A Primer to Cost-Effectiveness Analysis in Breast Cancer Imaging : A Review of the Literature
Copyright © 2022, Waller et al..
Currently, there is a multitude of methods for evaluating the costs and benefits of programs, tools, etc. While cost-benefit analysis (CBA) is commonly used, cost-effectiveness analysis (CEA) is a more appropriate method of evaluation in clinical contexts, such as radiology practices, as CEAs use units such as life years gained as opposed to money (as is the case for CBAs). This review examines CEAs performed within the past 15 years to highlight their applications and key findings in the context of medical imaging. In total, 20 articles published between 2006 and 2022 were identified using a PubMed search for keywords including "cost-effectiveness analysis," "breast cancer," and "medical imaging," with studies lacking a substantial discussion of CEA or a related topic being excluded. CEAs have traditionally been criticized for lack of a standard methodology, despite their utility in the detection and treatment of various pathologies. Although mammography and magnetic resonance imaging (MRI) are the preferred and cost-effective imaging modalities for breast cancer, other imaging modalities, such as contrast-enhanced mammography and digital breast tomosynthesis, may be more cost-effective in the appropriate clinical context. Different combinations of mammography and MRI screenings for certain breast cancers may also prove to be more cost-effective compared to current mammography/MRI screening schedules. While CEA has shown potential utility in estimating the costs (per unit of health gained) of different imaging tools, CEA risks ignoring important outcomes not included in the analysis and cannot address if the benefits of the imaging tool exceed its costs, as a CBA would, suggesting the need for combining several economic evaluations for a more complete understanding.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:14 |
|---|---|
| Enthalten in: |
Cureus - 14(2022), 8 vom: 09. Aug., Seite e28356 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Waller, Joseph [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Breast cancer |
|---|
| Anmerkungen: |
Date Revised 17.09.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.7759/cureus.28356 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM346230179 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM346230179 | ||
| 003 | DE-627 | ||
| 005 | 20231226030925.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.7759/cureus.28356 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1154.xml |
| 035 | |a (DE-627)NLM346230179 | ||
| 035 | |a (NLM)36106225 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Waller, Joseph |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A Primer to Cost-Effectiveness Analysis in Breast Cancer Imaging |b A Review of the Literature |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 17.09.2022 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Copyright © 2022, Waller et al. | ||
| 520 | |a Currently, there is a multitude of methods for evaluating the costs and benefits of programs, tools, etc. While cost-benefit analysis (CBA) is commonly used, cost-effectiveness analysis (CEA) is a more appropriate method of evaluation in clinical contexts, such as radiology practices, as CEAs use units such as life years gained as opposed to money (as is the case for CBAs). This review examines CEAs performed within the past 15 years to highlight their applications and key findings in the context of medical imaging. In total, 20 articles published between 2006 and 2022 were identified using a PubMed search for keywords including "cost-effectiveness analysis," "breast cancer," and "medical imaging," with studies lacking a substantial discussion of CEA or a related topic being excluded. CEAs have traditionally been criticized for lack of a standard methodology, despite their utility in the detection and treatment of various pathologies. Although mammography and magnetic resonance imaging (MRI) are the preferred and cost-effective imaging modalities for breast cancer, other imaging modalities, such as contrast-enhanced mammography and digital breast tomosynthesis, may be more cost-effective in the appropriate clinical context. Different combinations of mammography and MRI screenings for certain breast cancers may also prove to be more cost-effective compared to current mammography/MRI screening schedules. While CEA has shown potential utility in estimating the costs (per unit of health gained) of different imaging tools, CEA risks ignoring important outcomes not included in the analysis and cannot address if the benefits of the imaging tool exceed its costs, as a CBA would, suggesting the need for combining several economic evaluations for a more complete understanding | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a breast cancer | |
| 650 | 4 | |a cost-effectiveness analysis | |
| 650 | 4 | |a imaging | |
| 650 | 4 | |a mammography | |
| 650 | 4 | |a mri | |
| 700 | 1 | |a DeStefano, Kyle |e verfasserin |4 aut | |
| 700 | 1 | |a Dempsey, John |e verfasserin |4 aut | |
| 700 | 1 | |a Leckron, Joshua |e verfasserin |4 aut | |
| 700 | 1 | |a Tucker, Amy |e verfasserin |4 aut | |
| 700 | 1 | |a Umair, Muhammad |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Cureus |d 2013 |g 14(2022), 8 vom: 09. Aug., Seite e28356 |w (DE-627)NLM24118083X |x 2168-8184 |7 nnns |
| 773 | 1 | 8 | |g volume:14 |g year:2022 |g number:8 |g day:09 |g month:08 |g pages:e28356 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.7759/cureus.28356 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 14 |j 2022 |e 8 |b 09 |c 08 |h e28356 | ||