Association of NADPH oxidase polymorphisms with anthracycline-induced cardiotoxicity in the RICOVER-60 trial of patients with aggressive CD20(+) B-cell lymphoma.
GLA - German Lymphoma Alliance

Abstract (Expand)

AIM: To identify gene variants responsible for anthracycline-induced cardiotoxicity. PATIENTS & METHODS: Polymorphisms of the NADPH oxidase subunits and of the anthracycline transporters ABCC1, … ABCC2 and SLC28A3 were genotyped in elderly patients (61-80 years) treated for aggressive CD20(+) B-cell lymphomas with CHOP-14 with or without rituximab and followed up for 3 years. RESULTS: The accumulation of RAC2 subunit genotypes TA/AA among cases was statistically significant upon adjustment for gender, age and doxorubicin dose in a multivariate logistic regression analysis (OR: 2.3, p = 0.028; univariate: OR: 1.8, p = 0.077). RAC2 and CYBA genotypes were significantly associated with anthracycline-induced cardiotoxicity in a meta-analysis of this and a similar previous study. CONCLUSION: Our results support the theory that NADPH oxidase is involved in anthracycline-induced cardiotoxicity. Original submitted 9 July 2014; Revision submitted 19 December 2014.

Authors: A. Reichwagen, M. Ziepert, M. Kreuz, U. Godtel-Armbrust, T. Rixecker, V. Poeschel, M. Reza Toliat, P. Nurnberg, M. Tzvetkov, S. Deng, L. Trumper, G. Hasenfuss, M. Pfreundschuh, L. Wojnowski

Date Published: 1st Apr 2015

Publication Type: Not specified

Human Diseases: B-cell lymphoma

Towards Phenotyping of Clinical Trial Eligibility Criteria.
NLP4CR - Natural Language Processing for Clinical Research

Abstract (Expand)

BACKGROUND: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts … in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES: This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals. METHOD: Based on the inclusion/exclusion criteria of 5 sample studies and a text corpus consisting of 212 doctor's letters and medical follow-up documentation from a university cancer center, a prototype was developed and technically evaluated using NLP procedures (UIMA) for the extraction of facts from medical free texts. RESULTS: It was found that although the extracted entities are not always correct (precision between 23% and 96%), they provide a decisive indication as to which patient file should be read preferentially. CONCLUSION: The prototype presented here demonstrates the technical feasibility. In order to find available, lucrative phenotypes, an in-depth evaluation is required.

Authors: M. Lobe, S. Staubert, C. Goldberg, I. Haffner, A. Winter

Date Published: 5th May 2018

Publication Type: Journal article

Human Diseases: breast cancer

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