Software Application for Data Collection and Analysis in Acute Myeloid Leukemia

Authors

  • Anca BACÂREA University of Medicine and Pharmacy Târgu Mureş, Physiopathology Department, 38 Gh. Marinescu str., Tîrgu Mureş, Romania.
  • Bogdan Adnan HAIFA University of Medicine and Pharmacy Târgu Mureş, Medical Informatics and Biostatistics Department, 38 Gh. Marinescu str., Tîrgu Mureş, Romania.
  • Marius MUJI University Petru Maior Târgu Mureş, Engineering Department, 1 Nicolae Iorga str., Tîrgu Mureş, Romania.
  • Alexandru SCHIOPU University of Medicine and Pharmacy Târgu Mureş, Physiopathology Department, 38 Gh. Marinescu str., Tîrgu Mureş, Romania.

Keywords:

Acute myeloid leukaemia, Database, Survival.

Abstract

Aim: It is important in the context of the informatics development and also of medical research,that new software technology to be integrated in order to achieve easier research. The aim of thisstudy was to develop a software application that uses few resources, and that enable data collection,their primary processing in statistical terms (e.g. mean, median, etc.), drawing of survival curvesand survival Log Rank statistic testing according to the collected parameters. Material and Method:For this purpose, a database in SQLite3 was developed. Because the database engine is embeddedin the Database Management System (DBMS) this program allows absolute portability. Graphicalinterface was made in wxWidgets. Statistical calculations were obtained using R software (the`addons` E1071 was used for descriptive statistics and the `Survival `for testing survival andNorthest for Kaplan Meier survival curve). Patients were cases admitted and treated in theHematology Department of County Emergency Hospital Tîrgu Mureş hospitalized and treatedduring 2007-2010. Results: We created a GUI in wxWidgets to collect the desired medical data: age,date of diagnosis, date of death, blood count values, and the CD leukocyte markers detected byflow cytometry. Entwining of medical data collection and processing statistics (for acute myeloidleukemia - survival, prognostic factors evaluation) is a further step in medical research. Conclusion:The tool presented is a useful for research. Application in acute myeloid leukemia derives from theauthor's interest in the subject; development of this tool in other directions is possible anddesirable.

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How to Cite

1.
BACÂREA A, HAIFA BA, MUJI M, SCHIOPU A. Software Application for Data Collection and Analysis in Acute Myeloid Leukemia. Appl Med Inform [Internet]. 2011 Mar. 24 [cited 2024 Jun. 18];28(1):16-22. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/59

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