Rheumatology International

, Volume 39, Issue 3, pp 509–515 | Cite as

Factors associated with long-term retention of treatment with golimumab in a real-world setting: an analysis of the Spanish BIOBADASER registry

  • Maria V. Hernandez
  • Carlos Sanchez-Piedra
  • Blanca Garcia-Magallon
  • Eduardo Cuende
  • Javier Manero
  • Cristina Campos-Fernandez
  • Raquel Martin-Domenech
  • Javier del Pino-Montes
  • Sara Manrique
  • Maria C. Castro-Villegas
  • Dolores Ruiz-Montesinos
  • Fernando Sanchez-Alonso
  • Federico Diaz-Gonzalez
  • Luis Cea-Calvo
  • Juan J. Gómez-ReinoEmail author
  • On behalf of the BIOBADASER Study Group
Open Access
Observational Research


The retention rate of a biological drug (percentage of patients remaining on treatment over time) provides an index of a drug’s overall effectiveness. The golimumab retention rate as first-line biological therapy was high in clinical trial extensions lasting 5 years. Real-world studies also indicate good retention rates but have been of shorter duration. The probability of retention with golimumab treatment was assessed, as any line of anti-tumor necrosis factor-alpha therapy, for up to 5 years in patients with rheumatoid arthritis (RA), axial spondyloarthritis (SpA) or psoriatic arthritis (PsA), associated factors were analyzed. A retrospective database analysis of the Spanish registry of patients with rheumatic disorders receiving biological drugs (BIOBADASER) was performed. Among 353 patients, 29.8% had RA, 41.6% SpA and 28.6% PsA. Golimumab was the first biological drug in 40.1% of patients, second in 30.1% and third/later in 29.8%. The overall probability of retention of golimumab at years 1, 2, 3, 4 and 5 was 85.9% (95% confidence interval 81.4–89.5%), 73.7% (67.1–79.1%), 68.5% (60.5–75.1%), 60.6% (50.2–69.5%) and 57.1% (44.9–67.5%), respectively. Retention was similar across indications (p = 0.070) but was greater when golimumab was used as the first biological agent compared with later therapy lines (p < 0.001). Factors associated with higher retention of golimumab treatment (Cox regression) were use as a first-line biological and concomitant methotrexate treatment; corticosteroid need was associated with lower retention. The long-term probability of golimumab retention was high in this real-world study of patients with rheumatic diseases, especially when used as the first biological drug.


Ankylosing spondylitis Axial spondyloarthritis Golimumab Medication retention rate Psoriatic arthritis Rheumatoid arthritis 


Biological disease-modifying antirheumatic drugs (bDMARDs) have improved the treatment of patients with immune-mediated rheumatic disorders, with tumor necrosis factor-alpha (TNFα) inhibitors being the most widely prescribed class of bDMARD for this patient population. Patients need to maintain long-term treatment to continue benefitting from the improvements achieved with these drugs. However, it has been reported that, after 4 years, up to 50% of patients discontinue treatment [1], generally because of a lack of efficacy, but also because of adverse events or personal preference [2].

The retention rate of treatment with biological therapy, or the probability of treatment persistence with the same biological drug (i.e. the probability of maintaining the treatment over time) provides an index of overall drug effectiveness, patient satisfaction and treatment compliance [3, 4]. Patients with rheumatic diseases who need to switch to another drug can incur higher healthcare-related costs [5]. It has been shown that persistence with a first TNFα inhibitor is greater than with a second TNFα inhibitor in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), and that patients treated with a second TNFα inhibitor incur higher costs than those receiving their first TNFα inhibitor [6]. This highlights the importance of maintaining treatment with the same TNFα inhibitor from both clinical and healthcare cost perspectives.

Golimumab is a human anti-TNFα monoclonal antibody with high binding affinity for both soluble and transmembrane TNF [7]. It improves the signs and symptoms of disease in patients with RA, axial spondyloarthritis (SpA; including non-radiographic SpA and ankylosing spondylitis) or PsA [7]. In phase III trials, the golimumab retention rate was high among patients who received it as first-line biological therapy, with approximately 70% of recipients remaining on golimumab after 5 years [8, 9, 10]. In patients with RA who had experienced failure on other anti-TNFα agents, the 5-year retention rate for golimumab was approximately 40% [11]. Studies in a real-world setting have also indicated a high probability of persistence with golimumab treatment in patients with RA, axial SpA or PsA, with 3-year retention rates generally around 60% when it was used as the first biological drug and 50–60% when it was given as second-line biological treatment [12, 13].

The BIOBADASER registry, which was established in 2001, collects long-term follow-up data on patients with rheumatic disorders being treated with biological drugs in a real-world setting in Spain [14]. The database provides an opportunity to evaluate real-life, long-term persistence with antirheumatic treatments among patients with immune-mediated rheumatic disorders. The objective of the current study was to assess the probability of retention with golimumab treatment for up to 5 years after treatment initiation in patients with RA, axial SpA or PsA who received it as any line of anti-TNFα therapy, and to identify factors associated with greater retention rate, using data from the BIOBADASER registry.


This was a retrospective noninterventional study, involving a database analysis of BIOBADASER, which focused on the long-term retention rate of golimumab therapy. BIOBADASER involves investigators from 35 university hospitals representative of the Spanish healthcare system. Patients are enrolled when they initiate a biological therapy and are followed up prospectively until treatment discontinuation. The registry is supported by the Spanish Agency of Medicines ( and the Spanish Society of Rheumatology (


The present study included all adult patients from participating centers who had ever been treated with golimumab for an approved indication (RA, axial SpA including non-radiographic axial SpA and ankylosing spondylitis, or PsA) and had initiated it more than 6 months before the analysis date. Data extraction occurred in October 2017. All patients had signed informed consent to be included in the BIOBADASER registry, covering subsequent analysis such as the present analysis. Patients’ information was managed as anonymized aggregated data and, as approved by the Clinical Research Committee, specific informed consent for this analysis was not required.

Outcome variables

The primary objective of this analysis was to assess the probability of retention with golimumab treatment up to 5 years after treatment initiation. The main variables were treatment start date (the date golimumab was administered for the first time after prescription) and treatment discontinuation date (the date golimumab was definitively stopped). Patients who stopped golimumab and resumed it after more than 90 days were counted as permanent discontinuations. Secondary objectives were to assess the probability of golimumab retention by disease type (RA, axial SpA and PsA) and by line of biological therapy (first, second, or third or later), and to explore potential factors associated with retention (including demographic and disease-related variables).


Data were obtained retrospectively from the BIOBADASER database for all patients for the period from first golimumab prescription until permanent golimumab discontinuation (or last observation for those remaining on treatment). Data collection did not affect the treatment administered to patients. The study was approved by the reference committee and performed in accordance with Good Pharmacoepidemiology Practice standards and the principles of the Declaration of Helsinki. An aggregated report was obtained for this analysis, with no individualized data; consequently, specific informed consent for this study was not required.

Statistical analysis

Summary descriptive statistics were presented as means with standard deviations, medians with percentiles and percentages when applicable. The probability of retention of golimumab treatment was assessed using Kaplan–Meier survival analysis. Patients were right-censored if data were not available for a specific timepoint and for patients remaining on treatment at the time of data analysis. Kaplan–Meier analyses were performed for each specific disease (RA, axial SpA, PsA) and line of golimumab therapy (first, second, or third or later line of biological therapy). Differences according to indication and line of treatment were evaluated using the log-rank test. Cox regression analysis was performed to identify factors associated with golimumab discontinuation. Factors included in the Cox regression were background disease, line of therapy, co-medication and other factors described in previous literature as potential influencers of response to TNFα inhibitors, namely gender, smoking status or weight [15, 16, 17].


At the time of data extraction, 353 patients (mean age 52.2 years) fulfilled the inclusion criteria [162 men (45.9%) and 191 women (54.1%)]. The main patient demographic and disease characteristics are summarized in Table 1. The indication for golimumab was RA for 105 patients (29.8%), axial SpA for 147 (41.6%) and PsA for 101 (28.6%). Median duration of disease at the onset of golimumab treatment was 8.0 (interquartile range 2.8–15.0) years. Golimumab was the first biological drug in 40.1% of patients, second in 30.1% and third or later biological drug in 29.8%. Overall, the most common concomitant medications at the time of golimumab initiation were methotrexate (33.7%) and steroids (26.0%). Percentages for specific background disease are shown in Table 1.

Table 1

General characteristics of patients at golimumab initiation


All (N = 353)

Rheumatoid arthritis (N = 105)

Axial spondyloarthritis (N = 147)

Psoriatic arthritis (N = 101)


 Years, mean (SD)

52.2 (11.0)

57.2 (11.2)

49.8 (11.5)

50.4 (11.8)


 Male, n (%)

162 (45.9)

23 (21.9)

98 (66.7)

41 (40.6)

 Female, n (%)

191 (54.1)

82 (78.1)

49 (33.3)

60 (59.4)

Duration of disease

 Years, median (IQR)

8.0 (2.8–15.0)

7.1 (2.7–12.9)

8.9 (3.2–19.4)

7.1 (2.8–11.6)

Smoking habit

 Never, n (%)

194 (55.0)

49 (46.7)

76 (51.7)

69 (68.3)

 Current, n (%)

81 (23.0)

21 (20.0)

46 (31.3)

14 (13.9)

 Past, n (%)

37 (10.5)

18 (17.1)

10 (6.8)

9 (8.9)

 Not available, n (%)

41 (11.6)

17 (16.2)

15 (10.2)

9 (8.9)

Body mass index

 Normal weight

75 (21.2)

28 (26.7)

27 (18.4)

20 (19.8)


120 (34.0)

24 (22.9)

61 (41.5)

35 (34.7)


74 (21.0)

23 (21.9)

30 (20.4)

21 (20.8)

 Not available, n (%)

84 (23.8)

30 (28.6)

29 (19.7)

25 (24.7)

Order of golimumab treatmenta

 First biological, n (%)

145 (40.1)

57 (52.8)

47 (31.3)

41 (39.4)

 Second, n (%)

109 (30.1)

24 (22.2)

52 (34.7)

33 (31.7)

 Third or later, n (%)

108 (29.8)

27 (25.0)

51 (34.0)

30 (28.9)

Concomitant medication

 Steroids, n (%)

94 (26.0)

54 (50.0)

19 (12.7)

21 (20.2)

 Methotrexate, n (%)

122 (33.7)

59 (54.6)

22 (14.7)

41 (39.4)

 Sulfasalazine, n (%)

22 (6.1)

2 (1.9)

15 (10.0)

5 (4.8)

 Leflunomide, n (%)

46 (12.7)

27 (25.0)

4 (2.7)

15 (14.4)

IQR interquartile range, SD standard deviation

aNine patients received two different golimumab treatments during follow-up

The overall probability of retention of golimumab since treatment initiation was 85.9% (95% confidence interval 81.4–89.5%) at year 1, 73.7% (67.1–79.1%) at year 2, 68.5% (60.5–75.1%) at year 3, 60.6% (50.2–69.5%) at year 4 and 57.1% (44.9–67.5%) at year 5.

Retention of golimumab was similar for patients with RA, axial SpA or PsA (log-rank p = 0.070, Fig. 1). For RA, the probability of retention at years 1, 2 and 3 was 81.8%, 62.4% and 58.3%, respectively; patient numbers at year 4 or later were too small to estimate probability. For patients with axial SpA, the probability of retention was 87.5% (year 1), 76.1% (year 2), 70.2% (year 3), 56.0% (year 4) and 48.0% (year 5), whilst it was 87.6% (year 1), 80.1% (year 2), 75.6% (year 3) and 70.6% (year 4) for PsA patients.

Fig. 1

Rate of retention of treatment with golimumab according to the underlying rheumatic disease (log-rank p = 0.070)

The rate of retention with golimumab therapy was greater when it was used as the first biological agent than when it was used as the second or third (or later) biological drug (log-rank p < 0.001, Fig. 2). When used as the first biological drug, the probability of retention was 94.5% (year 1) and 85.4% (year 2); there were insufficient cases for assessment at year 3 or beyond. When used as the second biological drug, the probability of retention was 89.8% (year 1), 75.2% (year 2), 67.4% (year 3) and 59.2% (year 4). The values were 69.6%, 58.4%, 54.5% and 46.1%, respectively, when golimumab was used as third-line/later biological therapy.

Fig. 2

Rate of retention of treatment with golimumab according to treatment line (log-rank p < 0.001)

Results from the Cox regression analysis to identify factors associated with retention of golimumab are shown in Table 2. The probability of retaining golimumab therapy was greater in patients who received it as first-line biological therapy rather than second- or third-line/later biological therapy (hazard ratio for discontinuation with second-line vs first-line therapy 2.30, 95% CI 1.16–4.55, and for third-line vs first-line therapy 3.92, 95% CI 2.07–7.39), and in those receiving concomitant methotrexate (HR for discontinuation 0.55, 95% CI 0.33–0.91). The probability was lower in those needing concomitant steroids (HR for discontinuation 2.83, 95% CI 1.72–4.66). The rate of golimumab retention seemed to be slightly lower in patients with RA compared with axial SpA or PsA but did not reach statistical significance.

Table 2

Factors associated with the retention of treatment with golimumab: hazard ratios for risk of discontinuation of golimumab (Cox regression analysis)


Hazard ratio

95% confidence interval


Initial model

 Gender (women vs men)




 Age at golimumab initiation




 Disease duration




 Smoking habit (vs non-smoker)




 Overweight (vs normal)




 Obesity (vs normal)




 Second vs first biological drug




 Third vs first biological drug



< 0.01

 Axial SpA vs RA




 PsA vs RA











< 0.01

Final model

 Gender (women vs men)




 Age at golimumab initiation




 Second vs first biological drug




 Third vs first biological drug



< 0.01








< 0.01

PsA psoriatic arthritis, RA rheumatoid arthritis, SpA spondyloarthritis


This registry analysis found that the overall probability of retention of golimumab treatment for patients with RA, axial SpA or PsA in a real-world setting was high in the short term (approximately 86% after 1 year) as well as in the long term, with an overall retention rate of up to 57% after 5 years of treatment initiation. Retention rates did not differ significantly between the different indications but were higher when golimumab was used as the first biological agent rather than as a later line of biological treatment.

The high level of golimumab retention seen in the BIOBADASER registry is consistent with previous data. Other real-world studies have shown high persistence with golimumab therapy over time, although they were limited by a shorter follow-up or were restricted to one specific disease [12, 13, 18, 19]. Overall, across all indications and lines of therapy, 3-year retention rates were 32–67% in these studies, with the lowest rates generally reported for third or later lines of biological treatment [12]. In the current study, golimumab retention at 3 years was 68.5% and, although findings are limited by lower patient numbers, data suggest a high retention rate also at years 4 and 5, which has not been described previously for golimumab in routine clinical practice.

Real-world studies complement the information provided by clinical trials [12, 20]. In long-term extensions of golimumab clinical trials, the 5-year retention rate on the drug was approximately 70% when it was administered as first-line biological therapy in patients with RA, axial SpA or PsA, and 40% when given after failure of other TNFα inhibitors in RA patients [8, 9, 10, 11]. The current registry study was only able to estimate retention rates up to year 2 for first-line use (85.4%), but the results appear to be consistent with the clinical trial findings.

The current analysis did not include a comparison with other TNFα inhibitors. However, other real-world studies have suggested that retention is at least as good, and possibly better, with golimumab than with some other TNFα inhibitors over 3 years [5, 21]. Low immunogenicity, good tolerability with a very low percentage of injection-related side effects and ease of use (1-month dosing and easy-to-use device) can account for better patient acceptance of the drug and, ultimately, high golimumab retention rates [22]. In the current study, regression analysis confirmed that the probability of continuing treatment with golimumab was higher when it was used as the first biological agent rather than as second- or third-line/later biological therapy. This is consistent with data reported previously for golimumab and other TNFα inhibitors [11, 12, 23]. Golimumab retention was better in patients who were receiving concomitant methotrexate. This has been reported previously for golimumab and other anti-TNFα agents in RA patients, and probably relates to a synergistic effect associated with a reduction in the immunogenicity of anti-TNFα monoclonal antibodies [1, 21, 24]. Finally, golimumab retention was reduced in patients who were receiving concomitant steroids, which is consistent with other reports that suggest a need for steroids may be a marker of increased risk of future treatment failure [1]. With regard to other potential factors, smoking habit, body mass index and diagnosis were not associated with golimumab retention rate in the Cox regression model. However, several studies suggest that smoking habit [17] and being overweight or obese [15, 16] can reduce the response to anti-TNFα agents. Failure to find these associations in our study can be explained, in part, by the limited sample size.

In conclusion, long-term retention of treatment with golimumab was high in this real-world study of patients with RA, axial SpA or PsA. Factors associated with an increased probability of retaining golimumab treatment included use as first-line biological therapy and concomitant methotrexate treatment, while steroid need was associated with reduced retention. We cannot rule out the influence of other factors; this aspect requires a larger study to be conducted.



The authors thank Kathy Croom and David P. Figgitt, Ph.D., ISMPP CMPP™, Content Ed Net, for providing medical writing/editorial assistance in the preparation of the manuscript, with funding from MSD Spain.

Author contributions

MVH, CS-P, FD-G, LC-C and JJG-R were involved in the design of the study. Statistical analysis was independently executed by CS-P and FD-G, with overview from MVH, and interpretation by the abovementioned authors. LC-C, an employee of MSD Spain, was involved in the design of the study but was not involved in data collection and had no access to the data source. The rest of the authors are regular investigators of BIOBADASER and made contributions to the current work. All authors reviewed and approved the final version of the manuscript.


This specific analysis was funded by Merck Sharp & Dohme, Spain.

Compliance with ethical standards

Conflict of interest

L Cea-Calvo is an employee of Merck Sharp & Dohme, Spain. The other authors declare no conflict of interest in relation to this article.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institution and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

All patients signed informed consent to be included in the BIOBADASER registry. Informed consent included consent for subsequent analysis, such as in the present analysis. Patients’ information was managed as anonymized aggregated data and, as approved by the Clinical Research Committee, specific informed consent for this analysis was not required.


  1. 1.
    Souto A, Maneiro JR, Gómez-Reino JJ (2016) Rate of discontinuation and drug survival of biologic therapies in rheumatoid arthritis: a systematic review and meta-analysis of drug registries and health care databases. Rheumatology 55(3):523–534Google Scholar
  2. 2.
    Ebina K, Hashimoto M, Yamamoto W, Ohnishi A, Kabata D, Hirano T, Hara R, Katayama M, Yoshida S, Nagai K, Son Y, Amuro H, Akashi K, Fujimura T, Hirao M, Yamamoto K, Shintani A, Kumanogoh A, Yoshikawa H (2018) Drug retention and discontinuation reasons between seven biologics in patients with rheumatoid arthritis—the ANSWER cohort study. PLoS One 13(3):e0194130CrossRefGoogle Scholar
  3. 3.
    Wolfe F (1995) The epidemiology of drug treatment failure in rheumatoid arthritis. Baillieres Clin Rheumatol 9(4):619–632CrossRefGoogle Scholar
  4. 4.
    Favalli EG, Pregnolato F, Biggioggero M, Becciolini A, Penatti AE, Marchesoni A, Meroni PL (2016) Twelve-year retention rate of first-line tumor necrosis factor inhibitors in rheumatoid arthritis: real-life data from a local registry. Arthritis Care Res (Hoboken) 68(4):432–439CrossRefGoogle Scholar
  5. 5.
    Dalén J, Svedbom A, Black CM, Lyu R, Ding Q, Sajjan S, Sazonov V, Kachroo S (2016) Treatment persistence among patients with immune-mediated rheumatic disease newly treated with subcutaneous TNF-alpha inhibitors and costs associated with non-persistence. Rheumatol Int 36(7):987–995CrossRefGoogle Scholar
  6. 6.
    Svedbom A, Dalén J, Black CM, Kachroo S (2017) Persistence and costs with subcutaneous TNF-alpha inhibitors in immune-mediated rheumatic disease stratified by treatment line. Patient Prefer Adher 11:95–106CrossRefGoogle Scholar
  7. 7.
    Rossini M, Viapiana O, Orsolini G, Fracassi E, Idolazzi L, Gatti D, Adami S, Govoni M (2015) Why golimumab in the treatment of psoriatic arthritis, ankylosing spondylitis and rheumatoid arthritis? Reumatismo 66(4):285–303CrossRefGoogle Scholar
  8. 8.
    Deodhar A, Braun J, Inman RD, van der Heijde D, Zhou Y, Xu S, Han C, Hsu B (2015) Golimumab administered subcutaneously every 4 weeks in ankylosing spondylitis: 5-year results of the GO-RAISE study. Ann Rheum Dis 74(4):757–761CrossRefGoogle Scholar
  9. 9.
    Keystone EC, Genovese MC, Hall S, Bae SC, Han C, Gathany TA, Xu S, Zhou Y, Leu JH, Hsia EC (2016) Safety and efficacy of subcutaneous golimumab in patients with active rheumatoid arthritis despite methotrexate therapy: final 5-year results of the GO-FORWARD trial. J Rheumatol 43(2):298–306CrossRefGoogle Scholar
  10. 10.
    Emery P, Fleischmann RM, Strusberg I, Durez P, Nash P, Amante EJ, Churchill M, Park W, Pons-Estel B, Han C, Gathany TA, Xu S, Zhou Y, Leu JH, Hsia EC (2016) Efficacy and safety of subcutaneous golimumab in methotrexate-naive patients with rheumatoid arthritis: five-year results of a randomized clinical trial. Arthritis Care Res (Hoboken) 68(6):744–752CrossRefGoogle Scholar
  11. 11.
    Smolen JS, Kay J, Doyle M, Landewé R, Matteson EL, Gaylis N, Wollenhaupt J, Murphy FT, Xu S, Zhou Y, Hsia EC (2015) Golimumab in patients with active rheumatoid arthritis after treatment with tumor necrosis factor α inhibitors: findings with up to five years of treatment in the multicenter, randomized, double-blind, placebo-controlled, phase 3 GO-AFTER study. Arthritis Res Ther 17:14CrossRefGoogle Scholar
  12. 12.
    Svedbom A, Storck C, Kachroo S, Govoni M, Khalifa A (2017) Persistence with golimumab in immune-mediated rheumatic diseases: a systematic review of real-world evidence in rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis. Patient Prefer Adher 11:719–729CrossRefGoogle Scholar
  13. 13.
    Favalli EG, Sinigaglia L, Becciolini A, Grosso V, Gorla R, Bazzani C, Atzeni F, Sarzi Puttini PC, Fusaro E, Pellerito R, Caporali R (2018) Two-year persistence of golimumab as second-line biologic agent in rheumatoid arthritis as compared to other subcutaneous tumor necrosis factor inhibitors: real-life data from the LORHEN registry. Int J Rheum Dis 21(2):422–430CrossRefGoogle Scholar
  14. 14.
    BIOBADASER III web-based platform (2018) Spanish register on adverse events of biological therapies in rheumatic diseases. Accessed 22 June 2018
  15. 15.
    Gremese E, Bernardi S, Bonazza S, Nowik M, Peluso G, Massara A, Tolusso B, Messuti L, Miceli MC, Zoli A, Trotta F, Govoni M, Ferraccioli G (2014) Body weight, gender and response to TNF-α blockers in axial spondyloarthritis. Rheumatology 53(5):875–881CrossRefGoogle Scholar
  16. 16.
    Singh S, Facciorusso A, Singh AG, Casteele NV, Zarrinpar A, Prokop LJ, Grunvald EL, Curtis JR, Sandborn WJ (2018) Obesity and response to anti-tumor necrosis factor-α agents in patients with select immune-mediated inflammatory diseases: a systematic review and meta-analysis. PLoS One 13(5):e0195123CrossRefGoogle Scholar
  17. 17.
    Canhão H, Rodrigues AM, Mourão AF, Martins F, Santos MJ, Canas-Silva J, Polido-Pereira J, Pereira Silva JA, Costa JA, Araújo D, Silva C, Santos H, Duarte C, da Silva JA, Pimentel-Santos FM, Branco JC, Karlson EW, Fonseca JE, Solomon DH (2012) Comparative effectiveness and predictors of response to tumour necrosis factor inhibitor therapies in rheumatoid arthritis. Rheumatology 51(11):2020–2026CrossRefGoogle Scholar
  18. 18.
    Thomas K, Flouri I, Repa A, Fragiadaki K, Sfikakis PP, Koutsianas C, Kaltsonoudis E, Voulgari PV, Drosos AA, Petrikkou E, Sidiropoulos P, Vassilopoulos D (2018) High 3-year golimumab survival in patients with rheumatoid arthritis, ankylosing spondylitis and psoriatic arthritis: real world data from 328 patients. Clin Exp Rheumatol 36(2):254–262Google Scholar
  19. 19.
    Iannone F, Santo L, Anelli MG, Bucci R, Semeraro A, Quarta L, D’Onofrio F, Marsico A, Carlino G, Casilli O, Cacciapaglia F, Zuccaro C, Falappone PC, Cantatore FP, Muratore M, Lapadula G (2017) Golimumab in real-life settings: 2 years drug survival and predictors of clinical outcomes in rheumatoid arthritis, spondyloarthritis, and psoriatic arthritis. Semin Arthritis Rheum 47(1):108–114CrossRefGoogle Scholar
  20. 20.
    Wolfe F, Michaud K, Dewitt EM (2004) Why results of clinical trials and observational studies of antitumour necrosis factor (anti-TNF) therapy differ: methodological and interpretive issues. Ann Rheum Dis 63(Suppl 2):ii13–ii17Google Scholar
  21. 21.
    Aaltonen KJ, Joensuu JT, Pirilä L, Kauppi M, Uutela T, Varjolahti-Lehtinen T, Yli-Kerttula T, Isomäki P, Nordström D, Sokka T (2017) Drug survival on tumour necrosis factor inhibitors in patients with rheumatoid arthritis in Finland. Scand J Rheumatol 46(5):359–363CrossRefGoogle Scholar
  22. 22.
    Dasgupta B, Combe B, Louw I, Wollenhaupt J, Zerbini CA, Beaulieu A, Schulze-Koops H, Durez P, Wolff V, Yao R, Weng HH, Govoni M, Vastesaeger N (2014) Patient and physician expectations of add-on treatment with golimumab for rheumatoid arthritis: relationships between expectations and clinical and quality of life outcomes. Arthritis Care Res (Hoboken) 66(12):1799–1807CrossRefGoogle Scholar
  23. 23.
    Greenberg JD, Reed G, Decktor D, Harrold L, Furst D, Gibofsky A, Dehoratius R, Kishimoto M, Kremer JM, CORRONA Investigators (2012) A comparative effectiveness study of adalimumab, etanercept and infliximab in biologically naive and switched rheumatoid arthritis patients: results from the US CORRONA registry. Ann Rheum Dis 71(7):1134–1142CrossRefGoogle Scholar
  24. 24.
    Zhang J, Xie F, Delzell E, Yun H, Lewis JD, Haynes K, Chen L, Beukelman T, Saag KG, Curtis JR (2015) Impact of biologic agents with and without concomitant methotrexate and at reduced doses in older rheumatoid arthritis patients. Arthritis Care Res (Hoboken) 67(5):624–632CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Maria V. Hernandez
    • 1
  • Carlos Sanchez-Piedra
    • 2
  • Blanca Garcia-Magallon
    • 3
  • Eduardo Cuende
    • 4
  • Javier Manero
    • 5
  • Cristina Campos-Fernandez
    • 6
  • Raquel Martin-Domenech
    • 7
  • Javier del Pino-Montes
    • 8
  • Sara Manrique
    • 9
  • Maria C. Castro-Villegas
    • 10
  • Dolores Ruiz-Montesinos
    • 11
  • Fernando Sanchez-Alonso
    • 2
  • Federico Diaz-Gonzalez
    • 12
  • Luis Cea-Calvo
    • 13
  • Juan J. Gómez-Reino
    • 14
    Email author
  • On behalf of the BIOBADASER Study Group
  1. 1.Rheumatology ServiceHospital Clinic i ProvincialBarcelonaSpain
  2. 2.Research UnitSociedad Española de ReumatologíaMadridSpain
  3. 3.Rheumatology ServiceHospital San JorgeHuescaSpain
  4. 4.Rheumatology ServiceHospital Universitario Príncipe de Asturias (Alcalá de Henares)MadridSpain
  5. 5.Rheumatology ServiceHospital Miguel ServetZaragozaSpain
  6. 6.Rheumatology ServiceHospital General Universitario ValenciaValenciaSpain
  7. 7.Rheumatology ServiceHospital de EldaAlicanteSpain
  8. 8.Rheumatology ServiceHospital de SalamancaSalamancaSpain
  9. 9.Rheumatology ServiceHospital Carlos Haya de MálagaMálagaSpain
  10. 10.Rheumatology ServiceHospital Reina Sofía (Córdoba)CórdobaSpain
  11. 11.Rheumatology ServiceHospital Virgen de Macarena (Sevilla)SevilleSpain
  12. 12.Rheumatology ServiceHospital Universitario de CanariasSan Cristóbal de La LagunaSpain
  13. 13.Medical Affairs, DepartmentMerck Sharp and Dohme of SpainMadridSpain
  14. 14.Rheumatology DepartmentHospital Universitario de Santiago de CompostelaSantiago de CompostelaSpain

Personalised recommendations