Dual-Energy Computed Tomography Parameters Combined With Inflammatory Indicators Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer.

BACKGROUND AND OBJECTIVE: Cervical lymph node metastasis (CLNM) is considered a marker of papillar Fethicy thyroid cancer (PTC) progression and has a potential impact on the prognosis of PTC. The purpose of this study was to screen for predictors of CLNM in PTC and to construct a predictive model to guide the surgical approach in patients with PTC. METHODS: This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves. RESULTS: The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively. CONCLUSION: The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.

Transarterial chemoembolization with molecular targeted therapies plus camrelizumab for recurrent hepatocellular carcinoma.

BACKGROUND: The safety and efficacy of transarterial chemoembolization plus molecular targeted therapy (MTT) combined with immune checkpoint inhibitors (ICIs) in primary liver cancer have been demonstrated. However, the evidence for TACE plus MTT combined with ICIs in the treatment of recurrent hepatocellular carcinoma (RHCC) is limited. Given the excellent performance of this combination regimen in primary liver cancer, it is necessary to evaluate the efficacy of TACE plus MTT combined with ICIs in RHCC. METHODS: A total of 88 patients with RHCC treated with TACE plus MTT combined with camrelizumab (TACE-TC group, n = 46) or TACE plus MTT (TACE-T group, n = 42) were retrospectively collected and analyzed. In this study, we evaluated the effectiveness and safety of combination therapy for patients with RHCC by analyzing tumor response, progression-free survival (PFS), overall survival (OS), laboratory biochemical indices, and adverse events (AEs). RESULTS: TACE-TC was superior to TACE-T in PFS (14.0 vs. 8.9 months, p = 0.034) and OS (31.1 vs. 20.2 months, p = 0.009). Moreover, TACE-TC achieved more preferable benefits with respect to disease control rate (89.1% vs. 71.4%, p = 0.036) and objective response rate (47.8% vs. 26.2%, p = 0.036) compared with TACE-T in patients with RHCC. Compared with the TACE-T group, the AFP level in the TACE-TC group decreased more significantly after 3 months of treatment. Multivariate analysis showed that treatment option was a significant predictor of OS and PFS, while the portal vein tumor thrombus and interval of recurrence from initial treatment were another prognostic factor of PFS. There was no significant difference between the TACE-TC and TACE-T groups for Grade 3-4 adverse events. CONCLUSIONS: A combination therapy of TACE, MTT, and camrelizumab significantly improved tumor response and prolonged survival duration, showing a better survival prognosis for RHCC patients.

Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients.

OBJECTIVE: To explore the value of body composition changes (BCC) measured by quantitative computed tomography (QCT) for evaluating the survival of patients with locally advanced cervical cancer (LACC) underwent concurrent chemoradiotherapy (CCRT), nomograms combined BCC with clinical prognostic factors (CPF) were constructed to predict overall survival (OS) and progression-free survival (PFS). METHODS: Eighty-eight patients with LACC were retrospectively selected. All patients underwent QCT scans before and after CCRT, bone mineral density (BMD), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), paravertebral muscle area (PMA) were measured from two sets of computed tomography (CT) images, and change rates of these were calculated. RESULTS: Multivariate Cox regression analysis showed ΔBMD, ΔSFA, SCC-Ag, LNM were independent factors for OS (HR = 3.560, 5.870, 2.702, 2.499, respectively, all P < 0.05); ΔPMA, SCC-Ag, LNM were independent factors for PFS (HR = 2.915, 4.291, 2.902, respectively, all P < 0.05). Prognostic models of BCC combined with CPF had the highest predictive performance, and the area under the curve (AUC) for OS and PFS were 0.837, 0.846, respectively. The concordance index (C-index) of nomograms for OS and PFS were 0.834, 0.799, respectively. Calibration curves showed good agreement between the nomograms' predictive and actual OS and PFS, decision curve analysis (DCA) showed good clinical benefit of nomograms. CONCLUSION: CT-based body composition changes and CPF (SCC-Ag, LNM) were associated with survival in patients with LACC. The prognostic nomograms combined BCC with CPF were able to predict the OS and PFS in patients with LACC reliably.

Body composition predicts prognosis of hepatocellular carcinoma patients undergoing immune checkpoint inhibitors.

PURPOSE: Immune checkpoint inhibitors (ICIs) with anti-PD-1/PD-L1 antibody are promising treatments for hepatocellular carcinoma (HCC), but lack reliable biomarkers of response. In the present study, we aimed to investigate the correlation between pre-treatment body composition measures (muscle, adipose, etc.) and the prognosis of patients with HCC treated with ICIs. METHODS: We measured the total area of all skeletal muscles, total adipose tissue area, subcutaneous adipose tissue area, and visceral adipose tissue area at the level of the third lumbar vertebra using quantitative CT. Then, we calculated the skeletal muscle index, visceral adipose tissue index, subcutaneous adipose tissue index (SATI), and total adipose tissue index. The Cox regression model was used to determine the independent factors of the patient prognosis and construct a nomogram to predict survival. The consistency index (C-index) and calibration curve were used to determine the predictive accuracy and discrimination ability of the nomogram. RESULTS: Multivariate analysis revealed that the SATI (high- vs. low SATI; HR 0.251; 95% CI 0.109-0.577; P = 0.001), sarcopenia (sarcopenia vs. no sarcopenia; HR 2.171; 95% CI 1.100-4.284; P = 0.026), and portal vein tumor thrombus (PVTT) (PVTT vs. No PVTT; HR 2.429; 95% CI 1. 197-4. 929; P = 0.014) were indicated as independent prognostic factors for OS in multivariate analysis. Multivariate analysis indicated that Child-Pugh class (HR 0.477, 95% CI 0.257-0.885, P = 0.019) and sarcopenia (HR 2.376, 95% CI 1.335-4.230, P = 0.003) were independent prognostic factors of PFS. We established a nomogram using SATI, SA, and PVTT to predict the 12-month and 18-month survival probability of HCC patients treated with ICIs. The C-index of the nomogram was 0.754 (95% CI 0.686-0.823), and the calibration curve confirmed that the predicted results were in good agreement with the actual observations. CONCLUSION: Subcutaneous adipose and sarcopenia are significant prognostic factors of patients with HCC receiving ICIs. A nomogram based on body composition parameters and clinical factors could well predict survival in HCC patients treated with ICIs.