Differentiating knee pain phenotypes in older adults: a prospective cohort study

Dietary Inflammatory Index and Magnetic Resonance Imaging-Detected Knee Structural Change and Pain: A 10.7-Year Follow-up Study

OBJECTIVE

To determine whether the dietary inflammatory index (DII) scores were associated with knee structural changes and pain over a 10.7-year follow-up.

METHODS

This study used data from a prospective population-based cohort study (mean age 63 years, 51% female) in which 1,099, 875, 768, and 566 participants completed assessments at baseline, 2.6, 5.1, and 10.7 years, respectively. T1-weighted and T2-weighted magnetic resonance imaging was performed to measure cartilage volume (CV) and bone marrow lesions (BMLs) at baseline and 10.7 years. The Western Ontario and McMaster Universities Osteoarthritis Index pain questionnaire was used to measure knee pain at each visit. Pain trajectories ("minimal pain," "mild pain," and "moderate pain") were previously identified. Baseline energy-adjusted DII (E-DII) scores were calculated. Linear, log-binomial regression, linear mixed-effects modeling, and multi-nominal logistic regression were used for analyses.

RESULTS

The mean ± SD E-DII score at baseline was -0.48 ± 1.39. In multivariable analyses, higher E-DII scores were not associated with tibial CV loss or BML size increase except for medial tibial BML size increase. Higher E-DII scores were associated with a higher pain score (β = 0.21; 95% confidence interval [CI] 0.004-0.43) and an increased risk of belonging to the "moderate pain" compared to the "minimal pain" trajectory group (relative risk ratio 1.19; 95% CI 1.02-1.39).

CONCLUSION

A proinflammatory diet, as indicated by a higher DII score, may be associated with a greater pain score and higher risk of more severe pain trajectory over 10 years. However, inconsistent findings related to structural changes suggest a discordance between the potential impact of diet on structural damage and pain in knee OA.

Clinical Assessment of Osteoarthritis Pain: Contemporary Scenario, Challenges, and Future Perspectives

The multifaceted nature of osteoarthritis (OA) pain presents a challenge in understanding and managing the condition. The diverse pain experiences, progression rates, individual responses to treatments, and complex disease mechanisms contribute to heterogeneity in the clinical studies outcomes. The lack of a standardized methodology for assessing and classifying OA pain challenges healthcare practitioners. This complicates the establishment of universally applicable protocols or standardized guidelines for treatment. This article explores the heterogeneity observed in clinical studies evaluating OA pain treatments, highlighting the necessity for refined methodologies, personalized patient categorization, and consistent outcome measures. It discusses the role of the multidimensional nature of OA pain, underlying pain mechanisms, and other contributing factors to the heterogeneity in outcome measures. Addressing these variations is crucial to establishing a more consistent framework for evidence-based treatments and advancing care of the patient with OA pain.

Pain-phenotyping in osteoarthritis: Current concepts, evidence, and considerations towards a comprehensive framework for assessment and treatment

Objectives

Pain as central symptom of osteoarthritis (OA) needs to be addressed as part of successful treatment. The assessment of pain as feature of disease or outcome in clinical practice and drug development remains a challenge due to its multidimensionality and the plethora of confounders. This article aims at providing insights into our understanding of OA pain-phenotypes and suggests a framework for systematic and comprehensive assessments.

Methods

This narrative review is based on a search of current literature for various combinations of the search terms "pain-phenotype" and "knee OA" and summarizes current knowledge on OA pain-phenotypes, putting OA pain and its assessment into perspective of current research efforts.

Results

Pain is a complex phenomenon, not necessarily associated with tissue damage. Various pain-phenotypes have been described in knee OA. Among those, a phenotype with high pain levels not necessarily matching structural changes and a phenotype with low pain levels and impact are relatively consistent. Further subgroups can be differentiated based on patient reported outcome measures, assessments of comorbidities, anxiety and depression, sleep, activity and objective measures such as quantitative sensory testing.

Conclusions

The complexity of both OA as disease and pain in OA prompt the definition of a set of variables that facilitate assessments comparable across studies to maximize our understanding of pain, as central concern for the patient.

Exploring different models of pain phenotypes and their association with pain worsening in people with early knee osteoarthritis: The MOST cohort study

OBJECTIVE

To determine i) pain phenotypes (PP) in people with early-stage knee osteoarthritis (EKOA); ii) the longitudinal association between the phenotypes and pain worsening at two years.

DESIGN

We studied participants with EKOA from the Multicenter Osteoarthritis Study defined as pain intensity ≤3/10, Kellgren and Lawrence grade ≤2, intermittent pain none to sometimes, and no constant pain. Two models of PP were explored. Model A included pressure pain thresholds, temporal summation, conditioned pain modulation, pain catastrophizing, sleep quality, depression, and widespread pain (WSP). In Model B, gait characteristics, quadriceps strength, comorbidities, and magnetic resonance imaging features were added to Model A. Latent Class Analysis was used to create phenotypes, and logistic regression was used to determine their association with pain worsening.

RESULTS

750 individuals (60% females), mean age [standard deviation (SD)]: 60.3 (9.4) were included in Model A and 333 individuals (60% females), mean age (SD): 59.4 (8.1) in Model B. 3-class and 4-class solutions were chosen for Model A and Model B. In Model A, the most "severe" phenotype was dominated by psychosocial factors, WSP, and measures of nervous system sensitization. Similarly in Model B, the Model A phenotype plus gait variables, quadriceps strength, and comorbidities were dominant. Surprisingly, none of the phenotypes in either model had a significant relationship with pain worsening.

CONCLUSION

Phenotypes based upon various factors thought to be important for the pain experience were identified in those with EKOA but were not significantly related to pain worsening. These phenotypes require validation with clinically relevant endpoints.

Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort

OBJECTIVE

To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care.

DESIGN

Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation.

RESULTS

Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features.

CONCLUSIONS

Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection.

Singapore KneE osTeoarthritis CoHort (SKETCH): protocol for a multi-centre prospective cohort study

BACKGROUND

Knee osteoarthritis (OA) is a leading cause of global disability. The understanding of the role of psychosocial factors in knee OA outcomes is still evolving particularly in an Asian context. The primary aim of this study is to explore psychosocial factors that prognosticate short and long-term clinical outcomes, productivity, and healthcare utilization in patients with knee OA. Secondary aims are to explore the mediation and directional relationships and the role it plays in predicting the discordance between self-reported measures (SRM), physical-performance measures (PPMs) and objective clinical parameters.

METHODS

A multi-centre prospective cohort study of community ambulant knee OA patients seeking treatment in the tertiary healthcare institutions in Singapore will be conducted. Patients with secondary arthritis, significant cognitive impairment, severe medical comorbidities or previous knee arthroplasty will be excluded. Primary clinical outcome measure is the Knee injury and OA Outcome Score-12 (KOOS-12). Baseline characteristics include sociodemographic status, arthritis status including symptom duration and radiographic severity, comorbidities and functional status through Charlson Comorbidities Index (CCI), Barthel Index (BI) and Parker Mobility Score (PMS). Psychosocial variables include social support, kinesiophobia, negative affect, self-efficacy, injustice, chronic illness shame and the built environment. Clinical outcomes include quality of life, physical performance, global assessment, satisfaction and physical activity levels. Productivity and healthcare utilization will be assessed by a modified OA Cost and Consequences Questionnaire (OCC-Q) and the Work Productivity and Activity Impairment Questionnaire (WPAI). Variables will be collected at baseline, 4, 12 months and yearly thereafter. Regression, mediation and structural equation modelling will be used for analysis.

DISCUSSION

Results will allow contextualization, identification, and phenotyping of the critical (and potentially modifiable) psychosocial parameters that predict positive clinical outcomes in the OA population to guide optimization and refinement of healthcare and community. This will facilitate: 1. identification of high-risk knee OA subpopulations that will likely experience poor outcomes and 2. formulation of targeted multidisciplinary comprehensive approaches to address these psychosocial factors to optimize non-surgical treatment care, maximize functional outcomes and create more value-based care model for knee OA.

ETHICS AND DISSEMINATION

The study has been registered under clinicaltrials.gov registry (Identifier: NCT04942236).

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.

Association of Pain Phenotypes with Risk of Falls and Incident Fractures

Objective: To compare whether falls risk score and incident fracture over 10.7 years were different among three previously identified pain phenotypes. Methods: Data on 915 participants (mean age 63 years) from a population-based cohort study were studied at baseline and follow-ups at 2.6, 5.1 and 10.7 years. Three pain phenotypes were previously identified using the latent class analysis: Class 1: high prevalence of emotional problems and low prevalence of structural damage; Class 2: high prevalence of structural damage and low prevalence of emotional problems; Class 3: low prevalence of emotional problems and low prevalence of structural damage. Fractures were self-reported and falls risk score was measured using the Physiological Profile Assessment. Generalized estimating equations model and linear mixed-effects model were used to compare differences in incident fractures and falls risk score over 10.7 years between pain phenotypes, respectively. Results: There were 3 new hip, 19 vertebral, and 121 non-vertebral fractures, and 138 any site fractures during 10.7-year follow-up. Compared with Class 3, Class 1 had a higher risk of vertebral (relative risk (RR) = 2.44, 95% CI: 1.22-4.91), non-vertebral fractures (RR = 1.20, 95% CI: 1.01-1.42), and any site fractures (RR = 1.24, 95% CI: 1.04-1.46) after controlling for covariates, bone mineral density and falls risk score. Class 2 had a higher risk of non-vertebral and any site fracture relative to those in Class 3 (non-vertebral: RR = 1.41, 95% CI: 1.17-1.71; any site: RR = 1.44, 95% CI: 1.20-1.73), but not vertebral fracture. Compared with Class 3, Class 1 had a higher falls risk score at baseline (β = 0.16, 95% CI: 0.09-0.23) and over 10.7-year (β = 0.03, 95% CI: 0.01-0.04). Conclusions: Class 1 and/or Class 2 had a higher risk of incident fractures and falls risk score than Class 3, highlighting that targeted preventive strategies for fractures and falls are needed in pain population.

Study protocol for a randomised controlled trial of diacerein versus placebo to treat knee osteoarthritis with effusion-synovitis (DICKENS)

Background

There is an unmet need for treatments for knee osteoarthritis (OA). Effusion-synovitis is a common inflammatory phenotype of knee OA and predicts knee pain and structural degradation. Anti-inflammatory therapies, such as diacerein, may be effective for this phenotype. While diacerein is recommended for alleviating pain in OA patients, evidence for its effectiveness is inconsistent, possibly because studies have not targeted patients with an inflammatory phenotype. Therefore, we will conduct a multi-centre, randomised, placebo-controlled double-blind trial to determine the effect of diacerein on changes in knee pain and effusion-synovitis over 24 weeks in patients with knee OA and magnetic resonance imaging (MRI)-defined effusion-synovitis.

Methods

We will recruit 260 patients with clinical knee OA, significant knee pain, and MRI-detected effusion-synovitis in Hobart, Melbourne, Adelaide, and Perth, Australia. They will be randomly allocated to receive either diacerein (50mg twice daily) or identical placebo for 24 weeks. MRI of the study knee will be performed at screening and after 24 weeks of intervention. The primary outcome is improvement in knee pain at 24 weeks as assessed by a 100-mm visual analogue scale (VAS). Secondary outcomes include improvement in volumetric (ml) and semi-quantitative (Whole-Organ Magnetic Resonance Imaging Score, 0–3) measurements of effusion-synovitis using MRI over 24 weeks, and improvement in knee pain (VAS) at 4, 8, 12, 16, and 20 weeks. Intention-to-treat analyses of primary and secondary outcomes will be performed as the primary analyses. Per protocol analyses will be performed as the secondary analyses.

Discussion

This study will provide high-quality evidence to determine whether diacerein improves pain, changes disease trajectory, and slows disease progression in OA patients with effusion-synovitis. If diacerein proves effective, this has the potential to significantly benefit the substantial proportion (up to 60%) of knee OA patients with an inflammatory phenotype.

Trial registration

Australian and New Zealand Clinical Trial Registry ACTRN12618001656224. Registered on 08 October 2018.

Use of IMMPACT Recommendations to Explore Pain Phenotypes in People with Knee Osteoarthritis

OBJECTIVE

Knee osteoarthritis (OA) is a disease of multiple phenotypes of which a chronic pain phenotype (PP) is known. Previous PP studies have focused on one domain of pain and included heterogenous variables. We sought to identify multidimensional PPs using the IMMPACT recommendations and their relationship to clinical outcomes.

METHODS

Participants >40 years of age with knee OA having a first-time orthopaedic consultation at five university affiliated hospitals in Montreal, Quebec and Hamilton (Canada) were recruited. Latent profile analysis was used to determine PPs (classes) using variables recommended by IMMPACT. This included pain variability, intensity and qualities, somatization, anxiodepressive symptoms, sleep, fatigue, pain catastrophizing, neuropathic pain, and quantitative sensory tests. We used MANOVA and Chi-square tests to assess differences in participant characteristics across the classes and linear and Poisson regression to evaluate the association of classes to outcomes of physical performance tests, self-reported function and provincial healthcare data.

RESULTS

343 participants were included (mean age 64 years, 64% female). Three classes were identified with increasing pain burden (class3 > class1), characterized by significant differences across most self-report measures and temporal summation, and differed in terms of female sex, younger age, lower optimism and pain self-efficacy. Participants in class2 and class3 had significantly worse self-reported function, stair climb and 40m walk tests, and higher rates of healthcare usage compared to those in class1.

CONCLUSIONS

Three distinct PPs guided by IMMPACT recommendations were identified, predominated by self-report measures and temporal summation. Using this standardized approach may improve PP study variability and comparison.

Preoperative angiotensin II type 2 receptor is a predictor for developing chronic post-surgical pain after total knee arthroplasty surgery

OBJECTIVE

This study aimed to explore whether preoperative angiotensin II type 2 receptor (AT₂R) level in knee osteoarthritis (OA) patients was an independent risk factor for chronic post-surgical pain (CPSP) after total knee arthroplasty (TKA).

METHODS

A total of 220 patients who had undergone unilateral TKA were enrolled from October 2019 to January 2020. Quantitative sensory testing (QST), PainDETECT questionnaires (PD-Q), the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), the hospital anxiety and depression (HAD) and serum AT₂R were collected preoperatively. The primary outcome was the incidence of CPSP, which was defined as the visual analogue scale (VAS) score ≥ 4 in the ipsilateral knee joint six months after operation.

RESULTS

The prevalence of CPSP was 13.6% (n = 30). Multiple logistic regression analysis showed that patients with higher AT₂R level (OR: 1.007, 95% CI: 1.003-1.011) and PD-Q score (OR: 1.146, 95% CI: 1.008-1.298) before surgery had an increased risk of CPSP after surgery, and a combination of preoperative AT₂R and PD-Q (Akaike information criterion: 147.2; area under receiver operating characteristic (ROC) curve: 0.890) was able to correctly classify 90.16% of patients into CPSP positive or negative groups.

CONCLUSION

Our findings suggest that patients with higher preoperative AT₂R level are at increased risk of developing CPSP following TKA. AT₂R may serve as a candidate predictor for phenotyping CPSP in OA patients.

A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment

Purpose

The number of non-responders to treatment among patients with chronic pain (CP) is high, although intensive multimodal treatment is broadly accessible. One reason is the large variability in manifestations of CP. To facilitate the development of tailored treatment approaches, phenotypes of CP must be identified. In this study, we aim to identify subgroups in patients with CP based on several aspects of self-reported health.

Patients and Methods

A latent class analysis (LCA) was carried out in retrospective data from 411 patients with CP of different origins. All patients experienced severe physical and psychosocial consequences and were therefore undergoing multimodal inpatient pain treatment. Self-reported measures of pain (visual analogue scales for pain intensity, frequency, and impairment; Pain Perception Scale), emotional distress (Patient Health Questionnaire, PHQ-9; Generalized Anxiety Disorder Scale, GAD-7) and physical health (Short Form Health Survey; SF-8) were collected immediately after admission and before discharge. Instruments assessed at admission were used as input to the LCA. Resulting classes were compared in terms of patient characteristics and treatment outcome.

Results

A model with four latent classes demonstrated the best model fit and interpretability. Classes 1 to 4 included patients with high (54.7%), extreme (17.0%), moderate (15.6%), and low (12.7%) pain burden, respectively. Patients in class 4 showed high levels of emotional distress, whereas emotional distress in the other classes corresponded to the levels of pain burden. While pain as well as physical and mental health improved in class 1, only the levels of depression and anxiety improved in patients in the other groups during multimodal treatment.

Conclusion

The specific needs of these subgroups should be taken into account when developing individualized treatment programs. However, the retrospective design limits the significance of the results and replication in prospective studies is desirable.

Do Knee Pain Phenotypes Have Different Risks of Total Knee Replacement?

Pain is the main impetus for osteoarthritis (OA) patients to seek healthcare including joint replacement. The pain experience in OA is heterogeneous and affected by factors across multiple domains—peripheral, psychological, and neurological. This indicates the existence of homogenous subgroups/phenotypes within OA patients with pain. We recently identified three pain phenotypes using a wide spectrum of pain-related factors, including structural damage on magnetic resonance imaging (MRI), emotional problems, number of painful sites, sex, body mass index, education level and comorbidities (i.e., Class 1: high prevalence of emotional problems and low prevalence of structural damage (25%); Class 2: low prevalence of emotional problems and high prevalence of structural damage (20%); Class 3: low prevalence of emotional problems and low prevalence of structural damage (55%)). This study was to examine whether the total knee replacement (TKR) risk over 12 years was different among these three pain phenotypes. Data on 963 participants (mean age 62.8 ± 7.4 years) from a population-based cohort study were utilised. Data on socio-demographic, psychological and comorbidities were collected. MRI of the right knee structural pathology was performed. TKR history was ascertained by linking to the Australian Orthopedic Association National Joint Replacement Registry. Latent class analysis and the Cox proportional hazards model were applied for the analysis. During the follow-up period, 41 right and 44 left TKRs in 67 participants were identified. In multivariable analyses, participants in Class 1 and 2 had a higher risk of having a TKR (Class 1 vs. Class 3, HR (hazard ratio) 4.81, 95%CI (confidence interval) 2.33–9.93; Class 2 vs. Class 3, HR 9.23, 95%CI 4.66–18.30). These associations were stronger in the imaged right knee but were also significant in the left knee. Participants within distinct pain phenotypes have different risks of TKR, suggesting that the identified phenotypes reflect distinct clinical subgroups with different prognoses. The risk for TKR was higher in Class 1 than that in Class 3, suggesting that pain/emotional status is a stronger driver for TKR than structural damage, and that selecting patients for TKR needs to be optimized in clinical practice.

Identifying subgroups of community-dwelling older adults and their prospective associations with long-term knee osteoarthritis outcomes

OBJECTIVES

To identify subgroups of community-dwelling older adults and to assess their longitudinal associations with long-term osteoarthritis (OA) outcomes.

METHODS

1046 older adults aged 50-80 years were studied. At baseline, body mass index (BMI), pedometer-measured ambulatory activity (AA), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) determined knee pain and information on comorbidities were obtained. Tibial cartilage volume and bone-marrow lesions (BMLs) were assessed using MRI at baseline and 10 years and total knee replacements (TKR) by data linkage to the Australian Orthopaedic Association National Joint Replacement Registry. Latent class analysis was used to determine participant subgroups, considering baseline BMI, AA, pain and comorbidities, and linear mixed-effects or log-binomial models were used to assess the associations.

RESULTS

Three subgroups/classes were identified: subgroup 1 (43%): Normal/overweight participants with higher AA, lower pain and lower comorbidities; subgroup 2 (32%): Overweight participants with lower AA, mild pain and higher comorbidities; subgroup 3 (25%): Obese participants with lower AA, mild pain and higher comorbidities. Subgroup 3 had greater cartilage volume loss (β - 60.56 mm³, 95% CI - 105.91, - 15.21) and a higher risk of TKR (RR 3.19, 95% CI 1.75, 5.81), compared to subgroup 1. Subgroup 2 was not associated with cartilage volume change (β 13.06 mm³, 95% CI - 30.87, 57.00) or risk of TKR (RR 1.16, 95% CI 0.56, 2.36), compared to subgroup 1. Subgroup membership was not associated with worsening BMLs.

CONCLUSIONS

Our findings suggest the existence of homogeneous subgroups of participants and support the utility of identifying patterns of characteristics/risk factors that may cluster together and using them to identify subgroups of people who may be at a higher risk of developing and/or progressing OA. Key Points • Complex interplay among characteristics/factors leads to conflicting evidence between ambulatory activity and knee osteoarthritis. • Distinct subgroups are identifiable based on ambulatory activity, body mass index, knee pain, and comorbidities. • Identifying subgroups can be used to determine those who are at risk of developing/progressing osteoarthritis.