DOI: 10.5061/dryad.b2rbnzsrb
title: Integrating pharmacogenomics in three Middle Eastern countries’ healthcare (Lebanon, Qatar, and Saudi Arabia)

description: Background and Objectives: Pharmacogenomics (PGx) leverages genomic
 information to tailor drug therapies, enhancing precision medicine.
 Despite global advancements, its implementation in Lebanon, Qatar, and
 Saudi Arabia faces unique challenges in clinical integration. This study
 aimed to investigate PGx attitudes, knowledge implementation, associated
 challenges, forecast future educational needs, and compare findings across
 the three countries. Methods: This cross-sectional study utilized an
 anonymous, self-administered online survey distributed to healthcare
 professionals, academics, and clinicians in Lebanon, Qatar, and Saudi
 Arabia. The survey comprised 18 questions to assess participants'
 familiarity with PGx, current implementation practices, perceived
 obstacles, potential integration strategies, and future educational needs.
 Results: The survey yielded 337 responses from healthcare professionals
 across the three countries. Data revealed significant variations in PGx
 familiarity and educational involvement. Qatar and Saudi Arabia
 participants were more familiar with PGx compared to Lebanon (83%, 75%,
 and 67%, respectively). Participation in PGx-related talks was most
 prevalent in Saudi Arabia (96%), followed by Qatar (53%) and Lebanon
 (35%). Key challenges identified included test cost and reimbursement,
 insufficient physician knowledge, and lack of infrastructure. Lebanon
 reported the highest concern for test costs (16%), compared to the lowest
 in Saudi Arabia (5%). Despite these challenges, a strong consensus emerged
 on PGx's potential to improve patient outcomes, with over 86% of
 respondents in all three countries expressing this belief. Educational
 interest areas varied by country, with strong interest in PGx for cancer
 chemotherapy in Saudi Arabia and Lebanon and for diabetes mellitus in
 Qatar. Conclusion: This study highlights the significant influence of
 varied educational backgrounds and infrastructural limitations on PGx
 implementation across Lebanon, Qatar, and Saudi Arabia. The findings
 emphasize the need for targeted strategies in each country to address
 these distinct barriers. Integrating PGx education into healthcare
 training programs and clinical workflows could unlock PGx's potential
 to optimize patient care.
description: <strong>Ethical statement and informed
 consent</strong> Ethical approval for this study
 was obtained from the institutional review boards of the participating
 universities: Beirut Arab University (2023-H-0153-HS-R-0545), Qatar
 University (QU-IRB 1995-E/23), and Alfaisal University (IRB-20270).
 Informed consent was obtained from all participants online, ensuring their
 confidentiality and the right to withdraw from the study without any
 consequences. Participants were informed that all collected data would be
 anonymous and confidential, with only the principal investigator having
 access to the data. Completing and submitting the survey was considered an
 agreement to participate. <strong>Study
 design</strong> This study utilized a
 quantitative cross-sectional research design, involving healthcare
 professionals (pharmacists, nurses, medical laboratory technologists),
 university academics, and clinicians from Lebanon, Qatar, and Saudi
 Arabia. Data was collected through a voluntary, anonymous, private survey
 to gather PGx perspectives from specialists in the three countries. The
 study was conducted and reported following the Strengthening the Reporting
 of Observational Studies in Epidemiology (STROBE) guidelines (r
 1). <strong>Survey
 instrument</strong> The survey questions were
 adapted from the previously published manuscript by Ghaddar et al., with
 the approval of Pr. Nathalie Zgheib (2). The instrument comprised 18
 questions divided into several sections. The first section collected
 demographic information such as age, gender, country of residence,
 occupation, and years of experience in clinical practice or research. The
 second section focused on PGx implementation, examining participants'
 familiarity with the concept, attendance or presentation of educational
 talks, and integration of pharmacogenetic testing into their practice or
 research. The third section explored the obstacles faced in implementing
 PGx, asking participants to identify the top five obstacles from a
 provided list. The final section inquired about future considerations,
 including measures to overcome barriers in PGx implementation, belief in
 the potential of PGx to improve patient outcomes, interest in learning
 about pharmacogenomics, and specific topics of interest.
 Before launching, the survey was pilot-tested with a small group
 of healthcare professionals to ensure content clarity and relevance. Based
 on the pilot test, the survey questions were modified, added, or deleted
 to improve the content. The pilot responses were not included in the final
 analysis. The survey items were tailored to country-specific practice
 norms through consultation with experts from Lebanon and Qatar, where data
 collection began. For instance, the PGx of pain management was added due
 to its common testing in Qatari patients.
 <strong>Data collection</strong>
 Participants were recruited through purposive sampling, targeting
 professionals directly or indirectly involved in PGx. PGx opinion leaders
 or experts in each country were approached personally via direct email or
 social media and asked to complete and disseminate the survey within their
 teams. The survey was launched on September 27th, 2023, and data
 collection ended on December 23rd, 2023, in Lebanon; January 24th, 2024,
 in Qatar; and June 7th, 2024, in Saudi Arabia. Participants were briefed
 about the study's aim in the survey's introductory paragraph and
 directed to respond anonymously through Google Forms. The survey took
 approximately 4 minutes to complete. 1. Cuschieri S.
 The STROBE guidelines. Saudi J Anaesth. 2019;13(Suppl 1):S31-s4.
 2. Ghaddar F, Cascorbi I, Zgheib NK. Clinical implementation of
 pharmacogenetics: a nonrepresentative explorative survey to participants
 of WorldPharma 2010. Pharmacogenomics. 2011;12(7):1051-9.
description: # **Integrating pharmacogenomics in three Middle Eastern countries’
 healthcare (Lebanon, Qatar, and Saudi Arabia)** ## Description of the data
 and file structure * This is a data sheet exported as .CSV file from the
 original SPSS database. * Methods of data processing and analysis: data
 were generated by SPSS software version 20 (SPSS, Inc., IL, USA). Details
 are included in the manuscript. * No patient identifiers are included in
 these data sets. * Specialized software used: these data need to be
 entered in SPSS. * Description of the data set: o 1 dataset is included;
 PGx_database : it includes the raw data of our paper. o In the data set,
 each row represent one participant. o All the variables can contain empty
 cells. When participants didn't answer, empty cells were added to
 show the missing data. o The number in each cell has a specific value
 depending on the variable. - Listed variables: 1. **ID** * Description:
 Record identifier for each participant. * Values: Numeric
 (auto-generated). 2. **Age** * Description: Age group of the participant.
 * Values: “18-25”, “26-35”, “36-45”, “46-55”, or “Above 55.” 3. **Gender**
 * Description: Participant’s reported gender. * Values: “Male”, “Female.”
 4. **Occupation** * Description: Participant’s professional role (e.g.,
 academic, clinician, pharmacist, nurse, etc.). * Values: Text (e.g.,
 “Academic”, “Clinician”, “Pharmacist”, “Nurse”, “Other”). 5. **Degree** *
 Description: Highest degree or education level (e.g., BSc, MSc, PhD). *
 Values: Numeric code or descriptive text (e.g., “2” for master’s
 equivalent, “3” for PhD equivalent, “4” for MD, etc.). 6. **Country** *
 Description: Participant’s country of practice or residence. * Values:
 “Lebanon”, “Qatar”, or “KSA.” 7. **Field_of_Expertise** * Description:
 Broad field (e.g., “Academic”, “Clinician”, “Healthcare professional”). *
 Values: Text. 8. **Experience** * Description: Years of professional
 experience. * Values: Text categories (e.g., “&lt; 1 year”, “1-5 years”,
 “6-10 years”, “11-20 years”, “&gt; 20 years”). 9. **familiar_with_pgx** *
 Description: Whether participant is familiar with pharmacogenomics. *
 Values: “Yes”, “No.” 10. **v1** (or similar columns tracking the volume of
 knowledge) * Description: Frequency or amount of pharmacogenomics
 knowledge. * Values: Categorical text (e.g., “None”, “One”, “Few”, and
 “Many”). 11. **PGX_integration** * Description: Whether participant has
 integrated pharmacogenomics into practice. * Values: “Yes, routinely”,
 “Yes, occasionally”, “No, but considering”, “No, not interested”. 12.
 **Top1, Top2, Top3, etc.** * Description: Perceived barriers, challenges,
 or concerns about pharmacogenomics (e.g., test cost, lack of physician
 knowledge). * Values: Text entries describing each barrier. 13.
 **pgx_Improvement** * Description: Indicates whether participant thinks
 pharmacogenomics can improve care. * Values: “Yes”, “No”, or “Undecided”.
 14. **Learn_PGX** * Description: Level of interest in learning more about
 pharmacogenomics. * Values: “Very Interested”, “Interested”, “Slightly”,
 “Not interested”. 15. **specificpgxtopics** * Description: Therapeutic
 area(s) of interest for pharmacogenomics integration (e.g., “Cancer
 chemotherapy”, “Cardiovascular diseases”, “Infectious diseases”). *
 Values: Text. ## Sharing/Access information \* The complete findings
 derived from this data are in PLoS one Journal. \* There are no other
 associated datasets stored elsewhere. \* Contact information regarding
 analyses: [s.elshamieh@bau.edu.lb](mailto:s.elshamieh@bau.edu.lb)