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Background: Accurate staging is necessary for predicting hepatocellular carcinoma (HCC) prognosis and guiding patient management. The Barcelona Clinic Liver Cancer (BCLC) staging system has limitations due to heterogeneity observed among patients in BCLC stages B and C. In contrast, the Hong Kong Liver Cancer (HKLC) staging system offers more aggressive treatment strategies. Aim: To compare the prognostic performance of HKLC and BCLC staging systems in Egyptian patients with HCC. Methods: We conducted a retrospective study at the National Liver Institute, Menoufia University, Egypt, on 1015 HCC patients. Data was collected from patients' medical records over 10 years (from 2008 to 2018). The BCLC and HKLC stages were identified, and Kaplan-Meier survival analysis was used to compare patients' overall survival rates within each staging system. Additionally, we evaluated the comparative prognostic performance of the two staging systems. Results: Hepatitis C was identified as the underlying etiology in 799 patients (78.7%), hepatitis B in 12 patients (1.2%), and non-viral causes in 204 patients (20.1%). The survival analysis demonstrated significant differences across the various stages within both the BCLC and HKLC systems. The receiver operating characteristic (ROC) curves indicated a marginally superior performance of the HKLC system in predicting survival at 1, 2, and 3 years compared to the BCLC system. Furthermore, the HKLC staging provided a slightly enhanced prognostic capability, particularly for patients classified under BCLC stages B and C, suggesting a potential survival benefit. Conclusion: HKLC classification had a slightly better prognostic performance than BCLC staging system and may offer a survival advantage for certain patients with HCC in BCLC stage B and C HCC cases. [ABSTRACT FROM AUTHOR]

Background: Whether body composition is associated with the N-terminal pro-B-type natriuretic peptide (NTproBNP) level and its prognostic performance in acute coronary syndrome (ACS) remains unknown. We aimed to investigate the influence of body composition on the NT-proBNP level and its prognostic performance among ACS patients. Methods: In total, 1623 ACS patients with NT-proBNP data were enrolled. Percent body fat and lean mass index were estimated using the Clínica Universidad de Navarra--Body Adiposity Estimator equation. Patients were divided into three groups according to the tertiles of sex-specific body mass index, percent body fat, or lean mass index. The endpoints were death from any cause and cardiovascular death. Results: Body mass index was inversely correlated with NT-proBNP levels (β = -0.036, P = 0.003). Lean mass index, but not percent body fat, was inversely associated with NT-proBNP levels (β of lean mass index = -0.692, P = 0.002). During a median follow-up of 23 months, 161 all-cause deaths occurred, and of these, 93 (57.8 %) were attributed to cardiovascular causes. Multivariate Cox analysis showed that the NT-proBNP level independently predicted all-cause mortality or cardiovascular death in the lower body mass index, lean mass index, and percent body fat groups. However, the prognostic performance of NT-proBNP was attenuated in patients with high body mass index, lean mass index, and percent body fat. In the subgroup of patients with diabetes, inverse associations between NT-proBNP levels and body mass index or body composition were not observed. In addition, the negative influence of high body mass index and body composition on the prognostic performance of the NT-proBNP level appeared to be attenuated. Conclusions: Body mass index and lean mass index, but not percent body fat, are inversely associated with NTproBNP levels. The prognostic performance of this biomarker may be compromised in patients with high body mass index, percent body fat, or lean mass index. Additionally, the influence of body composition on the NT-proBNP level and its prognostic performance might be attenuated in diabetic patients with ACS. [ABSTRACT FROM AUTHOR]

Background: Disease prevalence is rarely explicitly considered in the early stages of the development of novel prognostic tests. Rather, researchers use the area under the receiver operating characteristic (AUROC) as the key metric to gauge and report predictive performance ability. Because this statistic does not account for disease prevalence, proposed tests may not appropriately address clinical requirements. This ultimately impedes the translation of prognostic tests into clinical practice., Methods: A method to express positive- and/or negative predictive value criteria (PPV, NPV) within the ROC space is presented. Equations are derived for so-called equi-PPV (and equi-NPV) lines. Herewith it is possible, for any given prevalence, to plot a series of sensitivity-specificity pairs which meet a specified PPV (or NPV) criterion onto the ROC space.This concept is introduced by firstly reviewing the well-established "mechanics", strengths and limitations of the ROC analysis in the context of developing prognostic models. Then, the use of PPV (and/or) NPV criteria to augment the ROC analysis is elaborated.Additionally, an interactive web tool was also created to enable people to explore the dynamics of lines of equi-predictive value in function of prevalence. The web tool also allows to gauge what ROC curve shapes best meet specific positive and/or negative predictive value criteria (http://d4ta.link/ppvnpv/)., Results: To illustrate the merits and implications of this concept, an example on the prediction of pre-eclampsia risk in low-risk nulliparous pregnancies is elaborated., Conclusions: In risk stratification, the clinical usefulness of a prognostic test can be expressed in positive- and negative predictive value criteria; the development of novel prognostic tests will be facilitated by the possibility to co-visualise such criteria together with ROC curves. To achieve clinically meaningful risk stratification, the development of separate tests to meet either a pre-specified positive value (rule-in) or a negative predictive value (rule-out) criteria should be considered: the characteristics of successful rule-in and rule-out tests may markedly differ., Competing Interests: In addition of being practising clinicians, PNB and LCK have a long-standing record in both basic and translational preeclampsia research. PNB and LCK are well-recognised pioneers in the use of “omics” for the discovery of novel biomarkers to predict pre-eclampsia. RT and GT have been involved in “omics” biomarker discovery and biomarker translational research for over a decade.Not applicable.Not applicable.GT is the owner of SQU4RE, an independent Statistics and Data mining provider. LCK is a minority shareholder in Metabolomic Diagnostics, a company that has licenced technology concerning the use of metabolomics biomarkers in the prediction of pre-eclampsia. LCK has also received consultancy fees and honoraria payments from Alere relating to the Triage PlGF test for the prediction of complications in women with suspected pre-eclampsia. LCK is also Director of INFANT which is funded in part by a range of industry partnerships. Full details can be found at www.infantcentre.ie. PNB is a minority shareholder in Metabolomic Diagnostics, a company that has licenced technology concerning the use of metabolomics biomarkers in the prediction of pre-eclampsia. RT is employed by Metabolomic Diagnostics, which is developing metabolomics-based prognostic tests for adverse pregnancy outcomes.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Background: Whether body composition is associated with the N-terminal pro-B-type natriuretic peptide (NT-proBNP) level and its prognostic performance in acute coronary syndrome (ACS) remains unknown. We aimed to investigate the influence of body composition on the NT-proBNP level and its prognostic performance among ACS patients., Methods: In total, 1623 ACS patients with NT-proBNP data were enrolled. Percent body fat and lean mass index were estimated using the Clínica Universidad de Navarra-Body Adiposity Estimator equation. Patients were divided into three groups according to the tertiles of sex-specific body mass index, percent body fat, or lean mass index. The endpoints were death from any cause and cardiovascular death., Results: Body mass index was inversely correlated with NT-proBNP levels (β = -0.036, P = 0.003). Lean mass index, but not percent body fat, was inversely associated with NT-proBNP levels (β of lean mass index = -0.692, P = 0.002). During a median follow-up of 23 months, 161 all-cause deaths occurred, and of these, 93 (57.8 %) were attributed to cardiovascular causes. Multivariate Cox analysis showed that the NT-proBNP level independently predicted all-cause mortality or cardiovascular death in the lower body mass index, lean mass index, and percent body fat groups. However, the prognostic performance of NT-proBNP was attenuated in patients with high body mass index, lean mass index, and percent body fat. In the subgroup of patients with diabetes, inverse associations between NT-proBNP levels and body mass index or body composition were not observed. In addition, the negative influence of high body mass index and body composition on the prognostic performance of the NT-proBNP level appeared to be attenuated., Conclusions: Body mass index and lean mass index, but not percent body fat, are inversely associated with NT-proBNP levels. The prognostic performance of this biomarker may be compromised in patients with high body mass index, percent body fat, or lean mass index. Additionally, the influence of body composition on the NT-proBNP level and its prognostic performance might be attenuated in diabetic patients with ACS.