The Systemic Immune Inflammation Index (SII) Combined with the Creatinine-to-Cystatin C Ratio (Cre/CysC) Predicts Sarcopenia in Patients with Liver Cirrhosis Complicated with Primary Hepatocellular Carcinoma.

BACKGROUND: Sarcopenia is a risk factor for poor cancer prognosis. Early identification and timely intervention of sarcopenia can improve patient prognosis. METHODS: A total of 91 patients with liver cirrhosis complicated with primary hepatocellular carcinoma were retrospectively analyzed. Based on the results of multivariable logistic regression analysis, a nomogram was developed. Moreover, 50 patients were enrolled for external validation. The predictive efficacy of the nomogram was evaluated using the receiver operating characteristic curve (ROC). RESULTS: According to the logistic regression analysis results, age, body mass index (BMI), creatinine-to-cystatin C ratio (Cre/CysC), and systemic immune inflammation index (SII) were independent risk factors of sarcopenia in patients with cirrhosis complicated with primary hepatocellular carcinoma (HCC) (all p < 0.05). The ABCS nomogram model was established, and the area under the ROC curve (AUC) was 0.896 (84.7% sensitivity, 81.2% specificity). The calibration curve of the nomogram was close to the ideal diagonal line. The predictive efficacy of the nomogram was verified through the external validation. CONCLUSION: The ABCS model based on SII and Cre/CysC can be used to identify high-risk sarcopenia in patients with cirrhosis complicated with HCC in the early stage.

Establishment of a prognostic model for hospitalized cirrhotic patients with infection based on lumbar muscle mass.

Background: Sarcopenia frequently complicates cirrhosis and leads to substantial mortality. Infection is a complication of cirrhosis that results in high mortality. Both sarcopenia and infection are accompanied by systemic inflammation and adversely affect the prognosis of cirrhosis. This article was designed to decipher the association of sarcopenia with infection occurrence, and to ascertain the risk factors for the 90-day death rate in hospitalized cirrhotic patients with infection. Methods: A total of 808 cirrhotic patients (373 with infection and 435 without) who had undergone abdominal CT from 2017 to 2021 were recruited for this retrospective single-center research. The skeletal muscle index was assessed at the level of the third lumbar vertebra (L3 SMI). The optimal cutoff value of the CAIL3 model (CTP score, AKI, INR, and L3 SMI) for the prediction of the 90-day death rate was authenticated with receiver operating characteristic (ROC) analysis. Results: L3 SMI was considered to be the independent risk factor for infection in cirrhotic patients and 90-day death rate in these patients with infection (HR 2.840 95% CI 2.076-3.886, p < 0.001 for infection and HR 2.097 95% CI 1.142-3.850, p = 0.017 for 90-day death rate, respectively). CAIL3 had an area under the ROC curve of 0.840, and a cutoff value of 0.21 for predicting the poor outcome (sensitivity 77.22% and specificity 76.53%, respectively). Conclusion: L3 SMI is an essential factor associated with infection and 90-day death rate in cirrhotic patients. CAIL3 may be a novel model for the prediction of the 90-day death risk in cirrhotic patients with infections.

Assessing recent recurrence after hepatectomy for hepatitis B-related hepatocellular carcinoma by a predictive model based on sarcopenia.

BACKGROUND: Sarcopenia may be associated with hepatocellular carcinoma (HCC) following hepatectomy. But traditional single clinical variables are still insufficient to predict recurrence. We still lack effective prediction models for recent recurrence (time to recurrence < 2 years) after hepatectomy for HCC. AIM: To establish an interventable prediction model to estimate recurrence-free survival (RFS) after hepatectomy for HCC based on sarcopenia. METHODS: We retrospectively analyzed 283 hepatitis B-related HCC patients who underwent curative hepatectomy for the first time, and the skeletal muscle index at the third lumbar spine was measured by preoperative computed tomography. 94 of these patients were enrolled for external validation. Cox multivariate analysis was per-formed to identify the risk factors of postoperative recurrence in training cohort. A nomogram model was developed to predict the RFS of HCC patients, and its predictive performance was validated. The predictive efficacy of this model was evaluated using the receiver operating characteristic curve. RESULTS: Multivariate analysis showed that sarcopenia [Hazard ratio(HR) = 1.767, 95%CI: 1.166-2.678, P < 0.05], alpha-fetoprotein ≥ 40 ng/mL (HR = 1.984, 95%CI: 1.307-3.011, P < 0.05), the maximum diameter of tumor > 5 cm (HR = 2.222, 95%CI: 1.285-3.842, P < 0.05), and hepatitis B virus DNA level ≥ 2000 IU/mL (HR = 2.1, 95%CI: 1.407-3.135, P < 0.05) were independent risk factors associated with postoperative recurrence of HCC. Based on the sarcopenia to assess the RFS model of hepatectomy with hepatitis B-related liver cancer disease (SAMD) was established combined with other the above risk factors. The area under the curve of the SAMD model was 0.782 (95%CI: 0.705-0.858) in the training cohort (sensitivity 81%, specificity 63%) and 0.773 (95%CI: 0.707-0.838) in the validation cohort. Besides, a SAMD score ≥ 110 was better to distinguish the high-risk group of postoperative recurrence of HCC. CONCLUSION: Sarcopenia is associated with recent recurrence after hepatectomy for hepatitis B-related HCC. A nutritional status-based prediction model is first established for postoperative recurrence of hepatitis B-related HCC, which is superior to other models and contributes to prognosis prediction.

A prognostic model of acute-on-chronic liver failure based on sarcopenia.

BACKGROUND: Acute-on-chronic liver failure (ACLF) is characterized by the development of a syndrome associated with a high risk of short-term death in patients with acute decompensated cirrhosis, and better indicators are needed to predict such outcomes. Sarcopenia, a common complication of cirrhosis, is closely associated with poor prognosis and increased mortality. In this study, the skeletal muscle index of ACLF patients was measured to determine whether sarcopenia combined with clinical parameters can aid in identifying those at high risk of progression. METHODS: A total of 433 hospitalized patients with ACLF according to the APASL criteria were included and allocated into two groups: transplantation-free survival (n = 293) or progression (n = 140, 107 died; 33 underwent liver transplantation) within 90 days. Muscle mass was assessed based on the skeletal muscle index. The optimal cut-off value of the AMPAS1 model (age, MELD score, platelet count, alpha-fetoprotein level, sarcopenia, and more than one complication combination) for progression prediction was identified using receiver-operating characteristic (ROC) analysis. RESULTS: Sarcopenia was an independent risk factor for progression in the ACLF population (HR 3.771 95% CI 2.114-6.727, p < 0.001). AMPAS1 was a good predictor, with an area under the ROC curve of 0.865, and the cut-off value for poor outcome prediction was 0.31 (sensitivity 79.4%, specificity 76.4%). CONCLUSION: We demonstrate that sarcopenia is a simple and objective indicator for predicting short-term prognosis in patients with ACLF. Moreover, compared to conventional prognostic scores, AMPAS1 is a better model for predicting 90 day adverse outcomes in ACLF patients.

The role of lymph node status in cancer-specific survival and decision-making of postoperative radiotherapy in poorly differentiated thyroid cancer: a population-based study.

OBJECTIVE: This study aimed to investigate the prognostic value of lymph node (LN) status for patients with poorly differentiated thyroid cancer (PDTC), and to develop a reliable nomogram to predict the 3-, 5- and 10-year cancer-specific survival (CSS) and assist the decision-making of postoperative radiotherapy (PORT). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was utilized to screen eligible patients who were diagnosed between 2004 and 2016. The optimal values of age, metastatic lymph node ratio (LNR), and the number of metastatic lymph nodes (MLN) were determined and incorporated into the construction of a nomogram. The performance of the model was evaluated by generating a calibration curve and calculating the consistency index (C-index). Based on the nomogram, patients were classified into three risk cohorts. The prognostic efficacy of PORT was evaluated in each cohort. RESULTS: A total of 522 PDTC patients were included in this study. The LN status-associated parameters (MLN and LNR) were independent risk factors for CSS of PDTC patients. Based on MLN, LNR, and other clinical characteristics (age and T stage), an individualized nomogram was constructed that showed an acceptable predictive performance. Furthermore, we proposed a novel risk-classification system to stratify PDTC patients and to assess the prognostic efficacy of PORT. Only patients in high-risk cohort were found eligible to benefit from PORT. CONCLUSION: LN status is statistically associated with the prognosis of PDTC patients. In addition, the individualized nomogram may be a significant tool to assist the evaluation of patients' long-term prognosis and to guide the decision-making for PORT.