{"paper_id":"3dbfa59e-cc0b-4bf4-b1c3-1635a64d3d10","body_text":"Strategies for DPYD Testing Prior to Fluoropyrimidine Chemotherapy in the United States | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Strategies for DPYD Testing Prior to Fluoropyrimidine Chemotherapy in the United States Tabea Tracksdorf, D. Max Smith, Skyler Pearse, Emily J Cicali, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4207186/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Purpose Patients with dihydropyrimidine dehydrogenase (DPD) deficiency are at high risk for severe and fatal toxicity from fluoropyrimidine (FP) chemotherapy. Pre-treatment DPYD testing is standard of care in many countries, but not the United States (US). This survey assessed pre-treatment DPYD testing approaches in the US to identify best practices for broader adoption. Methods From August to October 2023, a 22-item Qualtrics XM survey was sent to institutions and clinicians known to conduct pre-treatment DPYD testing and broadly distributed through relevant organizations and social networks. Responses were analyzed using descriptive analysis. Results Responses from 24 unique US sites that have implemented pre-treatment DPYD testing or have a detailed implementation plan in place were analyzed. Only 33% of sites ordered DPYD testing for all FP-treated patients; at the remaining sites, patients were tested depending on disease characteristics or clinician preference. Almost 50% of sites depend on individual clinicians to remember to order testing without the assistance of electronic alerts or workflow reminders. DPYD testing was most often conducted by commercial laboratories that tested for at least the 4 or 5 DPYD variants considered clinically actionable. Approximately 90% of sites reported receiving results within 10 days of ordering. Conclusion Implementing DPYD testing into routine clinical practice is feasible and requires a coordinated effort among the healthcare team. These results will be used to develop best practices for the clinical adoption of DPYD testing to prevent severe and fatal toxicity in cancer patients receiving FP chemotherapy. DPYD clinical implementation fluoropyrimidines survey pharmacogenetics oncology Figures Figure 1 Figure 2 Introduction Fluoropyrimidines (FP), including intravenous 5-fluorouracil and its oral prodrug capecitabine, have been used for over 60 years as a treatment for cancer [ 1 , 2 ]. An estimated 2 million patients worldwide receive these antimetabolite drugs annually to treat a variety of solid tumors such as colorectal, pancreatic, breast, and head and neck cancers [ 1 ]. About 30% of patients develop severe FP-associated toxicity, including diarrhea, hand-foot syndrome, mucositis, and myelosuppression, which can be fatal for ~ 0.1% of patients [ 3 , 4 ]. Over 80% of systemically available FP is catabolized by the dihydropyrimidine dehydrogenase (DPD) enzyme [ 1 ]. Germline mutations in DPYD , the gene encoding DPD, lead to diminished or null DPD activity, resulting in the systemic accumulation of FP and increased risk of severe adverse reactions [ 1 ]. More than 160 recurrent allelic variants in DPYD have been identified, including five ( DPYD *2A (rs3918290), DPYD *13 (rs55886062), DPYD p.D949V (rs67376798), DPYD HapB3 (rs56038477), and DPYD p.Y186C (rs115232898)) that have been reproducibly associated with an increased FP toxicity risk [ 5 – 7 ]. Approximately 6% of the United States (US) population carries one of these germline DPYD variants [ 8 ]. DPD enzyme activity may be determined using either genotypic or phenotypic methods, allowing individualization of FP dosing to mitigate the occurrence of treatment-related toxicity [ 1 ]. While phenotypic testing is standard of care in some European countries (e.g., France) [ 9 ], it is not readily available in the US, and its reliability has been called into question [ 10 ]. Thus, genotyping is the prevalent method of testing in the US. FP dosing recommendations for patients with known DPYD genotypes are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) [ 5 , 11 ]. Importantly, several prospective studies have demonstrated that pre-treatment DPYD testing and genotype-guided dosing decrease treatment-related toxicity, are cost-effective, and are feasible in routine clinical practice [ 11 – 14 ]. Accordingly, various countries, including England, Switzerland, Austria, and Germany, have adopted routine testing for DPD deficiency prior to FP treatment [ 15 , 16 ]. A survey conducted in Europe found that the number of DPYD genotyping tests doubled from 2019 to 2021 [ 17 ], primarily due to the European Medicine Agency (EMA) recommendation for pre-treatment DPD testing in 2020 [ 18 ] and consistent testing reimbursement [ 17 ]. Pharmacogenetic (PGx) testing to optimize treatment is rapidly expanding within the US [ 19 , 20 ] across a number of therapeutic areas and drugs [ 21 , 22 ]; however, DPYD testing prior to FP treatment is not currently recommended by any US-based clinical oncology guidelines or the FDA [ 23 – 25 ]. According to a 2017 survey, only 20% of US medical oncologists had ever ordered pre-treatment DPYD testing, despite 98% agreeing that patients with DPD deficiency have increased FP toxicity risk [ 26 ]. According to the survey and other qualitative studies, US-based medical oncologists refrain from DPYD testing due in part to the lack of clinical practice guideline recommendations and limited knowledge of testing options and interpretation [ 26 , 27 ]. Consequently, DPYD variants are often identified only after severe FP toxicity through reactive testing [ 23 ]. However, recent publications have raised awareness of the clinical benefit of pre-treatment DPYD testing [ 28 , 29 ], including evidence that dose reduction in DPYD variant carriers does not reduce treatment efficacy [ 30 ], leading to an increase in implementation of pre-treatment DPYD testing [ 13 , 31 , 32 ]. The objective of this survey is to summarize current approaches to the implementation of DPYD testing prior to FP treatment in the US to inform best practices for broader clinical adoption. Methods Survey Development This 22-item survey was developed by a multidisciplinary team of medical professionals and experts in PGx. It was modeled after previously conducted surveys of PGx implementation programs [21, 22] and adapted based on internal expertise to better understand the landscape of pre-treatment DPYD testing implementation strategies across the US. The survey included multiple-choice and free-response questions to assess each site’s DPYD testing program, including general site information (e.g., site type, clinical or research testing) (n=10 questions), test ordering (n=7), and interpreting, reporting, and storing of test results (n=5) (Survey Included as Online Material Appendix 1 ). Recruitment of Respondents The survey was created within the web-based survey software Qualtrics XM and distributed between August and October 2023. Individuals at sites known by the coauthors to conduct pre-treatment DPYD testing were contacted directly, and the survey was also broadly distributed through relevant organizations (e.g., Pharmacogenomics Global Research Network (PGRN), Multinational Association of Supportive Care in Cancer (MASCC), CPIC), and social networks (e.g., LinkedIn). Additionally, survey participants were asked to provide contact information for other sites that conduct pre-treatment DPYD testing and asked to forward the survey to individuals at those sites directly. The survey was approved as exempt from human subjects research by the University of Michigan IRBMED and survey respondents provided implied informed consent to participate by completing the non-anonymized survey. Data analysis Survey responses from a site were eligible for inclusion if the survey was completed, the site was located within the US, and the site had implemented pre-treatment DPYD testing or could provide a sufficiently detailed implementation plan. After filtering the raw data for eligibility (See Online Material Table 1 ), multiple responses from the same site were reconciled to enable a site-level analysis (See Online Material Table 2 ). Survey responses were reviewed to correct contradictory data or fill in missing information by asking respondents for clarification and/or searching for information online. For example, in some cases the number of genes and variants that sites indicated were tested by a commercial testing company did not match the information from those companies; in this event, we used the information from the testing companies. Additionally, responses to some questions were grouped to enhance understanding of the results in this manuscript (See Online Material Table 3 ). Responses were analyzed using descriptive analysis. Results Characteristics of the Sites Included in the Analysis Of the 134 survey responses that were initiated, 64 surveys were completed, including responses from 24 unique sites within the US that had implemented testing (n=21, 88%) or could provide a sufficiently detailed implementation plan (n=3, 13%) to be included in the analysis ( Fig. 1 ). Excluding three sites that did not complete the survey in a single attempt, all sites finished the survey in under 30 minutes. Characteristics of the respondents and 24 sites are summarized in Table 1 . Pharmacists submitted survey responses for 63% (15/24) of these sites. Most sites (71%; 17/24) were academic teaching institutions/hospitals, and 83% (20/24) utilized testing primarily for clinical practice. Pre-treatment DPYD testing was most often championed by multiple professionals, including medical oncologists (67%; 16/24), precision medicine teams (58%; 14/24), and pharmacists (58%; 14/24). Test Ordering Process The process for ordering and paying for testing is summarized in Table 2 . While 33% of sites (8/24) reported testing all FP-treated patients using different patient selection approaches, the majority (67%; 16/24) indicated testing only selected patients who are prescribed FP chemotherapy. Criteria for selecting patients for testing included disease characteristics (e.g., type of cancer) and clinician preference (e.g., the clinician’s familiarity with pre-treatment DPYD testing) ( Online Material Table 3 ). Medical oncologists/prescribers ordered testing at nearly every site (96%; 23/24), with many sites indicating that multiple clinicians participated in the ordering process, including nurses (33%; 8/24) and a PGx service (29%; 7/24). Additionally, approximately half of the sites reported having some type of systematized ordering process, such as order sets or clinical decision support (CDS, 54%; 13/24), whereas the other half of sites relied on clinicians to remember to order testing (46%; 11/24). To cover the cost of pre-treatment DPYD testing, 67% (16/24) of sites reported billing for insurance reimbursement, while 29% (7/24) indicated that tests were covered by institutional or research funds. One site reported that patients pay out of pocket. DPYD Testing Table 3 compares the turnaround time (TAT), number of DPYD variants, and number of genes included on the testing panels used by survey respondents. DPYD testing was conducted by commercial laboratories at 54% (13/24) of sites, with others using their own in-house testing (38%; 9/24) or another institution’s laboratory (8%; 2/24). Most sites (67%; 16/24) utilized at least one laboratory offering a multi-gene panel, and the vast majority included at least the 4 to 5 DPYD variants considered validated for clinical actionability ( DPYD *2A , DPYD *13 , DPYD p.D949V, DPYD HapB3, and DPYD p.Y186C) (86%;19/22, Fig. 2 ). OneOme was the most frequently used commercial laboratory (54%; 7/13) and had an estimated mean TAT of 8 days. In-house panels had the fastest estimated TAT (mean=6 days), though the maximum TAT of 10 days was similar to many of the commercial laboratories such as ARUP and Mayo Labs. Overall, 88% (21/24) of sites received results from at least one of their testing laboratories within an estimated average of 10 days or less. Interpreting, Reporting, and Storing Test Results Test interpretation and FP treatment selection are summarized in Table 4 . Test results were usually interpreted by multiple professionals, most commonly pharmacists (75%; 18/24) and medical oncologists (71%; 17/24). CDS with integrated recommendations from PGx guidelines (e.g., CPIC/DPWG) was available to assist with selecting the appropriate treatment plan (e.g., FP chemotherapy dose) at 54% (13/24) of sites, whereas 38% (9/24) of sites used pharmacy consultation. Another 38% (9/24) of sites relied on clinicians to consult PGx guidelines to determine the appropriate treatment plan. At 63% (15/24) of sites, the medical oncologist/prescriber was responsible for returning test results to patients. Additionally, most sites provided DPYD results through a patient portal connected to the electronic medical record (EMR, 71%; 17/24). Few sites (8%, 2/24) reported that they do not return results to patients. Finally, test results were stored as discrete data in a variety of locations within the EMR, including the PGx section or genomic indicators (63%; 15/24), problem list (25%; 6/24), or allergy list (8%; 2/24), whereas a minority of sites indicated that results are stored within clinical notes (4%; 1/24) or only in the lab results section (21%; 5/24). Discussion DPYD testing prior to FP treatment reduces severe toxicity and healthcare costs [12, 33]. Despite the lack of clinical guidelines recommending testing in the US, some sites have implemented pre-treatment DPYD testing programs [13, 31, 32]. To our knowledge, this is the first study to examine pre-treatment DPYD testing implementation methods at US sites that have implemented or are planning to launch implementation in the near future. These results demonstrate the feasibility of clinical implementation of DPYD testing in the US but also reveal variability in the implementation approaches and the need for best practice guidelines to facilitate implementation. Academic teaching institutions/hospitals comprised >70% of the sites that conducted pre-treatment DPYD testing. Relative to community oncology clinics, these tertiary cancer centers typically have greater access to financial and technical resources and PGx expertise [13, 31, 32]. These resources are critical to implementing robust system-wide strategies for clinical PGx adoption including interruptive alerts in the EMR [13], or integrating testing into medication order sets [13, 31, 32]. A recent study from Dana-Farber Cancer Institute reported an increase in pre-treatment DPYD testing frequency from 14% to 89% after implementing a system-wide testing program that included automated interruptive alerts at the time of initial FP chemotherapy order [31]. However, in our survey only about half of sites had built these robust ordering systems, with the rest relying on individual clinicians to remember to order testing. A 2022 survey found that most US medical oncologists lack familiarity with DPYD testing and DPYD -guided dosing guidelines from CPIC and DPWG [26]. Well-resourced sites overcome this challenge by building multidisciplinary teams with PGx expertise, especially PGx-trained pharmacists [34], who were heavily involved in each step of DPYD implementation at most of the sites in our survey. On the other hand, smaller community sites that lack pharmacists will need to rely on the PGx knowledge of their physicians and nurses [35]. Notably, Innocenti et al. have published a practitioner-friendly guide that can serve as a knowledge base for clinicians regarding DPYD testing [14]. Previous PGx implementation surveys from the Implementing GeNomics in PracTice (IGNITE) Network emphasized the potential benefits of in-house testing over a send-out to a commercial lab, including rapid TAT and control over the alleles tested [21, 22]. In our survey, >50% of respondents utilized commercial laboratories for DPYD testing, compared to ~40% using in-house testing. The widespread use of commercial labs may be partially due to improved TAT; ~90% of sites reported they received results within 10 days, which is fast enough for results to be available prior to FP treatment initiation in most patients [32]. Moreover, commercial DPYD tests have adequate allelic coverage [36, 37], with ~90% of sites using tests that include at least the 5 validated DPYD variants carried primarily by patients of European ancestry (i.e., DPYD *2A , DPYD *13 , DPYD p.D949V, DPYD HapB3, and DPYD p.Y186C) [5–7]. Other benefits of outsourcing to a commercial lab include less upfront cost and time to launch testing [38]. On the other hand, in-house testing has benefits including greater control over interpretation (e.g., using activity score or metabolic phenotype), EMR integration (e.g., ordering and results return), and inclusion of alleles of interest, such as DPYD variants carried by non-Europeans [39] to increase testing equity [24, 39–41]. At the time of our survey all sites were currently using genotyping and one site was in the planning stages of using DPYD sequencing. Since our survey, Dartmouth-Hitchcock Medical Center transitioned from genotyping to in-house DPYD sequencing to maximize allelic coverage (personal communications, Dr. Gabe Brooks, MD). All survey respondents indicated they followed CPIC/DPWG guidelines to determine appropriate DPYD genotype-informed treatment, though the operational approaches differed. Approximately half of sites incorporated guideline recommendations into CDS, whereas the remaining sites relied on PGx consultation or the clinician to consult guidelines independently, highlighting another opportunity to develop system-wide tools for implementation. In our survey >90% of respondents indicated returning DPYD test results to patients, which is much higher than frequencies reported in previous PGx surveys [21]. This likely reflects the rapid advancement in PGx implementation procedures that are enabling patients to benefit from these results in the future. For example, in the prospective PREPARE trial of pre-emptive genotyping on a 12-gene panel, 14% of patients were able to use their PGx results to inform treatment of another future medication [42]. Lack of PGx reimbursement is a commonly cited barrier to PGx implementation [13, 21, 22, 34, 43]. Nearly 1/3 of sites in our survey covered testing costs through institutional or research funds, indicating challenges with reimbursement continue despite recent progress toward expanded PGx coverage. Medicare covers DPYD testing in 40/50 states based on local coverage determinations that cover testing for all gene-drug pairs assigned CPIC level A or B [44]. An analysis of 12 major commercial payers and laboratory benefit managers from 2022 revealed that only 50% considered pre-treatment DPYD testing medically necessary, and therefore eligible for reimbursement [45]. Several limitations to this survey should be noted. First, we attempted to minimize sample bias by broadly distributing the survey; however, most of the 24 sites were academic teaching institutions/hospitals, indicating either that testing is limited in smaller clinics or that they did not receive or respond to our survey. Second, some responses were internally conflicting or lacked sufficient detail. For example, some sites reported using a commercial test but stated the wrong number of variants while others did not specify any test, or the number of variants or genes tested. We made every reasonable effort to reconcile conflicting responses, re-contact respondents, and verify responses using publicly available information, however, it is possible that our data contains errors. Finally, this survey does not address all barriers to the implementation of pre-treatment DPYD testing; for example, the costs of integrating testing within the institutional workflow. Rather, our objective was to provide an overview of current pre-treatment DPYD testing strategies in the US to identify best practices and opportunities for further research and education. In conclusion, implementation of pre-treatment DPYD testing in the US is feasible; however, robust, institution-wide systems were not always in place to maximize the efficiency or effectiveness of testing. Additional work is needed to develop best implementation practices, expand reimbursement, and enhance clinician education, all of which will aid in overcoming critical barriers to implementation. With increasing evidence and awareness of its clinical utility [12, 30], it is anticipated that the FDA and relevant professional guidelines will recommend pre-treatment DPYD testing in the near future. As such, institutions should begin to develop approaches to facilitate rapid and efficient implementation of DPYD testing to ensure patient safety and improve treatment outcomes in patients with cancer. Declarations Author contribution: All authors contributed to the study conception and design. Survey preparation was performed by D. Max Smith, Emily J. Cicali, Christina L. Aquilante, Stuart A Scott, Teresa T. Ho, Jai N. Patel J. Kevin Hicks, and Daniel L Hertz. Data collection and analysis were performed by Tabea Tracksdorf, Skyler Pearse. The first draft of the manuscript was written by Tabea Tracksdorf and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding: There was no funding supporting this work Data availability: Data are provided in the supplemental online material files. Supplementary Information: Raw and cleaned survey data Ethics approval: This survey was determined to be exempt human subjects research by the University of Michigan IRBMed (HUM00214220) Consent to participate: Survey participants supplied implied informed consent by participating in the survey. Consent to publish: Not applicable. 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Pharmacogenetics and Genomics 33:204–205. https://doi.org/10.1097/FPC.0000000000000507 Tables Table 1: Characteristics of Sites Included in Analysis (n=24) Number of Responses n (%) Role of Survey Respondent Pharmacist(s) 15 (62.5%) Medical oncologist(s) 4 (16.7%) Multiple respondents from same site 2 (8.3%) Other 2 (8.3%) Nurse/advanced practice provider 1 (4.2%) Status of Testing Implementation Implemented 21 (87.5%) Detailed plan in place for implementation 3 (12.5%) Site Type Academic teaching institution/hospital 17 (70.8%) Community hospital or outpatient cancer care 4 (16.7%) Multi-state health system 1 (4.2%) Non-academic hospital 1 (4.2%) VA hospital 1 (4.2%) Testing for Clinical or Research Purposes Clinical practice 20 (83.3%) Research study 4 (16.7%) Who Championed Pre-treatment Testing a Medical oncologist(s) 16 (66.7%) Precision medicine team 14 (58.3%) Pharmacy/pharmacist(s) 14 (58.3%) Institutional leadership/administration 5 (20.8%) Medical genetics/genetic counselor(s) 2 (8.3%) Other 2 (8.3%) a Sites could select all answers that apply so responses do not add up to 24 Table 2: Test Ordering Process (n=24) Number of Responses n (%) For Whom is Pre-treatment DPYD Testing Ordered Selected patients for whom FP chemotherapy is ordered 16 (66.7%) Every patient for whom FP chemotherapy is ordered 4 (16.7%) Every patient with all tumor types that typically receive FP 2 (8.3%) Every patient treated at the site 2 (8.3%) Who Orders Testing a Medical oncologist/prescriber 23 (95.8%) Nurse/advanced practice provider 8 (33.3%) Pharmacogenetics service/specialist 7 (29.2%) Pharmacist 5 (20.8%) Research team 2 (8.3%) Genetic counselor 1 (4.2%) How is Testing Initiated a Test ordering is included in a systematic process 13 (54.2%) Included in institutional workflow (e.g., order sets) 7 (29.2%) Automated CDS 2 (8.3%) Both CDS and included in institutional workflow 4 (16.7%) Clinician is responsible for remembering to order 11 (45.8%) Primary Source of Funding Testing is billed for insurance reimbursement 16 (66.7%) Institutional or research funds 7 (29.2%) Patient pays out of pocket 1 (4.2%) Abbreviations: CDS= Clinical Decision Support a Sites could select all answers that apply so responses do not add up to 24 Table 3: Summary of the Testing Laboratories Used and Their Characteristics (n=24) Name of Genetic Testing Laboratory Mean Turnaround Time (range) [days] a Number of DPYD Variants Tested Total Number of Genes Tested Number of Sites Using this Lab b n (%) In-house Testing 6 (3-10) N/A c N/A c 9 (37.5%) OneOme 8 (5-12) 5 27 7 (29.2%) ARUP 7 (5-10) 3 1 3 (12.5%) Mayo Labs 7 (5-10) 9 1 3 (12.5%) LabCorp 9 (7-10) 5 1 2 (8.3%) Invitae d 10 (7-12) 10 38 2 (8.3%) RPRD Diagnostics ≥14 (14-20) 22 38 2 (8.3%) CHOP 9 (7-10) 12 2 1 (4.2%) Sanford Imagenetics 10 (10-10) 3 11 1 (4.2%) Tempus ≥14 (14-21) 5 1 1 (4.2%) Abbreviations: CHOP= Children’s Hospital of Philadelphia a Time spans were included in the average by using the median days in the span (e.g., 7-10 days=8.5 days) b Sites could select all answers that apply so responses do not add up to 24 c Number of variants and genes differed between sites and not all sites provided this information. See Online Material Table 3 for details provided by each site. d Invitae has discontinued DPYD testing but information was included for completeness Table 4: Interpreting, Reporting, and Storing Test Results (n=24) Number of Responses n (%) Who Interprets Test Results a Pharmacist 18 (75.0%) Medical oncologist 17 (70.8%) Clinical decision support 15 (62.5%) Nurse/Advanced practice provider 4 (16.7%) Genetic counselor 2 (8.3%) Resources to Select Appropriate Drug Regimens a Guideline-based clinical decision support 13 (54.2%) Recommendations from pharmacy consult 9 (37.5%) Clinician consults CPIC/PharmGKB/DPWG 9 (37.5%) Recommendation from laboratory report 6 (25.0%) Who Returns Results to Patients a Medical oncologist/prescriber 15 (62.5%) Pharmacist 8 (33.3%) Nurse or advanced practice provider 6 (25.0%) Patient receives results directly (no provider involved) 6 (25.0%) Genetic counselor 2 (8.3%) Results are not returned to patients 2 (8.3%) How are Results Returned to Patients a Patient-specific portal 17 (70.8%) Verbal return of results 10 (41.7%) Physical paper copy/letter 5 (20.8%) Electronic copy 4 (16.7%) Results are not returned to patients 2 (8.3%) I don’t know/Other 1 (4.2%) How are Results Stored in the EMR? a Pharmacogenetics section or genomic indicators 15 (62.5%) Problem list 6 (25.0%) PDF upload or lab results section only 5 (20.8%) Allergy list 2 (8.3%) Clinical note 1 (4.2%) Abbreviations: CPIC= Clinical Pharmacogenetics Implementation Consortium; PharmGKB= Pharmacogenomics Knowledgebase; DPWG = Dutch Pharmacogenetics Working Group; EMR= Electronic Medical Record a Sites could select all answers that apply so responses do not add up to 24 Additional Declarations Competing interest reported. D.L.H. is an unpaid medical advisory board member for Advocates for Universal DPD/DPYD Testing (AUDT), a non-profit patient advocacy organization that advocates for expansion of DPYD testing in the USA. Supplementary Files Appendix1Survey.pdf SupplementalTables040224.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 20 Jun, 2024 Reviewers agreed at journal 12 Jun, 2024 Reviewers agreed at journal 10 Jun, 2024 Reviews received at journal 24 May, 2024 Reviewers agreed at journal 24 May, 2024 Reviewers invited by journal 07 May, 2024 Editor assigned by journal 06 May, 2024 Submission checks completed at journal 03 Apr, 2024 First submitted to journal 02 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4207186\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":301596723,\"identity\":\"ab8e4bf2-8c2a-4a1c-aad2-cf20fb49eb98\",\"order_by\":0,\"name\":\"Tabea Tracksdorf\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Michigan College of Pharmacy\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tabea\",\"middleName\":\"\",\"lastName\":\"Tracksdorf\",\"suffix\":\"\"},{\"id\":301596724,\"identity\":\"5310d681-ce56-4b99-8626-e9eae0cba8c3\",\"order_by\":1,\"name\":\"D. Max Smith\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"MedStar Health\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"D.\",\"middleName\":\"Max\",\"lastName\":\"Smith\",\"suffix\":\"\"},{\"id\":301596725,\"identity\":\"6f5f0d91-2e17-4d64-af56-c763d0d65b70\",\"order_by\":2,\"name\":\"Skyler Pearse\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Michigan College of Pharmacy\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Skyler\",\"middleName\":\"\",\"lastName\":\"Pearse\",\"suffix\":\"\"},{\"id\":301596726,\"identity\":\"df4a6f51-6a12-4c16-b673-bcb2e957dbda\",\"order_by\":3,\"name\":\"Emily J Cicali\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Florida\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Emily\",\"middleName\":\"J\",\"lastName\":\"Cicali\",\"suffix\":\"\"},{\"id\":301596727,\"identity\":\"b94487b4-bdff-4a24-997a-e03b65db851a\",\"order_by\":4,\"name\":\"Christina L Aquilante\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Colorado Anschutz Medical Campus\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Christina\",\"middleName\":\"L\",\"lastName\":\"Aquilante\",\"suffix\":\"\"},{\"id\":301596728,\"identity\":\"521fba19-38c0-4f17-b73b-bca3d3e9240a\",\"order_by\":5,\"name\":\"Stuart A. Scott\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Florida\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Stuart\",\"middleName\":\"A.\",\"lastName\":\"Scott\",\"suffix\":\"\"},{\"id\":301596729,\"identity\":\"bbdac4bc-daab-472b-9814-04c3bd0085dc\",\"order_by\":6,\"name\":\"Teresa T Ho\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Moffitt Cancer Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Teresa\",\"middleName\":\"T\",\"lastName\":\"Ho\",\"suffix\":\"\"},{\"id\":301596730,\"identity\":\"c6197240-56a8-40f1-8929-80aba8d4829a\",\"order_by\":7,\"name\":\"Jai N Patel\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Atrium Health Levine Cancer Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jai\",\"middleName\":\"N\",\"lastName\":\"Patel\",\"suffix\":\"\"},{\"id\":301596731,\"identity\":\"07b2bf79-28ae-43bf-931c-27c482db6d60\",\"order_by\":8,\"name\":\"J. Kevin Hicks\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Moffitt Cancer Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"J.\",\"middleName\":\"Kevin\",\"lastName\":\"Hicks\",\"suffix\":\"\"},{\"id\":301596732,\"identity\":\"b5ccced0-a628-459e-a665-5bd3465918bb\",\"order_by\":9,\"name\":\"Daniel L Hertz\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYBACewkeAxAtB8QghgSUxAMMZ4C0JDAYE6/F4AZES2IDRAsDUVoMH1f+qEtf2968gZk3x0LenIH54G0evFr4PxueSWDL3XbmWAEz7zYJw50NbMnW+LXwmEk2JPDkbruRYwDSkmBwgMdMmoAW858NCRLpZvffwLTwfyOkxYyxIcEgwQwYDjBb2PBqAQaysWRDWoLhtjNpBQfnAv2y4TCbseUcPFrs5c8YfmywqZM3O35444O32+rkDY43P7zxBo8WFHAATDITq3wUjIJRMApGAU4AALuhSIiCdV+dAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"University of Michigan College of Pharmacy\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Daniel\",\"middleName\":\"L\",\"lastName\":\"Hertz\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-02 13:53:55\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4207186/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4207186/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":56478933,\"identity\":\"c5d24f1c-f314-4858-ace1-973ab7d50a0a\",\"added_by\":\"auto\",\"created_at\":\"2024-05-14 17:57:45\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":42532,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eConsort diagram describing filtering from 134 initiated survey responses to the 24 unique sites included in the analysis\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4207186/v1/22eff470dc52d3b5d9a8cfd9.jpg\"},{\"id\":56478932,\"identity\":\"f214e20e-95d9-40c7-9920-81abe9227a67\",\"added_by\":\"auto\",\"created_at\":\"2024-05-14 17:57:45\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":39595,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTesting Panels used for Pre-treatment DPYD Testing.\\u003cem\\u003e \\u003c/em\\u003e\\u003cstrong\\u003eFig. 2\\u003c/strong\\u003eLeft: the number of \\u003cem\\u003eDPYD\\u003c/em\\u003e variants tested at each site. Of the sites that reported the number of variants tested, most (19/22; 86.4%) tested for at least the 4-5 \\u003cem\\u003eDPYD\\u003c/em\\u003e variants considered validated for clinical actionability \\u003cem\\u003e(DPYD\\u003c/em\\u003e*2A\\u003cem\\u003e, DPYD\\u003c/em\\u003e*13\\u003cem\\u003e, DPYD \\u003c/em\\u003ep.D949V\\u003cem\\u003e, DPYD \\u003c/em\\u003eHapB3\\u003cem\\u003e, and DPYD \\u003c/em\\u003ep.Y186C\\u003cem\\u003e). \\u003c/em\\u003e\\u003cstrong\\u003eFig. 2\\u003c/strong\\u003e Right: whether sites tested on a multi-gene panel (16/24; 66.7%) or only for \\u003cem\\u003eDPYD\\u003c/em\\u003e (8/24; 33.3%).\\u003c/p\\u003e\\n\\u003cp\\u003eNote: n=24; If sites used multiple laboratories, only the laboratory testing for the highest number of genes was included in the analysis\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4207186/v1/879e6b8417a400ca038ff1ec.jpg\"},{\"id\":56479619,\"identity\":\"962aa903-7cb7-4d51-aa28-e953e0577191\",\"added_by\":\"auto\",\"created_at\":\"2024-05-14 18:05:45\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":794684,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4207186/v1/9b4ab455-ac1a-4471-b918-e83ae00262de.pdf\"},{\"id\":56478935,\"identity\":\"cfeea191-f1f2-421e-96be-3a5b1f6ddf4d\",\"added_by\":\"auto\",\"created_at\":\"2024-05-14 17:57:45\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":183211,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Appendix1Survey.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4207186/v1/3e8495bc3c28c0f43eb57297.pdf\"},{\"id\":56478936,\"identity\":\"2aa89b90-3dc4-49f3-a9fa-87ddfde9445c\",\"added_by\":\"auto\",\"created_at\":\"2024-05-14 17:57:45\",\"extension\":\"xlsx\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":38347,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementalTables040224.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4207186/v1/b326aa8395484c9550da4bda.xlsx\"}],\"financialInterests\":\"Competing interest reported. D.L.H. is an unpaid medical advisory board member for Advocates for Universal DPD/DPYD Testing (AUDT), a non-profit patient advocacy organization that advocates for expansion of DPYD testing in the USA.\",\"formattedTitle\":\"Strategies for DPYD Testing Prior to Fluoropyrimidine Chemotherapy in the United States\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eFluoropyrimidines (FP), including intravenous 5-fluorouracil and its oral prodrug capecitabine, have been used for over 60 years as a treatment for cancer [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. An estimated 2\\u0026nbsp;million patients worldwide receive these antimetabolite drugs annually to treat a variety of solid tumors such as colorectal, pancreatic, breast, and head and neck cancers [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. About 30% of patients develop severe FP-associated toxicity, including diarrhea, hand-foot syndrome, mucositis, and myelosuppression, which can be fatal for ~\\u0026thinsp;0.1% of patients [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOver 80% of systemically available FP is catabolized by the dihydropyrimidine dehydrogenase (DPD) enzyme [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. Germline mutations in \\u003cem\\u003eDPYD\\u003c/em\\u003e, the gene encoding DPD, lead to diminished or null DPD activity, resulting in the systemic accumulation of FP and increased risk of severe adverse reactions [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. More than 160 recurrent allelic variants in \\u003cem\\u003eDPYD\\u003c/em\\u003e have been identified, including five (\\u003cem\\u003eDPYD\\u003c/em\\u003e*2A (rs3918290), \\u003cem\\u003eDPYD\\u003c/em\\u003e*13 (rs55886062), \\u003cem\\u003eDPYD\\u003c/em\\u003e p.D949V (rs67376798), \\u003cem\\u003eDPYD\\u003c/em\\u003e HapB3 (rs56038477), and \\u003cem\\u003eDPYD\\u003c/em\\u003e p.Y186C (rs115232898)) that have been reproducibly associated with an increased FP toxicity risk [\\u003cspan additionalcitationids=\\\"CR6\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. Approximately 6% of the United States (US) population carries one of these germline \\u003cem\\u003eDPYD\\u003c/em\\u003e variants [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eDPD enzyme activity may be determined using either genotypic or phenotypic methods, allowing individualization of FP dosing to mitigate the occurrence of treatment-related toxicity [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. While phenotypic testing is standard of care in some European countries (e.g., France) [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e], it is not readily available in the US, and its reliability has been called into question [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Thus, genotyping is the prevalent method of testing in the US. FP dosing recommendations for patients with known \\u003cem\\u003eDPYD\\u003c/em\\u003e genotypes are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Importantly, several prospective studies have demonstrated that pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing and genotype-guided dosing decrease treatment-related toxicity, are cost-effective, and are feasible in routine clinical practice [\\u003cspan additionalcitationids=\\\"CR12 CR13\\\" citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. Accordingly, various countries, including England, Switzerland, Austria, and Germany, have adopted routine testing for DPD deficiency prior to FP treatment [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. A survey conducted in Europe found that the number of \\u003cem\\u003eDPYD\\u003c/em\\u003e genotyping tests doubled from 2019 to 2021 [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], primarily due to the European Medicine Agency (EMA) recommendation for pre-treatment DPD testing in 2020 [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e] and consistent testing reimbursement [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003ePharmacogenetic (PGx) testing to optimize treatment is rapidly expanding within the US [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] across a number of therapeutic areas and drugs [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]; however, \\u003cem\\u003eDPYD\\u003c/em\\u003e testing prior to FP treatment is not currently recommended by any US-based clinical oncology guidelines or the FDA [\\u003cspan additionalcitationids=\\\"CR24\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. According to a 2017 survey, only 20% of US medical oncologists had ever ordered pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing, despite 98% agreeing that patients with DPD deficiency have increased FP toxicity risk [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. According to the survey and other qualitative studies, US-based medical oncologists refrain from \\u003cem\\u003eDPYD\\u003c/em\\u003e testing due in part to the lack of clinical practice guideline recommendations and limited knowledge of testing options and interpretation [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. Consequently, \\u003cem\\u003eDPYD\\u003c/em\\u003e variants are often identified only after severe FP toxicity through reactive testing [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. However, recent publications have raised awareness of the clinical benefit of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], including evidence that dose reduction in \\u003cem\\u003eDPYD\\u003c/em\\u003e variant carriers does not reduce treatment efficacy [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e], leading to an increase in implementation of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. The objective of this survey is to summarize current approaches to the implementation of \\u003cem\\u003eDPYD\\u003c/em\\u003e testing prior to FP treatment in the US to inform best practices for broader clinical adoption.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003ch2\\u003eSurvey Development\\u003c/h2\\u003e\\n\\u003cp\\u003eThis 22-item survey was developed by a multidisciplinary team of medical professionals and experts in PGx. It was modeled after previously conducted surveys of PGx implementation programs\\u0026nbsp;[21, 22]\\u0026nbsp;and adapted based on internal expertise to better understand the landscape of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing implementation strategies across the US. The survey included multiple-choice and free-response questions to assess each site\\u0026rsquo;s \\u003cem\\u003eDPYD\\u003c/em\\u003e testing program, including general site information (e.g., site type, clinical or research testing) (n=10 questions), test ordering (n=7), and interpreting, reporting, and storing of test results (n=5) (Survey Included as \\u003cstrong\\u003eOnline Material Appendix 1\\u003c/strong\\u003e).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003eRecruitment of Respondents\\u003c/h2\\u003e\\n\\u003cp\\u003eThe survey was created within the web-based survey software Qualtrics\\u003csup\\u003eXM\\u003c/sup\\u003e and distributed between August and October 2023. Individuals at sites known by the coauthors to conduct pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing were contacted directly, and the survey was also broadly distributed through relevant organizations (e.g., Pharmacogenomics Global Research Network (PGRN), Multinational Association of Supportive Care in Cancer (MASCC), CPIC), and social networks (e.g., LinkedIn). Additionally, survey participants were asked to provide contact information for other sites that conduct pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing and asked to forward the survey to individuals at those sites directly. The survey was approved as exempt from human subjects research by the University of Michigan IRBMED and survey respondents provided implied informed consent to participate by completing the non-anonymized survey.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003eData analysis\\u003c/h2\\u003e\\n\\u003cp\\u003eSurvey responses from a site were eligible for inclusion if the survey was completed, the site was located within the US, and the site had implemented pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing or could provide a sufficiently detailed implementation plan. \\u0026nbsp;After filtering the raw data for eligibility (See \\u003cstrong\\u003eOnline Material Table 1\\u003c/strong\\u003e), multiple responses from the same site were reconciled to enable a site-level analysis (See \\u003cstrong\\u003eOnline Material Table\\u0026nbsp;2\\u003c/strong\\u003e). Survey responses were reviewed to correct contradictory data or fill in missing information by asking respondents for clarification and/or searching for information online. For example, in some cases the number of genes and variants that sites indicated were tested by a commercial testing company did not match the information from those companies; in this event, we used the information from the testing companies. Additionally, responses to some questions were grouped to enhance understanding of the results in this manuscript (See\\u0026nbsp;\\u003cstrong\\u003eOnline Material Table 3\\u003c/strong\\u003e). Responses were analyzed using descriptive analysis.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003ch2\\u003eCharacteristics of the Sites Included in the Analysis\\u003c/h2\\u003e\\n\\u003cp\\u003eOf the 134 survey responses that were initiated, 64 surveys were completed, including responses from 24 unique sites within the US that had implemented testing (n=21, 88%) or could provide a sufficiently detailed implementation plan (n=3, 13%) to be included in the analysis (\\u003cstrong\\u003eFig. 1\\u003c/strong\\u003e). Excluding three sites that did not complete the survey in a single attempt, all sites finished the survey in under 30\\u0026nbsp;minutes.\\u003c/p\\u003e\\n\\u003cp\\u003eCharacteristics of the respondents and 24 sites are summarized in \\u003cstrong\\u003eTable 1\\u003c/strong\\u003e. Pharmacists submitted survey responses for 63% (15/24) of these sites. Most sites (71%; 17/24) were academic teaching institutions/hospitals, and 83% (20/24) utilized testing primarily for clinical practice. Pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing was most often championed by multiple professionals, including medical oncologists (67%; 16/24), precision medicine teams (58%; 14/24), and pharmacists (58%; 14/24).\\u003c/p\\u003e\\n\\u003ch2\\u003eTest Ordering Process\\u003c/h2\\u003e\\n\\u003cp\\u003eThe process for ordering and paying for testing is summarized in \\u003cstrong\\u003eTable 2\\u003c/strong\\u003e. While 33% of sites (8/24) reported testing all FP-treated patients using different patient selection approaches, the majority (67%; 16/24) indicated testing only selected patients who are prescribed FP chemotherapy. Criteria for selecting patients for testing included disease characteristics (e.g., type of cancer) and clinician preference (e.g., the clinician’s familiarity with pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing) (\\u003cstrong\\u003eOnline Material Table 3\\u003c/strong\\u003e). Medical oncologists/prescribers ordered testing at nearly every site (96%; 23/24), with many sites indicating that multiple clinicians participated in the ordering process, including nurses (33%; 8/24) and a PGx service (29%; 7/24). Additionally, approximately half of the sites reported having some type of systematized ordering process, such as order sets or clinical decision support (CDS, 54%; 13/24), whereas the other half of sites relied on clinicians to remember to order testing (46%; 11/24).\\u0026nbsp;To cover the cost of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing, 67% (16/24) of sites reported billing for insurance reimbursement, while 29% (7/24) indicated that tests were covered by institutional or research funds. One site reported that patients pay out of pocket.\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cem\\u003eDPYD\\u003c/em\\u003e Testing\\u003c/h2\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3\\u003c/strong\\u003e compares the turnaround time (TAT), number of \\u003cem\\u003eDPYD\\u003c/em\\u003e variants, and number of genes included on the testing panels used by survey respondents.\\u0026nbsp;\\u003cem\\u003eDPYD\\u003c/em\\u003e testing was conducted by commercial laboratories at 54% (13/24) of sites, with others using their own in-house testing (38%; 9/24) or another institution’s laboratory (8%; 2/24). Most sites (67%; 16/24) utilized at least one laboratory offering a multi-gene panel, and the vast majority included at least the 4 to 5 \\u003cem\\u003eDPYD\\u003c/em\\u003e variants considered validated for clinical actionability (\\u003cem\\u003eDPYD\\u003c/em\\u003e*2A\\u003cem\\u003e, DPYD\\u003c/em\\u003e*13\\u003cem\\u003e, DPYD\\u0026nbsp;\\u003c/em\\u003ep.D949V, \\u003cem\\u003eDPYD\\u003c/em\\u003e HapB3, and \\u003cem\\u003eDPYD\\u003c/em\\u003e p.Y186C) (86%;19/22, \\u003cstrong\\u003eFig. 2\\u003c/strong\\u003e). OneOme was the most frequently used commercial laboratory (54%; 7/13) and had an estimated mean TAT of 8 days. In-house panels had the fastest estimated TAT (mean=6 days), though the maximum TAT of 10 days was similar to many of the commercial laboratories such as ARUP and Mayo Labs. Overall, 88% (21/24) of sites received results from at least one of their testing laboratories within an estimated average of 10 days or less.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003eInterpreting, Reporting, and Storing Test Results\\u003c/h2\\u003e\\n\\u003cp\\u003eTest interpretation and FP treatment selection are summarized in \\u003cstrong\\u003eTable 4\\u003c/strong\\u003e. Test results were usually interpreted by multiple professionals, most commonly pharmacists (75%; 18/24) and medical oncologists (71%; 17/24). CDS with integrated recommendations from PGx guidelines (e.g., CPIC/DPWG) was available to assist with selecting the appropriate treatment plan (e.g., FP chemotherapy dose) at 54% (13/24) of sites, whereas 38% (9/24) of sites used pharmacy consultation. Another 38% (9/24) of sites relied on clinicians to consult PGx guidelines to determine the appropriate treatment plan. At 63% (15/24) of sites, the medical oncologist/prescriber was responsible for returning test results to patients. Additionally, most sites provided \\u003cem\\u003eDPYD\\u003c/em\\u003e results through a patient portal connected to the electronic medical record (EMR, 71%; 17/24). Few sites (8%, 2/24) reported that they do not return results to patients. Finally, test results were stored as discrete data in a variety of locations within the EMR, including the PGx section or genomic indicators (63%; 15/24), problem list (25%; 6/24), or allergy list (8%; 2/24), whereas a minority of sites indicated that results are stored within clinical notes (4%; 1/24) or only in the lab results section (21%; 5/24).\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eDPYD\\u003c/em\\u003e testing prior to FP treatment reduces severe toxicity and healthcare costs\\u0026nbsp;[12, 33]. Despite the lack of clinical guidelines recommending testing in the US, some sites have implemented pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing programs\\u0026nbsp;[13, 31, 32]. To our knowledge, this is the first study to examine pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing implementation methods at US sites that have implemented or are planning to launch implementation in the near future. These results demonstrate the feasibility of clinical implementation of \\u003cem\\u003eDPYD\\u003c/em\\u003e testing in the US but also reveal variability in the implementation approaches and the need for best practice guidelines to facilitate implementation.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAcademic teaching institutions/hospitals comprised \\u0026gt;70% of the sites that conducted pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing. Relative to community oncology clinics, these tertiary cancer centers typically have greater access to financial and technical resources and PGx expertise\\u0026nbsp;[13, 31, 32]. These resources are critical to implementing robust system-wide strategies for clinical PGx adoption including interruptive alerts in the EMR\\u0026nbsp;[13], or integrating testing into medication order sets\\u0026nbsp;[13, 31, 32]. A recent study from Dana-Farber Cancer Institute reported an increase in pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing frequency from 14% to 89% after implementing a system-wide testing program that included automated interruptive alerts at the time of initial FP chemotherapy order\\u0026nbsp;[31]. However, in our survey only about half of sites had built these robust ordering systems, with the rest relying on individual clinicians to remember to order testing. A 2022 survey found that most US medical oncologists lack familiarity with \\u003cem\\u003eDPYD\\u003c/em\\u003e testing and \\u003cem\\u003eDPYD\\u003c/em\\u003e-guided dosing guidelines from CPIC and DPWG\\u0026nbsp;[26]. Well-resourced sites overcome this challenge by building multidisciplinary teams with PGx expertise, especially PGx-trained pharmacists\\u0026nbsp;[34], who were heavily involved in each step of \\u003cem\\u003eDPYD\\u003c/em\\u003e implementation at most of the sites in our survey. On the other hand, smaller community sites that lack pharmacists will need to rely on the PGx knowledge of their physicians and nurses\\u0026nbsp;[35]. Notably, Innocenti \\u003cem\\u003eet al.\\u003c/em\\u003e have published a practitioner-friendly guide that can serve as a knowledge base for clinicians regarding \\u003cem\\u003eDPYD\\u003c/em\\u003e testing\\u0026nbsp;[14].\\u003c/p\\u003e\\n\\u003cp\\u003ePrevious PGx implementation surveys from the Implementing GeNomics in PracTice (IGNITE) Network emphasized the potential benefits of in-house testing over a send-out to a commercial lab, including rapid TAT and control over the alleles tested\\u0026nbsp;[21, 22]. In our survey, \\u0026gt;50% of respondents utilized commercial laboratories for \\u003cem\\u003eDPYD\\u003c/em\\u003e testing, compared to ~40% using in-house testing. The widespread use of commercial labs may be partially due to improved TAT; ~90% of sites reported they received results within 10 days, which is fast enough for results to be available prior to FP treatment initiation in most patients\\u0026nbsp;[32]. Moreover, commercial \\u003cem\\u003eDPYD\\u003c/em\\u003e tests have adequate allelic coverage\\u0026nbsp;[36, 37], with\\u0026nbsp;~90% of sites using tests that include at least the 5 validated \\u003cem\\u003eDPYD\\u003c/em\\u003e variants carried primarily by patients of European ancestry (i.e.,\\u0026nbsp;\\u003cem\\u003eDPYD\\u003c/em\\u003e*2A\\u003cem\\u003e, DPYD\\u003c/em\\u003e*13\\u003cem\\u003e, DPYD\\u0026nbsp;\\u003c/em\\u003ep.D949V, \\u003cem\\u003eDPYD\\u0026nbsp;\\u003c/em\\u003eHapB3, and \\u003cem\\u003eDPYD\\u003c/em\\u003e p.Y186C)\\u0026nbsp;[5\\u0026ndash;7]. Other benefits of outsourcing to a commercial lab include less\\u0026nbsp;upfront cost and time to launch testing\\u0026nbsp;[38]. On the other hand, in-house testing has benefits including greater control over interpretation (e.g., using activity score or metabolic phenotype), EMR integration (e.g., ordering and results return), and inclusion of alleles of interest, such as \\u003cem\\u003eDPYD\\u003c/em\\u003e variants carried\\u0026nbsp;by non-Europeans\\u0026nbsp;[39]\\u0026nbsp;to increase testing equity\\u0026nbsp;[24, 39\\u0026ndash;41]. At the time of our survey all sites were currently using genotyping and one site was in the planning stages of using \\u003cem\\u003eDPYD\\u003c/em\\u003e sequencing. Since our survey, Dartmouth-Hitchcock Medical Center transitioned from genotyping to in-house \\u003cem\\u003eDPYD\\u003c/em\\u003e sequencing to maximize allelic coverage (personal communications, Dr. Gabe Brooks, MD).\\u003c/p\\u003e\\n\\u003cp\\u003eAll survey respondents indicated they followed CPIC/DPWG guidelines to determine appropriate \\u003cem\\u003eDPYD\\u0026nbsp;\\u003c/em\\u003egenotype-informed treatment, though the operational approaches differed. Approximately half of sites incorporated guideline recommendations into CDS, whereas the remaining sites relied on PGx consultation or the clinician to consult guidelines independently, highlighting another opportunity to develop system-wide tools for implementation. In our survey \\u0026gt;90% of respondents indicated returning \\u003cem\\u003eDPYD\\u003c/em\\u003e test results to patients, which is much higher than frequencies reported in previous PGx surveys\\u0026nbsp;[21]. This likely reflects the rapid advancement in PGx implementation procedures that are enabling patients to benefit from these results in the future. For example, in the prospective PREPARE trial of pre-emptive genotyping on a 12-gene panel, 14% of patients were able to use their PGx results to inform treatment of another future medication\\u0026nbsp;[42].\\u003c/p\\u003e\\n\\u003cp\\u003eLack of PGx reimbursement is a commonly cited barrier to PGx implementation\\u0026nbsp;[13, 21, 22, 34, 43]. Nearly 1/3 of sites in our survey covered testing costs through institutional or research funds, indicating challenges with reimbursement continue despite recent progress toward expanded PGx coverage. Medicare covers \\u003cem\\u003eDPYD\\u003c/em\\u003e testing in 40/50 states based on local coverage determinations that cover testing for all gene-drug pairs assigned CPIC level A or B\\u0026nbsp;[44]. An analysis of 12 major commercial payers and laboratory benefit managers from 2022 revealed that only 50% considered pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing medically necessary, and therefore eligible for reimbursement\\u0026nbsp;[45].\\u003c/p\\u003e\\n\\u003cp\\u003eSeveral limitations to this survey should be noted. First, we attempted to minimize sample bias by broadly distributing the survey; however, most of the 24 sites were academic teaching institutions/hospitals, indicating either\\u0026nbsp;that testing is limited in smaller clinics or that they did not receive or respond to our survey. Second, some responses were internally conflicting or lacked sufficient detail. For example, some sites reported using a commercial test but stated the wrong number of variants while others did not specify any test, or the number of variants or genes tested.\\u0026nbsp;We made every reasonable effort to reconcile conflicting responses, re-contact respondents, and verify responses using publicly available information, however, it is possible that our data contains errors. Finally, this survey does not address all barriers to the implementation of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing; for example, the\\u0026nbsp;costs of integrating testing within the institutional workflow. Rather, our objective was to provide an overview of current pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing strategies in the US to\\u0026nbsp;identify best practices and opportunities for further research and education.\\u003c/p\\u003e\\n\\u003cp\\u003eIn conclusion,\\u0026nbsp;implementation of pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing in the US is feasible; however, robust, institution-wide systems were not always in place to maximize the efficiency or effectiveness of testing. Additional work is needed to develop best implementation practices, expand reimbursement, and enhance clinician education, all of which will aid in overcoming critical barriers to implementation. With increasing\\u0026nbsp;evidence and awareness of its clinical utility\\u0026nbsp;[12, 30], it is anticipated that the FDA and relevant professional guidelines will recommend pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing in the near future. As such, institutions should begin to develop approaches to facilitate rapid and efficient implementation of \\u003cem\\u003eDPYD\\u003c/em\\u003e testing to ensure patient safety and improve treatment outcomes in patients with cancer.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cu\\u003eAuthor contribution:\\u003c/u\\u003e All authors contributed to the study conception and design. Survey preparation was performed by D. Max Smith, Emily J. Cicali, Christina L. Aquilante, Stuart A Scott, Teresa T. Ho, Jai N. Patel J. Kevin Hicks, and Daniel L Hertz. Data collection and analysis were performed by Tabea Tracksdorf, Skyler Pearse. The first draft of the manuscript was written by Tabea Tracksdorf and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding:\\u0026nbsp;There was no funding supporting this work\\u003c/p\\u003e\\n\\u003cp\\u003eData availability:\\u0026nbsp;Data are provided in the supplemental online material files.\\u003c/p\\u003e\\n\\u003cp\\u003eSupplementary Information:\\u0026nbsp;Raw and cleaned survey data\\u003c/p\\u003e\\n\\u003cp\\u003eEthics approval:\\u0026nbsp;This survey was determined to be exempt human subjects research by the University of Michigan IRBMed (HUM00214220)\\u003c/p\\u003e\\n\\u003cp\\u003eConsent to participate:\\u0026nbsp;Survey participants supplied implied informed consent by participating in the survey.\\u003c/p\\u003e\\n\\u003cp\\u003eConsent to publish:\\u0026nbsp;Not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting Interests: D.L.H. is an unpaid medical advisory board member for Advocates for Universal DPD/DPYD Testing (AUDT), a non-profit patient advocacy organization that advocates for expansion of DPYD testing in the USA. \\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eDeac A-L, Burz CC, Bocșe HF, et al (2020) A systematic review on the importance of genotyping and phenotyping in fluoropyrimidine treatment. Medicine and Pharmacy Reports 93:223\\u0026ndash;230. https://doi.org/10.15386/mpr-1564\\u003c/li\\u003e\\n\\u003cli\\u003eSpectrum Pharmaceuticals (2016) Fluorouracil [package insert]\\u003c/li\\u003e\\n\\u003cli\\u003eLunenburg CATC, Henricks LM, Guchelaar H-J, et al (2016) Prospective DPYD genotyping to reduce the risk of fluoropyrimidine-induced severe toxicity: Ready for prime time. European Journal of Cancer 54:40\\u0026ndash;48. https://doi.org/10.1016/j.ejca.2015.11.008\\u003c/li\\u003e\\n\\u003cli\\u003eSharma BB, Rai K, Blunt H, et al (2021) Pathogenic DPYD Variants and Treatment‐Related Mortality in Patients Receiving Fluoropyrimidine Chemotherapy: A Systematic Review and Meta‐Analysis. Oncologist 26:1008\\u0026ndash;1016. https://doi.org/10.1002/onco.13967\\u003c/li\\u003e\\n\\u003cli\\u003eLunenburg CATC, van der Wouden CH, Nijenhuis M, et al (2020) Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene\\u0026ndash;drug interaction of DPYD and fluoropyrimidines. Eur J Hum Genet 28:508\\u0026ndash;517. https://doi.org/10.1038/s41431-019-0540-0\\u003c/li\\u003e\\n\\u003cli\\u003eAmstutz U, Henricks LM, Offer SM, et al (2018) Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Dihydropyrimidine Dehydrogenase Genotype and Fluoropyrimidine Dosing: 2017 Update. Clin Pharmacol Ther 103:210\\u0026ndash;216. https://doi.org/10.1002/cpt.911\\u003c/li\\u003e\\n\\u003cli\\u003eOffer SM, Lee AM, Mattison LK, et al (2013) A DPYD variant (Y186C) in individuals of African ancestry associated with reduced DPD enzyme activity. Clin Pharmacol Ther 94:158\\u0026ndash;166. https://doi.org/10.1038/clpt.2013.69\\u003c/li\\u003e\\n\\u003cli\\u003eHertz DL (2023) Reply to H.S. Hochster. JCO 41:2120\\u0026ndash;2121. https://doi.org/10.1200/JCO.23.00038\\u003c/li\\u003e\\n\\u003cli\\u003eHaute Autorit\\u0026eacute; de Sant\\u0026eacute; (2018) Screening for dihydropyrimidine dehydrogenase deficiency to decrease the risk of severe toxicities related to fluoropyrimidines (5-fluorouracil or capecitabine) - INAHTA Brief. https://www.has-sante.fr/jcms/c_2891090/en/screening-for-dihydropyrimidine-dehydrogenase-deficiency-to-decrease-the-risk-of-severe-toxicities-related-to-fluoropyrimidines-5-fluorouracil-or-capecitabine-inahta-brief. Accessed 7 Mar 2024\\u003c/li\\u003e\\n\\u003cli\\u003ede With M, Knikman J, de Man FM, et al (2022) Dihydropyrimidine Dehydrogenase Phenotyping Using Pretreatment Uracil: A Note of Caution Based on a Large Prospective Clinical Study. Clin Pharmacol Ther 112:62\\u0026ndash;68. https://doi.org/10.1002/cpt.2608\\u003c/li\\u003e\\n\\u003cli\\u003eHenricks LM, Lunenburg CATC, de Man FM, et al (2018) DPYD genotype-guided dose individualisation of fluoropyrimidine therapy in patients with cancer: a prospective safety analysis. The Lancet Oncology 19:1459\\u0026ndash;1467. https://doi.org/10.1016/S1470-2045(18)30686-7\\u003c/li\\u003e\\n\\u003cli\\u003eBrooks GA, Tapp S, Daly AT, et al (2022) Cost-effectiveness of DPYD genotyping prior to fluoropyrimidine-based adjuvant chemotherapy for colon cancer. Clin Colorectal Cancer 21:e189\\u0026ndash;e195. https://doi.org/10.1016/j.clcc.2022.05.001\\u003c/li\\u003e\\n\\u003cli\\u003eMorris SA, Moore DC, Musselwhite LW, et al (2023) Addressing barriers to increased adoption of DPYD genotyping at a large multisite cancer center. Am J Health Syst Pharm 80:1342\\u0026ndash;1349. https://doi.org/10.1093/ajhp/zxad117\\u003c/li\\u003e\\n\\u003cli\\u003eInnocenti F, Mills SC, Sanoff H, et al (2020) All You Need to Know About DPYD Genetic Testing for Patients Treated With Fluorouracil and Capecitabine: A Practitioner-Friendly Guide. JCO Oncology Practice 16:793\\u0026ndash;798. https://doi.org/10.1200/OP.20.00553\\u003c/li\\u003e\\n\\u003cli\\u003eNHS England (2020) Clinical Commissioning Urgent Policy Statement: Pharmacogenomic testing for DPYD polymorphisms with fluoropyrimidine therapies. https://www.england.nhs.uk/wp-content/uploads/2020/11/1869-dpyd-policy-statement.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eW\\u0026ouml;rmann B, Bokemeyer C, Burmeister T, et al (2020) Dihydropyrimidine Dehydrogenase Testing prior to Treatment with 5-Fluorouracil, Capecitabine, and Tegafur: A Consensus Paper. Oncology Research and Treatment 43:628\\u0026ndash;636. https://doi.org/10.1159/000510258\\u003c/li\\u003e\\n\\u003cli\\u003ede With M, Sadlon A, Cecchin E, et al (2023) Implementation of dihydropyrimidine dehydrogenase deficiency testing in Europe. ESMO Open 8:. https://doi.org/10.1016/j.esmoop.2023.101197\\u003c/li\\u003e\\n\\u003cli\\u003eEuropean Medicines Agency (2020) New testing and treatment recommendations for fluorouracil, capecitabine, tegafur and flucytosine. https://www.ema.europa.eu/en/documents/referral/fluorouracil-fluorouracil-related-substances-article-31-referral-new-testing-treatment_en.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eHalbisen AL, Lu CY (2023) Trends in Availability of Genetic Tests in the United States, 2012\\u0026ndash;2022. J Pers Med 13:638. https://doi.org/10.3390/jpm13040638\\u003c/li\\u003e\\n\\u003cli\\u003eAnderson HD, Crooks KR, Kao DP, Aquilante CL (2020) The landscape of pharmacogenetic testing in a US managed care population. Genetics in Medicine 22:1247\\u0026ndash;1253. https://doi.org/10.1038/s41436-020-0788-3\\u003c/li\\u003e\\n\\u003cli\\u003eEmpey PE, Stevenson JM, Tuteja S, et al (2018) Multi-site investigation of strategies for the implementation of CYP2C19 genotype-guided antiplatelet therapy. Clin Pharmacol Ther 104:664\\u0026ndash;674. https://doi.org/10.1002/cpt.1006\\u003c/li\\u003e\\n\\u003cli\\u003eCavallari LH, Driest SLV, Prows CA, et al (2019) Multi-site investigation of strategies for the clinical implementation of CYP2D6 genotyping to guide drug prescribing. Genetics in Medicine 21:2255\\u0026ndash;2263. https://doi.org/10.1038/s41436-019-0484-3\\u003c/li\\u003e\\n\\u003cli\\u003eVarughese LA, Lau-Min KS, Cambareri C, et al (2020) DPYD and UGT1A1 Pharmacogenetic Testing in Patients with Gastrointestinal Malignancies: An Overview of the Evidence and Considerations for Clinical Implementation. Pharmacotherapy 40:1108\\u0026ndash;1129. https://doi.org/10.1002/phar.2463\\u003c/li\\u003e\\n\\u003cli\\u003eHertz DL, Smith DM, Scott SA, et al (2023) Response to the FDA Decision Regarding DPYD Testing Prior to Fluoropyrimidine Chemotherapy. Clinical Pharmacology \\u0026amp; Therapeutics 114:768\\u0026ndash;779. https://doi.org/10.1002/cpt.2978\\u003c/li\\u003e\\n\\u003cli\\u003eBenson et al. (2024) Colon Cancer, Version 1.2024, NCCN Clinical Practice Guidelines in Oncology. https://www.nccn.org/professionals/physician_gls/pdf/colon.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eKoo K, Pasternak AL, Henry NL, et al (2022) Survey of US Medical Oncologists\\u0026rsquo; Practices and Beliefs Regarding DPYD Testing Before Fluoropyrimidine Chemotherapy. JCO Oncology Practice 18:e958\\u0026ndash;e965. https://doi.org/10.1200/OP.21.00874\\u003c/li\\u003e\\n\\u003cli\\u003eLau-Min KS, Varughese LA, Nelson MN, et al (2022) Preemptive pharmacogenetic testing to guide chemotherapy dosing in patients with gastrointestinal malignancies: a qualitative study of barriers to implementation. BMC Cancer 22:47. https://doi.org/10.1186/s12885-022-09171-6\\u003c/li\\u003e\\n\\u003cli\\u003eBaker SD, Bates SE, Brooks GA, et al (2023) DPYD Testing: Time to Put Patient Safety First. JCO 41:2701\\u0026ndash;2705. https://doi.org/10.1200/JCO.22.02364\\u003c/li\\u003e\\n\\u003cli\\u003eHertz DL (2022) Assessment of the Clinical Utility of Pretreatment DPYD Testing for Patients Receiving Fluoropyrimidine Chemotherapy. JCO 40:3882\\u0026ndash;3892. https://doi.org/10.1200/JCO.22.00037\\u003c/li\\u003e\\n\\u003cli\\u003eKnikman JE, Wilting TA, Lopez-Yurda M, et al (2023) Survival of Patients With Cancer With DPYD Variant Alleles and Dose-Individualized Fluoropyrimidine Therapy\\u0026mdash;A Matched-Pair Analysis. JCO JCO.22.02780. https://doi.org/10.1200/JCO.22.02780\\u003c/li\\u003e\\n\\u003cli\\u003eRompelman G, Espiritu J, Chen A, et al (2023) Implementing a high-reliability, system-wide program for pre-emptive DPD deficiency testing for patients planned for a systemic fluoropyrimidine. JCO Oncol Pract 19:396\\u0026ndash;396. https://doi.org/10.1200/OP.2023.19.11_suppl.396\\u003c/li\\u003e\\n\\u003cli\\u003eMuldoon M, Beck M, Sebree N, et al (2024) Real‐world implementation of DPYD and UGT1A1 pharmacogenetic testing in a community‐based cancer center. Clin Transl Sci 17:e13704. https://doi.org/10.1111/cts.13704\\u003c/li\\u003e\\n\\u003cli\\u003eDeenen MJ, Meulendijks D, Cats A, et al (2016) Upfront Genotyping of DPYD*2A to Individualize Fluoropyrimidine Therapy: A Safety and Cost Analysis. JCO 34:227\\u0026ndash;234. https://doi.org/10.1200/JCO.2015.63.1325\\u003c/li\\u003e\\n\\u003cli\\u003eNorris M, Dalton R, Alam B, et al (2023) Lessons from clinical implementation of a preemptive pharmacogenetic panel as part of a testing pilot program with an employer-sponsored medical plan. Front Genet 14:1249003. https://doi.org/10.3389/fgene.2023.1249003\\u003c/li\\u003e\\n\\u003cli\\u003eDodson C (2018) Oncology Nurses\\u0026rsquo; Knowledge of Pharmacogenomics Before and After Implementation of an Education Module. Oncol Nurs Forum 45:575\\u0026ndash;580. https://doi.org/10.1188/18.ONF.575-580\\u003c/li\\u003e\\n\\u003cli\\u003eOneOme\\u0026reg; The OneOme RightMed\\u0026reg; Test. https://oneome.com/rightmed-test/. Accessed 15 Feb 2024\\u003c/li\\u003e\\n\\u003cli\\u003eRPRD Diagnostics RPRD Pharmacogenomics Testing Services. In: RPRDx. https://www.rprdx.com/testing/overview/. Accessed 15 Feb 2024\\u003c/li\\u003e\\n\\u003cli\\u003eMroz P, Michel S, Allen JD, et al (2021) Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System. Front Genet 12:712602. https://doi.org/10.3389/fgene.2021.712602\\u003c/li\\u003e\\n\\u003cli\\u003eOffer SM, Fossum CC, Wegner NJ, et al (2014) Comparative functional analysis of DPYD variants of potential clinical relevance to dihydropyrimidine dehydrogenase activity. Cancer Res 74:2545\\u0026ndash;2554. https://doi.org/10.1158/0008-5472.CAN-13-2482\\u003c/li\\u003e\\n\\u003cli\\u003eLarrue R, Fellah S, Hennart B, et al (2024) Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity. Pharmacogenomics J 24:1. https://doi.org/10.1038/s41397-023-00322-x\\u003c/li\\u003e\\n\\u003cli\\u003eShriver SP, Adams D, McKelvey BA, et al (2024) Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology. J Clin Oncol JCO2301748:. https://doi.org/10.1200/JCO.23.01748\\u003c/li\\u003e\\n\\u003cli\\u003eSwen JJ, van der Wouden CH, Manson LE, et al (2023) A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. The Lancet 401:347\\u0026ndash;356. https://doi.org/10.1016/S0140-6736(22)01841-4\\u003c/li\\u003e\\n\\u003cli\\u003eLemke LK, Alam B, Williams R, et al (2023) Reimbursement of pharmacogenetic tests at a tertiary academic medical center in the United States. Front Pharmacol 14:1179364. https://doi.org/10.3389/fphar.2023.1179364\\u003c/li\\u003e\\n\\u003cli\\u003eEmpey PE, Pratt VM, Hoffman JM, et al (2021) Expanding Evidence Leads to New Pharmacogenomics Payer Coverage. Genet Med 23:830\\u0026ndash;832. https://doi.org/10.1038/s41436-021-01117-w\\u003c/li\\u003e\\n\\u003cli\\u003eSarah A. Morris, D. Grace Nguyen, Karine Eboli Lopes, et al (2023) Assessing real-world clinical impact of an in-house dihydropyrimidine dehydrogenase (DPYD) genotyping test on fluoropyrimidine dosing and toxicity at a multisite cancer hospital. Pharmacogenetics and Genomics 33:204\\u0026ndash;205. https://doi.org/10.1097/FPC.0000000000000507\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 1:\\u003c/strong\\u003e Characteristics of Sites Included in Analysis (n=24)\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"624\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNumber of Responses\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003en (%)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eRole of Survey Respondent\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Pharmacist(s)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e15 (62.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Medical oncologist(s)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Multiple respondents from same site\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Other\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Nurse/advanced practice provider\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eStatus of Testing Implementation\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Implemented\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e21 (87.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Detailed plan in place for implementation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3 (12.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSite Type\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Academic teaching institution/hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e17 (70.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Community hospital or outpatient cancer care\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Multi-state health system\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Non-academic hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; VA hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eTesting for Clinical or Research Purposes\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Clinical practice\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e20 (83.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Research study\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWho Championed Pre-treatment Testing \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Medical oncologist(s)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e16 (66.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Precision medicine team\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e14 (58.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Pharmacy/pharmacist(s)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e14 (58.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Institutional leadership/administration\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5 (20.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Medical genetics/genetic counselor(s)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Other\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e Sites could select all answers that apply so responses do not add up to 24\\u003cbr\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2:\\u003c/strong\\u003e Test Ordering Process (n=24)\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"624\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNumber of Responses\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003en (%)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eFor Whom is Pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e Testing Ordered\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Selected patients for whom FP chemotherapy is ordered\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e16 (66.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Every patient for whom FP chemotherapy is ordered\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Every patient with all tumor types that typically receive FP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Every patient treated at the site\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWho Orders Testing \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026emsp;Medical oncologist/prescriber\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e23 (95.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Nurse/advanced practice provider\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e8 (33.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Pharmacogenetics service/specialist\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e7 (29.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Pharmacist\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5 (20.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Research team\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Genetic counselor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHow is Testing Initiated\\u0026nbsp;\\u003c/strong\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Test ordering is included in a systematic process\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e13 (54.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Included in institutional workflow (e.g., order sets)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;7 (29.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Automated CDS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Both CDS and included in institutional workflow\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Clinician is responsible for remembering to order\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e11 (45.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePrimary Source of Funding\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Testing is billed for insurance reimbursement\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e16 (66.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; Institutional or research funds\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e7 (29.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34615384615384%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePatient pays out of pocket\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65384615384615%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviations: CDS= Clinical Decision Support\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e Sites could select all answers that apply so responses do not add up to 24\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3:\\u003c/strong\\u003e Summary of the Testing Laboratories Used and Their Characteristics (n=24)\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"7\\\" cellpadding=\\\"0\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eName of Genetic Testing Laboratory\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMean Turnaround Time (range) [days]\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNumber of \\u003cem\\u003eDPYD\\u003c/em\\u003e Variants Tested\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eTotal Number of Genes Tested\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNumber of Sites Using this Lab \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003en (%)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eIn-house Testing\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6 (3-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eN/A \\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eN/A \\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9 (37.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOneOme\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e8 (5-12)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e7 (29.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eARUP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e7 (5-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3 (12.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMayo Labs\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e7 (5-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3 (12.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLabCorp\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9 (7-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eInvitae\\u003csup\\u003e\\u0026nbsp;d\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e10 (7-12)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eRPRD Diagnostics\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026ge;14 (14-20)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCHOP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9 (7-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSanford Imagenetics\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e10 (10-10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"25.249169435215947%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eTempus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"23.754152823920265%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026ge;14 (14-21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.777408637873755%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"17.774086378737543%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.44518272425249%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviations: CHOP= Children\\u0026rsquo;s Hospital of Philadelphia\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u0026nbsp;\\u003c/sup\\u003eTime spans were included in the average by using the median days in the span (e.g., 7-10 days=8.5 days)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003eb\\u0026nbsp;\\u003c/sup\\u003eSites could select all answers that apply so responses do not add up to 24\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ec\\u003c/sup\\u003e Number of variants and genes differed between sites and not all sites provided this information. See \\u003cstrong\\u003eOnline Material Table 3\\u003c/strong\\u003e for details provided by each site.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ed\\u003c/sup\\u003e Invitae has discontinued \\u003cem\\u003eDPYD\\u003c/em\\u003e testing but information was included for completeness\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003e\\u003c/em\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 4:\\u003c/strong\\u003e Interpreting, Reporting, and Storing Test Results (n=24)\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"630\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNumber of Responses\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003en (%)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWho Interprets Test Results \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Pharmacist\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e18 (75.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Medical oncologist\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e17 (70.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Clinical decision support\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e15 (62.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Nurse/Advanced practice provider\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Genetic counselor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eResources to Select Appropriate Drug Regimens \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGuideline-based clinical decision support\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e13 (54.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Recommendations from pharmacy consult\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9 (37.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Clinician consults CPIC/PharmGKB/DPWG\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e9 (37.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Recommendation from laboratory report\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6 (25.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWho Returns Results to Patients \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Medical oncologist/prescriber\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e15 (62.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Pharmacist\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e8 (33.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Nurse or advanced practice provider\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6 (25.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Patient receives results directly (no provider involved)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6 (25.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Genetic counselor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Results are not returned to patients\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHow are Results Returned to Patients \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Patient-specific portal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e17 (70.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Verbal return of results\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e10 (41.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Physical paper copy/letter\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5 (20.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Electronic copy\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e4 (16.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Results are not returned to patients\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;I don\\u0026rsquo;t know/Other\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHow are Results Stored in the EMR? \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Pharmacogenetics section or genomic indicators\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e15 (62.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Problem list\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6 (25.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;PDF upload or lab results section only\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5 (20.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Allergy list\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2 (8.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"66.34920634920636%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Clinical note\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.65079365079365%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1 (4.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviations: \\u0026nbsp;\\u0026nbsp;CPIC= Clinical Pharmacogenetics Implementation Consortium;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003ePharmGKB= Pharmacogenomics Knowledgebase;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eDPWG\\u003cem\\u003e= \\u003cem\\u003eDutch Pharmacogenetics Working Group;\\u003c/em\\u003e\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eEMR= Electronic Medical Record\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e Sites could select all answers that apply so responses do not add up to 24\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"supportive-care-in-cancer\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"jscc\",\"sideBox\":\"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)\",\"snPcode\":\"520\",\"submissionUrl\":\"https://submission.nature.com/new-submission/520/3\",\"title\":\"Supportive Care in Cancer\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"DPYD, clinical implementation, fluoropyrimidines, survey, pharmacogenetics, oncology\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4207186/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4207186/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003ePurpose\\u003c/h2\\u003e \\u003cp\\u003ePatients with dihydropyrimidine dehydrogenase (DPD) deficiency are at high risk for severe and fatal toxicity from fluoropyrimidine (FP) chemotherapy. Pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing is standard of care in many countries, but not the United States (US). This survey assessed pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing approaches in the US to identify best practices for broader adoption.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eFrom August to October 2023, a 22-item Qualtrics\\u003csup\\u003eXM\\u003c/sup\\u003e survey was sent to institutions and clinicians known to conduct pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing and broadly distributed through relevant organizations and social networks. Responses were analyzed using descriptive analysis.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eResponses from 24 unique US sites that have implemented pre-treatment \\u003cem\\u003eDPYD\\u003c/em\\u003e testing or have a detailed implementation plan in place were analyzed. Only 33% of sites ordered \\u003cem\\u003eDPYD\\u003c/em\\u003e testing for all FP-treated patients; at the remaining sites, patients were tested depending on disease characteristics or clinician preference. Almost 50% of sites depend on individual clinicians to remember to order testing without the assistance of electronic alerts or workflow reminders. \\u003cem\\u003eDPYD\\u003c/em\\u003e testing was most often conducted by commercial laboratories that tested for at least the 4 or 5 \\u003cem\\u003eDPYD\\u003c/em\\u003e variants considered clinically actionable. Approximately 90% of sites reported receiving results within 10 days of ordering.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e \\u003cp\\u003eImplementing \\u003cem\\u003eDPYD\\u003c/em\\u003e testing into routine clinical practice is feasible and requires a coordinated effort among the healthcare team. These results will be used to develop best practices for the clinical adoption of \\u003cem\\u003eDPYD\\u003c/em\\u003e testing to prevent severe and fatal toxicity in cancer patients receiving FP chemotherapy.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Strategies for DPYD Testing Prior to Fluoropyrimidine Chemotherapy in the United States\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-05-14 17:57:40\",\"doi\":\"10.21203/rs.3.rs-4207186/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-06-20T15:49:20+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"99380289036204683002644870293828598609\",\"date\":\"2024-06-12T21:29:02+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"134292794373108957433452227584723506695\",\"date\":\"2024-06-10T15:21:57+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-05-24T08:42:32+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"58624923071196426052362989172222552022\",\"date\":\"2024-05-24T06:02:48+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-05-07T19:28:04+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-05-06T20:25:08+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-04-03T07:52:24+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Supportive Care in Cancer\",\"date\":\"2024-04-02T13:52:47+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"supportive-care-in-cancer\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"jscc\",\"sideBox\":\"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)\",\"snPcode\":\"520\",\"submissionUrl\":\"https://submission.nature.com/new-submission/520/3\",\"title\":\"Supportive Care in Cancer\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"d82a0cb7-be52-4192-a2e3-e91827127e3c\",\"owner\":[],\"postedDate\":\"May 14th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-06-20T16:48:45+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-05-14 17:57:40\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4207186\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4207186\",\"identity\":\"rs-4207186\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}