Understanding the Complexity of Pain in Osteoarthritis Through the Use of Pain Phenotyping: Current Evidence

Latent transition analysis of pain phenotypes in people at risk of knee osteoarthritis: The MOST cohort study

OBJECTIVE

Pain phenotypes (PP) have been identified across different stages of knee osteoarthritis (KOA) and understanding the stability of PPs prior to the development of symptomatic KOA can help to inform preventative strategies. We aimed to identify PPs and their transitions in people without radiographic KOA and profile participant characteristics.

DESIGN

Data from 5 - (T1), 7- (T2) and 12-year (T3) visits from the Multicenter Osteoarthritis Study (MOST) were used. Individuals with Kellgren-Lawrence grade 0 and knee pain ≤30/100 at T1 were sampled. PP variables included pressure pain thresholds, temporal summation (with method changed at T3), depressive symptoms, pain catastrophizing, sleep quality, and widespread pain. Latent Transition Analysis using Bayesian Information Criteria informed class numbers and transitions. Unconstrained, constrained, and modified constrained models (conditional response probabilities fixed for indicator variables except for TS) were compared for fit. Participant characteristics were used to profile class membership.

RESULTS

348 individuals (59% females), mean age (SD): 59.3 (6.7) were included. The optimal model fit for data across T1-T3 was a "modified" constrained model with 3 classes (class 1: low pain burden, class 2: high pain sensitization, class 3: high psychological burden). Classes were similar over time except for the increased probability of TS at T3. Most (86%) participants remained in the same class; only 14% transitioned overtime.

CONCLUSION

Distinct PPs were identified in those at risk of KOA that remained stable over time, suggesting these trait-like features may require consideration for comprehensive management of the symptom experience.

Clinical phenotypes and prognostic factors in persons with hip osteoarthritis undergoing total hip arthroplasty: protocol for a longitudinal prospective cohort study (HIPPROCLIPS)

BACKGROUND

Large heterogeneity exists in the clinical manifestation of hip osteoarthritis (OA). It is therefore not surprising that pain and disability in individuals with hip OA and after total hip arthroplasty (THA) cannot be explained by biomedical variables alone. Indeed, also maladaptive pain-related cognitions and emotions can contribute to pain and disability, and can lead to poor treatment outcomes. Traumatic experiences, mental disorders, self-efficacy and social support can influence stress appraisal and strategies to cope with pain, but their influence on pain and disability has not yet been established in individuals with hip OA undergoing THA. This study aims (1) to determine the influence of traumatic experiences and mental disorders on pain processing before and shortly after THA (2) to identify preoperative clinical phenotypes in individuals with hip OA eligible for THA, (3) to identify pre- and early postoperative prognostic factors for outcomes in pain and disability after THA, and (4) to identify postoperative clinical phenotypes in individuals after THA.

METHODS

This prospective longitudinal cohort study will investigate 200 individuals undergoing THA for hip OA. Phenotyping variables and candidate prognostic factors include pain-related fear-avoidance behaviour, perceived injustice, mental disorders, traumatic experiences, self-efficacy, and social support. Peripheral and central pain mechanisms will be assessed with thermal quantitative sensory testing. The primary outcome measure is the hip disability and osteoarthritis outcome score. Other outcome measures include performance-based measures, hip muscle strength, the patient-specific functional scale, pain intensity, global perceived effect, and outcome satisfaction. All these measurements will be performed before surgery, as well as 6 weeks, 3 months, and 12 months after surgery. Pain-related cognitions and emotions will additionally be assessed in the early postoperative phase, on the first, third, fifth, and seventh day after THA. Main statistical methods that will be used to answer the respective research questions include: LASSO regression, decision tree learning, gradient boosting algorithms, and recurrent neural networks.

DISCUSSION

The identification of clinical phenotypes and prognostic factors for outcomes in pain and disability will be a first step towards pre- and postoperative precision medicine for individuals with hip OA undergoing THA.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05265858. Registered on 04/03/2022.

Study Protocol Modeling Evoked Pain in Older African Americans With Knee Osteoarthritis

BACKGROUND

African American (AA) older adults with knee osteoarthritis experience more severe chronic pain and advanced physical disability. One of the most prominent stimuli that provokes knee pain is movement. Research suggests that, compared to Whites, AAs report significantly higher movement-evoked pain (MEP) in the knee. However, little is known about the biopsychosocial-behavioral mechanisms underlying MEP.

OBJECTIVES

The aim of the study was to present a study protocol to (a) characterize the biopsychosocial-behavioral mechanisms that predict MEP in AAs with knee osteoarthritis and (b) develop a targeted, mechanism-based self-management intervention to reduce MEP and maximize movement.

METHODS

An observational, mixed-methods cohort study will enroll 90 AA/Black adults (ages 55-90 years) to understand intraindividual and interindividual effects on MEP. Participants will complete assessments of MEP, function and gait, biopsychosocial-behavioral questionnaires, quantitative sensory testing, and 7-day ecological momentary assessments of pain and related symptoms. For the qualitative phase, focus groups will be conducted to co-construct a mechanism-based pain self-management intervention.

RESULTS

We will develop phenotypes of MEP based on biopsychosocial-behavioral predictors and correlate measures of MEP with function. Our central hypothesis is that higher levels of MEP will predict lower self-reported function and poorer performance on functional tasks and that multiple biopsychosocial and behavioral factors will be associated with MEP and function. Predictors may serve as risk or protective factors for MEP and physical function. In targeting the biopsychosocial-behavioral mechanisms of MEP, we anticipate that older AAs may request that intervention components include culturally tailored self-management education, movement/physical activity training, treatment decision-making skills, coaching, spirituality, and social/kinship support.

CONCLUSION

Osteoarthritis is now the single most common cause of disability, mobility limitations, and persistent pain in older adults-especially AA older adults. To our knowledge, this will be the first study to systematically phenotype MEP in an older racial minority population with knee osteoarthritis and will be relevant for reducing knee pain and improving function.

In Vitro Human Joint Models Combining Advanced 3D Cell Culture and Cutting-Edge 3D Bioprinting Technologies

Joint-on-a-chip is a new technology able to replicate the joint functions into microscale systems close to pathophysiological conditions. Recent advances in 3D printing techniques allow the precise control of the architecture of the cellular compartments (including chondrocytes, stromal cells, osteocytes and synoviocytes). These tools integrate fluid circulation, the delivery of growth factors, physical stimulation including oxygen level, external pressure, and mobility. All of these structures must be able to mimic the specific functions of the diarthrodial joint: mobility, biomechanical aspects and cellular interactions. All the elements must be grouped together in space and reorganized in a manner close to the joint organ. This will allow the study of rheumatic disease physiopathology, the development of biomarkers and the screening of new drugs.