Rheumatoid arthritis patients treated in trial and real world settings: comparison of randomized trials with registries

Rheumatoid arthritis patients treated in trial and real world settings: comparison of randomized... Abstract Objective To investigate whether patients with RA enrolled in randomized controlled trials (RCTs) and observational studies may differ in terms of characteristics that could modify treatment effects, leading to an efficacy–effectiveness gap. Methods We conducted systematic literature reviews to identify RCTs and observational studies with RA, treated with rituximab, tocilizumab or etanercept. We extracted baseline characteristics and compared the data of RCTs and observational studies using fixed-effects meta-analyses for the RCTs and random-effects meta-analyses for the observational studies. We also assessed whether the baseline characteristics changed over time. Results Compared with patients enrolled in RCTs, those from observational studies were on average 3.0 years older (P < 0.001), suffered from RA for 3.1 years longer (P < 0.001), had 1.6 more prior disease modifying drugs (P = 0.001), and had a lower DAS-28 (difference −0.6, P < 0.001). CRP and ESR levels were slightly higher in RCTs. The HAQ-Disability Index (HAQ-DI) score was slightly lower in the RCT group. No differences were found in the percentages of included females or RF positivity. Over time, we found a significant decrease of − 0.08 in DAS-28 and a decrease of − 0.04 in HAQ-DI both in patients in RCTs and in patients from registries. Furthermore, ESR and CRP declined over time in RCT patients, but not in patients participating in observational studies. Conclusion There are substantial systematic differences in patient characteristics between RCTs and registries in RA. The efficacy seen in RCTs may not reflect real-world effectiveness. baseline characteristics, randomized controlled trials, observational studies, rituximab, tocilizumab, etanercept, rheumatoid arthritis Rheumatology key messages There are important differences in RA patients regarding the efficacy–effectiveness gap. Randomized controlled trials enrolled RA patients with better prognostic factors, potentially overestimating the treatment effect. Introduction The randomized controlled trial (RCT) is the gold standard for assessing the efficacy of pharmacological treatments and other interventions [1]. The main advantage of random treatment allocation is the high internal validity of estimates of treatment effects. Estimates from RCTs may, however, lack external validity [2] due to their highly standardized design, strict inclusion and exclusion criteria, and fixed treatment regimens that may often be at odds with real world conditions [3, 4]. In health technology assessment it is essential to gauge the effectiveness of drugs in the real world settings where they will be used [5]. Several authors have recommended using non-randomized studies, clinical databases and registry data (i.e. observational studies) to assess whether RCT-based estimates apply to a target population [5–8]. Patient characteristics may differ between RCTs and observational studies, and may modify treatment effects [7]. A treatment may be less effective or more effective depending on age, stage of disease or comorbidities [8–11]. For example, studies comparing treatment effects between RCTs and observational studies in cardiovascular disease showed that patients with acute coronary syndrome included in clinical trials were younger, more likely to be men, and had fewer co-morbidities and risk factors when compared with registry patients [12, 13]. Similar results were found by Ezekowitz and colleagues [14], who compared characteristics of patients with heart failure between RCTs and observational studies. In this context Eichler and colleagues [8] coined the term efficacy–effectiveness gap to describe the gap between treatment effects observed in RCTs and those observed in real world settings. A comparison of baseline characteristics of patients with RA in RCTs and observational studies is lacking. We performed a systematic review extracting baseline characteristics from available RCTs and observational studies in RA. This review was a deliverable of Workpackage 4 of the GetReal project (incorporating real-life data into drug development), a consortium of academia, pharmaceutical companies, health technology assessment agencies, regulators and patient organizations [15]. Using case studies, WP4 developed best practices in evidence synthesis and predictive modelling, with the goal of improving estimates of the real world effectiveness of drugs by incorporating the results of RCTs with other sources of clinical data, including observational data. WP4 obtained access to individual participant data from clinical trials of three widely used biologics, namely etanercept (ETN), rituximab (RTX) and tocilizumab (TCZ), as well as patient registries in RA. Our systematic review thus also focused on ETN, RTX and TCZ. Methods Search strategy We performed two systematic reviews: one literature search was done for observational studies, the other for RCTs. We applied study design search filters from the BMJ Evidence Centre Information Specialists to the EMBASE and MEDLINE databases using Ovid [16]. We performed the search for observational studies on 4 March 2015, and the search for RCTs on 24 April 2015. The detailed search strategies can be found in supplementary Tables S1–S4, available at Rheumatology Online. In addition, we manually searched known registries and screened reference lists of all papers. Inclusion criteria and study selection We included studies of adult patients diagnosed with RA who were treated with RTX, TCZ or ETN. Studies were required to have reported the following outcomes: DAS-28, including CRP (DAS-28-CRP) or ESR (DAS-28-ESR), or HAQ-Disability Index (HAQ-DI) scores. The studies had to include at least 30 patients per study arm. The retrieved titles and abstracts of the identified articles were imported into EppiReviewer 4 [17]. Duplicates across databases were removed, and for each treatment, the latest publication fulfilling the inclusion criteria was used. Each paper was independently assessed by two reviewers (G.K. and N.H. or G.K. and E.D.), based on title and abstract and, if the study was potentially eligible, on the full text of the article. Disagreements were resolved by consensus, after discussion with M.E. or S.R. whenever necessary. Data extraction Data from each included paper were extracted using a standardized form developed for this project. Extracted data covered three areas: first, general data included author, publication year, study design, country, overall number of patients in the study, follow-up time and the main objective of the study; second, treatment data included drug, dose, frequency and route of administration; and third, data on patient characteristics at baseline included number of patients receiving each drug, age, gender, current smoking, disease duration, comorbidities, ESR, CRP, seropositivity for RF or ACPA, DAS-28 and HAQ-DI, switching from another biologic agent to the current drug, number of prior DMARDs and use of corticosteroids and other drugs. We extracted dichotomous data as numbers and percentages. For continuous data, we extracted the mean or median, together with the standard deviation or range (minimum/maximum or interquartile range). Statistical analysis We converted medians and ranges to means (s.d.) using the methods described by Wan et al. [18]. For binary data we used the variance estimator (v) for proportions (p) to derive the standard error: v = p(1 – p). We performed meta-analyses of patient characteristics separately for RCTs and observational studies, overall and by drug. If necessary, we first combined the data from the study arm into a single mean or proportion using fixed-effect meta-analyses. Secondly, we combined the data separately for RCTs and observational studies using random-effects meta-analyses with the Knapp–Hartung adjustment [19]. We used mixed-effects meta-regression analyses to assess the differences in patient characteristics between RCTs and observational studies by including the study design as a dichotomous covariate. We used restricted maximum-likelihood estimation to assess between-study variance (tau-squared) and applied the Knapp–Hartung adjustment. We stratified our main analysis by study type to explore whether the approaches differed in terms of baseline characteristics. In further meta-regression analyses, we included the year of publication of the studies to examine whether patient characteristics of patients included in RCTs or observational studies changed over calendar time. In a sensitivity analysis, we excluded phase IV and pragmatic trials, as reported by the trialists. All analyses were done with the R package metaphor [20]. Results We identified 308 references in our literature search for RCTs and 594 for observational studies, and considered 89 RCTs and 194 observational studies to be potentially eligible (supplementary Figs S1 and S2, available at Rheumatology Online). Fifty-one RCTs and 76 observational studies met our inclusion criteria and were included in the meta-analysis. Study characteristics The eligible studies were published between 1999 and 2015 for RCTs and between 2003 and 2015 for observational studies. Among RCTs, we included 5 phase II studies, 23 phase III studies, 10 phase IV studies and 1 pragmatic trial. For the remaining 12 RCTs we could not retrieve any information on the phase. Observational studies comprised 17 cohort, 28 registry and 31 case series studies. Most observational studies (71; 93.4%) were conducted in a single country whereas almost half of RCTs (25; 49.0%) were multi-country trials, mostly involving European countries. The number of study participants ranged from 70 to 1262 patients for RCTs and from 30 to 8908 for observational studies. Among RCTs, we included 17 TCZ, 10 RTX and 24 ETN trials, and among observational studies, we included 16 TCZ, 28 RTX and 32 ETN studies. Tables 1 and 2 summarize characteristics of RCTs and observational studies. Table 1 Study characteristics of 51 randomized controlled trials Reference  Year  Study design  Country/region  No. of centres  Overall, n  From/to  Drugs analysed  Trial name  Burmester et al. [21]  2014  Phase IIa  NA  NA  1262  NA  TCZ  SUMMACTA  Cohen et al. [22]  2006  Phase IIIa  USA, EU, Canada, Israel  NA  520  NA  RTX  REFLEX  Combe et al. [23]  2006  NA  Europe, Australia  NA  254  NA  ETN    Dougados et al. [24]  2014  Phase IIIb  Europe  NA  556  NA  TCZ  ACT RAY  Emery et al. [25]  2006  Phase IIb  NA  NA  465  NA  RTX    Emery et al. [26]  2010  Phase IIIa  11 countries  102  511  NA  RTX  SERENE  Emery et al. [27]  2008  Phase IV  EU, Latin America, Asia, Australia  NA  542  2004–06  ETN  COMET  Emery et al. [28]  2008  Phase IIIa  USA, EU  NA  499  NA  TCZ  RADIATE  Gabay et al. [29]  2013  Phase IV  15 countries  76  452  NA  TCZ  ADACTA  Genovese et al. [30]  2004  NA  USA  41  244  NA  ETN    Genovese et al. [31]  2008  Phase IIIa  EU, South America, Asia, Australia  18 countries  1220  2005–06  TCZ  TOWARD  Gerlag et al. [32]  2010  Phase IIb  Eastern EU 14 countries  61  482  NA  ETN    Jobanputra et al. [33]  2012  Pragmatic  UK  NA  125  NA  ETN  RED SEA  Jones et al. [34]  2010  Phase III  USA, Canada, Israel  NA  673  NA  TCZ  AMBITION  Kameda et al. [35]  2010  Phase IV  Japan  NA  151  2005–07  ETN  JESMER  Keystone et al. [36]  2004  NA  USA, Canada  48  476  NA  ETN    Keystone et al. [37]  2008  Phase III  USA, EU, Canada, Israel  114    NA  RTX  REFLEX  Kim et al. [38]  2012  Phase IV  Asia-Pacific  31  300  2007–09  ETN  APPEAL  Kivitz et al. [39]  2014  Phase IIIa  Not further spec.  NA  656  NA  TCZ  BREVACTA  Klareskog et al. [40]  2004  NA  EU  NA  682  2000–01  ETN  TEMPO  Kosinski et al. [41]  2002  NA  Not further spec.  NA  424  NA  ETN    Kremer et al. [42]  2011  Phase IIIa  14 countries  121  1196  2004–07  TCZ  LITHE  Machado et al. [43]  2014  Phase IV  Latin America  30  570  2009–11  ETN    Maini et al. [44]  2006  Phase II  EU  57  359  2001–02  TCZ  CHARISMA  Mariette et al. [45]  2014  Phase III  France  44  234  2006–11  RTX  SMART  McInnes et al. [46]  2015  Phase III  USA, Canada, UK  34  132  2007–08  TCZ  MEASURE  Mease et al. [47]  2008  Phase IIb  Not further spec.  95  367  NA  RTX  DANCER  Mease et al. [48]  2010  Phase III  USA  143  475  NA  RTX  SUNRISE  Moreland et al. [49]  1999  Phase III  USA  13  234  NA  ETN    Moreland et al. [50]  2012  Phase IV  USA, Netherland  44  755  NA  ETN  TEAR  Nam et al. [51]  2014  Phase IIIa  England  NA  132  NA  ETN  EMPIRE  Nishimoto et al. [52]  2004  NA  Japan  NA  164  2001–01  TCZ    Nishimoto et al. [53]  2007  Phase III  Japan  28  306  NA  TCZ  SAMURAI  Nishimoto et al. [54]  2009  Phase III  Japan  25  127  2004–05  TCZ  SATORI  O’Dell et al. [55]  2013  NA  USA, Canada  20  353  2007–10  ETN  RACAT  Ogata et al. [56]  2014  Phase IIIa  Japan  NA  348  NA  TCZ  MUSASHI  Pavelka et al. [57]  2014  Phase IV  EU, Latin America, Asia  80  495  2008–09  ETN  PRESERVE  Pope et al. [58]  2014  Phase IV  Canada  27  258  NA  ETN  CAMEO  Raffeiner et al. [59]  2015  NA  Italy  1  524  2006–12  ETN    Rigby et al. [60]  2011  Phase IIIa  Not further spec.  NA  748  NA  RTX  IMAGE  Rubbert-Roth et al. [61]  2010  Phase III  18 countries  81  378  NA  RTX  MIRROR  Smolen et al. [62]  2008  Phase III  17 countries  73  623  2005–06  TCZ  OPTION  Smolen et al. [63]  2013  Phase IV  EU, Latin America, Asia, Australia   80  834  2008–09  ETN  PRESERVE  Strand et al. [64]  2006  NA  Not further spec.  NA  161  NA  RTX    Tada et al. [65]  2012  NA  Japan  7  70  2008–10  ETN  PRECEPT  Takeuchi et al. [66]  2013  Phase III  Japan  40  550  NA  ETN    van Riel et al. [67]  2006  NA  EU  60  315  2003–04  ETN  ADORE  Weinblatt et al. [68]  1999  NA  Not further spec.  NA  89  NA  ETN    Weinblatt et al. [69]  2008  Phase IV  USA  63  200  NA  ETN    Weinblatt et al. [70]  2013  Phase IIIb  USA  NA  886  2009–10  TCZ    Yazici et al. [71]  2012  Phase IIIb  Not further spec.  NA  619  NA  TCZ  ROSE  Reference  Year  Study design  Country/region  No. of centres  Overall, n  From/to  Drugs analysed  Trial name  Burmester et al. [21]  2014  Phase IIa  NA  NA  1262  NA  TCZ  SUMMACTA  Cohen et al. [22]  2006  Phase IIIa  USA, EU, Canada, Israel  NA  520  NA  RTX  REFLEX  Combe et al. [23]  2006  NA  Europe, Australia  NA  254  NA  ETN    Dougados et al. [24]  2014  Phase IIIb  Europe  NA  556  NA  TCZ  ACT RAY  Emery et al. [25]  2006  Phase IIb  NA  NA  465  NA  RTX    Emery et al. [26]  2010  Phase IIIa  11 countries  102  511  NA  RTX  SERENE  Emery et al. [27]  2008  Phase IV  EU, Latin America, Asia, Australia  NA  542  2004–06  ETN  COMET  Emery et al. [28]  2008  Phase IIIa  USA, EU  NA  499  NA  TCZ  RADIATE  Gabay et al. [29]  2013  Phase IV  15 countries  76  452  NA  TCZ  ADACTA  Genovese et al. [30]  2004  NA  USA  41  244  NA  ETN    Genovese et al. [31]  2008  Phase IIIa  EU, South America, Asia, Australia  18 countries  1220  2005–06  TCZ  TOWARD  Gerlag et al. [32]  2010  Phase IIb  Eastern EU 14 countries  61  482  NA  ETN    Jobanputra et al. [33]  2012  Pragmatic  UK  NA  125  NA  ETN  RED SEA  Jones et al. [34]  2010  Phase III  USA, Canada, Israel  NA  673  NA  TCZ  AMBITION  Kameda et al. [35]  2010  Phase IV  Japan  NA  151  2005–07  ETN  JESMER  Keystone et al. [36]  2004  NA  USA, Canada  48  476  NA  ETN    Keystone et al. [37]  2008  Phase III  USA, EU, Canada, Israel  114    NA  RTX  REFLEX  Kim et al. [38]  2012  Phase IV  Asia-Pacific  31  300  2007–09  ETN  APPEAL  Kivitz et al. [39]  2014  Phase IIIa  Not further spec.  NA  656  NA  TCZ  BREVACTA  Klareskog et al. [40]  2004  NA  EU  NA  682  2000–01  ETN  TEMPO  Kosinski et al. [41]  2002  NA  Not further spec.  NA  424  NA  ETN    Kremer et al. [42]  2011  Phase IIIa  14 countries  121  1196  2004–07  TCZ  LITHE  Machado et al. [43]  2014  Phase IV  Latin America  30  570  2009–11  ETN    Maini et al. [44]  2006  Phase II  EU  57  359  2001–02  TCZ  CHARISMA  Mariette et al. [45]  2014  Phase III  France  44  234  2006–11  RTX  SMART  McInnes et al. [46]  2015  Phase III  USA, Canada, UK  34  132  2007–08  TCZ  MEASURE  Mease et al. [47]  2008  Phase IIb  Not further spec.  95  367  NA  RTX  DANCER  Mease et al. [48]  2010  Phase III  USA  143  475  NA  RTX  SUNRISE  Moreland et al. [49]  1999  Phase III  USA  13  234  NA  ETN    Moreland et al. [50]  2012  Phase IV  USA, Netherland  44  755  NA  ETN  TEAR  Nam et al. [51]  2014  Phase IIIa  England  NA  132  NA  ETN  EMPIRE  Nishimoto et al. [52]  2004  NA  Japan  NA  164  2001–01  TCZ    Nishimoto et al. [53]  2007  Phase III  Japan  28  306  NA  TCZ  SAMURAI  Nishimoto et al. [54]  2009  Phase III  Japan  25  127  2004–05  TCZ  SATORI  O’Dell et al. [55]  2013  NA  USA, Canada  20  353  2007–10  ETN  RACAT  Ogata et al. [56]  2014  Phase IIIa  Japan  NA  348  NA  TCZ  MUSASHI  Pavelka et al. [57]  2014  Phase IV  EU, Latin America, Asia  80  495  2008–09  ETN  PRESERVE  Pope et al. [58]  2014  Phase IV  Canada  27  258  NA  ETN  CAMEO  Raffeiner et al. [59]  2015  NA  Italy  1  524  2006–12  ETN    Rigby et al. [60]  2011  Phase IIIa  Not further spec.  NA  748  NA  RTX  IMAGE  Rubbert-Roth et al. [61]  2010  Phase III  18 countries  81  378  NA  RTX  MIRROR  Smolen et al. [62]  2008  Phase III  17 countries  73  623  2005–06  TCZ  OPTION  Smolen et al. [63]  2013  Phase IV  EU, Latin America, Asia, Australia   80  834  2008–09  ETN  PRESERVE  Strand et al. [64]  2006  NA  Not further spec.  NA  161  NA  RTX    Tada et al. [65]  2012  NA  Japan  7  70  2008–10  ETN  PRECEPT  Takeuchi et al. [66]  2013  Phase III  Japan  40  550  NA  ETN    van Riel et al. [67]  2006  NA  EU  60  315  2003–04  ETN  ADORE  Weinblatt et al. [68]  1999  NA  Not further spec.  NA  89  NA  ETN    Weinblatt et al. [69]  2008  Phase IV  USA  63  200  NA  ETN    Weinblatt et al. [70]  2013  Phase IIIb  USA  NA  886  2009–10  TCZ    Yazici et al. [71]  2012  Phase IIIb  Not further spec.  NA  619  NA  TCZ  ROSE  TCZ: Tocilizumab; RTX: Rituximab; ETN: Etanercept; NA: not available. Table 2 Study characteristics of 76 observational studies References  Year  Study design (Cohort, case series, registry)  Country/ Region  Overall, n  Calender years  Drugs analysed  Name registry  Ajeganova et al. [72]  2011  Cohort  Sweden  215  2000–07  RTX    Atzeni et al. [73]  2012  Registry  Italy  2769  1999  ETN    Backhaus et al. [74]  2015  Cohort  Germany  1603  2010–11  TCZ    Bingham et al. [75]  2009  Case series  CAN/USA  201  NA  ETN    Blom et al. [76]  2011  Registry  Netherland  154  1997–2010  RTX  DREAM  Bobbio-Pallavicini et al. [77]  2007  Cohort  Italy  132  NA  ETN    Bokarewa et al. [78]  2007  Case series  Sweden  48  2002–05  RTX    Bykerk et al. [79]  2015  Cohort  25 countries  1681  2008–10  TCZ    Cannon et al. [80]  2014  Registry  USA  1767  2003–11  ETN  VARA  Carter et al. [81]  2012  Case series  USA  64  2008–11  RTX    Chatzidionysiou et al. [82]  2015  Registry  Sweden  7052  2005–12  ETN  ARTIS  Chen et al. [83]  2013  Case series  Taiwan  56  NA  RTX    Conigliaro et al. [84]  2014  Case series  Italy  82  NA  ETN    Coulthard et al. [85]  2011  Registry  UK  1102  NA  ETN  BRAGGSS  De Keyser et al. [86]  2014  Registry  Belgium  649  2006–11  RTX  MIRA  Diaz-Torne et al. [87]  2014  Case series  Spain  33  NA  RTX    Dougados et al. [88]  2012  Case series  France  120  NA  ETN    Einarsson et al. [89]  2015  Registry  Sweden  2416  1999–2009  ETN    Emery et al. [90]  2014  Cohort  11 countries  1312  NA  RTX    Enevold et al. [91]  2014  Case series  Denmark  79  NA  TCZ    Fabris et al. [92]  2013  Case series  Italy, UK  152  NA  RTX    Feltelius et al. [93]  2005  Registry  Sweden  1073  1999–2005  ETN    Fernández-Nebro et al. [94]  2007  Cohort  Spain  161  1999–2006  ETN    Finckh et al. [95]  2006  Registry  Switzerland  1198  1998–2004  ETN  SCQM  Finckh et al. [96]  2010  Registry  Switzerland  318  1998–2008  RTX  SCQM  Fortunet et al. [97]  2014  Cohort  France  220  2009–11  ETN    Gardette et al. [98]  2014  Cohort  France  114  NA  RTX    Gibofsky et al. [99]  2011  Registry  USA  5032  2002–03  ETN    Gomez-Reino et al. [100]  2012  Cohort  Spain  1124  2006  RTX  MIRAR  Greenberg et al. [101]  2012  Registry  USA  2242  NA  ETN  CORONNA  Guis et al. [102]  2007  Case series  France  86  2000–05  ETN    Harrold et al. [103]  2015  Registry  USA  615  2006–11  RTX  CORONNA  Hasan et al. [104]  2012  Case series  Kuwait  45  NA  RTX    Hetland et al. [105]  2010  Registry  Denmark  8074  2000–09  ETN  DANBIO  Hirabayashi et al. [106]  2013  Case series  Japan  285  2008–09  TCZ    Hirata et al. [107]  2014  Cohort  Japan  147  2003–10  ETN    Hyrich et al. [108]  2006  Registry  UK  2879  2001–04  ETN  BSRBR  Izumi et al. [109]  2015  Cohort  Japan  115  2008–11  TCZ  KEIO-TCZ  Jamnitski et al. [110]  2010  Case series  Netherland  292  2004–08  ETN    Jančić et al. [111]  2013  Case series  Serbia  82  NA  ETN    Kaneko et al. [112]  2012  Case series  Japan  31  2008–08  TCZ    Kawashiri et al. [113]  2010  Case series  Japan  45  NA  ETN    Kawashiri et al. [114]  2011  Cohort  Japan  32  NA  TCZ    Kekow et al. [115]  2012  Cohort  Germany  196  NA  RTX    Kojima et al. [116]  2015  Registry  Japan  2176  2008–09  TCZ  TBCR  Kume et al. [117]  2011  Case series  Japan  34  2006–09  TCZ    Kume et al. [118]  2014  Case series  Japan  86  NA  TCZ    Laas et al. [119]  2008  Case series  Finland  91  1999–2003  ETN    Leffers et al. [120]  2011  Registry  Denmark  328  2010–11  TCZ  DANBIO  Listing et al. [121]  2006  Registry  Germany  1083  2001–03  ETN  RABBIT  Listing et al. [122]  2013  Registry  Germany  8908  2001–11  RTX  RABBIT  Marchesoni et al. [123]  2009  Registry  Italy  1114  1999  ETN  LOHREN  Mazilu et al. [124]  2014  Case series  Romania  74  2010  RTX    McGonagle et al. [125]  2008  Case series  UK  39  2004–07  RTX    Montes et al. [126]  2014  Cohort  Spain, Greece  429  2000–10  ETN    Nakashima et al. [127]  2014  Registry  Japan  236  2008  TCZ  FRAB  Narváez et al. [128]  2011  Case series  Spain  108  2007–09  RTX    Payet et al. [129]  2014  Registry  France  1709  NA  RTX  AIR  Perera et al. [130]  2006  Case series  Australia  50  NA  ETN    Richez et al. [131]  2012  Cohort  France  45  NA  TCZ    Scirè et al. [132]  2013  Registry  Italy  2640  2007–12  ETN  MonitorNet  Sebastiani et al. [133]  2014  Registry  Italy  338  1999  RTX  GISEA  Solau-Gervais et al. [134]  2012  Case series  France  108  2005–08  RTX    Soliman et al. [135]  2012  Registry  UK  646  2010  RTX  BSRBR  Song et al. [136]  2013  Cohort  Japan  93  2008  TCZ    Su et al. [137]  2009  Case series  Taiwan  94  2004–07  ETN    Takeuchi et al. [138]  2011  Cohort  Japan  232  2008–09  TCZ  REACTION  Thurlings et al. [139]  2008  Case series  Netherland  30  NA  RTX    Valleala et al. [140]  2009  Case series  Finland  81  2005–08  RTX    Valleala et al. [141]  2015  Case series  Finland  151  2005–11  RTX    Van Dartel et al. [142]  2013  Registry  Netherland  2356  2003  ETN  DREAM  van Vollenhoven et al. [143]  2003  Registry  Sweden  97  NA  ETN  STURE  Váncsa et al. [144]  2013  Case series  Hungary  77  NA  RTX    Wakabayashi et al. [145]  2011  Case series  Japan  107  2008–10  TCZ    Wendler et al. [146]  2014  Case series  Germany  2484  NA  RTX    Zink et al. [147]  2006  Registry  Germany  1458  2001–03  ETN  RABBIT  References  Year  Study design (Cohort, case series, registry)  Country/ Region  Overall, n  Calender years  Drugs analysed  Name registry  Ajeganova et al. [72]  2011  Cohort  Sweden  215  2000–07  RTX    Atzeni et al. [73]  2012  Registry  Italy  2769  1999  ETN    Backhaus et al. [74]  2015  Cohort  Germany  1603  2010–11  TCZ    Bingham et al. [75]  2009  Case series  CAN/USA  201  NA  ETN    Blom et al. [76]  2011  Registry  Netherland  154  1997–2010  RTX  DREAM  Bobbio-Pallavicini et al. [77]  2007  Cohort  Italy  132  NA  ETN    Bokarewa et al. [78]  2007  Case series  Sweden  48  2002–05  RTX    Bykerk et al. [79]  2015  Cohort  25 countries  1681  2008–10  TCZ    Cannon et al. [80]  2014  Registry  USA  1767  2003–11  ETN  VARA  Carter et al. [81]  2012  Case series  USA  64  2008–11  RTX    Chatzidionysiou et al. [82]  2015  Registry  Sweden  7052  2005–12  ETN  ARTIS  Chen et al. [83]  2013  Case series  Taiwan  56  NA  RTX    Conigliaro et al. [84]  2014  Case series  Italy  82  NA  ETN    Coulthard et al. [85]  2011  Registry  UK  1102  NA  ETN  BRAGGSS  De Keyser et al. [86]  2014  Registry  Belgium  649  2006–11  RTX  MIRA  Diaz-Torne et al. [87]  2014  Case series  Spain  33  NA  RTX    Dougados et al. [88]  2012  Case series  France  120  NA  ETN    Einarsson et al. [89]  2015  Registry  Sweden  2416  1999–2009  ETN    Emery et al. [90]  2014  Cohort  11 countries  1312  NA  RTX    Enevold et al. [91]  2014  Case series  Denmark  79  NA  TCZ    Fabris et al. [92]  2013  Case series  Italy, UK  152  NA  RTX    Feltelius et al. [93]  2005  Registry  Sweden  1073  1999–2005  ETN    Fernández-Nebro et al. [94]  2007  Cohort  Spain  161  1999–2006  ETN    Finckh et al. [95]  2006  Registry  Switzerland  1198  1998–2004  ETN  SCQM  Finckh et al. [96]  2010  Registry  Switzerland  318  1998–2008  RTX  SCQM  Fortunet et al. [97]  2014  Cohort  France  220  2009–11  ETN    Gardette et al. [98]  2014  Cohort  France  114  NA  RTX    Gibofsky et al. [99]  2011  Registry  USA  5032  2002–03  ETN    Gomez-Reino et al. [100]  2012  Cohort  Spain  1124  2006  RTX  MIRAR  Greenberg et al. [101]  2012  Registry  USA  2242  NA  ETN  CORONNA  Guis et al. [102]  2007  Case series  France  86  2000–05  ETN    Harrold et al. [103]  2015  Registry  USA  615  2006–11  RTX  CORONNA  Hasan et al. [104]  2012  Case series  Kuwait  45  NA  RTX    Hetland et al. [105]  2010  Registry  Denmark  8074  2000–09  ETN  DANBIO  Hirabayashi et al. [106]  2013  Case series  Japan  285  2008–09  TCZ    Hirata et al. [107]  2014  Cohort  Japan  147  2003–10  ETN    Hyrich et al. [108]  2006  Registry  UK  2879  2001–04  ETN  BSRBR  Izumi et al. [109]  2015  Cohort  Japan  115  2008–11  TCZ  KEIO-TCZ  Jamnitski et al. [110]  2010  Case series  Netherland  292  2004–08  ETN    Jančić et al. [111]  2013  Case series  Serbia  82  NA  ETN    Kaneko et al. [112]  2012  Case series  Japan  31  2008–08  TCZ    Kawashiri et al. [113]  2010  Case series  Japan  45  NA  ETN    Kawashiri et al. [114]  2011  Cohort  Japan  32  NA  TCZ    Kekow et al. [115]  2012  Cohort  Germany  196  NA  RTX    Kojima et al. [116]  2015  Registry  Japan  2176  2008–09  TCZ  TBCR  Kume et al. [117]  2011  Case series  Japan  34  2006–09  TCZ    Kume et al. [118]  2014  Case series  Japan  86  NA  TCZ    Laas et al. [119]  2008  Case series  Finland  91  1999–2003  ETN    Leffers et al. [120]  2011  Registry  Denmark  328  2010–11  TCZ  DANBIO  Listing et al. [121]  2006  Registry  Germany  1083  2001–03  ETN  RABBIT  Listing et al. [122]  2013  Registry  Germany  8908  2001–11  RTX  RABBIT  Marchesoni et al. [123]  2009  Registry  Italy  1114  1999  ETN  LOHREN  Mazilu et al. [124]  2014  Case series  Romania  74  2010  RTX    McGonagle et al. [125]  2008  Case series  UK  39  2004–07  RTX    Montes et al. [126]  2014  Cohort  Spain, Greece  429  2000–10  ETN    Nakashima et al. [127]  2014  Registry  Japan  236  2008  TCZ  FRAB  Narváez et al. [128]  2011  Case series  Spain  108  2007–09  RTX    Payet et al. [129]  2014  Registry  France  1709  NA  RTX  AIR  Perera et al. [130]  2006  Case series  Australia  50  NA  ETN    Richez et al. [131]  2012  Cohort  France  45  NA  TCZ    Scirè et al. [132]  2013  Registry  Italy  2640  2007–12  ETN  MonitorNet  Sebastiani et al. [133]  2014  Registry  Italy  338  1999  RTX  GISEA  Solau-Gervais et al. [134]  2012  Case series  France  108  2005–08  RTX    Soliman et al. [135]  2012  Registry  UK  646  2010  RTX  BSRBR  Song et al. [136]  2013  Cohort  Japan  93  2008  TCZ    Su et al. [137]  2009  Case series  Taiwan  94  2004–07  ETN    Takeuchi et al. [138]  2011  Cohort  Japan  232  2008–09  TCZ  REACTION  Thurlings et al. [139]  2008  Case series  Netherland  30  NA  RTX    Valleala et al. [140]  2009  Case series  Finland  81  2005–08  RTX    Valleala et al. [141]  2015  Case series  Finland  151  2005–11  RTX    Van Dartel et al. [142]  2013  Registry  Netherland  2356  2003  ETN  DREAM  van Vollenhoven et al. [143]  2003  Registry  Sweden  97  NA  ETN  STURE  Váncsa et al. [144]  2013  Case series  Hungary  77  NA  RTX    Wakabayashi et al. [145]  2011  Case series  Japan  107  2008–10  TCZ    Wendler et al. [146]  2014  Case series  Germany  2484  NA  RTX    Zink et al. [147]  2006  Registry  Germany  1458  2001–03  ETN  RABBIT  TCZ: Tocilizumab; RTX: Rituximab; ETN: Etanercept; NA: not available. Comparison of patient characteristics Compared with patients participating in RCTs, those from observational studies were on average 3.0 years older (P < 0.001), suffered from RA for 3.1 years longer (P < 0.001) and had 1.6 more prior DMARDs (P = 0.001; Fig. 1). Patients in RCTs had higher disease activity: the DAS-28 was 0.6 points higher in RCT than in observational studies (P < 0.001; Fig. 2). CRP and ESR levels were also slightly higher in RCTs, but differences failed to reach conventional levels of statistical significance (Fig. 2). Similarly, there was little evidence for any difference between HAQ-DI scores, RF positivity or the proportion of women participating in the studies. Fig. 1 View largeDownload slide Comparison between randomized controlled trials and observational studies for age, gender, disease duration and number of prior DMARDs RCT: randomized controlled trial; OBS: observational study. Fig. 1 View largeDownload slide Comparison between randomized controlled trials and observational studies for age, gender, disease duration and number of prior DMARDs RCT: randomized controlled trial; OBS: observational study. Fig. 2 View largeDownload slide Comparison between randomized controlled trials and observational studies: DAS-28, HAQ, CRP, ESR and RF positivity RCT: randomized controlled trial; OBS: observational study. Fig. 2 View largeDownload slide Comparison between randomized controlled trials and observational studies: DAS-28, HAQ, CRP, ESR and RF positivity RCT: randomized controlled trial; OBS: observational study. Analyses stratified by drug showed that differences generally were in the same direction for the three drugs, but tended to be more pronounced for TCZ and RTX than for ETN (Figs 1 and 2). Patients on TCZ were 3.9 years older in observational studies than in RCTs (P < 0.001), their disease duration was 2.4 years longer (P = 0.06), they had been exposed on average to 1.4 additional DMARDs (P = 0.346) and the DAS-28 was 1.2 points lower than in RCTs (P < 0.001). Similarly, patients on RTX were 3.3 years older (P = 0.013), their disease duration was 2.6 years longer (P = 0.05), they had been exposed to 1.8 more DMARDs (P = 0.083) and the DAS-28 was 1.1 points (P < 0.001) lower in observational studies than in RCTs. Patients on ETN were 2.4 years older in observational studies than in RCTs (P = 0.017), their disease duration was 3.4 years longer (P < 0.001) and they had been exposed to 1.6 more DMARDs (P = 0.056). There was no difference in DAS-28 (0 points, P = 0.86). Analyses stratified by study type gave similar results compared with the main analyses (supplementary Figs S3–S11, available at Rheumatology Online, forest plots for all baseline characteristics). Trends over calendar time We found that DAS-28 declined over calendar time both in RCTs (slope of −0.08, P = 0.026) and in observational studies (slope of −0.08, P = 0.002) (Fig. 3). HAQ-DI declined slightly over calendar time both in RCTs (slope of −0.04, P = 0.004) and in observational studies (slope of −0.04, P = 0.063) (Fig. 4). Furthermore, ESR and CRP declined over calendar time in RCTs (slope of −1.69, P = 0.009 for ESR and slope of −1.68, P = 0.001 for CRP), but not significantly so in observational studies (supplementary Figs S16-S17). There was little evidence for changes in baseline patient characteristics over time for any of the other socio-demographic or clinical characteristics (supplementary Figs S12–S15, available at Rheumatology Online). Fig. 3 View largeDownload slide Comparison of DAS-28 between randomized controlled trials and observational studies plotted over time Fig. 3 View largeDownload slide Comparison of DAS-28 between randomized controlled trials and observational studies plotted over time Fig. 4 View largeDownload slide Comparison of HAQ disability index between randomized controlled trials and observational studies plotted over time Fig. 4 View largeDownload slide Comparison of HAQ disability index between randomized controlled trials and observational studies plotted over time Sensitivity analysis In a sensitivity analysis we excluded 10 phase IV trials and 1 pragmatic trial. Ten of the excluded trials included patients on ETN, while one trial included patients on TCZ. There was no substantial change compared with the main analyses, except that ESR increased from 46.3 to 49.4 mm/h in RCTs, which is significantly higher than in observational studies (P = 0.004). Discussion In this study of the characteristics of patients with RA we found clinically relevant differences between RCTs and observational studies in RA. Compared with RCTs, RA patients in observational studies were older, disease duration was longer, a higher number of different DMARDs were administered before starting biologic treatment and disease activity was lower at baseline. Over time, baseline DAS-28 and HAQ-DI declined in patients included in RCTs but not in patients from observational databases. Differences between real-world and trial data are important, especially when making decisions in everyday clinical practice. Eichler and colleagues [8] argue that the efficacy–effectiveness gap is due to variability in drug response caused by biological and behavioural factors. Biological factors can be separated into genetic and non-genetic factors, which in turn can be further divided into intrinsic and extrinsic factors. Intrinsic factors are characteristics of the person such as age, sex, body weight, comorbidities and baseline severity of disease, whereas extrinsic factors relate to lifestyle factors such as smoking [8]. Kirsch and colleagues studied all available data of clinical trials submitted to the Food and Drug Administration for the licensing of four new-generation antidepressants [9]. They found a relationship between initial disease severity and anti-depressant efficacy, an association that was due to decreased responsiveness to placebo among very severely depressed patients as opposed to increased responsiveness to medication. Similarly, in patients with RA a high DAS-28 score at baseline is a good predictor of a decline in the DAS-28 following treatment with ETN [148] and TCZ [120]. Our review showed higher DAS-28 scores in patients enrolled in RCTs and we can therefore speculate that the response was better in trial patients than in observational studies. In other words, the treatment effect in everyday clinical praxis might be smaller than that in RCTs. High numbers of prior DMARDs and higher age were associated with decreased response rates in patients with ETN [149]. Older age was also associated with decreased response rate in age with TCZ [150]; these two baseline characteristics differed significantly between RCTs and observational studies in our analysis. Predictive factors for better response to biologics were male gender (in ETN-treated patients [149]), non-smokers (ETN [149]), RF positivity (RTX and TC [151]) and low HAQ-DI (TCZ [120] and RTX [149]). For all these factors, if data were available, we found no difference between RCTs and observational studies. In our time trend analysis, we saw a decrease in baseline DAS-28 and HAQ-DI in RCTs over the past 10 years. A decrease in DAS-28 has also been shown for other biologics such as infliximab [152]. These findings support the results of an inception cohort study published 10 years ago, where the trend was thought to be caused by a more aggressive treatment strategy [153]. In a sensitivity analysis we excluded 10 phase IV clinical trials and one pragmatic trial. Interestingly, we found no difference compared with the main results described above. In particular, the results in the ETN group where 10 trials were excluded remained virtually the same. This may call into question the notion that phase IV trials accurately represent real-world scenarios, and that their estimates of comparative effectiveness are closer to those of observational studies. We acknowledge that the number of phase IV and pragmatic trials was small and that the results from our sensitivity analysis should be interpreted with caution. Our review has several strengths and weaknesses. Strengths are that the review was based on a systematic literature search, and study selection and screening were performed independently by two authors. Data extraction was performed by one person and checked by a second. Our search was comprehensive, but we included only English-language studies. Also, we did not look into reports by the European Medicines Agency or Food and Drug Administration. Data for each biologic may have been assessed at different time points in each registry. For instance, in the Rabbit registry, we used data for ETN from 2006, whereas data for RTX was assessed from a publication in 2013. We cannot exclude the possibility that some of the included patients were counted twice, because patients might have switched their treatment from ETN to RTX. However, in the absence of individual patient data we can only speculate the percentage of patients who switched treatment regimens. Overall, 7 of the 28 included registries had more than one publication, and it is therefore possible that patients were counted twice. Since we did not assess outcomes, we did not apply any risk of bias tool or similar instrument to examine the quality of studies. Our main interest was the characteristics of patients included in RCTs and observational studies and it is therefore unlikely that the comparison was distorted by publication or other selection bias. We transformed median values into mean values. This might lead to bias in the aggregated mean if the data summarized by the median were clearly not normally distributed. Since we transformed only about 8% of the values provided in the RCTs and only about 17% of the values from the observational studies, any bias introduced is likely small. Several relevant variables were poorly reported: concomitant MTX use, concomitant DMARD use, percentage of smokers (reported in only one RCT), comorbidities and ACPA positivity. These variables were therefore not included in our analyses, despite their potential relevance in the context of generalizing results from RCTs to real world settings. Clearly, more work is required on how best to narrow the efficacy–effectiveness gap. In phase IV and pragmatic trials, inclusion and exclusion criteria need to be widened to reflect the real world. The baseline characteristics of patients included in these trials should better reflect what we found in observational studies. In addition, evidence synthesis and modelling approaches should be used to combine data from both RCT and observational studies to generate real-world evidence [15]. In summary, we found important differences between RA patients included in RCTs as compared with observational studies; in particular, patients with better prognostic factors were included in the RCTs, leading to potential overestimation of the treatment effect. More research is needed to overcome this efficacy–effectiveness gap in RA to generate real-world evidence. Funding: The research leading to these results was conducted as part of the GetReal consortium. For further information please refer to www.imi–getreal.eu. This paper only reflects the personal views of the stated authors. The work leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115546, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007‐ 2013) and European Federation of Pharmaceutical Industries and Associations companies in kind contribution. In addition as a special form of the IMI JU grant Eva-Maria Didden received a direct financial contribution from Boehringer Ingelheim. 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Rheumatoid arthritis patients treated in trial and real world settings: comparison of randomized trials with registries

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Oxford University Press
Copyright
© The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
1462-0324
eISSN
1462-0332
D.O.I.
10.1093/rheumatology/kex394
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See Article on Publisher Site

Abstract

Abstract Objective To investigate whether patients with RA enrolled in randomized controlled trials (RCTs) and observational studies may differ in terms of characteristics that could modify treatment effects, leading to an efficacy–effectiveness gap. Methods We conducted systematic literature reviews to identify RCTs and observational studies with RA, treated with rituximab, tocilizumab or etanercept. We extracted baseline characteristics and compared the data of RCTs and observational studies using fixed-effects meta-analyses for the RCTs and random-effects meta-analyses for the observational studies. We also assessed whether the baseline characteristics changed over time. Results Compared with patients enrolled in RCTs, those from observational studies were on average 3.0 years older (P < 0.001), suffered from RA for 3.1 years longer (P < 0.001), had 1.6 more prior disease modifying drugs (P = 0.001), and had a lower DAS-28 (difference −0.6, P < 0.001). CRP and ESR levels were slightly higher in RCTs. The HAQ-Disability Index (HAQ-DI) score was slightly lower in the RCT group. No differences were found in the percentages of included females or RF positivity. Over time, we found a significant decrease of − 0.08 in DAS-28 and a decrease of − 0.04 in HAQ-DI both in patients in RCTs and in patients from registries. Furthermore, ESR and CRP declined over time in RCT patients, but not in patients participating in observational studies. Conclusion There are substantial systematic differences in patient characteristics between RCTs and registries in RA. The efficacy seen in RCTs may not reflect real-world effectiveness. baseline characteristics, randomized controlled trials, observational studies, rituximab, tocilizumab, etanercept, rheumatoid arthritis Rheumatology key messages There are important differences in RA patients regarding the efficacy–effectiveness gap. Randomized controlled trials enrolled RA patients with better prognostic factors, potentially overestimating the treatment effect. Introduction The randomized controlled trial (RCT) is the gold standard for assessing the efficacy of pharmacological treatments and other interventions [1]. The main advantage of random treatment allocation is the high internal validity of estimates of treatment effects. Estimates from RCTs may, however, lack external validity [2] due to their highly standardized design, strict inclusion and exclusion criteria, and fixed treatment regimens that may often be at odds with real world conditions [3, 4]. In health technology assessment it is essential to gauge the effectiveness of drugs in the real world settings where they will be used [5]. Several authors have recommended using non-randomized studies, clinical databases and registry data (i.e. observational studies) to assess whether RCT-based estimates apply to a target population [5–8]. Patient characteristics may differ between RCTs and observational studies, and may modify treatment effects [7]. A treatment may be less effective or more effective depending on age, stage of disease or comorbidities [8–11]. For example, studies comparing treatment effects between RCTs and observational studies in cardiovascular disease showed that patients with acute coronary syndrome included in clinical trials were younger, more likely to be men, and had fewer co-morbidities and risk factors when compared with registry patients [12, 13]. Similar results were found by Ezekowitz and colleagues [14], who compared characteristics of patients with heart failure between RCTs and observational studies. In this context Eichler and colleagues [8] coined the term efficacy–effectiveness gap to describe the gap between treatment effects observed in RCTs and those observed in real world settings. A comparison of baseline characteristics of patients with RA in RCTs and observational studies is lacking. We performed a systematic review extracting baseline characteristics from available RCTs and observational studies in RA. This review was a deliverable of Workpackage 4 of the GetReal project (incorporating real-life data into drug development), a consortium of academia, pharmaceutical companies, health technology assessment agencies, regulators and patient organizations [15]. Using case studies, WP4 developed best practices in evidence synthesis and predictive modelling, with the goal of improving estimates of the real world effectiveness of drugs by incorporating the results of RCTs with other sources of clinical data, including observational data. WP4 obtained access to individual participant data from clinical trials of three widely used biologics, namely etanercept (ETN), rituximab (RTX) and tocilizumab (TCZ), as well as patient registries in RA. Our systematic review thus also focused on ETN, RTX and TCZ. Methods Search strategy We performed two systematic reviews: one literature search was done for observational studies, the other for RCTs. We applied study design search filters from the BMJ Evidence Centre Information Specialists to the EMBASE and MEDLINE databases using Ovid [16]. We performed the search for observational studies on 4 March 2015, and the search for RCTs on 24 April 2015. The detailed search strategies can be found in supplementary Tables S1–S4, available at Rheumatology Online. In addition, we manually searched known registries and screened reference lists of all papers. Inclusion criteria and study selection We included studies of adult patients diagnosed with RA who were treated with RTX, TCZ or ETN. Studies were required to have reported the following outcomes: DAS-28, including CRP (DAS-28-CRP) or ESR (DAS-28-ESR), or HAQ-Disability Index (HAQ-DI) scores. The studies had to include at least 30 patients per study arm. The retrieved titles and abstracts of the identified articles were imported into EppiReviewer 4 [17]. Duplicates across databases were removed, and for each treatment, the latest publication fulfilling the inclusion criteria was used. Each paper was independently assessed by two reviewers (G.K. and N.H. or G.K. and E.D.), based on title and abstract and, if the study was potentially eligible, on the full text of the article. Disagreements were resolved by consensus, after discussion with M.E. or S.R. whenever necessary. Data extraction Data from each included paper were extracted using a standardized form developed for this project. Extracted data covered three areas: first, general data included author, publication year, study design, country, overall number of patients in the study, follow-up time and the main objective of the study; second, treatment data included drug, dose, frequency and route of administration; and third, data on patient characteristics at baseline included number of patients receiving each drug, age, gender, current smoking, disease duration, comorbidities, ESR, CRP, seropositivity for RF or ACPA, DAS-28 and HAQ-DI, switching from another biologic agent to the current drug, number of prior DMARDs and use of corticosteroids and other drugs. We extracted dichotomous data as numbers and percentages. For continuous data, we extracted the mean or median, together with the standard deviation or range (minimum/maximum or interquartile range). Statistical analysis We converted medians and ranges to means (s.d.) using the methods described by Wan et al. [18]. For binary data we used the variance estimator (v) for proportions (p) to derive the standard error: v = p(1 – p). We performed meta-analyses of patient characteristics separately for RCTs and observational studies, overall and by drug. If necessary, we first combined the data from the study arm into a single mean or proportion using fixed-effect meta-analyses. Secondly, we combined the data separately for RCTs and observational studies using random-effects meta-analyses with the Knapp–Hartung adjustment [19]. We used mixed-effects meta-regression analyses to assess the differences in patient characteristics between RCTs and observational studies by including the study design as a dichotomous covariate. We used restricted maximum-likelihood estimation to assess between-study variance (tau-squared) and applied the Knapp–Hartung adjustment. We stratified our main analysis by study type to explore whether the approaches differed in terms of baseline characteristics. In further meta-regression analyses, we included the year of publication of the studies to examine whether patient characteristics of patients included in RCTs or observational studies changed over calendar time. In a sensitivity analysis, we excluded phase IV and pragmatic trials, as reported by the trialists. All analyses were done with the R package metaphor [20]. Results We identified 308 references in our literature search for RCTs and 594 for observational studies, and considered 89 RCTs and 194 observational studies to be potentially eligible (supplementary Figs S1 and S2, available at Rheumatology Online). Fifty-one RCTs and 76 observational studies met our inclusion criteria and were included in the meta-analysis. Study characteristics The eligible studies were published between 1999 and 2015 for RCTs and between 2003 and 2015 for observational studies. Among RCTs, we included 5 phase II studies, 23 phase III studies, 10 phase IV studies and 1 pragmatic trial. For the remaining 12 RCTs we could not retrieve any information on the phase. Observational studies comprised 17 cohort, 28 registry and 31 case series studies. Most observational studies (71; 93.4%) were conducted in a single country whereas almost half of RCTs (25; 49.0%) were multi-country trials, mostly involving European countries. The number of study participants ranged from 70 to 1262 patients for RCTs and from 30 to 8908 for observational studies. Among RCTs, we included 17 TCZ, 10 RTX and 24 ETN trials, and among observational studies, we included 16 TCZ, 28 RTX and 32 ETN studies. Tables 1 and 2 summarize characteristics of RCTs and observational studies. Table 1 Study characteristics of 51 randomized controlled trials Reference  Year  Study design  Country/region  No. of centres  Overall, n  From/to  Drugs analysed  Trial name  Burmester et al. [21]  2014  Phase IIa  NA  NA  1262  NA  TCZ  SUMMACTA  Cohen et al. [22]  2006  Phase IIIa  USA, EU, Canada, Israel  NA  520  NA  RTX  REFLEX  Combe et al. [23]  2006  NA  Europe, Australia  NA  254  NA  ETN    Dougados et al. [24]  2014  Phase IIIb  Europe  NA  556  NA  TCZ  ACT RAY  Emery et al. [25]  2006  Phase IIb  NA  NA  465  NA  RTX    Emery et al. [26]  2010  Phase IIIa  11 countries  102  511  NA  RTX  SERENE  Emery et al. [27]  2008  Phase IV  EU, Latin America, Asia, Australia  NA  542  2004–06  ETN  COMET  Emery et al. [28]  2008  Phase IIIa  USA, EU  NA  499  NA  TCZ  RADIATE  Gabay et al. [29]  2013  Phase IV  15 countries  76  452  NA  TCZ  ADACTA  Genovese et al. [30]  2004  NA  USA  41  244  NA  ETN    Genovese et al. [31]  2008  Phase IIIa  EU, South America, Asia, Australia  18 countries  1220  2005–06  TCZ  TOWARD  Gerlag et al. [32]  2010  Phase IIb  Eastern EU 14 countries  61  482  NA  ETN    Jobanputra et al. [33]  2012  Pragmatic  UK  NA  125  NA  ETN  RED SEA  Jones et al. [34]  2010  Phase III  USA, Canada, Israel  NA  673  NA  TCZ  AMBITION  Kameda et al. [35]  2010  Phase IV  Japan  NA  151  2005–07  ETN  JESMER  Keystone et al. [36]  2004  NA  USA, Canada  48  476  NA  ETN    Keystone et al. [37]  2008  Phase III  USA, EU, Canada, Israel  114    NA  RTX  REFLEX  Kim et al. [38]  2012  Phase IV  Asia-Pacific  31  300  2007–09  ETN  APPEAL  Kivitz et al. [39]  2014  Phase IIIa  Not further spec.  NA  656  NA  TCZ  BREVACTA  Klareskog et al. [40]  2004  NA  EU  NA  682  2000–01  ETN  TEMPO  Kosinski et al. [41]  2002  NA  Not further spec.  NA  424  NA  ETN    Kremer et al. [42]  2011  Phase IIIa  14 countries  121  1196  2004–07  TCZ  LITHE  Machado et al. [43]  2014  Phase IV  Latin America  30  570  2009–11  ETN    Maini et al. [44]  2006  Phase II  EU  57  359  2001–02  TCZ  CHARISMA  Mariette et al. [45]  2014  Phase III  France  44  234  2006–11  RTX  SMART  McInnes et al. [46]  2015  Phase III  USA, Canada, UK  34  132  2007–08  TCZ  MEASURE  Mease et al. [47]  2008  Phase IIb  Not further spec.  95  367  NA  RTX  DANCER  Mease et al. [48]  2010  Phase III  USA  143  475  NA  RTX  SUNRISE  Moreland et al. [49]  1999  Phase III  USA  13  234  NA  ETN    Moreland et al. [50]  2012  Phase IV  USA, Netherland  44  755  NA  ETN  TEAR  Nam et al. [51]  2014  Phase IIIa  England  NA  132  NA  ETN  EMPIRE  Nishimoto et al. [52]  2004  NA  Japan  NA  164  2001–01  TCZ    Nishimoto et al. [53]  2007  Phase III  Japan  28  306  NA  TCZ  SAMURAI  Nishimoto et al. [54]  2009  Phase III  Japan  25  127  2004–05  TCZ  SATORI  O’Dell et al. [55]  2013  NA  USA, Canada  20  353  2007–10  ETN  RACAT  Ogata et al. [56]  2014  Phase IIIa  Japan  NA  348  NA  TCZ  MUSASHI  Pavelka et al. [57]  2014  Phase IV  EU, Latin America, Asia  80  495  2008–09  ETN  PRESERVE  Pope et al. [58]  2014  Phase IV  Canada  27  258  NA  ETN  CAMEO  Raffeiner et al. [59]  2015  NA  Italy  1  524  2006–12  ETN    Rigby et al. [60]  2011  Phase IIIa  Not further spec.  NA  748  NA  RTX  IMAGE  Rubbert-Roth et al. [61]  2010  Phase III  18 countries  81  378  NA  RTX  MIRROR  Smolen et al. [62]  2008  Phase III  17 countries  73  623  2005–06  TCZ  OPTION  Smolen et al. [63]  2013  Phase IV  EU, Latin America, Asia, Australia   80  834  2008–09  ETN  PRESERVE  Strand et al. [64]  2006  NA  Not further spec.  NA  161  NA  RTX    Tada et al. [65]  2012  NA  Japan  7  70  2008–10  ETN  PRECEPT  Takeuchi et al. [66]  2013  Phase III  Japan  40  550  NA  ETN    van Riel et al. [67]  2006  NA  EU  60  315  2003–04  ETN  ADORE  Weinblatt et al. [68]  1999  NA  Not further spec.  NA  89  NA  ETN    Weinblatt et al. [69]  2008  Phase IV  USA  63  200  NA  ETN    Weinblatt et al. [70]  2013  Phase IIIb  USA  NA  886  2009–10  TCZ    Yazici et al. [71]  2012  Phase IIIb  Not further spec.  NA  619  NA  TCZ  ROSE  Reference  Year  Study design  Country/region  No. of centres  Overall, n  From/to  Drugs analysed  Trial name  Burmester et al. [21]  2014  Phase IIa  NA  NA  1262  NA  TCZ  SUMMACTA  Cohen et al. [22]  2006  Phase IIIa  USA, EU, Canada, Israel  NA  520  NA  RTX  REFLEX  Combe et al. [23]  2006  NA  Europe, Australia  NA  254  NA  ETN    Dougados et al. [24]  2014  Phase IIIb  Europe  NA  556  NA  TCZ  ACT RAY  Emery et al. [25]  2006  Phase IIb  NA  NA  465  NA  RTX    Emery et al. [26]  2010  Phase IIIa  11 countries  102  511  NA  RTX  SERENE  Emery et al. [27]  2008  Phase IV  EU, Latin America, Asia, Australia  NA  542  2004–06  ETN  COMET  Emery et al. [28]  2008  Phase IIIa  USA, EU  NA  499  NA  TCZ  RADIATE  Gabay et al. [29]  2013  Phase IV  15 countries  76  452  NA  TCZ  ADACTA  Genovese et al. [30]  2004  NA  USA  41  244  NA  ETN    Genovese et al. [31]  2008  Phase IIIa  EU, South America, Asia, Australia  18 countries  1220  2005–06  TCZ  TOWARD  Gerlag et al. [32]  2010  Phase IIb  Eastern EU 14 countries  61  482  NA  ETN    Jobanputra et al. [33]  2012  Pragmatic  UK  NA  125  NA  ETN  RED SEA  Jones et al. [34]  2010  Phase III  USA, Canada, Israel  NA  673  NA  TCZ  AMBITION  Kameda et al. [35]  2010  Phase IV  Japan  NA  151  2005–07  ETN  JESMER  Keystone et al. [36]  2004  NA  USA, Canada  48  476  NA  ETN    Keystone et al. [37]  2008  Phase III  USA, EU, Canada, Israel  114    NA  RTX  REFLEX  Kim et al. [38]  2012  Phase IV  Asia-Pacific  31  300  2007–09  ETN  APPEAL  Kivitz et al. [39]  2014  Phase IIIa  Not further spec.  NA  656  NA  TCZ  BREVACTA  Klareskog et al. [40]  2004  NA  EU  NA  682  2000–01  ETN  TEMPO  Kosinski et al. [41]  2002  NA  Not further spec.  NA  424  NA  ETN    Kremer et al. [42]  2011  Phase IIIa  14 countries  121  1196  2004–07  TCZ  LITHE  Machado et al. [43]  2014  Phase IV  Latin America  30  570  2009–11  ETN    Maini et al. [44]  2006  Phase II  EU  57  359  2001–02  TCZ  CHARISMA  Mariette et al. [45]  2014  Phase III  France  44  234  2006–11  RTX  SMART  McInnes et al. [46]  2015  Phase III  USA, Canada, UK  34  132  2007–08  TCZ  MEASURE  Mease et al. [47]  2008  Phase IIb  Not further spec.  95  367  NA  RTX  DANCER  Mease et al. [48]  2010  Phase III  USA  143  475  NA  RTX  SUNRISE  Moreland et al. [49]  1999  Phase III  USA  13  234  NA  ETN    Moreland et al. [50]  2012  Phase IV  USA, Netherland  44  755  NA  ETN  TEAR  Nam et al. [51]  2014  Phase IIIa  England  NA  132  NA  ETN  EMPIRE  Nishimoto et al. [52]  2004  NA  Japan  NA  164  2001–01  TCZ    Nishimoto et al. [53]  2007  Phase III  Japan  28  306  NA  TCZ  SAMURAI  Nishimoto et al. [54]  2009  Phase III  Japan  25  127  2004–05  TCZ  SATORI  O’Dell et al. [55]  2013  NA  USA, Canada  20  353  2007–10  ETN  RACAT  Ogata et al. [56]  2014  Phase IIIa  Japan  NA  348  NA  TCZ  MUSASHI  Pavelka et al. [57]  2014  Phase IV  EU, Latin America, Asia  80  495  2008–09  ETN  PRESERVE  Pope et al. [58]  2014  Phase IV  Canada  27  258  NA  ETN  CAMEO  Raffeiner et al. [59]  2015  NA  Italy  1  524  2006–12  ETN    Rigby et al. [60]  2011  Phase IIIa  Not further spec.  NA  748  NA  RTX  IMAGE  Rubbert-Roth et al. [61]  2010  Phase III  18 countries  81  378  NA  RTX  MIRROR  Smolen et al. [62]  2008  Phase III  17 countries  73  623  2005–06  TCZ  OPTION  Smolen et al. [63]  2013  Phase IV  EU, Latin America, Asia, Australia   80  834  2008–09  ETN  PRESERVE  Strand et al. [64]  2006  NA  Not further spec.  NA  161  NA  RTX    Tada et al. [65]  2012  NA  Japan  7  70  2008–10  ETN  PRECEPT  Takeuchi et al. [66]  2013  Phase III  Japan  40  550  NA  ETN    van Riel et al. [67]  2006  NA  EU  60  315  2003–04  ETN  ADORE  Weinblatt et al. [68]  1999  NA  Not further spec.  NA  89  NA  ETN    Weinblatt et al. [69]  2008  Phase IV  USA  63  200  NA  ETN    Weinblatt et al. [70]  2013  Phase IIIb  USA  NA  886  2009–10  TCZ    Yazici et al. [71]  2012  Phase IIIb  Not further spec.  NA  619  NA  TCZ  ROSE  TCZ: Tocilizumab; RTX: Rituximab; ETN: Etanercept; NA: not available. Table 2 Study characteristics of 76 observational studies References  Year  Study design (Cohort, case series, registry)  Country/ Region  Overall, n  Calender years  Drugs analysed  Name registry  Ajeganova et al. [72]  2011  Cohort  Sweden  215  2000–07  RTX    Atzeni et al. [73]  2012  Registry  Italy  2769  1999  ETN    Backhaus et al. [74]  2015  Cohort  Germany  1603  2010–11  TCZ    Bingham et al. [75]  2009  Case series  CAN/USA  201  NA  ETN    Blom et al. [76]  2011  Registry  Netherland  154  1997–2010  RTX  DREAM  Bobbio-Pallavicini et al. [77]  2007  Cohort  Italy  132  NA  ETN    Bokarewa et al. [78]  2007  Case series  Sweden  48  2002–05  RTX    Bykerk et al. [79]  2015  Cohort  25 countries  1681  2008–10  TCZ    Cannon et al. [80]  2014  Registry  USA  1767  2003–11  ETN  VARA  Carter et al. [81]  2012  Case series  USA  64  2008–11  RTX    Chatzidionysiou et al. [82]  2015  Registry  Sweden  7052  2005–12  ETN  ARTIS  Chen et al. [83]  2013  Case series  Taiwan  56  NA  RTX    Conigliaro et al. [84]  2014  Case series  Italy  82  NA  ETN    Coulthard et al. [85]  2011  Registry  UK  1102  NA  ETN  BRAGGSS  De Keyser et al. [86]  2014  Registry  Belgium  649  2006–11  RTX  MIRA  Diaz-Torne et al. [87]  2014  Case series  Spain  33  NA  RTX    Dougados et al. [88]  2012  Case series  France  120  NA  ETN    Einarsson et al. [89]  2015  Registry  Sweden  2416  1999–2009  ETN    Emery et al. [90]  2014  Cohort  11 countries  1312  NA  RTX    Enevold et al. [91]  2014  Case series  Denmark  79  NA  TCZ    Fabris et al. [92]  2013  Case series  Italy, UK  152  NA  RTX    Feltelius et al. [93]  2005  Registry  Sweden  1073  1999–2005  ETN    Fernández-Nebro et al. [94]  2007  Cohort  Spain  161  1999–2006  ETN    Finckh et al. [95]  2006  Registry  Switzerland  1198  1998–2004  ETN  SCQM  Finckh et al. [96]  2010  Registry  Switzerland  318  1998–2008  RTX  SCQM  Fortunet et al. [97]  2014  Cohort  France  220  2009–11  ETN    Gardette et al. [98]  2014  Cohort  France  114  NA  RTX    Gibofsky et al. [99]  2011  Registry  USA  5032  2002–03  ETN    Gomez-Reino et al. [100]  2012  Cohort  Spain  1124  2006  RTX  MIRAR  Greenberg et al. [101]  2012  Registry  USA  2242  NA  ETN  CORONNA  Guis et al. [102]  2007  Case series  France  86  2000–05  ETN    Harrold et al. [103]  2015  Registry  USA  615  2006–11  RTX  CORONNA  Hasan et al. [104]  2012  Case series  Kuwait  45  NA  RTX    Hetland et al. [105]  2010  Registry  Denmark  8074  2000–09  ETN  DANBIO  Hirabayashi et al. [106]  2013  Case series  Japan  285  2008–09  TCZ    Hirata et al. [107]  2014  Cohort  Japan  147  2003–10  ETN    Hyrich et al. [108]  2006  Registry  UK  2879  2001–04  ETN  BSRBR  Izumi et al. [109]  2015  Cohort  Japan  115  2008–11  TCZ  KEIO-TCZ  Jamnitski et al. [110]  2010  Case series  Netherland  292  2004–08  ETN    Jančić et al. [111]  2013  Case series  Serbia  82  NA  ETN    Kaneko et al. [112]  2012  Case series  Japan  31  2008–08  TCZ    Kawashiri et al. [113]  2010  Case series  Japan  45  NA  ETN    Kawashiri et al. [114]  2011  Cohort  Japan  32  NA  TCZ    Kekow et al. [115]  2012  Cohort  Germany  196  NA  RTX    Kojima et al. [116]  2015  Registry  Japan  2176  2008–09  TCZ  TBCR  Kume et al. [117]  2011  Case series  Japan  34  2006–09  TCZ    Kume et al. [118]  2014  Case series  Japan  86  NA  TCZ    Laas et al. [119]  2008  Case series  Finland  91  1999–2003  ETN    Leffers et al. [120]  2011  Registry  Denmark  328  2010–11  TCZ  DANBIO  Listing et al. [121]  2006  Registry  Germany  1083  2001–03  ETN  RABBIT  Listing et al. [122]  2013  Registry  Germany  8908  2001–11  RTX  RABBIT  Marchesoni et al. [123]  2009  Registry  Italy  1114  1999  ETN  LOHREN  Mazilu et al. [124]  2014  Case series  Romania  74  2010  RTX    McGonagle et al. [125]  2008  Case series  UK  39  2004–07  RTX    Montes et al. [126]  2014  Cohort  Spain, Greece  429  2000–10  ETN    Nakashima et al. [127]  2014  Registry  Japan  236  2008  TCZ  FRAB  Narváez et al. [128]  2011  Case series  Spain  108  2007–09  RTX    Payet et al. [129]  2014  Registry  France  1709  NA  RTX  AIR  Perera et al. [130]  2006  Case series  Australia  50  NA  ETN    Richez et al. [131]  2012  Cohort  France  45  NA  TCZ    Scirè et al. [132]  2013  Registry  Italy  2640  2007–12  ETN  MonitorNet  Sebastiani et al. [133]  2014  Registry  Italy  338  1999  RTX  GISEA  Solau-Gervais et al. [134]  2012  Case series  France  108  2005–08  RTX    Soliman et al. [135]  2012  Registry  UK  646  2010  RTX  BSRBR  Song et al. [136]  2013  Cohort  Japan  93  2008  TCZ    Su et al. [137]  2009  Case series  Taiwan  94  2004–07  ETN    Takeuchi et al. [138]  2011  Cohort  Japan  232  2008–09  TCZ  REACTION  Thurlings et al. [139]  2008  Case series  Netherland  30  NA  RTX    Valleala et al. [140]  2009  Case series  Finland  81  2005–08  RTX    Valleala et al. [141]  2015  Case series  Finland  151  2005–11  RTX    Van Dartel et al. [142]  2013  Registry  Netherland  2356  2003  ETN  DREAM  van Vollenhoven et al. [143]  2003  Registry  Sweden  97  NA  ETN  STURE  Váncsa et al. [144]  2013  Case series  Hungary  77  NA  RTX    Wakabayashi et al. [145]  2011  Case series  Japan  107  2008–10  TCZ    Wendler et al. [146]  2014  Case series  Germany  2484  NA  RTX    Zink et al. [147]  2006  Registry  Germany  1458  2001–03  ETN  RABBIT  References  Year  Study design (Cohort, case series, registry)  Country/ Region  Overall, n  Calender years  Drugs analysed  Name registry  Ajeganova et al. [72]  2011  Cohort  Sweden  215  2000–07  RTX    Atzeni et al. [73]  2012  Registry  Italy  2769  1999  ETN    Backhaus et al. [74]  2015  Cohort  Germany  1603  2010–11  TCZ    Bingham et al. [75]  2009  Case series  CAN/USA  201  NA  ETN    Blom et al. [76]  2011  Registry  Netherland  154  1997–2010  RTX  DREAM  Bobbio-Pallavicini et al. [77]  2007  Cohort  Italy  132  NA  ETN    Bokarewa et al. [78]  2007  Case series  Sweden  48  2002–05  RTX    Bykerk et al. [79]  2015  Cohort  25 countries  1681  2008–10  TCZ    Cannon et al. [80]  2014  Registry  USA  1767  2003–11  ETN  VARA  Carter et al. [81]  2012  Case series  USA  64  2008–11  RTX    Chatzidionysiou et al. [82]  2015  Registry  Sweden  7052  2005–12  ETN  ARTIS  Chen et al. [83]  2013  Case series  Taiwan  56  NA  RTX    Conigliaro et al. [84]  2014  Case series  Italy  82  NA  ETN    Coulthard et al. [85]  2011  Registry  UK  1102  NA  ETN  BRAGGSS  De Keyser et al. [86]  2014  Registry  Belgium  649  2006–11  RTX  MIRA  Diaz-Torne et al. [87]  2014  Case series  Spain  33  NA  RTX    Dougados et al. [88]  2012  Case series  France  120  NA  ETN    Einarsson et al. [89]  2015  Registry  Sweden  2416  1999–2009  ETN    Emery et al. [90]  2014  Cohort  11 countries  1312  NA  RTX    Enevold et al. [91]  2014  Case series  Denmark  79  NA  TCZ    Fabris et al. [92]  2013  Case series  Italy, UK  152  NA  RTX    Feltelius et al. [93]  2005  Registry  Sweden  1073  1999–2005  ETN    Fernández-Nebro et al. [94]  2007  Cohort  Spain  161  1999–2006  ETN    Finckh et al. [95]  2006  Registry  Switzerland  1198  1998–2004  ETN  SCQM  Finckh et al. [96]  2010  Registry  Switzerland  318  1998–2008  RTX  SCQM  Fortunet et al. [97]  2014  Cohort  France  220  2009–11  ETN    Gardette et al. [98]  2014  Cohort  France  114  NA  RTX    Gibofsky et al. [99]  2011  Registry  USA  5032  2002–03  ETN    Gomez-Reino et al. [100]  2012  Cohort  Spain  1124  2006  RTX  MIRAR  Greenberg et al. [101]  2012  Registry  USA  2242  NA  ETN  CORONNA  Guis et al. [102]  2007  Case series  France  86  2000–05  ETN    Harrold et al. [103]  2015  Registry  USA  615  2006–11  RTX  CORONNA  Hasan et al. [104]  2012  Case series  Kuwait  45  NA  RTX    Hetland et al. [105]  2010  Registry  Denmark  8074  2000–09  ETN  DANBIO  Hirabayashi et al. [106]  2013  Case series  Japan  285  2008–09  TCZ    Hirata et al. [107]  2014  Cohort  Japan  147  2003–10  ETN    Hyrich et al. [108]  2006  Registry  UK  2879  2001–04  ETN  BSRBR  Izumi et al. [109]  2015  Cohort  Japan  115  2008–11  TCZ  KEIO-TCZ  Jamnitski et al. [110]  2010  Case series  Netherland  292  2004–08  ETN    Jančić et al. [111]  2013  Case series  Serbia  82  NA  ETN    Kaneko et al. [112]  2012  Case series  Japan  31  2008–08  TCZ    Kawashiri et al. [113]  2010  Case series  Japan  45  NA  ETN    Kawashiri et al. [114]  2011  Cohort  Japan  32  NA  TCZ    Kekow et al. [115]  2012  Cohort  Germany  196  NA  RTX    Kojima et al. [116]  2015  Registry  Japan  2176  2008–09  TCZ  TBCR  Kume et al. [117]  2011  Case series  Japan  34  2006–09  TCZ    Kume et al. [118]  2014  Case series  Japan  86  NA  TCZ    Laas et al. [119]  2008  Case series  Finland  91  1999–2003  ETN    Leffers et al. [120]  2011  Registry  Denmark  328  2010–11  TCZ  DANBIO  Listing et al. [121]  2006  Registry  Germany  1083  2001–03  ETN  RABBIT  Listing et al. [122]  2013  Registry  Germany  8908  2001–11  RTX  RABBIT  Marchesoni et al. [123]  2009  Registry  Italy  1114  1999  ETN  LOHREN  Mazilu et al. [124]  2014  Case series  Romania  74  2010  RTX    McGonagle et al. [125]  2008  Case series  UK  39  2004–07  RTX    Montes et al. [126]  2014  Cohort  Spain, Greece  429  2000–10  ETN    Nakashima et al. [127]  2014  Registry  Japan  236  2008  TCZ  FRAB  Narváez et al. [128]  2011  Case series  Spain  108  2007–09  RTX    Payet et al. [129]  2014  Registry  France  1709  NA  RTX  AIR  Perera et al. [130]  2006  Case series  Australia  50  NA  ETN    Richez et al. [131]  2012  Cohort  France  45  NA  TCZ    Scirè et al. [132]  2013  Registry  Italy  2640  2007–12  ETN  MonitorNet  Sebastiani et al. [133]  2014  Registry  Italy  338  1999  RTX  GISEA  Solau-Gervais et al. [134]  2012  Case series  France  108  2005–08  RTX    Soliman et al. [135]  2012  Registry  UK  646  2010  RTX  BSRBR  Song et al. [136]  2013  Cohort  Japan  93  2008  TCZ    Su et al. [137]  2009  Case series  Taiwan  94  2004–07  ETN    Takeuchi et al. [138]  2011  Cohort  Japan  232  2008–09  TCZ  REACTION  Thurlings et al. [139]  2008  Case series  Netherland  30  NA  RTX    Valleala et al. [140]  2009  Case series  Finland  81  2005–08  RTX    Valleala et al. [141]  2015  Case series  Finland  151  2005–11  RTX    Van Dartel et al. [142]  2013  Registry  Netherland  2356  2003  ETN  DREAM  van Vollenhoven et al. [143]  2003  Registry  Sweden  97  NA  ETN  STURE  Váncsa et al. [144]  2013  Case series  Hungary  77  NA  RTX    Wakabayashi et al. [145]  2011  Case series  Japan  107  2008–10  TCZ    Wendler et al. [146]  2014  Case series  Germany  2484  NA  RTX    Zink et al. [147]  2006  Registry  Germany  1458  2001–03  ETN  RABBIT  TCZ: Tocilizumab; RTX: Rituximab; ETN: Etanercept; NA: not available. Comparison of patient characteristics Compared with patients participating in RCTs, those from observational studies were on average 3.0 years older (P < 0.001), suffered from RA for 3.1 years longer (P < 0.001) and had 1.6 more prior DMARDs (P = 0.001; Fig. 1). Patients in RCTs had higher disease activity: the DAS-28 was 0.6 points higher in RCT than in observational studies (P < 0.001; Fig. 2). CRP and ESR levels were also slightly higher in RCTs, but differences failed to reach conventional levels of statistical significance (Fig. 2). Similarly, there was little evidence for any difference between HAQ-DI scores, RF positivity or the proportion of women participating in the studies. Fig. 1 View largeDownload slide Comparison between randomized controlled trials and observational studies for age, gender, disease duration and number of prior DMARDs RCT: randomized controlled trial; OBS: observational study. Fig. 1 View largeDownload slide Comparison between randomized controlled trials and observational studies for age, gender, disease duration and number of prior DMARDs RCT: randomized controlled trial; OBS: observational study. Fig. 2 View largeDownload slide Comparison between randomized controlled trials and observational studies: DAS-28, HAQ, CRP, ESR and RF positivity RCT: randomized controlled trial; OBS: observational study. Fig. 2 View largeDownload slide Comparison between randomized controlled trials and observational studies: DAS-28, HAQ, CRP, ESR and RF positivity RCT: randomized controlled trial; OBS: observational study. Analyses stratified by drug showed that differences generally were in the same direction for the three drugs, but tended to be more pronounced for TCZ and RTX than for ETN (Figs 1 and 2). Patients on TCZ were 3.9 years older in observational studies than in RCTs (P < 0.001), their disease duration was 2.4 years longer (P = 0.06), they had been exposed on average to 1.4 additional DMARDs (P = 0.346) and the DAS-28 was 1.2 points lower than in RCTs (P < 0.001). Similarly, patients on RTX were 3.3 years older (P = 0.013), their disease duration was 2.6 years longer (P = 0.05), they had been exposed to 1.8 more DMARDs (P = 0.083) and the DAS-28 was 1.1 points (P < 0.001) lower in observational studies than in RCTs. Patients on ETN were 2.4 years older in observational studies than in RCTs (P = 0.017), their disease duration was 3.4 years longer (P < 0.001) and they had been exposed to 1.6 more DMARDs (P = 0.056). There was no difference in DAS-28 (0 points, P = 0.86). Analyses stratified by study type gave similar results compared with the main analyses (supplementary Figs S3–S11, available at Rheumatology Online, forest plots for all baseline characteristics). Trends over calendar time We found that DAS-28 declined over calendar time both in RCTs (slope of −0.08, P = 0.026) and in observational studies (slope of −0.08, P = 0.002) (Fig. 3). HAQ-DI declined slightly over calendar time both in RCTs (slope of −0.04, P = 0.004) and in observational studies (slope of −0.04, P = 0.063) (Fig. 4). Furthermore, ESR and CRP declined over calendar time in RCTs (slope of −1.69, P = 0.009 for ESR and slope of −1.68, P = 0.001 for CRP), but not significantly so in observational studies (supplementary Figs S16-S17). There was little evidence for changes in baseline patient characteristics over time for any of the other socio-demographic or clinical characteristics (supplementary Figs S12–S15, available at Rheumatology Online). Fig. 3 View largeDownload slide Comparison of DAS-28 between randomized controlled trials and observational studies plotted over time Fig. 3 View largeDownload slide Comparison of DAS-28 between randomized controlled trials and observational studies plotted over time Fig. 4 View largeDownload slide Comparison of HAQ disability index between randomized controlled trials and observational studies plotted over time Fig. 4 View largeDownload slide Comparison of HAQ disability index between randomized controlled trials and observational studies plotted over time Sensitivity analysis In a sensitivity analysis we excluded 10 phase IV trials and 1 pragmatic trial. Ten of the excluded trials included patients on ETN, while one trial included patients on TCZ. There was no substantial change compared with the main analyses, except that ESR increased from 46.3 to 49.4 mm/h in RCTs, which is significantly higher than in observational studies (P = 0.004). Discussion In this study of the characteristics of patients with RA we found clinically relevant differences between RCTs and observational studies in RA. Compared with RCTs, RA patients in observational studies were older, disease duration was longer, a higher number of different DMARDs were administered before starting biologic treatment and disease activity was lower at baseline. Over time, baseline DAS-28 and HAQ-DI declined in patients included in RCTs but not in patients from observational databases. Differences between real-world and trial data are important, especially when making decisions in everyday clinical practice. Eichler and colleagues [8] argue that the efficacy–effectiveness gap is due to variability in drug response caused by biological and behavioural factors. Biological factors can be separated into genetic and non-genetic factors, which in turn can be further divided into intrinsic and extrinsic factors. Intrinsic factors are characteristics of the person such as age, sex, body weight, comorbidities and baseline severity of disease, whereas extrinsic factors relate to lifestyle factors such as smoking [8]. Kirsch and colleagues studied all available data of clinical trials submitted to the Food and Drug Administration for the licensing of four new-generation antidepressants [9]. They found a relationship between initial disease severity and anti-depressant efficacy, an association that was due to decreased responsiveness to placebo among very severely depressed patients as opposed to increased responsiveness to medication. Similarly, in patients with RA a high DAS-28 score at baseline is a good predictor of a decline in the DAS-28 following treatment with ETN [148] and TCZ [120]. Our review showed higher DAS-28 scores in patients enrolled in RCTs and we can therefore speculate that the response was better in trial patients than in observational studies. In other words, the treatment effect in everyday clinical praxis might be smaller than that in RCTs. High numbers of prior DMARDs and higher age were associated with decreased response rates in patients with ETN [149]. Older age was also associated with decreased response rate in age with TCZ [150]; these two baseline characteristics differed significantly between RCTs and observational studies in our analysis. Predictive factors for better response to biologics were male gender (in ETN-treated patients [149]), non-smokers (ETN [149]), RF positivity (RTX and TC [151]) and low HAQ-DI (TCZ [120] and RTX [149]). For all these factors, if data were available, we found no difference between RCTs and observational studies. In our time trend analysis, we saw a decrease in baseline DAS-28 and HAQ-DI in RCTs over the past 10 years. A decrease in DAS-28 has also been shown for other biologics such as infliximab [152]. These findings support the results of an inception cohort study published 10 years ago, where the trend was thought to be caused by a more aggressive treatment strategy [153]. In a sensitivity analysis we excluded 10 phase IV clinical trials and one pragmatic trial. Interestingly, we found no difference compared with the main results described above. In particular, the results in the ETN group where 10 trials were excluded remained virtually the same. This may call into question the notion that phase IV trials accurately represent real-world scenarios, and that their estimates of comparative effectiveness are closer to those of observational studies. We acknowledge that the number of phase IV and pragmatic trials was small and that the results from our sensitivity analysis should be interpreted with caution. Our review has several strengths and weaknesses. Strengths are that the review was based on a systematic literature search, and study selection and screening were performed independently by two authors. Data extraction was performed by one person and checked by a second. Our search was comprehensive, but we included only English-language studies. Also, we did not look into reports by the European Medicines Agency or Food and Drug Administration. Data for each biologic may have been assessed at different time points in each registry. For instance, in the Rabbit registry, we used data for ETN from 2006, whereas data for RTX was assessed from a publication in 2013. We cannot exclude the possibility that some of the included patients were counted twice, because patients might have switched their treatment from ETN to RTX. However, in the absence of individual patient data we can only speculate the percentage of patients who switched treatment regimens. Overall, 7 of the 28 included registries had more than one publication, and it is therefore possible that patients were counted twice. Since we did not assess outcomes, we did not apply any risk of bias tool or similar instrument to examine the quality of studies. Our main interest was the characteristics of patients included in RCTs and observational studies and it is therefore unlikely that the comparison was distorted by publication or other selection bias. We transformed median values into mean values. This might lead to bias in the aggregated mean if the data summarized by the median were clearly not normally distributed. Since we transformed only about 8% of the values provided in the RCTs and only about 17% of the values from the observational studies, any bias introduced is likely small. Several relevant variables were poorly reported: concomitant MTX use, concomitant DMARD use, percentage of smokers (reported in only one RCT), comorbidities and ACPA positivity. These variables were therefore not included in our analyses, despite their potential relevance in the context of generalizing results from RCTs to real world settings. Clearly, more work is required on how best to narrow the efficacy–effectiveness gap. In phase IV and pragmatic trials, inclusion and exclusion criteria need to be widened to reflect the real world. The baseline characteristics of patients included in these trials should better reflect what we found in observational studies. In addition, evidence synthesis and modelling approaches should be used to combine data from both RCT and observational studies to generate real-world evidence [15]. In summary, we found important differences between RA patients included in RCTs as compared with observational studies; in particular, patients with better prognostic factors were included in the RCTs, leading to potential overestimation of the treatment effect. More research is needed to overcome this efficacy–effectiveness gap in RA to generate real-world evidence. Funding: The research leading to these results was conducted as part of the GetReal consortium. For further information please refer to www.imi–getreal.eu. This paper only reflects the personal views of the stated authors. The work leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115546, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007‐ 2013) and European Federation of Pharmaceutical Industries and Associations companies in kind contribution. In addition as a special form of the IMI JU grant Eva-Maria Didden received a direct financial contribution from Boehringer Ingelheim. 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RheumatologyOxford University Press

Published: Feb 1, 2018

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