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10.1053/j.seminoncol.2014.04.002 http://scihub22266oqcxt.onion/10.1053/j.seminoncol.2014.04.002 C4109657!4109657!25023357     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Semin+Oncol 2014 ; 41 (3): 406-14 Nephropedia Template TP {{tp|p=25023357|t=2014. Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters |pdf=|usr=}}{{25023357}} gab.com Text Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters JO: Semin Oncol http://www.kidney.de/pget.php?&tw=1&pmid=25023357 #FOAvip Background: Previous work has shown that 2 general processes contribute to hepatocellular cancer (HCC) prognosis. They are: a. liver damage, monitored by indices such as blood bilirubin, prothrombin time and AST; as well as b. tumor biology, monitored by indices such as tumor size, tumor number, presence of PVT and blood AFP levels. These 2 processes may affect one another, with prognostically significant interactions between multiple tumor and host parameters. These interactions form a context that provide personalization of the prognostic meaning of these factors for every patient. Thus, a given level of bilirubin or tumor diameter might have a different significance in different personal contexts. We previously applied Network Phenotyping Strategy (NPS) to characterize interactions between liver function indices of Asian HCC patients and recognized two clinical phenotypes, S and L, differing in tumor size and tumor nodule numbers. Aims: To validate the applicability of the NPS-based HCC S/L classification on an independent European HCC cohort, for which survival information was additionally available. Methods: Four sets of peripheral blood parameters, including AFP-platelets, derived from routine blood parameter levels and tumor indices from the ITA.LI.CA database, were analyzed using NPS, a graph-theory based approach, which compares personal patterns of complete relationships between clinical data values to reference patterns with significant association to disease outcomes. Results: Without reference to the actual tumor sizes, patients were classified by NPS into 2 subgroups with S and L phenotypes. These two phenotypes were recognized using solely the HCC screening test results, consisting of eight common blood parameters, paired by their significant correlations, including an AFP-Platelets relationship. These trends were combined with patient age, gender and self-reported alcoholism into NPS personal patient profiles. We subsequently validated (using actual scan data) that patients in L phenotype group had 1.5x larger mean tumor masses relative to S, p=6×10?16. Importantly, with the new data, liver test pattern-identified S-phenotype patients had typically 1.7 × longer survival compared to L-phenotype. NPS integrated the liver, tumor and basic demographic factors. Cirrhosis associated thrombocytopenia was typical for smaller S-tumors. In L-tumor phenotype, typical platelet levels increased with the tumor mass. Hepatic inflammation and tumor factors contributed to more aggressive L tumors, with parenchymal destruction and shorter survival. Summary: NPS provides integrative interpretation for HCC behavior, identifying two tumor and survival phenotypes by clinical parameter patterns. The NPS classifier is provided as an Excel tool. The NPS system shows the importance of considering each tumor marker and parameter in the total context of all the other parameters of an individual patient. Twit Text FOAVip Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters ????Semin Oncol http://www.kidney.de/pget.php?&tw=1&pmid=25023357 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25023357 #FOAvip English Wikipedia <ref>{{Cite pmid|25023357}}</ref> Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters #MMPMID25023357 Carr BI; Pancoska P; Giannini EG; Farinati F; Ciccarese F; Rapaccini GL; Marco MD; Benvegnù L; Zoli M; Borzio F; Caturelli E; Chiaramonte M; Trevisani F Semin Oncol 2014[Jun]; 41 (3): 406-14 PMID25023357show ga Background: Previous work has shown that 2 general processes contribute to hepatocellular cancer (HCC) prognosis. They are: a. liver damage, monitored by indices such as blood bilirubin, prothrombin time and AST; as well as b. tumor biology, monitored by indices such as tumor size, tumor number, presence of PVT and blood AFP levels. These 2 processes may affect one another, with prognostically significant interactions between multiple tumor and host parameters. These interactions form a context that provide personalization of the prognostic meaning of these factors for every patient. Thus, a given level of bilirubin or tumor diameter might have a different significance in different personal contexts. We previously applied Network Phenotyping Strategy (NPS) to characterize interactions between liver function indices of Asian HCC patients and recognized two clinical phenotypes, S and L, differing in tumor size and tumor nodule numbers. Aims: To validate the applicability of the NPS-based HCC S/L classification on an independent European HCC cohort, for which survival information was additionally available. Methods: Four sets of peripheral blood parameters, including AFP-platelets, derived from routine blood parameter levels and tumor indices from the ITA.LI.CA database, were analyzed using NPS, a graph-theory based approach, which compares personal patterns of complete relationships between clinical data values to reference patterns with significant association to disease outcomes. Results: Without reference to the actual tumor sizes, patients were classified by NPS into 2 subgroups with S and L phenotypes. These two phenotypes were recognized using solely the HCC screening test results, consisting of eight common blood parameters, paired by their significant correlations, including an AFP-Platelets relationship. These trends were combined with patient age, gender and self-reported alcoholism into NPS personal patient profiles. We subsequently validated (using actual scan data) that patients in L phenotype group had 1.5x larger mean tumor masses relative to S, p=6×10?16. Importantly, with the new data, liver test pattern-identified S-phenotype patients had typically 1.7 × longer survival compared to L-phenotype. NPS integrated the liver, tumor and basic demographic factors. Cirrhosis associated thrombocytopenia was typical for smaller S-tumors. In L-tumor phenotype, typical platelet levels increased with the tumor mass. Hepatic inflammation and tumor factors contributed to more aggressive L tumors, with parenchymal destruction and shorter survival. Summary: NPS provides integrative interpretation for HCC behavior, identifying two tumor and survival phenotypes by clinical parameter patterns. The NPS classifier is provided as an Excel tool. The NPS system shows the importance of considering each tumor marker and parameter in the total context of all the other parameters of an individual patient. äIdentification of two clinical hepatocellular carcinoma patient phenot(epmc).pdf DeepDyve Pubget Overpricing