Home > Journals > The Quarterly Journal of Nuclear Medicine and Molecular Imaging > Past Issues > The Quarterly Journal of Nuclear Medicine 2000 June;44(2) > The Quarterly Journal of Nuclear Medicine 2000 June;44(2):197-203

CURRENT ISSUE
 

ARTICLE TOOLS

Reprints

THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

A Journal on Nuclear Medicine and Molecular Imaging


A Journal on Nuclear Medicine and Molecular Imaging
Affiliated to the Society of Radiopharmaceutical Sciences and to the International Research Group of Immunoscintigraphy
Indexed/Abstracted in: Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index (SciSearch), Scopus
Impact Factor 2,481


eTOC

 

  ECONOMICS OF NUCLEAR MEDICINE
Guest Editor: Gambhir S. S.
FREEfree


The Quarterly Journal of Nuclear Medicine 2000 June;44(2):197-203

Copyright © 2009 EDIZIONI MINERVA MEDICA

language: English

Clinical trials of cost effectiveness in technology evaluation

Valk P. E.

From the Northern California PET Imaging Center Sacramento, CA, USA and Department of Molecular and Medical Pharmacology UCLA School of Medicine, Los Angeles, CA, USA


FULL TEXT  


This arti­cle dis­cuss­es mod­els of effi­ca­cy, ­design of clin­i­cal ­trials and the ­role of math­e­mat­i­cal mod­el­ing in diag­nos­tic tech­nol­o­gy eval­u­a­tion and deter­mi­na­tion of ­cost-effec­tive­ness. A mul­ti-­tiered mod­el of effi­ca­cy, ­which ­views diag­nos­tic imag­ing as ­part of a glo­bal pro­cess of ­patient man­age­ment and out­come, has ­been ­described. The ­first ­tier ­involves imag­ing effi­ca­cy, ­which ­must be deter­mined by clin­i­cal ­trial. Direct com­par­i­son of new and estab­lished modal­ities in a sin­gle ­study pop­u­la­tion has ­major advan­tag­es ­over ran­dom­ized con­trolled ­trials, ­which are extreme­ly cost­ly and ­time-con­sum­ing and are not appro­pri­ate for ­most eval­u­a­tions of diagnostic modal­ities. Selection of ­patients for inclu­sion in the ­trial, inter­pre­ta­tion and ver­ifi­ca­tion of ­results, and deter­mi­na­tion of a ref­er­ence stan­dard are all pos­sible sourc­es of ­bias, ­which ­need to be iden­ti­fied and con­trolled. Decision anal­y­sis mod­el­ing can be ­used to ­assess diag­nos­tic, ther­a­peu­tic, ­patient-out­come and ­cost effi­ca­cy, ­once imag­ing effi­ca­cy has ­been eval­u­at­ed by clin­i­cal ­trial. Decision anal­y­sis is easi­er and ­less expen­sive to per­form ­than clin­i­cal ­trials, and ­results are eas­i­ly gener­a­liz­able to oth­er set­tings. Disadvantages ­arise ­from the non-descrip­tive ­nature of mod­el­ing and ­lack of trans­pa­ren­cy, ­which ­make it dif­fi­cult to eval­u­ate the appro­pri­ate­ness of deci­sion ­tree struc­tures and ­input ­data. Modeling is an unavoid­a­ble ­fact of ­life in tech­nol­o­gy eval­u­a­tion, ­since the resourc­es ­that ­would be ­required for ­full eval­u­a­tion of imag­ing modal­ities by clin­i­cal ­trial are not avail­able.

top of page

Publication History

Cite this article as

Corresponding author e-mail