Dataset Information

Prodromal symptoms in knee osteoarthritis: a nested case-control study using data from the Osteoarthritis Initiative.

ABSTRACT:

Objective

In order to gain a better understanding of the timing of emergent symptoms of osteoarthritis, we sought to investigate the existence, duration and nature of a prodromal symptomatic phase preceding incident radiographic knee osteoarthritis (ROA).

Design

Data were from the incidence cohort of the Osteoarthritis Initiative (OAI) public use datasets. Imposing a nested case-control design, ten control knees were selected for each case of incident tibiofemoral ROA between 2004 and 2010 from participants aged 45-79 years. Candidate prodromal symptoms were Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) subscale scores and individual items, available up to 4 years prior to the time of incident ROA. Multi-level models were used to estimate the length of the prodromal phases.

Results

The prodromal phase for subscale scores ranged from 29 months (KOOS Other Symptoms) to 37 months (WOMAC Pain). Pain and difficulty on activities associated with higher dynamic knee loading were associated with longer prodromal phases (e.g., pain on twisting/pivoting (39 months, 95% confidence interval: 13, 64) vs pain on standing (25 months: 7, 42)).

Conclusions

Our analysis found that incident ROA is preceded by prodromal symptoms lasting at least 2-3 years. This has potential implications for understanding phasic development and progression of osteoarthritis and for early recognition and management.

SUBMITTER: Case R

PROVIDER: S-EPMC4491193 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

Prodromal symptoms in knee osteoarthritis: a nested case-control study using data from the Osteoarthritis Initiative.

Case R R Thomas E E Clarke E E Peat G G

Osteoarthritis and cartilage 20150403 7

<h4>Objective</h4>In order to gain a better understanding of the timing of emergent symptoms of osteoarthritis, we sought to investigate the existence, duration and nature of a prodromal symptomatic phase preceding incident radiographic knee osteoarthritis (ROA).<h4>Design</h4>Data were from the incidence cohort of the Osteoarthritis Initiative (OAI) public use datasets. Imposing a nested case-control design, ten control knees were selected for each case of incident tibiofemoral ROA between 2004 ...[more]

PMID: 25843364

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Project description:ObjectiveOsteoarthritis (OA) is a disease with a substantial public health burden. Quantitative assessments of periarticular bone may be a biomarker capable of monitoring early disease progression. The purpose of this study was to evaluate whether measures of periarticular bone associate with longitudinal structural progression.MethodsWe conducted a 12-18 months longitudinal study using the Osteoarthritis Initiative (OAI). Participants received knee dual-energy x-ray absorptiometry (DXA), trabecular magnetic resonance (MR) imaging, and x-rays. Knee DXAs generated proximal tibial medial:lateral periarticular bone mineral density (paBMD) measures. Proximal tibial trabecular MR images were assessed for trabecular morphometry: apparent bone volume fraction (BVF), trabecular number, thickness, and spacing. Weight-bearing x-rays were assessed for medial tibiofemoral joint space narrowing (JSN). Chi-squared analyses assessed whether periarticular bone measures were predictive of worsening medial tibiofemoral JSN, adjusted for age, sex, and BMI.ResultsIn all, 444 participants, mean age 64.2 ± 9.2 years, BMI 29.5 ± 4.6kg/m2, and 52% male at baseline. Medial JSN (radiographic progression) occurred in 40 participants (9%). Higher baseline medial:lateral paBMD, apparent BVF, trabecular number and thickness, and lower baseline and decreased trabecular spacing were all associated with more progression of JSN in the medial compartment. From lowest to highest baseline medial:lateral paBMD quartile groups, 2%, 5%, 11%, and 18% had medial JSN progression, respectively, between the 36- and 48-month visits, p-values = 0.001 and 0.002 unadjusted and adjusted. The rate of change in medial:lateral paBMD, apparent BVF, and spacing were associated with more medial JSN. For rate of medial:lateral paBMD change from lowest to highest quartile, the proportion of each group that experienced medial JSN progression were 5%, 5%, 11%, and 18%, with an unadjusted and adjusted p-value of 0.005.ConclusionBaseline and most rates of periarticular bone change associate with knee OA structural progression, highlighting the close relationship between subchondral bone and JSN. Future studies should focus on developing these measures as predictive and pathophysiological biomarkers, and evaluating their deployment in clinical trials testing bone-targeted therapeutics.

Project description:Background Longitudinal data on the association of quantitative thigh muscle MRI markers with knee osteoarthritis (KOA) outcomes are scarce. These associations are of clinical importance, with potential use for thigh muscle-directed disease-modifying interventions. Purpose To measure KOA-associated longitudinal changes in MRI-derived muscle cross-sectional area (CSA) and adipose tissue and their association with downstream symptom worsening and knee replacement (KR). Materials and Methods In a secondary analysis of the Osteoarthritis Initiative multicenter prospective cohort (February 2004 through October 2015), knees of participants with available good-quality thigh MRI scans at baseline and at least one follow-up visit were included and classified as with and without KOA according to baseline radiographic Kellgren-Lawrence grade of 2 or higher and matched for confounders with use of propensity score matching. An automated deep learning model for thigh MRI two-dimensional segmentation was developed and tested. Markers of muscle CSA and intramuscular adipose tissue (intra-MAT) were measured at baseline and 2nd- and 4th-year follow-up (period 1) and compared between knees with and without KOA by using linear mixed-effect regression models. Furthermore, in knees with KOA, the association of period 1 changes in muscle markers with risk of KR (Cox proportional hazards) and symptom worsening (mixed-effect models) during the 4th to 9th year (period 2) was evaluated. Results This study included 4634 matched thighs (2317 with and 2317 without KOA) of 2344 participants (mean age, 62 years ± 9 [SD]; 1292 women). Compared with those without, knees with KOA had a decrease in quadriceps CSA (mean difference, -8.21 mm2/year; P = .004) and an increase in quadriceps intra-MAT (1.98 mm2/year; P = .007). Decreased CSA and increased intra-MAT of quadriceps during period 1 was predictive of downstream (period 2) KOA symptom worsening (Western Ontario and McMaster Universities Osteoarthritis Index total score: odds ratio, 0.24 [negative association] [P < .001] and 1.38 [P = .012], respectively). Quadriceps CSA changes were negatively associated with higher future KR risk (hazard ratio, 0.70; P < .001). Conclusion Knee osteoarthritis was associated with longitudinal MRI-derived decreased quadriceps cross-sectional area and increased intramuscular adipose tissue. These potentially modifiable risk factors were predictive of downstream symptom worsening and knee replacement. Clinical trial registration no. NCT00080171 © RSNA, 2022 Online supplemental material is available for this article.

Project description:Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome predictions. Purpose To develop a deep learning (DL) prediction model for risk of OA progression by using knee radiographs in patients who underwent total knee replacement (TKR) and matched control patients who did not undergo TKR. Materials and Methods In this retrospective analysis that used data from the OA Initiative, a DL model on knee radiographs was developed to predict both the likelihood of a patient undergoing TKR within 9 years and Kellgren-Lawrence (KL) grade. Study participants included a case-control matched subcohort between 45 and 79 years. Patients were matched to control patients according to age, sex, ethnicity, and body mass index. The proposed model used a transfer learning approach based on the ResNet34 architecture with sevenfold nested cross-validation. Receiver operating characteristic curve analysis and conditional logistic regression assessed model performance for predicting probability and risk of TKR compared with clinical observations and two binary outcome prediction models on the basis of radiographic readings: KL grade and OA Research Society International (OARSI) grade. Results Evaluated were 728 participants including 324 patients (mean age, 64 years ± 8 [standard deviation]; 222 women) and 324 control patients (mean age, 64 years ± 8; 222 women). The prediction model based on DL achieved an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI]: 0.85, 0.90), outperforming a baseline prediction model by using KL grade with an AUC of 0.74 (95% CI: 0.71, 0.77; P < .001). The risk for TKR increased with probability that a person will undergo TKR from the DL model (odds ratio [OR], 7.7; 95% CI: 2.3, 25; P < .001), KL grade (OR, 1.92; 95% CI: 1.17, 3.13; P = .009), and OARSI grade (OR, 1.20; 95% CI: 0.41, 3.50; P = .73). Conclusion The proposed deep learning model better predicted risk of total knee replacement in osteoarthritis than did binary outcome models by using standard grading systems. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Richardson in this issue.

Project description:ObjectivesThe aim of this study was to investigate changes over time in osteoarthritis risk factors most closely associated with the occurrence of total knee arthroplasty (TKA). We hypothesize that the robustness of a longitudinal case-control study will provide new information on the association between changes in various clinical and structural parameters in different time frames before TKA.MethodsCases (195; TKA after cohort entry) and controls (468) matched for age, gender, income, WOMAC pain, Kellgren-Lawrence grade and follow-up duration were from the Osteoarthritis Initiative cohort. Associations between changes in sociodemographic, clinical, imaging and osteoarthritis therapies with the occurrence of TKA were performed using conditional logistic regression analyses.ResultsWorsening of WOMAC scores (cOR 1.02-1.20, p ⩽ 0.012), KOOS (1.02-1.04, p ⩽ 0.014), knee injuries sustained in the previous 30-40 years (women 2.70, p = 0.034) and valgus alignment (1.10, p = 0.052) were associated with the occurrence of TKA. Also associated with TKA was cartilage volume loss in the lateral (overall 1.76, p = 0.025; women 1.93, p = 0.047) and medial compartments (⩾10%, overall 1.54, p = 0.027; men 2.34, p = 0.008), occurrence of medial meniscal extrusion (overall 1.77, p = 0.046; men 2.86, p = 0.028), and increase in bone marrow lesions (BMLs) for women (1.09, p = 0.048). The association of risk factors with TKA was reinforced when both an increase in WOMAC pain and cartilage volume loss (1.85, p = 0.001) were combined. Pain medication usage, mainly narcotics and intra-articular steroid injections (IASI), was also associated with TKA, with no impact on changes in cartilage loss or structure.ConclusionThis study provides new information about gender differences in risk factors associated with the occurrence of TKA. Worsening of valgus alignment, cartilage volume loss in the lateral compartment, BMLs and older injuries are important risk factors in women, while medial compartment cartilage loss and meniscal extrusion are in men. The use of pain medication and IASI although associated was found not causal with TKA.

Dataset Information

Prodromal symptoms in knee osteoarthritis: a nested case-control study using data from the Osteoarthritis Initiative.

Objective

Design

Results

Conclusions

Publications

Prodromal symptoms in knee osteoarthritis: a nested case-control study using data from the Osteoarthritis Initiative.

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