AB0186 NO PREDICTIVE VALUE OF ADALIMUMAB SERUM LEVELS AND ANTI-ADALIMUMAB ANTIBODIES AT TIME OF ADALIMUMAB FAILURE FOR PREDICTION OF RESPONSE TO THE NEXT BDMARD

Background:

After adalimumab treatment failure, TNFi and non-TNFi bDMARDs are equally viable as subsequent treatment in RA. However, preliminary data suggest that anti-drug antibodies (ADA) and adalimumab serum levels (ADL) predict response to a subsequent TNFi [1].

Objectives:

To assess the association of presence of ADA and/or low ADL with response to a subsequent TNFi bDMARD or non-TNFi bDMARD.

Methods:

A retrospective cohort study to assess the predictive value of ADA and ADL for response to a subsequent TNFi or non-TNFi bDMARD in RA patients.

All RA patients who received adalimumab (standard dose, ≥ 3 months) and subsequently switched to another TNFi or a non-TNFi (rituximab, tocilizumab, abatacept) in the Sint Maartenskliniek or Radboud University Medical Centre between January 2012 and January 2018 were considered for inclusion in the current study. Further inclusion criteria were the availability of (random timed) serum samples between ≥8 weeks after start, and ≤2 weeks (for ADL) or ≤12 weeks (for ADA) after discontinuation of adalimumab, and clinical outcome measurements (DAS28-CRP/BSE) between 3-6 months after treatment switch. Serum samples were derived from a period of biobanking at every visit of RA patients and an observational cohort study including consecutive bDMARD starters.

The primary outcome of this study was the association between ADL or ADA and EULAR good response (DAS28-CRP/ESR based) to the subsequent bDMARD. When DAS28-based response was unreliable due to glucocorticoid use, or low baseline DAS28 (if switching due to adverse effects), judgement of the rheumatologist was used.

A drug-tolerant competitive enzyme-linked immunosorbent assay (Sanquin, the Netherlands) was used to quantify ADA, and thereafter, ADL was determined via an ELISA. Reference values were ≥5 µg/ml for ADL and <12 AU/ml for ADA [2,3]. Treatment was blinded for ADL and ADA levels.

Prediction of response were assessed using the area under the receiver-operator characteristic (AUROC) and sensitivity/specificity. Sub-analyses were performed for primary and secondary non-responders. Correlations between ADL and ADA presence and clinical variables were also cross-sectionally explored.

Results:

137 patients were included, 47 of whom switched to a second TNFi and 90 to a non-TNFi. Sensitivity and specificity of the proposed ADA and ADL reference values were low (table 1). The AUROC did not differ appreciably or significantly from 0.5. Results were similar for both primary and secondary non-responders to adalimumab.

Table 1.

predictive values of ADA and ADL for response to a subsequent bDMARD in TNFi and non-TNFi switchers.

sensitivity (%)specificity (%)AUCCITNFi switchersADA presence (>12AU/mL)18750.460.32-0.59low ADL (<5mg/L)32690.500.29-0.71non-TNFi switchersADA presence (>12AU/mL)33700.520.42-0.63low ADL (<5mg/L)50520.500.34-0.65

Higher ADL (Spearman’s ρ = -0.68, p = 0.00) but not ADA (ρ = 0.23, p = 0.28) presence was associated with a lower DAS28 at the time of switching to a subsequent bDMARD, but not with follow-up DAS28 after starting the subsequent bDMARD (ρ = -0.29, p = 0.17, and ρ = 0.10, p = 0.65, respectively). In addition, higher ADL were associated with lower baseline CRP (ρ = – 0.67, p = 0.00) and ESR (ρ = – 0.546, p = 0.006) and higher ADA correlated with higher baseline ESR (ρ = 0.49, p = 0.01).

Conclusion:

No predictive value for response to a second TNFi or non-TNFi was found for either ADA or random timed ADL. Limitations of this study are the retrospective design and random timed serum sampling. An ongoing randomized blinded test-treatment trial will provide more definitive answers [4].

References:

[1]Van Herwaarden et al.Expert Opin Drug Metab Toxicol.2017;13:843–57.

[2]Pouw et al.Ann Rheum Dis.2015 Mar;74(3):513-8.

[3]Bartelds et al.Ann Rheum Dis.2007 Jul;66(7):921-6.

[4]ADDORA-SWITCH study,www.trialregister.nl,no NL 8210

Disclosure of Interests:

Nathan den Broeder: None declared, Evy Ulijn: None declared, Maike Wientjes: None declared, Noortje van Herwaarden: None declared, Inger Meek: None declared, Lieke Tweehuysen: None declared, Aatke van der Maas: None declared, Bart van den Bemt Grant/research support from: UCB, Pfizer and Abbvie, Consultant of: Delivered consultancy work for UCB, Novartis and Pfizer, Speakers bureau: Pfizer, AbbVie, UCB, Biogen and Sandoz., Alfons den Broeder: None declared

Therapeutic drug monitoring of adalimumab in RA: no predictive value of adalimumab serum levels and anti-adalimumab antibodies for prediction of response to the next bDMARD

BACKGROUND

After adalimumab treatment failure, tumour necrosis factor inhibition (TNFi) and non-TNFi biological disease-modifying anti-rheumatic drugs (bDMARDs) are equally viable options on a group level as subsequent treatment in rheumatoid arthritis (RA) based on the current best evidence synthesis. However, preliminary data suggest that anti-adalimumab antibodies (anti-drug antibodies, ADA) and adalimumab serum levels (ADL) during treatment predict response to a TNFi as subsequent treatment.

OBJECTIVE

To validate the association of presence of ADA and/or low ADL with response to a subsequent TNFi bDMARD or non-TNFi bDMARD. Sub-analyses were performed for primary and secondary non-responders.

METHODS

A diagnostic test accuracy retrospective cohort study was done in consenting RA patients who discontinued adalimumab after >3 months of treatment due to inefficacy and started another bDMARD. Inclusion criteria included the availability of (random timed) serum samples between ≥8 weeks after start and ≤2 weeks after discontinuation of adalimumab, and clinical outcome measurements Disease Activity Score in 28 joints - C-reactive protein (DAS28-CRP) between 3 to 6 months after treatment switch. Test characteristics for EULAR (European League Against Rheumatism) good response (DAS28-CRP based) after treatment with the next (non-)TNFi bDMARD were assessed using area under the receiver operating characteristic and sensitivity/specificity.

RESULTS

137 patients were included. ADA presence was not predictive for response in switchers to a TNFi (sensitivity/specificity 18%/75%) or a non-TNFi (sensitivity/specificity 33%/70%). The same was true for ADL levels in patients that switched to a TNFi (sensitivity/specificity 50%/52%) and patients that switched to a non-TNFi (sensitivity/specificity 32%/69%). Predictive value of ADA and ADL were similar for both primary and secondary non-responders to adalimumab.

CONCLUSIONS

In contrast to earlier research, we could not find predictive value for response to a second TNFi or non-TNFi for either ADA or random timed ADL.

Predictive value of ex-vivo drug-inhibited cytokine production for clinical response to biologic DMARD therapy in rheumatoid arthritis

OBJECTIVES

To investigate ex-vivo drug-inhibited cytokine production before the start of a biological DMARD (bDMARD) as predictor of treatment response in rheumatoid arthritis (RA).

METHODS

In a prospective RA cohort study [BIO-TOP], blood samples were obtained from patients before the start of a bDMARD (abatacept, adalimumab, etanercept, rituximab or tocilizumab). Peripheral blood mononuclear cells were pre-incubated for 1 hour with the therapeutic in-vivo concentration of the bDMARD and stimulated for 24 hours with heat-killed Candida albicans or Pam3Cys. Concentrations of IL-1β, IL-6, TNFα, IL-17 and IFNγ were determined by ELISA. EULAR response (good vs. moderate/no) was assessed at month 6. Area under the receiver operating characteristic curves (AUCs) were generated to evaluate the predictive value of baseline characteristics and ex-vivo cytokine production (including stimulated cytokine concentrations and absolute changes after inhibition by a bDMARD). Logistic prediction models were created to assess the added value of potential cytokine predictors.

RESULTS

277 RA patients were included with 330 blood samples. Good response was reached in 39% of the cases. DAS28-CRP was predictive for response to adalimumab (AUC 0.70, 95%CI 0.57-0.83), etanercept (AUC 0.68, 95%CI 0.58-0.78) and rituximab (AUC 0.76, 95%CI 0.65-0.86). ACPA was modestly predictive for response to abatacept (AUC 0.63, 95%CI 0.52-0.75). In the ex-vivo analysis, 4 of 64 (6%) tests showed some predictive value but these had no added value to clinical factors routinely measured in RA, such as DAS28-CRP.

CONCLUSIONS

Ex-vivo inhibition of cytokine production by bDMARDs is unable to help prediction of treatment response to bDMARDs in RA.

Genetic variant in IL-32 is associated with the ex vivo cytokine production of anti-TNF treated PBMCs from rheumatoid arthritis patients

About 60% of RA patients don't achieve good response with biological disease-modifying anti-rheumatic drugs bDMARD treatment (including TNF inhibitors, TNFi's). Previously, a link between TNFα and interleukin (IL)-32 was reported in RA. However, the exact mechanism linking IL-32 to response to treatment as not been studied yet. Therefore, we explored the influence of a promoter single nucleotide polymorphism (SNP) rs4786370 in IL-32 on clinical responsiveness to TNFi's in RA patients, potentially serving as new biomarker in RA. Expression of pro-inflammatory cytokines by peripheral mononuclear cells (PBMCs) from RA patients and healthy individuals were studied. Moreover, "ex vivo response" and clinical response to anti-TNFα therapy (etanercept, adalimumab) were measured and stratified for the IL-32 SNP. Higher IL-32 protein production was observed in RA patients. Additionally, patients bearing the CC genotype showed higher IL-32 protein and cytokine expression. DAS28 was independent of the promoter SNP, however, the "ex vivo" cytokine response was not. IL-32 mRNA and protein production was higher in RA patients, with a trend towards higher concentrations in patients bearing the CC genotype. Furthermore, genotype dependent IL-1 beta production might predict clinical response to etanercept/adalimumab. This indicates that IL-32 could play a role in predicting response to treatment in RA.

Flares in Rheumatoid Arthritis Patients with Low Disease Activity: Predictability and Association with Worse Clinical Outcomes

OBJECTIVE

To investigate predictors of flare in rheumatoid arthritis (RA) patients with low disease activity (LDA) and to evaluate the effect of flare on 12-month clinical outcomes.

METHODS

Patients with RA who were taking disease-modifying antirheumatic drugs and had a stable 28-joint count Disease Activity Score (DAS28) < 3.2 were eligible for inclusion. At baseline and every 3 months, clinical (DAS28), functional [Health Assessment Questionnaire-Disability Index (HAQ-DI), EQ-5D, Functional Assessment of Chronic Illness Therapy Fatigue scale (FACIT-F), Medical Outcomes Study Short Form-36 (SF-36)], serum biomarkers [multibiomarker disease activity (MBDA) score, calprotectin, CXCL10], and imaging data were collected. Flare was defined as an increase in DAS28 compared with baseline of > 1.2, or > 0.6 if concurrent DAS28 ≥ 3.2. Cox regression analyses were used to identify baseline predictors of flare. Biomarkers were cross-sectionally correlated at time of flare. Linear regressions were performed to compare clinical outcomes after 1 year.

RESULTS

Of 152 patients, 46 (30%) experienced a flare. Functional disability at baseline was associated with flare: HAQ-DI had an unadjusted HR 1.82 (95% CI 1.20-2.72) and EQ-5D had HR 0.20 (95% CI 0.07-0.57). In multivariate analyses, only HAQ-DI remained a significant independent predictor of flare (HR 1.76, 95% CI 1.05-2.93). At time of flare, DAS28 and its components significantly correlated with MBDA and calprotectin, but correlation coefficients were low at 0.52 and 0.49, respectively. Two-thirds of flares were not associated with a rise in biomarkers. Patients who flared had significantly worse outcomes at 12 months (HAQ-DI, EQ-5D, FACIT-F, SF-36, and radiographic progression).

CONCLUSION

Flares occur frequently in RA patients with LDA and are associated with worse disease activity, quality of life, and radiographic progression. Higher baseline HAQ-DI was modestly predictive of flare, while biomarker correlation at the time of flare suggests a noninflammatory component in a majority of events.

Open-Label, Non-Mandatory Transitioning From Originator Etanercept to Biosimilar SB4: Six-Month Results From a Controlled Cohort Study

OBJECTIVE

To evaluate the effects of non-mandatory transitioning from the originator biologic drug etanercept (ETN) to its biosimilar, SB4, on drug survival and effectiveness in a controlled cohort study of patients with an inflammatory rheumatic disease.

METHODS

In 2016, 642 patients were asked to transition their treatment from originator ETN to biosimilar SB4 by a structured communication strategy with opt-out option. Patients who consented to switch to SB4 were considered eligible for inclusion in the transition cohort, while patients being treated with originator ETN in 2014 were recruited as the historical cohort. Drug survival was compared between the 2 cohorts using Cox regression analyses, which were adjusted for age, sex, diagnosis, ETN treatment duration, ETN dose interval, conventional synthetic disease-modifying antirheumatic drug usage, and C-reactive protein (CRP) level, with a robust variance estimator applied to account for repeated subjects (i.e., patients who were included in both the transition cohort and the historical cohort). Adjusted differences in the 6-month change in CRP level, Disease Activity Score in 28 joints using CRP level (DAS28-CRP), and Bath Ankylosing Spondylitis Disease Activity Index were also assessed.

RESULTS

Of the 642 ETN-treated patients, 635 (99%) agreed to transition from originator ETN to biosimilar SB4, of whom 625 patients (433 with rheumatoid arthritis, 128 with psoriatic arthritis, and 64 with ankylosing spondylitis) were included in the transition cohort, and 600 ETN-treated patients from 2014 were included in the historical cohort. The crude treatment persistence rate for biosimilar SB4 over 6 months was 90% (95% confidence interval [95% CI] 88-93%), compared to a 6-month treatment persistence rate of 92% (95% CI 90-94%) for originator ETN. Patients in the transition cohort, compared to the historical cohort, had a statistically significantly higher relative risk of treatment discontinuation (adjusted hazard ratio 1.57, 95% CI 1.05-2.36) and showed smaller decreases in the CRP level (adjusted difference 1.8, 95% CI 0.3-3.2) and DAS28-CRP (adjusted difference 0.15, 95% CI 0.05-0.25) over 6 months.

CONCLUSION

Non-mandatory transitioning from originator ETN to biosimilar SB4 using a specifically designed communication strategy resulted in a slightly lower 6-month treatment persistence rate and smaller decreases in disease activity in the transition cohort compared to the historical cohort, but these differences were not considered clinically relevant.

Abatacept and tocilizumab tapering in rheumatoid arthritis patients: results of SONATA-a retrospective, exploratory cohort study

Objectives

As data on disease-activity-guided dose optimization of abatacept and tocilizumab are scarce, we explored the feasibility, effectiveness and safety of dose optimization of these biological DMARDs in RA patients in daily practice.

Methods

RA patients who had been treated with abatacept or tocilizumab for ≥6 months, with DAS28 <3.2, were included. Four groups were identified: abatacept dose reduction (DR) and usual care (UC), and tocilizumab DR and UC. Successful DR and discontinuation entailed being on a lower dose than at baseline or having discontinued abatacept or tocilizumab, while maintaining disease activity score with ESR using 28 joint count (DAS28) <3.2. Proportions of patients with successful DR or discontinuation at 12 months were described. Maintenance of DR was investigated using Kaplan-Meier curves. Between-group differences in mean DAS28 and Health assessment questionnaire disability index (HAQ-DI) change (Δ) over 6 and 12 months were estimated.

Results

One hundred and nineteen patients were included. DR was attempted in 13 of 28 (46%; 95% CI: 28, 66%) abatacept and 64 of 91 (70%; 95% CI: 60, 79%) tocilizumab patients. At 12 months, 3 of 11 (27%; 95% CI: 6, 61%) abatacept and 20 of 48 (42%; 95% CI: 28, 57%) tocilizumab patients were successfully tapered. One of 11 (9%; 95% CI: 0, 41%) abatacept and 5 of 48 (10%; 95% CI: 3, 23%) tocilizumab patients were successfully discontinued. Mean ΔDAS28 and ΔHAQ-DI at months 6 and 12 were not significantly different between DR and UC. For tocilizumab, DAS28 was significantly higher in the DR compared with the UC group at 6 months. Adverse events were comparable between groups.

Conclusion

Abatacept and tocilizumab DR appears to be feasible and safe in clinical practice. No benefits in terms of fewer adverse events in the DR group were observed. Furthermore, DR was suboptimal, because all patients were eligible for DR, but in a substantial number of patients no DR was attempted.

Predictive value of serum calprotectin (S100A8/A9) for clinical response after starting or tapering anti-TNF treatment in patients with rheumatoid arthritis

Objectives

Calprotectin (S100A8/A9) has been correlated with disease activity in rheumatoid arthritis (RA). The aim of this study was to investigate the predictive value of serum calprotectin for clinical response after starting and tapering anti-tumour necrosis factor treatment in RA.

Methods

Serum samples and clinical outcomes were derived from two longitudinal RA studies.

At baseline (starting or tapering of adalimumab or etanercept), calprotectin levels were determined by ELISA. In the Biologic Individual Optimised Treatment Outcome Prediction (BIO-TOP) study, treatment effect was assessed after 6 months using the European League Against Rheumatism (EULAR) response criteria. In the Dose Reduction Strategies of Subcutaneous TNF Inhibitors (DRESS) study, patients were classified at 18 months as being successfully dose reduced, discontinued or not able to reduce the dose. Area under the receiver operating characteristic curves (AUC) were generated to evaluate the predictive value of calprotectin and logistic prediction models were created to assess its added value.

Results

In the BIO-TOP study, calprotectin levels were higher in responders (n=50: 985 ng/mL (p25–p75: 558–1417)) compared with non-responders (n=75: 645 ng/mL (p25–p75: 415–973), p=0.04).

AUC for predicting EULAR good response was 0.61 (95% CI 0.50 to 0.71). The prediction model with calprotectin (AUC 0.77, 95% CI 0.68 to 0.85) performed similarly to the baseline model (AUC 0.74, 95% CI 0.65 to 0.82, p=0.29). In the DRESS study, calprotectin levels were similar between the three groups (n=47; n=19; n=36) and calprotectin was not predictive for clinical response after tapering.

Conclusions

Serum calprotectin has some predictive value for clinical response after starting anti-TNF treatment, although it has no added value to other clinical factors. In patients with low disease activity, serum calprotectin is not predictive for clinical response after tapering anti-TNF treatment.

Trial registration number

NTR4647 (BIO-TOP study) and NTR3216 (DRESS study); Pre-results.

Ex vivo inhibited cytokine profiling may explain inferior treatment response to golimumab after adalimumab failure in rheumatoid arthritis

OBJECTIVES

Clinical data suggest that the response of rheumatoid arthritis patients to treatment with golimumab is much lower among those who switched from adalimumab than among those who switched from etanercept. To elucidate the mechanism behind this difference in response to sequential biologic treatment, we examined the effect of TNF inhibitors on ex vivo cytokine production profiling.

METHODS

In a prospective cohort study, blood samples were obtained from patients before the start of a biologic. Peripheral blood mononuclear cells were pre-incubated for 1 hour with the therapeutic in vivo concentration of adalimumab, etanercept or golimumab and stimulated for 24 hours with heat killed Candida albicans or Pam3Cys. Cytokine concentrations of IL-1β, IL-6 and TNFα were determined by ELISA.

RESULTS

Ex vivo cytokine profiling was performed in 71 patients. Golimumab, adalimumab and etanercept significantly (p<0.01) decreased Candida albicans-induced IL-1β and IL-6 production and Pam3Cys-induced IL-6 production. In contrast to etanercept, golimumab and adalimumab decreased the concentration of TNFα below the detection limit. Absolute changes in cytokine levels after inhibition by golimumab or adalimumab were all significantly correlated (Spearman rank rs: 0.52-0.99, p<0.001). These correlations were much lower or non-significant between etanercept and either golimumab or adalimumab.

CONCLUSIONS

High similarity between ex vivo inhibited cytokine profiling by golimumab and adalimumab, compared to etanercept, may explain the previously found inferior treatment response to golimumab after adalimumab failure. This suggests that patients who are non-responsive to adalimumab should preferably not switch to golimumab and vice versa.

Subjective Complaints as the Main Reason for Biosimilar Discontinuation After Open-Label Transition From Reference Infliximab to Biosimilar Infliximab

OBJECTIVE

To evaluate drug survival, effectiveness, pharmacokinetics, immunogenicity, and safety in daily practice after transitioning treatment from original reference infliximab (Remicade [REM]) to a biosimilar infliximab (CT-P13 [Remsima; Inflectra]) in patients with rheumatoid arthritis, psoriatic arthritis, or ankylosing spondylitis.

METHODS

Of the initial 222 REM-treated patients, 192 agreed to transition to CT-P13 and were included in this multicenter prospective cohort study. Changes in the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP) and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and changes in the CRP levels, infliximab trough levels, and anti-infliximab antibody levels were assessed after 6 months, and adverse events (AEs) were documented. Drug survival and prognostic factors were analyzed using Kaplan-Meier and Cox regression analyses.

RESULTS

During 6 months follow-up, 24% of the patients (n = 47) discontinued CT-P13. Thirty-seven patients restarted REM, 7 switched to another biologic drug, and 3 continued without a biologic drug. The DAS28-CRP remained stable from baseline to month 6, with a mean ± SD score of 2.2 ± 0.9 at baseline to 2.2 ± 0.8 at 6 months (difference of 0.0 [95% confidence interval (95% CI) -0.1, 0.2]). The BASDAI increased from a mean ± SD of 3.8 ± 2.0 at baseline to 4.3 ± 2.1 at 6 months (difference of +0.5 [95% CI 0.1, 0.9]). The CRP levels, infliximab trough levels, and anti-infliximab antibody levels did not change. Just prior to CT-P13 discontinuation, the DAS28-CRP components tender joint count and patient's global assessment of disease activity, as well as the BASDAI were increased compared to baseline. The most frequently reported AEs were arthralgia, fatigue, pruritus, and myalgia. A shorter REM infusion interval (hazard ratio: 0.77 [95% CI 0.62, 0.95]) at baseline was predictive of discontinuing CT-P13.

CONCLUSION

In our cohort, one-fourth of patients discontinued CT-P13 during 6 months of follow-up, mainly due to an increase in the subjective features of the tender joint count and the patient's global assessment of disease activity and/or subjective AEs, possibly explained by nocebo effects and/or incorrect causal attribution effects.

Little Evidence for Usefulness of Biomarkers for Predicting Successful Dose Reduction or Discontinuation of a Biologic Agent in Rheumatoid Arthritis: A Systematic Review

OBJECTIVE

To systematically review studies addressing prediction of successful dose reduction or discontinuation of a biologic agent in rheumatoid arthritis (RA).

METHODS

PubMed, Embase, and Cochrane Library databases were searched for studies that examined the predictive value of biomarkers for successful dose reduction or discontinuation of a biologic agent in RA. Two reviewers independently selected studies, and extracted data and assessed the risk of bias. A biomarker was classified as a "potential predictor" if the univariate association was either strong (odds ratio or hazard ratio >2.0 or <0.5) or statistically significant. For biomarkers that were studied multiple times, qualitative best-evidence synthesis was performed separately for the prediction of successful dose reduction and discontinuation. Biomarkers that were defined in ≥75% of the studies as potential predictors were regarded as "predictor" for the purposes of our study.

RESULTS

Of 3,029 nonduplicate articles initially searched, 16 articles regarding 15 cohorts were included in the present study. Overall, 17 biomarkers were studied multiple times for the prediction of successful dose reduction, and 33 for the prediction of successful discontinuation of a biologic agent. Three predictors were identified: higher adalimumab trough level for successful dose reduction and lower Sharp/van der Heijde erosion score and shorter symptom duration at the start of a biologic agent for successful discontinuation.

CONCLUSION

The predictive value of a wide variety of biomarkers for successful dose reduction or discontinuation of biologic treatment in RA has been investigated. We identified only 3 biomarkers as predictors, in just 2 studies. The strength of the evidence is limited by the low quality of the included studies and the likelihood of reporting bias and multiple testing.

The discriminative capacity of soluble Toll-like receptor (sTLR)2 and sTLR4 in inflammatory diseases

Background

The extracellular domains of cytokine receptors are released during inflammation, but little is known about the shedding of Toll-like receptors (TLR) and whether they can be used as diagnostic biomarkers.

Methods

The release of sTLR2 and sTLR4 was studied in in-vitro stimulations, as well as in-vivo during experimental human endotoxemia (n = 11, 2 ng/kg LPS), and in plasma of 394 patients with infections (infectious mononucleosis, measles, respiratory tract infections, bacterial sepsis and candidemia) or non-infectious inflammation (Crohn’s disease, gout, rheumatoid arthritis, autoinflammatory syndromes and pancreatitis). Using C-statistics, the value of sTLR2 and sTLR4 levels for discrimination between infections and non-infectious inflammatory diseases, as well as between viral and bacterial infections was analyzed.

Results

In-vitro, peripheral blood mononuclear cells released sTLR2 and sTLR4 by exposure to microbial ligands. During experimental human endotoxemia, plasma concentrations peaked after 2 hours (sTLR4) and 4 hours (sTLR2). sTLR4 did not correlate with cytokines, but sTLR2 correlated positively with TNFα (r_s = 0.80, P < 0.05), IL-6 (r_s = 0.65, P < 0.05), and IL-1Ra (r_s = 0.57, P = 0.06), and negatively with IL-10 (r_s = -0.58, P = 0.06), respectively. sTLR4 had a similar area under the ROC curve [AUC] for differentiating infectious and non-infectious inflammation compared to CRP: 0.72 (95% CI 0.66-0.79) versus 0.74 (95% CI 0.69-0.80) [P = 0.80], while sTLR2 had a lower AUC: 0.60 (95% CI 0.54-0.66) [P = 0.0004]. CRP differentiated bacterial infections better from viral infections than sTLR2 and sTLR4: AUC 0.94 (95% CI 0.90-0.96) versus 0.58 (95% CI 0.51-0.64) and 0.75 (95% CI 0.70-0.80), respectively [P < 0.0001 for both].

Conclusions

sTLRs are released into the circulation, and suggest the possibility to use sTLRs as diagnostic tool in inflammatory conditions.