Statistical shape modeling of the hip and the association with hip osteoarthritis: a systematic review

Objective: To summarize available evidence on the association between hip shape as quantified by statistical shape modeling (SSM) and the incidence or progression of hip osteoarthritis. Design: We conducted a systematic search of five electronic databases, based on a registered protocol (available: PROSPERO CRD42020145411). Articles presenting original data on the longitudinal relationship between radiographic hip shape (quantified by SSM) and hip OA were eligible. Quantitative meta-analysis was precluded because of the use of different SSM models across studies. We used the Newcastle–Ottawa Scale (NOS) for risk of bias assessment. Results: Nine studies (6,483 hips analyzed with SSM) were included in this review. The SSM models used to describe hip shape ranged from 16 points on the femoral head to 85 points on the proximal femur and hemipelvis. Multiple hip shape features and combinations thereof were associated with incident or progressive hip OA. Shape variants that seemed to be consistently associated with hip OA across studies were acetabular dysplasia, cam morphology, and deviations in acetabular version (either excessive anteversion or retroversion). Conclusions: Various radiographic, SSM-defined hip shape features are associated with hip OA. Some hip shape features only seem to increase the risk for hip OA when combined together. The heterogeneity of the used SSM models across studies precludes the estimation of pooled effect sizes. Further studies using the same SSM model and definition of hip OA are needed to allow for the comparison of outcomes across studies, and to validate the found associations

Staging of osteoarthritis for clinical trials on femoroacetabular impingement

Future clinical trials investigating the natural history and treatment of femoroacetabular impingement (FAI) will require multimodal staging systems for hip osteoarthritis because the optimal system will differ based on the size of the study population, the specific objective in question, and the time frame in which the investigator expects to see the specified end point. Plain radiographs are readily available, low in cost, and of unquestioned validity, but they are relatively insensitive to early joint damage. MRI allows assessment of both bony and soft-tissue pathology within the joint, and it is much more sensitive for early joint damage because cartilage is visualized directly. Biochemical imaging techniques such as delayed gadolinium-enhanced MRI of cartilage, T2 mapping, and T1rho offer the potential to identify biochemical damage to cartilage before the onset of irreversible tissue loss. In the future, biomarkers may allow earlier detection of osteoarthritis before the development of radiographic evidence of disease

The current state of the osteoarthritis drug development pipeline:a comprehensive narrative review of the present challenges and future opportunities

Abstract In this narrative review article, we critically assess the current state of the osteoarthritis (OA) drug development pipeline. We discuss the current state-of-the-art in relation to the development and evaluation of candidate disease-modifying OA drugs (DMOADs) and the limitations associated with the tools and methodologies that are used to assess outcomes in OA clinical trials. We focus on the definition of DMOADs, highlight the need for an updated definition in the form of a consensus statement from all the major stakeholders, including academia, industry, regulatory agencies, and patient organizations, and provide a summary of the results of recent clinical trials of novel DMOAD candidates. We propose that DMOADs should be more appropriately targeted and investigated according to the emerging clinical phenotypes and molecular endotypes of OA. Based on the findings from recent clinical trials, we propose key topics and directions for the development of future DMOADs

An updated algorithm recommendation for the management of knee osteoarthritis from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO)

Objectives: The European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) sought to revisit the 2014 algorithm recommendations for knee osteoarthritis (OA), in light of recent efficacy and safety evidence, in order to develop an updated stepwise algorithm that provides practical guidance for the prescribing physician that is applicable in Europe and internationally. Methods: Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process, a summary of evidence document for each intervention in OA was provided to all members of an ESCEO working group, who were required to evaluate and vote on the strength of recommendation for each intervention. Based on the evidence collected, and on the strength of recommendations afforded by consensus of the working group, the final algorithm was constructed. Results: An algorithm for management of knee OA comprising a stepwise approach and incorporating consensus on 15 treatment recommendations was prepared by the ESCEO working group. Both “strong” and “weak” recommendations were afforded to different interventions. The algorithm highlights the continued importance of non-pharmacological interventions throughout the management of OA. Benefits and limitations of different pharmacological treatments are explored in this article, with particular emphasis on safety issues highlighted by recent literature analyses. Conclusions: The updated ESCEO stepwise algorithm, developed by consensus from clinical experts in OA and informed by available evidence for the benefits and harms of various treatments, provides practical, current guidance that will enable clinicians to deliver patient-centric care in OA practice

Mapping the Oxford hip score onto the EQ-5D utility index

PURPOSE: To assess different mapping methods for the estimation of a group's mean EQ-5D score based on responses to the Oxford hip score (OHS) questionnaire. METHODS: Four models were considered: a) linear regression using total OHS as a continuous regressor; b) linear regression employing responses to the twelve OHS questions as categorical predictors; c) two-part approach combining logistic and linear regression; and d) response mapping. The models were internally validated on the estimation data set, which included OHS and EQ-5D scores for total hip replacements, both before and six months after procedure for 1,759 operations. An external validation was also performed. RESULTS: All models estimated the mean EQ-5D score within 0.005 of an observed health-state utility estimate, ordinary least squares (OLS) continuous being the most accurate and OLS categorical the most consistent. Age, gender and deprivation did not improve the models. More accurate estimations at the individual level were achieved for higher scores of observed OHS and EQ-5D. CONCLUSION: Based on these results, when EQ-5D scores are not available, answers to the OHS questionnaire can be used to estimate a group's mean EQ-5D with a high degree of accuracy

Mapping the Oxford hip score onto the EQ-5D utility index

PURPOSE: To assess different mapping methods for the estimation of a group's mean EQ-5D score based on responses to the Oxford hip score (OHS) questionnaire. METHODS: Four models were considered: a) linear regression using total OHS as a continuous regressor; b) linear regression employing responses to the twelve OHS questions as categorical predictors; c) two-part approach combining logistic and linear regression; and d) response mapping. The models were internally validated on the estimation data set, which included OHS and EQ-5D scores for total hip replacements, both before and six months after procedure for 1,759 operations. An external validation was also performed. RESULTS: All models estimated the mean EQ-5D score within 0.005 of an observed health-state utility estimate, ordinary least squares (OLS) continuous being the most accurate and OLS categorical the most consistent. Age, gender and deprivation did not improve the models. More accurate estimations at the individual level were achieved for higher scores of observed OHS and EQ-5D. CONCLUSION: Based on these results, when EQ-5D scores are not available, answers to the OHS questionnaire can be used to estimate a group's mean EQ-5D with a high degree of accuracy