Evaluating novel agent effects in multiple-treatments meta-regression
Φόρτωση...
Ημερομηνία
Συγγραφείς
Salanti, G.
Dias, S.
Welton, N. J.
Ades, A. E.
Golfinopoulos, V.
Kyrgiou, M.
Mauri, D.
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
Stat Med
Όνομα βιβλίου
Σειρά βιβλίου
Έκδοση βιβλίου
Συμπληρωματικός/δευτερεύων τίτλος
Περιγραφή
Multiple-treatments meta-analyses are increasingly used to evaluate the relative effectiveness of several competing regimens. In some fields which evolve with the continuous introduction of new agents over time, it is possible that in trials comparing older with newer regimens the effectiveness of the latter is exaggerated. Optimism bias, conflicts of interest and other forces may be responsible for this exaggeration, but its magnitude and impact, if any, needs to be formally assessed in each case. Whereas such novelty bias is not identifiable in a pair-wise meta-analysis, it is possible to explore it in a network of trials involving several treatments. To evaluate the hypothesis of novel agent effects and adjust for them, we developed a multiple-treatments meta-regression model fitted within a Bayesian framework. When there are several multiple-treatments meta-analyses for diverse conditions within the same field/specialty with similar agents involved, one may consider either different novel agent effects in each meta-analysis or may consider the effects to be exchangeable across the different conditions and outcomes. As an application, we evaluate the impact of modelling and adjusting for novel agent effects for chemotherapy and other non-hormonal systemic treatments for three malignancies. We present the results and the impact of different model assumptions to the relative ranking of the various regimens in each network. We established that multiple-treatments meta-regression is a good method for examining whether novel agent effects are present and estimation of their magnitude in the three worked examples suggests an exaggeration of the hazard ratio by 6 per cent (2-11 per cent).
Περιγραφή
Λέξεις-κλειδιά
Antineoplastic Agents/*therapeutic use, Antineoplastic Combined Chemotherapy Protocols/*therapeutic use, Bayes Theorem, Bias (Epidemiology), Breast Neoplasms/*drug therapy, Colorectal Neoplasms/*drug therapy, Female, Humans, *Meta-Analysis as Topic, Multivariate Analysis, Ovarian Neoplasms/*drug therapy, Randomized Controlled Trials as Topic, Treatment Outcome
Θεματική κατηγορία
Παραπομπή
Σύνδεσμος
http://www.ncbi.nlm.nih.gov/pubmed/20687172
http://onlinelibrary.wiley.com/store/10.1002/sim.4001/asset/4001_ftp.pdf?v=1&t=h0dohmy6&s=d70f795f61778a85f260fa7a9fcd46f55356fc1a
http://onlinelibrary.wiley.com/store/10.1002/sim.4001/asset/4001_ftp.pdf?v=1&t=h0dohmy6&s=d70f795f61778a85f260fa7a9fcd46f55356fc1a
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