Pharmacogenetic and clinical predictors of voriconazole concentration in hematopoietic stem cell transplant recipients receiving CYP2C19-guided dosing.

CYP2C19-guided voriconazole dosing reduces pharmacokinetic variability, but many patients remain subtherapeutic. The aim of this study was to evaluate the effect of candidate genes and a novel CYP2C haplotype on voriconazole trough concentrations in patients receiving CYP2C19-guided dosing. This is a retrospective candidate gene study in allogeneic hematopoietic cell transplant (HCT) patients receiving CYP2C19-guided voriconazole dosing. Patients were genotyped for ABCB1, ABCG2, CYP2C9, CYP3A4, CYP3A5, and the CYP2C haplotype. Of 185 patients, 36% were subtherapeutic (of which 79% were normal or intermediate metabolizers). In all patients, CYP2C19 (p < 0.001), age (p = 0.018), and letermovir use (p = 0.001) were associated with voriconazole concentrations. In the subset receiving 200 mg daily (non-RM/UMs), CYP2C19 (p = 0.004) and ABCG2 (p = 0.015) were associated with voriconazole concentrations; CYP2C19 (p = 0.028) and letermovir use (p = 0.001) were associated with subtherapeutic status. CYP2C19 phenotype and letermovir use were significantly associated with subtherapeutic voriconazole concentrations and may be used to improve voriconazole precision dosing, while further research is needed to clarify the role of ABCG2 in voriconazole dosing.

Potentially actionable pharmacogenetic variants and symptom control medications in oncology.

PURPOSE: We estimated the prevalence of potentially actionable pharmacogenetic (PGx) variants related to symptom control medications (SCMs) based on institutional prescribing patterns and correlated presenting symptoms with SCM prescribing. METHODS: This was a retrospective study of adult ambulatory cancer patients undergoing electronic distress screening (EDS) within 90 days of intake to the cancer hospital. We estimated the proportion prescribed SCM(s) with PGx evidence within 90 days of intake. Those with potentially actionable variants were estimated using population frequency data from 1000 genomes. The expected number at risk of altered drug response was estimated. The associations between symptom scores and SCM(s) were estimated with logistic regression and threshold analyses performed with receiver operating characteristic (ROC) curves. RESULTS: Of 6985 patients, 3222 (46%) received ≥ one SCM. Of these, 2760 (86%) received SCM(s) with PGx evidence for CYP2B6, CYP2C19, CYP2D6, or SLC6A4; 2719 (84%) received a drug metabolized by CYP2D6, most commonly hydrocodone (40.4%), ondansetron (35.6%), oxycodone (24.2%), and/or tramadol (7.1%). Based on this, about one quarter were expected to have altered metabolism and/or drug response. One third were prescribed two or more SCMs with PGx evidence. About half reported at least one severe symptom, which significantly correlated with SCM prescribing (p < 0.001). Threshold scores were identified that highly correlated with SCM prescribing for anxiety, depression, nausea, neuropathy, pain, and sleep. CONCLUSION: About half presented with significant symptom burden, which highly correlated with SCM prescribing. Most received SCMs with PGx evidence. Preemptive PGx testing for these variants should be evaluated in prospective trials to evaluate the impact on symptom control.

Opioid Monitoring Using Urine Toxicology Screens in Outpatient Oncology Palliative Medicine.

PURPOSE: There is a paucity of real-world data on opioid screening and urine toxicology testing in outpatient oncology palliative medicine. METHODS: This was a retrospective analysis of adult patients with cancer completing ≥ one outpatient palliative medicine visit and the Edmonton Symptom Assessment Scale (ESAS). Patient demographics, the Screener and Opioid Assessment for Patients with Pain-Short Form (SOAPP-SF), ESAS, medications, and urine toxicology screens (UTSs) were collected at baseline and follow-up visits. The primary end point was the frequency and type(s) of noncompliant UTSs (ie, presence of a nonprescribed substance or absence of a prescribed substance). Secondarily, risk factors for noncompliant UTSs were evaluated using univariate and multivariable logistic regression. RESULTS: Of 189 evaluable patients (632 clinic visits), 113 underwent ≥one UTSs, 125 SOAPP-SF, and 75 had both. The median age was 56 (range, 26-80) years, 56% were female, 58% were White, 40% were Black, 48% had stage IV disease, the median baseline pain score was 7, and the median SOAPP-SF was 3. Oxycodone was the most prescribed drug (n = 125). Of 113 patients who underwent UTSs, 54% (n = 61) had ≥one noncompliant result. Thirty-nine percent (n = 44) had a total of 128 noncompliant results for the presence of a nonprescribed substance; 29% (n = 33) had a total of 53 noncompliant results for the absence of a prescribed substance. SOAPP-SF Q4 (use of illegal drugs) (odds ratio [OR], 3.61; 95% CI, 1.81 to 7.19; P < .001) and prescription with nonopioid adjuvant medications (OR, 2.83; 95% CI, 1.12 to 7.19; P = .029) were associated with increased odds of a noncompliant UTS. CONCLUSION: More than half of the tested population had noncompliant UTS. Screening and evaluating risk factors for nonmedical opioid use is critical in oncology palliative medicine.

Pharmacogenomics-guided supportive oncology: A tale of two trials.

Cancer-related symptoms, like depression, nausea, and pain, are common and negatively affect quality of life. Unfortunately, there is large inter-individual variability in response to supportive care medications for these symptoms. Pharmacogenomics may inform prescribing by identification of those genetically at risk for drug related adverse events or therapeutic failure. While such information can be applied to many drugs, there are specific oncology populations that could greatly benefit from pharmacogenomics-guided supportive care management due to high symptom burden, including those receiving palliative medicine and hematopoietic stem cell transplantation. The goal of this paper is to provide an overview of, and lessons learned from, the development of two prospective pharmacogenomics-guided interventional trials ("Supportive Care PGx Trial" and "Transplant PGx Trial") across two different clinical settings at the Levine Cancer Institute: the Department of Supportive Oncology and the Transplant and Cellular Therapy section. Key considerations included the appropriate study design and endpoints (balancing study goals and resources), dissemination and application of individual pharmacogenetics results, technical details about assay development, and overall care coordination to minimize clinic disruption.

Thromboembolism Incidence and Risk Factors in Multiple Myeloma After First Exposure to Immunomodulatory Drug-Based Regimens.

BACKGROUND: We evaluated time to thromboembolism (TE) and risk factors in multiple myeloma (MM) patients after first exposure to immunomodulatory therapy, stratified by thromboprophylaxis. PATIENTS AND METHODS: We retrospectively analyzed adult MM patients who received immunomodulatory therapy with or without dexamethasone between February 2012 and October 2017. Thromboprophylaxis included aspirin, anticoagulants (low-molecular-weight heparin, direct oral anticoagulants, or warfarin), or none. Primary endpoint was time to on-treatment TE by thromboprophylaxis type. Time to TE using death as a competing risk censored at 12 months was used in univariate and multivariable analyses to identify risk factors. RESULTS: Of 485 evaluable patients, 57% were white and 36% African American; median age was 66. Most received lenalidomide (97.5%) and dexamethasone (90%). Half presented with ≥ 1 comorbidities. Sixty-nine had no documented receipt of prophylaxis, 357 aspirin, and 59 anticoagulation. More patients receiving anticoagulants had ≥ 1 comorbidities compared to aspirin or no-prophylaxis groups (P < .001). There was no difference in 12-month estimated cumulative incidence of TE (7.3%; 95% confidence interval, 5.2-9.9) between thromboprophylaxis groups (none 4.4%, aspirin 8.5%, anticoagulant 3.4%) (P = .24). In multivariable analyses, male sex (hazard ratio, 2.50; 95% confidence interval, 1.21-5.17; P = .014) and presence of any comorbidity (hazard ratio, 2.35; 95% confidence interval, 1.17-4.73; P = .016) were associated with TE incidence; thromboprophylaxis type was not (P = .12). CONCLUSION: Male sex and presence of any comorbidity were associated with time to TE. There were no differences in TE incidence between thromboprophylaxis groups despite a higher proportion of those in the anticoagulant group having ≥ 1 comorbidities.