Abstract
Objectives
There is no consensus on how musculoskeletal ultrasound (US), especially power Doppler (PD) positivity, should inform treatment decisions in RA. We aimed to summarize the literature on whether PD positivity can predict response to intensification of RA therapies in patients with moderate to high clinical disease activity.
Methods
A systematic literature review was performed using a predefined PICO strategy. The titles and abstracts, and subsequently full texts, were independently screened and reviewed by two reviewers and any disagreement was resolved by a third investigator. Studies that investigated the predictive value of PD were included.
Results
Among 2580 abstracts/titles, 13 studies were included. Studies were heterogeneous regarding the inclusion criteria, baseline and new treatments, scanned joints and follow-up duration. In eight studies, patients with higher baseline PD activity had a better response to treatment, mostly with higher reductions in clinical indices. In contrast, two studies found that the probability of achieving clinical remission decreased as the baseline PD score increased. There was no association between baseline PD and the achievement of clinical remission at the follow-up in the remaining three studies.
Conclusion
The baseline Doppler severity may suggest better improvement with higher reductions in composite scores, but this may not be enough to predict a remission state. How US can be used to predict response in RA management requires a well-designed study that will need to be shaped by the existing observations, most importantly identifying the outcome measure that will also be important for daily practice.
Keywords: rheumatoid arthritis, ultrasound, power Doppler, treatment, remission
Key messages.
Controversies exist regarding the value of ultrasound in predicting response to RA treatment.
Higher baseline Doppler severity may predict a higher reduction in clinical indices with treatment.
Introduction
Clinical outcomes for RA have drastically improved in the last several decades due to new therapeutic agents and treatment strategies. The current treatment paradigm utilizes composite clinical indices such as the DAS or Clinical Disease Activity Index (CDAI) to monitor clinical activity and guide therapeutic decisions, ultimately targeting a state of clinical remission [1, 2]. However, these clinical indices can be affected by a multitude of factors other than RA disease activity, including pain, fatigue and physical disability from concomitant non-inflammatory pathologies such as fibromyalgia or osteoarthritis [3]. A reliance on these indices in clinical practice can result in overtreatment and exposure to undue medication side effects in the absence of objective signs of inflammation.
Musculoskeletal ultrasound (US) is a technology that has been shown to improve the accuracy of physical examination [4, 5]. US is often employed at the bedside to identify objective inflammation and is particularly helpful when patient symptoms do not correlate with findings on physical examination [6]. Two randomized controlled trials (RCTs) that focused on treating subclinical disease failed to demonstrate improved outcomes with US-driven treat-to-target approaches [7, 8]. However, there are no RCTs on the role of US in informing treatment decisions for RA therapy escalation when there is a discrepancy between the patient and the physician, with the patient scoring higher, although this applies to one of the most common uses of musculoskeletal US in clinical practice [9]. The objective of our study was to summarize the existing literature to determine whether power Doppler US (PDUS) activity can predict response to the intensification of RA therapies in patients with moderate to high clinical disease activity.
Methods
Search and selection strategy
A systematic literature review was performed using a predefined PICO (population, intervention, comparator and outcome) strategy on the MEDLINE, Embase and Cochrane Central Register databases by an experienced librarian at the University of Ottawa. Details of the search strategy are provided in Supplementary Table S1, available at Rheumatology Advances in Practice online. Since this is a systematic literature review that does not involve human subjects, ethics approval was not required. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO: CRD42021258344). The literature search was performed from January 2000 to November 2023. To be eligible for inclusion, studies had to meet the following criteria: RCTs, observational studies including case–control studies, cohort studies, nested case–control studies and cross-sectional studies with assessment of the prediction of PD for treatment response. Our search identified 2580 abstracts. We excluded articles with incomplete data, reporting bias, duplication, case reports, review articles, consensus reports and languages other than English. An overview of our literature search and screening results are outlined in Supplementary Fig. S1 and Supplementary Table S1, available at Rheumatology Advances in Practice online.
Data extraction
The titles and abstracts were independently screened by two of three reviewers (U.G.G., A.Z., N.K.). All abstracts with a discrepancy were carried to a full-text review. The full texts were reviewed independently by the same investigators. A third investigator (S.Z.A.) resolved any disagreement at this stage. In addition, the references of all included articles were manually scanned. Articles that did not fulfil the inclusion criteria were identified and the reason for exclusion was documented. The following data were extracted: publication year, study design, sample size, sex distribution, baseline and new treatment, change in disease activity parameter and results for the prediction.
Quality assessment
The National Heart, Lung, and Blood Institute of the National Institutes of Health tool for quality assessment of observational cohort and cross-sectional studies was used to assess the quality of all included studies [10]. The studies were divided into three groups: fair, poor and good.
Results
We identified 2580 abstracts and titles. After the duplicates were removed, 2515 were screened. Among 149 studies eligible for full-text review, 136 studies were excluded. Reasons for exclusion during the full-text review were eight studies for being only study protocols, 2 in the wrong language, 46 poster presentations, 2 wrong study designs, 1 included <10 patients and 77 for wrong study outcomes (details provided in Supplementary Fig. S1 and Supplementary Table S2, available at Rheumatology Advances in Practice online). After the full-text review, 13 studies were found to be eligible for inclusion.
Study designs and patient profiles
All the studies’ designs were prospective observational, except Kawashiri et al.’s study, which was a retrospective data collection [11]. The sample size of the studies varied from 10 to 141. The mean age ranged from 46 to 59 years and sex dominance was female in all. At recruitment, the patients were treatment naïve in one study [12], biologic DMARD (bDMARD) naïve in five studies [13–17] and on bDMARDs or conventional synthetic DMARDs in five studies [11, 18–21]. Baseline treatment was not reported in three studies [22, 23]. In seven studies, patients had to have active disease at baseline according to the 28-joint DAS (DAS28) with CRP, ESR or CDAI in various cut-offs before the new therapy [12, 14, 16, 18–20, 23]. Also, in Razmjou et al.’s study [18], having a total PDUS ≥10, and in Ranganath et al.’s study [16], having a PDUS >1 in at least one joint was one of the inclusion criterion. In four studies, a new treatment was either biologic or conventional DMARDs [12, 13, 20, 23], while in the rest of the studies, only patients who started a biologic treatment were included. The duration of follow-up ranged from 3 to 12 months.
US scanning and scoring
There was heterogeneity in terms of the joints that were assessed by the US. Two studies included only the wrist joint from the dorsal view and one included only the MCP joints [14, 17, 22]. The other studies assessed multiple joints by US. Most of the studies used a semiquantitative PD score of 0–3 per joint, resulting in an overall PD score per patient. Overall PD scores changed based on the number of joints scanned by US, with the upper limit ranging from 39 to 102. Three of thirteen studies used a cut-off for the PD score for the analysis [12, 16, 17]. Table 1 and Supplementary Table S3, available at Rheumatology Advances in Practice online, display detailed information regarding the study characteristics.
Table 1.
Study characteristics.
| Author | Sample sizec, n | Age, years, mean (s.d.) | Sex(male/female), n/n | Baseline treatment at study entry |
New treatment | Follow-up duration | Joints assessed with US, n | US Doppler parameter | PD score range | PD cut-off used for analysis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| csDMARD | bDMARD | ||||||||||
| Gazel et al., 2023 [20]f | 20 | 57 (16.9) | 9/10 | NR | NR | Any treatment modification | 3–6 months | 36 | Semiquantitative PD scoring of 0–3 | 0–3 | >1 PD positivity |
| Ceccarelli et al., 2022 [21]f | 102 | 59.2 (17.7) | 15/87 | 51 (50%) | NR | Baricitinib or tofacitinib | Median 6 months (IQR 3) | 22 | Semiquantitative PD scoring of 0–3 | 0–66 | NA |
| Morris et al., 2021 [19]f | 44 | 51.9 (15.2) | 5/49 | 100% | 0% | Tocilizumab 4 mg/kg every 4 weeks | 24 weeks | 34 | Semiquantitative PD scoring of 0–3 | 0–3 | NA |
| Razmjou et al., 2020 [18]f | 24 | 52 (9.9) | 3/22 | 72% | 32% | Tofacitinib | 12 weeks | 34 | Semiquantitative PD scoring of 0–3 | 0–102 | NA |
| Sapundzhieva et al., 2018 [23]f | 141 | 58.90 (11.04) | 30/111 | NR | NR | sDMARDs 55% or bDMARDs 45% | 12 months | 7 | Semiquantitative PD scoring of 0–3 (joints and tendons, per US-7 score)h,b | 0–39 | NA |
| Kawashiri et al., 2017 [11]f | 39 | 47.1 (12.4) | 8/31 | 84% | 30.8% | bDMARDs | 6 months | 22 | Semiquantitative PD scoring of 0–3 | 0–66 | NA |
| Christensen et al., 2016 [13]d | 98 |
|
22/76 | csDMARD initiation group 76%, bDMARD initiation group 51% | csDMARD initiation group 0%, bDMARD initiation group 0% | csDMARD 48%, bDMARD 52% | 4 months | 24 projections in 11 jointsa | Semiquantitative PD scoring of 0–3g | 0–72 | NA |
| Horton et al., 2016 [12]d | 105 | 59 (13) | 26/79 | 0% | 0% | csDMARD 91%, bDMARD 5%, steroids 4% | 12 months | 26 | Semiquantitative PD scoring of 0–3 | 0–78 |
|
| Hull et al., 2016 [14]e | 25 | 59 (13) | 7/18 | 100% (treated with at least two DMARDs) | 0% | Anti-TNF-α treatment | 12 weeks | 10 (MCP joints only) | Synovial vascularity score (trans-PDA)a | NR | NA |
| Inanc et al., 2016 [15]e | 39 |
|
9/30 | NR | 0% | Anti-TNF-α treatment | 3 months | 28 | Semiquantitative PD scoring of 0–3 | 0–84 | NA |
| Ranganath et al., 2015 [16]e | 19 | NR | NR | NR | 0% | Abatacept | 12 months | 7 | Semiquantitative PD scoring of 0–3 | NR | PDUS ≥ 5 and PDUS ≤5 (prediction analysis is not based on this) |
| Ellegaard et al., 2014 [22]e | 46 | 57.9 (13.9) | 9/37 | NR | NR | Anti-TNF-α treatment | 12 months | 1 (dorsal wrist only) | Semiquantitative PD scoring of 0–3 and quantitative colour fraction | PDUS 0–3, CF 0–1 | NA |
| Ellegaard et al., 2011 [17]e | 109 | 57.9 (13.9) | 31/78 | MTX 49.5%;SSZ 10.1% | 0% | Anti-TNF-α treatment | 12 months | 1 (wrist only) | Colour fraction (CF) and √CFb | NR | √CF > 0.23 |
The power Doppler area (PDA) is a count of the number of pixels with PDUS signal within the defined region of interest. Synovial vascularity score (trans-PDA) is the sum of all joints.
The CF is the number of colour pixels divided by the total number of pixels in a region of interest.
Final sample size that is included in the analysis is displayed.
1987 ACR and/or 2010 ACR/EULAR criteria.
1987 ACR criteria.
2010 ACR/EULAR criteria.
MCP 2–4 (dorsal projections); wrist central, radial and ulnar projections; m. extensor carpi ulnaris tendon; elbow (posterior projection); knee suprapatellar, lateral and medial projections; ankle central, medial and lateral projections; tarsometatarsal central, medial and lateral projections; MTP 24; m. tibialis posterior tendon; and m. peroneus longus et brevis tendons.
Seven joints of the clinically dominant hand/foot, affected more by swelling or tenderness, using the German US-7 score wrist, second and third MCP and PIP, second and fifth MTP joints, Palmar scan was used to assess MCP2 and MCP3 for synovitis and tenosynovitis and dorsal scan for paratenonitis.
Definition of response, primary outcomes and analysis
Two different outcome measures were used to define improvement of disease activity: six studies used improvement in the DAS28 and/or CDAI scores [13, 16, 18, 19, 21, 22] and one used the change in tender joint count (TJC) and swollen joint count (SJC) [20]. Six studies used achieving remission after treatment [11, 12, 14, 15, 17, 23]. The mean/median disease activity results for the baseline and follow-up, as well as the difference, are given in Table 2. Different analyses were used in the studies, including correlation, regression and effect size.
Table 2.
Outcome results of the studies.
| Author | Analysis | Outcome | Results | Conclusion |
|---|---|---|---|---|
| Studies that found better response to treatment with higher PD score at baseline | ||||
| Gazel et al., 2022 [20] | Percentage of change in clinical activity indices | Mean change in TJC and SJCa,c |
|
Simple definition of the presence of moderate PD positivity in one joint may predict favourable clinical responses to treatment alterations |
| Ceccarelli et al., 2022 [21] | Significance of change in disease activity indices over time; multivariate regression analysis | Change in DAS28-CRP in weeks 12, 24 and 48 |
|
PD and tenosynovitis scores could play a predictive role in response to treatment with JAK inhibitors in RA patients |
| Morris et al., 2021 [19] | Correlation analysis of baseline PD score with DAS28‐ESR and CDAI | Change in disease activity measures (CDAI and DAS28-ESR) | Baseline PDUS scores and 12-week change is significantly correlated with changes in CDAI from 12 to 24 weeks (r = 0.42, P < 0.01) | Baseline US34-PDUS and its early changes after initiating biologic therapy may be a useful predictor for IV-TCZ response in RA patients |
| Razmjou et al., 2020 [18] | Pearson correlations for associations between baseline US and changes in CDAI or DAS28; multiple linear regression models for the outcomes of change in clinical indices | Change in CDAI and DAS28 scores |
|
Higher baseline PDUS values are associated with larger CDAI and DAS28 responses at 6 weeks, with a trend observed at 12 weeks |
| Christensen et al., 2016 [13] | Multiple regression analysis | Change in DAS28 score |
|
|
| Hull et al., 2016 [14] | Wilcoxon matched pairs test to compare baseline trans-PDA score with follow-up | Number of patients who achieved improvement in the DAS28 score >1.2 from baseline to 12 weeks | Baseline Doppler score is numerically higher in responders than non-responders: 3213 (115–6772)b vs 25 (0–1079)b | The quantitative measures of synovial thickening and synovial vascularity were both able to discriminate between EULAR good responders and non-responders to anti-TNF treatment |
| Ranganath et al., 2015 [16] | Correlation between the baseline PDUS and change in DAS28; multivariate linear regression analysis | Change in DAS28-ESR score |
|
Patients with high baseline PDUS had a more robust response to therapy |
| Ellegaard et al., 2011 [17] | Effect size | Percent of completers vs drop-outs (due to lack of efficacy) |
|
Higher US Doppler measurement using CF obtained at baseline was the only outcome measure that could significantly predict which patients would remain on anti-TNF therapy |
| Studies that found less response to treatment with higher PD score at baseline | ||||
| Sapundzhieva et al., 2018 [23] | Binary logistic regression, Spearman rho correlation analysis | Number of patients in DAS28 remission |
|
The probability of achieving DAS28 remission decreases as baseline PDUS score increases for both the csDMARD and bDMARD therapies |
| Inanc et al., 2016 [15] | Stepwise-multivariable logistic regression | Number of patients in EULAR response (good/moderate) |
|
|
| Studies that found no association between response to treatment and with PD score at baseline | ||||
| Kawashiri et al., 2017 [11] | Mann–Whitney U test and Wilcoxon’s signed rank test | Number of patients in clinical remission according to EULAR good response and DAS28-ESR remission | EULAR moderate and good responders PD score = 8 vs non-responders PD score = 7, P = 0.74; EULAR good responders PD score = 10 vs non-responders PD score = 7, P = 0.45; DAS28-ESR remission PD score = 9 vs non-remission PD score = 7, P = 0.33 | There were no differences for baseline PD score according to clinical remission at 6 months |
| Horton et al., 2016 [12] | Univariate and multivariate multiple regression analysis | Number of patients in remission according to DAS28-CRP4v remission | Univariable analysis: baseline total PDA score for DAS28-CRP4v 0.98 (95% CI 0.92, 1.05), P = NS; for DAS44-CRP4v 0.97 (95% CI 0.91, 1.04), P = NS; for Boolean 0.98 (95% CI 0.89, 1.07) | Baseline PDA did not predict DAS28-CRP4v remission in new-onset RA patients |
| Ellegaard et al., 2014 [22] | Spearman’s rank order correlation analysis | Change in DAS28 score | NR | The discriminative ability (ability to predict treatment success measured as decrease in DAS28) was poor for both PD scoring systems (data not shown) |
Mean (s.d.).
Median (IQR).
Mean (95% CI).
Prediction with the baseline PD
In eight studies, authors found that patients who had higher baseline PD activity had a better response to treatment. Among these, five studies found that patients who had higher PD scores at baseline had greater reductions in clinical indices compared with patients with lower PD scores [13, 16, 18–21]. Similarly, Hull et al. [14] found that synovial vascularity was higher in patients who were good EULAR responders at follow-up. Also, in Ellegaard et al.’s study [17], patients with higher PDUS scores at baseline remained on anti-TNF therapy longer. In contrast with these findings, two studies found that the probability of achieving clinical remission decreases as the baseline PDUS score increases [15, 23]. In the other three studies, there was no association between baseline PDUS and the achievement of clinical remission at the follow-up after treatment escalation for the disease activity. Table 2 and Supplementary Table S3, available at Rheumatology Advances in Practice online, provide details regarding the study results.
Quality assessment
In 10 studies included in our review, 7 were rated as ‘good’, 4 articles as ‘fair’ and 2 articles as ‘poor’ (Supplementary Table S4, available at Rheumatology Advances in Practice online).
Discussion
The utility of US to modify clinicians’ treatment choices in real life has been demonstrated, but the way it has been utilized has yet to be proven effective [24]. Previous observational studies showed that the presence of PD-positive synovitis might be more helpful than clinical examination in predicting flares in patients who are in clinical remission, suggesting that sonography can help clinicians decide how to manage patients in remission [25–27]. Also, there is evidence that PD positivity may predict radiographic damage progression in RA patients [28, 29]. However, despite the superiority of US over clinical assessment to detect inflammation, how to incorporate that information into daily practice is unclear. In this study, our results showed that there is a controversy regarding studies evaluating the role of baseline PD positivity for treatment response in RA patients. The majority (8/13) of the studies showed that patients with higher baseline PD activity had a better response to treatment, while two studies found the opposite and the other three found no association. Although these controversial findings can suggest an unclear association between baseline Doppler findings and the response, we observed major differences in the studies’ designs, which can also explain the different results achieved. Some differences included the inclusion criterion, treatments and the number of scanned joints, which may all contribute. However, we believe the biggest difference is the primary outcome that was used in these studies. In eight studies that found PD to have a predictive value for better response, six of them identified the outcome as the change in DAS scores [13, 14, 16, 18, 19, 21]. In contrast, within the other five studies that found the opposite or were found to be neutral, in four of them, the outcome was chosen as a disease state or included the disease state in the definition of response (EULAR good or moderate response) [11, 12, 15, 23]. These differences indicate that the baseline Doppler severity may suggest a greater reduction in composite scores, but this may not be enough to predict a remission state.
Based on previous research regarding clinical disease activity scores, patients with high disease activity at baseline appear to have a greater potential for favourable therapeutic responses [30]. This finding is consistent with US assessments; however, a key distinction emerges in that patients with similar clinical disease activity scores may exhibit differing levels of US-detected synovitis. Therefore, US may play a critical role in further stratifying disease activity and guiding management in this regard.
Our findings are limited by the heterogeneity of the studies analysed, preventing us from drawing robust conclusions. Nevertheless, we believe it is essential to highlight this issue as a critical area for future investigation, supported by evidence from the current literature. Our research group is presently conducting an RCT to evaluate the feasibility of a study design aimed at determining whether the integration of US influences treatment outcomes in newly diagnosed RA patients with high disease activity. Additionally, as part of our research agenda, we plan to investigate other objective features in RA, such as functional MRI, to gain a deeper understanding of pain mechanisms. Given that pain may arise from multiple sources, it can confound clinical disease activity assessments, underscoring the need for more precise evaluation tools [31].
In conclusion, the role of baseline Doppler activity in predicting remission in RA is still controversial. The heterogeneity between studies is likely to affect the results of the existing literature and make it challenging to draw conclusions. How US can be used to predict response in RA management requires well-designed studies that will need to be shaped on the existing observations, such as determining the right study outcome (response vs disease state). The wide range of patient profiles, based on disease durations, disease activities and/or baseline and new therapies, may require more than one study design to understand the predictive value of Doppler positivity in different scenarios. With the cumulative data of studies exploring this question, we will be able to understand the best way to incorporate US in the management algorithms in RA.
Supplementary Material
Contributor Information
Ummugulsum Gazel, Faculty of Medicine, Rheumatology, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
Alan Zhou, Faculty of Medicine, Internal Medicine, University of Ottawa, Ottawa, ON, Canada.
Nicholas Jinhyung Kim, Faculty of Medicine, Internal Medicine, University of Ottawa, Ottawa, ON, Canada.
Gizem Ayan, Faculty of Medicine, Rheumatology, Hacettepe University, Ankara, Turkey.
Dilek Solmaz, Rheumatology, Izmir Katip Celebi Research and Education Hospital, Izmir, Turkey.
Servet Akar, Rheumatology, Izmir Katip Celebi Research and Education Hospital, Izmir, Turkey.
Sibel Zehra Aydin, Faculty of Medicine, Rheumatology, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
Supplementary material
Supplementary material is available at Rheumatology Advances in Practice online.
Data availability
The data underlying this article will be shared upon reasonable request to the corresponding author.
Authors’ contributions
U.G. contributed to data collection, data analysis, and drafting of the manuscript. A.Z. and N.J.K. assisted with data collection. G.A., D.S., and S.A. were involved in the study design. S.Z.A. contributed to the study’s conception and design, data analysis, and critical revision of the manuscript. All authors read and approved the final manuscript.
Funding
No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article.
Disclosure statement: S.Z.A. has received honoraria from AbbVie, Celgene, UCB, Novartis, Jannsen, Pfizer and Sanofi. The other authors have declared no conflicts of interest.
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Associated Data
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The data underlying this article will be shared upon reasonable request to the corresponding author.