Role of aetiology, diabetes, tobacco smoking and hypertension in hepatocellular carcinoma survival

Raffetti, Elena; Portolani, Nazario; Molfino, Sarah; Baiocchi, Gian Luca; Limina, Rosa Maria; Caccamo, Giovanni; Lamera, Rossella; Donato, Francesco

doi:10.1016/j.dld.2015.07.010

Cited by 16 publications

(12 citation statements)

References 35 publications

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“…27 The presence of DM has also been reported to increase the risk of mortality due to HCC. 28 However, increased coffee consumption seems to reduce the risk of HCC and chronic liver disease. 29 …”

Section: Discussionmentioning

confidence: 99%

Impact of HCV Infection on Diabetes Patients for the Risk of End-Stage Renal Failure

Hwang

Jiang

et al. 2016

Medicine

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Both diabetes mellitus (DM) and hepatitis C virus infection (HCVI) are associated with chronic kidney disease (CKD). The aim of this study was to evaluate whether HCVI increases the risk of end-stage renal disease (ESRD) in patients with DM.The National Health Insurance Research database of Taiwan was used to conduct this study. After excluding patients with a prior history of CKD, all patients with a first diagnosis of DM from January 1, 2000 to December 31, 2002 were enrolled. The patients who also had HCVI were defined as index cases (HCV group, n = 9787). A comparison cohort at a 1:1 ratio of random incident patients with DM without HCVI matched by age, sex, age at the diagnosis of DM, duration between the diagnosis of DM and the index date, and various comorbidities through propensity score matching were recruited (non-HCV group, n = 9787). The patients were followed until December 31, 2011.The cumulative incidence rate of developing ESRD was significantly higher in the HCV(+) group than in the non-HCV group (P = 0.008). The incidence rate ratio (IRR) for the risk of ESRD was also significantly higher in the HCV(+) group (IRR: 1.44; 95% CI: 1.09–1.89) than in the non-HCV group, especially for those with a younger age (<50 years; IRR: 2.05; 95% CI: 1.22–3.45) and HCVI within 4 years after the diagnosis of DM (IRR: 1.85; 95% CI: 1.16–2.97). After adjusting for comorbidities in multivariate Cox proportional hazard regression analysis, HCVI (HR: 1.47; 95% CI: 1.11–1.93) was an independent factor for developing ESRD in the patients with DM. After starting dialysis for ESRD, the HCV(+) patients had a similar mortality rate to those without HCVI (P = 0.84).HCVI increases the risk of developing ESRD in patients with DM, especially in younger patients and in those who develop HCVI sooner after a diagnosis of DM.

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Section: Discussionmentioning

confidence: 99%

Impact of HCV Infection on Diabetes Patients for the Risk of End-Stage Renal Failure

Hwang

Jiang

et al. 2016

Medicine

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“…[2, 3] The pathogenic and prognostic roles of metabolic factors, such as diabetes mellitus (DM), metabolic syndrome, or obesity, had also been studied. [4–6] Epidemiologic studies have disclosed association between presence of DM and higher HCC incidence, suggesting that DM is an independent risk factor for development of HCC. [7–10]…”

Section: Introductionmentioning

confidence: 99%

Prognostic impact of diabetes mellitus on hepatocellular carcinoma: Special emphasis from the BCLC perspective

Liu

Hsu

et al. 2017

PLoS ONE

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BackgroundDiabetes mellitus (DM) is associated with higher incidence and poorer prognosis of hepatocellular carcinoma (HCC). The influence of DM on patient survival in different HCC stages is not known.MethodsA prospective dataset of 3,182 HCC patients was collected between 2002 and 2014. Patients were divided into three groups according to BCLC stages (BCLC stage 0 and stage A, BCLC stage B, BCLC stage C and stage D). We compared the cumulative survival rate of diabetic and non-diabetic patients in different BCLC groups. The correlation between DM and overall survival was also analyzed by multivariate Cox regression model within each group.ResultsDM is present in 25.2% of all patients. Diabetic patients had lower cumulative survival in BCLC stage 0 plus BCLC stage A group (log rank p<0.001), and BCLC stage B group (log rank p = 0.012), but not in BCLC stage C plus BCLC stage D group (log rank p = 0.132). Statistically significant differences in overall survival are found between diabetic and non-diabetic patients in BCLC stage 0 plus stage A group (adjusted hazard ratio [HR] = 1.45, 95% confidence interval [CI] 1.08–1.93, p = 0.013), and BCLC stage B (adjusted HR = 1.77, 95% CI 1.24–2.51, p = 0.002). In contrast, the survival difference is not seen in BCLC stage C plus stage D group (adjusted HR = 1.09, 95% CI 0.90–1.30, p = 0.387).ConclusionsDM is prevalent in HCC, and is associated with lower survival rate in HCC patients with BCLC stage 0 plus stage A and B, but not in those with BCLC stage C plus stage D.

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“…These scoring systems comprise the parameters BCLC stage, alpha‐fetoprotein level, tumour size and number, Child‐Pugh score, radiological tumour response and aspartate aminotransferase level. We also included other potentially clinically meaningful parameters regarding aetiology (alcohol abuse, hepatitis B and C, non‐alcoholic steatohepatitis), comorbidities (nicotine abuse, obesity, diabetes) and tumour growth pattern . In addition, we included the following potentially meaningful parameters indicating liver function: MELD, bilirubin, albumin and the international normalized ratio .…”

Section: Methodsmentioning

confidence: 99%

“…These scoring systems comprise the parameters BCLC stage, alpha-fetoprotein level, tumour size and number, Child-Pugh score, radiological tumour response and aspartate aminotransferase level. We also included other potentially clinically meaningful parameters regarding aetiology (alcohol abuse, hepatitis B and C, non-alcoholic steatohepatitis26 ), comorbidities (nicotine abuse, 27 obesity,28…”

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confidence: 99%

Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study

Mähringer‐Kunz

Wagner

Hähn

et al. 2020

Liver International

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Background and aims Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. Methods For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores and other clinically meaningful parameters. Following an 80:20 split, the first 225 patients were used for training; the more recently treated 20% were used for validation. Results The ANN had a promising performance at predicting 1‐year survival, with an area under the ROC curve (AUC) of 0.77 ± 0.13. Internal validation yielded an AUC of 0.83 ± 0.06, a positive predictive value of 87.5% and a negative predictive value of 68.0%. The sensitivity was 77.8% and specificity 81.0%. In a head‐to‐head comparison, the ANN outperformed the aforementioned scoring systems, which yielded lower AUCs (SNACOR 0.73 ± 0.07, ABCR 0.70 ± 0.07 and ART 0.54 ± 0.08). This difference reached significance for ART (P < .001); for ABCR and SNACOR significance was not reached (P = .143 and P = .201). Conclusions Artificial neural networks could be better at predicting patient survival after TACE for HCC than traditional scoring systems. Once established, such prediction models could easily be deployed in clinical routine and help determine optimal patient care.

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Role of aetiology, diabetes, tobacco smoking and hypertension in hepatocellular carcinoma survival

Cited by 16 publications

References 35 publications

Impact of HCV Infection on Diabetes Patients for the Risk of End-Stage Renal Failure

Impact of HCV Infection on Diabetes Patients for the Risk of End-Stage Renal Failure

Prognostic impact of diabetes mellitus on hepatocellular carcinoma: Special emphasis from the BCLC perspective

Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study

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