scholarly journals Albumin-to-Alkaline Phosphatase Ratio: A Novel Prognostic Index for Hepatocellular Carcinoma

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Anthony W. H. Chan ◽  
Stephen L. Chan ◽  
Frankie K. F. Mo ◽  
Grace L. H. Wong ◽  
Vincent W. S. Wong ◽  
...  

Prognosis of patients with hepatocellular carcinoma (HCC) depends on both tumour extent and hepatic function reserve. Liver function test (LFT) is a basic routine blood test to evaluate hepatic function. We first analysed LFT components and their associated scores in a training cohort of 217 patients who underwent curative surgery to identify LFT parameters with high performance (discriminatory capacity, homogeneity, and monotonicity of gradient). We derived a novel index, albumin-to-alkaline phosphatase ratio (AAPR), which had the highest c-index (0.646) andχ2(24.774) among other liver biochemical parameters. The AAPR was an independent prognostic factor for overall and disease-free survival. The adjusted hazard ratio of death and tumour relapse was 2.36 (P=0.002) and 1.85 (P=0.010), respectively. The independent prognostic significance of AAPR on top of 5 commonly used and well established staging systems was further confirmed in 2 independent cohorts of patients receiving surgical resection (n=256) and palliative therapy (n=425). In summary, the AAPR is a novel index readily derived from a simple low-cost routine blood test and is an independent prognostic indicator for patients with HCC regardless of treatment options.

2000 ◽  
Vol 28 (5) ◽  
pp. 562-565 ◽  
Author(s):  
A. Flabouris ◽  
G. Bishop ◽  
L. Williams ◽  
M. Cunningham

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 480-480
Author(s):  
Xiu-Rong Cai ◽  
Zhan-Hong Chen ◽  
Qu Lin ◽  
Min Dong ◽  
Xiao-kun Ma ◽  
...  

480 Background: Child-Pugh grade is widely used to assess hepatic function reserve, but it is relatively subjective for assessment of hepatic encephalopathy. A newly developed scoring system combining albumin and bilirubin, called ALBI grade, aims to assess liver function objectively. In prognosis prediction of hepatocellular carcinoma (HCC), The Cancer of the Liver Italian Program (CLIP) score is commonly used in clinical practice and includes Child-Pugh evaluation. We substituted ALBI grade for Child-Pugh grade to establish ALBI-CLIP system and conducted this study to validate the prognostic value of ALBI -CLIP in HBV-related HCC patients after TACE therapy. Methods: We retrospectively analyzed HBV-related HCC patients who received TACE therapy. Baseline data were collected and evaluated. Child-Pugh grade and ALBI grade were integrated into CLIP and ALBI-CLIP systems, respectively. Univariate and multivariate analyses were conducted to identify independent prognostic factors for overall survival. Comparisons of receiver operating characteristic (ROC) curves and likelihood ratio test (LRT) were used to compare the value of ALBI-CLIP, CLIP and TNM staging systems in predicting survival. Results: A total of 207 patients were included. 153 (73.9%) and 54 (26.1%) patients were classified as Child-Pugh grade A and B, respectively. But according to ALBI grade, 57 (27.5%), 136 (65.7%) and 14 (6.8%) of them were correspondingly divided into Grade 1, 2 and 3. Comparisons of ROC curves showed that ALBI-CLIP and CLIP had similar areas under the curve, both of which were larger than that of TNM system in predicting 3-month, 6-month, 1-year and 2-year survival. LRT indicated that both ALBI-CLIP and CLIP had larger χ2 values and smaller values of Akaike information criterion (AIC), compared with TNM system (χ2 = 29.771, 29.479, 9.105; AIC = 858.215, 858.069, 879.410 for ALBI-CLIP, CLIP and TNM, respectively). Conclusions: Our current study suggested that modified CLIP score with albumin-bilirubin grade retained prognostic value in HBV-related HCC treated with TACE therapy.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Simon Podnar ◽  
Matjaž Kukar ◽  
Gregor Gunčar ◽  
Mateja Notar ◽  
Nina Gošnjak ◽  
...  

Abstract Routine blood test results are assumed to contain much more information than is usually recognised even by the most experienced clinicians. Using routine blood tests from 15,176 neurological patients we built a machine learning predictive model for the diagnosis of brain tumours. We validated the model by retrospective analysis of 68 consecutive brain tumour and 215 control patients presenting to the neurological emergency service. Only patients with head imaging and routine blood test data were included in the validation sample. The sensitivity and specificity of the adapted tumour model in the validation group were 96% and 74%, respectively. Our data demonstrate the feasibility of brain tumour diagnosis from routine blood tests using machine learning. The reported diagnostic accuracy is comparable and possibly complementary to that of imaging studies. The presented machine learning approach opens a completely new avenue in the diagnosis of these grave neurological diseases and demonstrates the utility of valuable information obtained from routine blood tests.


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