Analgesic prescribing trends in a national sample of older veterans with osteoarthritis: 2012-2017

Digital Self-Management, Analgesic Use, and Patient-Reported Outcomes in Knee or Hip Osteoarthritis

OBJECTIVE

To investigate changes in analgesic use before and after participation in a digital first-line treatment program (exercise, patient education) in persons with knee or hip osteoarthritis (OA) and to explore associations between these changes in medication use and participant-reported pain and function.

DESIGN

Retrospective cohort study with pre-post measures.

SETTING

Community setting.

PARTICIPANTS

Individuals (N=4100; mean age ± SD, 64.5±9.3y; 73.3% women) participating in the digital program.

INTERVENTIONS

A digital supervised education and exercise therapy.

MAIN OUTCOME MEASURES

Self-reported analgesic use for knee/hip pain during the past month at baseline and 12-week follow-up, knee/hip numeric rating scale pain (0-10, a higher value indicating more pain), and Knee Injury and Osteoarthritis Outcome Score 12 or Hip Disability and Osteoarthritis Outcome Score 12 function subscale (0-100, higher values indicating better function). McNemar test, multivariable logistic regression, and linear random intercept model were used for statistical analyses.

RESULTS

Among participants, 61.4% and 49.4% were analgesic users at baseline and 12-week follow-up, respectively, (absolute reduction 12.0%; 95% confidence interval, 10.5-13.5). Being female, having hip OA, lower education, higher body mass index, living outside large metropolitan cities, coexisting rheumatoid arthritis, and walking difficulties were associated with higher odds of analgesic use at baseline. At both time points, persons not using analgesics at the time reported better outcomes. All groups but "new users" experienced improvements in their pain and function following participation in digital program with the greatest improvements observed among "quitters."

CONCLUSIONS

Engaging in a digital exercise and patient education program as a primary treatment for knee or hip OA was associated with a reduction in the use of analgesics. The greatest improvements were seen for those who stopped analgesic use. These results highlight the importance of providing effective first-line treatment to people with knee or hip OA.

Trends for opioid prescribing and the impact of the COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases between 2006 and 2021

OBJECTIVE

To investigate opioid prescribing trends and assess the impact of the COVID-19 pandemic on opioid prescribing in rheumatic and musculoskeletal diseases (RMDs).

METHODS

Adult patients with RA, PsA, axial spondyloarthritis (AxSpA), SLE, OA and FM with opioid prescriptions between 1 January 2006 and 31 August 2021 without cancer in UK primary care were included. Age- and gender-standardized yearly rates of new and prevalent opioid users were calculated between 2006 and 2021. For prevalent users, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006 and 2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of prevalent opioid users between January 2015 and August 2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic.

RESULTS

The study included 1 313 519 RMD patients. New opioid users for RA, PsA and FM increased from 2.6, 1.0 and 3.4/10 000 persons in 2006 to 4.5, 1.8 and 8.7, respectively, in 2018 or 2019. This was followed by a fall to 2.4, 1.2 and 5.9, respectively, in 2021. Prevalent opioid users for all RMDs increased from 2006 but plateaued or dropped beyond 2018, with a 4.5-fold increase in FM between 2006 and 2021. In this period, MME/day increased for all RMDs, with the highest for FM (≥35). During COVID-19 lockdowns, RA, PsA and FM showed significant changes in the trend of prevalent opioid users. The trend for FM increased pre-pandemic and started decreasing during the pandemic.

CONCLUSION

The plateauing or decreasing trend of opioid users for RMDs after 2018 may reflect the efforts to tackle rising opioid prescribing in the UK. The pandemic led to fewer people on opioids for most RMDs, providing reassurance that there was no sudden increase in opioid prescribing during the pandemic.

Pain Intensity and Trajectory Following Intra-Articular Injection of Mono-Iodoacetate in Experimental Osteoarthritis: A Meta-Analysis of In Vivo Studies

OBJECTIVE

Although most frequently used in experimental osteoarthritis (OA) pain induction, intra-articular mono-iodoacetate (MIA) injection lacks concluded references for dose selection and timing of intervention. Herein, we aimed to compare the pain intensity of rats induced by different doses of MIA and explored the trajectory of pain.

DESIGN

PubMed, Embase, and Web of Science were searched up to June 2021 for literatures involving MIA experiments investigating OA pain. Pain intensity was measured based on weightbearing distribution (WBD) and paw withdrawal thresholds (PWT), and the pain trajectory was constructed by evaluating pain intensity at a series of time points after MIA injection. A conventional meta-analysis was conducted.

RESULTS

A total of 140 studies were included. Compared with saline, MIA injections caused significantly higher pain intensity for WBD and PWT. Dose-response relationships between different doses of MIA and pain intensity were observed (P-for-trend<0.05). A pronounced increase in pain occurred from day 0 to day 7, but the uptrend ceased between day 7 and day 14, after which the pain intensity continued to rise and reached the maximum by day 28.

CONCLUSIONS

Pain intensity after intra-articular MIA injection increased in a dose-dependent manner and the pain trajectory manifested a specific pattern consistent with the pathological mechanisms of MIA-induced pain, providing possible clues for proper dose selection and timing of specific OA pain interventions.

The Association Between Nonsteroidal Anti-Inflammatory Drug Use and Inflammatory Bowel Disease Exacerbations: A True Association or Residual Bias?

INTRODUCTION

Studies suggest that nonsteroidal anti-inflammatory drugs (NSAID) may contribute to inflammatory bowel disease (IBD) exacerbations. We examined whether variation in the likelihood of IBD exacerbations is attributable to NSAID.

METHODS

In a cohort of patients with IBD (2004-2015), we used 3 analytic methods to examine the likelihood of an exacerbation after an NSAID exposure. First, we matched patients by propensity for NSAID use and examined the association between NSAID exposure and IBD exacerbation using an adjusted Cox proportional hazards model. To assess for residual confounding, we estimated a previous event rate ratio and used a self-controlled case series analysis to further explore the relationship between NSAID and IBD exacerbations.

RESULTS

We identified 15,705 (44.8%) and 19,326 (55.2%) IBD patients with and without an NSAID exposure, respectively. Findings from the Cox proportional hazards model suggested an association between NSAID and IBD exacerbation (hazard ratio 1.24; 95% confidence interval 1.16-1.33). However, the likelihood of an IBD exacerbation in the NSAID-exposed arm preceding NSAID exposure was similar (hazard ratio 1.30; 95% confidence interval 1.21-1.39). A self-controlled case series analysis of 3,968 patients who had both an NSAID exposure and IBD exacerbation demonstrated similar exacerbation rates in the 1 year preceding exposure, 2-6 weeks postexposure, and 6 weeks to 6 months postexposure, but a higher incidence in 0-2 weeks postexposure, suggesting potential confounding by reverse causality.

DISCUSSION

While we see an association between NSAID and IBD exacerbations using traditional methods, further analysis suggests this may be secondary to residual bias. These findings may reassure patients and clinicians considering NSAID as a nonopioid pain management option.

Treating osteoarthritis pain: mechanisms of action of acetaminophen, nonsteroidal anti-inflammatory drugs, opioids, and nerve growth factor antibodies

Osteoarthritis (OA) is a common difficult-to-treat condition where the goal, in the absence of disease-modifying treatments, is to alleviate symptoms such as pain and loss of function. Acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs), and opioids are common pharmacologic treatments for OA. Antibodies directed against nerve growth factor (NGF-Abs) are a new class of agents under clinical investigation for the treatment of OA. This narrative review describes (and uses schematics to visualize) nociceptive signaling, chronification of pain, and the mechanisms of action (MOAs) of these different analgesics in the context of OA-related pain pathophysiology. Further, the varying levels of efficacy and safety of these agents observed in patients with OA is examined, based on an overview of published clinical data and/or treatment guidelines (when available), in the context of differences in their MOAs.

A systematic review of community pharmacy initiatives to improve treatment of depression and pain: Focus on types of programs and patient-reported outcomes

INTRODUCTION

Depression and pain are common, disabling, mutually exacerbating conditions. Many patients living with these conditions present to community pharmacies on a regular schedule to purchase both prescribed and over-the-counter medications. Community-pharmacy based programs have been developed to improve depression and pain outcomes.

METHODS

The PRISMA guidelines were utilized to answer the following question: In patients with depression and/or pain, what is the effect of the existing community pharmacy programs on depression and/or pain outcomes. Queried databases included Pubmed, EMBASE, and PsychINFO. DistillerSR was used to organize the screening, abstraction, and review of data. All potential articles were evaluated by two authors, and conflicts were discussed to achieve resolution. In addition to primary outcomes, sources of potential bias and quality indicators were abstracted for every article.

RESULTS

Three thousand nine hundred and twenty articles were reviewed, and 13 studies met eligibility criteria (n = 7 for depression; n = 6 for pain). Most studies demonstrated improvement in measures of depression or pain. However, compared to usual care or other control conditions, most of the depression and pain-specific interventions did not provide additional symptomatic benefit. The community pharmacy-based interventions were superior for other outcomes including medication adherence, reducing stigma, improvement in self-efficacy, and improvement in general management of disease.

CONCLUSION

Community pharmacies may be uniquely positioned to deliver interventions that improve outcomes associated with successful depression and pain treatment outcomes. However, the benefits of published community pharmacy-based treatments for actually improving depression and pain severity has not yet been established. Innovative interventions and additional research may be needed to achieve clinical success for pharmacy interventions for depression and pain.

Osteoarthritis year in review 2020: epidemiology & therapy

This personal choice of research themes and highlights from within the past year (1 May 2019 to 14 April 2020) spans descriptive, analytical-observational, and intervention studies. Descriptive estimates of the burden of osteoarthritis continue to underscore its position as a leading cause of disability worldwide, but whose burden is often felt greatest among disadvantaged and marginalised communities. Many of the major drivers of that burden are known but epidemiological studies continue the important work of elaborating on their timing, dose, specificity, and reversibility and placing them within an appropriate multi-level framework. A similar process of elaboration is seen also in studies (re-)estimating the relative benefits and risks of existing interventions, in some cases helping to identify low-value care, unwarranted variation, and initiating processes of deprescribing and decommissioning. Such research need not engender therapeutic nihilism. Our review closes by highlighting some emerging evidence on the efficacy and safety of novel therapeutic interventions and with a selective roll-call of methodological and meta-research in OA illustrating the continued commitment to improving research quality.

Patients use fewer analgesics following supervised exercise therapy and patient education: an observational study of 16 499 patients with knee or hip osteoarthritis

OBJECTIVES

To investigate changes in analgesic use before and after supervised exercise therapy and patient education in patients with knee or hip osteoarthritis (OA).

METHODS

We recruited 16 499 of 25 933 eligible patients (64%; mean age 64.9; SD 9.6; 73% women) from the Good Life with osteoArthritis in Denmark (GLA:D) registry. Change in proportions of analgesic users (categorised according to analgesic risk profile; opioids > non-steroidal anti-inflammatory drugs > paracetamol) was assessed from before to after an 8-week supervised exercise therapy and patient education programme targeting knee or hip OA pain and functional limitations.

RESULTS

Patients reported 13.2 mm (95% CI 12.8 to 13.6) less pain (visual analogue scale 0-100 mm) at follow-up compared with baseline. The proportion of analgesic users reduced from 62.2% (95% CI 61.5 to 63.0) at baseline to 44.1% (95% CI 43.3 to 44.9) at follow-up (absolute change: 18.1% (95% CI 17.3 to 19.0)). Among patients using analgesics at baseline, 52% changed to a lower risk analgesic or discontinued analgesic use. The proportion of opioid users after the exercise therapy was 2.5% (95% CI 2.1 to 2.9) lower than baseline; this represents a relative reduction of 36%.

CONCLUSION

Among patients with knee or hip OA using analgesics, more than half either discontinued analgesic use or shifted to lower risk analgesics following an 8-week structured exercise therapy and patient education programme (GLA:D). These data encourage randomised controlled trial evaluation of whether supervised exercise therapy, combined with patient education, can reduce analgesic use, including opioids, among patients with knee and hip OA pain.

Prescribing patterns of opioid analgesics in a dental setting: 2013-2018

OBJECTIVE

Analgesic prescribing patterns are influenced by internal and external factors. Understanding these factors could help improve prescribing practices.

STUDY DESIGN

We conducted a retrospective analysis of electronic health records with regard to analgesic prescriptions written from 2013 through 2018 at the University of Kentucky College of Dentistry. Deidentified information (age, gender, dental procedures, analgesic drug, quantity, and refills) were recorded and studied with respect to national guidelines and recent state legislation using the χ² test, analysis of variance, logistic regression, and multiple linear regression.

RESULTS

Opioids comprised 74.9% of the 17,099 analgesic prescriptions written. Extractions were most commonly associated with opioid prescriptions. Multivariate analysis showed that (1) older patients were more likely to receive an opioid prescription (P < .01) but with fewer pills (P < .01); (2) surgical extractions were associated with a lower opioid prescription rate (P < .01) but more opioid pills per prescription compared with nonsurgical extractions (P < .01); and (3) the odds of receiving an opioid prescription and the number of opioid pills prescribed decreased over year after release of the national guideline (P < .01) and after enactment of state legislation (P < .01).

CONCLUSIONS

Regulations and guidelines were associated with reduction in opioid prescriptions.

Viewpoint on Time Series and Interrupted Time Series Optimum Modeling for Predicting Arthritic Disease Outcomes

PURPOSE OF REVIEW

The propose of this viewpoint is to improve or facilitate the clinical decision-making in the management/treatment strategies of arthritis patients through knowing, understanding, and having access to an interactive process allowing assessment of the patient disease outcome in the future.

RECENT FINDINGS

In recent years, the time series (TS) concept has become the center of attention as a predictive model for making forecast of unseen data values. TS and one of its technologies, the interrupted TS (ITS) analysis (TS with one or more interventions), predict the next period(s) value(s) of a given patient based on their past and current information. Traditional TS/ITS methods involve segmented regression-based technologies (linear and nonlinear), while stochastic (linear modeling) and artificial intelligence approaches, including machine learning (complex nonlinear relationships between variables), are also used; however, each have limitations. We will briefly describe TS/ITS, provide examples of their application in arthritic diseases; describe their methods, challenges, and limitations; and propose a combined (stochastic and artificial intelligence) procedure in post-intervention that will optimize ITS modeling. This combined method will increase the accuracy of ITS modeling by profiting from the advantages of both stochastic and nonlinear models to capture all ITS deterministic and stochastic components. In addition, this combined method will allow ITS outcomes to be predicted as continuous variables without having to consider the time lag produced between the pre- and post-intervention periods, thus minimizing the prediction error not only for the given data but also for all possible future patterns in ITS. The use of reliable prediction methodologies for arthritis patients will permit treatment of not only the disease, but also the patient with the disease, ensuring the best outcome prediction for the patient.