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

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          Abstract

          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.

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          Most cited references52

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            A new definition for metabolic associated fatty liver disease: an international expert consensus statement

            The exclusion of other chronic liver diseases including "excess" alcohol intake has until now been necessary to establish a diagnosis of metabolic dysfunction-associated fatty liver disease (MAFLD). However, given our current understanding of the pathogenesis of MAFLD and its rising prevalence, "positive criteria" to diagnose the disease are required. In this work, a panel of international experts from 22 countries propose a new definition for the diagnosis of MAFLD that is both comprehensive and simple, and is independent of other liver diseases. The criteria are based on evidence of hepatic steatosis, in addition to one of the following three criteria, namely overweight/obesity, presence of type 2 diabetes mellitus, or evidence of metabolic dysregulation. We propose that disease assessment and stratification of severity should extend beyond a simple dichotomous classification to steatohepatitis vs. non-steatohepatitis. The group also suggests a set of criteria to define MAFLD-associated cirrhosis and proposes a conceptual framework to consider other causes of fatty liver disease. Finally, we bring clarity to the distinction between diagnostic criteria and inclusion criteria for research studies and clinical trials. Reaching consensus on the criteria for MAFLD will help unify the terminology (e.g. for ICD-coding), enhance the legitimacy of clinical practice and clinical trials, improve clinical care and move the clinical and scientific field of liver research forward.
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              Nomograms in oncology: more than meets the eye.

              Nomograms are widely used as prognostic devices in oncology and medicine. With the ability to generate an individual probability of a clinical event by integrating diverse prognostic and determinant variables, nomograms meet our desire for biologically and clinically integrated models and fulfill our drive towards personalised medicine. Rapid computation through user-friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared with conventional staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision making. This has led to the appearance of many nomograms on the internet and in medical journals, and an increase in nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use are generally misunderstood. This issue is leading to an under-appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.
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                Author and article information

                Journal
                J Hepatocell Carcinoma
                J Hepatocell Carcinoma
                jhc
                Journal of Hepatocellular Carcinoma
                Dove
                2253-5969
                18 January 2024
                2024
                : 11
                : 145-157
                Affiliations
                [1 ]Department of Traditional and Western Medical Hepatology, Hebei Medical University Third Hospital & Hebei International Joint Research Center for Liver Cancer Molecular Diagnosis, Hebei International Science and Technology Cooperation Base , Shijiazhuang, Hebei Province, 050051, People’s Republic of China
                [2 ]Department of Biochemistry and Molecular Biology, Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University , Shijiazhuang, Hebei Province, 050017, People’s Republic of China
                Author notes
                Correspondence: Yuemin Nan, Department of Traditional and Western Medical Hepatology, Hebei Medical University Third Hospital & Hebei International Joint Research Center for Liver Cancer Molecular Diagnosis, Hebei International Science and Technology Cooperation Base , No. 139, Ziqiang Road, Shijiazhuang, Hebei Province, 050051, People’s Republic of China, Tel +86 18533112266, Email nanyuemin@163.com
                Dong Ma, Department of Biochemistry and Molecular Biology, Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University , No. 361, Zhongshan East Road, Shijiazhuang, Hebei Province, 050017, People’s Republic of China, Tel +86 15081650349, Email madong119@hebmu.edu.cn
                [*]

                These authors contributed equally to this work

                Author information
                http://orcid.org/0000-0003-1078-9730
                Article
                439397
                10.2147/JHC.S439397
                10802127
                38260867
                32fcf1fd-ce62-479c-a455-14cfadc2bec5
                © 2024 Miao et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 13 September 2023
                : 13 January 2024
                Page count
                Figures: 9, Tables: 3, References: 52, Pages: 13
                Funding
                Funded by: Key Research and Development Program of Hebei Province;
                This work was supported by Key Research and Development Program of Hebei Province (Grant No. 19277779D).
                Categories
                Original Research

                lipid metabolism,mafld-hcc,prognostic prediction,nomogram,mhr

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