Harmonising data collection from osteoarthritis studies to enable stratification: recommendations on core data collection from an Arthritis Research UK clinical studies group

Fundamentals of osteoarthritis: outcome evaluation with patient-reported measures and functional tests

Evaluating outcome in osteoarthritis (OA) clinical research and practice requires reliable, valid and responsive patient-reported outcome measures (PROMs) and functional tests that reflect important problems experienced by people with OA. The goal of this work is to provide information to start to guide the reader in selecting measures for people with OA. In this narrative review, we begin by providing an overview of measurement properties that can help clinicians and researchers in making decisions about whether a measure might be appropriate for use in their research or clinical context. We then report evidence supporting the use of measures of pain (e.g., Pain Visual Analogue (VAS), Numeric Pain Rating Scale (NPRS), Intermittent and Constant Osteoarthritis Pain, PROMIS Pain Interference, and, for screening in research, the painDETECT and the Self-report Leeds Assessment of Neuropathic Symptoms and Signs) and fatigue (e.g., PROMIS-Fatigue) at a group level in clinical research. Several multi-dimensional joint-specific measures (e.g., Western Ontario McMaster Universities' Osteoarthritis Outcomes Scale, Knee/Hip Injury and Osteoarthritis Outcome Score, Oxford Hip/Knee Scale) also have evidence for group-level use. Functional tests (e.g., timed walk tests, 30 Second Chair Stand, Timed Up and Go, etc.) have measurement properties supporting their use at the group level in clinical research and at the individual patient level as do the pain VAS and NPRS. Other generic and disease-specific PROMs have been used in or could be used in OA studies but their measurement properties require further evaluation in people with OA.

The future of deep phenotyping in osteoarthritis: How can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease?

Osteoarthritis (OA) is the most common form of musculoskeletal disease with significant healthcare costs and unmet needs in terms of early diagnosis and treatment. Many of the drugs that have been developed to treat OA failed in phase 2 and phase 3 clinical trials or produced inconclusive and ambiguous results. High throughput omics technologies are a powerful tool to better understand the mechanisms of the development of OA and other arthritic diseases. In this paper we outline the strategic reasons for increasingly applying deep phenotyping in OA for the benefit of gaining a better understanding of disease mechanisms and developing targeted treatments. This editorial is intended to launch a special themed issue of Osteoarthritis and Cartilage Open addressing the timely topic of "Advances in omics technologies for deep phenotyping in osteoarthritis". High throughput omics technologies are increasingly being applied in mechanistic studies of OA and other arthritic diseases. Applying multi-omics approaches in OA is a high priority and will allow us to gather new information on disease pathogenesis at the cellular level, and integrate data from diverse omics technology platforms to enable deep phenotyping. We anticipate that new knowledge in this area will allow us to harness the power of Big Data Analytics and resolve the extremely complex and overlapping clinical phenotypes into molecular endotypes, revealing new information about the cellular taxonomy of OA and "druggable pathways", thus facilitating future drug development.

Clinical and molecular associations with outcomes at 2 years after acute knee injury: a longitudinal study in the Knee Injury Cohort at the Kennedy (KICK)

BACKGROUND

Joint injury is a major risk factor for osteoarthritis and provides an opportunity to prospectively examine early processes associated with osteoarthritis. We investigated whether predefined baseline demographic and clinical factors, and protein analytes in knee synovial fluid and in plasma or serum, were associated with clinically relevant outcomes at 2 years after knee injury.

METHODS

This longitudinal cohort study recruited individuals aged 16-50 years between Nov 1, 2010, and Nov 28, 2014, across six hospitals and clinics in London, UK. Participants were recruited within 8 weeks of having a clinically significant acute knee injury (effusion and structural injury on MRI), which was typically treated surgically. We measured several predefined clinical variables at baseline (eg, time from injury to sampling, extent and type of joint injury, synovial fluid blood staining, presence of effusion, self-reported sex, age, and BMI), and measured 12 synovial fluid and four plasma or serum biomarkers by immunoassay at baseline and 3 months. The primary outcome was Knee Injury and Osteoarthritis Outcome Score (KOOS4) at 2 years, adjusted for baseline score, assessed in all patients. Linear and logistic regression models adjusting for predefined covariates were used to assess associations between baseline variables and 2-year KOOS4. This study is registered with ClinicalTrials.gov, number NCT02667756.

FINDINGS

We enrolled 150 patients at a median of 17 days (range 1-59, IQR 9-26) after knee injury. 123 (82%) were male, with a median age of 25 years (range 16-50, IQR 21-30). 98 (65%) of 150 participants completed a KOOS4 at 2 (or 3) years after enrolment (50 participants were lost to follow-up and two were withdrawn due to adverse events unrelated to study participation); 77 (51%) participants had all necessary variables available and were included in the core variable adjusted analysis. In the 2-year dataset mean KOOS4 improved from 38 (SD 18) at baseline to 79 (18) at 2 years. Baseline KOOS4, medium-to-large knee effusion, and moderate-to-severe synovial blood staining and their interaction significantly predicted 2-year KOOS4 (n=77; coefficient -20·5, 95% CI -34·8 to -6·18; p=0·0060). The only predefined biomarkers that showed independent associations with 2-year KOOS4 were synovial fluid MCP-1 (n=77; -0·015, 0·027 to -0·004 per change in 1 pg/mL units; p=0·011) and IL-6 (n=77; -0·0005, -0·0009 to -0·0001 per change in 1 pg/mL units; p=0·017). These biomarkers, combined with the interaction of effusion and blood staining, accounted for 39% of outcome variability. Two adverse events occurred that were linked to study participation, both at the time of blood sampling (one presyncopal episode, one tenderness and pain at the site of venepuncture).

INTERPRETATION

The combination of effusion and haemarthrosis was significantly associated with symptomatic outcomes after acute knee injury. The synovial fluid molecular protein response to acute knee injury (best represented by MCP-1 and IL-6) was independently associated with symptomatic outcomes but not with structural outcomes, with the biomarkers overall playing a minor role relative to clinical predictors. The relationship between symptoms and structure after acute knee injury and their apparent dissociation early in this process need to be better understood to make clinical progress.

FUNDING

Versus Arthritis, Kennedy Trust for Rheumatology Research, and NIHR Oxford Biomedical Research Centre.

Clinical Efficacy and Safety of Thai Herbal Formulation-6 in the Treatment of Symptomatic Osteoarthritis of the Knee: A Randomized-Controlled Trial

Background

Osteoarthritis of the knee is the most common form of arthritis. Identifying effective and safe herbal formulations that are locally available is viewed as a priority for sustainable development in a region. This study aimed to evaluate the efficacy and safety of Thai herbal formulation-6 (THF-6) in comparison with oral diclofenac in patients with moderate-to-severe osteoarthritis of the knee.

Methods

This randomized, double-blind, active-controlled, noninferiority trial randomly assigned patients with osteoarthritis of the knee to receive either THF-6 or diclofenac for four weeks. The primary outcome measure was the change from baseline in knee pain as measured by a 100 mm visual analog scale (VAS). Secondary outcome measures included knee stiffness, a stair climb test, the Knee Injury and Osteoarthritis Outcome Score, and safety parameters. Outcomes were assessed on a biweekly basis. Modified intention-to-treat (MITT) and perprotocol (PP) analyses were applied.

Results

A total of 200 patients were enrolled of whom 175 (87.5%) were included in the MITT analysis and 153 (76.5%) in the PP analysis. The mean change in VAS pain did not differ between the two groups, and the upper limit of the two-sided 95% confidence interval (CI) for comparison between the two groups was within the prespecified margin of 10 mm for noninferiority (MITT analysis: mean difference = 0.86, 95% CI = -4.39 to 6.10, p=0.748; PP analysis: mean difference = 1.98, 95% CI = -3.61 to 7.56, p=0.486). Significant improvement was observed in all the efficacy parameters in both groups. Dyspepsia was the most common adverse event: 23 patients in the THF-6 group and 28 in the diclofenac group (p=0.417).

Conclusions

THF-6 offers an alternative to oral diclofenac for the short-term treatment of osteoarthritis of the knee. It was shown to be noninferior to oral diclofenac in relieving knee pain. This trial is registered with ChiCTR-IPR-15007213.

The use of technology in the subcategorisation of osteoarthritis: a Delphi study approach

Objective

This UK-wide OATech Network + consensus study utilised a Delphi approach to discern levels of awareness across an expert panel regarding the role of existing and novel technologies in osteoarthritis research. To direct future cross-disciplinary research it aimed to identify which could be adopted to subcategorise patients with osteoarthritis (OA).

Design

An online questionnaire was formulated based on technologies which might aid OA research and subcategorisation. During a two-day face-to-face meeting concordance of expert opinion was established with surveys (23 questions) before, during and at the end of the meeting (Rounds 1, 2 and 3, respectively). Experts spoke on current evidence for imaging, genomics, epigenomics, proteomics, metabolomics, biomarkers, activity monitoring, clinical engineering and machine learning relating to subcategorisation. For each round of voting, ≥80% votes led to consensus and ≤20% to exclusion of a statement.

Results

Panel members were unanimous that a combination of novel technological advances have potential to improve OA diagnostics and treatment through subcategorisation, agreeing in Rounds 1 and 2 that epigenetics, genetics, MRI, proteomics, wet biomarkers and machine learning could aid subcategorisation. Expert presentations changed participants' opinions on the value of metabolomics, activity monitoring and clinical engineering, all reaching consensus in Round 2. X-rays lost consensus between Rounds 1 and 2; clinical X-rays reached consensus in Round 3.

Conclusion

Consensus identified that 9 of the 11 technologies should be targeted towards OA subcategorisation to address existing OA research technology and knowledge gaps. These novel, rapidly evolving technologies are recommended as a focus for emergent, cross-disciplinary osteoarthritis research programmes.

Risk factors for pain and functional impairment in people with knee and hip osteoarthritis: a systematic review and meta-analysis

OBJECTIVE

To identify risk factors for pain and functional deterioration in people with knee and hip osteoarthritis (OA) to form the basis of a future 'stratification tool' for OA development or progression.

DESIGN

Systematic review and meta-analysis.

METHODS

An electronic search of the literature databases, Medline, Embase, CINAHL, and Web of Science (1990-February 2020), was conducted. Studies that identified risk factors for pain and functional deterioration to knee and hip OA were included. Where data and study heterogeneity permitted, meta-analyses presenting mean difference (MD) and ORs with corresponding 95% CIs were undertaken. Where this was not possible, a narrative analysis was undertaken. The Downs & Black tool assessed methodological quality of selected studies before data extraction. Pooled analysis outcomes were assessed and reported using the Grading of Reccomendation, Assessment, Development and Evaluation (GRADE) approach.

RESULTS

82 studies (41 810 participants) were included. On meta-analysis: there was moderate quality evidence that knee OA pain was associated with factors including: Kellgren and Lawrence≥2 (MD: 2.04, 95% CI 1.48 to 2.81; p<0.01), increasing age (MD: 1.46, 95% CI 0.26 to 2.66; p=0.02) and whole-organ MRI scoring method (WORMS) knee effusion score ≥1 (OR: 1.35, 95% CI 0.99 to 1.83; p=0.05). On narrative analysis: knee OA pain was associated with factors including WORMS meniscal damage ≥1 (OR: 1.83). Predictors of joint pain in hip OA were large acetabular bone marrow lesions (BML; OR: 5.23), chronic widespread pain (OR: 5.02) and large hip BMLs (OR: 4.43).

CONCLUSIONS

Our study identified risk factors for clinical pain in OA by imaging measures that can assist in predicting and stratifying people with knee/hip OA. A 'stratification tool' combining verified risk factors that we have identified would allow selective stratification based on pain and structural outcomes in OA.

PROSPERO REGISTRATION NUMBER

CRD42018117643.

New Drug Treatments for Osteoarthritis: What Is on the Horizon?

Osteoarthritis (OA) is the most common form of arthritis, yet has historically lagged far behind rheumatoid arthritis in terms of drug development. Despite the many challenges presented by clinical trials in OA, improvements in our understanding of disease pathogenesis and a move to treat pain, as well as underlying disease process, mean there are now many new pharmacological therapies currently in various stages of clinical trials. The medical need for these therapies and the evidence for recent tissue and molecular targets are reviewed. Current therapeutic examples in each area are discussed, including both novel therapeutics and existing agents which may be repurposed from other disease areas. Some challenges remain, but opportunities for improving symptoms and disease process in OA in the clinic with new pharmacological agents would appear to be on the close horizon.

New Drug Treatments for Osteoarthritis: What is on the Horizon?

Osteoarthritis (OA) is the most common form of arthritis, yet has historically lagged far behind rheumatoid arthritis in terms of drug development. Despite the many challenges presented by clinical trials in OA, improvements in our understanding of disease pathogenesis and a move to treat pain, as well as underlying disease process, mean there are now many new pharmacological therapies currently in various stages of clinical trials. The medical need for these therapies and the evidence for recent tissue and molecular targets are reviewed. Current therapeutic examples in each area are discussed, including both novel therapeutics and existing agents which may be repurposed from other disease areas. Some challenges remain, but opportunities for improving symptoms and disease process in OA in the clinic with new pharmacological agents would appear to be on the close horizon.