort, 216 in the internal validation cohort, and 295 in the external validation cohort. We conducted Cox regression analyses to discern the independent risk factors associated with PVTT events, PFS, and OS, then constructed and validated predictive models. The predictive and discriminatory capabilities of models were assessed using the calibration, time-dependent ROC, and DCA curves.

Results

In our study, 136 patients (13.3%) experienced PVTT events during the follow-up period. The Cox regression analysis unveiled that male gender, AAPR ≤0.49, APRI >0.48, extrahepatic metastasis, and multiple tumors were independent risk factors for PVTT. In the training cohort, non-invasive biomarkers (AAR and APRI), AFP, ascites, and tumor-related characteristics (extrahepatic metastasis, tumor diameter, tumor number, and PVTT event) were independent risk factors for both OS and PFS, whereas age and ALBI grade independently correlated with OS. The C-indexes of OS and PFS nomogram models were 0.795 and 0.733 in the training cohort, 0.765 and 0.716 in the internal validation cohort, and 0.780 and 0.722 in the external validation cohort, respectively. Our models demonstrated strong predictive and discriminative abilities in all cohorts and yielded a greater net benefit compared to three traditional staging systems.

Conclusion

Non-invasive biomarkers are expected to be reliable predictors for assessing PVTT risk and predicting prognosis among HBV-related HCC patients without PVTT.

Clinical-Radiological Characteristic for Predicting Ultra-Early Recurrence After Liver Resection in Solitary Hepatocellular Carcinoma Patients

Objective

This study aims to identify independent risk factors for ultra-early recurrence in patients with early solitary hepatocellular carcinoma (HCC) and develop an individualized predictive nomogram for ultra-early recurrence.

Materials and Methods

A total of 332 patients with early solitary HCC who underwent curative liver resection at our hospital from January 2015 to May 2021 were included in this study. Based on the patients' recurrence status at 6 months, they were divided into the non-ultra-early recurrence group and the ultra-early recurrence group. Univariate and multivariate Cox regression analyses were used to construct the nomogram, and internal validation of its performance was performed using calibration plots with bootstrapping.

Results

Among the 332 patients with early solitary HCC, 39 (11.7%) experienced ultra-early recurrence. Tumor morphology, age > 46 years, AFP > 332.4 ng/mL, GGT > 51.2 U/L, ALP > 126 U/L, PT > 12.8 s, and satellite nodules were identified as independent prognostic factors for ultra-early recurrence in patients with early solitary HCC and were incorporated into the final predictive nomogram. The C-index of the nomogram and bootstrap resampling were 0.842 and 0.815, respectively. The calibration plot demonstrated good agreement between the predicted and observed probabilities of ultra-early recurrence, and DCA indicated the favorable clinical utility of the nomogram. Additionally, AFP > 332.4 ng/mL, AST > 35 U/L, GGT > 51.2 U/L, ALP > 126 U/L, tumor morphology, tumor size, satellite nodules, and intratumoral hemorrhage were identified as risk factors for overall survival in patients with early solitary HCC.

Conclusion

Our study establishes a nomogram for predicting the postoperative ultra-early recurrence status in patients with early solitary HCC, which provides valuable supplementary decision-making information for clinical decision-makers and guides the selection of the most appropriate treatment strategy.

Predicting symptomatic post-hepatectomy liver failure in patients with hepatocellular carcinoma: development and validation of a preoperative nomogram

OBJECTIVE

To develop and validate a nomogram based on liver stiffness (LS) for predicting symptomatic post-hepatectomy (PHLF) in patients with hepatocellular carcinoma (HCC).

METHODS

A total of 266 patients with HCC were enrolled prospectively from three tertiary referral hospitals from August 2018 to April 2021. All patients underwent preoperative laboratory examination to obtain parameters of liver function. Two-dimensional shear wave elastography (2D-SWE) was performed to measure LS. Three-dimensional virtual resection obtained the different volumes including future liver remnant (FLR). A nomogram was developed by using logistic regression and determined by receiver operating characteristic (ROC) curve analysis and calibration curve analysis, which was validated internally and externally.

RESULTS

A nomogram was constructed with the following variables: FLR ratio (FLR of total liver volume), LS greater than 9.5 kPa, Child-Pugh grade, and the presence of clinically significant portal hypertension (CSPH). This nomogram enabled differentiation of symptomatic PHLF in the derivation cohort (area under curve [AUC], 0.915), internal fivefold cross-validation (mean AUC, 0.918), internal validation cohort (AUC, 0.876) and external validation cohort (AUC, 0.845). The nomogram also showed good calibration in the derivation, internal validation, and external validation cohorts (Hosmer-Lemeshow goodness-of-fit test, p = 0.641, p = 0.06, and p = 0.127, respectively). Accordingly, the safe limit of the FLR ratio was stratified using the nomogram.

CONCLUSION

An elevated level of LS was associated with the occurrence of symptomatic PHLF in HCC. A preoperative nomogram integrating LS, clinical and volumetric features was useful in predicting postoperative outcomes in patients with HCC, which might help surgeons in the management of HCC resection.

CLINICAL RELEVANCE STATEMENT

A serial of the safe limit of the future liver remnant was proposed by a preoperative nomogram for hepatocellular carcinoma, which might help surgeons in 'how much remnant is enough in liver resection'.

KEY POINTS

• An elevated liver stiffness with the best cutoff value of 9.5 kPa was associated with the occurrence of symptomatic post-hepatectomy liver failure in hepatocellular carcinoma. • A nomogram based on both quality (Child-Pugh grade, liver stiffness, and portal hypertension) and quantity of future liver remnant was developed to predict symptomatic post-hepatectomy liver failure for HCC, which enabled good discrimination and calibration in both derivation and validation cohorts. • The safe limit of future liver remnant volume was stratified using the proposed nomogram, which might help surgeons in the management of HCC resection.

Current status of preoperative risk assessment for posthepatectomy liver failure in patients with hepatocellular carcinoma

Liver resection is an effective therapeutic option for patients with hepatocellular carcinoma. However, posthepatectomy liver failure (PHLF) remains a major cause of hepatectomy-related mortality, and the accurate prediction of PHLF based on preoperative assessment of liver functional reserve is a critical issue. The definition of PHLF proposed by the International Study Group for Liver Surgery has gained acceptance as a standard grading criterion. Liver function can be estimated using a variety of parameters, including routine blood biochemical examinations, clinical scoring systems, dynamic liver function tests, liver stiffness and fibrosis markers, and imaging studies. The Child-Pugh score and model for end-stage liver disease scores are conventionally used for estimating liver decompensation, although the alternatively developed albumin-bilirubin score shows superior performance for predicting hepatic dysfunction. Indocyanine green clearance, a dynamic liver function test mostly used in Japan and other Asian countries, serves as a quantitative estimation of liver function reserve and helps determine indications for surgical procedures according to the estimated risk of PHLF. In an attempt to improve predictive accuracy, specific evaluation of liver fibrosis and portal hypertension has gained popularity, including liver stiffness measurements using ultrasonography or magnetic resonance elastography, as well as noninvasive fibrosis markers. Imaging modalities, including Tc-99m-labeled galactosyl serum albumin scintigraphy and gadolinium-enhanced magnetic resonance imaging, are used for preoperative evaluation in combination with liver volume. This review aims to provide an overview of the usefulness of current options for the preoperative assessment of liver function in predicting PHLF.

CT Rule-in and Rule-out Criteria for Clinically Significant Portal Hypertension in Chronic Liver Disease

Background The value of CT in assessment of clinically significant portal hypertension (CSPH) has not been well determined. Purpose To evaluate the performance of CT features that have been associated with portal hypertension for diagnosing CSPH in patients with chronic liver disease (CLD). Materials and Methods This retrospective study included patients with CLD who underwent contrast-enhanced CT and subsequent hepatic venous pressure gradient (HVPG) measurement within 3 months at two tertiary institutions from January 2001 to December 2019. Two readers independently evaluated the presence of gastroesophageal varix, spontaneous portosystemic shunt (SPSS), and ascites on CT images. Splenomegaly at CT was determined using three methods, as follows: personalized or fixed volume criteria, based on spleen volume as measured by a deep learning algorithm, or manually measured spleen diameter. The diagnostic performance of these findings alone or in combination for detecting CSPH (HVPG ≥10 mm Hg) was evaluated. Results A total of 235 patients (mean age, 53.2 years ± 13.0 [SD]; 155 male patients), including 110 (46.8%) with CSPH, were included. Detection of CSPH according to the presence of both splenomegaly and at least one other CT feature (ie, gastroesophageal varix, SPSS, and ascites) achieved specificities of 94.4%-97.6%, whereas detection of CSPH according to the presence of any feature (ie, splenomegaly, gastroesophageal varix, SPSS, or ascites) achieved sensitivities of 94.5%-98.2%. When employing the former as rule-in criteria with the absence of splenomegaly, gastroesophageal varix, SPSS, and ascites as rule-out criteria for CSPH, 171-185 (range, 72.8%-78.7%) of 235 patients were correctly classified as either having CSPH or not, seven to 13 (range, 3%-5.5%) of 235 patients were incorrectly classified, and 42-54 (range, 17.9%-23%) of 235 patients were unclassified. Conclusion The presence or absence of splenomegaly, gastroesophageal varix, SPSS, and/or ascites on CT images may be useful for ruling in and ruling out CSPH in patients with CLD. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Fraum in this issue.

A virtual biopsy of liver parenchyma to predict the outcome of liver resection

The preoperative risk assessment of liver resections (LR) is still an open issue. Liver parenchyma characteristics influence the outcome but cannot be adequately evaluated in the preoperative setting. The present study aims to elucidate the contribution of the radiomic analysis of non-tumoral parenchyma to the prediction of complications after elective LR. All consecutive patients undergoing LR between 2017 and 2021 having a preoperative computed tomography (CT) were included. Patients with associated biliary/colorectal resection were excluded. Radiomic features were extracted from a virtual biopsy of non-tumoral liver parenchyma (a 2 mL cylinder) outlined in the portal phase of preoperative CT. Data were internally validated. Overall, 378 patients were analyzed (245 males/133 females-median age 67 years-39 cirrhotics). Radiomics increased the performances of the preoperative clinical models for both liver dysfunction (at internal validaton, AUC = 0.727 vs. 0.678) and bile leak (AUC = 0.744 vs. 0.614). The final predictive model combined clinical and radiomic variables: for bile leak, segment 1 resection, exposure of Glissonean pedicles, HU-related indices, NGLDM_Contrast, GLRLM indices, and GLZLM_ZLNU; for liver dysfunction, cirrhosis, liver function tests, major hepatectomy, segment 1 resection, and NGLDM_Contrast. The combined clinical-radiomic model for bile leak based on preoperative data performed even better than the model including the intraoperative data (AUC = 0.629). The textural features extracted from a virtual biopsy of non-tumoral liver parenchyma improved the prediction of postoperative liver dysfunction and bile leak, implementing information given by standard clinical data. Radiomics should become part of the preoperative assessment of candidates to LR.

Management of early-stage hepatocellular carcinoma: challenges and strategies for optimal outcomes

Although hepatocellular carcinoma (HCC) is associated with a poor prognosis, management of early-stage HCC is often successful with highly efficacious treatment modalities such as liver transplantation, surgical resection, and radiofrequency ablation. However, unfavorable clinical outcomes have been observed under certain circumstances, even after efficient treatment. Factors that predict unsuitable results after treatment include tumor markers, inflammatory markers, imaging findings reflecting tumor biology, specific outcome indicators for each treatment modality, liver functional reserve, and the technical feasibility of the treatment modalities. Various strategies may overcome these challenges, including the application of reinforced treatment indication criteria with predictive markers reflecting tumor biology, compensation for technical issues with up-to-date technologies, modification of treatment modalities, downstaging with locoregional therapies (such as transarterial chemotherapy or radiotherapy), and recently introduced combination immunotherapies. In this review, we discuss the challenges to achieving optimal outcomes in the management of early-stage HCC and suggest strategies to overcome these obstacles.

A Nomogram Model for Stratifying the Risk of Recurrence in Patients with Meningioma After Surgery

BACKGROUND

Here, we aimed to investigate the clinical parameters affecting the recurrence of meningiomas, and to construct a predictive nomogram model, so as to predict the recurrence-free survival (RFS) of meningiomas more accurately.

METHODS

The Clinical, imaging, and pathological data of 155 primary meningioma patients treated surgically from January 2014 to March 2021 were retrospectively analyzed. Independent prognostic factors affecting postoperative recurrence of meningioma were identified by univariate and multivariate Cox regression analyses. A predictive nomogram was established based on independent influence parameters. Subsequently, time-dependent receiver operating characteristic curve, calibration curve, and Kaplan-Meier method were utilized to evaluate the predictive ability of the model.

RESULTS

The multivariate Cox regression analysis showed that tumor size, Ki-67 index, and resection extent had independent prognostic significance, and these parameters were subsequently used to construct a predictive nomogram. Receiver operating characteristic curves indicated that the model was more accurate in predicting RFS than independent factors. Calibration curves suggested that the predicted RFS were similar to the actual observed RFS. In the Kaplan-Meier analysis, the RFS of high-risk cases was obviously shorter than that of low-risk cases.

CONCLUSIONS

The tumor size, Ki-67 index, and extent of resection were independent factors affecting the RFS of meningioma. The predictive nomogram based on these factors can be used as an effective method to stratify the recurrence risk of meningioma and provide a reference for patients to choose personalized treatment.

A nomogram based on radiomics intermuscular adipose analysis to indicate arteriosclerosis in patients with newly diagnosed type 2 diabetes

Objective

Early identifying arteriosclerosis in newly diagnosed type 2 diabetes (T2D) patients could contribute to choosing proper subjects for early prevention. Here, we aimed to investigate whether radiomic intermuscular adipose tissue (IMAT) analysis could be used as a novel marker to indicate arteriosclerosis in newly diagnosed T2D patients.

Methods

A total of 549 patients with newly diagnosed T2D were included in this study. The clinical information of the patients was recorded and the carotid plaque burden was used to indicate arteriosclerosis. Three models were constructed to evaluate the risk of arteriosclerosis: a clinical model, a radiomics model (a model based on IMAT analysis proceeded on chest CT images), and a clinical-radiomics combined model (a model that integrated clinical-radiological features). The performance of the three models were compared using the area under the curve (AUC) and DeLong test. Nomograms were constructed to indicate arteriosclerosis presence and severity. Calibration curves and decision curves were plotted to evaluate the clinical benefit of using the optimal model.

Results

The AUC for indicating arteriosclerosis of the clinical-radiomics combined model was higher than that of the clinical model [0.934 (0.909, 0.959) vs. 0.687 (0.634, 0.730), P < 0.001 in the training set, 0.933 (0.898, 0.969) vs. 0.721 (0.642, 0.799), P < 0.001 in the validation set]. Similar indicative efficacies were found between the clinical-radiomics combined model and radiomics model (P = 0.5694). The AUC for indicating the severity of arteriosclerosis of the combined clinical-radiomics model was higher than that of both the clinical model and radiomics model [0.824 (0.765, 0.882) vs. 0.755 (0.683, 0.826) and 0.734 (0.663, 0.805), P < 0.001 in the training set, 0.717 (0.604, 0.830) vs. 0.620 (0.490, 0.750) and 0.698 (0.582, 0.814), P < 0.001 in the validation set, respectively]. The decision curve showed that the clinical-radiomics combined model and radiomics model indicated a better performance than the clinical model in indicating arteriosclerosis. However, in indicating severe arteriosclerosis, the clinical-radiomics combined model had higher efficacy than the other two models.

Conclusion

Radiomics IMAT analysis could be a novel marker for indicating arteriosclerosis in patients with newly diagnosed T2D. The constructed nomograms provide a quantitative and intuitive way to assess the risk of arteriosclerosis, which may help clinicians comprehensively analyse radiomics characteristics and clinical risk factors more confidently.

Clinical Application of Shear Wave Elastography With Shear Wave Dispersion Imaging in the Preoperative Evaluation of Hepatic Parenchyma in Patients With Liver Tumors

OBJECTIVES

This study aimed to compare the diagnostic accuracy of shear wave elastography (SWE) with that of shear wave dispersion (SWD) in evaluation of hepatic parenchyma in patients with liver tumors before resection.

METHODS

A total of 174 patients with liver tumors were prospectively enrolled. SWE and SWD examinations were performed. Fibrosis stage and necroinflammatory activity were determined histopathologically according to the Scheuer standard. We compared the diagnostic accuracy of SWE and SWD.

RESULTS

Both SWE and SWD values of the liver were highly correlated with liver fibrosis stage (P < .05, respectively). Both SWE and SWD values of the liver were moderately correlated with necroinflammatory activity (P < .05, respectively). Both SWE and SWD values of the liver were not correlated with steatosis (P > .05, respectively). Both SWE and SWD values were significantly different among the patients with different stages of liver fibrosis (P < .001, respectively). The area under the receiver operating characteristic (ROC) curve of SWE value was 0.982, 0.977, 0.969, and 0.984 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWE values were 6.9, 7.9, 8.7, and 10.6 kPa for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The area under the ROC curve of SWD value was 0.967, 0.960, 0.925, and 0.954 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWD values were 11.2, 12.0, 13.2, and 16.0 m/s/kHz for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively.

CONCLUSIONS

SWE and SWD could be noninvasive and accurate for predicting the stage of liver fibrosis in patients with liver tumors before surgery. SWE was more accurate than SWD in predicting severe fibrosis (S ≥ 3) and cirrhosis (S = 4).

The Effect of a Liver Transplant Program on the Outcomes of Resectable Hepatocellular Carcinoma: A Nationwide Multicenter Analysis

OBJECTIVE

To evaluate the effect of a liver transplantation (LT) program on the outcomes of resectable hepatocellular carcinoma (HCC).

BACKGROUND

Surgical treatment of HCC includes both hepatic resection (HR) and LT. However, the presence of cirrhosis and the possibility of recurrence make the management of this disease complex and probably different according to the presence of a LT program.

METHODS

Patients undergoing HR for HCC between January 2005 and December 2019 were identified from a national database of HCC. The main study outcomes were major surgical complications according to the Comprehensive Complication Index, posthepatectomy liver failure (PHLF), 90-day mortality, overall survival, and disease-free survival. Secondary outcomes were salvage liver transplantation (SLT) and postrecurrence survival.

RESULTS

A total of 3202 patients were included from 25 hospitals over the study period. Three of 25 (12%) had an LT program. The presence of an LT program within a center was associated with a reduced probability of PHLF (odds ratio=0.38) but not with overall survival and disease-free survival. There was an increased probability of SLT when HR was performed in a transplant hospital (odds ratio=12.05). Among transplant-eligible patients, those who underwent LT had a significantly longer postrecurrence survival.

CONCLUSIONS

This study showed that the presence of a LT program was associated with decreased PHLF rates and an increased probability to receive SLT in case of recurrence.

Machine learning integrations develop an antigen-presenting-cells and T-Cells-Infiltration derived LncRNA signature for improving clinical outcomes in hepatocellular carcinoma

As a highly heterogeneous cancer, the prognostic stratification and personalized management of hepatocellular carcinoma (HCC) are still challenging. Recently, Antigen-presenting-cells (APCs) and T-cells-infiltration (TCI) have been reported to be implicated in modifying immunology in HCC. Nevertheless, the clinical value of APCs and TCI-related long non-coding RNAs (LncRNAs) in the clinical outcomes and precision treatment of HCC is still obscure. In this study, a total of 805 HCC patients were enrolled from three public datasets and an external clinical cohort. 5 machine learning (ML) algorithms were transformed into 15 kinds of ML integrations, which was used to construct the preliminary APC-TCI related LncRNA signature (ATLS). According to the criterion with the largest average C-index in the validation sets, the optimal ML integration was selected to construct the optimal ATLS. By incorporating several vital clinical characteristics and molecular features for comparison, ATLS was demonstrated to have a relatively more significantly superior predictive capacity. Additionally, it was found that the patients with high ATLS score had dismal prognosis, relatively high frequency of tumor mutation, remarkable immune activation, high expression levels of T cell proliferation regulators and anti-PD-L1 response as well as extraordinary sensitivity to Oxaliplatin/Fluorouracil/Lenvatinib. In conclusion, ATLS may serve as a robust and powerful biomarker for improving the clinical outcomes and precision treatment of HCC.

Development and external validation of a prognosis model to predict outcomes after curative resection of early-stage intrahepatic cholangiocarcinoma

Background

Early-stage intrahepatic cholangiocarcinoma (ESICC) with curative resection and lymph node-negative still has the risk of poor prognosis, and there lacks prognosis-assessing tools for these patients. The objective of this study was to develop a prognosis model to predict outcomes and identify risk stratification for ESICC after resection.

Methods

Totally 263 patients with ESICC after hepatectomy from January 2012 to January 2022 were analyzed. Clinicopathological factors were selected using multivariable Cox regression analysis and a prognosis model was developed. The performance of the model was evaluated by concordance index (C-index), calibration plots, decision curves analysis (DCA), and net reclassification index (NRI). Kaplan-Meier curves were analyzed for risk stratification of overall survival (OS) and recurrence-free survival (RFS) based on the prognosis model.

Results

The clinicopathological features that were independently associated with OS of ESICC included carbohydrate antigen19-9, carcinoembryonic antigen, tumor size, tumor differentiation, and T stage. The prognosis model based on these prognostic factors demonstrated excellent discriminatory performance in both derivation cohort (C-index, 0.71) and external validation cohort (C-index, 0.78), which outperformed the TNM staging system (C-index, 0.59) and individual prognostic factors (all C-index &lt; 0.7). Calibration plots, DCA and NRI also showed superior predictive performance. According to the risk for survival, the model stratified patients into low risk (median OS, 66.6 months; median RFS, 24.3 months) and high risk (median OS, 24.0 months; median RFS, 6.4 months) (P &lt; 0.001).

Conclusions

Our prognosis model can robustly predict the outcomes of ESICC after curative resection and provide precise evaluation on prognosis risk, facilitating clinicians to develop individualized postoperative treatment options.

Development of sarcopenia-based nomograms predicting postoperative complications of benign liver diseases undergoing hepatectomy: A multicenter cohort study

Background

Sarcopenia has a remarkable negative impact on patients with liver diseases. We aimed to evaluate the impact of preoperative sarcopenia on the short-term outcomes after hepatectomy in patients with benign liver diseases.

Methods

A total of 558 patients with benign liver diseases undergoing hepatectomy were prospectively reviewed. Both the muscle mass and strength were measured to define sarcopenia. Postoperative outcomes including complications, major complications and comprehensive complication index (CCI) were compared among four subgroups classified by muscle mass and strength. Predictors of complications, major complications and high CCI were identified by univariate and multivariate logistic regression analysis. Nomograms based on predictors were constructed and calibration cures were performed to verify the performance.

Results

120 patients were involved for analysis after exclusion. 33 patients were men (27.5%) and the median age was 54.0 years. The median grip strength was 26.5 kg and the median skeletal muscle index (SMI) was 44.4 cm²/m². Forty-six patients (38.3%) had complications, 19 patients (15.8%) had major complications and 27 patients (22.5%) had a CCI ≥ 26.2. Age (p = 0.005), SMI (p = 0.005), grip strength (p = 0.018), surgical approach (p = 0.036), and operation time (p = 0.049) were predictors of overall complications. Child-Pugh score (p = 0.037), grip strength (p = 0.004) and surgical approach (p = 0.006) were predictors of major complications. SMI (p = 0.047), grip strength (p < 0.001) and surgical approach (p = 0.014) were predictors of high CCI. Among the four subgroups, patients with reduced muscle mass and strength showed the worst short-term outcomes. The nomograms for complications and major complications were validated by calibration curves and showed satisfactory performance.

Conclusion

Sarcopenia has an adverse impact on the short-term outcomes after hepatectomy in patients with benign liver diseases and valuable sarcopenia-based nomograms were constructed to predict postoperative complications and major complications.

Cancer-Associated Fibroblasts in Hepatocellular Carcinoma and Cholangiocarcinoma

Primary liver cancer (PLC) includes hepatocellular carcinoma and intrahepatic cholangiocarcinoma and is the sixth most common cancer worldwide with poor prognosis. PLC is characterized by an abundant stromal reaction in which cancer-associated fibroblasts (CAFs) are one of the major stromal components. Solid evidence has demonstrated the crucial role of CAFs in tumor progression, and CAF abundance is often correlated with poor clinical outcomes. Although CAFs are regarded as an attractive and promising target for PLC treatment, a poor understanding of CAF origins and heterogeneity and a lack of specific CAF markers are the major hurdles to efficient CAF-specific therapy. In this review, we examine recent advances in the understanding of CAF diversity in the context of biomarkers, subtypes, and functions in PLC. The regulatory roles of CAFs in extracellular matrix remodeling, metastasis, cancer stemness, and therapeutic resistance are summarized. With an increasing link between CAF abundance and reduced antitumor immune responses, we provide updated knowledge on the crosstalk between CAFs and immune cells within the tumor microenvironment, which leads to immune resistance. In addition, we present current CAF-targeted therapies and describe some future perspectives. A better understanding of CAF biology will shed light on a novel therapeutic strategy against PLC.

Developing and validating a nomogram based on skeletal muscle index and clinical scoring system for prediction of liver failure after hepatectomy

Background and objectives

Hepatectomy is the preferred treatment for patients with liver tumors. Post-hepatectomy liver failure (PHLF) remains one of the most fatal postoperative complications. We aim to explore the risk factors of PHLF and create a nomogram for early prediction of PHLF.

Methods

We retrospectively analyzed patients undergoing hepatectomy at the Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University between 2015 and 2022, and the patients were divided into training and internal validation cohorts at an 8:2 ratio randomly. The patients undergoing liver resection from the Affiliated Huaian Hospital of Xuzhou Medical University worked as external validation. Then, a nomogram was developed which was based on multivariate analyses to calculate the risk of PHLF. The area under the ROC curve (AUROC) and Hosmer -Lemeshow test was used to evaluate the prediction effect of the model.

Results

A total of 421 eligible patients were included in our study. Four preoperative variables were identified after multivariate analysis as follows, ASA (American Society of Anesthesiologists) score, Child-Pugh score, SMI (Skeletal muscle index), and MELD (Model for end-stage liver disease) score as independent predictors of PHLF. The area under the ROC curve of the predictive model in the training, internal, and external validation cohorts were 0.89, 0.82, and 0.89. Hosmer -Lemeshow P values in the training, internal, and external validation cohorts were 0.91, 0.22, and 0.15. The Calibration curve confirmed that our nomogram prediction results were in accurate agreement with the actual occurrence of PHLF.

Conclusion

We construct a nomogram to predict the grade B/C PHLF of ISGLS (International Study Group of Liver Surgery) in patients who underwent hepatic resection based on risk factors. This tool can provide a visual and accurate preoperative prediction of the grade B/C PHLF and guide the next step of clinical decision-making.

Prognostic nomograms for HBV-related BCLC 0-a stage hepatocellular carcinoma incorporating aspartate aminotransferase to albumin ratio

BACKGROUND

Curative hepatectomy is currently the first-line treatment for hepatocellular carcinoma (HCC), but the prognosis is still not optimistic. The prediction model for prognosis of hepatitis B virus (HBV)-related BCLC 0-A stage HCC has not been well established. Therefore, we aimed to develop new nomograms to predict recurrence and survival in these patients.

METHODS

A total of 982 patients with HBV-related BCLC 0-A stage HCC who underwent curative hepatectomy at West China Hospital from February 2007 to February 2016 were retrospectively collected and randomly allocated to a training set and a validation set in a ratio of 4:1. Prognostic nomograms using data from the training set were developed using a Cox regression model and validated on the validation set.

RESULTS

We constructed nomograms based on independent factors for recurrence-free survival (RFS) (tumor size, satellite, microvascular invasion, capsular invasion, differentiation and aspartate aminotransferase to albumin ratio (ASAR)) and overall survival (OS) (gender, tumor size, satellite, microvascular invasion, differentiation, lymphocyte count, and ASAR). Compared with conventional HCC staging systems and other nomograms reported by previous literature, our ASAR integrated nomograms predicted RFS and OS with the highest C-indexes (0.682 (95%CI: 0.646-0.709), 0.729 (95%CI: 0.691-0.766), respectively) and had well-fitted calibration curves in the training set. Concurrently, the nomograms also obtained consistent results in the validation set. DCA revealed that our nomograms provided the largest clinical net benefits.

CONCLUSION

We first constructed ASAR integrated nomograms to predict the prognosis of HBV-related BCLC 0-A stage HCC patients after curative hepatectomy with good performance.

Development and validation of novel nomograms to predict survival of patients with tongue squamous cell carcinoma

BACKGROUND

There is no unified standard to predict postoperative survival in patients with tongue squamous cell carcinoma (TSCC), hence the urgency to develop a model to accurately predict the prognosis of these patients.

AIM

To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with TSCC.

METHODS

A cohort of 3454 patients with TSCC from the Surveillance, Epidemiology, and End Results (SEER) database was used to develop nomograms; another independent cohort of 203 patients with TSCC from the Department of Oral and Maxillofacial Surgery, First Affiliated Hospital of Zhejiang University School of Medicine, was used for external validation. Univariate and multivariate analyses were performed to identify useful variables for the development of nomograms. The calibration curve, area under the receiver operating characteristic curve (AUC) analysis, concordance index (C-index), net reclassification index (NRI), and decision curve analysis (DCA) were used to assess the calibration, discrimination ability, and clinical utility of the nomograms.

RESULTS

Eight variables were selected and used to develop nomograms for patients with TSCC. The C-index (0.741 and 0.757 for OS and CSS in the training cohort and 0.800 and 0.830 in the validation cohort, respectively) and AUC indicated that the discrimination abilities of these nomograms were acceptable. The calibration curves of OS and CSS indicated that the predicted and actual values were consistent in both the training and validation cohorts. The NRI values (training cohort: 0.493 and 0.482 for 3- and 5-year OS and 0.424 and 0.402 for 3- and 5-year CSS; validation cohort: 0.635 and 0.750 for 3- and 5-year OS and 0.354 and 0.608 for 3- and 5-year CSS, respectively) and DCA results indicated that the nomograms were significantly better than the tumor-node-metastasis staging system in predicting the prognosis of patients with TSCC.

CONCLUSION

Our nomograms can accurately predict patient prognoses and assist clinicians in improving decision-making concerning patients with TSCC in clinical practice.

Clinical value of predictive models based on liver stiffness measurement in predicting liver reserve function of compensated chronic liver disease

BACKGROUND

Assessment of liver reserve function (LRF) is essential for predicting the prognosis of patients with chronic liver disease (CLD) and determines the extent of liver resection in patients with hepatocellular carcinoma.

AIM

To establish noninvasive models for LRF assessment based on liver stiffness measurement (LSM) and to evaluate their clinical performance.

METHODS

A total of 360 patients with compensated CLD were retrospectively analyzed as the training cohort. The new predictive models were established through logistic regression analysis and were validated internally in a prospective cohort (132 patients).

RESULTS

Our study defined indocyanine green retention rate at 15 min (ICGR15) ≥ 10% as mildly impaired LRF and ICGR15 ≥ 20% as severely impaired LRF. We constructed predictive models of LRF, named the mLPaM and sLPaM, which involved only LSM, prothrombin time international normalized ratio to albumin ratio (PTAR), age and model for end-stage liver disease (MELD). The area under the curve of the mLPaM model (0.855, 0.872, respectively) and sLPaM model (0.869, 0.876, respectively) were higher than that of the methods for MELD, albumin-bilirubin grade and PTAR in the two cohorts, and their sensitivity and negative predictive value were the highest among these methods in the training cohort. In addition, the new models showed good sensitivity and accuracy for the diagnosis of LRF impairment in the validation cohort.

CONCLUSION

The new models had a good predictive performance for LRF and could replace the indocyanine green (ICG) clearance test, especially in patients who are unable to undergo ICG testing.

Development and validation of an efficient nomogram for risk assessment of norovirus infection in pediatric patients

This study aimed to establish a predictive model and nomogram based on routine laboratory blood indicators and clinical symptoms, subsequently providing a rapid risk assessment of norovirus (NoV) infection in children. This retrospective study enrolled 307 pediatric patients with symptoms of acute gastroenteritis and detected NoV using real-time quantitative polymerase chain reaction. Significant indicators selected by multivariate logistic regression, including routine blood tests and consultation symptoms, were used to develop the nomogram. We divided the sample into training and internal validation sets and performed external validation of the final model. Furthermore, we evaluated the clinical performance using the Akaike information criterion (AIC), area under the curve (AUC), calibration curve, decision curve analysis (DCA), sensitivity, specificity, concordance rate, positive predictive value, and negative predictive value. Overall, 153 cases were NoV-PCR-positive, and 154 were negative. The multivariate logistic regression included five predictors of NoV infection, including symptoms of vomiting, upper respiratory tract infection, and indicators of white blood cells, lymphocyte absolute counts, and platelet counts. The nomogram showed a significant predictive value with overall internal set diagnosis, with an AUC of 0.827 (95% confidence interval (CI): 0.785–0.868), and 0.812 (95% CI: 0.755–0.869) with 0.799 (95% CI: 0.705–0.894) in the training and internal validation sets, respectively. Nevertheless, the AUC in the external validation set was higher (0.915; 95% CI: 0.862–0.968). This nomogram is a useful tool for risk assessment for NoV infection. Moreover, the evaluated indicators are accessible, substantially reducing the time for laboratory testing.

Hepatocellular carcinoma

Hepatocellular carcinoma is one of the most common cancers worldwide and represents a major global health-care challenge. Although viral hepatitis and alcohol remain important risk factors, non-alcoholic fatty liver disease is rapidly becoming a dominant cause of hepatocellular carcinoma. A broad range of treatment options are available for patients with hepatocellular carcinoma, including liver transplantation, surgical resection, percutaneous ablation, and radiation, as well as transarterial and systemic therapies. As such, clinical decision making requires a multidisciplinary team that longitudinally adapts the individual treatment strategy according to the patient's tumour stage, liver function, and performance status. With the approval of new first-line agents and second-line agents, as well as the establishment of immune checkpoint inhibitor-based therapies as standard of care, the treatment landscape of advanced hepatocellular carcinoma is more diversified than ever. Consequently, the outlook for patients with hepatocellular carcinoma has improved. However, the optimal sequencing of drugs remains to be defined, and predictive biomarkers are urgently needed to inform treatment selection. In this Seminar, we present an update on the causes, diagnosis, molecular classification, and treatment of hepatocellular carcinoma.

An Integrative Multi-Omics Analysis Based on Nomogram for Predicting Prostate Cancer Bone Metastasis Incidence

Background

The most common site of prostate cancer metastasis is bone tissue with many recent studies having conducted genomic and clinical research regarding bone metastatic prostate cancer. However, further work is needed to better define those patients that are at an elevated risk of such metastasis.

Methods

SEER and TCGA databases were searched to develop a nomogram for predicting prostate cancer bone metastasis.

Results

Herein, we leveraged the Surveillance, Epidemiology, and End Results (SEER) database to construct a predictive nomogram capable of readily and accurately predicted the odds of bone metastasis in prostate cancer patients. This nomogram was utilized to assign patients with prostate cancer included in The Cancer Genome Atlas (TCGA) to cohorts at a high or low risk of bone metastasis (HRBM and LRBM, respectively). Comparisons of these LRBM and HRBM cohorts revealed marked differences in mutational landscapes between these patient cohorts, with increased frequencies of gene fusions, somatic copy number variations (CNVs), and single nucleotide variations (SNVs), particularly in the P53 gene, being evident in the HRBM cohort. We additionally identified lncRNAs, miRNAs, and mRNAs that were differentially expressed between these two patient cohorts and used them to construct a competing endogenous RNA (ceRNA) network. Moreover, three weighted gene co-expression network analysis (WGCNA) modules were constructed from the results of these analyses, with KIF14, MYH7, and COL10A1 being identified as hub genes within these modules. We further found immune response activity levels in the HRBM cohort to be elevated relative to that in the LRBM cohort, with single sample gene enrichment analysis (ssGSEA) scores for the immune checkpoint signature being increased in HRBM patient samples relative to those from LRBM patients.

Conclusion

We successfully developed a nomogram capable of readily detecting patients with prostate cancer at an elevated risk of bone metastasis.

Three-dimensional modeling in complex liver surgery and liver transplantation

Liver resection and transplantation are the most effective therapies for many hepatobiliary tumors and diseases. However, these surgical procedures are challenging due to the anatomic complexity and many anatomical variations of the vascular and biliary structures. Three-dimensional (3D) printing models can clearly locate and describe blood vessels, bile ducts and tumors, calculate both liver and residual liver volumes, and finally predict the functional status of the liver after resection surgery. The 3D printing models may be particularly helpful in the preoperative evaluation and surgical planning of especially complex liver resection and transplantation, allowing to possibly increase resectability rates and reduce postoperative complications. With the continuous developments of imaging techniques, such models are expected to become widely applied in clinical practice.

Quantitative parameters obtained from gadobenate dimeglumine-enhanced MRI at the hepatobiliary phase can predict post-hepatectomy liver failure and overall survival in patients with hepatocellular carcinoma

PURPOSE

To determine the value of the quantitative parameters obtained from gadobenate dimeglumine-enhanced magnetic resonance imaging (MRI) at the hepatobiliary phase for predicting post-hepatectomy liver failure and overall survival in patients with hepatocellular carcinoma.

METHOD

This multicenter retrospective study included 307 patients who underwent gadobenate dimeglumine-enhanced MRI. The quantitative liver-to-portal vein contrast ratio (LPC) and liver-spleen contrast ratio (LSC) at the hepatobiliary phase were measured. Logistic regression analyses were used to evaluate risk factors for post-hepatectomy liver failure. The capacity of the LPC and LSC to predict post-hepatectomy liver failure was evaluated via receiver operating characteristic (ROC) curve. The Cox proportional hazards regression was used to identify prognostic factors for overall survival (OS).

RESULTS

Post-hepatectomy liver failure was observed in 69 patients (22.5%). The LPC and LSC were independent risk factors for the development of post-hepatectomy liver failure, and the areas under the ROC curves of LPC and LSC were 0.882 and 0.782, respectively. The predictive performance of LPC for post-hepatectomy liver failure was superior to LSC. The LPC and LSC were also significant prognostic factors for OS. The cut-off values for the LPC and LSC were 1.07 and 0.89, respectively. The 5-year OS rate was higher in patients with LPC > 1.07 or LSC > 0.89 than in patients with LPC ≤ 1.07 or LSC ≤ 0.89.

CONCLUSIONS

The quantitative parameters obtained from gadobenate dimeglumine-enhanced MRI at the hepatobiliary phase were effective imaging biomarkers for predicting both post-hepatectomy liver failure and overall survival in patients with hepatocellular carcinoma.

The value of gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase for predicting post-hepatectomy liver failure in HCC patients

OBJECTIVES

To determine the value of gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC).

METHODS

Patients with HCC who underwent gadobenate dimeglumine-enhanced hepatobiliary magnetic resonance imaging prior to hepatectomy were collected in two centers. The relative enhancement ratio of the biliary system (REB) and the liver to muscle ratio (LMR) were measured at the hepatobiliary phase. Potential risk factors for PHLF were analyzed by logistic regression. The capacity of the REB and LMR to predict PHLF was analyzed via receiver operating characteristic curve.

RESULTS

Of the 221 patients, post-hepatectomy liver failure occurred in 60 patients (27.1%). The REB was an independent risk factor for PHLF (odds ratio [OR] = 0.127 [0.047-0.348], p < 0.001). Although the LMR tended to be associated with PHLF (p = 0.063), it was not an independent risk factor in the multivariable analysis (OR = 0.624 [0.023-16.709], p = 0.779). Moreover, the area under the receiver operating characteristic curve of the REB and LMR was 0.87 and 0.60. The most appropriate cutoff value for the REB was 2.21. The HCC patients with the REB ≤ 2.21 had a higher incidence of post-hepatectomy liver failure than those with the REB > 2.21 (60.0% versus 8.5%, p < 0.001).

CONCLUSIONS

Gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase was valuable in predicting post-hepatectomy liver failure in HCC patients.

KEY POINTS

• The relative enhancement ratio of the biliary system (REB) was an independent risk factor for post-hepatectomy liver failure in HCC patients. • HCC patients with the REB ≤ 2.21 had significantly higher incidence of post-hepatectomy liver failure than those with the REB > 2.21 (60.0% versus 8.5%).

An Efficient Nomogram for Discriminating Intrahepatic Cholangiocarcinoma From Hepatocellular Carcinoma: A Retrospective Study

Objective

This study aims to establish a nomogram and provide an effective method to distinguish between intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).

Methods

A total of 1,591 patients with HCC or ICC hospitalized at Shandong Provincial Hospital between January 2016 and August 2021 were included and randomly divided into development and validation groups in a ratio of 3:1. Univariate and multivariate analyses were performed to determine the independent differential factors between HCC and ICC patients in the development cohort. By combining these independent differential factors, the nomogram was established for discriminating ICC from HCC. The accuracy of the nomogram was estimated by using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Furthermore, the predictive nomogram was assessed in the internal testing set.

Results

Through multivariate analysis, independent differential factors between HCC and ICC involved hepatitis B virus (HBV), logarithm of alpha-fetoprotein (Log AFP), logarithm of protein induced by vitamin K absence or antagonist-II (Log PIVKA-II), logarithm of carbohydrate antigen 199 (Log CA199), and logarithm of carbohydrate antigen 125 (Log CA125). A nomogram was finally established by incorporating these five independent differential factors. Comparing a model of conventional tumor biomarkers including AFP and CA199, the nomogram showed a better distinction between ICC and HCC. The area under the ROC curve (AUC) of ICC diagnosis was 0.951 (95% CI, 0.938–0.964) for the nomogram. The results were consistent in the validation cohort with an AUC of 0.958 (95% CI, 0.938–0.978). After integrating patient preferences into the analysis, the DCA showed that using this nomogram to distinguish ICC and HCC increased more benefit compared with the conventional model.

Conclusion

An efficient nomogram has been established for the differential diagnosis between ICC and HCC, which may facilitate the detection and diagnosis of ICC. Further use of the nomogram in multicenter investigations will confirm the practicality of the tool for future clinical application.

A Novel Nomogram for Predicting Risk Factors and Outcomes in Bloodstream Infections Caused by Klebsiella pneumoniae

Background

Our study aimed to explore the risk factors in bloodstream infections Klebsiella pneumoniae (BSI-KP) patients and establish nomograms to predict the probability of BSI-CRKP and the prognosis of BSI-KP.

Methods

A total of 252 BSI-KP patients were enrolled from a tertiary teaching hospital between January 1, 2015, and May 31, 2020. Risk factors associated with BSI-CRKP and factors associated with the 30-day mortality were identified using LASSO analysis, univariate and multivariate analysis.

Results

There were 121 (48.0%) patients with carbapenem-resistant K. pneumoniae (CRKP) and 131 (52.0%) patients with carbapenem-susceptible K. pneumoniae (CSKP). The multivariate logistic regression analysis demonstrated that gastric tube indwelling before BSI (OR=2.442, P=0.043) and more types of antibiotics use before BSI (OR=1.305, P=0.009) were independent risk factors for BSI-CRKP. And previous transplantations, prior ICU stay, gastric tube indwelling before BSI, more types of antibiotics use before BSI, lower Hb and cholinesterase were associated with CRKP-BSI. The C-index of models indicated its good accuracy (C-index 0.816, 95% CI 0.763-0.868). In patients with BSI-CRKP, further logistic regression analysis revealed urinary catheterization (OR=0.298, P=0.017) was found to be an independent risk factor for 30-day mortality, while ceftazidime/avibactam use (OR=8.438, P=0.003) was an independent favorable prognostic factor. The nomogram predicated CRKP, ICU hospitalization, more types of antibiotics use, tigecycline, PLT, urinary catheterization were associated with 30-day mortality in patients with BSI-KP. The discriminative ability of the predictive model, as assessed by C-index, was 0.813 (95% CI: 0.780-0.867).

Conclusion

Previous transplantations, prior ICU stay, gastric tube indwelling before BSI, more types of antibiotics use before BSI, lower Hb and cholinesterase represent significant risk factors for the development of BSI-CRKP. Our nomogram predicated thrombocytopenia was a sign for poor prognosis. Tigecycline resulted in higher mortality for patients with BSI-KP. Rational use of nomograms may help clinicians make better Clinical decisions when treating BSI-KP patients.

A postresection perfusion deficit in the right colon is an independent predictor of perioperative outcome after major hepatectomy

BACKGROUND

There is a strong interaction between hepatic hemodynamics and perfusion in the splanchnic system. However, little is known about differences in perfusion in different splanchnic compartments and their changes after hepatectomy.

METHODS

Perfusion in various splanchnic compartments (ie, stomach, small intestine, right and left colon, liver) was assessed pre- and post-hepatectomy by intraoperative laser Doppler flowmetry. Differences of splanchnic perfusion between compartments were evaluated by ANOVA, and risk factors of postoperative complications (graded by the comprehensive complication index [CCI]) were analyzed by univariate and multivariate analyses. A prediction model of postoperative complications was developed.

RESULTS

A total of 50 and 29 patients with major and minor hepatectomy were enrolled. Splanchnic perfusion at baseline varied significantly across different splanchnic compartments with highest values in the small bowel and right colon (P < .001). Major hepatectomy induced a significant perfusion decrease in the stomach (P = .006), right colon (P < .001) and small bowel (P = .035). A postresection perfusion deficit in the right colon with values below 254 perfusion units (PU) was identified as an independent predictor of clinically relevant complications after major hepatectomy (concordance index: 0.79, 95% CI 0.66-0.87, P = .002). Bootstrap validation confirmed internal validity and excellent calibration.

CONCLUSIONS

Major hepatectomy causes significant reduction of splanchnic perfusion. An intraoperative posthepatectomy microcirculatory perfusion deficit of the right colon is a strong and independent predictor of clinically relevant postoperative complications after major hepatectomy.

Liver stiffness measured by virtual touch quantification predicts the occurrence of posthepatectomy refractory ascites in patients with hepatocellular carcinoma

PURPOSE

This study assessed the significance of measuring liver stiffness using virtual touch quantification before hepatectomy to predict posthepatectomy refractory ascites.

METHODS

A total of 267 patients with hepatocellular carcinoma who underwent hepatectomy were prospectively analyzed. Liver stiffness was defined as the median value of the virtual touch quantification (Vs; m/s) by acoustic radio-force-impulse-based virtual touch.

RESULTS

A multivariate analysis showed that Vs and the aspartate aminotransferase-to-platelet ratio index were independent risk factors for postoperative refractory ascites (odds ratio = 3.27 and 3.08, respectively). The cutoff value for Vs was 1.52 m/s (sensitivity: 59.5%, specificity: 88.6%) as determined by the analysis of the receiver-operating characteristic curve, and the area under the receiver-operating characteristic curve was 0.79. The cutoff value for the aspartate aminotransferase-to-platelet ratio was 0.952 (sensitivity: 65.5%, specificity: 82.9%), and the area under the receiver-operating characteristic curve was 0.75.

CONCLUSIONS

Vs is an independent risk factor for refractory ascites after hepatectomy. The measurement of liver stiffness by virtual touch quantification before hepatectomy can help estimate the risk of postoperative refractory ascites. Nonsurgical treatments should be considered for the management of patients who are at high risk for refractory ascites.

Development of Models to Predict Postoperative Complications for Hepatitis B Virus-Related Hepatocellular Carcinoma

Background

Surgical treatment remains the best option for patients with hepatocellular carcinoma (HCC) caused by chronic hepatitis B virus (HBV) infection. However, there is no optimal tool based on readily accessible clinical parameters to predict postoperative complications. Herein, our study aimed to develop models that permitted risk of severe complications to be assessed before and after liver resection based on conventional variables.

Methods

A total of 1,047 patients treated by hepatectomy for HCC with HBV infection at three different centers were recruited retrospectively between July 1, 2014, and July 1, 2018. All surgical complications were recorded and scored by the Comprehensive Complication Index (CCI). A CCI ≥26.2 was used as a threshold to define patients with severe complications. We built two models for the CCI, one using preoperative and one using preoperative and postoperative data. Besides, CCI and other potentially relevant factors were evaluated for their ability to predict early recurrence and metastasis. All the findings were internally validated in the Hangzhou cohort and then externally validated in the Lanzhou and Urumqi cohorts.

Results

Multivariable analysis identified National Nosocomial Infections Surveillance (NNIS) index, tumor number, gamma-glutamyltransferase (GGT), total cholesterol (TC), potassium, and thrombin time as the key preoperative parameters related to perioperative complications. The nomogram based on the preoperative model [preoperative CCI After Surgery for Liver tumor (CCIASL-pre)] showed good discriminatory performance internally and externally. A more accurate model [postoperative CCI After Surgery for Liver tumor (CCIASL-post)] was established, combined with the other four postoperative predictors including leukocyte count, basophil count, erythrocyte count, and total bilirubin level. No significant association was observed between CCI and long-term complications.

Conclusion

Based on the widely available clinical data, statistical models were established to predict the complications after hepatectomy in patients with HBV infection. All the findings were extensively validated and shown to be applicable nationwide. Such models could be used as guidelines for surveillance follow-up and the design of post-resection adjuvant therapy.

A New Clinical Nomogram From the TCGA Database to Predict the Prognosis of Hepatocellular Carcinoma

Background and Aim

Hepatocellular carcinoma is a common malignant tumor of the digestive system with a poor prognosis. The high recurrence rate and metastasis after surgery reduce the survival time of patients. Therefore, assessing the overall survival of patients with hepatocellular carcinoma after hepatectomy is critical to clinicians' clinical decision-making. Conventional hepatocellular carcinoma assessment systems (such as tumor lymph node metastasis and Barcelona clinical hepatocellular carcinoma) are obviously insufficient in assessing the overall survival rate of patients. This research is devoted to the development of nomogram assessment tools to assess the overall survival probability of patients undergoing liver resection.

Methods

We collected the clinical and pathological information of 438 hepatocellular carcinoma patients undergoing surgery from The Cancer Genome Atlas (TCGA) database, then excluded 87 patients who did not meet inclusion criteria. Univariate and multivariate analyses were performed on patient characteristics and related pathological factors. Finally, we developed a nomogram model to predict patient's prognosis.

Results

A retrospective analysis of 438 consecutive samples from the TCGA database of patients with hepatocellular carcinoma who underwent potentially curative liver resections. Six risk factors were included in the final model. In the training set, the discriminative ability of the nomogram was very good (concordance index = 0.944), and the external verification method (concordance index = 0.962) was used for verification. At the same time, the internal and external calibration of the model was verified, showing that the model was well calibrated. The calibration between the evaluation of the nomogram and the actual observations was good. According to the patient's risk factors, we determined the patient's Kaplan-Meyer survival analysis curve. Finally, the clinical decision curve was used to compare the benefits of two different models in evaluating patients' clinical outcomes.

Conclusions

The nomogram can be used to evaluate the post-hepatectomy 1-, 3-, and 5-year survival rates of patients with hepatocellular carcinoma. The Kaplan-Meyer curve can intuitively display the survival differences among patients with various risk factors. The clinical decision curve is a good reference guide for clinical application.

A nomogram to predict stricture-free survival in patients with ureteral stricture after balloon dilation

Background

Balloon dilation is a commonly used minimally invasive endourological treatment of ureteral stricture, but the postoperative recurrence rate is relatively high. And factors contributing to recurrence after treatment are poorly understood. Herein, we sought to develop a novel clinical nomogram to predict ureteral stricture-free survival in patients suffering from ureter stricture and performed balloon dilation.

Methods

The nomogram was established based on a retrospective analysis of 321 patients who received endoscopic balloon dilation alone for ureter strictures from January 2016 to January 2020 in Sun Yat-sen Memorial Hospital using the Cox regression model. Perioperative clinical data and disease outcomes were analyzed. The primary endpoint was the onset of ureteral re-stricture after ureter balloon dilation. Discrimination of the nomogram was assessed by the concordance index (C-index) and the calibration curve. The results were internally validated using bootstrap resampling.

Results

Overall, 321 patients with a median follow-up of 590 days were enrolled in the study, among which 97 patients (30.2%) developed recurrence of ureteral stricture during follow-up. Five variables remained significant predictors of ureteral re-stricture after multivariable analyses: stricture nature (P < 0.001), urinary nitrite (P = 0.041), CKD (P = 0.005), stent retention time (P < 0.001), and balloon size (P = 0.029). The calibration craves for the probability of 1-, 3-, and 5-years stricture-free survival (SFS) presented satisfied with the consistency of nomogram prediction and actual observation. The C-index of the model was 0.74 (95% CI 0.70–0.79).

Conclusions

Our study developed the first nomogram to effectively predict stricture-free survival in patients suffering from ureter stricture after balloon dilation. It is helpful to identify the optimal patients with ureter stricture for balloon dilation and improve treatment outcomes. However, further external validation of the nomogram is warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-021-00896-3.

Nomogram for predicting pathologic complete response after transarterial chemoembolization in patients with hepatocellular carcinoma

Background

The pathologic responses to transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) are heterogeneous and result in disparate outcomes. The study aimed to establish and validate an effective nomogram for predicting pathologic complete response (PCR) after TACE.

Methods

We analyzed the clinicopathologic characteristics of HCC patients undergoing hepatectomy following TACE. Variables with statistical significance in a multivariate logistic regression analysis were incorporated in the nomogram.

Results

We detected PCR in 64 (50.4%) patients in the training cohort and 18 (37.5%) patients in the validation cohort. Univariable and multivariable logistic regression revealed that hepatitis B virus (HBV) DNA load (P=0.031), α-fetoprotein (AFP, P=0.040), maximum tumor diameter (P=0.003), preoperative TACE session (P=0.026), and modified Response Evaluation Criteria in Solid Tumors (mRECIST) complete response (P=0.030) were identified as significant predictors of PCR. Incorporating these 5 factors, a nomogram was developed which attained concordance indexes of 0.80 [95% confidence interval (CI): 0.72–0.87] and 0.82 (95% CI: 0.68–0.95) for predicting PCR in the training and validation cohorts, respectively.

Conclusions

The easy-to-use nomogram achieved a good post-TACE prediction of PCR in HCC patients. Using the model, patients who would benefit most from TACE could be identified, and the subsequent appropriate procedures could be guided accordingly.

Gastrectomy history as a predictor of post-hepatectomy complications

PURPOSE

The effect of a history of gastrectomy on patients undergoing hepatectomy is unclear. We investigated the relationship between postoperative complications of Clavien-Dindo grade III or higher and a history of gastrectomy in patients undergoing hepatectomy.

METHODS

The subjects of this retrospective analysis were 474 consecutive patients who underwent hepatectomy at our institute for hepatic malignancy, classified into groups of those with or without a history of gastrectomy and those with or without postoperative complications. We compared the clinicopathological factors between the groups.

RESULTS

There were no hospital deaths. Gastrectomy history was identified in 22 patients (4.6%) and was significantly associated with advanced age, low body mass index, male sex, decreased serum albumin level, decreased hemoglobin level, low PNI, low CONUT score, high incidence of postoperative complications, and longer hospital stay. Multivariate analyses revealed that the independent risk factors for postoperative complications were gastrectomy history, an albumin-bilirubin score of 2/3, primary liver cancer, high serum creatinine level, advanced age, and prolonged operation time.

CONCLUSIONS

Gastrectomy history was an independent predictor of postoperative complications in patients undergoing hepatectomy for hepatic malignancies. Patients with a history of gastrectomy were likely to suffer postoperative bile leakage and pneumonia.

Somatostatin Therapy Improves Stellate Cell Activation and Early Fibrogenesis in a Preclinical Model of Extended Major Hepatectomy

Liver resection treats primary and secondary liver tumors, though clinical applicability is limited by the remnant liver mass and quality. Herein, major hepatic resections were performed in pigs to define changes associated with sufficient and insufficient remnants and improve liver-specific outcomes with somatostatin therapy. Three experimental groups were performed: 75% hepatectomy (75H), 90% hepatectomy (90H), and 90% hepatectomy + somatostatin (90H + SST). Animals were followed for 24 h (N = 6) and 5 d (N = 6). After hepatectomy, portal pressure gradient was higher in 90H versus 75H and 90H + SST (8 (3-13) mmHg vs. 4 (2-6) mmHg and 4 (2-6) mmHg, respectively, p < 0.001). After 24 h, changes were observed in 90H associated with stellate cell activation and collapse of sinusoidal lumen. Collagen chain type 1 alpha 1 mRNA expression was higher, extracellular matrix width less, and percentage of collagen-staining areas greater at 24 h in 90H versus 75H and 90H + SST. After 5 d, remnant liver mass was higher in 75H and 90H + SST versus 90H, and Ki-67 immunostaining was higher in 90H + SST versus 75H and 90H. As well, more TUNEL-staining cells were observed in 90H versus 75H and 90H + SST at 5 d. Perioperative somatostatin modified portal pressure, injury, apoptosis, and stellate cell activation, stemming changes related to hepatic fibrogenesis seen in liver remnants not receiving treatment.