Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Clinical management and risk stratification of B-lymphoblastic leukemia/ lymphoma (B-ALL/LBL) depend largely on identification of chromosomal abnormalities obtained using conventional cytogenetics and Fluorescence In Situ Hybridization (FISH) testing. In the last few decades, testing algorithms have been implemented to support an optimal risk-oriented therapy, leading to a large improvement in overall survival. In addition, large scale genomic studies have identified multiple aberrations of prognostic significance that are not routinely tested by existing modalities. However, as chromosomal microarray analysis (CMA) and next-generation sequencing (NGS) technologies are increasingly used in clinical management of hematologic malignancies, these abnormalities may be more readily detected. In this article, we have compiled a comprehensive, evidence-based review of the current B-ALL literature, focusing on known and published subtypes described to date. More specifically, we describe the role of various testing modalities in the diagnosis, prognosis, and therapeutic relevance. In addition, we propose a testing algorithm aimed at assisting laboratories in the most effective detection of the underlying genomic abnormalities.
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http://dx.doi.org/10.1016/j.cancergen.2020.03.001 | DOI Listing |