title: Use of a variety of biological parameters in distinguishing cirrhotic from malignant ascites.
abstract: Twenty-two different protein measurements were taken in the serum and ascitic fluid of fifty consecutive patients in an attempt to investigate which tests are the most reliable for the differential diagnosis of ascites. Serum and ascitic fluid total proteins (TPR), albumin (ALB), lactate (LAC), ferritin (FER), C3 and C4 complement factors, C-reactive protein (CRP), ceruloplasmin (CER), alpha2-macroglobulin (alpha2MG), haptoglobin (HAP), alpha1-antitrypsin (alpha1AT), alpha1-acid glycoprotein (alpha1AG), transferrin (TRF), immunoglobulins IgG, IgA, IgM and cytokines such as interleukin-1alpha (IL-1alpha), interleukin-1beta (IL-1beta), interleukin-2 (IL-2), interleukin-6 (IL-6), interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNF-alpha) were measured to distinguish between malignant and cirrhotic ascites. Correlations and non-parametric Mann-Whitney tests were used for ascitic fluid:serum ratio comparisons between the two groups. Multivariate analyses were used to determine the most significant biochemical ratio predictors for the differential diagnosis and a recursive partitioning model was constructed. Highly positive correlations (r>0.50) were found between the ratios IgA, IgG, IgM, CER, alpha2 MG, HAP, alpha1AT, alpha1AG and TRF. There was evidence that TPR, ALB, LAC, FER, IgG, CER, alpha2MG, alpha1AT, alpha1AG, TRF and IL-8 ascitic fluid:serum ratios are significnatly higher in patients with malignant neoplasms than in cirrhotics. In the recursive partitioning model the most significant parameters were found to be the ratios of albumin and IL-1alpha. The model fitted allowed for 100% correct classification of ascites. In conclusion, we have shown that a simple and very accurate model based on two ascitic fluid: serum measurements is able to differentiate between malignant and non-malignant ascites.
authors: Department of Hematology, University Hospital of Heraklion, School of Medicine, University of Crete, Greece.
authors: M G
authors: MG
authors: Alexandrakis
authors: J
authors: J
authors: Moschandrea
authors: D S
authors: DS
authors: Kyriakou
authors: R
authors: R
authors: Alexandraki
authors: E
authors: E
authors: Kouroumalis
mesh_terms: D000209:Acute-Phase Proteins / Q000378:metabolism; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000418:Albumins / Q000378:metabolism; D001201:Ascites / Q000097:blood / Q000175:diagnosis* / Q000378:metabolism; D001202:Ascitic Fluid / Q000378:metabolism; D014408:Biomarkers, Tumor / Q000097:blood* / Q000378:metabolism*; D001798:Blood Proteins / Q000378:metabolism; D016207:Cytokines / Q000097:blood / Q000378:metabolism; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007136:Immunoglobulins / Q000097:blood / Q000378:metabolism; D019344:Lactic Acid / Q000097:blood / Q000378:metabolism; D008103:Liver Cirrhosis / Q000097:blood / Q000175:diagnosis* / Q000378:metabolism; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000097:blood / Q000378:metabolism; D009369:Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000378:metabolism; D012709:Serum Albumin / Q000378:metabolism
chemical_list: D000209:Acute-Phase Proteins; D000418:Albumins; D014408:Biomarkers, Tumor; D001798:Blood Proteins; D016207:Cytokines; D007136:Immunoglobulins; D009363:Neoplasm Proteins; D012709:Serum Albumin; D019344:Lactic Acid