Proton pump inhibitors and cancer treatments: Emerging evidence against coadministration.

BACKGROUND: Proton pump inhibitors (PPIs) are widely used in cancer patients despite accumulating data showing that they can impact the efficacy of major anticancer drugs. This is particularly important with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (CPIs). RESULTS: Most TKIs require gastric acidity for their absorption and some retrospective series demonstrated that coprescription decreases the survival benefit of some TKI use (erlotinib, gefitinib and pazopanib). Relations between microbiota, the immune system, and the efficacy of immunotherapy are now obvious, just as modifications to gut flora after PPIs use are well-known. Many retrospective articles, including articles based on individual-participant data from randomized studies, demonstrated that patients treated with CPIs have a poorer outcome (overall survival, progression-free survival and response rate) when they received PPIs concomitantly, while there was no impact of such coprescription among patients in control arms, not treated with immunotherapies. Similar data were also observed in patients treated with palbociclib. CONCLUSION: For these interactions, it is very important to use the precautionary principle and warn patients and physicians about this. In patients who require acid suppression because of severe symptoms, using antacids or H2 blockers could be recommended.

Drugs That Interact With Colchicine Via Inhibition of Cytochrome P450 3A4 and P-Glycoprotein: A Signal Detection Analysis Using a Database of Spontaneously Reported Adverse Events (FAERS).

BACKGROUND: Colchicine has a narrow therapeutic index. Its toxicity can be increased due to concomitant exposure to drugs inhibiting its metabolic pathway; these are cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp). OBJECTIVE: To examine clinical outcomes associated with colchicine drug interactions using the spontaneous reports of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). METHODS: We conducted a disproportionality analysis using FAERS data from January 2004 through June 2020. The reporting odds ratio (ROR) and observed-to-expected ratio (O/E) with shrinkage for adverse events related to colchicine's toxicity (ie, rhabdomyolysis/myopathy, agranulocytosis, hemorrhage, acute renal failure, hepatic failure, arrhythmias, torsade de pointes/QT prolongation, and cardiac failure) were compared between FAERS reports. RESULTS: A total of 787 reports included the combined mention of colchicine, an inhibitor of both CYP3A4 and P-gp drug, and an adverse event of interest. Among reports that indicated the severity, 61% mentioned hospitalization and 24% death. A total of 37 ROR and 34 O/E safety signals involving colchicine and a CYP3A4/P-gp inhibitor were identified. The strongest ROR signal was for colchicine + atazanavir and rhabdomyolysis/myopathy (ROR = 35.4, 95% CI: 12.8-97.6), and the strongest O/E signal was for colchicine + atazanavir and agranulocytosis (O/E = 3.79, 95% credibility interval: 3.44-4.03). CONCLUSION AND RELEVANCE: This study identifies numerous safety signals for colchicine and CYP3A4/P-gp inhibitor drugs. Avoiding the interaction or monitoring for toxicity in patients when co-prescribing colchicine and these agents is highly recommended.

Colchicine Drug Interaction Errors and Misunderstandings: Recommendations for Improved Evidence-Based Management.

Colchicine is useful for the prevention and treatment of gout and a variety of other disorders. It is a substrate for CYP3A4 and P-glycoprotein (P-gp), and concomitant administration with CYP3A4/P-gp inhibitors can cause life-threatening drug-drug interactions (DDIs) such as pancytopenia, multiorgan failure, and cardiac arrhythmias. Colchicine can also cause myotoxicity, and coadministration with other myotoxic drugs may increase the risk of myopathy and rhabdomyolysis. Many sources of DDI information including journal publications, product labels, and online sources have errors or misleading statements regarding which drugs interact with colchicine, as well as suboptimal recommendations for managing the DDIs to minimize patient harm. Furthermore, assessment of the clinical importance of specific colchicine DDIs can vary dramatically from one source to another. In this paper we provide an evidence-based evaluation of which drugs can be expected to interact with colchicine, and which drugs have been stated to interact with colchicine but are unlikely to do so. Based on these evaluations we suggest management options for reducing the risk of potentially severe adverse outcomes from colchicine DDIs. The common recommendation to reduce the dose of colchicine when given with CYP3A4/P-gp inhibitors is likely to result in colchicine toxicity in some patients and therapeutic failure in others. A comprehensive evaluation of the almost 100 reported cases of colchicine DDIs is included in table form in the electronic supplementary material. Colchicine is a valuable drug, but improvements in the information about colchicine DDIs are needed in order to minimize the risk of serious adverse outcomes.

QTc Prolongation with the Use of Hydroxychloroquine and Concomitant Arrhythmogenic Medications: A Retrospective Study Using Electronic Health Records Data.

INTRODUCTION: Hydroxychloroquine can induce QT/QTc interval prolongation for some patients; however, little is known about its interactions with other QT-prolonging drugs. OBJECTIVE: The purpose of this retrospective electronic health records study was to evaluate changes in the QTc interval in patients taking hydroxychloroquine with or without concomitant QT-prolonging medications. METHODS: De-identified health records were obtained from the Cerner Health Facts® database. Variables of interest included demographics, diagnoses, clinical procedures, laboratory tests, and medications. Patients were categorized into six cohorts based on exposure to hydroxychloroquine, methotrexate, or sulfasalazine alone, or the combination of any those drugs with any concomitant drug known to prolong the QT interval. Tisdale QTc risk score was calculated for each patient cohort. Two-sample paired t-tests were used to test differences between the mean before and after QTc measurements within each group and ANOVA was used to test for significant differences across the cohort means. RESULTS: A statistically significant increase in QTc interval from the last measurement prior to concomitant exposure of 18.0 ms (95% CI 3.5-32.5; p < 0.05) was found in the hydroxychloroquine monotherapy cohort. QTc changes varied considerably across cohorts, with standard deviations ranging from 40.9 (hydroxychloroquine monotherapy) to 57.8 (hydroxychloroquine + sulfasalazine). There was no difference in QTc measurements among cohorts. The hydroxychloroquine + QTc-prolonging agent cohort had the highest average Tisdale Risk Score compared with those without concomitant exposure (p < 0.05). CONCLUSION: Our analysis of retrospective electronic health records found hydroxychloroquine to be associated with a moderate increase in the QTc interval compared with sulfasalazine or methotrexate. However, the QTc was not significantly increased with concomitant exposure to other drugs known to increase QTc interval.

Overriding Drug-Drug Interaction Alerts in Clinical Decision Support Systems: A Scoping Review.

Ineffective computerized alerts for potential Drug-Drug Interactions (DDI) is a longstanding informatics issue. Prescribing clinicians often ignore or override such alerts due to lack of context and clinical relevance, among various other reasons. In this study, we reveiwed published data on the rate of DDI alert overrides and medications involved in the overrides. We identified 34 eligible studies from sites across Asia, Europe, the United States, and the United Kingdom. The override rate of DDI alerts ranged from 55% to 98%, with more than half of the studies reporting the most common drug pairs or medications involved in acceptance or overriding of alerts. The high prevalance of alert overrides highlights the need for decision support systems that take user, drug, and institutional factors into consideration, as well as actionable metrics to better characterize harm associated with overrides.

Serum potassium changes due to concomitant ACEI/ARB and spironolactone therapy: A systematic review and meta-analysis.

PURPOSE: To provide evidence of serum potassium changes in individuals taking angiotensin-converting enzyme inhibitors (ACEIs) and/or angiotensin receptor blockers (ARBs) concomitantly with spironolactone compared to ACEI/ARB therapy alone. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies including exposure to both spironolactone and ACEI/ARB therapy compared to ACEI/ARB therapy alone. The primary outcome was serum potassium change over time. Main effects were calculated to estimate average treatment effect using random effects models. Heterogeneity was assessed using Cochran's Q and I2. Risk of bias was assessed using the revised Cochrane risk of bias tool. RESULTS: From the total of 1,225 articles identified, 20 randomized controlled studies were included in the meta-analysis. The spironolactone plus ACEI/ARB group included 570 patients, while the ACEI/ARB group included 547 patients. Treatment with spironolactone and ACEI/ARB combination therapy compared to ACEI/ARB therapy alone increased the mean serum potassium concentration by 0.19 mEq/L (95% CI, 0.12-0.26 mEq/L), with intermediate heterogeneity across studies (Q statistic = 46.5, P = 0.004; I2 = 59). Sensitivity analyses showed that the direction and magnitude of this outcome did not change with the exclusion of individual studies, indicating a high level of reliability. Reporting risk of bias was low for 16 studies (80%), unclear for 3 studies (15%) and high for 1 study (5%). CONCLUSION: Treatment with spironolactone in combination with ACEI/ARB therapy increases the mean serum potassium concentration by less than 0.20 mEq/L compared to ACEI/ARB therapy alone. However, serum potassium and renal function must be monitored in patients starting combination therapy to avoid changes in serum potassium that could lead to hyperkalemia.

Designing and evaluating contextualized drug-drug interaction algorithms.

OBJECTIVE: Alert fatigue is a common issue with off-the-shelf clinical decision support. Most warnings for drug-drug interactions (DDIs) are overridden or ignored, likely because they lack relevance to the patient's clinical situation. Existing alerting systems for DDIs are often simplistic in nature or do not take the specific patient context into consideration, leading to overly sensitive alerts. The objective of this study is to develop, validate, and test DDI alert algorithms that take advantage of patient context available in electronic health records (EHRs) data. METHODS: Data on the rate at which DDI alerts were triggered but for which no action was taken over a 3-month period (override rates) from a single tertiary care facility were used to identify DDIs that were considered a high-priority for contextualized alerting. A panel of DDI experts developed algorithms that incorporate drug and patient characteristics that affect the relevance of such warnings. The algorithms were then implemented as computable artifacts, validated using a synthetic health records data, and tested over retrospective data from a single urban hospital. RESULTS: Algorithms and computable knowledge artifacts were developed and validated for a total of 8 high priority DDIs. Testing on retrospective real-world data showed the potential for the algorithms to reduce alerts that interrupt clinician workflow by more than 50%. Two algorithms (citalopram/QT interval prolonging agents, and fluconazole/opioid) showed potential to filter nearly all interruptive alerts for these combinations. CONCLUSION: The 8 DDI algorithms are a step toward addressing a critical need for DDI alerts that are more specific to patient context than current commercial alerting systems. Data commonly available in EHRs can improve DDI alert specificity.

Risk of Bleeding with Exposure to Warfarin and Nonsteroidal Anti-Inflammatory Drugs: A Systematic Review and Meta-Analysis.

BACKGROUND: Warfarin use can trigger the occurrence of bleeding independently or as a result of a drug-drug interaction when used in combination with nonsteroidal anti-inflammatory drugs (NSAIDs). OBJECTIVES: This article examines the risk of bleeding in individuals exposed to concomitant warfarin and NSAID compared with those taking warfarin alone (Prospero Registry ID 145237). METHODS: PubMed, EMBASE, Scopus, and Web of Science were searched. The primary outcome of interest was gastrointestinal bleeding and general bleeding. Summary effects were calculated to estimate average treatment effect using random effects models. Heterogeneity was assessed using Cochran's Q and I 2. Risk of bias was also assessed using the Agency for Healthcare Research and Quality bias assessment tool. RESULTS: A total of 651 studies were identified, of which 11 studies met inclusion criteria for meta-analysis. The odds ratio (OR) for gastrointestinal bleeding when exposed to warfarin and an NSAID was 1.98 (95% confidence interval [CI]: 1.55-2.53). The risk of gastrointestinal bleeding was also significantly elevated with exposure to a COX-2 inhibitor and warfarin relative to warfarin alone (OR = 1.90, 95% CI: 1.46-2.46). There was an increased risk of general bleeding with the combination of warfarin with NSAIDs (OR = 1.58, 95% CI: 1.18-2.12) or COX-2 inhibitors (OR = 1.54, 95% CI: 0.86-2.78) compared with warfarin alone. CONCLUSION: Risk of bleeding is significantly increased among persons taking warfarin and a NSAID or COX-2 inhibitor together as compared with taking warfarin alone. It is important to caution patients about taking these medications in combination.

Evidence of Clinically Meaningful Drug-Drug Interaction With Concomitant Use of Colchicine and Clarithromycin.

INTRODUCTION: Colchicine is currently approved for the treatment of gout and familial Mediterranean fever, among other conditions. Clarithromycin, a strong inhibitor of CYP3A4 and P-glycoprotein, dramatically increases colchicine's half-life, augmenting the risk of a life-threatening adverse reaction when used inadvertently with colchicine. OBJECTIVES: The aim of this study was to examine the evidence and clinical implications of concomitant use of colchicine and clarithromycin. METHODS: Case reports of colchicine-clarithromycin co-administration were searched using the FDA's Adverse Event Reporting System (FAERS) database. PubMed, EMBASE, and Web of Science electronic databases were also searched from January 2005 through November 2019 for articles reporting colchicine-clarithromycin concomitant use. Individual reports were reviewed to identify consequences of coadministration, dose, days to onset of interaction, symptoms, evidence of renal disease, time to resolution of symptoms, and Drug Interaction Probability Scale (DIPS) rating. RESULTS: The FAERS search identified 58 reported cases, nearly 53% of which were from patients aged between 65 and 85 years. Of 30 reported deaths, 11 occurred in males, and 19 in females. Other frequent complications reported in FAERS included diarrhea (31%), pancytopenia (22%), bone marrow failure (14%), and vomiting (14%). From published literature, we identified 20 case reports of concomitant exposure, 19 of which were rated 'probable' and one 'possible' according to DIPS rating. Of these cases, four 'probable' patients expired. The documented onset of colchicine toxicity occurred within 5 days of starting clarithromycin, and death within 2 weeks of concomitant exposure. CONCLUSION: Clinical manifestations of colchicine-clarithromycin interaction may resemble other systemic diseases and may be life threatening. Understanding this clinically meaningful interaction can help clinicians avoid unsafe medication combinations.

The Underrated Risks of Tamoxifen Drug Interactions.

Tamoxifen is a prodrug, and most of the therapeutic effect in treating breast cancer stems from its metabolite, endoxifen. Since cytochrome P450 (CYP) 2D6 is the most important enzyme in the production of endoxifen, drugs that inhibit CYP2D6 would be expected to reduce tamoxifen efficacy. In addition to drug-drug interactions (DDI) involving CYP2D6, there is growing evidence that enzyme inducers can substantially alter the disposition of endoxifen, reducing tamoxifen efficacy. Although the clinical evidence on the impact of CYP2D6 inhibitors on tamoxifen efficacy is mixed, there were serious flaws in many of the studies. Thus, there is a reasonable chance that CYP2D6 inhibitors do in fact inhibit tamoxifen efficacy. Tamoxifen has extraordinarily complex pharmacokinetics, with more than a dozen drug-metabolizing enzymes and transporters involved in its disposition. Enzyme inducers may increase the activity of several of these pathways, including phase II enzymes, ABC transporters, and various CYP enzymes other than CYP2D6. Based on current clinical evidence, one could argue that enzyme inducers are potentially more dangerous than CYP2D6 inhibitors in patients taking tamoxifen. Moreover, early evidence suggests that the combination of CYP2D6 inhibitors plus enzyme inducers may produce catastrophic inhibition of tamoxifen efficacy. One could argue that, given the available evidence, an agnostic "wait and see" position on tamoxifen DDI is ethically untenable, and that many women with breast cancer are currently being subjected to an unnecessary risk of cancer recurrence. Specific recommendations to reduce the risk of adverse tamoxifen DDI are offered for consideration.

Recommendations for selecting drug-drug interactions for clinical decision support.

PURPOSE: Recommendations for including drug-drug interactions (DDIs) in clinical decision support (CDS) are presented. SUMMARY: A conference series was conducted to improve CDS for DDIs. A work group consisting of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information vendors, and healthcare organizations was convened to address (1) the process to use for developing and maintaining a standard set of DDIs, (2) the information that should be included in a knowledge base of standard DDIs, (3) whether a list of contraindicated drug pairs can or should be established, and (4) how to more intelligently filter DDI alerts. We recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated and more research to identify methods to safely reduce repetitive and less-relevant alerts. CONCLUSION: An expert panel with a centralized organizer or convener should be established to develop and maintain a standard set of DDIs for CDS in the United States. The process should be evidence driven, transparent, and systematic, with feedback from multiple stakeholders for continuous improvement. The scope of the expert panel's work should be carefully managed to ensure that the process is sustainable. Support for research to improve DDI alerting in the future is also needed. Adoption of these steps may lead to consistent and clinically relevant content for interruptive DDIs, thus reducing alert fatigue and improving patient safety.

Clinical Weighting of Drug-Drug Interactions in Hospitalized Elderly.

Adverse drug reactions impact on patient health, effectiveness of pharmacological therapy and increased health care costs. This investigation intended to detect the most critical drug-drug interactions in hospitalized elderly patients, weighting clinical risk. We conducted a cross-sectional study between January and April 2014; all patients 70 years or older, hospitalized for >24 hr and prescribed at least one medication were included in the study. Drug-drug interactions were estimated by combining Stockley's, Hansten and Tatro drug interactions. Drug-drug interactions were weighted using a risk-analysis method based on failure modes, effects and criticality analysis. We calculated a criticality index for each drug involved in the drug-drug interactions based on the severity of the interaction mechanism, the frequency the drug was involved in drug-drug interactions and the risk of drug-drug interactions in patients with impaired renal function. The average number of drugs consumed in the hospital was 6 ± 2.69, involving 160 active ingredients. The most frequent were as follows: Furosemide, followed by Enalapril. Of drug-drug interactions, 2% were classified as contraindicated, 14% advised against and 83% advised caution during the hospital stay. Thirty-four drug-drug interactions were assessed, of which 23 were pharmacodynamic drug-drug interactions and 12 were pharmacokinetic drug-drug interactions (1 was both). The clinical risk calculated for each drug-drug interaction included heparins + non-steroidal anti-inflammatory drugs (NSAIDs) or Digoxin + Calcium Gluconate, cases which are pharmacodynamic drug-drug interactions with agonist effect and clinical risk of bleeding, one of the most common clinical risks in the hospital. An index of clinical risk for drug-drug interactions can be calculated based on severity by the interaction mechanism, the frequency that the drug is involved in drug-drug interactions and the risk of drug-drug interactions in an elderly patient with impaired renal function.

Is digoxin use for cardiovascular disease associated with risk of prostate cancer?

PURPOSE: Digoxin is a commonly used medication for heart failure and cardiac arrhythmias that has recently been suggested as a novel chemotherapeutic agent. Preclinical studies of prostate cancer (PCa) have shown anti-tumor activity with digoxin. We explore the relationship between use of digoxin and PCa risk. METHODS: Data from a population-based case-control study of incident cases aged 35-74 years at PCa diagnosis in 2002-2005 in King County, Washington were available. Controls were identified by random digit dialing and frequency matched by age. Use of digoxin was determined from in-person questionnaires regarding medical and prescription history. The relationship of digoxin use with PCa risk was evaluated with logistic regression. RESULTS: One thousand one cases of PCa and 942 controls were analyzed. The prevalence of digoxin use in controls was 2.7%, and use was positively correlated with age. In multivariate analysis adjusting for age, race, PSA screening, and family history of PCa, digoxin use was associated with a reduction in the odds ratio of PCa (OR 0.58, 95% CI: 0.30-1.10). Among those with ≥3 PSA tests over the preceding 5 years (546 cases, 380 controls), digoxin use was associated with a stronger reduction of PCa risk (OR 0.44, 95% CI: 0.20-0.98). CONCLUSION: These data indicate digoxin use may be associated with a reduction in risk of PCa. Given the potential mechanisms by which digoxin may exert an anti-neoplastic effect and other recent studies showing a negative association between digoxin use and PCa, further research is warranted.

Statin use and risk of prostate cancer: results from a population-based epidemiologic study.

Epidemiologic studies of statin use in relation to prostate cancer risk have been inconclusive. Recent evidence, however, suggests that longer-term use may reduce risk of more advanced disease. The authors conducted a population-based study of 1,001 incident prostate cancer cases diagnosed in 2002-2005 and 942 age-matched controls from King County, Washington, to evaluate risk associated with statin use. Logistic regression was used to generate odds ratios for ever use, current use, and duration of use. No overall association was found between statin use and prostate cancer risk (odds ratio (OR) = 1.0, 95% confidence interval (CI): 0.8, 1.2 for current use; OR = 1.1, 95% CI: 0.7, 1.8 for >10 years' use), even for cases with more advanced disease. Risk related to statin use, however, was modified by body mass index (interaction p = 0.04). Obese men (BMI > or =30 kg/m2) who used statins had an increased risk (OR = 1.5, 95% CI: 1.0, 2.2) relative to obese nonusers, with a stronger association for longer-term use (OR = 1.8, 95% CI: 1.1, 3.0 for > or =5 years' use). Although statin use was not associated with overall prostate cancer risk, the finding of an increased risk associated with statin use among obese men, particularly use for extended durations, warrants further investigation.

Proposal for a new tool to evaluate drug interaction cases.

The assessment of causation for a potential drug interaction requires thoughtful consideration of the properties of both the object and precipitant drugs, patient-specific factors, and the possible contribution of other drugs that the patient may be taking. The Naranjo nomogram was designed to evaluate single-drug adverse events, not drug-drug interactions. Several of the questions on the Naranjo nomogram do not apply to potential drug-drug interactions, while others do not specify object or precipitant drug. Nevertheless, it has been inappropriately used to evaluate drug-drug interactions. The Drug Interaction Probability Scale (DIPS) was developed to provide a guide to evaluating drug interaction causation in a specific patient. It is intended to be used to assist practitioners in the assessment of drug interaction-induced adverse outcomes. The DIPS uses a series of questions relating to the potential drug interaction to estimate a probability score. An accurate assessment using the DIPS requires knowledge of the pharmacologic properties of both the object and precipitant drugs. Inadequate knowledge of either the drugs involved or the basic mechanisms of interaction will be a limitation for some users. The DIPS can also serve as a guide in the preparation of articles describing case reports of drug interactions, as well as in the evaluation of published case reports.

Assessment of potential drug-drug interactions with a prescription claims database.

PURPOSE: The prevalence of 25 clinically important potential drug-drug interactions (DDIs) in a population represented by the drug claims database of a pharmacy benefit management company (PBM) was studied. METHODS: A retrospective cross-sectional analysis of pharmaceutical claims for almost 46 million participants in a PBM was conducted to determine the frequency of 25 DDIs previously identified as clinically important. A DDI was counted when drugs in potentially interacting combinations were dispensed within 30 days of each other during a 25-month period between April 2000 and June 2002. RESULTS: The number of DDIs ranged from 37 for pimozide and an azole antifungal to 127,684 for warfarin and a nonsteroidal antiinflammatory drug (NSAID). The highest prevalence (278.56 per 100,000 persons) and highest case-exposure rate (242.7 per 1,000 warfarin recipients) occurred with the warfarin-NSAID combination. The combination with the lowest overall prevalence (cyclosporine and a rifamycin, 0.10/100,000) differed from the combination with the lowest case-exposure rate (pimozide and an azole antifungal, 0.028 per 1,000 azole antifungal recipients). Number of cases, prevalence, and case-exposure rates for both sexes generally increased with age. An estimated 374,000 plan participants were exposed to a clinically important DDI during a 25-month period. Between 20% and 46% of prescription drug claims were reversed (canceled) for a medication with a drug interaction when a warning about the interaction was sent to the pharmacy. CONCLUSION: Analysis of prescription claims data from a major PBM found that 374,000 of 46 million plan participants had been exposed to a potential DDI of clinical importance.