Literature DB >> 25179409

Preappointment testing for BRAF/KIT mutation in advanced melanoma: a model in molecular data delivery for individualized medicine.

Taofic Mounajjed1, Char L Brown2, Therese K Stern3, Annette M Bjorheim2, Andrew J Bridgeman4, Kandelaria M Rumilla2, Robert R McWilliams3, Thomas J Flotte2.   

Abstract

The emergence of individualized medicine is driven by developments in precision diagnostics, epitomized by molecular testing. Because treatment decisions are being made based on such molecular data, data management is gaining major importance. Among data management challenges, creating workflow solutions for timely delivery of molecular data has become pivotal. This study aims to design and implement a scalable process that permits preappointment BRAF/KIT mutation analysis in melanoma patients, allowing molecular results necessary for treatment plans to be available before the patient's appointment. Process implementation aims to provide a model for efficient molecular data delivery for individualized medicine. We examined the existing process of BRAF/KIT testing in melanoma patients visiting our institution for oncology consultation. We created 5 working groups, each designing a specific segment of an alternative process that would allow preappointment BRAF/KIT testing and delivery of results. Data were captured and analyzed to evaluate the success of the alternative process. For 1 year, 35 (59%) of 55 patients had prior BRAF/KIT testing. The remaining 20 patients went through the new process of preappointment testing; results were available at the time of appointment for 12 patients (overall preappointment results availability, 85.5%). The overall process averaged 13.4 ± 4.7 days. In conclusion, we describe the successful implementation of a scalable workflow solution that permits preappointment BRAF/KIT mutation analysis and result delivery in melanoma patients. This sets the stage for further applications of this model to other conditions, answering an increasing demand for robust delivery of molecular data for individualized medicine.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BRAF; KIT; Melanoma; Preappointment testing; Workflow solutions

Mesh:

Substances:

Year:  2014        PMID: 25179409      PMCID: PMC4521775          DOI: 10.1016/j.humpath.2014.07.009

Source DB:  PubMed          Journal:  Hum Pathol        ISSN: 0046-8177            Impact factor:   3.466


  21 in total

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Review 2.  Moving towards individualized medicine with pharmacogenomics.

Authors:  William E Evans; Mary V Relling
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Review 3.  BRAF mutation testing in clinical practice.

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Review 4.  Pharmacogenomics: the promise of personalized medicine.

Authors:  L Mancinelli; M Cronin; W Sadée
Journal:  AAPS PharmSci       Date:  2000

Review 5.  Therapeutic implications of KIT in melanoma.

Authors:  Michael A Postow; Richard D Carvajal
Journal:  Cancer J       Date:  2012 Mar-Apr       Impact factor: 3.360

6.  A national agenda for the future of pathology in personalized medicine: report of the proceedings of a meeting at the Banbury Conference Center on genome-era pathology, precision diagnostics, and preemptive care: a stakeholder summit.

Authors:  Peter J Tonellato; James M Crawford; Mark S Boguski; Jeffrey E Saffitz
Journal:  Am J Clin Pathol       Date:  2011-05       Impact factor: 2.493

Review 7.  Targeted therapies and predictive markers in epithelial malignancies of the gastrointestinal tract.

Authors:  Maria McIntire; Mark Redston
Journal:  Arch Pathol Lab Med       Date:  2012-01-09       Impact factor: 5.534

Review 8.  The genetics of frontotemporal lobar degeneration.

Authors:  Rosa Rademakers; Mike Hutton
Journal:  Curr Neurol Neurosci Rep       Date:  2007-09       Impact factor: 5.081

Review 9.  Personalized medicine: individualized care of cancer patients.

Authors:  Scott Ely
Journal:  Transl Res       Date:  2009-09-01       Impact factor: 7.012

10.  Bioinformatics challenges for personalized medicine.

Authors:  Guy Haskin Fernald; Emidio Capriotti; Roxana Daneshjou; Konrad J Karczewski; Russ B Altman
Journal:  Bioinformatics       Date:  2011-05-19       Impact factor: 6.937

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