Knee pain trajectories over 18 months in non-Hispanic Black and non-Hispanic White adults with or at risk for knee osteoarthritis

Osteoarthritis year in review 2022: epidemiology & therapy

This 'Year in Review' provides a synopsis of key research themes and individual studies from the clinical osteoarthritis (OA) field, focused on epidemiology and therapy. The electronic database search for the review was adapted from the 2021 year in review search, to increase search specificity for relevant study designs, and was conducted in Medline, Embase and medRxiv (31^st March 2021 to 4^th March 2022). Following screening for eligibility, studies were grouped according to their key research design, including reviews, cohorts and randomised trials. 11 key themes emerged, including the importance of several comorbidities in predicting OA incidence and prevalence, surgical approaches that can reduce the risk of post-traumatic OA, the heterogenous but nevertheless relatively stable nature of OA subgroup trajectories, the paucity of robust studies particularly of surgery for OA and the very modest benefit of many therapies under evaluation in trials. A particular interest of the authors was to consider whether new studies are helping determine how to better ensure the right patient with OA is matched to the right treatment at the right time. There are several new studies developing improved predictive models through big data analytics and machine learning which show promise, need validation, and may support new approaches to stratified care.

Elucidating factors contributing to disparities in pain-related experiences among adults with or at risk for knee osteoarthritis

Background and purpose

We and others have reported ethnic/race group differences in clinical pain, physical function, and experimental pain sensitivity. However, recent research indicates that with consideration for socioenvironmental factors, ethnicity/race differences become less or non-significant. Understanding of factors contributing to pain inequities are needed. Guided by the NIA and NIMHD Health Disparities Research Frameworks, we evaluate the contributions of environmental and behavioral factors on previously reported ethnic/race group differences in: (1) clinical pain, (2) physical function, and (3) experimental pain in individuals with knee pain.

Methods

Baseline data from Understanding of Pain and Limitations in Osteoarthritis Disease (UPLOAD) and UPLOAD-2 studies were analyzed. Participants were adults 45 to 85 years old who self-reported as non-Hispanic white (NHW) or black (NHB) with knee pain. A health assessment and quantitative sensory testing were completed. Sociodemographics, environmental, health, clinical and experimental pain, and physical functioning measures were included in nested regressions.

Results

Pooled data from 468 individuals, 57 ± 8 years of age, 63% women, and 53% NHB adults. As NHB adults were younger and reported greater socioenvironmental risk than the NHW adults, the term sociodemographic groups is used. With inclusion of recognized environmental and behavioral variables, sociodemographic groups remained a significant predictor accounting for <5% of the variance in clinical pain and physical function and <10% of variance in experimental pain.

Conclusion

The incorporation of environmental and behavioral factors reduced relationships between sociodemographic groups and pain-related outcomes. Pain sites, BMI, and income were significant predictors across multiple models. The current study adds to a body of research on the complex array of factors contributing to disparities in pain-related outcomes.

Cross-Sectional Brain-Predicted Age Differences in Community-Dwelling Middle-Aged and Older Adults with High Impact Knee Pain

Purpose

Knee OA-related pain varies in impact across individuals and may relate to central nervous system alterations like accelerated brain aging processes. We previously reported that older adults with chronic musculoskeletal pain had a significantly greater brain-predicted age, compared to pain-free controls, indicating an "older" appearing brain. Yet this association is not well understood. This cross-sectional study examines brain-predicted age differences associated with chronic knee osteoarthritis pain, in a larger, more demographically diverse sample with consideration for pain's impact.

Patients and Methods

Participants (mean age = 57.8 ± 8.0 years) with/without knee OA-related pain were classified according to pain's impact on daily function (ie, impact): low-impact (n=111), and high-impact (n=60) pain, and pain-free controls (n=31). Participants completed demographic, pain, and psychosocial assessments, and T1-weighted magnetic resonance imaging. Brain-predicted age difference (brain-PAD) was compared across groups using analysis of covariance. Partial correlations examined associations of brain-PAD with pain and psychosocial variables.

Results

Individuals with high-impact chronic knee pain had significantly "older" brains for their age compared to individuals with low-impact knee pain (p < 0.05). Brain-PAD was also significantly associated with clinical pain, negative affect, passive coping, and pain catastrophizing (p's<0.05).

Conclusion

Our findings suggest that high impact chronic knee pain is associated with an older appearing brain on MRI. Future studies are needed to determine the impact of pain-related interference and pain management on somatosensory processing and brain aging biomarkers for high-risk populations and effective intervention strategies.

Characterizing 16-Week Responder Profiles Using Group-Based Trajectory Modeling in Over 4300 Clinical Trial Participants Receiving Pharmaceutical Treatment for Moderate to Severe Osteoarthritis

INTRODUCTION

We sought to identify and characterize distinct responder profiles among osteoarthritis (OA) subjects treated with tanezumab, nonsteroidal anti-inflammatory drugs (NSAIDs), or placebo.

METHODS

Subject-level data were derived from three randomized, double-blind, placebo- or NSAID-controlled trials of tanezumab in subjects with moderate-to-severe OA. Subjects received subcutaneous tanezumab (2.5 mg, n = 1527; 5 mg, n = 1279) every 8 weeks, oral NSAIDs (n = 994) daily, or placebo (n = 513). Group-based trajectory modeling (GBTM, an application of finite mixture statistical modeling that uses response trajectory to identify and summarize complex patterns in longitudinal data) was used to identify subgroups of subjects following similar patterns of response in each treatment arm, based on daily pain intensity scores from baseline through Week 16. We then examined whether subject-related variables were associated with any of the subgroups using multinomial logistic regression.

RESULTS

A three-subgroup/four-inflection point trajectory model was selected based on clinical and statistical considerations. The subgroups were high responders (substantial pain improvement and a large majority of members achieved ≥ 30% improvement before Week 16), medium responders (gradual pain improvement and a majority of members achieved ≥ 30% improvement by Week 16), and non-responders (little to no pain improvement over 16 weeks). Across all treatments, fluctuation in pain intensity in the week prior to treatment was consistently associated with treatment response. Other variables were positively (age, body mass index, days of rescue medication use) or negatively (severity of disease based on Kellgren-Lawrence grading) associated with response but effects were small and/or varied across treatments.

CONCLUSIONS

Across all treatments, GBTM identified three subgroups of subjects that were characterized by extent of treatment response (high, medium, and non-responders). Similar analyses (e.g., grouping of subjects based on response trajectory and identification of subgroup-related variables) in other studies of OA could inform clinical trial design and/or treatment approaches. (NCT02697773; NCT02709486; NCT02528188).

Short-term pain trajectories in patients with knee osteoarthritis

AIM

It is unknown if pain in knee osteoarthritis (KOA) follows distinct patterns over the short term. Therefore, the aim of this study was to identify whether persons with a previous history of KOA pain fluctuations have distinct trajectories of pain over 90 days and to examine associations between baseline characteristics and pain trajectories.

METHOD

People with a previous history of KOA were selected from a web-based longitudinal study. Baseline variables were sex, age, being obese/overweight, years of KOA, knee injury, knee buckling, satisfactory Lubben Social Support Score, pain and stress scales, Intermittent Constant Osteoarthritis Pain Score (ICOAP), medication use, and physical activity. Participants completed a Knee Injury and Osteoarthritis Outcomes Score (KOOS) pain subscale (KOOS-p, rated 0 = extreme to 100 = no knee problems) at 10-day intervals for 90 days. Short-term KOOS-p trajectories were identified using latent growth mixture modeling and the baseline risk factors for these pain trajectories were examined.

RESULTS

Participants (n = 313) had a mean age of 62.2 (SD ± 8.1) years and and a body mass index of 29.8 (SD ± 6.6) kg/m² . The three-class latent growth mixture modeling quadratic model with best fit indices was chosen (based on lowest sample-size-adjusted Bayesian Information Criterion, high probability of belonging, interpretability). Three distinct pain trajectory clusters (over 90 days) were identified: low-moderate pain at baseline with large improvement (n = 11), minimal change in pain over 90 days (n = 248), and moderate-high pain with worsening (n = 46). Higher ICOAP (intermittent scale), perceived stress, negative affect score, and knee buckling at baseline were associated with a worse knee pain trajectory (P < 0.05).

CONCLUSIONS

Persons with KOA showed unique short-term pain trajectories over 90 days, with distinct characteristics at baseline associated with each trajectory.