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American Association for Cancer Research, Cancer Research, 4_Supplement(82), p. P5-19-04-P5-19-04, 2022

DOI: 10.1158/1538-7445.sabcs21-p5-19-04

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Abstract P5-19-04: The WISDOM study: Reducing sequential steps and implementing parallel workflows in pragmatic trials

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Background:The WISDOM Study is a preference-tolerant pragmatic study, comparing annual mammograms to a risk-based screening. Eligibility includes women ages 40-74 years with no history of breast cancer or DCIS. Participants are enrolled to one study arm: annual screening or risk-based screening (includes genetic testing). Pragmatic trials often involve gathering real-time data over multiple time points. Collecting real-time data sequentially can limit enrollment, delay study assignments, and reduce participant engagement. The WISDOM Study has identified such bottlenecks and has implemented parallel workflows, reducing the overall wait time for participants to complete required study steps. These data highlight how moving participants through the study more efficiently can improve enrollment and retention and inform other pragmatic trials. Methods: WISDOM participants have the option to either choose their study arm or be randomized into one as part of the preference tolerant randomized trial design. Participants then complete breast health questionnaires and genetic testing (if in the risk-based arm). This information is analyzed by the WISDOM breast cancer risk assessment algorithm, the result of which is then communicated to the participant through a screening assignment letter (SAL). Specific data elements, such as breast density found participants’ mammogram reports and genetic testing results are required for study randomization process and risk assessment calculations, respectively. The WISDOM randomization algorithm is stratified by several factors, including breast cancer risk estimated using the Breast Cancer Surveillance Consortium (BCSC) model, which uses mammographic density as a key input variable. The study team changed the workflow to allow participants to proceed to randomization without specific information by imputing both density and risk. Additionally, a parallel workflow improvement process was implemented to obtain mammogram reports while genetic testing was being completed. Results: Before the weighted BCSC and imputed density algorithms were introduced, it took an average of 47 days to randomize participants after completion of the baseline enrollment questionnaires. Now, participants are randomized immediately which has reduced delays by 100%. Prior to implementing the parallel workflow for genetic testing and mammogram ascertainment, genetic testing kits were sent only after mammogram reports were collected and validated. The expected turnaround time for genetic testing results was 30-60 days and on average, results were returned to participants in 42 days. Streamlining the study design to obtain mammogram reports while participants complete their genetic testing has shortened the time for participants to receive their screening assignment letters (SALs) from an average of 160 days to 78 days, a reduction by 49%. In comparison, participants in the annual arm of the study who do not complete genetic testing, receive their SALs after an average of 38 days from enrollment. This is due to long wait times to obtain mammographic densities from outside medical facilities. Conclusions: Creating parallel data ascertainment workflows and reducing sequential steps in the study process has increased completion of individual enrollment activities. Participants now are randomized immediately upon joining the study and have access to their SALs and genetic results more rapidly. This approach eliminated randomization wait times and improved efficiency of the early in the enrollment process. We are evaluating the impact on participant retention going forward. Workflow efficiency is critical to improve the patient experience, and our learnings can inform future trial design, particularly for studies requiring data from outside sources. Citation Format: Tomiyuri Lewis, Stephanie Flores, Leah Sabacan, Patricia Choy, Halle Thannickal, Yiwey Shieh, Jeffrey Tice, Elad Ziv, Lisa Madlensky, Martin Eklund, Christina Yau, Amie Blanco, Barry Tong, Deborah Goodman, Nancy Anderson, Heather Harvey, Steele Fors, Hannah L Park, Samrrah Raouf, Skye Stewart, Janet Wernisch, Barbara Koenig, Celia Kaplan, Robert Hiatt, Neil Wenger, Vivian Lee, Diane Heditsian, Susie Brain, Dolores Moorehead, Barbara A Parker, Alexander Borowsky, Hoda Anton-Culver, Arash Naeim, Andrea Kaster, Laura van ‘t Veer, Andrea Z LaCroix, Olufunmilayo I Olopade, Deepa Sheth, Agustin Garcia, Rachel Lancaster, Michael Plaza, Wisdom Study, Athena Breast Health Network Investigators, Advocate Partners, Allison S Fiscalini, Laura Esserman. The WISDOM study: Reducing sequential steps and implementing parallel workflows in pragmatic trials [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-19-04.