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A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting

BACKGROUND: Randomized clinical trials constitute the gold-standard for evaluating new anti-cancer therapies; however, real-life data are key in complementing clinically useful information. We developed a computational tool for real-life data analysis and applied it to the metastatic colorectal canc...

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Autores principales: Siegelmann-Danieli, Nava, Farkash, Ariel, Katzir, Itzhak, Vesterman Landes, Janet, Rotem Rabinovich, Hadas, Lomnicky, Yossef, Carmeli, Boaz, Parush-Shear-Yashuv, Naama
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4856262/
https://www.ncbi.nlm.nih.gov/pubmed/27144545
http://dx.doi.org/10.1371/journal.pone.0154689
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author Siegelmann-Danieli, Nava
Farkash, Ariel
Katzir, Itzhak
Vesterman Landes, Janet
Rotem Rabinovich, Hadas
Lomnicky, Yossef
Carmeli, Boaz
Parush-Shear-Yashuv, Naama
author_facet Siegelmann-Danieli, Nava
Farkash, Ariel
Katzir, Itzhak
Vesterman Landes, Janet
Rotem Rabinovich, Hadas
Lomnicky, Yossef
Carmeli, Boaz
Parush-Shear-Yashuv, Naama
author_sort Siegelmann-Danieli, Nava
collection PubMed
description BACKGROUND: Randomized clinical trials constitute the gold-standard for evaluating new anti-cancer therapies; however, real-life data are key in complementing clinically useful information. We developed a computational tool for real-life data analysis and applied it to the metastatic colorectal cancer (mCRC) setting. This tool addressed the impact of oncology/non-oncology parameters on treatment patterns and clinical outcomes. METHODS: The developed tool enables extraction of any computerized information including comorbidities and use of drugs (oncological/non-oncological) per individual HMO member. The study in which we evaluated this tool was a retrospective cohort study that included Maccabi Healthcare Services members with mCRC receiving bevacizumab with fluoropyrimidines (FP), FP plus oxaliplatin (FP-O), or FP plus irinotecan (FP-I) in the first-line between 9/2006 and 12/2013. RESULTS: The analysis included 753 patients of whom 15.4% underwent subsequent metastasectomy (the Surgery group). For the entire cohort, median overall survival (OS) was 20.5 months; in the Surgery group, median duration of bevacizumab-containing therapy (DOT) pre-surgery was 6.1 months; median OS was not reached. In the Non-surgery group, median OS and DOT were 18.7 and 11.4 months, respectively; no significant OS differences were noted between FP-O and FP-I, whereas FP use was associated with shorter OS (12.3 month; p <0.002; notably, these patients were older). Patients who received both FP-O- and FP-I-based regimens achieved numerically longer OS vs. those who received only one of these regimens (22.1 [19.9–24.0] vs. 18.9 [15.5–21.9] months). Among patients assessed for wild-type KRAS and treated with subsequent anti-EGFR agent, OS was 25.4 months and 18.7 months for 124 treated vs. 37 non-treated patients (non-significant). Cox analysis (controlling for age and gender) identified several non-oncology parameters associated with poorer clinical outcomes including concurrent use of diuretics and proton-pump inhibitors. CONCLUSIONS: Our tool provided insights that confirmed/complemented information gained from randomized-clinical trials. Prospective tool implementation is warranted.
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spelling pubmed-48562622016-05-07 A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting Siegelmann-Danieli, Nava Farkash, Ariel Katzir, Itzhak Vesterman Landes, Janet Rotem Rabinovich, Hadas Lomnicky, Yossef Carmeli, Boaz Parush-Shear-Yashuv, Naama PLoS One Research Article BACKGROUND: Randomized clinical trials constitute the gold-standard for evaluating new anti-cancer therapies; however, real-life data are key in complementing clinically useful information. We developed a computational tool for real-life data analysis and applied it to the metastatic colorectal cancer (mCRC) setting. This tool addressed the impact of oncology/non-oncology parameters on treatment patterns and clinical outcomes. METHODS: The developed tool enables extraction of any computerized information including comorbidities and use of drugs (oncological/non-oncological) per individual HMO member. The study in which we evaluated this tool was a retrospective cohort study that included Maccabi Healthcare Services members with mCRC receiving bevacizumab with fluoropyrimidines (FP), FP plus oxaliplatin (FP-O), or FP plus irinotecan (FP-I) in the first-line between 9/2006 and 12/2013. RESULTS: The analysis included 753 patients of whom 15.4% underwent subsequent metastasectomy (the Surgery group). For the entire cohort, median overall survival (OS) was 20.5 months; in the Surgery group, median duration of bevacizumab-containing therapy (DOT) pre-surgery was 6.1 months; median OS was not reached. In the Non-surgery group, median OS and DOT were 18.7 and 11.4 months, respectively; no significant OS differences were noted between FP-O and FP-I, whereas FP use was associated with shorter OS (12.3 month; p <0.002; notably, these patients were older). Patients who received both FP-O- and FP-I-based regimens achieved numerically longer OS vs. those who received only one of these regimens (22.1 [19.9–24.0] vs. 18.9 [15.5–21.9] months). Among patients assessed for wild-type KRAS and treated with subsequent anti-EGFR agent, OS was 25.4 months and 18.7 months for 124 treated vs. 37 non-treated patients (non-significant). Cox analysis (controlling for age and gender) identified several non-oncology parameters associated with poorer clinical outcomes including concurrent use of diuretics and proton-pump inhibitors. CONCLUSIONS: Our tool provided insights that confirmed/complemented information gained from randomized-clinical trials. Prospective tool implementation is warranted. Public Library of Science 2016-05-04 /pmc/articles/PMC4856262/ /pubmed/27144545 http://dx.doi.org/10.1371/journal.pone.0154689 Text en © 2016 Siegelmann-Danieli et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Siegelmann-Danieli, Nava
Farkash, Ariel
Katzir, Itzhak
Vesterman Landes, Janet
Rotem Rabinovich, Hadas
Lomnicky, Yossef
Carmeli, Boaz
Parush-Shear-Yashuv, Naama
A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title_full A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title_fullStr A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title_full_unstemmed A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title_short A Novel Computational Tool for Mining Real-Life Data: Application in the Metastatic Colorectal Cancer Care Setting
title_sort novel computational tool for mining real-life data: application in the metastatic colorectal cancer care setting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4856262/
https://www.ncbi.nlm.nih.gov/pubmed/27144545
http://dx.doi.org/10.1371/journal.pone.0154689
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