Caroline M Vass1, Dan Rigby2, Katherine Payne3. 1. Manchester Centre for Health Economics, The University of Manchester, Manchester, UK. 2. Department of Economics, The University of Manchester, Manchester, UK. 3. Manchester Centre for Health Economics, The University of Manchester, Manchester, UK. Electronic address: katherine.payne@manchester.ac.uk.
Abstract
BACKGROUND: The relative benefits and risks of screening programs for breast cancer have been extensively debated. OBJECTIVES: To quantify and investigate heterogeneity in women's preferences for the benefits and risks of a national breast screening program (NBSP) and to understand the effect of risk communication format on these preferences. METHODS: An online discrete choice experiment survey was designed to elicit preferences from female members of the public for an NBSP described by three attributes (probability of detecting a cancer, risk of unnecessary follow-up, and out-of-pocket screening costs). Survey respondents were randomized to one of two surveys, presenting risk either as percentages only or as icon arrays and percentages. Respondents were required to choose between two hypothetical NBSPs or no screening in 11 choice sets generated using a Bayesian D-efficient design. The trade-offs women made were analyzed using heteroskedastic conditional logit and scale-adjusted latent class models. RESULTS: A total of 1018 women completed the discrete choice experiment (percentages-only version = 507; icon arrays and percentages version = 511). The results of the heteroskedastic conditional logit model suggested that, on average, women were willing-to-accept 1.72 (confidence interval 1.47-1.97) additional unnecessary follow-ups and willing-to-pay £79.17 (confidence interval £66.98-£91.35) for an additional cancer detected per 100 women screened. Latent class analysis indicated substantial heterogeneity in preferences with six latent classes and three scale classes providing the best fit. The risk communication format received was not a predictor of scale class or preference class membership. CONCLUSIONS: Most women were willing to trade-off the benefits and risks of screening, but decision makers seeking to improve uptake should consider the disparate needs of women when configuring services.
BACKGROUND: The relative benefits and risks of screening programs for breast cancer have been extensively debated. OBJECTIVES: To quantify and investigate heterogeneity in women's preferences for the benefits and risks of a national breast screening program (NBSP) and to understand the effect of risk communication format on these preferences. METHODS: An online discrete choice experiment survey was designed to elicit preferences from female members of the public for an NBSP described by three attributes (probability of detecting a cancer, risk of unnecessary follow-up, and out-of-pocket screening costs). Survey respondents were randomized to one of two surveys, presenting risk either as percentages only or as icon arrays and percentages. Respondents were required to choose between two hypothetical NBSPs or no screening in 11 choice sets generated using a Bayesian D-efficient design. The trade-offs women made were analyzed using heteroskedastic conditional logit and scale-adjusted latent class models. RESULTS: A total of 1018 women completed the discrete choice experiment (percentages-only version = 507; icon arrays and percentages version = 511). The results of the heteroskedastic conditional logit model suggested that, on average, women were willing-to-accept 1.72 (confidence interval 1.47-1.97) additional unnecessary follow-ups and willing-to-pay £79.17 (confidence interval £66.98-£91.35) for an additional cancer detected per 100 women screened. Latent class analysis indicated substantial heterogeneity in preferences with six latent classes and three scale classes providing the best fit. The risk communication format received was not a predictor of scale class or preference class membership. CONCLUSIONS: Most women were willing to trade-off the benefits and risks of screening, but decision makers seeking to improve uptake should consider the disparate needs of women when configuring services.
Authors: Suzana Karim; Benjamin M Craig; Caroline Vass; Catharina G M Groothuis-Oudshoorn Journal: Pharmacoeconomics Date: 2022-08-12 Impact factor: 4.558
Authors: Alexander G Mathioudakis; Minna Salakari; Liisa Pylkkanen; Zuleika Saz-Parkinson; Anke Bramesfeld; Silvia Deandrea; Donata Lerda; Luciana Neamtiu; Hector Pardo-Hernandez; Ivan Solà; Pablo Alonso-Coello Journal: Psychooncology Date: 2019-03-24 Impact factor: 3.894
Authors: Ash Kieran Clift; David Dodwell; Simon Lord; Stavros Petrou; Sir Michael Brady; Gary S Collins; Julia Hippisley-Cox Journal: Br J Cancer Date: 2021-10-26 Impact factor: 9.075
Authors: Emily Grayek; Yanran Yang; Baruch Fischhoff; Karen E Schifferdecker; Steven Woloshin; Karla Kerlikowske; Diana L Miglioretti; Anna N A Tosteson Journal: Med Decis Making Date: 2022-01-22 Impact factor: 2.749