Albumin-myosteatosis gauge as a novel prognostic risk factor in patients with non-metastatic colorectal cancer

Albumin-myosteatosis gauge as a prognostic factor in patients with advanced pancreatic cancer undergoing first-line chemotherapy

BACKGROUND

Sarcopenia and myosteatosis have been associated with a poor prognosis for several cancers. The albumin-myosteatosis gauge (AMG) is a novel integrated measure proposed to assess myosteatosis along with serum albumin level as a surrogate of systemic inflammation and malnutrition. The aim of this study was to investigate the prognostic value of AMG in patients with advanced pancreatic ductal adenocarcinoma (PDAC).

METHODS

Patients with advanced PDAC treated with chemotherapy between 2013 and 2022 were evaluated. Skeletal muscle radiodensity (SMD) and skeletal muscle index (SMI) were calculated using computed tomography at the level of the L3 vertebra. The AMG was defined as albumin x SMD and expressed as an arbitrary unit (AU). Patients were first categorized by sex-specific quartiles and then dichotomized at the sex-specific median value of the AMG.

RESULTS

A total of 196 patients were included. The median age (interquartile range) was 62 (54-67), and 128 (65.3%) were male. With regard to AMG, 142.86 and 114.15 AU were identified as cutoff values for males and females, respectively. In multivariable analyses, lower AMG values (G1-G2 vs. G3-G4) (HR: 1.61, 95% CI 1.17-2.21, p = 0.003), higher ECOG performance score (> 0 vs. 0) (HR: 1.51, 95% CI 1.10-2.06, p = 0.009) and metastatic disease (vs. locally advanced) (HR: 1.88, 95% CI 1.27-2.79, p = 0.001) were associated with OS.

CONCLUSION

The study findings suggest the prognostic value of AMG in patients with advanced PDAC undergoing first-line chemotherapy. Further studies are warranted to validate these findings and assess potential predictive role of AMG in guiding treatment selection.

Sarcopenia diagnosis in patients with colorectal cancer: a review of computed tomography-based assessments and emerging ways to enhance practicality

Traditionally, cancer treatment has focused on the stages of the disease; however, recent studies have highlighted the importance of considering the overall health status of patients in the prognosis of cancer. Loss of skeletal muscle, known as sarcopenia, has been found to significantly affect outcomes in many different types of cancers, including colorectal cancer. In this review, we discuss the guidelines for diagnosing sarcopenia, with a specific focus on CT-based assessments. Many groups worldwide, including those in Europe and Asia, have introduced their own diagnostic guidelines for sarcopenia. Seemingly similar yet subtle discrepancies, particularly in the cutoff values used, limit the use of these guidelines in the general population, warranting a more universal guideline. Although CT-based measurements, such as skeletal muscle index and radiodensity, have shown promise in predicting outcomes, the lack of standardized values in these measurements hinders their universal adoption. To overcome these limitations, innovative approaches are being developed to assess changes in muscle mass trajectories and introduce new indices, such as skeletal and appendicular muscle gauges. Additionally, machine learning models have shown superior performance in predicting sarcopenic status, providing an alternative to CT-based diagnosis, particularly after surgery. CT has tremendous benefits and a significant role in visually as well as quantitatively retrieving information on patient body composition. In order to compensate for the limitation of standard cutoff value, 3-dimensional analysis of the CT, artificial intelligence-based body composition analysis, as well as machine learning algorithms for data interpretation and analysis have been proposed and are being utilized. In conclusion, despite the varying definitions of sarcopenia, CT-based measurements coupled with machine-learning models are promising for evaluating patients with cancer. Standardization efforts can improve diagnostic accuracy, reduce the reliance on CT examinations, and make sarcopenia assessments more accessible in clinical settings.

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer

BACKGROUND

Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients.

METHODS

This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients.

RESULTS

Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese.

CONCLUSIONS

The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

Impact of Low Skeletal Muscle Mass on Long-Term Outcomes in Hepatocellular Carcinoma Treated with Trans-Arterial Radioembolization: A Retrospective Multi-Center Study

Trans-arterial radioembolization (TARE) is a form of radiation therapy performed for hepatocellular carcinoma (HCC) via selective intra-arterial injection of Yttrium-90-loaded microspheres. This was a multi-center retrospective study of consecutive patients with HCC who underwent TARE between July 2009 and May 2019. Using pre-treatment computed tomography imaging, the total cross-sectional area (cm2) of the abdominal skeletal muscle at the third lumbar vertebra was measured. The skeletal muscle index (SMI) was calculated by normalizing the muscle area to patient height. In total, 347 patients (median age, 65 years; 284 male) were included in the study. A total of 108 (31.1%) patients had portal vein tumor thrombus (PVTT), and 126 (36.3%) were classified as LSMM. The median overall survival (OS) was 28.1 months (95% CI, 24.8-35.7), and median progression-free survival was 8.0 months (95% CI, 6.4-9.4). Multivariate Cox regression analysis revealed that LSMM (hazard ratio [HR], 1.36; 95% CI, 1.00-1.85, p = 0.05), PVTT (HR, 1.82; 95% CI, 1.33-2.49, p < 0.01), alpha-fetoprotein (AFP) (≥200 ng/mL) (HR 1.41; 95% CI, 1.04-1.92, p = 0.03), and albumin-bilirubin grade (2-3) (HR 1.74; 95% CI, 1.24-2.43, p < 0.01) were independently associated with poor OS. TARE provided favorable long-term outcomes for patients with advanced HCC. Pre-treatment LSMM independently associated with survival, suggesting its utility as a surrogate biomarker for identifying TARE candidates.