Funding and conclusions of network meta-analyses on targeted therapies in inflammatory diseases: an overview.

OBJECTIVE: To explore the association between industry funding and network meta-analyses' (NMAs) conclusion, and the use in Clinical Practice Guidelines (CPGs) of NMAs. STUDY DESIGN AND SETTING: This was an overview of NMAs and CPGs. We searched PubMed/MEDLINE, Epistemonikos, and several guideline databases up to February 18th 2023. We included CPGs from the last 5 years and NMAs of randomized controlled trials that evaluated targeted therapies in immune-mediated inflammatory diseases. Data extraction and outcome assessments were done in duplicate by independent authors. RESULTS: We included 216 NMAs and 99 CPGs. 31% (67/216) were industry-funded. The proportion of industry-funded NMAs that cited one treatment as being best was 44% (25/57) compared to 26% (30/116) for non-industry funded (OR=2.24 [1.15-4.39]; aOR=1.76 [0.81-3.81]). The abstract's conclusion of 39/67 (58%) industry-funded and 69/149 (46%) non-industry funded NMAs were considered unsupported by the results (OR = 1.61 [0.90-2.89]; aOR=1.40 [0.71-2.78]). All industry-funded NMAs that cited one treatment as best cited their own sponsored drug. 59/99 (60%) CPGs included at least one NMA, with 23/59 (39%) of them citing industry-funded NMAs. CONCLUSIONS: We did not find evidence that industry-funded NMAs were more likely to have unsupported conclusions or to cite only one treatment as being best in their conclusions compared to non-industry funded NMAs. However, almost all industry-funded NMAs favored their own treatments. Even though 40% of the CPGs did not rely on NMA, over a third of those who did used industry-funded NMAs. Limitations include the possible misclassification due to undisclosed funding and potential confounders that have not been accounted for.

Management of patients with rheumatoid arthritis by telemedicine: connected monitoring. A randomized controlled trial.

OBJECTIVES: Rheumatoid arthritis (RA) is a prevalent and disabling disease that is the source of significant direct and indirect costs. The current recommended therapeutic strategy is based on the rapid introduction of therapy with conventional Disease-Modifying Anti-Rheumatic Drugs (DMARDs) combined with regular disease monitoring by the rheumatologist. The onerous nature of such intense monitoring has motivated the development of new, less demanding strategies such as telemedicine. This study aimed to estimate the cost-effectiveness of the connected monitoring of RA patients initiating a new DMARD therapy versus conventional monitoring. METHODS: An economic evaluation based on a randomized controlled trial of 89 patients was conducted. The patients in the intervention group (n=45) were monitored using a connected monitoring interface on a smartphone, while patients in the control group (n=44) were conventionally monitored. Health outcomes were measured as the gain in quality-adjusted life-years (QALYs), assessed using the EuroQol-5D questionnaire. Resource use and health outcomes were collected alongside the trial and at the six-month follow-up using application data and the related clinical case manager time, visits, hospitalisations, and transport records. These outcomes were valued using externally collected data on unit costs and QALY weights. RESULTS: Compared to conventionally monitored patients, patients receiving connected monitoring had a slightly greater but not significant gain in the average QALY of 0.07. The economic analysis found that connected monitoring resulted in a significant cost reduction of 72€ (2927€ vs. 2999€, P<0.01). The incremental cost-utility ratio of the intervention was equal to -1,029€ per QALY (95% CI: -32,033; +24,625) with a 97.8% chance of being cost-effective at a threshold of 30,000€ per QALY gained. CONCLUSION: Implementing EULAR recommendations for RA patients initiating a DMARD treatment using connected monitoring is more efficient and less expensive than conventional care. CLINICAL TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT03005925).

Identification of a Novel Serum Proteomic Signature for Primary Sjögren's Syndrome.

Context: Primary Sjögren's syndrome (pSS) is a complex heterogeneous autoimmune disease (AID) which can mimic rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE). Our exploratory study investigated serum biomarkers that may discriminate pSS from RA and SLE. Methods: Serum concentrations of 63 biomarkers involved in immune cell trafficking, inflammatory response, cellular movement, and cell-to-cell signaling were measured in AID patients, included prospectively into the study at the Montpellier University Hospital. A multivariate analysis by multiple logistic regression was performed, and discriminative power assessed using logistic regression adjusted on significant demographic factors. Results: Among the 95 patients enrolled, 42 suffered from pSS, 28 from RA, and 25 from SLE. Statistical analysis showed that concentrations of BDNF (OR = 0.493 with 95% CI [0.273-0.891]; p = 0.0193) and I-TAC/CXCL11 (OR = 1.344 with 95% CI [1.027-1.76]; p = 0.0314) can significantly discriminate pSS from RA. Similarly, greater concentrations of sCD163 (OR = 0.803 with 95% CI [0.649-0.994]; p = 0.0436), Fractalkine/CX3CL1 (OR = 0.534 with 95% CI [0.287-0. 991]; p = 0.0466), MCP-1/CCL2 (OR = 0.839 with 95% CI [0.732-0.962]; p = 0.0121), and TNFa (OR = 0.479 with 95% CI [0.247-0.928]; p = 0.0292) were associated with SLE diagnosis compared to pSS. In addition, the combination of low concentrations of BDNF and Fractalkine/CX3CL1 was highly specific for pSS (specificity 96.2%; positive predictive value 80%) compared to RA and SLE, as well as the combination of high concentrations of I-TAC/CXCL11 and low concentrations of sCD163 (specificity 98.1%; positive predictive value 75%). Conclusion: Our study highlights biomarkers potentially involved in pSS, RA, and SLE pathophysiology that could be useful for developing a pSS-specific diagnostic tool.