About

Professor Christine Luu Cadiz is a Health Sciences Clinical Associate Professor at the School of Pharmacy & Pharmaceutical Sciences at UC Irvine. She holds a B.S. in Aquatic Biology and a B.A. in Cultural Anthropology from the University of California Santa Barbara, an M.A.T. from the University of California Irvine, and a Pharm.D. from the University of California San Diego. Her research interests include nephrology, pharmacogenomics, cardiology, and teaching and learning. Dr. Cadiz practices as a clinical pharmacist in cardiology, with a specialty in advanced heart failure, and is board certified in pharmacotherapy with an advanced practice pharmacist license. Since 2013, she has been a pharmacy educator, teaching didactic courses in the first-year Pharmacy Practice series and the second-year Cardiology Pharmacotherapy course, while also precepting students and residents on clinical rotations. She serves as the Chair of the PharmD Education Committee, overseeing the program's curriculum. Her scholarly work includes research on machine learning for clinical prediction models, sociodemographic disparities in vaccination, pharmacogenomics, medication adherence, and health disparities in pharmacy practice.

Research topics

• Computer Science
• Medicine
• Family medicine
• Internal medicine
• Nursing
• Political Science
• Surgery
• Pharmacology
• Physical therapy
• Medical education
• Emergency medicine
• Public relations

Selected publications

• Assessment of Guideline-Directed Medical Therapy Optimization Scores and Readmission Risk in Heart Failure With Reduced Ejection Fraction

  Annals of Pharmacotherapy · 2025-11-14

  articleOpen access

  BACKGROUND: Heart failure with reduced ejection fraction carries high morbidity and mortality. Guideline-directed medical therapy (GDMT) improves outcomes, yet real-world use is often suboptimal. Multiple scoring tools quantifying GDMT optimization have been developed to identify areas of improvement, including GDMT count, Optimal Medical Therapy (OMT), modified OMT (mOMT), and Kansas City Medical Optimization (KCMO) scores. Their clinical utility in predicting readmissions is uncertain. OBJECTIVE: To evaluate the association between four GDMT scoring systems and 30- and 90-day heart failure (HF) readmissions. METHODS: This multi-center, retrospective cohort study included adults with a left-ventricular ejection fraction ≤40% hospitalized for HF across five academic medical centers between February 2021 and July 2023. Patients discharged on ≥1 GDMT class with ≥1 healthcare encounter within 90 days were included. GDMT scores were calculated at discharge, and their associations with 30- and 90-day HF readmissions were analyzed using mixed-effects Cox proportional hazards models adjusted for clinical covariates. RESULTS: Among 544 patients, 13.1% experienced 30-day and 26.8% experienced 90-day HF readmissions. At 30 days, no GDMT score was significantly associated with readmission. At 90 days, higher OMT (hazard ratios [HR]: 0.93, 95% CI: 0.86-0.99) and mOMT (HR: 0.94, 95% CI: 0.88-0.99) scores were associated with lower readmission risk, whereas GDMT count and KCMO scores were not. Patients on minimal GDMT regimens contributed disproportionately to 90-day readmissions. CONCLUSION AND RELEVANCE: In this multi-center cohort, OMT and mOMT scores, but not GDMT count or KCMO, were associated with 90-day HF readmissions. Findings highlight the potential utility of simpler GDMT scoring systems while underscoring the need for refined tools incorporating dose intensity, class-specific weighting, and longitudinal therapy to better guide optimization efforts.

  PublisherDOI

• Comparison of standard versus adjusted dose of enoxaparin for venous thromboembolism prophylaxis in patients with obesity and cancer

  Journal of Oncology Pharmacy Practice · 2025-05-21 · 1 citations

  articleOpen access

  Introduction Active cancer and body mass index (BMI) greater than 30 kg/m 2 have been shown to increase venous thromboembolism (VTE) risk in hospitalized patients. Optimal dosing strategies in this population remain uncertain. This study evaluated the incidence of healthcare associated VTE (HA-VTE) in patients with active malignancy and obesity, comparing adjusted versus standard dose enoxaparin for VTE prophylaxis. Methods This multicenter, retrospective, cohort study compared enoxaparin 40 mg subcutaneously (SC) daily with adjusted enoxaparin dosing (> 40 mg SC daily) for VTE prophylaxis in hospitalized adult patients with a BMI greater than 30 kg/m 2 who received cancer therapy between January 1, 2020, and August 17, 2023. The primary outcome was incidence of HA-VTE. Secondary outcomes included VTE type and bleeding events. Descriptive statistics were used for all outcomes. Results A total of 330 patients were included, with a median BMI of 33.7 kg/m² (IQR 31.6–37.9 kg/m²). Standard dose enoxaparin was administered to 300 patients, while 30 received adjusted doses. HA-VTE occurred in 13 patients in the standard dose group, with no HA-VTE events in the adjusted group (p = 0.245). In the standard dose group, 4 patients had minor bleeds, and 2 had clinically relevant non-major bleeds. One minor bleed occurred in the adjusted group (p = 0.490). Conclusions HA-VTE was more frequent in the standard dosing group, though the small sample size limits the clinical significance. Patients on adjusted doses did not have increased bleeding events. Further research is needed to determine optimal thromboprophylaxis strategies for cancer patients with a BMI over 30 kg/m².

  PublisherDOI

• An evaluation of racial and ethnic disparities in cardiovascular risks in patients who underwent percutaneous coronary intervention

  International Journal of Cardiology · 2025-08-12 · 1 citations

  articleOpen access1st authorCorresponding

  BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of death in the United States, and individuals undergoing percutaneous coronary intervention (PCI) face an elevated risk for recurrent events. Racial and ethnic disparities may contribute to differences in cardiovascular risk factor control, yet comprehensive assessments across multiple risk domains are limited. METHODS: We conducted a retrospective chart review of adult patients who underwent PCI at a single academic medical center between January 2018 and November 2022. Baseline cardiovascular risk was assessed at hospital discharge across four domains: systolic blood pressure (SBP), low-density lipoprotein (LDL), hemoglobin A1c (A1c), and body mass index (BMI). Individual and cumulative risk factor goal attainment were compared across racial and ethnic groups using multivariate logistic regression. RESULTS: The study included 862 patients from four racial/ethnic groups: White, Black, Asian/Pacific Islander, and Hispanic. Overall, only 4.0 % of participants met all four cardiovascular goals at discharge. Hispanic patients had the lowest cumulative goal attainment, with 46.2 % meeting one or fewer goals, and only 14.7 % achieving at least three out of four goals. In adjusted models, Hispanic patients had significantly lower odds of achieving LDL (OR 0.48, 95 % CI: 0.29-0.77) and A1c (OR 0.40, 95 % CI: 0.27-0.58) goals compared to White patients. Asian/Pacific Islanders had the highest rates of cumulative goal achievement. CONCLUSION: Marked disparities in cardiovascular risk factor control were observed after PCI, particularly among Hispanic patients. These findings highlight the need for targeted, multidisciplinary strategies to improve equity in secondary cardiovascular prevention.

  PublisherDOI

• Pharmacogenomic Testing to Guide Treatment of Major Depressive Disorder: A Systematic Review

  Current Treatment Options in Psychiatry · 2024-05-31 · 4 citations

  reviewOpen accessSenior author

  Abstract Purpose of review Major depressive disorder is a prevalent psychiatric illness associated with significant morbidity, mortality, and economic burden worldwide. Despite the widespread use of antidepressants, remission rates among those treated with antidepressants remain low. Opportunities to personalize medication choices and doses and optimize clinical outcomes using pharmacogenomic testing have been evaluated. Recent findings Several prospective clinical trials and a recent meta-analysis have evaluated the impact of PGx-guided prescribing compared to treatment as usual and found no difference in clinical outcomes for patients with MDD. Summary We performed a systematic review of all prospective trials evaluating the effect of pharmacogenomic-guided prescribing on clinical outcomes of patients being treated with antidepressants for major depressive disorder. A literature search was performed using PubMed, Scopus, Web of Science, and PsychINFO databases for articles in English published from January 2010 to December 2022. Studies that did not report any patient-level outcomes were excluded. A total of 2489 studies were screened for eligibility. Full-text screening for 315 yielded 293 exclusions; thus, 22 studies were included. Sixteen of the 22 studies were randomized-controlled trials with durations varying from 90 days to 52 weeks. The findings of this systematic review suggest widespread routine pharmacogenomic testing may not yield significant changes in clinical outcomes when compared to treatment as usual. These results may or may not be generalizable to all persons taking antidepressants given guideline recommendations for pharmacogenomic-guided prescribing in patients on specific antidepressants. Future studies are warranted evaluating the utility of such testing in these subpopulations.

  PublisherOA PDFDOI

• Interprofessional team‐based care in the community pharmacy setting: A summary of existing models and best practice recommendations

  JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY · 2024-09-03 · 5 citations

  articleOpen access

  Abstract Community pharmacies are rapidly becoming destinations for health services beyond medication dispensing. Delivery models for community‐based services have become increasingly complex, creating expanded opportunities and necessitating collaboration between pharmacists in the community setting and other health care professionals. As a result, it is essential to articulate best practices and recommendations to assist stakeholders in responding to the changing landscape and optimize care for patients. This white paper provides a summary of published examples of interprofessional practice that include community pharmacies in the United States and internationally, and then adapts established guiding principles for interprofessional practice to the community pharmacy setting to outline a framework and specific recommendations for consideration. This framework highlights a need to place patients at the center of collaborative community‐based care models, have organizational leaders show a commitment to and establish an infrastructure for interprofessional collaboration that includes community‐based pharmacists, foster respect for community pharmacy practice, address communication and technology barriers in the health care system, and finally, embrace interprofessional learning in the community pharmacy setting. Addressing challenges and embracing opportunities is vital to accelerate practice transformation and further position community‐based pharmacists as essential members of interprofessional care teams.

  PublisherOA PDFDOI

• Enhancing Medication Safety: How Clinical Decision Support Systems and Clinical Pharmacists’ Interventions Address Drug-Disease Interactions

  Pharmaceutical Sciences Asia · 2024-01-01

  articleOpen access

  Drug-disease interactions (DDSIs) occur when a medicine aimed at treating one disease may worsen another comorbidity or condition (1) .These may be attributed to preventable medication errors (2) .They contribute to an increased risk of adverse drug reactions (ADR), which can lead to serious clinical consequences,

  PublisherOA PDFDOI

• Using Machine Learning to Develop a Clinical Prediction Model for SSRI-associated bleeding: a feasibility study

  Research Square · 2023-01-10

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

  BMC Medical Informatics and Decision Making · 2023-06-10 · 9 citations

  articleOpen accessSenior authorCorresponding

  INTRODUCTION: Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding. METHODS: The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians' input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models. RESULTS: There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632-0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs. CONCLUSIONS: We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction.

  PublisherOA PDFDOI

• Worldwide characteristics and trends of pharmacist interventions contributed to minimize health disparities

  JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY · 2022-05-26 · 2 citations

  article

  Abstract Health disparities in outcomes are ubiquitous and must be addressed. Pharmacist‐led clinical services have been shown to improve patient outcomes and reduce costs. However, their involvement in addressing health disparities has not been well documented. We conducted a literature review to summarize worldwide pharmacist‐involved interventions that contributed to reducing health disparities. The overarching goal is to provide guidance on future directions to advance health equity. PubMed, Scopus, Embase, and CINAHL were searched from inception to October 2021. Studies included were those that evaluated pharmacist‐involved interventions contributing to the mitigation of health disparities. Pilot or preliminary studies and those published in non‐English languages were excluded. Study characteristics, clinical areas, targeted patient population, types of interventions, and outcomes were evaluated. A total of 151 studies were included, of which 27% were randomized controlled trials. The majority of studies (82%) conducted in high‐income countries targeted cardiometabolic conditions (49%). Infectious diseases were commonly managed conditions among studies (56%) conducted in low‐/middle‐income countries. Most pharmacist‐involved interventions were delivered to rural communities (45%), followed by patients with low income (33%) and racial/ethnic minorities (24%). A minimal number of studies (1%) addressed gender‐ or disability‐related interventions. Multidisciplinary team care (70%) and medication management (64%) were the most prevalent care models reported among the studies, followed by education (49%) and screenings/health fairs (21%). Commonly reported outcome measures included laboratory values (38%), medication utilization (29%), and medication adherence (16%). Only 7% and 9% of the studies reported humanistic and economic outcomes, respectively. Pharmacists have been involved in a variety of clinical interventions targeting a diverse range of patient populations, which unveiled pharmacists' roles in contributing to reducing health disparities. Variability of implemented interventions exists geographically and in certain groups for whom few interventions have been implemented, highlighting the need for further efforts to achieve equity in health care.

  PublisherDOI

• Sociodemographic characteristics differ across routine adult vaccine cohorts: An All of Us descriptive study

  Journal of the American Pharmacists Association · 2022-11-13 · 4 citations

  articleOpen access

  BACKGROUND: The National Institutes of Health All of Us (AoU) Research Program is currently building a database of 1million+ adult subjects. With it, we describe the characteristics of those with documented vaccinations. OBJECTIVES: To describe the sociodemographic, health status, and lifestyle factors associated with vaccinations. METHODS: This is a retrospective study involving data from the AoU program (R2020Q4R2, N = 315,297). Five vaccine cohorts [influenza, hepatitis B (HBV), pneumococcal <65 years old, pneumococcal ≥65 years old, and human papillomavirus (HPV)] were generated based on vaccination history. The influenza cohort comprised participants with documented influenza vaccinations in electronic health records (EHRs) from September 2017 to May 2018. Other vaccine cohorts comprised participants with ≥1 lifetime record(s) of vaccination documented in the EHR by December 2018. The vaccine cohorts were compared to the overall AoU cohort. Descriptive statistics were generated using EHR- and survey-based sociodemographic, health, and lifestyle information. The SAMBA (0.9.0) R package was utilized to adjust for EHR selection and outcome misclassification biases to infer sources of disparity for pneumococcal vaccinations in older adults. RESULTS: Cohort counts were as follows: influenza (n = 15,346), HBV (n = 6323), pneumococcal <65 (n = 15,217), pneumococcal ≥65 (n = 15,100), and HPV (n = 2125). All vaccine cohorts had higher proportions of White and non-Hispanic/Latino participants compared to the overall AoU cohort. The largest differences were found in pneumococcal age ≥65, with 80.2% White participants compared to 52.9% in the overall study population. Multivariable analysis revealed that race/ethnic disparities in pneumococcal vaccination among older adults were explained by biological sex, income, health insurance, and education-related variables. CONCLUSION: Racial, ethnic, education, and income characteristics differ across the vaccine cohorts among AoU participants. These findings inform future utilization of large health databases in vaccine epidemiology research and emphasize the need for more targeted interventions that address differences in vaccine uptake.

  PublisherDOI

Frequent coauthors

• Candis M. Morello

  7 shared

• Alexandre Chan

  University of California, Irvine

  7 shared

• Keri Hurley‐Kim

  University of California, Irvine

  6 shared

• Mark Bounthavong

  University of Montana

  5 shared

• Jan D. Hirsch

  University of California, Irvine

  5 shared

• Ding Quan Ng

  University of California, Irvine

  5 shared

• Andrew Zimmerman

  4 shared

• Shanthi Kappagoda

  4 shared