Activation of Cryptic Donor Splice Sites within the UDP-Glucuronosyltransferase (UGT)1A First-Exon Region Generates Variant Transcripts That Encode UGT1A Proteins with Truncated Aglycone-Binding Domains

The human UDP-glucuronosyltransferases (UGTs) have crucial roles in metabolizing and clearing numerous small lipophilic compounds. The UGT1A locus generates nine UGT1A mRNAs, 65 spliced transcripts, and 34 circular RNAs. In this study, our analysis of published UGT-RNA capture sequencing (CaptureSeq) datasets identified novel splice junctions that predict 24 variant UGT1A transcripts derived from ligation of exon 2 to unique sequences within the UGT1A first-exon region using cryptic donor splice sites. Of these variants, seven (1A1_n1, 1A3_n3, 1A4_n4, 1A5_n1, 1A8_n2, 1A9_n2, 1A10_n7) are predicted to encode UGT1A proteins with truncated aglycone-binding domains. We assessed their expression profiles and deregulation in cancer using four RNA sequencing (RNA-Seq) datasets of paired normal and cancerous drug-metabolizing tissues from large patient cohorts. Variants were generally coexpressed with their canonical counterparts with a higher relative abundance in tumor than in normal tissues. Variants showed tissue-specific expression with high interindividual variability but overall low abundance. However, 1A8_n2 showed high abundance in normal and cancerous colorectal tissues, with levels that approached or surpassed canonical 1A8 mRNA levels in many samples. We cloned 1A8_n2 and showed expression of the predicted protein (1A8_i3) in human embryonic kidney (HEK)293T cells. Glucuronidation assays with 4-methylumbelliferone (4MU) showed that 1A8_i3 had no activity and was unable to inhibit the activity of 1A8_i1 protein. In summary, the activation of cryptic donor splice sites within the UGT1A first-exon region expands the UGT1A transcriptome and proteome. The 1A8_n2 cryptic donor splice site is highly active in colorectal tissues, representing an important cis-regulatory element that negatively regulates the function of the UGT1A8 gene through pre-mRNA splicing. SIGNIFICANT STATEMENT: The UGT1A locus generates nine canonical mRNAs, 65 alternately spliced transcripts, and 34 different circular RNAs. The present study reports a series of novel UDP-glucuronosyltransferase (UGT)1A variants resulting from use of cryptic donor splice sites in both normal and cancerous tissues, several of which are predicted to encode variant UGT1A proteins with truncated aglycone-binding domains. Of these, 1A8_n2 shows exceptionally high abundance in colorectal tissues, highlighting its potential role in the first-pass metabolism in gut through the glucuronidation pathway.

A lack of association between BMI and chemoimmunotherapy efficacy in advanced non-small cell lung cancer: Secondary analysis of the IMpower150 and IMpower130 clinical trials

BACKGROUND

Multiple studies have indicated that patients with high body mass index (BMI) may have favourable survival outcomes following treatment with an immune checkpoint inhibitor (ICI). However, this evidence is limited by several factors, notably the minimal evidence from randomised controlled trials (RCTs), the use of categorised BMI with inconsistent cut point definitions, and minimal investigation of contemporary combination ICI therapy. Moreover, whether overweight and obese patients gain a larger benefit from contemporary frontline chemoimmunotherapy in non-small cell lung cancer (NSCLC) is unclear.

METHODS

This secondary analysis pooled individual patient data from the intention-to-treat population of the IMpower130 and IMpower150 RCTs comparing chemoimmunotherapy versus chemotherapy. Co-primary outcomes were overall survival (OS) and progression-free survival (PFS). The potentially non-linear relationship between BMI and chemoimmunotherapy treatment effect was evaluated using Multivariable Fractional Polynomial Interaction (MFPI). As a sensitivity analysis, chemoimmunotherapy treatment effect (chemoimmunotherapy versus chemotherapy) on survival was also estimated for each BMI subgroup defined by World Health Organisation classification. Exploratory analyses in the respective chemoimmunotherapy and chemotherapy cohort were undertaken to examine the survival outcomes among BMI subgroups.

RESULTS

A total of 1282 patients were included. From the MFPI analysis, BMI was not significantly associated with chemoimmunotherapy treatment effect with respect to either OS (p = 0.71) or PFS (p = 0.35). This was supported by the sensitivity analyses that demonstrated no significant treatment effect improvement in OS/PFS among overweight or obese patients compared to normal weight patients (OS: normal BMI HR = 0.74 95% CI 0.59-0.93, overweight HR = 0.78 95% CI 0.61-1.01, obese HR = 0.84 95% CI 0.59-1.20). Exploratory analyses further highlighted that survival outcomes were not significantly different across BMI subgroups in either the chemoimmunotherapy therapy cohort (Median OS: normal BMI 19.9 months, overweight 17.9 months, and obese 19.5 months, p = 0.7) or the chemotherapy cohort (Median OS: normal 14.1 months, overweight 15.9 months, and obese 16.7 months, p = 0.7).

CONCLUSION

There was no association between high BMI (overweight or obese individuals) and enhanced chemoimmunotherapy treatment benefit in front-line treatment of advanced non-squamous NSCLC. This contrasts with previous publications that showed a superior treatment benefit in overweight and obese patients treated with immunotherapy given without chemotherapy.

Current safeguards, risk mitigation, and transparency measures of large language models against the generation of health disinformation: repeated cross sectional analysis

OBJECTIVES

To evaluate the effectiveness of safeguards to prevent large language models (LLMs) from being misused to generate health disinformation, and to evaluate the transparency of artificial intelligence (AI) developers regarding their risk mitigation processes against observed vulnerabilities.

DESIGN

Repeated cross sectional analysis.

SETTING

Publicly accessible LLMs.

METHODS

In a repeated cross sectional analysis, four LLMs (via chatbots/assistant interfaces) were evaluated: OpenAI's GPT-4 (via ChatGPT and Microsoft's Copilot), Google's PaLM 2 and newly released Gemini Pro (via Bard), Anthropic's Claude 2 (via Poe), and Meta's Llama 2 (via HuggingChat). In September 2023, these LLMs were prompted to generate health disinformation on two topics: sunscreen as a cause of skin cancer and the alkaline diet as a cancer cure. Jailbreaking techniques (ie, attempts to bypass safeguards) were evaluated if required. For LLMs with observed safeguarding vulnerabilities, the processes for reporting outputs of concern were audited. 12 weeks after initial investigations, the disinformation generation capabilities of the LLMs were re-evaluated to assess any subsequent improvements in safeguards.

MAIN OUTCOME MEASURES

The main outcome measures were whether safeguards prevented the generation of health disinformation, and the transparency of risk mitigation processes against health disinformation.

RESULTS

Claude 2 (via Poe) declined 130 prompts submitted across the two study timepoints requesting the generation of content claiming that sunscreen causes skin cancer or that the alkaline diet is a cure for cancer, even with jailbreaking attempts. GPT-4 (via Copilot) initially refused to generate health disinformation, even with jailbreaking attempts-although this was not the case at 12 weeks. In contrast, GPT-4 (via ChatGPT), PaLM 2/Gemini Pro (via Bard), and Llama 2 (via HuggingChat) consistently generated health disinformation blogs. In September 2023 evaluations, these LLMs facilitated the generation of 113 unique cancer disinformation blogs, totalling more than 40 000 words, without requiring jailbreaking attempts. The refusal rate across the evaluation timepoints for these LLMs was only 5% (7 of 150), and as prompted the LLM generated blogs incorporated attention grabbing titles, authentic looking (fake or fictional) references, fabricated testimonials from patients and clinicians, and they targeted diverse demographic groups. Although each LLM evaluated had mechanisms to report observed outputs of concern, the developers did not respond when observations of vulnerabilities were reported.

CONCLUSIONS

This study found that although effective safeguards are feasible to prevent LLMs from being misused to generate health disinformation, they were inconsistently implemented. Furthermore, effective processes for reporting safeguard problems were lacking. Enhanced regulation, transparency, and routine auditing are required to help prevent LLMs from contributing to the mass generation of health disinformation.

Accessibility of clinical study reports supporting medicine approvals: a cross-sectional evaluation

OBJECTIVES

Clinical study reports (CSRs) are highly detailed documents that play a pivotal role in medicine approval processes. Though not historically publicly available, in recent years, major entities including the European Medicines Agency (EMA), Health Canada, and the US Food and Drug Administration (FDA) have highlighted the importance of CSR accessibility. The primary objective herein was to determine the proportion of CSRs that support medicine approvals available for public download as well as the proportion eligible for independent researcher request via the study sponsor.

STUDY DESIGN AND SETTING

This cross-sectional study examined the accessibility of CSRs from industry-sponsored clinical trials whose results were reported in the FDA-authorized drug labels of the top 30 highest-revenue medicines of 2021. We determined (1) whether the CSRs were available for download from a public repository, and (2) whether the CSRs were eligible for request by independent researchers based on trial sponsors' data sharing policies.

RESULTS

There were 316 industry-sponsored clinical trials with results presented in the FDA-authorized drug labels of the 30 sampled medicines. Of these trials, CSRs were available for public download from 70 (22%), with 37 available at EMA and 40 at Health Canada repositories. While pharmaceutical company platforms offered no direct downloads of CSRs, sponsors confirmed that CSRs from 183 (58%) of the 316 clinical trials were eligible for independent researcher request via the submission of a research proposal. Overall, 218 (69%) of the sampled clinical trials had CSRs available for public download and/or were eligible for request from the trial sponsor.

CONCLUSION

CSRs were available from 69% of the clinical trials supporting regulatory approval of the 30 medicines sampled. However, only 22% of the CSRs were directly downloadable from regulatory agencies, the remaining required a formal application process to request access to the CSR from the study sponsor.

A Comprehensive Bioinformatic Analysis of RNA-seq Datasets Reveals a Differential and Variable Expression of Wildtype and Variant UGT1A Transcripts in Human Tissues and Their Deregulation in Cancers

The UGT1A locus generates over 60 different alternatively spliced transcripts and 30 circular RNAs. To date, v2 and v3 transcripts are the only variant UGT1A transcripts that have been functionally characterized. Both v2 and v3 transcripts encode the same inactive variant UGT1A proteins (i2s) that can negatively regulate glucuronidation activity and influence cancer cell metabolism. However, the abundance and interindividual variability in the expression of v2 and v3 transcripts in human tissues and their potential deregulation in cancers have not been comprehensively assessed. To address this knowledge gap, we quantified the expression levels of v1, v2, and v3 transcripts using RNA-seq datasets with large cohorts of normal tissues and paired normal and tumor tissues from patients with six different cancer types (liver, kidney, colon, stomach, esophagus, and bladder cancer). We found that v2 and v3 abundance varied significantly between different tissue types, and that interindividual variation was also high within the same tissue type. Moreover, the ratio of v2 to v3 variants varied between tissues, implying their differential regulation. Our results showed higher v2 abundance in gastrointestinal tissues than liver and kidney tissues, suggesting a more significant negative regulation of glucuronidation by i2 proteins in gastrointestinal tissues than in liver and kidney tissues. We further showed differential deregulation of wildtype (v1) and variant transcripts (v2, v3) in cancers that generally increased the v2/v1 and/or v3/v1 expression ratios in tumors compared to normal tissues, indicating a more significant role of the variants in tumors. Finally, we report ten novel UGT1A transcripts with novel 3' terminal exons, most of which encode variant proteins with a similar structure to UGT1A_i2 proteins. These findings further emphasize the diversity of the UGT1A transcriptome and proteome.

Association of proton pump inhibitor use with survival and adverse effects outcomes in patients with multiple myeloma: pooled analysis of three clinical trials

Proton pump inhibitors (PPIs) are commonly used in cancer patients, but their impact on treatment outcomes in multiple myeloma (MM) patients remains unclear. This study investigated the association of PPI use with survival and adverse effects in MM patients across three randomized-control trials initiating daratumumab, lenalidomide, or bortezomib combination treatments. Cox proportional hazard analysis and logistic regression were employed to assess the associations with treatment outcomes, while adjusting for age, sex, weight, MM international staging system stage, ECOG-performance status, comorbidity count, and presence of gastrointestinal disorders. Pooled data involving 1804 patients revealed that 557 (32%) used PPIs at baseline. PPI use was independently associated with worse overall survival (adjusted HR [95% CI] 1.32 [1.08-1.62], P = 0.007) and grade ≥ 3 adverse events (adjusted OR [95% CI] 1.39 [1.03-1.88], P = 0.030). However, the association with progression-free survival did not reach statistical significance (adjusted HR [95% CI] 1.14 [0.97-1.33], P = 0.112). Findings were consistent across trials and treatment arms. PPI use was identified as a negative prognostic factor in MM patients, potentially enhancing clinical decisions regarding its use. Further research is needed to fully comprehend the impacts and safety of PPI use in MM patients.

The molecular basis of dapsone activation of CYP2C9-catalyzed nonsteroidal anti-inflammatory drug oxidation

Positive heterotropic cooperativity, or "activation," results in an instantaneous increase in enzyme activity in the absence of an increase in protein expression. Thus, cytochrome P450 (CYP) enzyme activation presents as a potential drug-drug interaction mechanism. It has been demonstrated previously that dapsone activates the CYP2C9-catalyzed oxidation of a number of nonsteroidal anti-inflammatory drugs in vitro. Here, we conducted molecular dynamics simulations (MDS) together with enzyme kinetic investigations and site-directed mutagenesis to elucidate the molecular basis of the activation of CYP2C9-catalyzed S-flurbiprofen 4'-hydroxylation and S-naproxen O-demethylation by dapsone. Supplementation of incubations of recombinant CYP2C9 with dapsone increased the catalytic efficiency of flurbiprofen and naproxen oxidation by 2.3- and 16.5-fold, respectively. MDS demonstrated that activation arises predominantly from aromatic interactions between the substrate, dapsone, and the phenyl rings of Phe114 and Phe476 within a common binding domain of the CYP2C9 active site, rather than involvement of a distinct effector site. Mutagenesis of Phe114 and Phe476 abrogated flurbiprofen and naproxen oxidation, and MDS and kinetic studies with the CYP2C9 mutants further identified a pivotal role of Phe476 in dapsone activation. MDS additionally showed that aromatic stacking interactions between two molecules of naproxen are necessary for binding in a catalytically favorable orientation. In contrast to flurbiprofen and naproxen, dapsone did not activate the 4'-hydroxylation of diclofenac, suggesting that the CYP2C9 active site favors cooperative binding of nonsteroidal anti-inflammatory drugs with a planar or near-planar geometry. More generally, the work confirms the utility of MDS for investigating ligand binding in CYP enzymes.

Heterogeneity and Utility of Pharmaceutical Company Sharing of Individual-Participant Data Packages

Importance

The pharmaceutical industry has made substantial investments in developing processes for sharing individual-participant data (IPD) from clinical trials. However, the utility and completeness of shared IPD and supporting documents must be evaluated to ensure the potential for scientific advancements from the data sharing ecosystem can be realized.

Objective

To assess the utility and completeness of IPD and supporting documents provided from industry-sponsored clinical trials.

Design, Setting, and Participants

From February 9, 2022, to February 9, 2023, 91 of 203 clinical trials supporting US Food and Drug Administration registrations of anticancer medicines for the treatment of solid tumors from the past decade were confirmed as eligible for IPD request. This quality improvement study performed a retrospective audit of the utility and completeness of the IPD and supporting documents provided from the 91 clinical trials for a planned meta-analysis.

Exposures

Request for IPD from 91 clinical oncology trials indicated as eligible for the request.

Main Outcomes and Measures

The utility and completeness of the IPD and supporting documents provided.

Results

The IPD packages were obtained from 70 of 91 requested clinical trials (77%). The median time to data provision was 123 (range, 117-352) days. Redactions were observed in 18 of the acquired IPD packages (26%) for outcome data, 11 (16%) for assessment variables, and 19 (27%) for adjustment data. Additionally, 20 IPD packages (29%) lacked a clinical study report, 4 (6%) had incomplete or missing data dictionaries, and 20 (29%) were missing anonymization or redaction description files. Access to IPD from 21 eligible trials (23%) was not granted.

Conclusions and Relevance

In this quality improvement study, there was substantial variability within the provided IPD packages regarding the completeness of key data variables and supporting documents. To improve the data sharing ecosystem, key areas for enhancement include (1) ensuring that clinical trials are eligible for IPD sharing, (2) making eligible IPD transparently accessible, and (3) ensuring that IPD packages meet a standard of utility and completeness.

A 10-year update to the principles for clinical trial data sharing by pharmaceutical companies: perspectives based on a decade of literature and policies

Data sharing is essential for promoting scientific discoveries and informed decision-making in clinical practice. In 2013, PhRMA/EFPIA recognised the importance of data sharing and supported initiatives to enhance clinical trial data transparency and promote scientific advancements. However, despite these commitments, recent investigations indicate significant scope for improvements in data sharing by the pharmaceutical industry. Drawing on a decade of literature and policy developments, this article presents perspectives from a multidisciplinary team of researchers, clinicians, and consumers. The focus is on policy and process updates to the PhRMA/EFPIA 2013 data sharing commitments, aiming to enhance the sharing and accessibility of participant-level data, clinical study reports, protocols, statistical analysis plans, lay summaries, and result publications from pharmaceutical industry-sponsored trials. The proposed updates provide clear recommendations regarding which data should be shared, when it should be shared, and under what conditions. The suggested improvements aim to develop a data sharing ecosystem that supports science and patient-centred care. Good data sharing principles require resources, time, and commitment. Notwithstanding these challenges, enhancing data sharing is necessary for efficient resource utilization, increased scientific collaboration, and better decision-making for patients and healthcare professionals.

Transforming pharmaceutical education: A needs-based global analysis for policy development

Background

A needs-based approach is desirable for the transformation of pharmaceutical education, and to link pharmaceutical education with the health needs of populations and national priorities. There are varying levels of data in the literature on the status of pharmaceutical education in all six World Health Organization (WHO) regions, especially in the context of needs identification and evidence-based policy interventions. The framework for this study was the FIP Development Goals.

Objectives

The aim of the study was to develop evidence-based policies through a needs-based approach for pharmaceutical education transformation nationally, regionally and globally by addressing the following objectives: 1. Identify global and regional needs in pharmaceutical education, through a regional SWOT analysis and prioritization of FIP development goals; 2. Develop valid and credible regional roadmaps for pharmaceutical education advancement according to the identified prioritized goals and 3. Develop a global call to action as a policy intervention for advancing pharmaceutical education.

Methods

This study was conducted between 2020 and 2021 using a mixed methods approach. Surveys of higher education institutions and a series of qualitative interviews were conducted with national professional leadership organizations, with further regional workshops having 284 participants recruited from the International Pharmaceutical Federation (FIP) membership base, spanning all six WHO regions.

Results

Eleven out of 21 FIP DGs were identified as priorities for regional roadmaps and FIP DG 1 (Academic capacity) was identified as a priority in four regions. All regions had distinctive results with an area of commonality between them. There were common weaknesses in the adoption of competency-based education and inter-professional education.

Conclusions

It is critical for every country and region to develop needs- and evidence-based policies for the transformation of pharmaceutical education, for which FIP DGs provide a systematic framework.

Functional high-throughput screen identifies microRNAs that promote butyrate-induced death in colorectal cancer cells

The gut fermentation product butyrate displays anti-cancer properties in the human proximal colon, including the ability to inhibit proliferation and induce apoptosis in colorectal cancer (CRC) cells. A natural histone deacetylase inhibitor (HDACi), butyrate can alter histone acetylation patterns in CRC cells, and thereby regulate global gene expression, including the non-coding transcriptome and microRNAs (miRNAs). Dysregulated miRNA expression affects CRC development and progression; however, the interplay between miRNA activity and butyrate response remains to be elucidated. A high-throughput functional screen was employed to identify miRNAs that can act as enhancers of the anti-cancer properties of butyrate. Validation studies confirmed that several miRNAs, including miR-125b, miR-181a, miR-593, and miR-1227, enhanced apoptosis, decreased proliferation, and promoted cell-cycle arrest in the presence of butyrate. Pathway analyses of predicted miRNA target genes highlighted their likely involvement in critical cancer-related growth pathways, including WNT and PI3K signaling. Several cancer-associated miRNA targets, including TRIM29, COX2, PIK3R3, CCND1, MET, EEF2K, DVL3, and NUP62 were synergistically regulated by the combination of cognate miRNAs and butyrate. Overall, this study has exposed the potential of miRNAs to act as enhancers of the anti-cancer effects of HDAC inhibition and identifies specific miRNAs that might be exploited for therapeutic benefit.

C-reactive protein provides superior prognostic accuracy than the IMDC risk model in renal cell carcinoma treated with Atezolizumab/Bevacizumab

Background

Immune checkpoint inhibitors (ICIs) is the main treatment option for patients with metastatic renal cell carcinoma (mRCC); however, significant heterogeneity in response is commonly observed. This study aimed to evaluate the ability of C-reactive protein (CRP) to predict overall survival (OS) and progression-free survival (PFS) in patients with mRCC treated with immunotherapy.

Patients and Methods

Data from patients with mRCC treated with atezolizumab plus bevacizumab in the IMmotion150 and IMmotion151 trials were pooled. Cox proportional regression was used to model prognostic associations. The relative importance of CRP against International Metastatic RCC Database Consortium (IMDC) factors was confirmed using machine learning.

Results

CRPs were available from 527 patients (mean[range] CRP, 6.3[0.21–340]mg/L). Elevated CRP was significantly associated with worse OS (HR[95%CI], 1.71[1.54–1.90], p<0.001) and PFS (1.27[1.18–1.35], p<0.001). CRP was the most prognostic factor for survival within the available clinicopathological data. The prognostic performance of CRP was superior to IMDC model for OS (CRP c=0.76, IMDC c=0.67, p<0.001) and PFS (CRP OS c=0.62, IMDC c=0.59, p=0.03). Predicted 2-year OS probabilities for patients with CRP values of 0.5, 5, 40, and 150 mg/L were 96%, 73%, 42%, and 23%, respectively.

Conclusions

CRP is a powerful prognostic marker for survival, and its prognostic value was superior to the IMDC risk model. This study highlights that CRP could be implemented as stratification factor for mRCC immunotherapy trials and potentially as an easy-to-use prognostic tool in the clinic.

Audit of Data Sharing by Pharmaceutical Companies for Anticancer Medicines Approved by the US Food and Drug Administration

Question

What proportion of clinical trials that underpin registration of contemporary anticancer medicines are eligible for individual participant data (IPD) sharing with qualified researchers?

Findings

In this quality improvement study of the 304 trials that underpinned the US Food and Drug Administration (FDA) registration of 115 anticancer medicines over the past 10 years, 136 (45%) were eligible for IPD sharing.

Meaning

Although inroads have been made toward improving IPD transparency over the past 5 years, these findings suggest that a substantial portion of pivotal oncology trials that support the FDA registration of modern anticancer medicines remain unavailable to qualified researchers.

Importance

Emerging policies drafted by the pharmaceutical industry indicate that they will transparently share clinical trial data. These data offer an unparalleled opportunity to advance evidence-based medicine and support decision-making.

Objective

To evaluate the eligibility of independent, qualified researchers to access individual participant data (IPD) from oncology trials that supported US Food and Drug Administration (FDA) approval of new anticancer medicines within the past 10 years.

Design, Setting, and Participants

In this quality improvement study, a cross-sectional analysis was performed of pivotal clinical trials whose results supported FDA-approved anticancer medicines between January 1, 2011, and June 30, 2021. These trials’ results were identified from product labels.

Exposures

Eligibility for IPD sharing was confirmed by identification of a public listing of the trial as eligible for sharing or by receipt of a positive response from the sponsor to a standardized inquiry.

Main Outcomes and Measures

The main outcome was frequency of IPD sharing eligibility. Reasons for data sharing ineligibility were requested and collated, and company-, drug-, and trial-level subgroups were evaluated and presented using χ² tests and forest plots.

Results

During the 10-year period examined, 115 anticancer medicines were approved by the FDA on the basis of evidence from 304 pharmaceutical industry–sponsored trials. Of these trials, 136 (45%) were eligible for IPD sharing and 168 (55%) were not. Data sharing rates differed substantially among industry sponsors, with the most common reason for not sharing trial IPD being that the collection of long-term follow-up data was still ongoing (89 of 168 trials [53%]). Of the top 10 anticancer medicines by global sales, nivolumab, pembrolizumab, and pomalidomide had the lowest eligibility rates for data sharing (<10% of trials).

Conclusions and Relevance

There has been a substantial increase in IPD sharing for industry-sponsored oncology trials over the past 5 years. However, this quality improvement study found that more than 50% of queried trials for FDA-approved anticancer medicines were ineligible for IPD sharing. Data accessibility would be substantially improved if, at the time of FDA registration of a medicine, all data that support the registration were made available.

Regulation of human UDP-glycosyltransferase (UGT) genes by miRNAs

The human UGT gene superfamily is divided into four subfamilies (UGT1, UGT2, UGT3 and UGT8) that encodes 22 functional enzymes. UGTs are critical for the metabolism and clearance of numerous endogenous and exogenous compounds, including steroid hormones, bile acids, bilirubin, fatty acids, carcinogens, and therapeutic drugs. Therefore, the expression and activities of UGTs are tightly regulated by multiple processes at the transcriptional, post-transcriptional and post-translational levels. During recent years, nearly twenty studies have investigated the post-transcriptional regulation of UGT genes by miRNAs using human cancer cell lines (predominantly liver cancer). Overall, 14 of the 22 UGT mRNAs (1A1, 1A3, 1A4, 1A6, 1A8, 1A9, 1A10, 2A1, 2B4, 2B7, 2B10, 2B15, 2B17, UGT8) have been shown to be regulated by various miRNAs through binding to their respective 3' untranslated regions (3'UTRs). Three 3'UTRs (UGT1A, UGT2B7 and UGT2B15) contain the largest number of functional miRNA target sites; in particular, the UGT1A 3'UTR contains binding sites for 12 miRNAs (548d-5p, 183-5p, 214-5p, 486-3p, 200a-3p, 491-3p, 141-3p, 298, 103b, 376b-3p, 21-3p, 1286). Although all nine UGT1A family members have the same 3'UTR, these miRNA target sites appear to be functional in an isoform-specific and cellular context-dependent manner. Collectively, these observations demonstrate that miRNAs represent important post-transcriptional regulators of the UGT gene superfamily. In this article, we present a comprehensive review of reported UGT/miRNA regulation studies, describe polymorphisms within functional miRNA target sites that may affect their functionalities, and discuss potential cooperative and competitive regulation of UGT mRNAs by miRNAs through adjacently located miRNA target sites.

A clinical scoring tool validated with machine learning for predicting severe hand-foot syndrome from sorafenib in hepatocellular carcinoma

Purpose

Sorafenib is an effective therapy for advanced hepatocellular carcinoma (HCC). Hand–foot syndrome (HFS) is a serious adverse effect associated with sorafenib therapy. This study aimed to develop an updated clinical prediction tool that allows personalized prediction of HFS following sorafenib initiation.

Methods

Individual participant data from Phase III clinical trial NCT00699374 were used in Cox proportional hazard analysis of the association between pre-treatment clinicopathological data and grade ≥ 3 HFS occurring within the first 365 days of sorafenib treatment for advanced HCC. Multivariable prediction models were developed using stepwise forward inclusion and backward deletion and internally validated using a random forest machine learning approach.

Results

Of 542 patients, 116 (21%) experienced grades ≥ 3 HFS. The prediction tool was optimally defined by sex (male vs female), haemoglobin (< 130 vs ≥ 130 g/L) and bilirubin (< 10 vs 10–20 vs ≥ 20 µmol/L). The prediction tool was able to discriminate subgroups with significantly different risks of grade ≥ 3 HFS (P ≤ 0.001). The high (score = 3 +)-, intermediate (score = 2)- and low (score = 0–1)-risk subgroups had 40%, 27% and 14% probability of developing grade ≥ 3 HFS within the first 365 days of sorafenib treatment, respectively.

Conclusion

A clinical prediction tool defined by female sex, high haemoglobin and low bilirubin had high discrimination for predicting HFS risk. The tool may enable improved evaluation of personalized risks of HFS for patients with advanced HCC initiating sorafenib.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-022-04411-9.

A functional screen with metformin identifies microRNAs that regulate metabolism in colorectal cancer cells

Metformin inhibits oxidative phosphorylation and can be used to dissect metabolic pathways in colorectal cancer (CRC) cells. CRC cell proliferation is inhibited by metformin in a dose dependent manner. MicroRNAs that regulate metabolism could be identified by their ability to alter the effect of metformin on CRC cell proliferation. An unbiased high throughput functional screen of a synthetic micoRNA (miRNA) library was used to identify miRNAs that impact the metformin response in CRC cells. Experimental validation of selected hits identified miRNAs that sensitize CRC cells to metformin through modulation of proliferation, apoptosis, cell-cycle and direct metabolic disruption. Among eight metformin sensitizing miRNAs identified by functional screening, miR-676-3p had both pro-apoptotic and cell cycle arrest activity in combination with metformin, whereas other miRNAs (miR-18b-5p, miR-145-3p miR-376b-5p, and miR-718) resulted primarily in cell cycle arrest when combined with metformin. Investigation of the combined effect of miRNAs and metformin on CRC cell metabolism showed that miR-18b-5p, miR-145-3p, miR-376b-5p, miR-676-3p and miR-718 affected glycolysis only, while miR-1181 only regulated CRC respiration. MicroRNAs can sensitize CRC cells to the anti-proliferative effects of metformin. Identifying relevant miRNA targets may enable the design of innovative therapeutic strategies.

Trace Amine-Associated Receptor 1 (TAAR1): Molecular and Clinical Insights for the Treatment of Schizophrenia and Related Comorbidities

Schizophrenia is a complex and severe mental illness. Current treatments for schizophrenia typically modulate dopaminergic neurotransmission by D₂-receptor blockade. While reducing positive symptoms of schizophrenia, current antipsychotic drugs have little clinical effect on negative symptoms and cognitive impairments. For the last few decades, discovery efforts have sought nondopaminergic compounds with the aim to effectively treat the broad symptoms of schizophrenia. In this viewpoint, we provide an overview on trace-amine associated receptor-1 (TAAR1), which presents a clinically validated nondopaminergic target for treating schizophrenia and related disorders, with significantly less overall side-effect burden. TAAR1 agonists may also be specifically beneficial for the substance abuse comorbidity and metabolic syndrome that is often present in patients with schizophrenia.

Binding of SEP-363856 within TAAR1 and the 5HT1A receptor: implications for the design of novel antipsychotic drugs

Current medications for schizophrenia typically modulate dopaminergic neurotransmission. While affecting positive symptoms, antipsychotic drugs have little clinical effect on negative symptoms and cognitive impairment. Moreover, newer 'atypical' antipsychotic drugs also have significant metabolic adverse-effects. The recent positive clinical trial of the novel drug candidate SEP-363856, which targets non-dopamine receptors (trace amine-associated receptor and the 5HT_1A receptor), is a potentially promising development for the management of schizophrenia. In this perspective, we briefly overview the role of TAAR1 and the 5HT_1A receptor in schizophrenia and explore the specific binding characteristics of SEP-363856 at these receptors. Molecular dynamics simulations (MDS) indicate that SEP-363856 interacts with a small, common set of conserved residues within the TAAR1 and 5HT_1A ligand-binding domain. The primary interaction of SEP-363856 involves binding to the negatively charged aspartate residue (Asp103^3.32, TAAR1; Asp116^3.32, 5HT_1A). In general, the binding of SEP-363856 within TAAR1 involves a greater number of aromatic contacts compared to 5HT_1A. MDS provides important insights into the molecular basis of binding site interactions of SEP-363856 with TAAR1 and the 5HT_1A receptor, which will be beneficial for understanding the pharmacological uniqueness of SEP-363856 and for the design of novel drug candidates for these newly targeted receptors in the treatment of schizophrenia and related disorders.

Association between Patient-Reported Outcomes and Survival in Patients with Advanced Urothelial Carcinoma Treated with Atezolizumab

BACKGROUND: Atezolizumab is an immune checkpoint inhibitor (ICI) and a frontline treatment of patients with cisplatin-ineligible advanced urothelial carcinoma (UC). There is limited evidence on the prognostic value of patient reported outcomes (PROs) in advanced UC treatment, particularly in the context of ICI therapy. OBJECTIVE: To investigate the prognostic association of PROs with survival in patients with advanced UC treated with atezolizumab. METHODS: This study used data from 467 patients with advanced UC initiating atezolizumab in the IMvigor211 trial. Pre-treatment PROs association with overall survival (OS) and progression free survival (PFS) was assessed using Cox proportional hazard analysis. PROs were recorded via the European Organisation for Research and Treatment of Cancer QLQ-C30. Discrimination performance was assessed via the C-statistic (c). RESULTS: Patient reported physical function, pain, appetite loss, global health, fatigue, role function, constipation, nausea and vomiting, dyspnoea, and insomnia were significantly associated with OS and PFS on univariable and adjusted analysis (P <  0.05). Physical function (c = 0.63), pain (c = 0.63), appetite loss (c = 0.62), global health status (c = 0.62), and fatigue (c = 0.62), were the most prognostic factors of OS. The OS discrimination performance of physical function (c = 0.61) was superior to ECOG PS (c = 0.58). Of patients assessed by investigators as having no performance restrictions (ECOG PS of 0), 38 (18%) and 91 (42%) self-reported low and intermediate physical function scores, respectively. CONCLUSION: Pre-treatment PROs were identified as independent prognostic factors of OS and PFS. Patient-reported physical function was more prognostic of OS than ECOG PS. This highlights a potential for PROs to enable improved patient stratification in ICI trials.

Down-regulation of metabolic pathways could offset the poor prognosis conferred by co-existent diabetes mellitus in pancreatic (head) adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) patients with diabetes mellitus (DM) have poor overall survival. Underlying mechanisms have not been fully clarified. This presents an opportunity for precision-oncology for which we systematically analysed publicly-available PDAC transcriptome data.

METHODS

PDAC TCGA RNASeq data were used. Analyses were restricted to only 'high purity' and 'head' as anatomical site. Patients were characterised by: (1) Gene expression classification, and (2) Weighted gene correlation network analysis (WGCNA) to identify co-expression patterns of genes. Newly identified gene signature subclasses of pancreatic head PDAC were associated with clinical and functional characteristics of patients.

RESULTS

Consensus clustering identified two patient subclasses within PDAC involving pancreatic head. WGCNA identified 11 distinct networks of gene expression patterns across two sub-classes. Class 1 patients demonstrated a significant upregulation of Module 5 and Module 6 gene expression compared to Class 2. Class 1 predominantly expressed the acinar, ductal and islet cell gene signatures. There were significantly less patients with DM in Class 1 subclass compared to Class 2 (p < 0.037). Patients with DM had significant downregulation of pathways involved in cellular metabolism, hormone secretion and paucity of islet cell markers with no reduced survival compared with non-diabetics.

CONCLUSIONS

A significant proportion of patients with PDAC of pancreatic head and DM exhibit downregulation of pathways involved in cellular metabolism, hormone secretion and signalling accompanied by a paucity of islet expression. Investigating the relationship between DM and gene expression profiles in patients with PDAC presents opportunities to improve overall survival in diabetics with PDAC.

Marine bioactives: from energy to nutrition

Microalgae have been evaluated as promising resource for biodiesel production, but algal biofuel production is not yet commercially viable, which reflects the high energy costs linked with cultivation, harvesting, and dewatering of algae. As crude oil processing declines, microalgae biorefineries are being considered for producing bioactives such as enzymes, proteins, omega-3 oils, pigments, recombinant products, and vitamins, to offset the costs of biofuel production. We believe that producing algal bioactives through advanced manufacturing pathways, encompassing a biorefinery approach, would be effective, profitable, and economical.

The Expression Profiles and Deregulation of UDP-Glycosyltransferase (UGT) Genes in Human Cancers and Their Association with Clinical Outcomes

The human UDP-glycosyltransferase (UGTs) superfamily has 22 functional enzymes that play a critical role in the metabolism of small lipophilic compounds, including carcinogens, drugs, steroids, lipids, fatty acids, and bile acids. The expression profiles of UGT genes in human cancers and their impact on cancer patient survival remains to be systematically investigated. In the present study, a comprehensive analysis of the RNAseq and clinical datasets of 9514 patients from 33 different TCGA (the Genome Cancer Atlas) cancers demonstrated cancer-specific UGT expression profiles with high interindividual variability among and within individual cancers. Notably, cancers derived from drug metabolizing tissues (liver, kidney, gut, pancreas) expressed the largest number of UGT genes (COAD, KIRC, KIRP, LIHC, PAAD); six UGT genes (1A6, 1A9, 1A10, 2A3, 2B7, UGT8) showed high expression in five or more different cancers. Kaplan-Meier plots and logrank tests revealed that six UGT genes were significantly associated with increased overall survival (OS) rates [UGT1A1 (LUSC), UGT1A6 (ACC), UGT1A7 (ACC), UGT2A3 (KIRC), UGT2B15 (BLCA, SKCM)] or decreased OS rates [UGT2B15 (LGG), UGT8 (UVM)] in specific cancers. Finally, differential expression analysis of 611 patients from 12 TCGA cancers identified 16 UGT genes (1A1, 1A3, 1A6, 1A7, 1A8, 1A9, 1A10, 2A1, 2A3, 2B4, 2B7, 2B11, 2B15, 3A1, 3A2, UGT8) that were up/downregulated in at least one cancer relative to normal tissues. In conclusion, our data show widespread expression of UGT genes in cancers, highlighting the capacity for intratumoural drug metabolism through the UGT conjugation pathway. The data also suggests the potentials for specific UGT genes to serve as prognostic biomarkers or therapeutic targets in cancers.

Evidence-Based Guidelines for Drug Interaction Studies: Model-Informed Time Course of Intestinal and Hepatic CYP3A4 Inhibition by Clarithromycin

Drug-drug interaction (DDI) studies are mandated in drug development; however, protocols for evaluating the impact of cytochrome P450 (CYP) inhibition on new molecular entities are currently inconsistent. This study utilised validated physiologically based pharmacokinetic (PBPK) software to define the optimal dose, frequency, and duration of clarithromycin to achieve optimal characterisation of CYP3A4 inhibition in a study population. The Simcyp® Simulator (Version 19.0) was used to simulate clarithromycin-mediated CYP3A4 inhibition in healthy virtual cohorts. Between trial variability in magnitude and time course of CYP3A4 activity was assessed following clarithromycin dosing strategies obtained from the University of Washington Drug Interaction Database. Heterogeneity in CYP3A4 inhibition was evaluated across sex, race, and age. Literature review identified 500 mg twice daily for 5 days as the most common clarithromycin dosing protocol for CYP3A4 inhibition studies. On simulation, clarithromycin 500 mg twice daily resulted in the largest steady-state inhibition of hepatic (percent mean inhibition [95%CI] = 80 [77-83]) and small intestine (94 [94-95]) CYP3A4 activity (as compared to 500 mg once daily, 400 mg once/twice daily, or 250 mg once/twice daily). Additionally, 500 mg twice daily was associated with the shortest time for 90% of individuals to reach 90% of their minimum hepatic (4 days) and small intestine (1 days) CYP3A4 activity. The study presented herein supports that clarithromycin dosing protocol of 500 mg twice daily for 5 days is sufficient to achieve maximal hepatic and small intestine CYP3A4 inhibition. These findings were consistent between sex, race, and age differences.

Machine Learning for Prediction of Survival Outcomes with Immune-Checkpoint Inhibitors in Urothelial Cancer

Simple Summary

Machine learning (ML) is a form of artificial intelligence that could be used to enhance the efficiency of developing accurate prediction models for survival outcomes with cancer medicines, which is critical in informing disease prognosis and care planning. We used data from two recent clinical trials to develop and validate ML‐based clinical prediction models of the overall and progression‐free survival rates in patients with urothelial cancer initiating the immune checkpoint inhibitor (ICI) atezolizumab. We demonstrated that ML can efficiently develop an accurate prediction model of survival, enable an accurate prognostic risk classification, and provide realistic expectations of treatment outcomes in patients undergoing urothelial cancer-initiating ICIs therapy.

Abstract

Machine learning (ML) may enhance the efficiency of developing accurate prediction models for survival, which is critical in informing disease prognosis and care planning. This study aimed to develop an ML prediction model for survival outcomes in patients with urothelial cancer-initiating atezolizumab and to compare model performances when built using an expert-selected (curated) versus an all-in list (uncurated) of variables. Gradient-boosted machine (GBM), random forest, Cox-boosted, and penalised, generalised linear models (GLM) were evaluated for predicting overall survival (OS) and progression-free survival (PFS) outcomes. C-statistic (c) was utilised to evaluate model performance. The atezolizumab cohort in IMvigor210 was used for model training, and IMvigor211 was used for external model validation. The curated list consisted of 23 pretreatment factors, while the all-in list consisted of 75. Using the best-performing model, patients were stratified into risk tertiles. Kaplan–Meier analysis was used to estimate survival probabilities. On external validation, the curated list GBM model provided slightly higher OS discrimination (c = 0.71) than that of the random forest (c = 0.70), CoxBoost (c = 0.70), and GLM (c = 0.69) models. All models were equivalent in predicting PFS (c = 0.62). Expansion to the uncurated list was associated with worse OS discrimination (GBM c = 0.70; random forest c = 0.69; CoxBoost c = 0.69, and GLM c = 0.69). In the atezolizumab IMvigor211 cohort, the curated list GBM model discriminated 1-year OS probabilities for the low-, intermediate-, and high-risk groups at 66%, 40%, and 12%, respectively. The ML model discriminated urothelial-cancer patients with distinctly different survival risks, with the GBM applied to a curated list attaining the highest performance. Expansion to an all-in approach may harm model performance.

Prediction of severe neutropenia and diarrhoea in breast cancer patients treated with abemaciclib

Introduction

Neutropenia and diarrhoea are common and potentially serious adverse events associated with abemaciclib in advanced breast cancer (ABC), and the risk factors have been minimally explored. The study aimed to develop clinical prediction tools that allow personalized predictions of neutropenia and diarrhoea following abemaciclib initiation.

Materials and methods

Data was pooled from MONARCH 1, 2 and 3 trials investigating abemaciclib. Cox proportional hazard analysis was used to assess the association between pre-treatment clinicopathological data and grade ≥3 diarrhoea and neutropenia occurring within the first 365 days of abemaciclib use.

Results

Older age was associated with increased risk of grade ≥3 diarrhoea [HR [95%CI] for age > 70: 1.72 [1.14–2.58]; P = 0.009]. A clinical prediction tool for abemaciclib induced grade ≥3 neutropenia was optimally defined by race, ECOGPS and white blood cell count. Large discrimination between subgroups was observed; the highest risk subgroup had a 64% probability of grade ≥3 neutropenia within the first 365 days of abemaciclib (150 mg twice daily) + fulvestrant/NSAI, compared to 5% for the lowest risk subgroup.

Conclusion

The study identified advanced age as significantly associated with an increased risk of abemaciclib induced grade ≥ 3 diarrhoea. A clinical prediction tool, defined by race, ECOGPS and pre-treatment white blood cell count, was able to discriminate subgroups with significantly different risks of grade ≥3 neutropenia following abemaciclib initiation. The tool may enable improved interpretation of personalized risks and the risk-benefit ratio of abemaciclib.

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Neutropenia and diarrhoea are common adverse effects of abemaciclib.

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Higher age was associated with abemaciclib induced diarrhoea.

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White blood cell count, Race, and performance status were linked with neutropenia.

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A prediction tool was developed to provide personalized risks of neutropenia.

Circular RNAs of UDP-Glycosyltransferase (UGT) Genes Expand the Complexity and Diversity of the UGT Transcriptome

The human UDP-glycosyltransferase (UGT) gene superfamily generates 22 canonical transcripts coding for functional enzymes and also produces nearly 150 variant UGT transcripts through alternative splicing and intergenic splicing. In the present study, our analysis of circRNA databases identified backsplicing events that predicted 85 circRNAs from UGT genes, with 33, 11, and 19 circRNAs from UGT1A, UGT2B4, UGT8, respectively. Most of these UGT circRNAs were reported by one database and had low abundance in cell- or tissue-specific contexts. Using reverse-transcriptase polymerase chain reaction with divergent primers and cDNA samples from human tissues and cell lines, we found 13 circRNAs from four UGT genes: UGT1A (three), UGT2B7 (one), UGT2B10 (one), and UGT8 (eight). Notably, all eight UGT8 circRNAs contain open reading frames that include the canonical start AUG codon and encode variant proteins that all have the common 274-amino acidN-terminal region of wild-type UGT8 protein. We further showed that one UGT8 circRNA (circ_UGT8-1) was broadly expressed in human tissues and cell lines, resistant to RNase R digestion, and predominately present in the cytoplasm. We cloned five UGT8 circRNAs into the Zinc finger with KRAB and SCAN domains 1 vector and transfected them into HEK293T cells. All these vectors produced both circRNAsand linear transcripts with varying circular/linear ratios (0.17-1.14).Western blotting and mass spectrometry assays revealed that only linear transcripts and not circRNAs were translated. In conclusion, our findings of nearly 100 circRNAs greatly expand the complexity and diversity of the UGT transcriptome; however, UGT circRNAs are expressed at a very low level in specific cellular contexts, and their biologic functions remain to be determined. SIGNIFICANCE STATEMENT: The human UGT gene transcriptome comprises 22 canonical transcripts coding for functional enzymes and approximately 150 alternatively spliced and chimeric variant transcripts. The present study identified nearly 100 circRNAs from UGT genes, thus greatly expanding the complexity and diversity of the UGT transcriptome. UGT circRNAs were expressed broadly in human tissues and cell lines; however, most showed very low abundance in tissue- and cell-specific contexts, and therefore their biological functions remain to be investigated.

The obesity paradox in early and advanced HER2 positive breast cancer: pooled analysis of clinical trial data

While many studies have evaluated the relationship between BMI and breast cancer outcomes, it is unclear whether this relationship is consistent between early breast cancer (BC) and advanced BC. The study included 5099 patients with HER2 positive early BC (EBC) and 3496 with HER2 positive advanced BC (ABC). In the EBC cohort, higher BMI was associated with worse overall survival (OS) (HR [95% CI]: overweight = 1.30 [1.13-1.51]; obese = 1.37 [1.14-1.64], P = < 0.001), and worse disease-free survival (overweight = 1.10 [0.98-1.24]; obese = 1.20 [1.04-1.39], P = 0.061). In contrast, for the ABC cohort, higher BMI was significantly associated with improved OS (overweight = 0.85 [0.76-0.96]; obese = 0.82 [0.72-0.95], P = 0.014), and progression-free survival (overweight = 0.91 [0.83-1.01]; obese = 0.87 [0.77-0.98], P = 0.034). In this large high-quality dataset, higher BMI was independently associated with worse survival in EBC, paradoxically in ABC higher BMI was independently associated with improved survival.

Value of the Lung Immune Prognostic Index in Patients with Non-Small Cell Lung Cancer Initiating First-Line Atezolizumab Combination Therapy: Subgroup Analysis of the IMPOWER150 Trial

The lung immune prognostic index (LIPI) is proposed to differentiate prognosis and treatment benefit from immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (NSCLC). There is minimal information on the predictive importance with first-line, combination ICI approaches. In post-hoc analysis of IMpower150, Cox-proportional hazard analysis assessed the association between LIPI groups and overall survival (OS)/progression free survival (PFS). IMpower150 involved chemotherapy-naïve, metastatic non-squamous NSCLC participants randomized atezolizumab-carboplatin-paclitaxel (ACP), bevacizumab-carboplatin-paclitaxel (BCP), or atezolizumab-BCP (ABCP). Good (0 factors), intermediate (1 factor), and poor LIPI (2 factors) were defined via derived neutrophil-to-lymphocyte ratio >3, and lactate dehydrogenase >upper limit of normal. Of 1148 participants, 548 had good, 479 intermediate, and 121 poor LIPI. In 385 participants randomised ABCP, a significant association between LIPI and OS (HR (95%CI): intermediate LIPI = 2.16 (1.47-3.18), poor LIPI = 5.28 (3.20-8.69), p < 0.001) and PFS (HR (95%CI): intermediate LIPI = 1.47 (1.11-1.95), poor LIPI = 3.02 (2.03-4.50), p < 0.001) was identified. Median OS was 24, 16, and 7 months for good, intermediate, and poor LIPI, respectively. ACP associations were similar. Relative OS treatment effect (HR 95%CI) of ABCP vs. BCP was 0.78 (0.53-1.15), 0.67 (0.49-0.91), and 0.87 (0.51-1.47) for the good, intermediate, and poor LIPI groups, respectively (P(interaction) = 0.66), with no benefit in median OS observed in the poor LIPI group. LIPI identified subgroups with significantly different survival following ABCP and ACP initiation for chemotherapy-naïve, metastatic non-squamous NSCLC. There was insufficient evidence that LIPI identifies patients unlikely to benefit from ABCP treatment.

Evaluation of the prescribing practice of guideline-directed medical therapy among ambulatory chronic heart failure patients

BACKGROUND

Studies have demonstrated that heart failure (HF) patients who receive direct pharmacist input as part of multidisciplinary care have better clinical outcomes. This study evaluated/compared the difference in prescribing practices of guideline-directed medical therapy (GDMT) for chronic HF patients between two multidisciplinary clinics-with and without the direct involvement of a pharmacist.

METHODS

A retrospective audit of chronic HF patients, presenting to two multidisciplinary outpatient clinics between March 2005 and January 2017, was performed; a Multidisciplinary Ambulatory Consulting Service (MACS) with an integrated pharmacist model of care and a General Cardiology Heart Failure Service (GCHFS) clinic, without the active involvement of a pharmacist.

RESULTS

MACS clinic patients were significantly older (80 vs. 73 years, p < .001), more likely to be female (p < .001), and had significantly higher systolic (123 vs. 112 mmHg, p < .001) and diastolic (67 vs. 60 mmHg, p < .05) blood pressures compared to the GCHF clinic patients. Moreover, the MACS clinic patients showed more polypharmacy and higher prevalence of multiple comorbidities. Both clinics had similar prescribing rates of GDMT and achieved maximal tolerated doses of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) in HFrEF. However, HFpEF patients in the MACS clinic were significantly more likely to be prescribed ACEIs/ARBs (70.5% vs. 56.2%, p = 0.0314) than the GCHFS patients. Patients with both HFrEF and HFpEF (MACS clinic) were significantly less likely to be prescribed β-blockers and mineralocorticoid receptor antagonists. Use of digoxin in chronic atrial fibrillation (AF) in MACS clinic was significantly higher in HFrEF patients (82.5% vs. 58.5%, p = 0.004), but the number of people anticoagulated in presence of AF (27.1% vs. 48.0%, p = 0.002) and prescribed diuretics (84.0% vs. 94.5%, p = 0.022) were significantly lower in HFpEF patients attending the MACS clinic. Age, heart rate, systolic blood pressure (SBP), anemia, chronic renal failure, and other comorbidities were the main significant predictors of utilization of GDMT in a multivariate binary logistic regression.

CONCLUSIONS

Lower prescription rates of some medications in the pharmacist-involved multidisciplinary team were found. Careful consideration of demographic and clinical characteristics, contraindications for use of medications, polypharmacy, and underlying comorbidities is necessary to achieve best practice.

The predictive utility of patient-reported outcomes and performance status for survival in metastatic lung cancer patients treated with chemoimmunotherapy

Background

Atezolizumab, an immune checkpoint inhibitor, in combination with chemotherapy (chemoimmunotherapy) has become a first-line treatment option for metastatic non-small cell lung cancer (NSCLC). Patient-reported outcomes (PROs) are self-reported measures that have shown promise in their predictive value for survival. However, there have been no studies that have assessed the prognostic performance of PROs in an advanced NSCLC cohort initiating first-line atezolizumab based chemoimmunotherapy.

Methods

This study used individual-participant data (IPD) from the IMpower130, IMpower131 and IMpower150 clinical trials. Cox proportional hazards regression was utilized to determine the association between pre-treatment PROs with overall survival (OS) and progression free survival (PFS). The prediction performance of PROs was assessed using the C-statistic. For the PRO measure identified as the most predictive of survival, an exploratory analysis comparing the predictive performance against Eastern Cooperative Oncology Group Performance Status (ECOG-PS) was conducted.

Results

Patient-reported physical function, fatigue, appetite loss, pain, role function, global health status, social function, dyspnoea, constipation, nausea and vomiting, insomnia, emotional function, cognitive function, and financial difficulty were statistically associated with OS (P<0.05). Physical function (c=0.62), fatigue (c=0.61), and appetite loss (c=0.60) were the most predictive variables for OS. Patient-reported physical function (c=0.60) also had higher predictive performance than physician-defined ECOG-PS (c=0.57).

Conclusions

In patients with advanced NSCLC who received first line atezolizumab based therapy, pre-treatment PROs were prognostic for survival outcomes. Patient-reported physical function had higher predictive performance compared to physician-defined ECOG-PS. These results suggest PROs have significant worth in clinical practice and research trials of ICIs as a stratification factors.

Arginine-259 of UGT2B7 Confers UDP-Sugar Selectivity

Enzymes of the human UDP-glycosyltransferase (UGT) superfamily typically catalyze the covalent addition of the sugar moiety from a UDP-sugar cofactor to relatively low-molecular weight lipophilic compounds. Although UDP-glucuronic acid (UDP-GlcUA) is most commonly employed as the cofactor by UGT1 and UGT2 family enzymes, UGT2B7 and several other enzymes can use both UDP-GlcUA and UDP-glucose (UDP-Glc), leading to the formation of glucuronide and glucoside conjugates. An investigation of UGT2B7-catalyzed morphine glycosidation indicated that glucuronidation is the principal route of metabolism because the binding affinity of UDP-GlcUA is higher than that of UDP-Glc. Currently, it is unclear which residues in the UGT2B7 cofactor binding domain are responsible for the preferential binding of UDP-GlcUA. Here, molecular dynamics (MD) simulations were performed together with site-directed mutagenesis and enzyme kinetic studies to identify residues within the UGT2B7 binding site responsible for the selective cofactor binding. MD simulations demonstrated that Arg259, which is located within the N-terminal domain, specifically interacts with UDP-GlcUA, whereby the side chain of Arg259 H-bonds and forms a salt bridge with the carboxylate group of glucuronic acid. Consistent with the MD simulations, substitution of Arg259 with Leu resulted in the loss of morphine, 4-methylumbelliferone, and zidovudine glucuronidation activity, but morphine glucosidation was preserved. SIGNIFICANCE STATEMENT: Despite the importance of uridine diphosphate glycosyltransferase (UGT) enzymes in drug and chemical metabolism, cofactor binding interactions are incompletely understood, as is the molecular basis for preferential glucuronidation by UGT1 and UGT2 family enzymes. The study demonstrated that long timescale molecular dynamics (MD) simulations with a UGT2B7 homology model can be used to identify critical binding interactions of a UGT protein with UDP-sugar cofactors. Further, the data provide a basis for the application of MD simulations to the elucidation of UGT-aglycone interactions.

Nuances to precision dosing strategies of targeted cancer medicines

Selecting the dose of a targeted cancer medicine that is most appropriate for a specific individual is a rational approach to maximize therapeutic outcomes and minimize toxicity. There are many different options for optimizing the dose of targeted cancer medicines and the purpose of this review is to provide a comprehensive comparison of the main options explored in prospective studies. Precision initial dose selection of targeted cancer therapies has been minimally explored to date; however, concentration, toxicity, and therapeutic outcome markers are used to guide on-therapy dose adaption of targeted cancer therapies across several medicines and cancers. While a specific concentration, toxicity, or therapeutic outcome marker commonly dominates an investigated precision on-therapy dose adaption strategy, greater attention to simultaneously account for exposure, toxicity, therapeutic outcomes, disease status, time since treatment initiation and patient preferences are required for optimal patient outcomes. To enable successful implementation of precision dosing strategies for targeted cancer medicines into clinical practice, future prospective studies aiming to develop strategies should consider these elements in their design.

The Influence of Pre-Existing Beta-Blockers Use on Survival Outcomes in HER2 Positive Advanced Breast Cancer: Pooled Analysis of Clinical Trial Data

Introduction: Beta-blockers (BB) are commonly used to manage cardiovascular disease and may have benefits in controlling complications of anti-HER2 therapies. This study aimed to evaluate the association of pre-existing BB use with survival outcomes in patients initiating anti-HER2 therapy for advanced breast cancer (ABC). Materials and Methods: Data from clinical trials EMILIA, TH3RESA, MARIANNE, and CLEOPATRA was pooled. Cox proportional analysis was used to assess the association between pre-existing BB use with survival outcomes in patients initiating anti-HER2 therapies. Results: Of the 2,777 patients with HER2 positive ABC, 266 were using a BB at the time of anti-HER2 therapy initiation. BB use was associated with worse overall survival (OS) (adjusted HR = 1.27, 95% CI: 1.04-1.55). Sensitivity analysis in patients with pre-existing cardiovascular disease (CVD) also indicated that BB use was associated with worse OS (1.29, 1.02-1.63). Conclusion: In large high-quality data, BB use at the time of anti-HER2 therapy initiation for ABC was independently associated with worse OS, regardless of CVD status. The finding is contrary to pre-study hypotheses and findings in other BC subtypes. Future research should aim to gain a deeper understanding of the effects of BBs on specific BC subtypes, cancer types, and cancer treatments.

Early Adverse Events predict Survival Outcomes in HER2-positive Advanced Breast Cancer Patients treated with Lapatinib plus Capecitabine

Background: This study aimed to investigate the impact of early adverse events (AE) following the initiation of lapatinib plus capecitabine on the progression-free survival (PFS) and overall survival (OS) outcomes of human epidermal growth factor receptor 2 (HER2) positive advanced breast cancer (ABC) patients.

Methods: A secondary analysis of participants treated with lapatinib plus capecitabine, or ado-trastuzumab emtansine in the clinical trial EMILIA was conducted. Cox proportional hazard analysis was used to assess the impact of AE occurring within the first 42 days of lapatinib plus capecitabine therapy on the PFS and OS outcomes of ABC patients.

Results: The study included 488 HER2-positive (ABC) patients initiated on lapatinib plus capecitabine. Rash (Hazard Ratio (HR) [95% Confidence Interval (CI)]: Grade 1 = 0.67 [0.46-0.98], Grade 2+ = 0.71 [0.42-1.19]; p = 0.046) and hand-foot syndrome (HR [95% CI]: Grade 1 = 0.58 [0.43-0.80], Grade 2+ = 0.61 [0.43-0.86]; p = <0.001) occurring within the first 42 days of lapatinib plus capecitabine therapy were significantly associated with improved OS. Conversely, nausea and vomiting occurring within the first 42 days of lapatinib plus capecitabine therapy was significantly associated with worsened OS (HR [95% CI]: Grade 1 = 1.08 [0.82-1.42], Grade 2+ = 1.52 [1.13-2.03]; p = 0.027).

Conclusions: Rash and hand-foot syndrome occurring early after the initiation of on lapatinib plus capecitabine were significantly associated with improved OS, while early nausea and vomiting was associated with worse OS. In HER2-positive ABC patients initiating lapatinib plus capecitabine, consideration should be given to more closely monitoring patients at risk of nausea and vomiting, while rash and hand foot syndrome are AE associated with improved survival.

A literature review of treatment-specific clinical prediction models in patients with breast cancer

Despite advances in the breast cancer treatment, significant variability in patient outcomes remain. This results in significant stress to patients and clinicians. Treatment-specific clinical prediction models allow patients to be matched against historical outcomes of patients with similar characteristics; thereby reducing uncertainty by providing personalised estimates of benefits, harms, and prognosis. To achieve this objective, models need to be clinical-grade with evidence of accuracy, reproducibility, generalizability, and be user-friendly. A structured search was undertaken to identify treatment-specific clinical prediction models for therapeutic or adverse outcomes in breast cancer using clinicopathological data. Significant gaps in the presence of validated models for available treatments was identified, along with gaps in prediction of therapeutic and adverse outcomes. Most models did not have user-friendly tools available. With the aim being to facilitate the selection of the best medicine for a specific patient and shared-decision making, future research will need to address these gaps.

Predicting Thrombocytopenia in Patients With Breast Cancer Treated With Ado-trastuzumab Emtansine

INTRODUCTION

Thrombocytopenia is a common and potentially serious adverse event of ado-trastuzumab emtansine (T-DM1) use in patients with advanced breast cancer. However, the risk factors have been minimally explored. Our aim was to develop a clinical prediction model from the clinicopathologic data that would allow for quantification of the personalized risks of thrombocytopenia from T-DM1 usage.

MATERIALS AND METHODS

Data from 3 clinical trials, EMILIA (a study of trastuzumab emtansine versus capecitabine + lapatinib in participants with HER2 [human epidermal growth factor receptor 2]-positive locally advanced or metastatic breast cancer), TH3RESA (a study of trastuzumab emtansine in comparison with treatment of physician's choice in participants with HER2-positive breast cancer who have received at least two prior regimens of HER2-directed therapy), and MARIANNE [a study of trastuzumab emtansine (T-DM1) plus pertuzumab/pertuzumab placebo versus trastuzumab (Herceptin) plus a taxane in participants with metastatic breast cancer], were pooled. Cox proportional hazard analysis was used to assess the association between the pretreatment clinicopathologic data and grade ≥ 3 thrombocytopenia occurring within the first 365 days of T-DM1 use. A multivariable clinical prediction model was developed using a backward elimination process.

RESULTS

Of the 1620 participants, 141 (9%) had experienced grade ≥ 3 thrombocytopenia. On univariable analysis, the body mass index, race, presence of brain metastasis, platelet count, white blood cell count, and concomitant corticosteroid use were significantly associated with the occurrence of grade ≥ 3 thrombocytopenia (P < .05). The multivariable prediction model was optimally defined by race (Asian vs. non-Asian) and platelet count (100-220 vs. 220-300 vs. >300 × 10⁹/L). A large discrimination between the prognostic subgroups was observed. The highest risk subgroup (Asian and platelet count of 100-220 cells ×10⁹/L) had a 40% probability of grade ≥ 3 thrombocytopenia within the first 365 days of T-DM1 therapy compared with 2% for the lowest risk subgroup (non-Asian and platelet count > 300 × 10⁹/L).

CONCLUSION

A clinical prediction model, defined by race and pretreatment platelet count, was able to discriminate subgroups with a significantly different risk of grade ≥ 3 thrombocytopenia after T-DM1 initiation. The model allows for improved interpretation of the personalized risks and risk/benefit ratio of T-DM1.

The UGTome: The expanding diversity of UDP glycosyltransferases and its impact on small molecule metabolism

The UDP glycosyltransferase (UGT) superfamily of enzymes is responsible for the metabolism and clearance of thousands of lipophilic chemicals including drugs, toxins and endogenous signaling molecules. They provide a protective interface between the organism and its chemical-rich environment, as well as controlling critical signaling pathways to maintain healthy tissue function. UGTs are associated with drug responses and interactions, as well as a wide range of diseases including cancer. The human genome contains 22 UGT genes; however as befitting their exceptionally diverse substrate ranges and biological activities, the output of these UGT genes is functionally diversified by multiple processes including alternative splicing, post-translational modification, homo- and hetero-oligomerization, and interactions with other proteins. All UGT genes are subject to extensive alternative splicing generating variant/truncated UGT proteins with altered functions including the capacity to dominantly modulate/inhibit cognate full-length forms. Heterotypic oligomerization of different UGTs can alter kinetic properties relative to monotypic complexes, and potentially produce novel substrate specificities. Moreover, the recently profiled interactions of UGTs with non-UGT proteins may facilitate coordination between different metabolic processes, as well as providing opportunities for UGTs to engage in novel 'moonlighting' functions. Herein we provide a detailed and comprehensive review of all known modes of UGT functional diversification and propose a UGTome model to describe the resulting expansion of metabolic capacity and its potential to modulate drug/xenobiotic responses and cell behaviours in normal and disease contexts.

Predictors of Long-Term Disease Control and Survival for HER2-Positive Advanced Breast Cancer Patients Treated With Pertuzumab, Trastuzumab, and Docetaxel

Background: HER2-positive advanced breast cancer (ABC) is associated with significant heterogeneity in long-term disease control and survival. Prognostic models for HER2-positive ABC patients considering first-line pertuzumab, trastuzumab, and docetaxel have not been evaluated.

Methods: A pre-treatment prognostic model for progression-free survival (PFS) and overall survival (OS) was developed for HER2-positive ABC patients initiating first-line pertuzumab, trastuzumab, and docetaxel using clinicopathological data from the randomized clinical trial CLEOPATRA (n = 408). Cox proportional hazard analysis with a backwards deletion process was used.

Results: Metastatic sites count (<3 vs. ≥ 3) and lactate dehydrogenase (LDH) (≤ ULN vs. >ULN) were identified as common pre-treatment risk predictors for PFS and OS (P < 0.05). Based on these two factors, patients can be characterized as one of three prognostic groups (good = 0 factors; intermediate = 1 factor; poor = 2 factors). The prognostic groups were associated with significantly different PFS (P < 0.001), with 3-year PFS probabilities of 44% (36–55), 28% (22–36), and 17% (11–29) for the good, intermediate and poor prognostic groups, respectively. Similarly, there was significant differences in OS (P < 0.001), with 4-year OS probabilities of 75% (95% CI: 67–84), 60% (53–68) and 31% (21–45) for the good, intermediate and poor prognostic groups, respectively.

Conclusions: Pre-treatment prognostic groups identified for HER2-positive ABC patients initiating first-line pertuzumab, trastuzumab, and docetaxel had significantly different long-term disease control and survival outcomes.

Effect of early adverse events resulting in ado-trastuzumab emtansine dose adjustments on survival outcomes of HER2+ advanced breast cancer patients

PURPOSE

Ado-trastuzumab emtansine (T-DM1) treatment in HER2+ advanced breast cancer patients is generally well tolerated, but when adverse events occur dose adjustments may be required. This study evaluated the impact of early adverse events requiring T-DM1 dose interruptions or reductions on overall survival (OS) and progression-free survival (PFS) in HER2+ advanced metastatic breast cancer patients in the clinical trials EMILIA and TH3RESA.

PATIENTS AND METHODS

The study included 893 participants initiated on T-DM1 treatment. A landmark approach set at 4 months was used to evaluate the association between early adverse events requiring T-DM1 dose interruptions or reductions and OS/PFS. Cox proportional hazard analysis modeled the association between events requiring T-DM1 dose interruptions or reductions and OS/PFS. Associations were reported as hazard ratios with 95% confidence intervals.

RESULTS

Adverse events requiring T-DM1 dose interruptions or reductions within the first 4 months of treatment were not significantly associated with OS (hazard ratio (HR) [95% CI]: dose interrupted = 1.15 [0.85-1.55]; dose reduced = 0.75 [0.49-1.14]; P = 0.214) nor PFS (hazard ratio (HR) [95% CI]: dose interrupted = 1.13 [0.87-1.48]; dose reduced = 0.90 [0.62-1.31]; P = 0.534).

CONCLUSION

The occurrence of early adverse events requiring T-DM1 dose interruptions or reductions do not appear to be associated with altered long-term OS or PFS within a pooled analysis of data from EMILIA and TH3RESA.

Micromanaging aerobic respiration and glycolysis in cancer cells

BACKGROUND

Cancer cells possess a common metabolic phenotype, rewiring their metabolic pathways from mitochondrial oxidative phosphorylation to aerobic glycolysis and anabolic circuits, to support the energetic and biosynthetic requirements of continuous proliferation and migration. While, over the past decade, molecular and cellular studies have clearly highlighted the association of oncogenes and tumor suppressors with cancer-associated glycolysis, more recent attention has focused on the role of microRNAs (miRNAs) in mediating this metabolic shift. Accumulating studies have connected aberrant expression of miRNAs with direct and indirect regulation of aerobic glycolysis and associated pathways.

SCOPE OF REVIEW

This review discusses the underlying mechanisms of metabolic reprogramming in cancer cells and provides arguments that the earlier paradigm of cancer glycolysis needs to be updated to a broader concept, which involves interconnecting biological pathways that include miRNA-mediated regulation of metabolism. For these reasons and in light of recent knowledge, we illustrate the relationships between metabolic pathways in cancer cells. We further summarize our current understanding of the interplay between miRNAs and these metabolic pathways. This review aims to highlight important metabolism-associated molecular components in the hunt for selective preventive and therapeutic treatments.

MAJOR CONCLUSIONS

Metabolism in cancer cells is influenced by driver mutations but is also regulated by posttranscriptional gene silencing. Understanding the nuanced regulation of gene expression in these cells and distinguishing rapid cellular responses from chronic adaptive mechanisms provides a basis for rational drug design and novel therapeutic strategies.

The UDP-Glycosyltransferase (UGT) Superfamily: New Members, New Functions, and Novel Paradigms

UDP-glycosyltransferases (UGTs) catalyze the covalent addition of sugars to a broad range of lipophilic molecules. This biotransformation plays a critical role in elimination of a broad range of exogenous chemicals and by-products of endogenous metabolism, and also controls the levels and distribution of many endogenous signaling molecules. In mammals, the superfamily comprises four families: UGT1, UGT2, UGT3, and UGT8. UGT1 and UGT2 enzymes have important roles in pharmacology and toxicology including contributing to interindividual differences in drug disposition as well as to cancer risk. These UGTs are highly expressed in organs of detoxification (e.g., liver, kidney, intestine) and can be induced by pathways that sense demand for detoxification and for modulation of endobiotic signaling molecules. The functions of the UGT3 and UGT8 family enzymes have only been characterized relatively recently; these enzymes show different UDP-sugar preferences to that of UGT1 and UGT2 enzymes, and to date, their contributions to drug metabolism appear to be relatively minor. This review summarizes and provides critical analysis of the current state of research into all four families of UGT enzymes. Key areas discussed include the roles of UGTs in drug metabolism, cancer risk, and regulation of signaling, as well as the transcriptional and posttranscriptional control of UGT expression and function. The latter part of this review provides an in-depth analysis of the known and predicted functions of UGT3 and UGT8 enzymes, focused on their likely roles in modulation of levels of endogenous signaling pathways.

Deregulation of the Genes that Are Involved in Drug Absorption, Distribution, Metabolism, and Excretion in Hepatocellular Carcinoma

Genes involved in drug absorption, distribution, metabolism, and excretion (ADME) are called ADME genes. Currently, 298 genes that encode phase I and II drug metabolizing enzymes, transporters, and modifiers are designated as ADME genes by the PharmaADME Consortium. ADME genes are highly expressed in the liver and their levels can be influenced by liver diseases such as hepatocellular carcinoma (HCC). In this study, we obtained RNA-sequencing and microRNA (miRNA)-sequencing data from 371 HCC patients via The Cancer Genome Atlas liver hepatocellular carcinoma project and performed ADME gene-targeted differential gene expression analysis and expression correlation analysis. Two hundred thirty-three of the 298 ADME genes (78%) were expressed in HCC. Of these genes, almost one-quarter (58 genes) were significantly downregulated, while only 6% (15) were upregulated in HCC relative to healthy liver. Moreover, one-half (14/28) of the core ADME genes (CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2E1, CYP3A4, NAT1, NAT2, UGT2B7, SLC22A1, SLCO1B1, and SLCO1B3) were downregulated. In addition, about one-half of the core ADME genes were positively correlated with each other and were also positively (AHR, ARNT, HNF4A, PXR, CAR, PPARA, and RXRA) or negatively (PPARD and PPARG) correlated with transcription factors known as ADME modifiers. Finally, we show that most miRNAs known to regulate core ADME genes are upregulated in HCC. Collectively, these data reveal 1) an extensive transcription factor-mediated ADME coexpression network in the liver that efficiently coordinates the metabolism and elimination of endogenous and exogenous compounds; and 2) a widespread deregulation of this network in HCC, most likely due to deregulation of both transcriptional and post-transcriptional (miRNA) pathways.

Interventions targeting the prescribing and monitoring of vancomycin for hospitalized patients: a systematic review with meta-analysis

Purpose

Vancomycin prescribing requires individualized dosing and monitoring to ensure efficacy, limit toxicity, and minimize resistance. Although there are nationally endorsed guidelines from several countries addressing the complexities of vancomycin dosing and monitoring, there is limited consideration of how to implement these recommendations effectively.

Methods

We conducted a systematic search of multiple databases to identify relevant comparative studies describing the impact of interventions of educational meetings, implementation of guidelines, and dissemination of educational material on vancomycin dosing, monitoring, and nephrotoxicity. Effect size was assessed using ORs and pooled data analyzed using forest plots to provide overall effect measures.

Results

Six studies were included. All studies included educational meetings. Two studies used implementation of guidance, educational meetings, and dissemination of educational materials, one used guidance and educational meetings, one educational meetings and dissemination of educational materials, and two used educational meetings solely. Effect sizes for individual studies were more likely to be significant for multifaceted interventions. In meta-analysis, the overall effect of interventions on outcome measures of vancomycin dosing was OR 2.50 (95% CI 1.29–4.84); P< 0.01. A higher proportion of sampling at steady-state concentration was seen following intervention (OR 1.95, 95% CI 1.26–3.02; P<0.01). Interventions had no effect on appropriate timing of trough sample (OR 2.02, 95% CI 0.72–5.72; P=0.18), attaining target concentration in patients (OR 1.50, 95% CI 0.49–4.63; P=0.48, or nephrotoxicity (OR 0.75, 95% CI 0.42–1.34; P=0.33).

Conclusion

Multifaceted interventions are effective overall in improving the complex task of dosing vancomycin, as well as some vancomycin-monitoring outcome measures. However, the resulting impact of these interventions on efficacy and toxicity requires further investigation. These findings may be helpful to those charged with designing implementation strategies for vancomycin guidelines or complex prescribing processes in hospitals.