assessing women’s preferences and preference modeling for breast reconstruction decision making

assessing women’s preferences and preference modeling for breast reconstruction decision making

;Clement S. Sun, MS;Scott B. Cantor, PhD;Gregory P. Reece, MD;Melissa A. Crosby, MD;Michelle C. Fingeret, PhD;Mia K. Markey, PhD
current therapeutic research, clinical and experimental 2014 Vol. 2 pp. e125-
95
ms2014plasticassessing

Abstract

Background: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. Methods: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. Results: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. Conclusions: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.

Keywords

Citation

ID: 165993
Ref Key: ms2014plasticassessing
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
165993
Unique Identifier:
10.1097/GOX.0000000000000062
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet