Unpacking overuse of androgen deprivation therapy for prostate cancer to inform de-implementation strategies

Ted A Skolarus, Sarah T Hawley, Jane Forman, Anne E Sales, Jordan B Sparks, Tabitha Metreger, Jennifer Burns, Megan V Caram, Archana Radhakrishnan, Lesly A Dossett, Danil V Makarov, John T Leppert, Jeremy B Shelton, Kristian D Stensland, Jennifer Dunsmore, Steven Maclennan, Sameer Saini, Brent K Hollenbeck, Vahakn Shahinian, Daniela A WittmannVarad Deolankar, S Sriram

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Abstract

BACKGROUND: Many men with prostate cancer will be exposed to androgen deprivation therapy (ADT). While evidence-based ADT use is common, ADT is also used in cases with no or limited evidence resulting in more harm than benefit, i.e., overuse. Since there are risks of ADT (e.g., diabetes, osteoporosis), it is important to understand the behaviors facilitating overuse to inform de-implementation strategies. For these reasons, we conducted a theory-informed survey study, including a discrete choice experiment (DCE), to better understand ADT overuse and provider preferences for mitigating overuse.

METHODS: Our survey used the Action, Actor, Context, Target, Time (AACTT) framework, the Theoretical Domains Framework (TDF), the Capability, Opportunity, Motivation-Behavior (COM-B) Model, and a DCE to elicit provider de-implementation strategy preferences. We surveyed the Society of Government Service Urologists listserv in December 2020. We stratified respondents based on the likelihood of stopping overuse as ADT monotherapy for localized prostate cancer ("yes"/"probably yes," "probably no"/"no"), and characterized corresponding Likert scale responses to seven COM-B statements. We used multivariable regression to identify associations between stopping ADT overuse and COM-B responses.

RESULTS: Our survey was completed by 84 respondents (13% response rate), with 27% indicating "probably no"/"no" to stopping ADT overuse. We found differences across respondents who said they would and would not stop ADT overuse in demographics and COM-B statements. Our model identified 2 COM-B domains (Opportunity-Social, Motivation-Reflective) significantly associated with a lower likelihood of stopping ADT overuse. Our DCE demonstrated in-person communication, multidisciplinary review, and medical record documentation may be effective in reducing ADT overuse.

CONCLUSIONS: Our study used a behavioral theory-informed survey, including a DCE, to identify behaviors and context underpinning ADT overuse. Specifying behaviors supporting and gathering provider preferences in addressing ADT overuse requires a stepwise, stakeholder-engaged approach to support evidence-based cancer care. From this work, we are pursuing targeted improvement strategies.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT03579680.

Original languageEnglish
Article number37
Number of pages13
JournalImplementation Science Communications
Volume5
DOIs
Publication statusPublished - 9 Apr 2024

Data Availability Statement

The data sets supporting the conclusions of this article will be shared upon request. Members of the scientific community who would like a copy of the final data sets (i.e., data sets underlying any publication) from this study can request a copy by e-mailing Dr. Ted Skolarus at [email protected]. The investigator should state their reason for requesting the data and their plans for analyzing the data. De-identified data will be provided after requestors sign a Letter of Agreement detailing the mechanisms by which the data will be kept secure and access restricted to their study team. The agreements will also state the recipient will not attempt to identify any individual whose data are included and will not share the data with anyone outside of their research team. The data set will not include private or protected information, and all dates will be changed to integers to allow for the calculation of time periods. Final data sets will be copied onto a CD and limited data sets will be encrypted, and the password will be sent to the requestor via e-mail. The CD will be sent to the requestor via FedEx. Each data set will be accompanied by documentation that lists all variables described in the publication and links them with variable names in the data set.

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