Economic implications of potential drug-drug interactions in chronic pain patients

The Medication Quantification Scale 4.0: An Updated Index Based on Prescribers' Perceptions of the Risk Associated With Chronic Pain Medications

To quantify risks associated with drug utilization in the real world for the treatment of chronic pain (CP), an index called the Medication Quantification Scale (MQS) was developed in 1992 in the United States and last updated in 2003. This study aimed to update, adapt to the contemporary Canadian context, and validate a revised version of the MQS (the MQS-4.0). Step 1: An expert committee adapted the MQS to the Canadian clinical practice context. Step 2: An update of risk weights given to medication subclasses was achieved using a prescriber survey (weights were derived from median 0-10 scores given to each subclass). Step 3: Construct validity of the MQS-4.0 was assessed after applying risk weights to the medication use profile of persons living with CP covered by public drug insurance plan. Thirty-six medication subclasses were included in the MQS-4.0. A total of 207 prescribers (physicians, pharmacists, and nurse practitioners) participated in the perception survey; 10.63% identified as pain specialists. When risk weights were applied to prescription claims (n = 9,122), the MQS-4.0 score was associated (P < .05) with the MQS-III score and variables associated with polypharmacy (eg, Charlson Comorbidity Index, number of prescribers or health care visits). This study provides an updated index intended for adult populations based on prescribers' perceptions of the risk associated with CP medications that can be useful for clinical practice and research among persons living with CP in Canada. It will, however, be relevant to verify whether similar risk weights are obtained in future pain specialist surveys. PERSPECTIVE: The MQS-4.0 is an update of the MQS used for quantifying the risk associated with the use of analgesics/coanalgesics. Adequate psychometrics properties were found.

Polypharmacy and Excessive Polypharmacy Among Persons Living with Chronic Pain: A Cross-Sectional Study on the Prevalence and Associated Factors

Purpose

Polypharmacy can be defined as the concomitant use of ≥5 medications and excessive polypharmacy, as the use of ≥10 medications. Objectives were to (1) assess the prevalence of polypharmacy and excessive polypharmacy among persons living with chronic pain, and (2) identify sociodemographic and clinical factors associated with excessive polypharmacy.

Patients and Methods

This cross-sectional study used data from 1342 persons from the ChrOnic Pain trEatment (COPE) Cohort (Quebec, Canada). The self-reported number of medications currently used by participants (regardless of whether they were prescribed or taken over-the-counter, or were used for treating pain or other health issues) was categorized to assess polypharmacy and excessive polypharmacy.

Results

Participants reported using an average of 6 medications (median: 5). The prevalence of polypharmacy was 71.4% (95% CI: 69.0-73.8) and excessive polypharmacy was 25.9% (95% CI: 23.6-28.3). No significant differences were found across gender identity groups. Multivariable logistic regression revealed that factors associated with greater chances of reporting excessive polypharmacy (vs <10 medications) included being born in Canada, using prescribed pain medications, and reporting greater pain intensity (0-10) or pain relief from currently used pain treatments (0-100%). Factors associated with lower chances of excessive polypharmacy were using physical and psychological pain treatments, reporting better general health/physical functioning, considering pain to be terrible/feeling like it will never get better, and being employed.

Conclusion

Polypharmacy is the rule rather than the exception among persons living with chronic pain. Close monitoring and evaluation of the different medications used are important for all persons, especially those with limited access to care.

Whole-Body Photobiomodulation Therapy for Fibromyalgia: A Feasibility Trial

Effective treatment for fibromyalgia (FM) is lacking and further treatment options are needed. Photobiomodulation therapy (PBMT) represents one potential treatment option. Whilst favourable findings have been reported using localised PBMT, no investigations have established the value of whole-body PBMT for the complete set of symptom domains in FM. A single-arm feasibility study was conducted in accordance with CONSORT (Consolidated Standards of Reporting Trials) guidelines. A non-probability sampling method was used to access individuals with FM. The primary outcome measure was identified as the Revised Fibromyalgia Impact Questionnaire (FIQR). Forty-nine participants were screened and twenty-one trial participants entered the trial. Nineteen participants completed the intervention (18 whole-body PBMT sessions over approximately six weeks). Descriptive statistics and qualitative analysis was undertaken to represent feasibility outcomes. Acceptability of the trial device and processes were established. Outcome measures towards efficacy data were guided by core and peripheral OMERACT (outcomes measures in rheumatological clinical trials) domains, utilising a combination of participant-reported and performance-based outcome measures. Data for the embedded qualitative component of the trial were captured by participant-reported experience measures and audio-recorded semi-structured interviews. Positive changes were observed for FM-specific quality of life, pain, tenderness, stiffness, fatigue, sleep disturbance, anxiety, depression and cognitive impairment. Patient global assessment revealed improvements at 6 weeks, with continued effect at 24 weeks. FM-specific quality of life at 24 weeks remained improved compared with baseline scores. The findings provided evidence to support a full-scale trial and showed promise regarding potential efficacy of this novel non-invasive treatment in an FM population.

Whole-body photobiomodulation therapy for chronic pain: a protocol for a feasibility trial

INTRODUCTION

Chronic pain conditions are a leading cause of disease and disability. They are associated with symptoms such as fatigue, sleep and mood disturbances. Minimal evidence is available to support effective treatments and alternatives treatment approaches are called for. Photobiomodulation therapy has been highlighted as one promising option. A whole-body therapy device (NovoTHOR) has recently been developed with a number of potential advantages for people with chronic pain. Research is needed to consider the feasibility of this device.

METHODS AND ANALYSIS

A single-centre single-armed (no placebo group) feasibility study with an embedded qualitative component will be conducted. The intervention will comprise 18 treatments over 6 weeks, with 6-month follow-up, in the whole-body photobiomodulation device. A non-probability sample of 20 adult participants with a clinician diagnosis of chronic axial pain, polyarthralgia, myofascial pain or widespread pain will be recruited (self-referral and clinician referral). Outcome measures will focus on acceptability of trial processes with a view to guiding a definitive randomised controlled trial. Analyses will use descriptive statistics for quantitative aspects. The qualitative element will be assessed by means of a participant-reported experience questionnaire postintervention and semistructured audio-recorded interviews at three stages; preintervention, midintervention and postintervention. The latter will be transcribed verbatim and a reflexive thematic analysis will be used to identify emerging themes. Exploratory outcomes (participant-reported and performance-based measures) will be analysed according to data distribution.

ETHICS AND DISSEMINATION

The study has received ethical approval from the Leicester Central Research and Ethics Committee. Findings will be disseminated via local chronic pain groups, public register update, submission for presentation at scientific meetings and open-access peer-reviewed journals, and via academic social networks.

TRIAL REGISTRATION NUMBER

NCT05069363.

Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data

Introduction:

Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug–drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs.

Methods:

We assessed the potential drug–drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug–drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug–drug interactions between repurposed COVID-19 and antitubercular drugs.

Results:

A total of 91 potential drug–drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug–drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug–drug interaction, whereas drug–drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug–drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs.

Conclusion:

Predicting these potential drug–drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug–drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug–drug interaction studies.

Plain Language Summary

Structured medicines reviews in HIV outpatients: a feasibility study (The MOR Study)

OBJECTIVES

Polypharmacy in people living with HIV (PLWH) increases the risks of medicine-related problems (events or circumstances involving drug therapy that actually or potentially interfere with desired health outcomes). We aimed to examine the feasibility and acceptability of a Medicines Management Optimisation Review (MOR) toolkit in HIV outpatients.

METHODS

This was a multi-centre randomized controlled study across four HIV centres. In all, 200 PLWH on combination antiretroviral therapy, either > 50 years old or < 50 years with other comorbidities, were enrolled to have a MOR or received standard pharmaceutical care. The primary outcome was the difference in the number of medicine-related problems (MRPs) between intervention and standard care groups at baseline and 6 months. Acceptability, cost of the intervention and health-related quality of life were also examined.

RESULTS

In all, 164 patients were analysed: 70 in the intervention group and 94 in the standard care group. A significant number of MRPs were detected in those patients receiving MOR compared with the standard care group at baseline (93 vs. 2; p = 0.001, z = -8.6, r = 0.6) and 6 months (33 vs. 3; p = 0.001, z = -5.7, r = 0.4). A significant reduction in the number of new MRPs at 6 months in the intervention group versus baseline was also observed (p = 0.001, Z = -3.7, r = 0.2); 44% of MRPs were fully resolved at baseline and 51% at 6 months. No changes in health-related quality of life following MOR or between MOR and standard care groups were observed. The MORs were highly acceptable among patients and healthcare professionals.

CONCLUSIONS

The MOR toolkit was feasible and acceptable, suggesting that HIV outpatient services might consider implementing MOR for targeted populations under their care.

Using a machine learning approach to investigate factors associated with treatment-resistant depression among adults with chronic non-cancer pain conditions and major depressive disorder

OBJECTIVE

Presence of chronic non-cancer pain conditions (CNPC) among adults with major depressive disorder (MDD) may reduce benefits of antidepressant therapy, thereby increasing the possibility of treatment resistance. This study sought to investigate factors associated with treatment-resistant depression (TRD) among adults with MDD and CNPC using machine learning approaches.

METHODS

This retrospective cohort study was conducted using a US claims database which included adults with newly diagnosed MDD and CNPC (January 2007-June 2017). TRD was identified using a clinical staging algorithm for claims data. Random forest (RF), a machine learning method, and logistic regression was used to identify factors associated with TRD. Initial model development included 42 known and/or probable factors that may be associated with TRD. The final refined model included 20 factors.

RESULTS

Included in the sample were 23,645 patients (73% female mean age: 55 years; 78% with ≥2 CNPC, and 91% with joint pain/arthritis). Overall, 11.4% adults (N = 2684) met selected criteria for TRD. The five leading factors associated with TRD were the following: mental health specialist visits, polypharmacy (≥5 medications), psychotherapy use, anxiety, and age. Cross-validated logistic regression model indicated that those with TRD were younger, more likely to have anxiety, mental health specialist visits, polypharmacy, and psychotherapy use with adjusted odds ratios (AORs) ranging from 1.93 to 1.27 (all ps < .001).

CONCLUSION

Machine learning identified several factors that warrant further investigation and may serve as potential targets for clinical intervention to improve treatment outcomes in patients with TRD and CNPC.

Potential Drug Interactions of Repurposed COVID-19 Drugs with Lung Cancer Pharmacotherapies

Lung cancer patients are at heightened risk for developing COVID-19 infection as well as complications due to multiple risk factors such as underlying malignancy, anti-cancer treatment induced immunosuppression, additional comorbidities and history of smoking. Recent literatures have reported a significant proportion of lung cancer patients coinfected with COVID-19. Chloroquine, hydroxychloroquine, lopinavir/ritonavir, ribavirin, oseltamivir, remdesivir, favipiravir, and umifenovir represent the major repurposed drugs used as potential experimental agents for COVID-19 whereas azithromycin, dexamethasone, tocilizumab, sarilumab, famotidine and ceftriaxone are some of the supporting agents that are under investigation for COVID-19 management. The rationale of this review is to identify potential drug-drug interactions (DDIs) occurring in lung cancer patients receiving lung cancer medications and repurposed COVID-19 drugs using Micromedex and additional literatures. This review has identified several potential DDIs that could occur with the concomitant treatments of COVID-19 repurposed drugs and lung cancer medications. This information may be utilized by the healthcare professionals for screening and identifying potential DDIs with adverse outcomes, based on their severity and documentation levels and consequently design prophylactic and management strategies for their prevention. Identification, reporting and management of DDIs and dissemination of related information should be a major consideration in the delivery of lung cancer care during this ongoing COVID-19 pandemic for better patient outcomes and updating guidelines for safer prescribing practices in this coinfected condition.

Neuroinflammation, Pain and Depression: An Overview of the Main Findings

Chronic pain is a serious public health problem with a strong affective-motivational component that makes it difficult to treat. Most patients with chronic pain suffer from severe depression; hence, both conditions coexist and exacerbate one another. Brain inflammatory mediators are critical for maintaining depression-pain syndrome and could be substrates for it. The goal of our paper was to review clinical and preclinical findings to identify the neuroinflammatory profile associated with the cooccurrence of pain and depression. In addition, we aimed to explore the regulatory effect of neuronal reorganization on the inflammatory response in pain and depression. We conducted a quantitative review supplemented by manual screening. Our results revealed inflammatory signatures in different preclinical models and clinical articles regarding depression-pain syndrome. We also identified that improvements in depressive symptoms and amelioration of pain can be modulated through direct targeting of inflammatory mediators, such as cytokines and molecular inhibitors of the inflammatory cascade. Additionally, therapeutic targets that improve and regulate the synaptic environment and its neurotransmitters may act as anti-inflammatory compounds, reducing local damage-associated molecular patterns and inhibiting the activation of immune and glial cells. Taken together, our data will help to better elucidate the neuroinflammatory profile in pain and depression and may help to identify pharmacological targets for effective management of depression-pain syndrome.

Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury

BACKGROUND

Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes.

OBJECTIVE

To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury DESIGN: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury.

SETTING

Beneficiaries of a major United States-based commercial health insurer during 2000-2015 PATIENTS: Persons aged 16-90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design EXPOSURE: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy.

OUTCOME

Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage.

RESULTS

We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05-1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88-9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase.

LIMITATIONS

Potential for reverse causation, confounding by indication, and chance CONCLUSIONS: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions.

Clinical Utility of Definitive Drug⁻Drug Interaction Testing in Primary Care

Drug–drug interactions (DDIs) are a leading cause of morbidity and mortality. New tools are needed to improve identification and treatment of DDIs. We conducted a randomized controlled trial to assess the clinical utility of a new test to identify DDIs and improve their management. Primary care physicians (PCPs) cared for simulated patients presenting with DDI symptoms from commonly prescribed medications and other ingestants. All physicians, in either control or one of two intervention groups, cared for six patients over two rounds of assessment. Intervention physicians were educated on the DDI test and given access to these test reports when caring for their patients in the second round. At baseline, we saw no significant differences in making the DDI diagnosis (p = 0.071) or DDI-related treatment (p = 0.640) between control and intervention arms. By round two, providers who accessed the DDI test performed significantly better in making the DDI diagnosis (+41.6%) and performing DDI-specific treatment (+12.2%) than in the previous round, and were 9.8 and 20.4 times more likely to diagnose and identify the DDI (p < 0.001 for all). The introduction of a definitive DDI test significantly increased identification, appropriate management, and counseling of DDIs among PCPs, which has the potential to improve clinical care.

Impact of Definitive Drug-Drug Interaction Testing on Medication Management and Patient Care

Background and Objective

Aegis Sciences Corporation developed a test (InterACT Rx^™) that objectively and definitively identifies substances known to interact with drug–drug interaction-prone medications commonly prescribed in the treatment of chronic pain and behavioral health disorders. The objective of this study was to assess the severity of identified drug–drug interactions, the reduction in the frequency and severity of identified drug–drug interactions, and the impact of the test on healthcare utilization.

Methods

Patients with chronic pain, behavioral health disorders, or both who had one or more drug–drug interaction tests and one or more drug–drug interactions identified in the study period were included. Drug–drug interaction test results described the number and severity of interactions and detected substances involved in drug–drug interactions. Patients’ electronic medical records were obtained to analyze outpatient visits and prescription medications. The cost of outpatient visits was based on the Medicare Physician Fee Schedule. Outcomes were compared between the pre- and post-study index periods to determine the impact of the drug–drug interaction test on patient care.

Results

A total of 262 patients were included. The majority of drug–drug interactions detected (77.9%) at index were of moderate severity. The number of monthly all-cause and pain-related outpatient visits was reduced in the post-index period compared with the pre-index period (0.74–0.54 and 0.69–0.49, respectively). Associated costs were reduced from US$64.92 to US$51.20, and from US$62.42 to US$47.62, (p < 0.0001 for both) for all-cause and pain-related outpatient visits, respectively. Follow-up drug–drug interaction testing for 43 patients revealed that previously reported drug–drug interactions at the index test were no longer identified in the subsequent test for 39.5% of patients.

Conclusions

Employing a definitive test to detect substances whose interactions may cause adverse drug events can enhance a provider’s insights, drive clinical decision making, and improve patient outcomes.

Electronic supplementary material

The online version of this article (10.1007/s40801-018-0143-z) contains supplementary material, which is available to authorized users.

Consumer Mobile Apps for Potential Drug-Drug Interaction Check: Systematic Review and Content Analysis Using the Mobile App Rating Scale (MARS)

BACKGROUND

General consumers can now easily access drug information and quickly check for potential drug-drug interactions (PDDIs) through mobile health (mHealth) apps. With aging population in Canada, more people have chronic diseases and comorbidities leading to increasing numbers of medications. The use of mHealth apps for checking PDDIs can be helpful in ensuring patient safety and empowerment.

OBJECTIVE

The aim of this study was to review the characteristics and quality of publicly available mHealth apps that check for PDDIs.

METHODS

Apple App Store and Google Play were searched to identify apps with PDDI functionality. The apps' general and feature characteristics were extracted. The Mobile App Rating Scale (MARS) was used to assess the quality.

RESULTS

A total of 23 apps were included for the review-12 from Apple App Store and 11 from Google Play. Only 5 of these were paid apps, with an average price of $7.19 CAD. The mean MARS score was 3.23 out of 5 (interquartile range 1.34). The mean MARS scores for the apps from Google Play and Apple App Store were not statistically different (P=.84). The information dimension was associated with the highest score (3.63), whereas the engagement dimension resulted in the lowest score (2.75). The total number of features per app, average rating, and price were significantly associated with the total MARS score.

CONCLUSIONS

Some apps provided accurate and comprehensive information about potential adverse drug effects from PDDIs. Given the potentially severe consequences of incorrect drug information, there is a need for oversight to eliminate low quality and potentially harmful apps. Because managing PDDIs is complex in the absence of complete information, secondary features such as medication reminder, refill reminder, medication history tracking, and pill identification could help enhance the effectiveness of PDDI apps.

Adverse Effects of Antidepressants for Chronic Pain: A Systematic Review and Meta-analysis

Background

Antidepressants are widely used in the treatment of chronic pain. Applied doses are lower than those needed to unfold an antidepressive effect. While efficacy of antidepressants for chronic pain has been reported in large randomized-controlled trials (RCT), there is inconsistent data on adverse effects and tolerability. We aimed at synthesizing data from RCT to explore adverse effect profiles and tolerability of antidepressants for treatment of chronic pain.

Methods

Systematic literature research and meta-analyses were performed regarding side effects and safety of different antidepressants in the treatment of chronic pain according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The National Center for Biotechnology Information library and MEDLINE were searched. Randomized placebo-controlled trials were included in quantitative data synthesis.

Results

Out of 1,975 screened articles, 33 papers published between 1995 and 2015 were included in our review and 23 studies were included in the meta-analyses. A higher risk for adverse effects compared to placebo was observed in all antidepressants included in our analyses, except nortriptyline. The most prevalent adverse effects were dry mouth, dizziness, nausea, headache, and constipation. Amitriptyline, mirtazapine, desipramine, venlafaxine, fluoxetine, and nortriptyline showed the highest placebo effect-adjusted risk of adverse effects. Risk for withdrawal due to adverse effects was highest in desipramine (risk ratio: 4.09, 95%-confidence interval [1.31; 12.82]) followed by milnacipran, venlafaxine, and duloxetine. The most common adverse effects under treatment with antidepressants were dry mouth, dizziness, nausea, headache, and constipation followed by palpitations, sweating, and drowsiness. However, overall tolerability was high. Each antidepressant showed distinct risk profiles of adverse effects.

Conclusion

Our synthesized data analysis confirmed overall tolerability of low-dose antidepressants for the treatment of chronic pain and revealed drug specific risk profiles. This encompassing characterization of adverse effect profiles might be useful in defining multimodal treatment regimens for chronic pain which also consider patients’ comorbidities and co-medication.