Is molecular profiling ready for use in clinical decision making?

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Μικρογραφία εικόνας

Ημερομηνία

Συγγραφείς

Ioannidis, J. P.

Τίτλος Εφημερίδας

Περιοδικό ISSN

Τίτλος τόμου

Εκδότης

Περίληψη

Τύπος

Είδος δημοσίευσης σε συνέδριο

Είδος περιοδικού

peer-reviewed

Είδος εκπαιδευτικού υλικού

Όνομα συνεδρίου

Όνομα περιοδικού

Oncologist

Όνομα βιβλίου

Σειρά βιβλίου

Έκδοση βιβλίου

Συμπληρωματικός/δευτερεύων τίτλος

Περιγραφή

Molecular profiling, the classification of tissue or other specimens for diagnostic, prognostic, and predictive purposes based on multiple gene expression, is a technology that holds major promise for optimizing the management of patients with cancer. However, the use of these tests for clinical decision making presents many challenges to overcome. Assay development and data analysis in this field have been largely exploratory, and leave numerous possibilities for the introduction of bias. Standardization of profiles remains the exception. Classifier performance is usually overinterpreted by presenting the results as p-values or multiplicative effects (e.g., relative risks), while the absolute sensitivity and specificity of classification remain modest at best, especially when tested in large validation samples. Validation has often been done with suboptimal attention to methodology and protection from bias. The postulated classifier performance may be inflated compared to what these profiles can achieve. With the exception of breast cancer, we have little evidence about the incremental discrimination that molecular profiles can provide versus classic risk factors alone. Clinical trials have started to evaluate the utility of using molecular profiles for breast cancer management. Until we obtain data from these trials, the impact of these tests and the net benefit under real-life settings remain unknown. Optimal incorporation into clinical practice is not straightforward. Finally, cost-effectiveness is difficult to appreciate until these other challenges are addressed. Overall, molecular profiling is a fascinating and promising technology, but its incorporation into clinical decision making requires careful planning and robust evidence.

Περιγραφή

Λέξεις-κλειδιά

*Decision Making, Gene Expression Profiling/*methods, Humans, Neoplasms/*genetics/pathology/therapy, Risk Factors

Θεματική κατηγορία

Παραπομπή

Σύνδεσμος

http://www.ncbi.nlm.nih.gov/pubmed/17405894
http://theoncologist.alphamedpress.org/content/12/3/301.full.pdf

Γλώσσα

en

Εκδίδον τμήμα/τομέας

Όνομα επιβλέποντος

Εξεταστική επιτροπή

Γενική Περιγραφή / Σχόλια

Ίδρυμα και Σχολή/Τμήμα του υποβάλλοντος

Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής

Πίνακας περιεχομένων

Χορηγός

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