Old drugs, old problems: where do we stand in
prediction of rheumatoid arthritis responsiveness
to methotrexate and other synthetic DMARDs?
Vasco Crispim Romão1,2, Helena Canhão1,2and João Eurico Fonseca1,2*
Methotrexate (MTX) is the central drug in the
management of rheumatoid arthritis (RA) and other
immune mediated inflammatory diseases. It is widely
used either in monotherapy or in association with
other synthetic and biologic disease modifying anti-
rheumatic drugs (DMARDs). Although comprehensive
clinical experience exists for MTX and synthetic
DMARDs, to date it has not been possible to preview
correctly whether or not a patient will respond to
treatment with these drugs. Predicting response to
MTX and other DMARDs would allow the selection of
patients based on their likelihood of response, thus
enabling individualized therapy and avoiding
unnecessary adverse effects and elevated costs.
However, studies analyzing this issue have struggled
to obtain consistent, replicable results and no factor
has yet been recognized to individually distinguish
responders from nonresponders at treatment start.
Variables possibly influencing drug effectiveness may
be disease-, patient- or treatment-related, clinical or
biological (genetic and nongenetic). In this review we
summarize current evidence on predictors of
response to MTX and other synthetic DMARDs,
discuss possible causes for the heterogeneity
observed and address its translation into daily clinical
Keywords: Predictors of response, Rheumatoid arthri-
tis, Synthetic DMARDs, Methotrexate
Methotrexate (MTX) is the anchor disease modifying
anti-rheumatic drug (DMARD) in the management of
rheumatoid arthritis (RA) and other immune mediated
chronic inflammatory disorders. In RA, it is the most
commonly used DMARD and the first one to be chosen
[1,2] due to its efficacy, safety and cost, ultimately trans-
lated by the best drug retention rate among DMARDs
[3-6]. It is the gold standard in the management of RA
and can be prescribed in monotherapy or in combination
with other synthetic or biological agents [7-9]. Multina-
tional recommendations have been issued for the use of
MTX in RA management  and are summarized in
Table 1. However, MTX is not effective or induces signif-
icant adverse events in a considerable number of patients
 who are forced to discontinue it and switch to
another DMARD regimen, generally with equally hetero-
geneous responses .
Being able to predict response to first-line DMARDs, has
been one of the main challenges in RA management for
over two decades  and it is a good example of the
increasingly appealing concept of personalized therapy,
that is, choosing the drug of most benefit for a particular
patient. This would be of tremendous benefit in several
ways. By identifying patients less prone to respond it would
avoid needless exposure to potentially toxic drugs and the
waste of precious time to achieve disease control, a crucial
endpoint to prevent development of structural damage
. Likely responders would be maintained with the most
appropriate DMARD with more certainty, obviating an
early, possibly unnecessary, switch to other potentially less
effective DMARDs or to more costly biologicals. Theoreti-
cally, this would allow physicians to quit the current trial-
and-error approach and adopt solid, objective criteria of
targeted drug selection, leading to cheaper, quicker, safer
and more effective control of the disease.
However, this has proved to be an arduous task and to
date there are few clear, reliable, variables that can be
* Correspondence: firstname.lastname@example.org
1Rheumatology Research Unit, Instituto de Medicina Molecular - Faculdade
de Medicina da Universidade de Lisboa, Edifício Egas Moniz - Av. Prof. Egas
Moniz, Lisboa 1649-028, Portugal
Full list of author information is available at the end of the article
Romão et al. BMC Medicine 2013, 11:17
© 2013 Romão et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
used in daily practice to allow prediction of response to
MTX or other DMARDs [14-19]. While predictors of
poor RA prognosis are well established [20,21], they do
not accurately correlate with response to treatment .
Furthermore, heterogeneous response is most likely
the result of multi-factor interactions and cannot be
explained by a single cause-effect mechanism within a
certain domain. Those factors that are possibly influen-
cing drug effectiveness can be divided into patient-related
(age, gender, ethnicity, comorbidities), disease-related
(duration, activity, disability, biomarkers), treatment-
related (compliance, dose, previous drugs) and genetic
factors . We conducted a literature review to sum-
marize current available data on predictors of response
to MTX and other DMARDs (dividing them into clinical
factors, nongenetic biomarkers and genetic biomarkers),
discuss the causes for the discrepancies reported and
critically analyze the possible translation into clinical
Clinical predictors of response
Several clinical factors have been studied and it has been
difficult to reach a consensus on which factors are
undoubtedly predictive of response to treatment with
MTX and other DMARDs (Table 2).
Regarding gender, it seems that men respond better to
MTX than women: in the systematic review by Drouin
et al. , the authors found that male gender was asso-
ciated with a better clinical response to MTX both in early
 and established RA . Similar conclusions were
reached by Anderson et al. in a large meta-analysis of ran-
domized controlled trials (RCTs), including 1,435 patients,
in terms of achieving American College of Rheumatology
(ACR) 20 responses , and by Saevarsdottir and
Table 1 Multinational recommendations for the use of methotrexate in RA.
Recommendation Level of
1 The work-up for patients starting methotrexate should include clinical assessment of risk
factors for methotrexate toxicity (including alcohol intake), patient education, AST, ALT,
albumin, CBC, creatinine, chest × ray (obtained within the previous year); consider serology for
HIV, hepatitis B/C, blood fasting glucose, lipid profile and pregnancy test.
2 Oral methotrexate should be started at 10 to 15 mg/week, with escalation of 5 mg every 2 to
4 weeks up to 20 to 30 mg/week, depending on clinical response and tolerability; parenteral
administration should be considered in the case of inadequate clinical response or
3 Prescription of at least 5 mg folic acid per week with methotrexate therapy is strongly
4 When starting methotrexate or increasing the dose, ALT with or without AST, creatinine and
CBC should be performed every 1 to 1.5 months until a stable dose is reached and every 1 to
3 months thereafter; clinical assessment for side effects and risk factors should be performed
at each visit.
5 Methotrexate should be stopped if there is a confirmed increase in ALT/AST greater than
three times the ULN, but may be reinstituted at a lower dose following normalization. If the
ALT/AST levels are persistently elevated up to three times the ULN, the dose of methotrexate
should be adjusted; diagnostic procedures should be considered in the case of persistently
elevated ALT/AST more than three times the ULN after discontinuation.
6 Based on its acceptable safety profile, methotrexate is appropriate for long-term use.
7 In DMARD-naïve patients the balance of the efficacy/toxicity favors methotrexate
monotherapy over combination with other conventional DMARDs; methotrexate should be
considered as the anchor for combination therapy when methotrexate monotherapy does not
achieve disease control.
8 Methotrexate can be safely continued in the perioperative period in RA patients undergoing
elective orthopedic surgery.
9 Methotrexate should not be used for at least three months before planned pregnancy for
men and women and should not be used during pregnancy or breast feeding
Adapted by permission from BMJ Publishing Group Limited. [Ann Rheum Dis, Visser K et al. 2009, 68:1086-1093]. Evidence-based recommendations for the use of
methotrexate in daily clinical care of rheumatic disorders, issued by 751 rheumatologists from 17 countries through systematic review of the literature, discussion
and voting. Levels of evidence and grades of recommendation were determined according to those established by the Oxford Centre for Evidence Based
Medicine , as follows: level 1a - systematic review (SR; with homogeneity) of randomized clinical trials (RCTs); level 1b - individual RCT (with narrow
confidence interval); level 1c - all or none; level 2a - SR (with homogeneity) of cohort studies; level 2b - individual cohort study (including low quality RCT); level
2c - ‘outcomes’ research, ecological studies; level 3a - SR (with homogeneity) of case-control studies; level 3b - individual case-control study; level 4 - case-series
(and poor quality cohort and case-control studies); level 5 - expert opinion without explicit critical appraisal or based on physiology, bench research or ‘first
principles’; a minus sign (-) can be added to a particular level, to denote that it fails to provide a conclusive answer because of either a single result with a wide
confidence interval or a SR with troublesome heterogeneity. Grade of recommendation A - consistent level 1 studies; grade of recommendation B - consistent
level 2 or 3 studies or extrapolations from level 1 studies; grade of recommendation C - level 4 studies or extrapolations from level 2 or 3 studies; grade of
recommendation D - level 5 evidence or troublingly inconsistent or inconclusive studies of any level. ALT, alanine aminotransferase; AST, aspartate
aminotransferase; CBC, complete blood count; DMARD, disease-modifying antirheumatic drug; RA, rheumatoid arthritis; SD, standard deviation; ULN, upper limit
Romão et al. BMC Medicine 2013, 11:17
Page 2 of 24
colleagues , in a population of early RA patients (SWE-
FOT trial), with a worse European League Against Rheuma-
tism (EULAR) response being observed in women (odds
ratio (OR) = 0.50, 95% confidence interval (CI) 0.31 to
0.81). Stranzl et al. also found female sex to be an indepen-
dent predictor of poor response to MTX (OR = 3.3, P =
0.009) . In the study by Vázquez et al. , in early RA
patients, male gender was associated with remission after
two years of MTX ± gold treatment in the univariate analy-
sis but not in the multivariate analysis. Hider et al. 
found no differences between men and women in response
rates to MTX in a prospective study of an early inflamma-
tory polyarthritis cohort and there are also other studies
that were not able to identify an influence of gender on
MTX response . In spite of some conflicting results, it
seems that most of the evidence points in the direction of
male gender being a predictor of good response to MTX in
both early and established RA. Indeed, in a recently pub-
lished study , a predictive model for 24-month remis-
sion was developed for patients with early RA treated in a
RCT with MTX ± corticosteroids ± cyclosporine ; it
was validated in an early RA cohort (ERAN) of patients
treated with MTX or other DMARDs . The authors
concluded that one of the three variables that predicted
remission at 24 months was male gender (OR = 3.14,
P <0.001). As in this latter study, most of the analyses of
response to other DMARDs have been done together with
MTX, so their individual effect is difficult to predict. Two
publications from the 1990s, a meta-analysis  and an
observational study , comprising a significant number of
patients, demonstrated that gender did not influence the
response to treatment with sulphasalazine (SSZ), gold and
penicillamine. A more recent open label trial showed no
influence of gender on whether patients with early RA
started on hydroxychloroquine (HCQ) would have to step
up therapy to MTX . Other studies have also failed to
detect a significant effect of gender on treatment response
to DMARDs, other than MTX [28,32,35-37]. Overall, it
seems that under the light of current evidence it is not pos-
sible to generalize the better response to MTX treatment
seen in men to other DMARDs. The possible explanation
of the influence of gender on MTX responsiveness, as pro-
posed by Hider et al. , might be that hormonal factors
that influence the pharmacokinetics and pharmacody-
namics of each drug contribute to a better or worse
response, explaining the apparent discrepancy in the influ-
ence of this factor on different DMARDs. Another question
could be raised based on the fact that female gender is per
se predictive of a worse global prognosis in terms of radio-
graphic progression and disability [21,38]: is the female
Table 2 Summary of clinical predictors of response to MTX and other DMARDs.
Factors Predictor of response? Comments
GenderYes, men respond better to
Both in early and established RA; not extendable to other DMARDs
Age Strong evidence showing lack of influence on MTX responsiveness, a few contradicting
studies; probably also no influence on other DMARDs
Despite the theoretical rationale, more data is needed
Most studies do not analyze it; however, available studies point to worse response in
active smokers; not certain as to extension to other DMARDs
Early RA has better response than established RA, but no influence of duration in
longstanding disease; controversial results due to methodological heterogeneity
Previous DMARD use associated with worse response to MTX and other DMARDs;
however, not confirmed in some studies; results likely to be affected by several clinical
However, frequently not replicable with different scores; unclear which scores are better,
likely to depend on response measures used
Contradicting findings; unreliable when variables are used separately
Likely, active smokers
respond worse to MTX
Yes, better response in
Yes, worse response
Prior DMARD use
Disease activity measured
by composite scores
Disease activity measured
by isolated variables
Yes, worse response if
higher baseline activity
Uncertain, not likely No association in most studies; inverse relation between HAQ and response in some
early RA studies
Strong evidence showing lack of influence on response to MTX and other DMARDs; a
few contradicting studies
Only two studies suggesting higher response to MTX in NSAIDs users; more data needed
Although most studies fail to analyze it, combined therapy with steroids seems to have
better results than DMARD monotherapy
Extensively shown that baseline radiographic scores do not predict clinical response to
Pain global assessmentNo
Likely, better response
Conclusions and comments are based on the findings reported and discussed in the text. DMARDs, disease modifying anti-rheumatic drugs; HAQ, health
assessment questionnaire; MTX, methotrexate; NSAIDs, non-steroidal anti-inflammatory drugs; RA, rheumatoid arthritis.
Romão et al. BMC Medicine 2013, 11:17
Page 3 of 24
worse response to treatment with MTX contributing to this
observation? This is a hypothesis that needs further
Age does not seem to be a predictive factor of response
to MTX or to other DMARDs. Most studies showed a
lack of effect of baseline age on clinical response to MTX
therapy, including two large meta-analyses [15,39], and,
therefore, it does not seem to influence responsiveness
[14,23,24,26-28,32,37,40-42]. Despite this strong body of
evidence, some studies have contradicting results, such as
the SWEFOT trial  which showed that older age was
associated with a higher likelihood of both EULAR and
the clinical disease activity index (CDAI) response to
MTX treatment at three to four months (OR = 1.30, 95%
CI 1.11 to 1.51) and the study by Ma et al. , where
older patients (>50 years old), on the contrary, were less
likely to be in remission at 24 months after the start of
MTX ± cyclosporine (OR = 0.97, P = 0.014). Thus,
despite these two early RA studies, where age seemed to
influence response to MTX treatment, although in oppo-
site directions, most studies, including large meta-
analyses, showed that age is not a predictor of response
to MTX. As to other DMARDs, a single study showed
that patients responding to SSZ were younger than non-
responders, with no effect of age on the response to peni-
cillamine and gold . All other publications excluded
age as an independent predictive marker of response to
Ethnicity may play a role in predicting response to
DMARDs. Genetic differences influencing drug-metabo-
lizing enzymes can contribute to a differential response
between ethnic groups . This can have a tremendous
impact in either limiting the ability to generalize data
from clinical trials to different population groups or
choosing the best DMARD for a specific patient based on
his/her ancestry. This can be particularly relevant in
some European and North American geographical areas,
where patients’ origins can be very heterogeneous. Helli-
well and Ibrahim reported differences in DMARD drug
survival, with South Asian patients discontinuing therapy
sooner than patients from Northern Europe .
Although inefficacy was one of the reasons for drug dis-
continuation, it was only patient-reported and not objec-
tively measured and it seemed that other factors, such as
adverse reactions and different expectations concerning
the disease and treatment, may have weighed more than
efficacy in the decision to stop treatment. Moreover,
some authors found no association between ethnicity and
likelihood of response [44,45] and most studies do not
analyze its predicting role. Thus, despite the favorable
theoretical rationale, ethnicity is currently not a definite
predictor of response to MTX and other DMARDs and
more data with large populations are needed to clarify its
influence on responsiveness.
Smoking has a negative impact on disease outcomes
and is associated with higher disease activity [46-49]. In
addition to that, smokers seem to respond worse to
MTX. Although most studies on treatment response did
not analyze this factor, there seems to be a common con-
clusion in the ones that did: current smokers do respond
worse to MTX treatment, at least in early RA. Wessels
et al. showed that early RA patients who smoke and are
rheumatoid factor (RF)-positive have a worse response to
MTX monotherapy (OR = 0.1, 95% CI 0.0 to 0.4) . In
an early RA cohort, where 873 patients started MTX
monotherapy at inclusion, current smoking was indepen-
dently associated with significantly worse early and late
EULAR, disease activity score (DAS) 28 and joint count
responses, when adjusted for other clinical, serologic and
genetic factors (OR = 0.60, 95% CI 0.39 to 0.94) .
Past smokers’ responses did not differ from never-smo-
kers’ and number of pack-years smoked was not asso-
ciated with responsiveness . Data from the SWEFOT
trial confirmed these findings on a similar population
and current smoking was the strongest predictor of
achieving a poor response (OR = 0.35, 95% CI 0.20 to
0.63), according to all response criteria except ACR50
and ACR70 (although a trend for a poor response was
observed) . It has also been shown that smokers tend
to consume a higher number of DMARDs over time, sug-
gesting that smoking can reduce therapeutic efficacy and
that non-smokers are more likely to achieve an ACR
response than smokers . As proposed by Saevarsdot-
tir et al., smoking may interfere with the pharmacody-
namic and pharmacokinetic properties of the drugs, thus
altering responsiveness . Stamp et al. showed that the
intracellular levels of some MTX polyglutamates were
decreased in smokers , suggesting that MTX metabo-
lism is altered which leads to a poor response. Whatever
the mechanism, active smoking is an important modifi-
able factor that seems to be associated with a poor
response to MTX. Tobacco discontinuation should be
encouraged and considered an important part of the
Longer disease duration has been identified by Ander-
son and colleagues as the most important factor to pre-
dict worse response to MTX in the extensive meta-
analysis mentioned before , and similar findings were
reported in other publications, regarding both MTX and
other DMARDs [16,25,32,33,37,53,54]. However, Hoek-
stra et al.  failed to demonstrate such an association
in a RCT comprising 411 patients treated with MTX
(although the mean disease duration was lower) and sev-
eral other studies also did not detect that association
with MTX and other DMARDs [14,15,22,27,28,55-57]. It
has been widely shown that treatment of early RA yields
better results than treatment of established disease
[6,58-61] leading to the ‘window of opportunity’ concept
Romão et al. BMC Medicine 2013, 11:17
Page 4 of 24
[62-64]. Discrepancies in these results might have been
induced by evaluations performed mostly in established
RA patients, who probably have a more uniform response
to MTX, or in early RA populations that have short-term
disease and a narrow disease-duration span making it
harder to detect differences in response rates. Thus,
while it is likely that patients with early disease respond
better than those with established RA, disease duration
seems to lose its negative influence with long-term pro-
gression of disease and this might confound the results of
studies addressing this factor.
An additional question is whether the worse response
to treatment in established RA patients is a direct conse-
quence of longstanding disease by itself or if it is related
to the failure of previous DMARDs, as was previously
discussed by Hider et al. in their 2005 review .
Despite the existence of a few reports suggesting that
previous DMARD use does not affect response to further
treatments [28,55,57], most evidence seems to point in
the opposite direction. In fact, literature findings include
references to a negative effect of previous DMARD use
on the response to treatment with MTX and other
DMARDs , shorter time to DMARD discontinuation
in patients who had previously taken MTX  and
lower drug survival for DMARDs started following pre-
vious therapy and late in the course of the disease .
Likewise, Lie et al. found that patients who had pre-
viously taken other DMARDs had significantly lower
response rates to MTX monotherapy . Based on this
study, the absence of any past DMARD therapy was iden-
tified as one of the predictive factors of a favorable
response to MTX monotherapy . Similar findings
were reported by Aletaha and colleagues in patients tak-
ing consecutive DMARD courses, with the first DMARDs
obtaining a greater decrease in C reactive protein (CRP)
than subsequent ones . Another study found that the
effectiveness of a particular DMARD was always higher
when started after non-steroidal anti-inflammatory drugs
(NSAIDs) than after another DMARD . It may be
postulated that patients who do not respond to a certain
drug might have a globally more severe and less respon-
sive disease, but other mechanisms might explain these
observations. As proposed by Hider et al.  previous
therapies may alter drug kinetics and influence metabo-
lism in such a way that the effectiveness of subsequent
drugs can be lowered. However, this hypothesis has not
been adequately tested so far.
Disease activity at baseline has been thoroughly investi-
gated as a potential marker of response but globally the
results are inconsistent, which can be related to the differ-
ent clinical instruments and response criteria used in the
studies. In fact, disease activity can be assessed by isolated
clinical-laboratory variables (CRP, erythrocyte sedimenta-
tion rate (ESR)), tender joint count (TJC), swollen joint
count (SJC), global assessment of disease activity on a
visual analogue scale (VAS) or by composite scores (DAS,
DAS28, CDAI, simplified disease activity index (SDAI))
and different criteria are used to define response (EULAR,
ACR, DAS/SDAI remission). Thus, it is crucial to consider
this information when interpreting literature data. In the
meta-analysis by Drouin et al., high disease activity at
baseline as measured by DAS or SDAI was identified as a
predictor of a weak response to MTX monotherapy .
Wessels et al. showed that in an early RA population, high
DAS and high SJC were associated with a poor response
to MTX monotherapy, defined as achieving a DAS ≤2.4 at
6 months (OR = 0.1, 95% CI 0.0 to 0.1) . Other factors
such as VAS, ESR and CRP did not seem to have an effect
on response. In an established RA study, higher disease
activity defined by DAS was also related to a decreased
likelihood of response to MTX (OR = 0.53, P <0.001) .
These results are in accordance with the findings of Ale-
taha et al., that early RA patients with higher baseline
SDAI (but also CDAI and DAS28) were less likely to
achieve remission or low disease activity at one year of
MTX monotherapy . In this study, it was observed
that the association between disease activity and remission
at one year was low but significant at baseline and
increased greatly in subsequent visits, with SDAI at three
months being highly predictive of one-year remission.
Similarly, Saevarsdottir and colleagues found that higher
DAS28 at the moment of MTX start predicted a lower
likelihood of EULAR response (OR = 0.64, 95% CI 0.52 to
0.80), despite no significant association being shown for
ACR, SDAI or CDAI response criteria . Vázquez et al.
demonstrated that in early RA, patients with low to mod-
erate disease activity at baseline (DAS28 <5.1) were four
times more likely to be in remission (DAS28 <2.6) after
two years of MTX ± gold therapy. Two other studies also
demonstrated that in patients with recent onset RA trea-
ted with MTX, SSZ or both, a lower baseline DAS was
predictive of remission at two , three and five years
. Thus, the literature seems to show that when disease
activity is assessed by composite measures, lower activity
at baseline predicts better responses to MTX. Despite this,
baseline DAS28 was not different between responders and
non-responders to MTX monotherapy in other early 
and established [28,71] RA studies.
When disease activity is determined by isolated labora-
tory and clinical variables, evidence is much weaker and
somewhat inconsistent. Anderson et al. found lower
patient, but not physician, global assessment at baseline to
be predictive of worse response to MTX and other
DMARDs, a result that contradicts the data presented
above. Most studies, however, did not find isolated
patient/physician global disease assessment to influence
response to treatment with MTX [22,27,29,66,71] or other
DMARDs [27,29,34,45]. Wessels et al. showed high SJC to
Romão et al. BMC Medicine 2013, 11:17
Page 5 of 24
predict poor response to MTX in early RA , a finding
not confirmed in established RA . Ma et al. deter-
mined that a TJC higher than 5 at baseline decreased the
likelihood of achieving DAS remission at 24 months, with
no effect observed for SJC . Verstappen et al. identified
a lower Thompson joint score  at baseline as predic-
tive of remission at 62 months in patients treated with
MTX, gold or HCQ . However, SJC and TJC as iso-
lated variables were also shown not to be predictors of
response to treatment with MTX and other DMARDs in
several studies [14,24,27,28,34,70,71]. As a whole, these
data suggest that low disease activity defined by isolated
clinical variables is probably associated with a better
response to treatment, which is in accordance with the
above results for composite measures. However, they
should not be used as independent response predictors
because comprehensive scores, such as DAS or SDAI, are
better predictive tools. Similarly, inflammatory markers
are sometimes used to assess disease activity but, globally,
results are also far from being in consensus. In the meta-
analysis by Drouin , neither CRP nor ESR were predic-
tors of response to MTX monotherapy. These conclusions
were based on two studies, one of them identifying high
ESR to be associated with a worse response in established
RA  but the other, regarding early RA, only finding
this association in the univariate analysis ; both
showed no effect of CRP. Other studies regarding therapy
with MTX ± other DMARDs did not show any effect of
ESR and/or CRP on response to treatment [14,24,26-29,
70,71]. On the other hand, the study by Combe et al. iden-
tified ESR and CRP as two of the five independent predic-
tive factors of disability at five years in early RA patients
treated mainly with MTX and SSZ . As to other
DMARDs, Matteson et al. found that ESR did not influ-
ence response to HCQ monotherapy  but in another
study a low baseline CRP was the only predictor of
a favorable response to HCQ monotherapy in early RA
patients (OR (CRP ≤10 mg/L) = 3.6, 95% CI 2.2 to 6.0)
. van Roon and colleagues identified ESR <35 mm.h-1
at treatment start to predict higher leflunomide survival
(hazard ratio (HR) = 1.38, 95% CI 1.01 to 1.88)  and
likewise, high ESR at disease onset and at DMARD initia-
tion predicted early discontinuation of treatment in an
established RA study (HR = 1.05 per 10 mm.h-1increase,
95% CI 1.02 to 1.08) . Contrary to these findings,
Capell et al. observed that a lower ESR was related to a
worse response to gold, penicillamine or SSZ . As a
whole, these results are not sufficient to state whether ESR
or CRP alone are predictive factors of response to MTX
and other DMARDs. While some studies showed a signifi-
cant association between inflammatory markers and
response, usually with higher baseline values associated
with weaker treatment responses, others, including large
meta-analyses, do not find these variables to be good
predictive markers, at least when considered indepen-
dently. In the light of current evidence, for the purpose of
predicting DMARD response, it is probably better to inte-
grate ESR and CRP components as part of disease activity
scores and not judge them individually.
Disease severity and disability at baseline were also pro-
posed by some authors as being predictive of treatment
response. Anderson et al. identified a lower functional sta-
tus, according to the Steinbrocker criteria, to be associated
with a weak response to MTX and other DMARDs .
In two early RA studies, patients treated with MTX, SSZ
or both were more likely to be in remission (DAS < 1.6) at
two  or three years , if they had a low baseline
health assessment questionnaire (HAQ) score. Similarly,
in other early RA studies, a high HAQ at baseline pre-
dicted a poorer response to MTX monotherapy [22,25,45]
and to a combination with HCQ , with HAQ being
the only significant predictor of remission, using all remis-
sion definitions, in the paper by Saevarsdottir et al. (OR =
0.56, 95% CI 0.40 to 0.80) . However, several studies
showed contradictory results, with baseline HAQ not
being an independent predictor of responsiveness to MTX
[14,27-29,66,71,74] and other DMARDs [27,28,34,35,74].
While some studies seem to suggest that a higher HAQ
predicts a weaker response to MTX and other DMARDs,
several other studies with similar populations did not con-
firm this association.
Pain score was not identified as a predictor of clinical
response to MTX monotherapy in the review by Drouin
et al.  but, contrarily, Goetz and colleagues con-
cluded that a higher baseline pain score was associated
with poor response to therapy . In fact, while some
studies identified high pain scores to be associated with
lower four-year remission rates after treatment with
MTX, gold or HCQ  and lower responsiveness to
HCQ , most authors were not able to define baseline
pain as an independent predictor of clinical response to
MTX [22,24,27,29,45,66,69-71] and other DMARDs
[24,27,35,69,70], either in early or established RA. Thus,
it seems that evidence suggests that baseline pain scores
are not independent predictors of response to DMARD
Other factors have been studied and there are scattered
reports proposing them as possible predictors of
response. Concomitant NSAIDs use was associated with
an increased efficacy of MTX monotherapy in established
RA  and a similar significant but weak association
was seen in early RA (OR = 1.31, 95% CI 0.84 to 2.06)
. Most studies did not analyze the effect of NSAIDs
and so, given the small amount of evidence, further stu-
dies are needed to confirm this association, although a
beneficial effect may be expected. Results on concomitant
corticosteroid therapy are more difficult to interpret
because of different doses and timings for starting
Romão et al. BMC Medicine 2013, 11:17
Page 6 of 24
steroids (before DMARD therapy, during, or both).
Saevarsdottir and colleagues found that early RA patients
who were already on stable low-dose prednisolone at the
start of MTX responded better (OR = 2.84, 95% CI 1.43
to 5.63)  and Hider et al. showed that absence of ster-
oid use predicted MTX inefficacy at two years, but not at
one year . These results are in accordance with trials
that showed that patients treated with combination
therapies including steroids have better responses than
those on DMARD monotherapy [76-79], even though in
these studies steroids and DMARDs were started simul-
taneously. However, other studies found no association
between corticosteroid use and DMARD response
[24,34]. Despite these latter observations it seems likely
that patients on corticosteroid concomitant treatment
are more likely to respond to DMARD therapy. Erosion
and radiographic scores at baseline do not seem to be
reliable predictors of treatment response to DMARDs as
was shown in several reports [27,29,35,45,53,69,73,74].
Nongenetic biomarkers of response
Among nongenetic biomarkers, autoantibodies are prob-
ably the most important and most studied (Table 3). In
fact, RF and anti-citrullinated protein antibodies (ACPA)
are important markers with diagnostic and prognostic
roles in RA and were both included in the 2010 RA classi-
fication criteria . RF is associated with persistent dis-
ease and radiographic progression [21,81-83] but its role
in predicting response to treatment is less clear. A large
number of studies, comprising a considerable number of
patients, showed that RF status does not predict response
to MTX and other DMARDs in both early and established
RA [1,14,23,25,27-29,34,36,37,42,45,53,55,66,84]. However,
in the study by Wessels et al.  RF-positivity alone pre-
sented a trend towards worse response to MTX
monotherapy in early RA patients; RF-positive smokers
were definitely worse responders. Similarly, in a retrospec-
tive study with 265 patients, Morgan and colleagues found
that resistance to three or more DMARDs was more fre-
quent in RF-positive patients (OR = 2.15, 95% CI 1.00 to
4.62) . Verstappen et al. found RF-negativity to be
associated with four-year remission in early RA patients
started on HCQ, MTX or gold (b = 1.63; P = 0.061) .
Some authors found RF-positivity to be associated with
lower remission rates [70,81,86-89]. However, these stu-
dies analyzed remission as an outcome and, thus, these
results were more likely to be directly related to the role of
RF as a marker of more persistent and severe disease, and
not necessarily linked to treatment effectiveness. Overall,
most of the available evidence seems to show that baseline
RF status does not influence the effectiveness of DMARDs.
The presence and levels of ACPA are currently very
important in the diagnosis and prognosis of RA. Diag-
nostically, they are highly specific (higher than RF) and
have a good sensitivity (equal or slightly lower than RF)
[90-92]. In terms of prognosis they are associated with
worse functional status [93,94], higher disease activity
[95,96], severe radiographic progression [13,97-104] and
worse disease course [104-106]. Data are much scarcer
than with RF, but two early RA studies (n = 205 and
n = 405, respectively) showed that ACPA did not influ-
ence MTX effectiveness [22,25]. The study by Cao et al.
also found no differences in second-line DMARD
response between ACPA-positive and ACPA-negative
patients from an early RA cohort that had previously
failed first-line DMARD therapy . Likewise, Hod-
kinson et al. , Verschueren et al. , Vázquez
et al. , Boire et al. , da Mota et al.  and
Gossec et al.  found no association between ACPA
status and the likelihood of achieving low disease
Table 3 Summary of nongenetic biomarkers of response to MTX and other DMARDs.
RF No Some results confounded by its poor prognostic role; however, most evidence is clear in that it does not
influence treatment response
More data needed but does not seem to predict response; associated with worse outcomes in some studies
but may reflect more severe disease; interesting reports in UA, pending confirmation
Suggested to relate to more severe disease; not yet addressed in terms of response to treatment
Few studies analyzed this factor, no association with MTX response in a meta-analysis
Uncertain Anecdotal reports of association with better response; needs confirmation and its role should be clarified in
Small/pilot studies suggesting association with response; potential promising role of baseline TNF levels,
TNFID50and IL-1ra/IL-1b ratio
Other interesting factors analyzed in small studies and not further confirmed include MMP-3, urinary 7-OH-
MTX and IgG hypogalactosylation
Conclusions and comments are based on the findings reported and discussed in the text. ACPA, anti-citrullinated protein antibodies; anti-MCV, anti-modified
citrullinated vimentin antibodies; DMARDs, disease modifying anti-rheumatic drugs; Hb, hemoglobin; IgG, immunoglobulin G; IL-1ra, interleukin-1 receptor
antagonist; IL-1b, interleukin-1b; MMP-3, matrix metalloproteinase-3; MTX, methotrexate; RF, rheumatoid factor; TNF, tumor necrosis factor; TNFID50, dose required
to suppress by 50% the production of tumor necrosis factor; UA, undifferentiated arthritis; 7-OH-MTX, 7-hydroxy-methotrexate.
Romão et al. BMC Medicine 2013, 11:17
Page 7 of 24
activity or remission at 1, 2, 2.5, 3 or 5 years in
DMARD-naïve early RA patients treated with MTX
and/or other DMARDs. A recent subanalysis at 8-years
follow-up of the BeSt study (n = 484) specifically
addressed the association of ACPA with treatment
response. The analysis of all treatment groups as a
whole, including one arm starting with infliximab ,
showed that ACPA-positive patients responded as well
as those who were ACPA-negative, with similar
decreases in disease activity, remission rates and func-
tional ability, although they had worse radiographic pro-
gression and were less likely to maintain drug-free
remission. This last finding was reproduced by other
authors who found ACPA positivity to be associated with
inability to maintain drug-free remission for more than
one  or five years . However, there are some
contradicting results. In a study comprising 124 Japanese
patients treated with MTX or SSZ within one year of dis-
ease onset, ACPA positivity was strongly associated with
resistance to treatment (OR = 6.31, P = 0.027), but the
criteria used to define non-responders (starting anti-
tumor necrosis factor (TNF) agents during two years of
follow-up) was different from other studies and this must
be taken into account . Verstappen et al. 
recently found the presence of ACPA to be strongly asso-
ciated with initiation of biological therapy in an early
inflammatory polyarthritis population, although this was
not directly linked to failure of initial DMARD therapy
and may represent the effect of a more severe disease
that will require more aggressive therapy. On the other
hand, there are some studies that identified an associa-
tion of ACPA with decreased likelihood of achieving
remission at two  or eight years  in recent onset
RA. Other studies have also found a lower response to
treatment in ACPA-positive patients, in terms of the
magnitude of decrease in DAS28, ESR, CRP and other
clinical variables [102,105,114]. This may be just a reflec-
tion of the higher disease activity that characterizes
ACPA-positive disease and it is difficult to state with cer-
tainty that it represents a worse response to the treat-
ment instituted. Another issue raised by van Dongen et
al.  and already reported by others  concerns
the beneficial effect of MTX in delaying the progression
to RA in ACPA-positive undifferentiated arthritis (UA)
but not in ACPA-negative UA. This would suggest a
favorable effect of ACPA in terms of response to therapy,
but the follow-up analysis showed that in ACPA-positive
patients, non-responders had higher pretreatment ACPA
levels, a finding confirmed in a similar population of
patients from the BeSt study . Although the number
of patients was small, these results would suggest that
while MTX is more effective in UA patients who are
ACPA-positive and, thus, probably at a higher risk of
developing RA, the titer of this antibody is inversely
related to the response to MTX. Larger studies are
needed to confirm this potential effect. Overall, evidence
does not support the role of ACPA as predictive markers
of response to MTX and other DMARDs. Despite some
opposite results in terms of remission and response to
treatment, the strong prognostic value of this marker
associated with worse disease outcomes must be taken
into account when analyzing the results and can some-
times disturb the distinction between poor response to
treatment and poor prognosis per se. Interesting findings
on UA need further confirmation with larger populations
and, as suggested by Visser et al. , pretreatment
ACPA levels should be obtained in studies analyzing
response to treatment.
The evidence presented above for ACPA was based on
studies using the most common assay, the second-gen-
eration anti-cyclic citrullinated peptide (anti-CCP2).
Recently, another test targeting modified citrullinated
vimentin (anti-MCV) was developed to identify a parti-
cular member of the ACPA family . While its cur-
rent role is not clearly defined in RA, it seems to be as
good as anti-CCP2 as a diagnostic marker, with sensitiv-
ity and specificity of 62% to 84% and 83% to 95%,
respectively, being reported in the literature [118-122].
However, in terms of prognosis there are contradicting
results. Anti-MCV was associated with more severe and
erosive disease in some studies [109,120,123,124], with a
clear correlation with disease activity. In this case, high
anti-MCV levels could relate to more active disease and
possibly lower response to treatment. However, neither
this association [119,122,125-128] nor this correlation
was observed by other authors [126-128] and to our
knowledge, the impact of anti-MCV status on response
to DMARD treatment was not specifically addressed in
the studies published to date. It would be of interest to
further analyze the role of this antibody as a potential
predictive marker of response in future investigations.
Other biomarkers have been studied as potential pre-
dictors of response to treatment. ESR and CRP have
been discussed earlier, as markers of disease activity.
Creatinine clearance was inversely related to MTX
efficacy in one established RA study  but the asso-
ciation was weak (OR = 0.99, 95% CI 0.98 to 1.0) and
no statistically significant difference was observed in
other studies , including a meta-analysis evaluating
11 RCT (n = 496) that specifically addressed the influ-
ence of renal function (and age) on MTX responsiveness
. Serum creatinine levels were also demonstrated to
be non-predictors of leflunomide treatment survival 
but data on other DMARDs are even scarcer. High
hemoglobin levels were associated with remission
(DAS28 <2.6) at two years in the univariate analysis in
early RA, DMARD-naïve patients. However, it was not
an independent predictor of remission when assessed by
Romão et al. BMC Medicine 2013, 11:17
Page 8 of 24
multivariate logistic regression analysis . In a recent
study with a similar population, high hemoglobin levels
independently predicted a low disease activity state
(SDAI <12) after two years of therapy with MTX ± SSZ
± chloroquine sulfate . Although most studies
regarding treatment response do not analyze the role of
baseline hemoglobin levels as a potential predictive mar-
ker, it is known that persistent inflammation can lead to
anemia, particularly through the action of IL-6 ,
and low hemoglobin levels have been associated with
more active and severe RA . Thus, while hemoglo-
bin concentration may constitute an indirect marker of
disease activity, caution is required when interpreting
response to treatment, because the suggested association
of high hemoglobin and a low disease activity at follow
up may simply reflect a milder disease, with less inflam-
mation, lower activity scores and not necessarily a true
correlation with better DMARD effectiveness. Neverthe-
less, as a simple, cheap and widely available laboratory
variable, it would be interesting if upcoming studies ana-
lyzing treatment response include hemoglobin levels and
further investigate whether it may play a true role as a
Being involved in the pathogenesis of RA , cyto-
kines are also influenced by MTX and other DMARDs
[132,133]. Therefore, they are an appealing potential bio-
marker of response to treatment and have been evaluated
in some studies. Baseline serum concentration of TNF
was inversely associated with six-month response to
MTX and other DMARDs, and levels below 20.1 pg/mL
could independently predict responders with high specifi-
city and sensitivity, in a small sample of both early and
established RA patients (n = 38) . No effect was seen
regarding IL-1b, IL-6, IL-8, IL-10 and IL-12. However, in
a study of 50 consecutive established RA patients who
had already failed one to three DMARDs, pretreatment
serum TNF and IL-1b levels were undetectable in the
majority of patients and did not predict response to treat-
ment; neither did serum levels of IL-1 receptor antago-
nist (IL-1ra) or soluble TNF receptor (sTNFR) p55 .
In this study, though, a significant association was seen
between a low IL-1ra/IL-1b synthesis ratio of unstimu-
lated pretreatment peripheral blood mononuclear cells
(PBMC) and good/excellent responses to MTX: an
IL-1Ra/IL-1b ratio lower than 100 strongly predicted an
ACR response higher than ACR50 (P <0.0001), with posi-
tive and negative predictive values of 94% and 91%,
respectively . It has also been demonstrated that
baseline IL-10 production by PBMC was higher in MTX
responders than in non-responders . Another study
comprising a reduced number of early RA patients (n =
8) reported a correlation between a higher baseline per-
centage of IL-4 positive CD4+ T cells and low disease
activity at six to nine months of MTX treatment , a
finding in line with other data suggesting a relationship
between a low IFN-/IL-4 ratio and better nine-month
response to HCQ and SSZ . Low pretreatment levels
of soluble IL-2 receptor (sIL-2R, <442 U/mL), translating
reduced T-cell activation, predicted six-month remission
in early RA patients treated with SSZ monotherapy ,
an association not confirmed in patients with established
disease treated with MTX (mean disease duration >10
years)  or SSZ/gold (mean disease duration >5
years) . A small study reported that in 14 early RA
patients treated with HCQ, soluble CD30 (sCD30) basal
levels were higher in responders than in non-responders
(P <0.03), which might be related to a higher activity of
Th0/Th2 anti-inflammatory cells . This was not
confirmed in a study of 92 RA and UA patients treated
with MTX and other DMARDs, where baseline sCD30
levels did not associate with treatment response at one
year . In a pilot experimental study (n = 25), the
MTX-induced in vitro inhibition of T-cell cytokine pro-
duction was studied and a strong negative correlation
was found between clinical response at four months and
the dose required to suppress by 50% the production of
TNF (ID50, r = -0.62, P <0.01) . Patients with a
TNFID50lower than 224 ng/mL had a significantly
greater reduction in DAS28 after four months of MTX
treatment than those with a value above this cutoff
(P <0.02), which had a sensitivity of 93% and a specificity
of 86% for predicting patients with a moderate EULAR
response. Since the effect was so pronounced, in vitro
suppression of TNF is an interesting assay that may pre-
dict response to MTX and guide individual therapeutic
decisions; to date and to our knowledge, validation in a
larger cohort is pending. As a whole, the data concerning
cytokines confirm their potential as predictors of treat-
ment response. Despite the elevated cost associated with
most of these assays, they may enable individualized ther-
apy in RA patients if clear associations are confirmed in
other, larger, studies.
Reports concerning other biological markers are avail-
able but no definite conclusions can be taken regarding
their true role as predictive markers, because most studies
were pilot studies, based on small samples and their find-
ings were not further validated. These include hypogalac-
tosylation of IgG , serum matrix metalloproteinase-3
(MMP-3) levels [145,146], urinary levels of the less effec-
tive MTX catabolite, 7-hydroxy-MTX , red blood cell
(RBC) levels of MTX polyglutamates (MTX PG), the
active anti-inflammatory metabolites of MTX [148-152]
and synovial vascularity .
Genetic biomarkers of response
Pharmacogenetics may provide an objective explanation
for the discrepancies observed in response to DMARDs
among patients: the genetic characteristics of each
Romão et al. BMC Medicine 2013, 11:17
Page 9 of 24
patient might interact with a certain drug, interfere with
its pharmacokinetics or target, thus affecting its pharma-
cological action and ultimately leading to different
effects. Intense efforts have been focused on the pursuit
of polymorphisms and genetic patterns that associate
with increased or decreased drug response and the
major findings are summarized in Table 4.
HLA-DRB1 shared epitope (SE) alleles are well-estab-
lished risk factors for RA [154,155] and are associated
with more severe and erosive disease [156-159]. However,
their influence on DMARD effectiveness is not clear
despite several studies that have tried to approach this
question. O’Dell et al. showed that SE-positive patients,
who had previously failed one DMARD, were much more
likely to obtain ACR50 responses if they were on combina-
tion treatment (MTX plus SSZ plus HCQ) compared to
MTX monotherapy (94% and 32% responders, respec-
tively; P <0.01), with no difference being seen in patients
who were SE-negative (n = 84) . Additionally, patients
on MTX monotherapy responded better if they were
SE-negative (83% and 32%, respectively, P <0.04), an
effect that was lost in the combination treatment group.
Similarly, Ferraccioli and colleagues demonstrated that, at
six months, HLA-DR 0401-positive patients responded
worse to MTX monotherapy (29% and 80% responders,
respectively) and better to cyclosporine (52% and 5.8%,
respectively) than those who were HLA-DR 0401-negative
. Hider et al. studied 309 patients from an inception
cohort with inflammatory polyarthritis and found that the
possession of the HLA-DRB1 SE was the only factor pre-
dicting MTX monotherapy inefficacy at one and two
years, with a strong association (adjusted OR = 5.88 and
3.04, respectively, both P = 0.02). In the recent Japanese
study mentioned above , early RA patients carrying
one or two copies of the SE-positive HLA-DRB1*04 allele
(especially *0405) were more likely to be resistant to
DMARD therapy (predominantly MTX) at two years (OR
= 2.89, P = 0.011), an effect not seen with other SE-posi-
tive alleles. In line with these findings, González-Gay et al.
previously reported that patients positive for SE alleles
were significantly more likely to be treated with cyclospor-
ine A, because of insufficient response to MTX or MTX
plus chloroquine (OR = 2.9, P = 0.006); the strongest risk
for requiring cyclosporine A treatment was seen with the
HLA-DRB1*0401/*0404 genotype . Yet, in a Pakistani
population of 91 RA patients, the only SE allele associated
with response to treatment was HLA-DRB1*03, signifi-
cantly more common in non-responders, with no effect
being observed in other alleles, including DRB1*04 and
DRB1*01 . As a whole, these studies indicate that SE-
positive patients may respond worse to MTX and that the
HLA-DRB1*04 allele (and maybe also HLA-DRB1*03)
plays an important role in this effect. However, several
authors failed to show an association between SE-status
and induction [27,37,70] or persistence  of remission
in patients treated with MTX and other DMARDs, while
Table 4 Summary of genetic biomarkers of response to MTX and other DMARDs.
Factors Predictors of
SE Yes, worse response
response to MTX
SE-positive patients seem to respond worse to MTX, especially carriers of the HLA-DRB1*04 allele;
association with remission controversial; not extendable to other DMARDs
80G>A: evidence suggests favorable response in variant allele carriers, although some studies did not
confirm it; other identified SNPs may have a role and explain discrepancies
3435C>T: several studies suggesting association with better response, not confirmed in others
Not thoroughly studied
Conflicting results regarding SNPs 401C>T, 452C>T and 16T>C
Few studies; contradicting findings with SNP 14G>A, no association of 14G>A with response in two
TSER *R/*R: opposite results suggesting better responses for both 2R/2R and 3R/3R and others showing
6 bp-del: favorable role suggested, but not found in other studies
Several SNPs described but addressed in single studies; 317A>G was the only one associated with
response but only when using rDAS28 and with marginal effect
347C>G is the most studied, but conflicting results did not allow a definition of its role; other SNPs have
been identified and associated with response in a few studies but lack replication
677C>T and 1298A>C have been extensively studied and two large meta-analysis found no association
with MTX effectiveness
Several reports of SNPs combinations associated with response, but lacking replication
Conclusions and comments are based on the findings reported and discussed in the text. ABC, ATP-binding cassette (B1, C1-4 and G2); ATIC, 5-aminoimidazole-4-
carbox-amide ribonucleotide transformylase; DMARDs, disease modifying anti-rheumatic drugs; DHFR, dihydrofolate reductase; FPGS, folylpolyglutamate
synthetase; GGH, g-glutamyl hydrolase; HCQ, hydroxychloroquine; HLA, human leukocyte antigen; MTHFR, 5,10-methylene-tetrahydrofolate reductase; MTX,
methotrexate; rDAS28, relative disease activity score - 28 joint; RFC1, reduced folate carrier 1; SE, shared epitope; SNPs, single nucleotide polymorphisms; TYMS,
Romão et al. BMC Medicine 2013, 11:17
Page 10 of 24
others found the absence of SE alleles to be associated
with DMARD-free remission  or remission to be
more likely in patients with ≤1 SE-allele . Few studies
have analyzed other DMARDs in monotherapy regimens
[34,164]. Globally, SE seems to influence response to
DMARD treatment, with an apparent negative effect on
MTX response, and further studies analyzing predictors of
response should include this genetic marker in order to
clarify its true influence on drug effectiveness.
Figure 1 illustrates the MTX cellular pathway and mode
of action. Single nucleotide polymorphisms (SNPs) in
genes codifying proteins involved in this process have
been identified and thoroughly studied for their influence
on the response to MTX.
Regarding membrane transporters, reduced folate carrier
1 (RFC1) 80G>A may influence influx of MTX into the
cell, but its influence on drug responsiveness is not clear.
It has been reported that patients with the RFC1 80A/A
genotype have a greater response to MTX (based on sev-
eral disease activity measurements) than wild-type 80G/G
patients: lower global VAS , lower SJC and disease
activity VAS , better EULAR responses  and a
3.32-fold higher probability of achieving remission (P =
0.021, n = 174), with statistically significant differences in
the A allele prevalence between good and poor responders
(62.1% and 47.8%, respectively, P = 0.013) . Other
relevant findings include higher RBC MTX PG levels in
AA homozygous RA patients compared to other geno-
types (P = 0.007) , higher MTX plasma levels in AA
children with acute lymphoblastic leukemia (P = 0.004)
 and lower uptake of MTX in CD4+ T cells and B
cells in healthy individuals expressing the GG genotype,
compared to those having the A allele . These argu-
ments seem to support a favorable role for the RFC1
80G>A SNP as a predictor of good response to MTX, but
other authors have failed to confirm its association with
MTX efficacy [150,152,171-173]. Caution must be taken
regarding interpretation of RBC MTX PG levels, because
currently it is not absolutely certain that they represent
the actual concentration of these metabolites inside other
important cells in RA such as leucocytes or synovial cells
. Furthermore, a recent study identified six other
SNPs in the RFC1 gene associated with poor response to
MTX, which contributes to the hypothesis that other poly-
morphisms in this gene may also affect the response to
MTX, thus providing an explanation for the contradictory
results in some of the studies .
ATP-binding cassette (ABC) B1 (ABCB1) codifies P-
glycoprotein, a cell membrane-associated transporter of
several drugs. Its influence on MTX efflux is unclear
[175,176]. Nevertheless, the effect of ABCB1 SNPs has
been studied, particularly that of 3435C>T. Pawlik et al.
showed that patients with the 3435TT genotype were
2.89 times more likely to respond to MTX than those
carrying one or two C alleles (n = 92)  and, like-
wise, Drozdzik and colleagues found a 4.65-fold higher
probability of symptom remission in TT-positive
patients, compared to those with the CC genotype (n =
174, P = 0.003) . A recent study also reported
lower mean DAS28 in 3435TT patients compared to the
3435CC genotype (P = 0.02) . On the other hand,
an Asian study found that patients with the 3435TT
SNP were nonresponders more frequently than patients
with the 3435CC genotype (adjusted OR = 8.78, P =
0.038) . However, these differences may be related
to the response criteria applied, which in this study
were based on MTX maintenance dose (responders if
dose was below 6 mg/week, nonresponders if MTX dose
was above 6 mg/week) and not directly on the evolution
of symptoms or disease activity. Additionally, other
authors found no association between ABCB1 3435C>T
and MTX efficacy [179,180]. Despite the description of
frequent SNPs in other transport proteins involved in
the efflux of MTX from the cell, such as ABCC1-4 and
ABCG2 , they have not been thoroughly addressed
regarding MTX effectiveness in RA; there are some
reports of better response to MTX in psoriasis patients
carrying SNPs for ABCC1 and ABCG2  but
recently three SNPs in ABCC2 and ABCG2 genes were
not related to MTX response  and further studies
are needed to clarify their true influence.
As to the enzymes involved in the glutamation cycle of
MTX inside the cell, g-glutamyl hydrolase (GGH) is the
most studied one. The SNP 401C>T of the promoter
region of GGH was shown to influence MTX PG levels,
which were lower in patients carrying the TT genotype
compared to those with one or two C alleles (OR = 4.8,
P = 0.002) . However, the same group of researchers
did not find any effect of this SNP on response rates to
MTX in a prospective longitudinal study (n = 48) .
Other SNPs in GGH include 452C>T, that has been asso-
ciated with decreased enzyme activity and accumulation of
intracellular MTX PG , but was found not to influ-
ence MTX efficacy [152,173,184]. The role of folylpolyglu-
tamate synthetase (FPGS) has been less studied. Although
its expression in PBMC has been associated with poor
response to MTX , an unexpected result given the role
it is thought to have in converting MTX to its active form,
the SNPs of the FPGS gene identified so far are of unclear
functional and clinical significance . Two studies
failed to demonstrate an association between the SNPs
14G>A and 1994A>G and MTX response [173,184], but
Sharma et al. showed that carriers of the A allele of the
14G>A SNP responded worse (OR = 3.47, 95% CI 1.19 to
10.12) . Thus, more data is needed to evaluate its
influence on drug responsiveness.
MTX PG inhibit several enzymes, including thymidy-
late synthase (TYMS), dihydrofolate reductase (DHFR),
Romão et al. BMC Medicine 2013, 11:17
Page 11 of 24
5-aminoimidazole-4-carbox-amide ribonucleotide trans-
formylase (ATIC) and, indirectly, 5,10-methylene-tetra-
hydrofolate reductase (MTHFR) (Figure 1). TYMS is
involved in the de novo synthesis of thymidylate,
required for cell proliferation. A polymorphic tandem
repeat sequence in the promoter region of the TYMS
gene has been described, with a variable number of
28 bp repeats (TSER *R/*R) . Dervieux et al. found
TSER 2R/2R patients responded better to MTX than
patients with other genotypes, based on physician VAS
. Similarly, a Japanese study reported that patients
with the TSER 3R/3R genotype required higher MTX
Figure 1 Methotrexate mode of action. Methotrexate (MTX) is actively transported into the cell by the reduced folate carrier 1 (RFC1; also
known as SLC19A1) and is then polyglutamated by folylpolyglutamate synthetase (FPGS) to form MTX polyglutamates (MTX PG), which are kept
inside the cell  and are responsible for MTX anti-inflammatory intracellular actions [17,174]. Glutamates can be removed by g-glutamyl
hydrolase (GGH) and MTX monoglutamate is rapidly effluxed from the cell via membrane transporters of the ATP-binding cassette (ABC) family
, especially ABCC1-4 and ABCG2 [223,224]. Inside the cell, MTX PG exert their anti-inflammatory actions through inhibition of essential
enzymes of the folate pathway: dihydrofolate reductase (DHFR) , blocking the conversion of dihydrofolate (DHF) to tetrahydrofolate (THF)
and ultimately leading to depletion of methionine and decreased DNA methylation; thymidylate synthase (TYMS) [226,227], interfering with
de novo pyrimidine synthesis; and 5-aminoimidazole-4-carbox-amide ribonucleotide (AICAR) transformylase (ATIC) [148,228], an enzyme of the
de novo purine synthesis, causing accumulation of AICAR, which will finally result in increased secretion of adenosine, a strong anti-inflammatory
mediator [229,230]. The enzyme 5,10-methylene-tetrahydrofolate reductase (MTHFR) is not directly inhibited by MTX, but is affected by it because
of its action in the folate pathway . ADA, adenosine deaminase; AMPd, adenosine monophosphate deaminase; dTMP, deoxythymidine
monophosphate; dUMP, deoxyuridine monophosphate; FAICAR, 10-formyl 5-aminoimidazole-4-carboxamide ribonucleotide; IMP, inosine
monophosphate; Methyl-THF, 5-methyl-tetrahydrofolate; Methylene-THF, 5,10-methylene-tetrahydrofolate; MS, methionine synthase; SHMT, serine
Romão et al. BMC Medicine 2013, 11:17
Page 12 of 24
doses than those carrying at least one allele with two
repetitions (P = 0.033) . Another study also found
that the 3R/3R genotype was associated with worse
response to treatment, as part of a pharmacogenetic
index comprising SNPs of other genes (RFC1 and ATIC)
. However, the same group found that after adjust-
ment for MTX dose and RBC MTX PG levels, 2R/2R
patients were less likely to respond, with no association
being observed in unadjusted data . Furthermore,
James et al. reported better 12-month EULAR responses
to MTX in patients carrying one or two 3R alleles trea-
ted with MTX, SSZ and HCQ ; other authors
found no association between MTX response and TSER
status [22,173,189]. Another polymorphism has been
identified which consists of a 6-bp deletion at the 3’-
UTR region of the TYMS gene  and is associated
with decreased mRNA stability and expression
[190,191]. Japanese patients homozygous for this dele-
tion have been shown to have greater reductions in CRP
(P = 0.0383)  and a lower MTX dosage required
for a 50% decrease in CRP (b = -0.268, P = 0.039) 
compared to other genotypes, although other studies did
not find an association between this polymorphism and
MTX response [172,173]. James et al. reported that
Australian patients homozygous for the 6-bp deletion
were all classified as responders (10 versus 0) and a
similar non-statistically significant trend was seen for
the 6-bp deletion allele as a whole . These authors
also found the 3R-del6 haplotype to be clearly associated
with a better clinical response to MTX plus SSZ and
HCQ (OR = 2.9, 95% CI 1.0 to 9.2) and defended the
concept that while currently it is not known which poly-
morphism of the TYMS gene is better in assessing MTX
efficacy, haplotype analysis should be used in future stu-
dies analyzing response to treatment .
DHFR is a major direct target of MTX PG and, as
such, polymorphisms affecting its expression, function,
or binding to MTX may interfere with response to treat-
ment . A Japanese study identified a SNP in the 3’-
UTR of the DHFR gene (829C>T), with homozygous
829TT patients having significantly higher expression of
the enzyme (P <0.001) . However, the effect of this
SNP on response to treatment is unknown and one
study of a European population found patients to be
100% CC wild-type and thus no 829TT patients were
detected . Wessels et al. found no association
between SNPs 473G>A or 35289G>A and MTX efficacy
 as was the case in the study from James et al. on
the 19 bp deletion in intron 1 of DHFR gene . A
recently published study analyzed the role of SNPs
216T>C and 317A>G and reported no difference in
these genotypes between responders and non-respon-
ders, using the EULAR response criteria; the authors did
find a significant difference, though, when using relative
DAS28 (rDAS28, improvement related to baseline value)
as a measure of MTX efficacy, with the 317AA genotype
being associated with worse response (P = 0.05) .
Additional, larger studies are needed to confirm this
ATIC is the third enzyme directly inhibited by MTX
and it is involved in the de novo purine synthesis and
adenosine cycle (Figure 1). The most studied SNP has
been the 347C>G and, as with other markers, results
have been contradictory. Dervieux et al. identified the
GG genotype to be associated with lower physician VAS,
SJC [149,187] and TJC, as part of a pharmacogenetic
index ; similar findings were found by Lee et al.
using a proxy SNP in linkage disequilibrium with
347C>G (OR = 3.89, P = 0.01) . However, these
were cross-sectional studies analyzing disease activity at a
single visit in patients treated with MTX and did not
consider baseline scores. This might explain the differ-
ences with the findings reported by Wessels et al. in two
analyses of the BeSt study population, in which patients
with the wild-type homozygous 347CC allele were more
likely to respond to MTX, after adjustment for baseline
DAS28 [22,196]. Additionally, several authors found no
association between 347C>G SNP and response to MTX
[150,166,172,173,197]. Although differences might be
related to different populations, stages of disease and
study designs, it is currently unclear which is the true
effect of this SNP on the effectiveness of MTX. Other
SNPs have recently been identified with different associa-
tions to drug response [173,194]. Overall, ATIC poly-
morphisms seem to play a significant role in determining
MTX effectiveness, which strengthens the great impor-
tance that adenosine is thought to have on the MTX
mode of action.
Among all genes potentially influencing MTX efficacy,
MTHFR is the best studied. This enzyme is responsible
for the conversion of 5,10-methylene-tetrahydrofolate to
5-methyl-tetrahydrofolate, which is essential to the con-
version of homocysteine to methionine . Albeit not
a direct target, it is influenced by MTX because of its
effects on the intracellular folate pool . Two SNPs
have been thoroughly investigated in the last decade,
with conflicting results. The 677C>T SNP leads to a
thermolabile form of MTHFR with reduced activity
 and among Caucasians around 50% carry at least
one T allele , up to 40% are CT-heterozygous (60%
enzyme activity) and approximately 10% are TT-homo-
zygous (30% enzyme activity) . The 1298A>C SNP
also leads to reduced MTHFR activity, although less
severely than the previously mentioned SNP , with
the variant allele being present in 32% of the Caucasian
population . These polymorphisms seem to inter-
act, as individuals heterozygous for both 677C>T and
1298A>C have greater decreases in enzyme activity,
Romão et al. BMC Medicine 2013, 11:17
Page 13 of 24
comparable to those homozygous for the 677C>T SNP
. Regarding the 677C>T SNP, although some
authors reported better or worse six-month responses in
patients with CC [171,204] or TT  genotypes,
respectively, and higher rates of remission in carriers of
the T allele , a striking number of studies showed
no association between 677C>T and MTX efficacy
[152,166,188,189,195, 206-215]. In a similar way, data
for the 1298A>C SNP is also controversial: while some
authors found better responses in 1298AA-positive
patients compared to other genotypes [152,171,204],
others, on the contrary, reported that C-allele carriers
had lower MTX maintenance doses [208,209] and a
non-significant tendency for higher remission rates
. Most studies failed to identify an association
[150,166,188,189,210-215]. Moreover, to overcome the
discrepancies observed for these polymorphisms two
meta-analyses have recently been performed, which
included a large number of studies and patients (n =
2,614 and 1,514, respectively), and in both the authors
concluded there was no association between 677C>T/
1298A>C and treatment response to MTX [213,216].
Thus, currently it is not possible to use MTHFR SNPs
as reliable predictors of response to treatment.
Overall, studies evaluating the role of individual SNPs
on response to MTX have been inconsistent. This may
be related to different study designs, insufficient statisti-
cal power and several clinical and pharmacological con-
founders, such as ethnicity, outcome measures used,
folate supplementation, MTX dose, duration and route of
administration and concurrent therapies . While
large prospective studies are missing, meta-analysis may
overcome this problem, but because there are numerous
pathways and a considerable number of targets that can
be affected by MTX, an individual genetic variant within
a single gene is unlikely to result in a significantly altered
response, enough to be detected and replicated in differ-
ent studies. As such, it is probably more advantageous to
address more than one gene and polymorphism simulta-
neously through polygenic analyses, haplotype analyses
or gene-gene interactions. Other approaches include
interaction of genetic and nongenetic factors and even, as
proposed by Stamp et al., genome-wide association stu-
dies, which would obviate selection biases and might
identify other potential predictors of response not
included in current studies . Examples of polygenic
analysis include the studies by Dervieux et al., analyzing
SNPs of different genes (ATIC 347C>G, TSER 2R/3R,
RFC1 80G>A) as part of a pharmacogenetic index, a sum
of the homozygous variant genotypes [149,187]. Higher
indexes (that is, more variant SNPs) were associated with
lower SJC, TJC and disease activity VAS [149,187], as
well as with an increased probability of good response,
with patients with at least one homozygous variant being
3.7 times more likely to have a good response to MTX
than those with none (OR = 3.7, P = 0.01) . Com-
parably, Wessels and colleagues investigated polymorph-
isms in genes involved in the adenosine pathway, such as
adenosine monophosphate deaminase (AMPD1) 34C>T,
ATIC 347C>G and inosine triphosphate pyrophosphatase
(ITPA) 94C>A, and found that patients carrying the
AMPD1 34T allele, ATIC 347CC or ITPA 94CC had a
greater likelihood of having a good response, which was
significantly increased if all three favorable genotypes
were present (OR = 27.8, 95% CI 3.2 to 250.0) .
These SNPs, alongside methylene-tetrahydrofolate dehy-
drogenase (MTHFD1) 1958G>A, were further included in
a clinical pharmacogenetic model that proved to be effec-
tive in predicting response to MTX . Haplotype ana-
lyses have been conducted in some studies. Urano et al.
found the MTHFR 677C-1298C haplotype to be asso-
ciated with lower MTX dose (RR = 2.14, P <0.05), while
no effect was seen in single locus analysis of the 677C>T
SNP . van der Straaten and colleagues found no
association between individual SNPs and MTX efficacy,
but identified patients with the GGH 16C-allele and one
or no copies of the GGH 452C-16T haplotype as having
good clinical improvement at three months, although
they concluded that globally the SNPs tested were not
likely to be predictive of treatment response . Simi-
larly, as mentioned above, James et al. found the 3R-del6
haplotype of the TYMS gene to significantly correlate
with response to treatment . These authors also
demonstrated interaction between different SNPs, with
patients having the 5-methyltetrahydrofolate-homocys-
teine methyltransferase (MTR, which codifies for methio-
nine synthase) 2756A allele in combination with either
the RFC1 80A allele or the TYMS 3R-del6 haplotype
being 35 times more likely to respond to MTX plus SSZ
and HCQ (P <0.0001) and 3.4 times more likely to
achieve remission (P = 0.04) . Hayashi et al. found
patients with the RFC1 80AA genotype to respond better
if they had no GGH 401T alleles, suggesting an interac-
tion between these two SNPs . In the study by
Sharma and colleagues a modest interaction, associated
with MTX efficacy, was seen between ABCB1 3435C>T
and GGH 16T>C (P = 0.05) . Dervieux et al.
recently published two studies addressing this issue and
found high-order interactions among SNPs in RFC1,
ITPA and ATIC genes, which were associated with effi-
cacy (3.89-fold lower likelihood of response in the
absence of favorable combinations, P <0.001) ; on
the other study, the authors reported an association
among three interacting SNPs (RFC1 80G>A, ITPA
94C>A and ATIC 347C>G) and MTX efficacy (OR = 2.9,
P <0.01), although it was not replicated in a different
cohort . While more studies are needed to
Romão et al. BMC Medicine 2013, 11:17
Page 14 of 24
reproduce these findings, as a whole, the analysis of dif-
ferent SNPs in various genes involved in the response to
MTX and the interactions between them seems to be a
promising approach that may bring more consistency to
the body of data on MTX pharmacogenetics.
We found a high discrepancy between studies’ results,
making it difficult to obtain clear-cut predictors of
response to MTX and other synthetic DMARDs (Tables 2,
3 and 4). This might be related to the heterogeneity in
study types, population size and ethnicity, disease charac-
teristics and outcome measures applied. While some fac-
tors (female gender, established disease, previous DMARD
use, smoking, high disease activity determined by compo-
site scores, absence of concomitant corticosteroids, SE-
positivity) seem to be individually associated with a weaker
response to MTX, drug effectiveness is ultimately the
result of multiple clinical and biological (genetic and non-
genetic) variables that interact to determine whether a
patient responds or not to a particular drug. This explains
why in most studies baseline factors merely associate
weakly with better or worse response but individually fail
to distinguish responders and nonresponders .
In line with this hypothesis, recent studies addressing
different types of factors and the interaction between them
have been shown to constitute a very promising approach
to define, at drug start, which patients will respond and
which will not [22,173]. In the study by Wessels et al., the
authors applied a clinical pharmacogenetic score including
clinical, genetic and nongenetic variables found to be asso-
ciated with treatment response (gender, RF, DAS, smoking
status, AMPD1 34C>T, ITPA 94C>A, ATIC 347C>G and
MTHFD1 1958G>A) and correctly classified around 54%
of the patients as responders or nonresponders (42% for
responders and 63% for nonresponders); furthermore,
scores of ≤3.5 had a positive predictive value of 95% and
scores ≥6 had a negative predictive value of 86% .
When the genetic variables were removed from the model,
the set of clinical and biological nongenetic factors cor-
rectly predicted response in only 29% of the cases (36% for
responders and 23% for nonresponders), although positive
and negative predictive values were still very high (89%
and 92%, respectively) . These findings clearly rein-
force the notion that considering groups of potential
predictive factors will be more efficient than simply ana-
lyzing them individually. Thus, including clinical, genetic
and nongenetic biological factors is more effective than a
parallel approach. Yet, this model has not been applied
routinely in other populations or studies and to date few
authors have replicated this type of approach, with most
studies still focusing on searching for associations between
individual markers and treatment outcome.
In this review, we were able to identify factors that seem
to be associated with response to treatment, especially
regarding clinical markers where the amount of evidence
is greater (Table 2). Female gender, smoking, established
disease, previous DMARD use, high disease activity mea-
sured by composite scores and the absence of concomitant
corticosteroids are associated with a lower response to
MTX. This is consistent with the results of the meta-ana-
lysis by Drouin et al. , with the difference that smoking
was considered together with RF-positivity for early RA
only and that corticosteroids were not shown to be predic-
tive of clinical response to MTX.
A few comments should be made on these results.
First, analyzing a significant number of studies for each
factor may help overcome heterogeneity by giving a glo-
bal view of the data and determining the direction evi-
dence is pointing at; second, caution is required when
interpreting results of individual negative studies; third,
several studies consider MTX in association with other
DMARDs, making it difficult to ascertain whether the
observed effect in those cases is the result of MTX itself,
the associated DMARD or the combination of both; and
finally, given the paucity of studies specifically analyzing
other DMARDs, it seems inappropriate to extend these
conclusions to drugs other than MTX.
Biological markers, both genetic and nongenetic, have
also been extensively studied. Despite some exceptions,
most of the results lack confirmation and replication in
larger studies (Table 3 and Table 4). The exceptions are
RF, ACPA and SE, all thoroughly analyzed, given their role
as predictors of poor prognosis. While most evidence
points towards an absence of effect of RF on DMARD
effectiveness (except for some early RA studies), SE-posi-
tivity (and especially the HLA-DRB1*04 allele) seems to be
associated with a worse response to MTX (non-extendable
to persistent remission). The presence of ACPA has a less
well-defined effect, with solid data suggesting it does not
influence response to DMARDs in early RA, although it
may play a role in UA patients’ response to MTX. Other
nongenetic biomarkers have been identified in smaller stu-
dies and some may deserve further clarification as poten-
tial predictive markers through larger studies.
Pharmacogenetics remains a promising field but to date,
and regardless of intense research, no SNPs have been
clearly identified as predictors of response to MTX .
This is probably related to the influence of several genes
and polymorphisms on the determination of the final drug
effectiveness; recent studies continue to identify new SNPs
in crucial pathways, underlining the complexity of this
area. Valid approaches to overcome this issue include ana-
lysis of haplotypes, multiple-gene models, and interactions
of different genes with nongenetic factors.
As previously mentioned, combining different factors
might be useful in determining whether a patient will
Romão et al. BMC Medicine 2013, 11:17
Page 15 of 24
respond to MTX. Although models such as the one
developed by Wessels et al.  might be more reliable
for achieving this purpose, we can assume that starting
and maintaining treatment with MTX will probably be
more effective in male, non-smoking, DMARD-naïve,
SE-negative patients with early, mild disease and that
corticosteroids should be added as adjuvants. Other
variables, such as genetic determinants, will be valuable
in increasing the accuracy of the prediction model, but
at the moment it is not possible to define them with
Standardization of studies addressing predictors of
response is needed. On the one hand, the inconsistencies in
results may reflect differences in study-design, population
size and features (ethnicity, age, socioeconomic context),
disease characteristics (early/established, activity, disability),
pharmacological variables (dose, previous or concomitant
DMARD, corticosteroids, NSAIDs) and, most importantly,
outcome definitions used. On the other hand, this hetero-
geneity makes it harder to compare studies and, generally,
systematic literature reviews and meta-analysis are forced
to exclude a great number of studies, with few being left to
analyze. In this review we included a wide variety of studies
and while this is certainly a limitation it also allowed us to
gather more data and have a broader picture of current evi-
dence. Of major importance is definition of response, a
question already raised by other authors [15,16,220].
Response to treatment may be defined as adequate symp-
tom and activity control and this can be assessed by iso-
lated clinical variables (VAS, SJC, TJC, pain VAS) or
composite scores (SDAI, CDAI, EULAR response), but it
must be taken into account that this is not the same as dis-
ease progression slowdown or halt. However, given the
direct relationship between higher disease activity and pro-
gression, assessing response to treatment as improvement
in activity or symptoms seems an adequate approach to use
in studies. In this sense, we think the best way to evaluate
response is through changes in composite scores such as
DAS, DAS28, SDAI and CDAI and especially using EULAR
response criteria, because these are the only measurements
to encompass both change in time and endpoint values,
assuring that patients with good response have a significant
decrease in disease activity and also have reached low dis-
ease activity. By using these standard measures of response
to treatment, comparison between studies would be facili-
tated and prediction capacities would be easier to detect.
In summary, predicting response to MTX and other
DMARDs is a stimulating challenge in RA research, not
yet fully accomplished. Although it is still not possible
to determine whether or not a patient will respond to
MTX, we identified clinical and biological factors asso-
ciated with increased effectiveness: male gender, non-
smoking, early disease stage, absence of previous
DMARD use, lower baseline disease activity measured
by composite scores, concomitant corticosteroids and
SE-negativity. Combining distinct factors, adopting new
approaches in emerging fields and applying them in lar-
ger standardized studies will help define prediction
models and reach the longed-for goal of tailor-made
3’-UTR: 3’-untranslated region; 7-OH-MTX: 7-hydroxy-methotrexate; ABC: ATP-
binding cassette; ACPA: anti-citrullinated protein antibodies; ACR: American
College of Rheumatology; ADA: adenosine deaminase; AICAR: 5-
aminoimidazole-4-carbox-amide ribonucleotide; ALT: alanine
aminotransferase; AMPd: adenosine monophosphate deaminase; anti-CCP2:
second-generation anti-cyclic citrullinated peptide; anti-MCV: anti-modified
citrullinated vimentin antibodies; AST: aspartate aminotransferase; ATIC: 5-
aminoimidazole-4-carbox-amide ribonucleotide transformylase; bp: base pair;
CBC: complete blood count; CDAI: clinical disease activity index; CI:
confidence interval; CRP: C reactive protein; DAS: disease activity score;
DAS28: disease activity score - 28 joint; DHF: dihydrofolate; DHFR:
dihydrofolate reductase; DMARDs: disease-modifying antirheumatic drugs;
dTMP: deoxythymidine monophosphate; dUMP: deoxyuridine
monophosphate; ESR: erythrocyte sedimentation rate; EULAR: European
League Against Rheumatism; FAICAR: 10-formyl 5-aminoimidazole-4-
carboxamide ribonucleotide; FPGS: folylpolyglutamate synthetase; GGH: γ-
glutamyl hydrolase; HAQ: health assessment questionnaire; Hb: hemoglobin;
HCQ: hydroxychloroquine; HLA: human leukocyte antigen; HR: hazard ratio;
IFN: interferon; IgG: immunoglobulin G; IL: interleukin; IL-1ra: interleukin-1
receptor antagonist; IMP: inosine monophosphate; ITPA: inosine triphosphate
pyrophosphatase; Methyl-THF: 5-methyl-tetrahydrofolate; Methylene-THF:
5:10-methylene-tetrahydrofolate; MMP-3: matrix metalloproteinase-3; MS:
methionine synthase; MTHFD1: methylene-tetrahydrofolate dehydrogenase;
MTHFR: 5:10-methylene-tetrahydrofolate reductase; MTR: 5-
methyltetrahydrofolate-homocysteine methyltransferase; MTX: methotrexate;
MTX PG: methotrexate polyglutamates; NSAIDs: non-steroidal anti-
inflammatory drugs; OR: odds ratio; PBMC: peripheral blood mononuclear
cells; RA: rheumatoid arthritis; RBC: red blood cells; RCT: randomized clinical
trial; rDAS28: relative disease activity score - 28 joint; RF: rheumatoid factor;
RFC1: reduced folate carrier 1; sCD30: soluble CD30; SD: standard deviation;
SDAI: simplified disease activity index; SE: shared epitope; SHMT: serine
hydroxymethil transferase; sIL-2R: soluble interleukin-2 receptor; SJC: swollen
joint count; SNPs: single nucleotide polymorphisms; SR: systematic review;
SSZ: sulphasalazine; sTNFR: soluble tumor necrosis factor receptor; THF:
tetrahydrofolate; TJC: tender joint count; TNF: tumor necrosis factor; TNFID50:
dose required to suppress by 50% the production of tumor necrosis factor;
TSER: thymidylate synthase enhancer region; TYMS: thymidylate synthase;
UA: undifferentiated arthritis; ULN: upper limit of normal; VAS: visual
All authors participated in the protocol design. VCR performed the literature
search, drafted and edited the manuscript, including figures and tables. HC
and JEF reviewed, commented and complemented the manuscript. All
authors have read and approved the final manuscript.
VCR, MD is a research trainee at the Rheumatology Research Unit, Instituto
de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa,
Lisbon, Portugal. He is also a Rheumatology fellow at the Lisbon Academic
Medical Centre, Portugal.
HC, MD, MMSc, PhD is Principal Investigator at the Rheumatology Research
Unit, Instituto de Medicina Molecular, Faculdade de Medicina da
Universidade de Lisboa. She is Assistant Professor of Rheumatology and a
Rheumatology Consultant at the Lisbon Academic Medical Centre. She is
also the National Coordinator of Reuma.pt (Rheumatic Diseases Portuguese
Register, Portuguese Society of Rheumatology).
Romão et al. BMC Medicine 2013, 11:17
Page 16 of 24
JEF, MD, PhD is the Head of the Rheumatology Research Unit and of the
Biobank at Instituto de Medicina Molecular, Faculdade de Medicina da
Universidade de Lisboa. He is Assistant Professor of Rheumatology and a
Rheumatology Consultant at the Lisbon Academic Medical Centre. He is also
the President-Elect of the Portuguese Society of Rheumatology.
The authors declare that they have no competing interests.
1Rheumatology Research Unit, Instituto de Medicina Molecular - Faculdade
de Medicina da Universidade de Lisboa, Edifício Egas Moniz - Av. Prof. Egas
Moniz, Lisboa 1649-028, Portugal.2Rheumatology Department, Lisbon
Academic Medical Centre, Av. Prof. Egas Moniz, Lisboa 1649-028, Portugal.
Received: 5 September 2012 Accepted: 23 January 2013
Published: 23 January 2013
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The pre-publication history for this paper can be accessed here:
Cite this article as: Romão et al.: Old drugs, old problems: where do we
stand in prediction of rheumatoid arthritis responsiveness to
methotrexate and other synthetic DMARDs? BMC Medicine 2013 11:17.
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