Methods: All patients with a physician-verified diagnosis of axSpA attending two specialist centres who fulfilled the eligibility criteria for TNFi were included. Routinely recorded patient data were reviewed retrospectively. Initial TNFi was recorded as the index drug.
Results: Six hundred and fifty-one patients (94% AS) were included; adalimumab (n = 332), etanercept (n = 205), infliximab (n = 51), golimumab (n = 40) and certolizumab pegol (n = 23) were index TNFi. The mean (s.d.) duration from symptom onset to time of diagnosis was 8.6 (8.7) years and mean (s.d.) duration from diagnosis to TNFi initiation was 12.6 (11.5) years. A total of 224 (34.4%) stopped index TNFi, and 105/224 switched to a second TNFi. Median drug survival for index and second TNFi were 10.2 years (95% CI: 8.8, 11.6 years) and 5.5 years (95% CI: 2.7, 8.3 years), respectively (P < 0.05). Survival rates were not influenced by choice of TNFi. HLA-B27 predicted BASDAI50 and/or two or more point reduction within 6 months and long-term drug survival (P < 0.05). Low disease activity was predicted by non-smoking and low baseline BASDAI (P < 0.05).
Conclusion: We have observed good TNFi survival rates in axSpA patients treated in a real-life setting. This is best for first TNFi and not influenced by drug choice.
METHODS: Circulating CD8+ T cells were analysed for differentiation status (CD45RO, CCR7), markers of activation (CD69 and CD25) and proliferation (Ki-67) in 14 newly diagnosed GCA patients and 18 healthy controls by flow cytometry. Proliferative capacity of CD8+ T cells upon anti-CD3 and anti-CD3/28 in vitro stimulation was assessed. Single-cell RNA sequencing of peripheral blood mononuclear cells of patients and controls (n = 3 each) was performed for mechanistic insight. Immunohistochemistry was used to detect CD3, CD8, Ki-67, TNF-α and IFN-γ in GCA-affected tissues.
RESULTS: GCA patients had decreased numbers of circulating effector memory CD8+ T cells but the percentage of Ki-67-expressing effector memory CD8+ T cells was increased. Circulating CD8+ T cells from GCA patients demonstrated reduced T cell receptor activation thresholds and displayed a gene expression profile that is concurrent with increased proliferation. CD8+ T cells were detected in GCA temporal arteries and aorta. These vascular CD8+ T cells expressed IFN-γ but not Ki-67.
CONCLUSION: In GCA, circulating effector memory CD8+ T cells demonstrate a proliferation-prone phenotype. The presence of CD8+ T cells in inflamed arteries seems to reflect recruitment of circulating cells rather than local expansion. CD8+ T cells in inflamed tissues produce IFN-γ, which is an important mediator of local inflammatory responses in GCA.
METHODS: The first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups.
RESULTS: We analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, P
METHODS: A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vaccination in 2022. BIs were defined as COVID-19 occurring ≥14 days after 2 vaccine doses. We compared BIs characteristics and severity among IIMs, other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HC). Multivariable Cox regression models assessed the risk factors for BI, severe BI and hospitalisations among IIMs.
RESULTS: Among 9449 included response, BIs occurred in 1447 (15.3%) respondents, median age 44 years (IQR 21), 77.4% female, and 182 BIs (12.9%) occurred among 1406 IIMs. Multivariable Cox regression among IIMs showed age as a protective factor for BIs [Hazard Ratio (HR)=0.98, 95%CI = 0.97-0.99], hydroxychloroquine and sulfasalazine use were risk factors (HR = 1.81, 95%CI = 1.24-2.64, and HR = 3.79, 95%CI = 1.69-8.42, respectively). Glucocorticoid use was a risk factor for severe BI (HR = 3.61, 95%CI = 1.09-11.8). Non-White ethnicity (HR = 2.61, 95%CI = 1.03-6.59) was a risk factor for hospitalisation. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIM = 6.0% vs AIRD = 1.8%, nrAID = 2.2%, and HC = 0.9%), intensive care unit admission (IIM = 2.2% vs AIRD = 0.6%, nrAID, and HC = 0%), advanced treatment with antiviral or monoclonal antibodies (IIM = 34.1% vs AIRD = 25.8%, nrAID = 14.6%, and HC = 12.8%), and had more hospitalisation (IIM = 7.7% vs AIRD = 4.6%, nrAID = 1.1%, and HC = 1.5%).
CONCLUSION: Patients with IIMs are susceptible to severe COVID-19 BI. Age and immunosuppressive treatments were related to the risk of BIs.
METHODS: The COVAD surveys were used to extract data on flare demographics, comorbidities, COVID-19 history, and vaccination details for patients with AIRDs. Flares following vaccination were identified as patient-reported (a), increased immunosuppression (b), clinical exacerbations (c) and worsening of PROMIS scores (d). We studied flare characteristics and used regression models to differentiate flares among various AIRDs.
RESULTS: Of 15 165 total responses, the incidence of flares in 3453 patients with AIRDs was 11.3%, 14.8%, 9.5% and 26.7% by definitions a-d, respectively. There was moderate agreement between patient-reported and immunosuppression-defined flares (K = 0.403, P = 0.022). Arthritis (61.6%) and fatigue (58.8%) were the most commonly reported symptoms. Self-reported flares were associated with higher comorbidities (P = 0.013), mental health disorders (MHDs) (P
METHODS: Data from the Asia Pacific Lupus Collaboration cohort, in which disease activity and medications were prospectively captured from 2013 to 2018, were used. Predictors of lymphopenia (lymphocyte count <0.8 × 109/l) and neutropenia (neutrophil count <1.5 × 109/l) were examined using multiple failure, time-dependent survival analyses.
RESULTS: Data from 2330 patients and 18 287 visits were analysed. One thousand and eighteen patients (43.7%) had at least one episode of leucopenia; 867 patients (37.2%) had lymphopenia, observed in 3065 (16.8%) visits, and 292 (12.5%) patients had neutropenia, in 622 (3.4%) visits. After multivariable analyses, lymphopenia was associated with overall disease activity, ESR, serology, prednisolone, AZA, MTX, tacrolimus, CYC and rituximab use. MTX and ciclosporin were negatively associated with neutropenia. Lupus low disease activity state was negatively associated with both lymphopenia and neutropenia.
CONCLUSION: Both lymphopenia and neutropenia were common in SLE patients but were differentially associated with disease and treatment variables. Lymphopenia and neutropenia should be considered independently in studies in SLE.
METHODS: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models.
RESULTS: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P
METHODS: Data were analysed from patients in a multinational longitudinal cohort with known anti-dsDNA results from 2013 to 2021. Patients were categorized based on their anti-dsDNA results as persistently negative, fluctuating or persistently positive. Cox regression models were used to examine longitudinal associations of anti-dsDNA results with flare.
RESULTS: Data from 37 582 visits of 3484 patients were analysed. Of the patients 1029 (29.5%) had persistently positive anti-dsDNA and 1195 (34.3%) had fluctuating results. Anti-dsDNA expressed as a ratio to the normal cut-off was associated with the risk of subsequent flare, including in the persistently positive cohort (adjusted hazard ratio [HR] 1.56; 95% CI: 1.30, 1.87; P 3. Both increases and decreases in anti-dsDNA more than 2-fold compared with the previous visit were associated with increased risk of flare in the fluctuating cohort (adjusted HR 1.33; 95% CI: 1.08, 1.65; P = 0.008) and the persistently positive cohort (adjusted HR 1.36; 95% CI: 1.08, 1.71; P = 0.009).
CONCLUSION: Absolute value and change in anti-dsDNA titres predict flares, including in persistently anti-dsDNA positive patients. This indicates that repeat monitoring of dsDNA has value in routine testing.
METHODS: Delayed-onset (>7 days) vaccine-related adverse events (AE), disease flares and AID-related treatment modifications were analysed upon diagnosis of AID vs healthy controls (HC) and the pregnancy/breastfeeding status at the time of at least one dose of vaccine.
RESULTS: Among the 9201 participants to the self-administered online survey, 6787 (73.8%) were women. Forty pregnant and 52 breastfeeding patients with AID were identified, of whom the majority had received at least one dose of COVID-19 vaccine (100% and 96.2%, respectively). AE were reported significantly more frequently in pregnant than in non-pregnant patients (overall AE 45% vs 26%, P = 0.01; minor AE 40% vs 25.9%, P = 0.03; major AE 17.5% vs 4.6%, P