Drug interaction screening in SWOG clinical trials

Pharmaceutical care in the screening process of phase I oncohaematological clinical trials

OBJECTIVE

To determine the pharmaceutical interventions in patients eligible for phase I cancer clinical trials, focusing specifically on exclusion criteria related to medication or relevant interactions.

METHOD

Descriptive, observational study conducted at a comprehensive cancer centre. Patients undergoing screening for phase I clinical trials (March 2019-December 2022) were included. The pharmacist reviewed concomitant medication and provided a recommendation.

RESULTS

The concomitant medication of 512 patients eligible to participate in 84 phase I clinical trials was analysed. In 230 (44.9%) patients, the clinical trial treatment included oral medication. The median number of concomitant medications was 5 (IQR 3-8) per patient.A total of 280 pharmaceutical interventions were performed in 140 (27.3%) patients: 240 (85.7%) were due to interactions in 124 (24.2%) patients, and 40 (14.3%) were due to exclusion criteria in 34 (6.6%) patients. Interactions and exclusion criteria were detected in 18 (3.5%) patients. The main groups of drugs involved were 68 (24.3%) antacids and antiulcer drugs, 28 (10.0%) antidepressants and 26 (9.3%) opioids. Acceptance analysis of the recommendation was applicable in 215 cases; in 208 (96.7%), the pharmaceutical intervention was accepted.Differences were identified for exclusion criteria (7 vs 27) and interactions (37 vs 87) between parenteral and oral clinical trial medication (p<0.001).

CONCLUSION

The pharmacist's review of concomitant medication during the screening period in phase I clinical trials enables the detection of prohibited medication or relevant interactions, potentially avoiding screening failures and increasing the efficacy and safety of treatments.

Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study

Abemaciclib demonstrated clinical benefit in women affected by HR+/HER2- advanced breast cancer (aBC). Drug-drug interactions (DDIs) can lead to reduced treatment efficacy or increased toxicity. This retro-prospective study aimed to evaluate outcomes, DDIs' impact, and toxicities of abemaciclib combined with endocrine therapy in a real-world setting. Patients from 12 referral Italian hospitals with HR+/HER2- aBC who received abemaciclib were included. Clinical data about comorbidities, concurrent medications, outcomes, and adverse events (AE) were collected. Drug-PIN® (Personalized Interactions Network) is a tool recognizing the role of multiple interactions between active and/or pro-drug forms combined with biochemical and demographic patient data. The software was used to define the Drug-PIN score and Drug-PIN tier (green, yellow, dark yellow, and red) for each patient. Univariate and multivariate analyses were performed to identify predictors of patients' PFS or toxicity. One hundred seventy-three patients were included. 13% of patients had >75years. The overall response rate (ORR) was 63%. The general population's median PFS (mPFS) was 22 months (mo), while mOS were not reached. Patients treated with abemaciclib in combination with AI and fulvestrant had a mPFS of 36 and 19 mo, respectively. The most common toxicities were diarrhea, asthenia, and neutropenia detected in 63%,49%, and 49% of patients. The number of concomitant medications and comorbidities were not associated with survival outcomes (22 vs 17 mo, p = 0.068, p = 0.99). Drug-PIN tier from dark yellow to red and Drug-PIN score >12 were associated with shorter PFS compared to no/low-risk DDIs and score <12 (15 vs 23, p = 0.005, p = 0.0017). Drug interaction was confirmed as an independent biomarker in a multivariate model (p = 0.02). No difference in any grade AE, severe toxicities, and diarrhea were detected among different age subgroups. No association was found between Drug-PIN score or Drug-PIN tier and overall toxicity (p = 0.44), severe AEs (p = 0.11), or drug reduction (p = 0.27). The efficacy and safety of abemaciclib plus ET were confirmed in a real-world setting, even in the elderly population and patients with comorbidities. Evaluation of DDIs with Drug-PIN appears to be an independent predictor of PFS.

Navigating the challenges of clinical trial professionals in the healthcare sector

Clinical trials (CTs) are essential for medical advancements but face significant challenges, particularly in professional training and role clarity. Principal investigators, clinical research coordinators (CRCs), nurses, clinical trial pharmacists, and monitors are key players. Each faces unique challenges, such as maintaining protocol compliance, managing investigational products, and ensuring data integrity. Clinical trials' complexity and evolving nature demand specialized and ongoing training for these professionals. Addressing these challenges requires clear role delineation, continuous professional development, and supportive workplace environments to improve retention and trial outcomes. Enhanced training programs and a collaborative approach are essential for the successful conduct of clinical trials and the advancement of medical research.

Impact of pharmacist consultation at clinical trial inclusion: an effective way to reduce drug-drug interactions with oral targeted therapy

PURPOSE

Pharmacist consultation is unfrequently performed in oncology clinical trials that include patients who often have many co-treatments increasing the risk of drug-drug interactions (DDI). The aim of this study was to determine whether best possible medication history (BPMH) by hospital pharmacist at inclusion and therapeutic drug monitoring could be used for DDI risk evaluation and for current oral targeted therapy management.

METHODS

A prospective clinical trial (ALCINA 2, NCT04025541) was carried out in metastatic breast cancer cohort treated by palbociclib to conduct pharmacokinetics-toxicity correlation study. BPMH was prospectively performed by the hospital pharmacist at each trial inclusion, followed by a contact to the patient's community pharmacy to complete the collected data. Pharmacokinetic analysis was performed on blood samples collected at day 15 of cycle 1 of palbociclib treatment.

RESULTS

Pharmacist interventions indicated that at inclusion, current medications were incomplete for 63% of the enrolled patients (32/51). It allowed the real-time management of high-risk DDI detected in third of patients. The palbociclib C_trough geometric median (min-max) was significantly higher in cohort with potential DDI [106 ng/mL (66.7-113)], than cohort without potential DDI [70.1 ng/mL (54.1-89.7)], p = 0.0284.

CONCLUSION

This is the first prospective study evaluating the relevance of proactive BPMH by pharmacist with contact to the community pharmacy during the inclusion step of a clinical trial to ensure the efficacy and safety of the investigated drug. This investigation was thus able to highlight the statistically significant impact of these DDI on palbociclib plasma concentration variation during the clinical trial.

TRIAL REGISTRATION

Clinicaltrials.gov identifier NCT04025541.

Drug-drug interactions in subjects enrolled in SWOG trials of oral chemotherapy

BACKGROUND

Patients with cancer are at increased risk of drug-drug interactions (DDI), which can increase treatment toxicity or decrease efficacy. It is especially important to thoroughly screen DDI in oncology clinical trial subjects to ensure trial subject safety and data accuracy. This study determined the prevalence of potential DDI involving oral anti-cancer trial agents in subjects enrolled in two SWOG clinical trials.

METHODS

Completed SWOG clinical trials of commercially available agents with possible DDI that had complete concomitant medication information available at enrollment were included. Screening for DDI was conducted through three methods: protocol-guided screening, Lexicomp® screening, and pharmacist determination of clinical relevance. Descriptive statistics were calculated.

RESULTS

SWOG trials S0711 (dasatinib, n = 83) and S0528 (everolimus/lapatinib, n = 84) were included. Subjects received an average of 6.6 medications (standard deviation = 4.9, range 0-29) at enrollment. Based on the clinical trial protocols, at enrollment 18.6% (31/167) of subjects had a DDI and 12.0% (20/167) had a DDI that violated a protocol exclusion criterion. According to Lexicomp®, 28.7% of subjects (48/167) had a DDI classified as moderate or worse, whereas pharmacist review indicated that 7.2% of subjects (12/167) had a clinically relevant interaction. The majority of clinically relevant DDI identified were due to the coadministration of acid suppression therapies with dasatinib (83.3%, 10/12).

CONCLUSIONS

The high DDI prevalence in subjects enrolled on SWOG clinical trials, including a high prevalence that violate trial exclusion criteria, support the need for improved processes for DDI screening to ensure trial subject safety and trial data accuracy.

Improvement Initiative to Develop and Implement a Tool for Detecting Drug-Drug Interactions During Oncology Clinical Trial Enrollment Eligibility Screening

OBJECTIVES

Screening subjects for drug-drug interactions (DDIs) before enrollment in oncology clinical trials is integral to ensuring safety, but standard procedures or tools are not readily available to screen DDI in this setting. Our objectives were to develop a DDI screening tool for use during oncology clinical trial enrollment and to test usability in single-center and multicenter pilot studies.

METHODS

A multistage approach was used for this quality improvement intervention. Semistructured interviews with individuals responsible for DDI screening were conducted to develop a prototype tool. The tool was used for screening DDI in subjects enrolling in National Clinical Trials Network trials of commercially available agents during a single-center 3-month pilot. Improvements were made, and a 3-month multicenter pilot was conducted at volunteer SWOG Cancer Research Network sites. Participants were surveyed to determine tool usability and efficiency.

RESULTS

A tool was developed from semistructured interviews. A critical feature was reporting which medications had specific pharmacokinetic and pharmacodynamic characteristics including transporter and cytochrome P450 substrates, inhibitors, or inducers and QT prolongation. In the 12-site study, average (SD) DDI screening time for each patient decreased by 15.7 (10.2) minutes (range, 3-35 minutes; P < 0.001). Users reported the tool highly usable, with >90% agreeing with all positive usability characterizations and disagreeing with all negative complexity characterizations.

CONCLUSIONS

A DDI screening tool for oncology clinical trial enrollment was created and its usability confirmed. Further testing with more diverse investigator sites and study drugs during eligibility screening is warranted to improve safety and data accuracy within clinical trials.

Prevalence of drug-drug interactions in oncology patients enrolled on National Clinical Trials Network oncology clinical trials

Background

Drug-drug interactions (DDIs) in subjects enrolling in clinical trials can impact not only safety of the patient but also study drug outcomes and data validity. This makes it critical to adequately screen and manage DDIs. The study objective was to determine the prevalence of DDIs involving study medications in subjects enrolling in National Clinical Trials Network (NCTN) clinical trials at a single institution. DDIs were evaluated based on study protocol recommendations for concomitant medication use (i.e. exclude, avoid or use caution), screening via DDI tool, and pharmacist review.

Methods

Subjects enrolled in NCTN trials of commercially available agents between January 2013 and August 2017 were included if a complete medication list was available. Complete medication lists were collected from the date of enrollment or the next available date then screened utilizing protocol guidance and the DDI screening tool, Lexicomp® Drug Interactions (Wolters Kluwer, Hudson, OH). Interactions were reviewed for clinical relevance: defined as a DDI that would require a medication change to ensure study agent safety and efficacy at enrollment.

Results

One hundred and twenty-eight subjects enrolled in 35 clinical trials were included. Protocol guidance detected 15 unique DDI pairs that should be avoided or used with caution in 10.2% (13/128) of subjects. The majority of these subjects did not have a clinically relevant DDI (69.2%, 9/13) based on pharmacist review. Lexicomp® detected moderate to major DDIs in 24.2% (31/128) of subjects, with 9.4% (12/128) having a clinically relevant DDI.

Conclusions

This study confirms a high prevalence of DDIs present in subjects enrolling in oncology clinical trials. Further efforts should be made to improve methods to detect and manage DDIs in patients enrolling on clinical trials to ensure patient safety and trial data validity.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5076-0) contains supplementary material, which is available to authorized users.