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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

Objective

Obesity is a mild, long-lasting inflammatory disease and, as such, could increase the inflammatory burden of rheumatoid arthritis (RA). The study aim was to determine whether obesity represents a risk factor for a poor remission rate in RA patients requiring anti–tumor necrosis factor α (anti-TNFα) therapy for progressive and active disease despite treatment with methotrexate or other disease-modifying antirheumatic drugs.

Methods

Patients were identified from 15 outpatient clinics of university hospitals and hospitals in Italy taking part in the Gruppo Italiano di Studio sulle Early Arthritis network. Disease Activity Score in 28 joints (DAS28), body mass index (BMI; categorized as <25, 25–30, and >30 kg/m2), acute-phase reactants, IgM rheumatoid factor, and anti–cyclic citrullinated peptide antibody values were collected. DAS28 remission was defined as a score of <2.6 lasting for at least 3 months.

Results

Six hundred forty-one outpatients with longstanding RA receiving anti-TNFα blockers (adalimumab, n = 260; etanercept, n = 227; infliximab, n = 154), recruited from 2006–2009 and monitored for at least 12 months, were analyzed. The mean ± SD DAS28 at baseline was 5.6 ± 1.4. A BMI of >30 kg/m2 was recorded in 66 (10.3%) of 641 RA patients. After 12 months of anti-TNFα treatment, a DAS28 of <2.6 was noted in 15.2% of the obese subjects, in 30.4% of the patients with a BMI of 25–30 kg/m2, and in 32.9% of the patients with a BMI of <25 kg/m2 (P = 0.01). The lowest percentage of remission, which was statistically significant versus adalimumab and etanercept (P = 0.003), was observed with infliximab.

Conclusion

Obesity represents a risk factor for a poor remission rate in patients with longstanding RA treated with anti-TNFα agents. A personalized treatment plan might be a possible solution.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

In the last 10 years, it has become clear that the white adipose tissue produces inflammation (1, 2). Being overweight has been associated with increased disability per se, and it represents a crucial risk factor in the worsening of osteoarthritis (3, 4). The link between obesity and the appearance of rheumatoid arthritis (RA) or its activity is still controversial (5–8). There is some evidence that in the early phases of RA, obesity may even slow down the progression of the disease (9), whereas in an advanced disease, obesity increases disease activity and disability (6, 10). The relationship between obesity and RA activity might imply that, in the long term, controlling disease activity becomes increasingly harder in overweight subjects, as suggested by a recent study of patients taking tumor necrosis factor α (TNFα) blockers monitored for only 4 months (11). If this were true in the overall RA population, it would be of the utmost importance given the cost of care of RA patients with high disease activity. The aim of this study was to examine whether the rate of remission to biologic therapy may be hampered by obesity.

Significance & Innovations

  • These data from a national registry show that obesity represents an additional risk of not reaching remission in rheumatoid arthritis (RA) patients receiving the first anti–tumor necrosis factor α drug due to an active disease under disease-modifying antirheumatic drug conventional therapy.

  • Obesity appears to influence the response to infliximab, the only drug administered according to body weight, more than the response to etanercept or adalimumab in RA patients.

  • The results may also be important not only from a clinical point of view, but even in terms of pharmacoeconomics, which means achieving the best possible results by making the right choice at any phase of the disease in a patient with a poor response to methotrexate.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

Study sample.

The data of subjects considered in the present study were taken from the Gruppo Italiano di Studio sulle Early Arthritis (GISEA) registry, which collects new cases of inflammatory arthritides from the 15 early arthritis clinics of the network (study collaborators of the GISEA are shown in Appendix A). The historical GISEA population is made up of patients with longstanding arthritides under treatment with biologic drugs, mainly anti-TNFα, for RA or spondylarthropathies (12).

The present study considered only the RA patients who, having an active moderate to severe disease despite treatment with methotrexate (MTX) at the usual dosage of 15–25 mg/week, according to the tolerability, were put on anti-TNFα drugs with the aim of reaching the best possible outcome (i.e., remission). They also had regular followup visits at 3-, 6-, and 12-month intervals, during which all of the parameters were recorded. All patients fulfilled the 1987 American College of Rheumatology criteria for RA (13). A total of 641 patients with longstanding RA, monitored for 12 months, were included in the study.

Among the more than 2,000 patients in the database, only RA patients that had no changes in their treatment in the 3 months preceding the anti-TNFα start were selected for the analysis. Therefore, the study eliminated all of the patients that had recent changes in corticosteroids, those that had to change from MTX to another disease-modifying antirheumatic drug (DMARD) and/or a modified MTX dose, those that had recent intraarticular injections, and those that had significant comorbidities requiring temporary changes in their biologic therapies, either as possible switches or as changes in the scheduled doses. Corticosteroids had to remain stable at ≤7.5 mg/day in prednisone equivalents during the 3 months preceding the biologic therapy. Moreover, all patients considered in the study maintained the same anti-TNF agent during the 12-month observation period. The 3 anti-TNFα agents were given according to the usual schedule, i.e., 40 mg subcutaneously every 2 weeks for adalimumab, 50 mg subcutaneously every week for etanercept, and 3 mg/kg intravenously every 8 weeks after the induction phase (time 0, time 15 days, time 45 days) for infliximab.

Measurements.

We stored data regarding the disease duration, body mass index (BMI), steroid treatment, dose and type of the anti-TNF drug initiated because of an incomplete response to MTX, acute-phase reactants (erythrocyte sedimentation rate [ESR]), IgM rheumatoid factor (RF), anti–cyclic citrullinated peptide (anti-CCP), Disease Activity Score in 28 joints (DAS28), visual analog scale (VAS) for pain, global health as assessed by the physician, and the Health Assessment Questionnaire (HAQ). RA patients were categorized as seropositive for RF when the nephelometric value was >20 IU/ml, and for anti-CCP when the CCP2 test was >5 IU/ml. The assessment of DAS28 remission, defined as such when the DAS28 was <2.6 for at least 3 months from month 6 to month 12, was made at months 6, 9, and 12.

BMI was categorized into 3 classes, i.e., <25 kg/m2 (normal weight), between 25 and 30 kg/m2 (overweight), and >30 kg/m2 (obese), according to the National Institutes of Health classification (14). Obese patients (BMI >30 kg/m2) were examined as the cohort of interest.

Treatments.

All of the patients had an active disease (DAS28 ≥3.7) at the start of anti-TNF treatment, despite receiving MTX at the highest tolerated dose or other DMARDs in patients with a serious intolerance to MTX. In each case, the rheumatologists initiated anti-TNFα treatment according to their personal choice and at the usual recommended dose. The only drug that had a relationship with body weight was infliximab. Corticosteroids were maintained for the entire observation period at the dosage of entry into the study that was set at ≤7.5 mg/day in prednisone equivalents.

Outcomes.

The primary outcome was to define whether obesity influences the clinical response to anti-TNF treatment. The secondary outcome was to verify whether the relationship between obesity and treatment outcome is different for the 3 biologic drugs taken into consideration.

Statistical analysis.

On the basis of the data relating to all of the selected GISEA patients who had longstanding RA and were receiving anti-TNFα agents for at least 1 year, the differences between the obese patients versus the other 2 subgroups were analyzed using the Kruskal-Wallis nonparametric test for the continuous variables as mean values and SDs, and the chi-square test for the categorical variables as absolute numbers and percentages.

Comparisons among the 3 anti-TNFα agents were performed using one-way analysis of variance and Kruskal-Wallis tests. Correlations between continuous variables were determined using the nonparametric Spearman's test. The multivariate analyses were performed using stepwise logistic regression models. The response variable was defined as DAS28 remission after 1 year. The baseline variables taken into account were age at the start of therapy, sex, disease duration, the DAS28, ESR, VAS pain, physician-assessed global health, HAQ scores, BMI, concurrent use of corticosteroids, RF positivity, anti-CCP positivity, and biologic agent treatment.

All of the analyses were performed using SAS, version 9.2, and a P value of 0.05 or less was considered statistically significant.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

Study cohort.

Six hundred forty-one RA patients satisfied the entry criteria, as reported in the Methods, and had regular followup visits. The demographic and clinical data are reported in Table 1: 81% of the RA patients were women, 67.8% were RF positive, 70.5% were anti-CCP positive, all had an active disease as shown by the high DAS28 (mean ± SD 5.6 ± 1.4) and a moderate disability as shown by HAQ values (mean ± SD 1.3 ± 0.7), and 10.3% had a BMI >30 kg/m2. In the obese cohort, 56 (84.8%) of the obese patients were women, thus reflecting the male to female ratio of the entire cohort.

Table 1. Characteristics of the total RA population at the start of biologic (anti-TNFα) therapy*
 RA patients (n = 641)
  • *

    Values are the mean ± SD unless otherwise indicated. RA = rheumatoid arthritis; anti-TNFα = anti–tumor necrosis factor α; DAS28 = Disease Activity Score in 28 joints; ESR = erythrocyte sedimentation rate; HAQ = Health Assessment Questionnaire; VAS = visual analog scale; RF = rheumatoid factor; anti-CCP = anti–cyclic citrullinated peptide; BMI = body mass index.

Female sex, no. (%)521 (81.3)
Age, years52.1 ± 13.5
Disease duration, years8.4 ± 8.8
DAS285.6 ± 1.4
ESR, mm/hour35.9 ± 22.1
HAQ score1.3 ± 0.7
Global health (range 0–100)60.6 ± 24.0
VAS pain (range 0–100)63.1 ± 23.7
RF positive, no./total (%)328/484 (67.8)
Anti-CCP positive, no./total (%)237/336 (70.5)
Current steroid therapy, no. (%)249 (38.9)
Anti-TNF agent, no. (%) 
 Adalimumab260 (40.6)
 Etanercept227 (35.4)
 Infliximab154 (24.0)
BMI, kg/m224.9 ± 4.2
 <25, no. (%)368 (57.4)
 25–30, no. (%)207 (32.3)
 >30, no. (%)66 (10.3)

At baseline, no correlations were found among the BMI values and the disease activity values (DAS28), the parameters of inflammation (ESR), and the disability index (HAQ). There was only a weak correlation between the BMI and the age at the start of anti-TNFα therapy (r = 0.16, P < 0.001).

The 3 anti-TNFα agents adalimumab, etanercept, and infliximab were used in 40.6%, 35.4%, and 24% of the cases, respectively. Table 2 shows data at baseline regarding the clinical characteristics of the RA patients according to the biologic drug given. There were no differences among the 3 subgroups of treatment in the percentage of women, the RF positivity, and the percentage of patients taking prednisone. The percentage of anti-CCP–positive patients was higher in the group treated with infliximab (84.8% in the infliximab-treated patients, 67.2% in the adalimumab-treated patients, and 62.7% in the etanercept-treated patients; P = 0.002). Indeed, patients assigned to adalimumab had lower baseline values of the DAS28, HAQ, VAS pain, and physician-assessed global health, but had a longer disease duration compared to patients receiving the other 2 anti-TNF drugs. No differences were seen in either the ESR or the BMI values among the 3 treated groups.

Table 2. Baseline characteristics of patients according to the anti-TNFα agent administered*
 Adalimumab (n = 260)Etanercept (n = 227)Infliximab (n = 154)P
  • *

    Values are the mean ± SD unless otherwise indicated. Anti-TNFα = anti–tumor necrosis factor α; NS = not significant; DAS28 = Disease Activity Score in 28 joints; ESR = erythrocyte sedimentation rate; HAQ = Health Assessment Questionnaire; VAS = visual analog scale; RF = rheumatoid factor; anti-CCP = anti–cyclic citrullinated peptide; BMI = body mass index.

Female sex, no. (%)208 (80)186 (81.9)127 (82.5)NS
Age, years52.5 ± 12.852.3 ± 14.651.0 ± 13.0NS
Disease duration, years9.7 ± 9.38.4 ± 8.66.5 ± 7.80.0002
DAS285.4 ± 1.35.7 ± 1.35.8 ± 1.50.004
ESR, mm/hour33.9 ± 21.036.8 ± 21.837.6 ± 24.2NS
HAQ score1.2 ± 0.61.4 ± 0.71.4 ± 0.70.0001
VAS pain59.6 ± 21.565.9 ± 24.065.9 ± 27.20.004
Global health55.8 ± 21.963.9 ± 23.765.6 ± 27.30.0001
RF positive, %65.268.570.5NS
Anti-CCP positive, %67.262.784.80.002
BMI, kg/m224.7 ± 3.824.9 ± 4.225.2 ± 4.7NS

Followup.

Primary outcome.

At the 12-month followup, 30.3% of the total RA cohort had reached DAS28 remission. As shown in Figure 1, the percentage of DAS28 remission was significantly different between the obese and nonobese patients. In particular, after 1 year of anti-TNF therapy, only 10 (15.2%) of 66 obese RA subjects achieved remission with respect to 184 (32.0%) of the 575 patients with a BMI of <30 kg/m2 (odds ratio [OR] 2.63, 95% confidence interval [95% CI] 1.31–5.26 for not achieving remission in obese patients; P = 0.005).

thumbnail image

Figure 1. Percentage of Disease Activity Score in 28 joints (DAS28) remission at the 12th month of anti–tumor necrosis factor α therapy in rheumatoid arthritis patients according to body mass index (BMI) categories.

Download figure to PowerPoint

Moreover, we then categorized patients according to different BMI thresholds (where <20 kg/m2 = underweight, 20–30 kg/m2 = normal weight, and >30 kg/m2 = obese). The remission rate fell from 46.7% in underweight subjects to 30.2% in normal weight patients and 15.2% in obese patients (BMI <20 kg/m2 versus 20–30 kg/m2: OR 2.03 [95% CI 1.91–3.46), P = 0.01; BMI 20–30 kg/m2 versus >30 kg/m2: OR 2.43 [95% CI 1.21–4.88], P = 0.01).

The RA patients reaching or not reaching DAS28 remission at the 12-month followup were compared for baseline characteristics, in particular to see whether the BMI per se was different at baseline between the remitters and the nonremitters (Table 3). At the start of the anti-TNFα therapy, the nonremitters were older and showed higher levels of disease activity, disability index, and ESR, as well as BMI, with respect to the remitters (mean ± SD BMI 25.2 ± 4.4 kg/m2 in the nonremitters versus 24.2 ± 3.6 kg/m2 in the remitters; P = 0.02).

Table 3. Baseline characteristics of rheumatoid arthritis patients reaching or not reaching remission after 12 months of anti-TNFα therapy*
 Remission (n = 194)No remission (n = 447)P
  • *

    Values are the mean ± SD. Anti-TNFα = anti–tumor necrosis factor α; NS = not significant; DAS28 = Disease Activity Score in 28 joints; ESR = erythrocyte sedimentation rate; HAQ = Health Assessment Questionnaire; VAS = visual analog scale; BMI = body mass index.

Age, years49.2 ± 13.453.6 ± 13.2< 0.001
Disease duration, years8.2 ± 7.28.7 ± 9.3NS
DAS285.1 ± 1.55.8 ± 1.3< 0.001
ESR, mm/hour27.9 ± 17.739.3 ± 23.0< 0.001
HAQ score1.1 ± 0.71.4 ± 0.7< 0.001
VAS pain59.9 ± 25.864.8 ± 22.4NS
Global health57.4 ± 27.161.8 ± 22.3NS
BMI, kg/m224.2 ± 3.625.2 ± 4.40.02

On the other hand, the baseline characteristics were similar among patients in the 3 categories of BMI considered (<25, 25–30, and >30 kg/m2), in particular with respect to disease activity (DAS28 values), parameters of inflammation (ESR or C-reactive protein level), and disability index (HAQ).

In our cohort, no differences were found in percentages of a good European League Against Rheumatism response among the 3 BMI categories (data not shown).

Secondary outcome.

As far as treatments are concerned, the 3 anti-TNF drugs considered in the study had different outcomes. In particular, the RA patients treated with etanercept and adalimumab obtained a similar percentage of DAS28 remission (35.6% and 34.3%, respectively; P = not significant), but DAS28 remission was significantly higher compared to subjects treated with infliximab (19.5%; P = 0.004 versus adalimumab and P = 0.001 versus etanercept). These results maintain the same significance even after applying an analysis of variance model to compensate for baseline imbalances, in particular for the DAS28, sex, BMI, nonbiologic therapy, and the HAQ.

When we considered obtaining remission according to obesity status, separating groups by anti-TNF agent used, we observed a trend of lower remission rates in obese subjects with all 3 anti-TNF agents considered in this study, as shown in Figure 2, but this finding reached statistical significance only in patients treated with infliximab. In particular, we found that none of the obese RA patients treated with infliximab reached DAS28 remission in comparison to 22.4% of the patients with a BMI of <30 kg/m2 (P = 0.01). In the other 2 subgroups, 14.8% of obese RA subjects treated with adalimumab obtained remission with respect to 30.1% of the nonobese patients (P = 0.08), with 27.6% versus 36.2% in the etanercept-treated group (P = 0.44) (Figure 2). Obesity seems to influence the response to infliximab more than the response to adalimumab and etanercept. The data suggest that the chimeric monoclonal antibody cannot overcome the obesity-related inflammatory barrier.

thumbnail image

Figure 2. Percentage of Disease Activity Score in 28 joints (DAS28) remission in obese and nonobese rheumatoid arthritis patients treated with adalimumab (ADA), etanercept (ETA), and infliximab (IFX). None of the obese patients responded to IFX. BMI = body mass index.

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Multivariate analysis.

When considering all of the clinical, laboratory, and therapeutic variables, it was noted that 2 clinical variables, the DAS28 and the BMI, and 1 therapeutic variable, the type of anti-TNF agent used, play the most important role in determining the primary results, as shown in Table 4. No role was foreseen for sex in this study. In other words, if the DAS28 and body weight are higher, the chance of obtaining remission is lower. In this setting, the appropriate treatment should be clearly personalized as much as possible.

Table 4. Multivariate model predicting the 12-month remission after anti-TNFα therapy in the overall cohort of rheumatoid arthritis patients*
Dependent variablesOR (95% CI)P
  • *

    OR = odds ratio; 95% CI = 95% confidence interval; NS = not significant; DAS28 = Disease Activity Score in 28 joints; ESR = erythrocyte sedimentation rate; VAS = visual analog scale; HAQ = Health Assessment Questionnaire; BMI = body mass index; RF = rheumatoid factor; anti-CCP = anti–cyclic citrullinated peptide.

  • Variables independently associated with DAS28 remission at 12 months of anti–tumor necrosis factor α (anti-TNFα) therapy.

Age, years0.985 (0.957–1.015)NS
Female sex0.457 (0.171–1.225)NS
Disease duration0.961 (0.91–1.015)NS
DAS280.436 (0.327–0.582)< 0.0001
ESR, mm/hour0.985 (0.962–1.01)NS
VAS pain1.005 (0.985–1.025)NS
Global health0.999 (0.979–1.019)NS
HAQ score0.778 (0.41–1.475)NS
BMI, kg/m20.892 (0.806–0.987)0.02
Baseline steroids, no vs. yes0.399 (0.218–0.729)0.003
RF, positive vs. negative0.882 (0.376–2.071)NS
Anti-CCP, positive vs. negative1.04 (0.474–2.282)NS
Adalimumab vs. infliximab2.435 (1.022–5.802)0.04
Etanercept vs. infliximab3.253 (1.334–7.929)0.01

These results maintain the same significance even after applying an analysis of variance model to compensate for baseline imbalances.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

Obesity is a serious illness in our society because it plays a major role in several chronic diseases and in premature death (15, 16). Furthermore, obesity is becoming more and more prevalent (17). The percentage of obese RA patients has been shown to reflect the trends of the general population, thus suggesting that patients with RA should be treated accordingly, considering the risk of comorbidities associated with adiposity (18, 19). Obesity was considered among the risk factors for developing RA (6, 7), but more recently, a group from Leiden, The Netherlands, did not confirm the BMI values as a risk factor of evolving into RA in patients with undifferentiated arthritis (20). Second, even more stringent, some studies showed that a BMI of >30 kg/m2 was associated with less erosions over time in an early arthritis cohort in Leiden (20), and was associated with a lower prevalence of mortality among RA patients in Texas (21). These data are very difficult to match with other data, showing that, in longstanding RA, obesity determines higher grades of arthritis-attributable physical limitations (22) and is associated with more disease activity and functional disability (6, 10, 23). In a large community practice database (Quantitative Standardized Monitoring of Patients with Rheumatoid Arthritis) that collected data from 5,161 patients in 25 countries, it was noted that BMI was similar between sexes, but it also transpired that the DAS28 scores among female subjects increased with increasing BMI from normal weight to overweight and obese (24). Of interest, in that study, the association between BMI and disease activity values was not explained by any single component of the DAS28. Our data are different from all of these reports because we focused on patients who were taking anti-TNFα drugs due to persistent unresponsiveness to MTX and who did not change their standard therapy. The findings imply that, besides being patients with longstanding RA, the disease was already persistent, stable, and active. In these patients, the possible positive effect of obesity as seen in other studies in the first years of the disease had already been lost. The patients considered in our study had a persistently active disease and mild to moderate disability, i.e., the worst situation in the long run in terms of future disability and future cardiovascular morbidity. In this setting, we have seen that obesity determines a lower chance of successful response to anti-TNFα therapy and that this occurs more with infliximab and less with adalimumab and etanercept. This result was confirmed in the subanalysis of the BeST (Behandelstrategieën voor Reumatoide Artritis) trial, in which overweight and obese patients responded less than normal weight patients (25) to the combination of MTX and infliximab, whereas in an abstract presented at the American College of Rheumatology Annual Scientific Meeting in Chicago, Illinois in 2011, even etanercept plus MTX in RA patients with moderate disease activity led to a lower clinical response in the 52-week PRESERVE trial (26). The reason that obesity affects the RA outcome in patients treated with infliximab much more than in those treated with etanercept and adalimumab needs to be clarified. In fact, these findings do not seem to be the result of pharmacokinetic factors, as discussed in the study by Klaasen et al (11), and to our knowledge, there are no data about a possible infliximab compartmentalization in the adipose tissue. On the other hand, it is well known that adipose tissue is a source of specific adipocytokines (e.g., leptin, resistin, adiponectin, and visfatin) that are increased in RA patients and are able to increase the expression of inflammatory cytokines, such as TNF and interleukin-6. Therefore, it could be speculated that the adipose tissue might play a role in creating a more inflammatory and therapy-resistant state. In this regard, however, studies testing the effect of TNF blockade on adipokine plasma levels in patients with RA are not conclusive, and the majority of the studies show that anti-TNF drugs have no influence on the levels of adipocytokines (27). However, the adipose tissue may be associated with an induction of resistance to all of the anti-TNF drugs, and understanding its role requires further research.

Our data obtained from a large cohort of patients provide more insight into the findings of Klaasen et al (11). In that study, after 16 weeks of treatment with infliximab, 89 patients observed a highly significant negative association between BMI and the absolute decrease in DAS28. From a clinical point of view, this appears to be extremely important because the persistence of inflammation already represents a high risk of cardiovascular disease and RA is considered at the same risk level as type 2 diabetes mellitus (1, 2, 28, 29). In this setting, obesity may represent a further challenge in terms of treatment of inflammatory conditions such as RA, either because it represents per se a mild inflammatory condition (1, 30) or because it can reduce the response to therapy, especially in patients who need to be treated with TNFα blockers, and then add to the conventional risk factors for cardiovascular morbidity. Indeed, even in our cohort, despite a great overall improvement, the nonremitters still had high inflammatory parameters, albeit in a minority of patients. Certainly, inflammation and disability represent the first target of any therapy in patients who are incomplete responders to MTX, yet there are no algorithms for choosing among the TNFα blockers as a rescue therapy in obese patients with RA. We have provided data obtained from a real-life setting that can be of help in clinical practice. The data should be further confirmed in other registry databases, so that all possible confounders existing in the general RA population can be normalized. After checking for possible confounders (steroids, DMARDs alternative to MTX, etc.), we have reached some practical conclusions.

The first conclusion is that a high DAS28 in the therapeutic protocol certainly plays the most relevant role in determining a lower chance of remission. Obesity represents a further additional risk of not reaching remission. In this setting, the highest chance of putting RA into remission is provided by 2 TNFα blockers (etanercept and adalimumab), with the lowest chance provided by another TNFα blocker (infliximab). The findings appear relevant when one considers the need of a personalized therapy (31). Moreover, the results indicate importance in terms of pharmacoeconomics, which means achieving the best possible results by making the right choice at any phase of the disease in a patient with a poor response to MTX.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Gremese had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Gremese, Padovan, Ferraccioli.

Acquisition of data. Gremese, Carletto, Padovan, Atzeni, Raffeiner, Giardina, Favalli, Erre, Gorla, Galeazzi, Foti, Cantini, Salvarani, Olivieri, Lapadula, Ferraccioli.

Analysis and interpretation of data. Gremese, Ferraccioli.

ROLE OF THE STUDY SPONSOR

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

CD-Pharma was involved in data cleaning and the statistical analysis of the study, but had no role in the study design, data collection, data analysis, or writing of the manuscript, as well as the approval of the content of the submitted manuscript. Publication of this article was not contingent on the approval of CD-Pharma.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

We sincerely thank all of the members of the GISEA group in addition to the authors (Silvano Adami, Marcello Govoni, Antonio Marchesoni, Giuseppe Passiu, Leonardo Punzi, Pier Carlo Sarzi Puttini, Giovanni Triolo, and Francesco Trotta), and Roberto Benini (CD-Pharma) for his support in data cleaning and statistical analysis.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A
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APPENDIX A

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. Acknowledgements
  10. REFERENCES
  11. APPENDIX A

STUDY COLLABORATORS OF THE GRUPPO ITALIANO DI STUDIO SULLE EARLY ARTHRITIS (GISEA)

Study collaborators of the Gruppo Italiano di Studio sulle Early Arthritis (GISEA) are as follows: Silvano Adami (Verona), Gianfilippo Bagnato (Messina), Gianluca Bagnato (Messina), Giovanni Miceli (Messina), Oscar Epis (Milan), Eleonora Bruschi (Milan), Cinzia Casu (Milan), Anna Laura Fedele (Rome), M. Di Gangi (Catania), Nicolò Cino (Catania), G. Amato (Catania), Bruno Frediani (Siena), Stefania Manganelli (Siena), Marcello Govoni (Ferrara), Valentina Foschi (Ferrara), Valentina Bagnari (Ferrara), Florenzo Iannone (Bari), Antonella Notarnicola (Bari), Antonio Marchesoni (Milan), Alessandro Mathieu (Cagliari), Matteo Piga (Cagliari), Giovanni Porru (Cagliari), Riccardo Meliconi (Bologna), Luana Mancarella (Bologna), Giuseppe Passiu (Sassari), Leonardo Punzi (Padua), Fausto Salaffi (Jesi), Stefania Gasparini (Jesi), Olga Addimonda (Reggio Emilia), Mariagrazia Catanoso (Reggio Emilia), Piercarlo Sarzi-Puttini (Milan), Sara Bongiovanni (Milan), Alberto Batticciotto (Milan), Raffaele Scarpa (Naples), and Giovanni Triolo (Palermo, Italy).