Association between sarcopenia and clinical outcomes in patients with hepatocellular carcinoma: an updated meta-analysis

Guo, Yusheng; Ren, Yanqiao; Zhu, Licheng; Yang, Lian; Zheng, Chuansheng

doi:10.1038/s41598-022-27238-z

Cited by 26 publications

(19 citation statements)

References 86 publications

(276 reference statements)

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“…The phenotype for malnutrition in end-stage liver disease is characterized by sarcopenia, a state of reduced skeletal muscle mass, strength and function and its presence portends a worse prognosis for patients with cirrhosis [36 ▪ ] and hepatocellular carcinoma (HCC) [37]. One recent metanalysis of 50 000 patients with HCC suggests that sarcopenia may be a stronger prognostic indicator than tumor stage [37].…”

Section: Introductionmentioning

confidence: 99%

Nutritional deficiencies in alcohol use disorder/alcohol-associated liver disease

Jophlin,

Liu,

McClain

2024

Current Opinion in Gastroenterology

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Purpose of review To delineate common and uncommon dietary and nutritional deficiencies in individuals with chronic heavy alcohol use and alcohol use disorder and to highlight important advances in the nutrition field in patients ranging from those with alcohol use disorder (AUD) and no liver disease to those with decompensated alcohol-associated liver disease (ALD). Recent findings Patients with AUD may have nutritional deficiencies, especially isolated nutrient deficiencies, such as thiamine or zinc deficiencies. This should not be surprising, as alcohol is a major source of “empty calories.” It is devoid of critical macronutrients, such as protein, and micronutrients including important vitamins and minerals. Patients with AUD frequently drink much more than often appreciated (10–20 drinks a day). Patients with AUD and early ALD often begin to develop more apparent nutritional deficiencies. Healthcare providers need to be aware of the presenting features of individual nutrient deficiencies, such as thiamine deficiency, and to provide prompt treatment. In patients with more advanced liver disease, malnutrition correlates with severity of liver disease. It is important to understand the value of nutritional support throughout the spectrum of AUD. Summary We review nutritional deficiencies in the spectrum of patients with AUD and ALD and highlight new information and recommendations.

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Section: Introductionmentioning

confidence: 99%

Nutritional deficiencies in alcohol use disorder/alcohol-associated liver disease

Jophlin,

Liu,

McClain

2024

Current Opinion in Gastroenterology

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“…2 LSMM can also predict lower objective response rate (odds ratio [OR] = 0.37, 95% CI: 0.17-0.81, P = 0.012) and more drug-related adverse events (OR = 2.23, 95% CI: 1.17-4.28, P = 0.015). 3 In addition, adipose tissue (AT), especially visceral adipose tissue (VAT), plays an important role in HCC. For instance, it was reported that preoperative visceral adiposity predicted poor outcomes after hepatectomy in patients with HCC.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, LSMM was associated with all‐cause mortality in patients with HCC (crude hazard ratio [HR] = 2.04, 95% confidence interval [CI]: 1.74–2.38; adjusted HR = 1.95, 95% CI: 1.60–2.37) 2 . LSMM can also predict lower objective response rate (odds ratio [OR] = 0.37, 95% CI: 0.17–0.81, P = 0.012) and more drug‐related adverse events (OR = 2.23, 95% CI: 1.17–4.28, P = 0.015) 3 . In addition, adipose tissue (AT), especially visceral adipose tissue (VAT), plays an important role in HCC.…”

Section: Introductionmentioning

confidence: 99%

Prognostic role of radiomics‐based body composition analysis for the 1‐year survival for hepatocellular carcinoma patients

Saalfeld,

Kreher,

Hille

et al. 2023

J cachexia sarcopenia muscle

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BackgroundParameters of body composition have prognostic potential in patients with oncologic diseases. The aim of the present study was to analyse the prognostic potential of radiomics‐based parameters of the skeletal musculature and adipose tissues in patients with advanced hepatocellular carcinoma (HCC).MethodsRadiomics features were extracted from a cohort of 297 HCC patients as post hoc sub‐study of the SORAMIC randomized controlled trial. Patients were treated with selective internal radiation therapy (SIRT) in combination with sorafenib or with sorafenib alone yielding two groups: (1) sorafenib monotherapy (n = 147) and (2) sorafenib and SIRT (n = 150). The main outcome was 1‐year survival. Segmentation of muscle tissue and adipose tissue was used to retrieve 881 features. Correlation analysis and feature cleansing yielded 292 features for each patient group and each tissue type. We combined 9 feature selection methods with 10 feature set compositions to build 90 feature sets. We used 11 classifiers to build 990 models. We subdivided the patient groups into a train and validation cohort and a test cohort, that is, one third of the patient groups.ResultsWe used the train and validation set to identify the best feature selection and classification model and applied it to the test set for each patient group. Classification yields for patients who underwent sorafenib monotherapy an accuracy of 75.51% and area under the curve (AUC) of 0.7576 (95% confidence interval [CI]: 0.6376–0.8776). For patients who underwent treatment with SIRT and sorafenib, results are accuracy = 78.00% and AUC = 0.8032 (95% CI: 0.6930–0.9134).ConclusionsParameters of radiomics‐based analysis of the skeletal musculature and adipose tissue predict 1‐year survival in patients with advanced HCC. The prognostic value of radiomics‐based parameters was higher in patients who were treated with SIRT and sorafenib.

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“…There is strong evidence that abnormal BC phenotypes predict cancer outcomes. In particular, sarcopenia predicts survival and postoperative complications in head and neck, breast, lung and gastrointestinal tract malignancies, 1–5 as well as recurrence 6–9 . Combinations of abnormal BC have further lethality; cancer patients with sarcopenic obesity are at even greater mortality risk 10,11 …”

Section: Introductionmentioning

confidence: 99%

“…In particular, sarcopenia predicts survival and postoperative complications in head and neck, breast, lung and gastrointestinal tract malignancies, [1][2][3][4][5] as well as recurrence. [6][7][8][9] Combinations of abnormal BC have further lethality; cancer patients with sarcopenic obesity are at even greater mortality risk. 10,11 In order for BC to routinely feature in treatment planning, two broad criteria need to be achieved: an effective time-critical treatment for abnormal BC proven to improve outcomes and an accurate and convenient method of measurement.…”

Section: Introductionmentioning

confidence: 99%

A systematic review of automated segmentation of 3D computed‐tomography scans for volumetric body composition analysis

Van

Drami

Pring

et al. 2023

J cachexia sarcopenia muscle

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Automated computed tomography (CT) scan segmentation (labelling of pixels according to tissue type) is now possible. This technique is being adapted to achieve three‐dimensional (3D) segmentation of CT scans, opposed to single L3‐slice alone. This systematic review evaluates feasibility and accuracy of automated segmentation of 3D CT scans for volumetric body composition (BC) analysis, as well as current limitations and pitfalls clinicians and researchers should be aware of. OVID Medline, Embase and grey literature databases up to October 2021 were searched. Original studies investigating automated skeletal muscle, visceral and subcutaneous AT segmentation from CT were included. Seven of the 92 studies met inclusion criteria. Variation existed in expertise and numbers of humans performing ground‐truth segmentations used to train algorithms. There was heterogeneity in patient characteristics, pathology and CT phases that segmentation algorithms were developed upon. Reporting of anatomical CT coverage varied, with confusing terminology. Six studies covered volumetric regional slabs rather than the whole body. One study stated the use of whole‐body CT, but it was not clear whether this truly meant head‐to‐fingertip‐to‐toe. Two studies used conventional computer algorithms. The latter five used deep learning (DL), an artificial intelligence technique where algorithms are similarly organized to brain neuronal pathways. Six of seven reported excellent segmentation performance (Dice similarity coefficients > 0.9 per tissue). Internal testing on unseen scans was performed for only four of seven algorithms, whilst only three were tested externally. Trained DL algorithms achieved full CT segmentation in 12 to 75 s versus 25 min for non‐DL techniques. DL enables opportunistic, rapid and automated volumetric BC analysis of CT performed for clinical indications. However, most CT scans do not cover head‐to‐fingertip‐to‐toe; further research must validate using common CT regions to estimate true whole‐body BC, with direct comparison to single lumbar slice. Due to successes of DL, we expect progressive numbers of algorithms to materialize in addition to the seven discussed in this paper. Researchers and clinicians in the field of BC must therefore be aware of pitfalls. High Dice similarity coefficients do not inform the degree to which BC tissues may be under‐ or overestimated and nor does it inform on algorithm precision. Consensus is needed to define accuracy and precision standards for ground‐truth labelling. Creation of a large international, multicentre common CT dataset with BC ground‐truth labels from multiple experts could be a robust solution.

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Association between sarcopenia and clinical outcomes in patients with hepatocellular carcinoma: an updated meta-analysis

Cited by 26 publications

References 86 publications

Nutritional deficiencies in alcohol use disorder/alcohol-associated liver disease

Nutritional deficiencies in alcohol use disorder/alcohol-associated liver disease

Prognostic role of radiomics‐based body composition analysis for the 1‐year survival for hepatocellular carcinoma patients

A systematic review of automated segmentation of 3D computed‐tomography scans for volumetric body composition analysis

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