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Risk of lymphoma in patients exposed to antitumour necrosis factor therapy: results from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis


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Objectives: Patients with rheumatoid arthritis (RA) are at increased risk of lymphoma compared with the general population. There are concerns that tumour necrosis factor inhibitors (TNFi) may exacerbate this risk. However, since the excess risk of lymphoma in RA is related to the cumulative burden of inflammation, TNFi may conversely reduce the risk of lymphoma by decreasing the burden of inflammation. The aim of this study was to compare the risk of lymphoma in subjects with RA treated with TNFi with those treated with non-biological therapy. Methods: Subjects diagnosed by a rheumatologist with RA enrolled in the British Society for Rheumatology Rheumatoid Arthritis Register (BSRBR-RA), a prospective cohort study, were followed until first lymphoma, death or until 30 November 2013. Rates of lymphoma in the TNFi and non-biological-treated cohorts were compared using Cox regression. Results: 11 931 TNFi-treated patients were compared with 3367 biological-naive patients. 84 lymphomas (88 (95% CI 70 to 109) per 100 000 person-years) were reported in the TNFi cohort and 30 lymphomas (154 (95% CI 104 to 220)) in the biological-naive cohort. After adjusting for differences in baseline characteristics, there was no difference in the risk of lymphoma for the TNFi versus the biological-naive group: HR 1.00 (95% CI 0.56 to 1.80). No risk differences were observed for individual TNFi. Conclusions: In medium-term follow-up, there is no evidence that tumour necrosis factor inhibition influences the risk of lymphoma over the background risk in subjects with RA.
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Risk of lymphoma in patients exposed to antitumour
necrosis factor therapy: results from the British
Society for Rheumatology Biologics Register
for Rheumatoid Arthritis
Louise K Mercer,
James B Galloway,
Mark Lunt,
Rebecca Davies,
Audrey L S Low,
William G Dixon,
Kath D Watson,
BSRBR Control Centre Consortium
Deborah P M Symmons,
Kimme L Hyrich
Handling editor Tore K Kvien
Additional material is
published online only. To view
please visit the journal online
Arthritis Research UK Centre
for Epidemiology, Centre for
Musculoskeletal Research,
Manchester Academic Health
Science Centre, The University
of Manchester, Manchester, UK
Department of Rheumatology,
Kings College London,
London, UK
NIHR Manchester
Musculoskeletal Biomedical
Research Unit, Central
Manchester University
Hospitals NHS Foundation
Trust and University of
Manchester Partnership,
Manchester, UK
Correspondence to
Professor Kimme L Hyrich,
Arthritis Research UK Centre
for Epidemiology, The
University of Manchester,
Stopford Building, Oxford
Road, Manchester M13 9PT,
UK; Kimme.hyrich@
Received 16 February 2016
Revised 22 May 2016
Accepted 19 June 2016
To cite: Mercer LK,
Galloway JB, Lunt M, et al.
Ann Rheum Dis Published
Online First: [please include
Day Month Year]
Objectives Patients with rheumatoid arthritis (RA) are
at increased risk of lymphoma compared with the general
population. There are concerns that tumour necrosis
factor inhibitors (TNFi) may exacerbate this risk. However,
since the excess risk of lymphoma in RA is related to the
cumulative burden of inammation, TNFi may conversely
reduce the risk of lymphoma by decreasing the burden of
inammation. The aim of this study was to compare the
risk of lymphoma in subjects with RA treated with TNFi
with those treated with non-biological therapy.
Methods Subjects diagnosed by a rheumatologist with
RA enrolled in the British Society for Rheumatology
Rheumatoid Arthritis Register (BSRBR-RA), a prospective
cohort study, were followed until rst lymphoma, death or
until 30 November 2013. Rates of lymphoma in the TNFi
and non-biological-treated cohorts were compared using
Cox regression.
Results 11 931 TNFi-treated patients were compared
with 3367 biological-naive patients. 84 lymphomas (88
(95% CI 70 to 109) per 100 000 person-years) were
reported in the TNFi cohort and 30 lymphomas (154
(95% CI 104 to 220)) in the biological-naive cohort. After
adjusting for differences in baseline characteristics, there
was no difference in the risk of lymphoma for the TNFi
versus the biological-naive group: HR 1.00 (95% CI 0.56
to 1.80). No risk differences were observed for individual
Conclusions In medium-term follow-up, there is no
evidence that tumour necrosis factor inhibition inuences
the risk of lymphoma over the background risk in subjects
with RA.
In the late 1990s, the treatment of rheumatoid
arthritis (RA) and other related autoimmune in-
ammatory conditions underwent a fundamental
shift, away from general immunosuppressive agents
towards an approach that targeted specic compo-
nents of the inammatory pathway. The rst treat-
ments in this therapeutic class, known collectively as
biological agents, were inhibitors of tumour necrosis
factor-alpha (TNF-alpha).
Tumour necrosis
factor (TNF) plays a pivotal role in inammation in
and tumour necrosis factor inhibitors (TNFi)
are highly effective in treating RA.
From early in
their development, there were concerns regarding
the long-term safety of the TNFi with respect to
malignancy, and in particular lymphoma.
possible effects of TNF inhibition on lymphomagen-
esis are difcult to predict. TNF has pleotropic
effects in the promotion and progression of malig-
nancy, with both tumour-promoting and tumour-
inhibiting actions.
One of the main indications
for anti-TNF therapies is RA and RA itself has a
long-recognised established increased risk of lymph-
oma compared with the general population,
especially the diffuse large B cell lymphoma
11 12
Importantly, a large Swedish nested
casecontrol study reported that patients in the
highest decile of cumulative RA disease activity had
more than a 60-fold increased risk of lymphoma
compared with those in the lowest decile (OR 61.6
(95% CI 21.0 to 181.1)).
A previous publication
from the British Society for Rheumatology
Rheumatoid Arthritis Register (BSRBR-RA) demon-
strated that there remains an increased risk of
lymphoma in biological-naïve patients treated with
non-biological therapy compared with the general
population in the modern era of early and aggressive
There is some evidence that this
increased risk in RA may be exacerbated further by
immunosuppressive therapy.
Therefore, given the
strong association between chronic inammation
and lymphoma development in RA, it is plausible
that TNFi could reduce the risk of lymphoma by
reducing ongoing inammation. Nonetheless, the
TNFi carry a black box warning with respect to
lymphoma and the US Food and Drug Administration
have highlighted concerns about the risk of hepatos-
plenic T cell lymphoma, a rare and aggressive cancer,
in children and adolescents.
Several European biological registers have been
established over the last 1015 years to examine the
long-term safety of TNFi.
One of the earliest and
largest of these, the BSRBR-RA, was established in
2001 with a primary aim to determine the relation-
ship between exposure to TNFi and lymphoma risk.
Here, we report the risk of lymphoma development in
patients with RA exposed to TNFi therapy and
compare that with the risk in patients with RA treated
with non-biological (synthetic) disease-modifying
drug (csDMARD) therapy.
Mercer LK, et al.Ann Rheum Dis 2016;0:17. doi:10.1136/annrheumdis-2016-209389 1
Clinical and epidemiological research
ARD Online First, published on August 8, 2016 as 10.1136/annrheumdis-2016-209389
Copyright Article author (or their employer) 2016. Produced by BMJ Publishing Group Ltd (& EULAR) under licence. on August 17, 2016 - Published by from
Subjects were participants in the BSRBR-RA, an ongoing
national prospective observational cohort study established in
2001 to monitor the long-term safety of biological therapy in
RA. UK national guidelines from the National Institute for
Health and Care Excellence (NICE) recommend that prescrip-
tion of TNFi is restricted to patients with highly active
18 19
This is dened as a score >5.1 using the 28-joint
Disease Activity Score (DAS28)
a composite score of swollen
and tender joint counts, erythrocyte sedimentation rate and a
patients global assessment of diseasedespite treatment with at
least two csDMARDs, one of which should be methotrex-
18 19
During the time period of recruitment of patients
included in this analysis, three TNFi agents were available in the
UK: etanercept (ETA), iniximab (INF) and adalimumab (ADA).
A comparison cohort of biological-naïve patients with RA was
recruited in parallel and followed in an identical manner to the
TNFi cohort.
These patients had active disease at recruitment
(target DAS284.2) despite current treatment with csDMARD.
The subjectswritten consent was obtained.
BSRBR-RA data collection methods
Baseline data for all patients, collected via rheumatologist/nurse-
completed questionnaire, included demographics, disease dur-
ation, disease activity, current and past csDMARDs, baseline
corticosteroid use, comorbidities and smoking history. Patients
completed a Stanford Health Assessment Questionnaire (HAQ)
adapted for British use
to indicate the level of physical disabil-
ity and were asked to select their ethnic group from a list:
white; black-African; black-Caribbean; black-British; black-
other; Indian; Pakistani; Bangladeshi; Chinese or other ( please
specify). All patients were agged at baseline with the National
Health Service Information Centre or the Northern Ireland
Cancer Registry, who link with the British cancer agencies. The
cancer registries notied the BSRBR-RA of past cancers and pro-
spectively of cancers that occurred after the patient entered the
register. Capture of cancer cases is very high using these
sources, for example, 97% for England cancer statistics pub-
lished for 2009.
All patients were continually followed until death or self-
withdrawal, regardless of changes to antirheumatic therapies.
Changes to RA therapy were reported on rheumatologist/nurse
questionnaires completed 6-monthly for 3 years then annually
thereafter. Data on adverse events were captured in three ways:
from rheumatologist/nurse questionnaires; from 6-monthly
patient diaries completed for 3 years on which details of any
new hospital admissions, physician consultations and treatments
were recorded and by agging with the national death register
and cancer registries which reported malignancies using the
10th edition of the International Classication of Diseases
(ICD-10). Additional information (including histology) was
sought from rheumatologist for all incident lymphomas.
The primary outcome measure for this analysis was rst veried
lymphoma per subject. Lymphomas were veried if they fullled
either of the following criteria: (i) conrmation on histology
report or (ii) reported by a national cancer agency. There were
no lymphomas identied from death certicates alone.
Histology reports and ICD-10 codes reported by the cancer
registries were used to classify lymphomas into subtypes.
Subject selection for the current analysis
Stata (StataCorp., College Station, Texas, USA) V.12.1 was used
for the analyses. Patients were selected from the register if they
had a physician diagnosis of RA and at least one returned
rheumatologist follow-up questionnaire prior to 30 November
2013. Patients with a prior diagnosis of lymphoproliferative or
myeloproliferative malignancy (LPM/MPM) were excluded from
the analysis (gure 1). The TNFi cohort was restricted to
patients who received ETA, INF or ADA as their rst biological
therapy and who registered with the BSRBR-RA within
6 months of starting treatment. Patients with prior biological
exposure were excluded. The rst 6 months of follow-up time
was excluded from both cohorts, to minimise the risk of in-
cluding prevalent lymphomas in the analysis, and so patients
who did not complete 6 months follow-up were excluded.
Patient-years (pyrs) of follow-up time were calculated from
6 months after the date of starting a TNFi or 6 months after the
date of registration with the BSRBR-RA for the csDMARD
cohort. Follow-up was censored at the date of rst lymphoma,
Figure 1 Selection of participants for the analysis. DAS28, 28-joint
Disease Activity Score; LPM, lymphoproliferative malignancy; MPM,
myeloproliferative malignancy; RA, rheumatoid arthritis; TNF, tumour
necrosis factor; TNFi, tumour necrosis factor inhibitors.
2 Mercer LK, et al.Ann Rheum Dis 2016;0:17. doi:10.1136/annrheumdis-2016-209389
Clinical and epidemiological research on August 17, 2016 - Published by from
death or on 30 November 2013, whichever came rst. Patients
in the csDMARD cohort who subsequently started a biological
drug contributed follow-up time up until the date of rst dose
biological therapy. Follow-up time after stopping TNFi was
included in the TNFi cohort, irrespective of whether or not the
patient started a second or subsequent biological drug, since it
was hypothesised that the effects of TNFi on lymphoma risk
may be long-lasting.
Statistical analysis
Baseline characteristics of the cohorts were compared using the
test for categorical variables and the Wilcoxon rank-sum test
for continuous items and p values were presented. Rates of
lymphoma are presented as total events per 100 000 pyrs with
95% CIs constructed assuming a Poisson distribution of cases.
Risk comparisons were made between the TNFi and csDMARD
cohorts using Cox regression. Potential confounders were iden-
tied a priori and comprised age, sex, smoking status and ethni-
city, since the incidence of lymphoma varies by ethnic group
(dichotomised as white or other ethnicity due to the high pro-
portion of white participants); prior cancer (excluding LPM or
MPM); comorbidity and markers of RA severity. The number of
comorbidities was calculated as a composite variable constructed
from the following conditions: hypertension; ischaemic heart
disease; stroke; asthma, bronchitis or emphysema; renal disease;
diabetes mellitus; liver disease and depression. Several baseline
dimensions of RA disease severity were included: DAS28 score;
HAQ score; RA duration; number of previous csDMARDs
(categorised as 3or4) and current exposure to corticoster-
oids. Date of registration with the BSRBR-RA (dichotomised as
before/after June 2004) was also included to account for
unmeasured confounding relating to temporal changes in the
way that rheumatologists managed patients with RA.
Adjustment for these covariates was performed by calculating a
propensity score (PS) that reected the likelihood that an individ-
ual patient was prescribed a TNFi, given the above character-
istics. The PS has a single value for each subject that can be
substituted into the regression model in place of all of the poten-
tially confounding covariates. The PS model was derived and
tested using Prop_selcommands in Stata. The balance of the
model was tested by examining the expected bias, which is the
likely bias in the treatment estimate due to each confounder. A
maximum bias of 2% in either direction was considered accept-
able (see online supplementary gure S1). The PS was stratied
into deciles of propensity score (PD) for use in adjusted analyses.
Subjects with a baseline DAS28 score 3.2 (csDMARD: 290;
TNFi: 56) were subsequently excluded from the analysis due to
an area of non-overlap in the PS between cohorts. Missing base-
line data were replaced using multiple imputation (see online sup-
plementary table S1). The assumptions of the Cox models were
tested using Schoenfeld residuals and met.
Drug exposure models
The primary analysis compared the rate of lymphoma in
patients ever treated with TNFi with the csDMARD cohort (ie,
subjects in the TNFi cohort were considered exposed from rst
dose until the end of follow-upever exposed analysis).
Additional analyses were performed to test the robustness of the
ndings. First, patients actively on TNFi (including a lag period
of 90 days from their rst missed dose) were compared with the
csDMARD cohort (on-drug analysis). For on-drug analyses,
time after last received consultant follow-up questionnaire was
excluded for all participants since information about current
drug exposure status came from these questionnaires. Second,
the outcome was restricted to lymphomas reported by the
national cancer agencies, in case there was any bias in reporting of
lymphomas by patients and rheumatologists to the BSRBR-RA.
Lymphoma subgroup-specic analyses were performed for sub-
types with 5 lymphomas in each cohort as a secondary outcome.
The risk of rst lymphoma for each TNFi agent was com-
pared separately with csDMARD. Propensity models for each
TNFi versus csDAMRD were created using the same method
and confounders as above. Three drug exposure models were
used. First, lymphomas were attributed to the most recently
received TNFi. Second, lymphomas were attributed to the rst
TNFi agent received and follow-up was censored when a
second biological drug was started and third, an on-drug model.
In total, 3367 csDMARD and 11 931 TNFi patients were
included (gure 1). The TNFi cohort comprised 4144 (35%)
patients starting ETA; INF 3499 (29%) and ADA 4288 (36%).
The TNFi cohort was younger and comprised more women
(table 1). As might be expected, the TNFi cohort had more
severe disease, of longer duration and greater exposure to corti-
costeroids and prior csDMARD. The median follow-up was
6.5 years (IQR 3.8, 8.0) for csDMARD and 8.6 (6.7, 9.7) for
Seven lymphomas were diagnosed in the rst 6 months and
not included (csDMARD 3, TNFi 4). One hundred and four-
teen lymphomas were diagnosed during subsequent follow-up
(30 in 19 473 pyrs in the csDMARD and 84 in 95 126 pyrs in
the TNFi cohort (table 2)). The proportion of lymphomas
Table 1 Baseline characteristics
All TNFi
n=11 931 p Value
Mean age: years (SD) 60 (12) 56 (12) <0.001
Females: % 2477 (74) 9115 (76) <0.001
Smoking history n (%)
Current smoker 795 (24) 2595 (22) 0.001
Former smoker 1335 (40) 4530 (38)
Never smoked 1222 (36) 4727 (40)
Not recorded 15 (0) 79 (1)
Ethnicity n (%)
White 2561 (76) 9848 (83) <0.001
Other 64 (2) 410 (3)
Not recorded 742 (22) 1673 (14)
Mean DAS28 (SD) 5.3 (1.1) 6.6 (0.9) <0.001
Mean HAQ (SD) 1.5 (0.7) 2.0 (0.6) <0.001
Median disease duration: years (IQR) 6 (1, 15) 11 (6 19) <0.001
Baseline steroid use: n (%) 759 (23) 5259 (44) <0.001
Number of prior csDMARD: median (IQR) 2 (1, 3) 4 (3, 5) <0.001
Comorbidity*: n (%)
None 1397 (41) 5530 (46) <0.001
1 comorbidity 1163 (35) 4098 (34)
2 comorbidities 560 (17) 1691 (14)
3 comorbidities 247 (7) 612 (5)
Prior solid cancer: n (%) 122 (4) 170 (1) <0.001
*Hypertension, ischaemic heart disease (myocardial infarction or angina), stroke, lung
disease (asthma, bronchitis or emphysema), diabetes mellitus, depression, renal disease
and liver disease.
csDMARD, non-biological (synthetic) disease-modifying drug; DAS28, 28-joint Disease
Activity Score; HAQ, Health Assessment Questionnaire; TNFi, tumour necrosis factor
Mercer LK, et al.Ann Rheum Dis 2016;0:17. doi:10.1136/annrheumdis-2016-209389 3
Clinical and epidemiological research on August 17, 2016 - Published by from
reported by the national cancer registries was 90% in the
csDMARD and TNFi cohorts (table 2). The unadjusted HR for
lymphoma for TNFi compared with csDMARD was 0.61 (95%
CI 0.40 to 0.92) (table 3). Age and male gender were associated
with the risk of lymphoma in univariate analysis (see online sup-
plementary table S2). After fully adjusting, using PD, there was
no difference in the risk of lymphoma for TNFi compared with
csDMARD; HR 1.00 (95% CI 0.56 to 1.80) (table 3). The
PD-adjusted HR for the on TNFianalysis was 1.17 (95% CI
0.60 to 2.26). Excluding time after starting second biological
drug or limiting the analysis to cancer registry-only reported
lymphomas did not materially alter the ndings (table 3). There
were ve Hodgkins lymphomas (HL; 17%) and 25 non-Hodgkins
lymphomas (NHL; 83%) in the csDMARD cohort; and 12 HL
(14%) and 72 NHL (86%) in the TNFi cohort (table 2). The
most frequently reported subtype of NHL was DLBCL (table 2).
No signicant differences in the proportion of HL, NHL or
DLBCL were seen between cohorts (table 3). Five T cell lymph-
omas were reported, none of which were the hepatosplenic
Thirty-four lymphomas were reported in patients most
recently exposed to ADA, 29 to ETA and 21 to INF. No differ-
ence in the relative risk of lymphoma was seen for any TNFi
compared with csDAMRD using each of the exposure models
(table 4).
This national prospective study, with over 120 000 pyrs of
exposure to anti-TNF or csDMARD, did not identify any differ-
ence in lymphoma risk for up to 8 years after the addition of
TNFi to the standard treatment regimen of patients with RA.
This study represents one of the largest and most detailed
analyses of TNFi and lymphoma risk published until now
and mirrors the results of previous cohort studies
The question of whether or not anti-TNF
inuences the risk of lymphoma is of particular concern to rheu-
matologists due to the known association between severity of
RA and lymphoma
and a signal for increased cancer risk fol-
lowing TNF inhibition in an early meta-analysis.
A clinically
meaningful increased risk of lymphoma associated with TNFi
was excluded from this analysis: the analysis had 98% power to
detect a twofold relative increased risk for TNFi compared with
the rate in the csDMARD cohort.
A further strength of the current study was that only incident
users of TNFi as their rst biological drug for RA were included.
Furthermore, data on lymphomas in our study were collected
by agging all participants with the UK cancer agencies that
have near-complete capture of cases, thus minimising potential
for bias in reporting between cohorts. Further information was
requested, including histology reports, for all reported cancers,
ensuring that a standard data set was received for each cancer.
The selection of an ever exposedto TNFi drug model
reects the hypothesis that any effect of TNFi on lymphoma
risk would be long-lasting and may operate in the latent period
of a cancer. Alternative exposure models were constructed,
which did not materially change the ndings.
Other strengths of this study include careful consideration of
potential biases. For example, the rst 6 months of follow-up
were excluded to reduce the probability of prevalent lymphomas
being included. In addition, prevalent users of TNFi at baseline
were excluded. The analysis adjusted for a wider range of con-
founders than previous studies, as confounding by indication is
likely to be present given the way these agents are currently pre-
scribed for RA. Differences in the baseline characteristics of the
cohorts reect this to some degree. The csDMARD cohort was
older and comprised more men than the TNFi cohort; both risk
factors for cancer, which may explain in part the lower crude risk
of lymphoma in the TNFi cohort. Despite lymphoma being a
relatively uncommon outcome, adjustment for multiple confoun-
ders was possible by using PS methods. Stratifying the PS into
deciles reduced the expected bias in the analysis to less than 5%.
The results of this study align with those of previous analyses
of lymphoma in users of anti-TNF. Wolfe and Michaud
data from the National Data Bank and reported an OR for
Table 2 Characteristics of lymphomas
N=11 931
Most recent TNFi
Total follow-up time (pyrs) 19 473 95 126 33 354 40 619 21 150
Median follow-up per subject (IQR) 6.5 (3.8, 8.0) 8.6 (6.7, 9.7) 6.2 (3.5, 8.0) 5.9 (1.4, 9.1) 8.1 (3.8, 9.2)
Lymphomas 30 84 34 29 21
Sources of reporting of lymphomas
Cancer registry (%) 27 (90) 76 (90) 30 (88) 25 (86) 21 (100)
Subtypes of lymphoma: N (%)
HL 5 (17) 12 (14) 4 (12) 5 (17) 3 (14)
DLBCL 10 (33) 31 (37) 19 (56) 5 (17) 7 (33)
FL 1 (3) 18 (21) 5 (15) 6 (21) 7 (33)
CLL/small lymphocytic 3 (10) 8 (9) 2 (6) 4 (14) 2 (10)
MALToma 0 4 (5) 1 (3) 3 (10) 0
Mantle cell 3 (10) 0 0 0 0
Burkitt 1 (3) 0 0 0 0
B cell NHL NOS 5 (17) 8 (9) 2 (6) 4 (14) 2 (10)
T cell 2 (7) 3 (4) 1 (3) 2 (7) 0
CLL, chronic lymphocytic leukaemia; DLBCL, diffuse large B cell lymphoma; FL, follicular lymphoma; HL, Hodgkins lymphoma; MALToma, mucosal-associated lymphoid tissue lymphoma;
NHL, non-Hodgkins lymphoma; NOS, not otherwise specified; pyrs, patient-years; TNFi, tumour necrosis factor inhibitors.
4 Mercer LK, et al.Ann Rheum Dis 2016;0:17. doi:10.1136/annrheumdis-2016-209389
Clinical and epidemiological research on August 17, 2016 - Published by from
exposure to TNFi of 1.0 (95% CI 0.6 to 1.8). However, this
study included prevalent users of TNFi, leading to possible left
censorship, unlike our study. The Swedish Biologics Register
(Anti-Rheumatic Therapies in Sweden; ARTIS) reported a rela-
tive risk of 1.35 (95% CI 0.82 to 2.11) in their most recent
However, despite having more than 350 000 pyrs
of follow-up in their csDMARD comparator cohort, they lacked
precision in their estimate of drug effect since they observed
only 26 lymphomas in 30 000 pyrs in the TNFi cohort.
The French Research Axed on Tolerance of bIOtherapies
(RATIO) registry reported that exposure to ADA or INF versus
ETA was a risk factor for lymphoma over a 3-year period (OR
4.7 (1.3 to 17.7) and 4.1 (1.4 to 12.5), respectively).
Conversely, this current study did not observe a difference in
the risk of lymphoma for any individual TNFi versus
csDMARD. Direct comparisons were not made in this study
since more than 50% of the cohort were exposed to multiple
TNFi during follow-up. Such patients who switch drugs, com-
monly for treatment inefcacy, may have a different underlying
risk of lymphoma.
The most frequently reported subtype in this study was
DLBCL, with follicular lymphoma being the next most frequent
subtype in the TNFi cohort, in line with previous studies of
biological-naive cohorts.
11 13
The distribution of lymphoma sub-
types varies by sex and age at diagnosis and so the difference in
age between the TNFi and csDMARD cohorts may have led to a
difference in the expected distribution of subtypes between
groups. The proportion of follicular lymphomas was lower in the
csDMARD cohort than expected but the numbers of individual
subtypes were low, highlighting the fact that this study was not
powered to study at the relative risk of individual subtypes.
Reporting of lymphoma subtypes was based on external histology
reports rather than rereview of lymphoma specimens and mis-
classication between lymphoma subtypes may have occurred.
A weakness of our study was that it was not possible to adjust
for, or explore the inuence of, cumulative RA disease activity.
However, HAQ, a marker of cumulative damage, baseline
DAS28 and RA duration were included in the PS model.
Missing data can adversely affect all studies, particularly
Table 3 Association between exposure to TNFi and lymphoma
N=11 931
Total follow-up time (pyrs) 19 473 95 126
Lymphomas 30 84
Incidence rate per 100 000 pyrs (95% CI) 154 (104 to
88 (70 to 109)
Unadjusted HR (95% CI) Referent 0.61 (0.40 to 0.92)
Age-adjusted and sex-adjusted HR (95% CI) Referent 0.75 (0.49 to 1.15)
PD-adjusted HR (95% CI) Referent 1.00 (0.56 to 1.80)
On TNFi (plus 90 days)*
Follow-up time ( pyrs) 15 167 57 949
Lymphomas 25 63
PD-adjusted HR (95% CI) Referent 1.17 (0.60 to 2.26)
Excluded time after switched to second biological drug*
Follow-up time ( pyrs) 15 167 55 167
Lymphomas 25 52
PD-adjusted HR (95% CI) Referent 1.12 (0.58 to 2.18)
Cancer registry-only reported lymphomas
Follow-up time ( pyrs) 19 473 95 126
Lymphomas 27 76
PD-adjusted HR (95% CI) Referent 1.02 (0.55 to 1.90)
Hodgkins lymphomas (HL)
Incidence rate of HL per 100 000 pyrs
(95% CI)
26 (8 to 60) 13 (7 to 22)
PD-adjusted HR for HL (95% CI) Referent 0.54 (0.12 to 2.50)
Non-Hodgkins lymphomas (NHL)
Incidence rate of NHL per 100 000 pyrs
(95% CI)
128 (83 to
75 (58 to 94
PD-adjusted HR for NHL (95% CI) Referent 1.10 (0.58 to 2.08)
Incidence rate of DLBCL per 100 000 pyrs
(95% CI)
67 (36 to
56 (42 to 73)
PD-adjusted HR for DLBCL (95% CI) Referent 1.54 (0.60 to 3.95)
*Time after last received consultant follow-up form excluded from this analysis.
DLBCL, diffuse large B cell lymphoma; pyrs, patient-years; TNFi, tumour necrosis factor
Table 4 Association between exposure to adalimumab (ADA), etanercept (ETA) or infliximab (INF) and lymphoma
First TNFi received (censored when second biological drug started)*
Total follow-up time (pyrs) 22 361 26 838 17 688
Number of lymphomas 20 20 18
Incidence rate per 100 000 pyrs (95% CI) 89 (55 to 138) 75 (45 to 115) 102 (60 to 161)
PD-adjusted HR (95% CI) (csDMARD referent) 1.00 (0.49 to 2.03) 1.02 (0.45 to 2.33) 0.91 (0.39 to 2.13)
Most recently received TNFi
Follow-up time ( pyrs) 33 354 40 618 21 149
Number of lymphomas 34 29 21
Incidence rate per 100 000 pyrs (95% CI) 102 (71 to 143) 71 (48 to 103) 99 (62 to 152)
PD-adjusted HR (95% CI) (csDMARD referent) 0.99 (0.52 to 1.88) 0.78 (0.37 to 1.66) 0.82 (0.37 to 1.82)
On drug (plus 90 days)*
Follow-up time ( pyrs) 18 818 24 984 12 328
Number of lymphomas 23 10 10
Incidence rate per 100 000 pyrs (95% CI) 122 (77 to 183) 40 (19 to 74) 81 (39 to 149)
PD-adjusted HR (95% CI) (csDMARD referent) 0.77 (0.37 to 1.61) 0.41 (0.14 to 1.19) 0.75 (0.27 to 2.09)
*Time after last received consultant follow-up form excluded from these analyses.
Includes both first and subsequent exposures to the drug.
pyrs, patient-years; TNFi, tumour necrosis factor inhibitors.
Mercer LK, et al.Ann Rheum Dis 2016;0:17. doi:10.1136/annrheumdis-2016-209389 5
Clinical and epidemiological research on August 17, 2016 - Published by from
observational studies. Overall, the proportion of missing base-
line data was low in the BSRBR-RA (see online supplementary
material). Response rates to follow-up questionnaires were
excellent; less than 1% of patients in each cohort had no
returned consultant follow-up. To minimise bias introduced by
missing baseline data, multiple imputation was used.
In conclusion, this study has ruled out an important risk of
lymphoma in patients with RA exposed to TNFi over the back-
ground risk associated with RA for up to 5 years after treatment
initiation. This is consistent with other published data and the
biological expectation that disease activity is the primary driver
for lymphoma in RA. Further follow-up of signicantly larger
populations is now needed to determine whether longer-term
exposure or cumulative drug exposure inuences risk, given the
overall low absolute risk of lymphoma in TNFi-treated patients.
Twitter Follow William Dixon at @WGDixon
Collaborators BSRBR Control Centre Consortium: The BSRBR Control Centre
Consortium consists of the following institutions (all in the UK): Antrim Area
Hospital, Antrim (Dr Nicola Maiden), Cannock Chase Hospital, Cannock Chase
(Dr Tom Price), Christchurch Hospital, Christchurch (Dr Neil Hopkinson), Royal Derby
Hospital, Derby (Dr Sheila OReilly), Dewsbury and District Hospital, Dewsbury
(Dr Lesley Hordon), Freeman Hospital, Newcastle-upon-Tyne (Dr Ian Grifths),
Gartnavel General Hospital, Glasgow (Dr Duncan Porter), Glasgow Royal Inrmary,
Glasgow (Dr R Madhok), Haywood Hospital, Stoke-on-Trent (Dr Andy Hassell), Hope
Hospital, Salford (Dr R G Cooper), Kings College Hospital, London (Dr Ernest Choy),
Kings Mill Centre, Sutton-In Asheld (Dr David Walsh), Chapel Allerton Hospital,
Leeds (Professor Paul Emery), Maccleseld District General Hospital, Maccleseld
(Dr Susan Knight), Manchester Royal Inrmary, Manchester (Dr Ian Bruce), Musgrave
Park Hospital, Belfast (Dr Allister Taggart), Norfolk and Norwich University Hospital,
Norwich (Professor David Scott), Poole Hospital, Poole (Dr Paul Thompson), Queen
Alexandra Hospital, Portsmouth (Dr Fiona McCrae), Royal Glamorgan Hospital,
Glamorgan (Dr Rhian Goodfellow), Russells Hall Hospital, Dudley (Professor George
Kitas), Selly Oak Hospital, Selly Oak (Dr Ronald Jubb), St Helens Hospital, St Helens
(Dr Rikki Abernethy), Weston General Hospital, Weston-super-Mare (Dr Sandra
Green), University Hospital of South Manchester/Withington Community Hospital,
(Dr Paul Sanders), Withybush General Hospital, Haverfordwest (Dr Amanda Coulson),
North Manchester General Hospital (Dr Bev Harrison), Royal Lancaster Inrmary
(Dr Marwan Bukhari) and The Royal Oldham Hospital (Dr Peter Klimiuk).
Contributors Study concept and design: All. Acquisition of data: BSRBR Control
Centre Consortium. Analysis and interpretation of data: All. Statistical analysis:
LKM, ML, RD, KLH. Drafting of manuscript: LKM, DPMS, KLH. Critical revision of
manuscript for important intellectual content: All. LKM and KLH had full access to
all the data in the study and take responsibility for the integrity of the data and the
accuracy of the data analysis.
Funding The BSR commissioned the BSRBR-RA as a UK-wide national project to
investigate the safety of biological agents in routine medical practice. BSR receives
restricted income from UK pharmaceutical companies, presently AbbVie (previously
Abbott Laboratories), Merck, Pzer, Roche, Union Chimique Belge Pharma Ltd (UCB)
and Swedish Orphan Biovitrum AB (SOBI). This income nances a wholly separate
contract between the BSR and the University of Manchester who provide and oversee
the BSRBR-RA data collection, management and analysis service. The principal
investigators and their team have full academic freedom and are able to work
independently of pharmaceutical industry inuence. All decisions concerning analyses,
interpretation and publication are made autonomously of any industrial contribution.
LM was funded by the Medical Research Council, UK (Grant Number G0701380/1).
Competing interests KH has received honoraria from AbbVie and Pzer.
Ethics approval UK North-West Multicentre research ethics committee.
Provenance and peer review Not commissioned; externally peer reviewed.
Open Access This is an Open Access article distributed in accordance with the
terms of the Creative Commons Attribution (CC BY 4.0) license, which permits
others to distribute, remix, adapt and build upon this work, for commercial use,
provided the original work is properly cited. See:
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Biologics Register for Rheumatoid Arthritis
from the British Society for Rheumatology
antitumour necrosis factor therapy: results
Risk of lymphoma in patients exposed to
Consortium, Deborah P M Symmons and Kimme L Hyrich
L S Low, William G Dixon, Kath D Watson, BSRBR Control Centre
Louise K Mercer, James B Galloway, Mark Lunt, Rebecca Davies, Audrey
published online August 8, 2016Ann Rheum Dis
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... Thirty-one studies were eligible for inclusion in the present systematic review; eleven population-based cohorts (Arkema et al., 2015;Raaschou et al., 2015;Mercer et al., 2015;Mercer et al., 2017;Desai et al., 2016;Low et al., 2017;Dreyer et al., 2018;Chen et al., 2020;Kim et al., 2020;Pettipher and Benitha, 2020;Hellgren et al., 2021), eight prospective (Listing et al., 2015;Richter et al., 2016;Meissner et al., 2017;Rutherford et al., 2018;Grøn et al., 2019;Grøn et al., 2020;Rahman et al., 2020;Ozen et al., 2021) and eight retrospective cohorts (Yun et al., 2014;Curtis et al., 2016;Zhang et al., 2016;Kim et al., 2017;Pawar et al., 2019;Patel et al., 2021), and four case-control studies (Harada et al., 2017;Sakai et al., 2018;de Germay et al., 2020;Chen et al., 2021), published from 2014 to 2021 (Supplementary Table S3). ...
... Thirteen studies estimated the safety of bDMARDs compared to csDMARDs (Arkema et al., 2015;Mercer et al., 2017;Listing et al., 2015;Mercer et al., 2015;Desai et al., 2016;Harada et al., 2017;Low et al., 2017;Meissner et al., 2017;Sakai et al., 2018;Dreyer et al., 2018;Kim et al., 2020;Ozen et al., 2021;Hellgren et al., 2021). No significant difference in the safety of these therapies was found (RR 0.99; 95% CI 0.82-1.20; ...
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Background: Rheumatoid arthritis (RA) is a systemic inflammatory disease that affects the synovial fluid of joints, tendons, and some extra-articular sites. Biologic agents have been highly effective and are comparable in reducing RA symptoms, slowing disease progression, and improving physical function; however, concerns have been raised about the risks of several potential adverse effects. Thus, this study aimed to assess the safety of biological therapy in patients with rheumatoid arthritis in observational studies using administrative health databases. Methods: PubMed, Embase, Lilacs, Ovid, Scopus, and Web of Science were searched from inception to 21 October 2021. The analysis was divided into five groups: tumor necrosis factor inhibitors (TNFi) versus non-TNFi; TNFi versus csDMARDs; bDMARDs versus csDMARDs; abatacept versus bDMARDs; and TNFi versus Janus kinase inhibitors (JAKi). The adverse events were cancer, cardiovascular events, infection, herpes zoster, tuberculosis, and death. The methodological quality of the studies was assessed by the Newcastle-Ottawa Scale. A random-effects model estimated risk ratios with 95% confidence intervals. Results: Thirty-one studies were eligible for inclusion in the present systematic review, published from 2014 to 2021. A total of 1,039,398 RA patients were assessed. The 31 studies evaluated eleven different biological drugs. No significant differences were found regarding safety between TNFi versus non-TNFi (RR 1.08; 95% CI 0.92–1.28; p < 0.01; I2 = 93.0%), TNFi versus csDMARDs (RR 0.91; 95% CI 0.75–1.10; p < 0.01; I2 = 87.0%), bDMARDs versus csDMARDs (RR 0.99; 95% CI 0.82–1.20; p < 0.01; I2 = 93.0%), abatacept versus bDMARDs (RR 0.80; 95% CI 0.54–1.18; p < 0.01; I2 = 90.0%), and TNFi versus JAKi (RR 3.54; 95% CI 0.30–42.09; p = 0.01; I2 = 81.0%). In the subgroup analysis, among studies comparing abatacept to TNFi, a lower risk of cardiovascular events was associated with abatacept (RR 0.37; 95% CI 0.24–0.55). Conclusion: Our results do not suggest an increased risk of adverse events associated with biological therapy in treating RA patients, indicating a lower risk of cardiovascular events with abatacept than TNFi. However, these findings must be interpreted with caution given the limitations of this study and the low/very low certainty of the evidence. Systematic Review Registration:, identifier [CRD42020190838].
... Moreover, evidence suggests that lymphomas are most prominent in those who are immune deficient. Long-term usage of some drugs, such as tumor necrosis factor-alpha (TNFα) inhibitors, has also been associated with an increased incidence of lymphomas in patients with inflammatory bowel disease and rheumatoid arthritis [25,26]. Lymphomas commonly exhibit some of the stereotypical immunophenotypic molecular lesions that can aid in accurate classification and better treatment patterns for lymphoma progression ( Figure 2) [27]. ...
... Moreover, evidence suggests that lymphomas are most prominent in those who are immune deficient. Longterm usage of some drugs, such as tumor necrosis factor-alpha (TNFα) inhibitors, has also been associated with an increased incidence of lymphomas in patients with inflammatory bowel disease and rheumatoid arthritis [25,26]. Lymphomas commonly exhibit some of the stereotypical immunophenotypic molecular lesions that can aid in accurate classification and better treatment patterns for lymphoma progression ( Figure 2) [27]. ...
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Lymphomas have been increasing at an alarming rate globally and causing deaths worldwide due to the lack of effective therapies. Among different pharmacological agents, selenium (Se) and selenium-related compounds are widely tested and have gained interest as anticancer agents due to their selectivity to cancer and high efficacy for lymphoma treatment over recent decades. Se is a trace non-metallic element identified as an essential micronutrient that mediates a range of biological functions after incorporation into selenoproteins (SePs), and thus affects the overall quality of human health. Specifically, low levels of Se in serum have been linked with aberrant immune functions, cancer, inflammatory diseases, and predictive of worse outcomes in patients with hematological malignancies including lymphoma. Over the past few years, a number of promising selenium compounds (SeCs) have been developed to mimic and alter the functions of SePs to achieve pharmacological interventions such as anticancer, antioxidant, and anti-inflammatory activities with minimal adverse effects by suitable chemical substitution. Here, we have reviewed various lymphoma types and their molecular characterization, along with emphasis on the potential role of Se and SeCs as anti-cancer agents for lymphoma treatment. In addition, we have discussed various pros and cons associated with the usage of Se/SeCs for selectively targeting cancers including lymphomas.
... 8 This possible increased risk of cancer with TNF inhibitors was not confirmed by further meta-analyses of RCTs or registry data, [9][10][11][12][13][14][15] nor by the more recent updates from bDMARD registries worldwide. [16][17][18][19][20][21] Nevertheless, many questions remain, among them the potential differential risk of lymphoma with TNF inhibitors according to their molecular structure (monoclonal antibodies or soluble receptor) 22 23 Effectively, specificities in their mechanism of action (same inhibition of soluble TNF but less inhibition of membrane TNF with the soluble receptor) were supposed to differentially impact the risk of different lymphoma subtypes. 24 Additionally, uncertainties remain regarding the risk of some specific cancers, particularly invasive melanoma, 23 25 that might be increased in northern countries, 26 and virusrelated cancer such as cancer of the cervix 27-29 that can be triggered by immunosuppressants. ...
... This design corresponds to a relevant question in clinical practice, of the risk associated with initiating of a bDMARD versus continuing on csDMARDs in bDMARD The main result-not observing any significant overall increased risk of malignancy in patients with RA initiating bDMARDs-is in concordance with RCT metaanalyses 10 12 and previous observational studies. [16][17][18][19][20][21] Considering the use of bDMARDs in association or not with csDMARDs did not change the results. By contrast, in a previous study on the same database involving patients with inflammatory bowel disease (IBD), the use of conventional immunomodulating agents in adjunction to TNF inhibitors increased the risk of lymphoma. ...
Full-text available
Objective To compare the risk of malignancy between patients with rheumatoid arthritis (RA) initiating their first biological disease-modifying antirheumatic drug (bDMARD) and those continuing conventional synthetic DMARDs (csDMARDs). Methods Nine-year historical Propensity Score (PS) matched cohort study within the French national healthcare database (87% of the French population; ~57 million people), including adults RA without malignancy. Exposures started with the first use of any systemic treatment (csDMARDs and/or bDMARDs). Incident users of bDMARDs were matched on a dynamic PS to patients continuing csDMARDs. Their risk of malignancy was compared by Cox model. Results From 1 January 2007 to 31 December 2014, 83 706 patients with RA started their first systemic treatment (63 837 remained on csDMARDs and 19 869 initiated a bDMARD during follow-up). After dynamic PS matching, 19 727 bDMARD initiators were compared with 19 727 RA remaining on csDMARDs. They did not statistically differ in risk of overall malignancies (HR 0.99 (95% CI 0.86 to 1.14)), solid cancer (HR 0.95 (95% CI 0.82 to 1.11)), nor lymphoma (HR 1.35 (95% CI 0.72 to 2.53)). Results were similar when bDMARDs were given as monotherapy or in association with csDMARDs. Analyses restricted to patients starting TNF inhibitor as first bDMARD compared with matched RA remaining on csDMARDs, provided similar results (HR for overall malignancy 1.03 (95% CI 0.88 to 1.21)). Sensitivity analyses, varying carry-over periods (up to 5 years) to define risk periods, provided similar results. Conclusions In this historical cohort study within the French nationwide healthcare database, the risk of overall, solid or haematological malignancies did not significantly differ between patients with RA initiating bDMARD and those continuing csDMARDs.
... 5 However, several large studies have in recent years shown reassuring results, without increased cancer risks (with a possible exception for non-melanoma skin cancer) for patients with RA on TNF inhibitors and other bDMARDs. [23][24][25][26][27] Thus, although our results from patients with early RA diagnosed in 2006-2019 suggest that rheumatologists are cautious of treating older patients with a history of cancer with b/tsDMARDs, it will be interesting to see whether bDMARD prescription in this patient subgroup will increase in the future. ...
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Objective To examine how comorbidities in patients with early rheumatoid arthritis (RA) associate with use of different disease-modifying antirheumatic drugs (DMARDs). Methods We used Swedish nationwide clinical and quality registers to collect comorbidity data for patients diagnosed with RA during 2006–2019 (n=13 505). We compared the use of DMARDs at diagnosis and after 1 year, in relation to comorbidity categories 5 years prior to RA diagnosis and overall comorbidity burden. For each comorbidity category, we also calculated adjusted ORs of being on treatment with other (or no) DMARDs compared with methotrexate (MTX) monotherapy 1 year after RA diagnosis. Results At RA diagnosis, 68% (n=9178) of all patients were treated with MTX monotherapy, with the lowest proportion in patients with chronic kidney (CKD, 48%, n=50) and respiratory diseases (57%, n=413). At 1 year, most patients still received MTX monotherapy (<11% decrease, across all comorbidity categories). At 1 year, 13% received biological/targeted synthetic DMARDs, with the lowest proportion among patients with malignant diseases (OR=0.69, 95% CI=0.51 to 0.95). Being without DMARD at 1 year was more common among patients with CKD (OR=3.25, 95% CI=2.20 to 4.81), respiratory diseases (OR=1.83, 95% CI=1.32 to 2.53) or a history of hospitalisation due to infection (OR=1.47, 95% CI=1.23 to 1.75), and among patients with higher comorbidity burden and older age. Conclusion In a nationwide setting with universal healthcare, most comorbid conditions do not limit the initiation or continuation of MTX or other DMARDs in early RA, although patients with certain comorbid conditions, higher comorbidity burden and higher age were somewhat less intensively treated.
... 2 4 IRs for lymphoma were higher in patients treated with tofacitinib versus TNFi, although the number of cases reported in the TNFi treatment group in this study (n=1) were lower than previous reports. [25][26][27] In addition, in the overall study population, the risk of malignancies excluding NMSC with tofacitinib versus TNFi was consistent through month 18 and diverged beyond that time; correspondingly, treatment-by-period interaction p values demonstrated that there was a stronger interaction between treatment duration and the risk of malignancies excluding NMSC at month 18 (before vs after), compared with month 24 (before vs after). These findings are in line with a recent real-world study in patients with RA, which demonstrated that in patients ≥50 years of age with CV risk factors, a numerically increased risk of malignancies was observed with tofacitinib versus TNFi. ...
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Objectives To evaluate malignancies and their associations with baseline risk factors and cardiovascular risk scores with tofacitinib versus tumour necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA). Methods In an open-label, randomised controlled trial (ORAL Surveillance; NCT02092467 ), 4362 patients with RA aged ≥50 years with ≥1 additional cardiovascular risk factor received tofacitinib 5 (N=1455) or 10 mg two times per day (N=1456) or TNFi (N=1451). Incidence rates (IRs; patients with first events/100 patient-years) and HRs were calculated for adjudicated malignancies excluding non-melanoma skin cancer (NMSC), NMSC and subtypes. Post hoc analyses for malignancies excluding NMSC, lung cancer and NMSC included risk factors identified via simple/multivariable Cox models and IRs/HRs categorised by baseline risk factors, history of atherosclerotic cardiovascular disease (HxASCVD) and cardiovascular risk scores. Results IRs for malignancies excluding NMSC and NMSC were higher with tofacitinib (combined and individual doses) versus TNFi. Risk of lung cancer (most common subtype with tofacitinib) was higher with tofacitinib 10 mg two times per day versus TNFi. In the overall study population, the risk of malignancies excluding NMSC was similar between both tofacitinib doses and TNFi until month 18 and diverged from month 18 onwards (HR (95% CIs) for combined tofacitinib doses: 0.93 (0.53 to 1.62) from baseline to month 18 vs 1.93 (1.22 to 3.06) from month 18 onwards, interaction p=0.0469). Cox analyses identified baseline risk factors across treatment groups for malignancies excluding NMSC, lung cancer and NMSC; interaction analyses generally did not show statistical evidence of interaction between treatment groups and risk factors. HxASCVD or increasing cardiovascular risk scores were associated with higher malignancy IRs across treatments. Conclusions Risk of malignancies was increased with tofacitinib versus TNFi, and incidence was highest in patients with HxASCVD or increasing cardiovascular risk. This may be due to shared risk factors for cardiovascular risk and cancer. Trial registration numbers NCT02092467 , NCT01262118 , NCT01484561 , NCT00147498 , NCT00413660 , NCT00550446 , NCT00603512 , NCT00687193 , NCT01164579 , NCT00976599 , NCT01059864 , NCT01359150 , NCT02147587 , NCT00960440 , NCT00847613 , NCT00814307 , NCT00856544 , NCT00853385 , NCT01039688 , NCT02281552 , NCT02187055 , NCT02831855 , NCT00413699 , NCT00661661
... [111][112][113] One study included in this SLR suggests, in line with others, 114 115 that bDMARDs reduce the excess risk of MACE in RA more than csDMARDs. 20 Another study included in this SLR, 53 in contrast to a previous one, 116 found a reduction of the excess risk of lymphoma with bDMARDs. It is reasonable to presume that these effects are mediated by the suppression of inflammation, however, that has not yet been proved. ...
Objectives: To perform a systematic literature review (SLR) concerning the safety of synthetic(s) and biological (b) disease-modifying antirheumatic drugs (DMARDs) to inform the 2022 update of the EULAR recommendations for the management of rheumatoid arthritis (RA). Methods: SLR of observational studies comparing safety outcomes of any DMARD with another intervention in RA. A comparator group was required for inclusion. For treatments yet without, or limited, registry data, randomised controlled trials (RCTs) were used. Results: Fifty-nine observational studies addressed the safety of DMARDs. Two studies (unclear risk of bias (RoB)) showed an increased risk of serious infections with bDMARDs compared with conventional synthetic (cs)DMARDs. Herpes zoster infections occurred more with JAKi than csDMARDs (adjusted HR (aHR): 3.66) and bDMARDs (aHR: 1.9-2.3) (four studies, two low RoB). The risk of malignancies was similar across bDMARDs (five studies) and with tofacitinib compared with bDMARDs (one study, low RoB). The risk of major adverse cardiovascular events (MACE) was similar with bDMARDs and tofacitinib (two studies, one low RoB). Thirty studies reported safety from RCTs, with one, designed to evaluate safety, showing that malignancies (HR (95% CI): 1.48 (1.04 to 2.09)) and MACE (HR (95% CI): 1.33 (0.91 to 1.94)) occurred numerically more frequently with tofacitinib (5 mg and 10 mg doses combined) than with TNFi in patients with cardiovascular risk factors. In this study, the risk of venous thromboembolism (VTE) was higher with tofacitinib 10 mg than with TNFi. Conclusion: The safety profile of bDMARDs was further demonstrated. Whether the difference in incidence of malignancies, MACE and VTE between tofacitinib and TNFi applies to other JAKi needs further evaluation.
... Bongartz et al. reported a significantly higher incidence of cancer, but Wu et al. reported decreased cancer risk with TNF inhibitor treatment [1,15]. For site-specific cancer, Raaschou et al. and Hellgren et al. reported nearly double the risk for squamous cell cancer and lymphoma [19,20], while other studies found no association between those types of cancer and treatment with TNF inhibitors [21,22]. ...
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Background Tumor necrosis factor (TNF) inhibitors use in patients with rheumatoid arthritis (RA) has raised safety concerns about cancer risk, but study results remain controversial. This largest nationwide study to date compared cancer risk in TNF inhibitor users to non-biologic disease-modifying anti-rheumatic drug (nbDMARD) users in Korean patients with RA. Methods Data on all the eligible patients diagnosed with RA between 2005 and 2016 were retrieved from the Korean National Health Information Database. The one-to-one matched patients consisted of the matched cohort. The risks for developing all-type and site-specific cancers were estimated using incidence and incidence rate (IR) per 1000 person-years. Adjusted hazard ratio (HR) and 95% confidence interval (CI) were estimated using a Cox regression model. Results Of the 22,851 patients in the before matching cohort, 4592 patients were included in the matched cohort. Treatment with TNF inhibitors was consistently associated with a lower risk of cancer than in the nbDMARD cohort (IR per 1000 person-years, 6.5 vs. 15.6; adjusted HR, 0.379; 95% CI, 0.255–0.563). The adjusted HR (95% CI) was significantly lower in the TNF inhibitor cohort than the nbDMARD cohort for gastrointestinal cancer (0.432; 0.235–0.797), breast cancer (0.146; 0.045–0.474), and genitourinary cancer (0.220; 0.059–0.820). Conclusions The use of TNF inhibitors was not associated with an increased risk of cancer development, and rather associated with a lower cancer incidence in Korean patients with RA. Cautious interpretation is needed not to oversimplify the study results as cancer-protective effects of TNF inhibitors. A further study linking claims and clinical data is needed to confirm our results.
Immune-checkpoint inhibitors (ICIs) have dramatically changed the management of advanced cancers. Designed to enhance the antitumour immune response, they can also cause off-target immune-related adverse events (irAEs), which are sometimes severe. Although the efficacy of ICIs suggests that they could have wide-ranging benefits, clinical trials of the drugs have so far excluded patients with pre-existing autoimmune disease. However, evidence is accumulating with regard to the use of ICIs in this 'at-risk' population, with retrospective data suggesting that they have an acceptable safety profile, but that there is a risk of disease flare or other irAE occurrence. The management of immunosuppressive drugs at ICI initiation in patients with autoimmune disease (or later in instances of disease flare or irAE) remains a question of particular interest in clinical practice, in which there is always a search for the balance between protecting against autoimmunity and ensuring a good tumour response. Although temporary use of immunosuppressants seems safe, prolonged use or use at ICI initiation might hamper the antitumour immune response, prompting clinicians to use the minimal efficient immunosuppressive regimen. However, a new paradigm is emerging, in which inhibitors of TNF or IL-6 could have synergistic effects with ICIs on tumour response, while also preventing severe irAEs. If confirmed, this 'decoupling' effect on toxicity and efficacy could change therapeutic practice in this field. Knowledge of the current use of ICIs in patients with pre-existing autoimmune disease, particularly with regard to the use of immunosuppressive drugs and/or biologic DMARDs, can help to guide clinical practice.
The management of inflammatory rheumatic diseases in patients with a simultaneous or previous malignant disease is associated with complex questions. Difficulties and possible solutions in the interpretation of meaningful studies are presented. Recommendations in guidelines on this topic are discussed. National registries and health insurance databases were examined with respect to the risk of tumor recurrence under disease-modifying antirheumatic drugs; however, these analyses mainly refer to tumor necrosis factor (TNF) inhibitors and rituximab. Data on tumor incidence and, if available, risk of tumor recurrence are summarized for commonly used disease-modifying antirheumatic drugs. Finally, an attempt is made to formulate proposals for rheumatological treatment in patients with a history of malignancy.
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Objectives. To quantify the risk of cancer and compare it with that for the general population in a modern cohort of UK patients with RA and to identify risk factors for cancer among this cohort. Methods. The study population comprised biologic-naïve RA subjects receiving non-biologic disease-modifying therapy recruited to the British Society for Rheumatology Biologics Register from 2002 to 2009. Standardized incidence ratios (SIRs) for cancers were calculated using age- and gender-specific cancer rates in the English population. Poisson regression models adjusted for age and gender using England general population data were used to determine the association of other predictors with incident malignancy. Results. The cohort comprised 3771 individuals with RA contributing 13 315 person-years of follow-up. One hundred and eighty-two cancers were reported: 156 solid and 26 myelo- or lymphoproliferative cancers. The overall SIR was 1.28 (95% CI 1.10, 1.48). Risks of lung cancer (SIR 2.39, 95% CI 1.75, 3.19), Hodgkin lymphoma (SIR 12.82, 95% CI 4.16, 29.92) and non-Hodgkin lymphoma (SIR 3.12, 95% CI 1.79, 5.07) were higher compared with the general population and risks of prostate cancer (SIR 0.35, 95% CI 0.11, 0.82) and cancers of the female genital organs (SIR 0.35, 95% CI 0.10, 0.90) were reduced. Within the cohort, cancer risk was more than 2-fold higher in current or ex-smokers than in non-smokers. Conclusion. The overall incidence of cancer was increased in this national cohort of subjects with RA. The association of RA with certain cancers needs to be considered when studying the effects of biologic therapy, such as anti-TNF, on cancer risk.
TNF is a cytokine whose diverse actions are dependent on the local microenvironment. As a member of the cytokine network, TNF plays an important role in infection and inflammation, but excessive and deregulated production can contribute to disease processes. Likewise in malignant disease, TNF may have a role in cancer therapy and contribute to host response against tumours, but it may also be involved in the progression and spread of the cancer. In experimental models, recombinant TNF can induce significant haemorrhagic necrosis, localised to the tumour vasculature and specific tumour immunity. Although the historical background and preclinical data are promising, systemic therapy with TNF in human cancer has proved highly toxic and is inactive against all tumour types so far tested. Local therapy, particularly isolated limb perfusion, has resulted in complete and long lasting tumour regressions with necrotic activity confined solely to the tumour vascular bed. However, in several animal models, TNF contributes to malignant progression and there is evidence that TNF may have autocrine or paracrine actions in human ovarian cancer.
The aetiology of most haematological malignancies is largely unknown. Studies of migrant populations can provide insights into the relative importance of genetic and environmental risk factors for these diseases. This study compares incidence rates in British Indians, Pakistanis, Bangladeshis, Black Africans, Black Caribbeans, Chinese and Whites in England from 2001 to 2007. We analysed 134 302 haematological cancer registrations with ethnicity obtained by linkage to the Hospital Episodes Statistics database. Mid-year population estimates from 2001 to 2007 were used. Incidence rate ratios adjusted for age, sex and income were calculated, comparing the six ethnic groups to Whites and to each other. Whites had the highest rates for most subtypes. However, Blacks experienced more than double the incidence of plasma cell and mature T-cell neoplasms compared to other ethnic groups. There were also significant differences in incidence between Indians, Pakistanis and Bangladeshis for Hodgkin lymphoma and mature B-cell neoplasms and between Black African and Black Caribbeans for mature B-cell and other lymphoid neoplasms (all P < 0·001). Our results show that the risk of haematological cancers varies greatly by ethnic group, including within those groups that have traditionally been grouped together (South Asians and Blacks) with many of these differences not explicable by known risk factors.
Not all patients with rheumatoid arthritis can tolerate or respond to methotrexate, a standard treatment for this disease. There is evidence that antitumour necrosis factor alpha (TNFalpha) is efficacious in relief of signs and symptoms. We therefore investigated whether infliximab, a chimeric human-mouse anti-TNFalpha monoclonal antibody would provide additional clinical benefit to patients who had active rheumatoid arthritis despite receiving methotrexate. In an international double-blind placebo-controlled phase III clinical trial, 428 patients who had active rheumatoid arthritis, who had received continuous methotrexate for at least 3 months and at a stable dose for at least 4 weeks, were randomised to placebo (n=88) or one of four regimens of infliximab at weeks 0, 2, and 6. Additional infusions of the same dose were given every 4 or 8 weeks thereafter on a background of a stable dose of methotrexate (median 15 mg/week for > or =6 months, range 10-35 mg/wk). Patients were assessed every 4 weeks for 30 weeks. At 30 weeks, the American College of Rheumatology (20) response criteria, representing a 20% improvement from baseline, were achieved in 53, 50, 58, and 52% of patients receiving 3 mg/kg every 4 or 8 weeks or 10 mg/kg every 4 or 8 weeks, respectively, compared with 20% of patients receiving placebo plus methotrexate (p<0.001 for each of the four infliximab regimens vs placebo). A 50% improvement was achieved in 29, 27, 26, and 31% of infliximab plus methotrexate in the same treatment groups, compared with 5% of patients on placebo plus methotrexate (p<0.001). Infliximab was well-tolerated; withdrawals for adverse events as well as the occurrence of serious adverse events or serious infections did not exceed those in the placebo group. During 30 weeks, treatment with infliximab plus methotrexate was more efficacious than methotrexate alone in patients with active rheumatoid arthritis not previously responding to methotrexate.
Objective: To compare the incidence of cancer following tumor necrosis factor α (TNFα) inhibitor therapy to that with commonly used alternative therapies across multiple immune-mediated diseases. Methods: The Safety Assessment of Biological Therapeutics study used data from 4 sources: national Medicaid and Medicare databases, Tennessee Medicaid, pharmacy benefits plans for Medicare beneficiaries in New Jersey and Pennsylvania, and Kaiser Permanente Northern California. Propensity score-adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) were computed to estimate the relative rates of cancer, comparing those treated with TNFα inhibitors to those treated with alternative disease-modifying therapies. The cancer-finding algorithm had a positive predictive value ranging from 31% for any leukemia to 89% for female breast cancer. Results: We included 29,555 patients with rheumatoid arthritis (RA) (13,102 person-years), 6,357 patients with inflammatory bowel disease (1,508 person-years), 1,298 patients with psoriasis (371 person-years), and 2,498 patients with psoriatic arthritis (618 person-years). The incidence of any solid cancer was not elevated in RA (HR 0.80 [95% CI 0.59-1.08]), inflammatory bowel disease (HR 1.42 [95% CI 0.47-4.26]), psoriasis (HR 0.58 [95% CI 0.10-3.31]), or psoriatic arthritis (HR 0.74 [95% CI 0.20-2.76]) during TNFα inhibitor therapy compared to disease-specific alternative therapy. Among RA patients, the incidence of any of the 10 most common cancers in the US and of nonmelanoma skin cancer was not increased with TNFα inhibitor therapy compared to treatment with comparator drugs. Conclusion: Short-term cancer risk was not elevated among patients treated with TNFα inhibitor therapy relative to commonly used therapies for immune- mediated chronic inflammatory diseases in this study.
Concerns exist regarding the potential development of malignancies in patients with rheumatoid arthritis (RA) who are receiving biologic response modifiers (BRMs). To assess the risk of malignancy in patients with RA enrolled in randomized controlled trials (RCTs) of BRMs. Electronic databases, conference proceedings, and websites of regulatory agencies were searched for RCTs evaluating abatacept, adalimumab, anakinra, certolizumab, etanercept, golimumab, infliximab, rituximab, and tocilizumab in RA from inception through July 9, 2012. Independent selection of studies included RCTs that compared the safety of any BRMs used in RA patients with placebo and/or any traditional disease-modifying antirheumatic drugs with a minimum of 24 weeks of follow-up. Independent reviewers selected studies and extracted data on quality and outcomes. Pooled estimates and 95% confidence intervals were calculated for each BRM. Sixty-three RCTs with 29,423 patients were analyzed. No statistically significant increased risk of developing malignancy was observed. Of the 29,423 patients, 211 developed a malignancy during the trial (118 solid tumors, 48 skin cancers, 14 lymphomas, 5 hematologic nonlymphomas, and 26 not specified). The incidence rate for any malignancy during the first year of therapy was very low in the BRM plus methotrexate group (0.77%; 95% CI, 0.65%-0.92%), the BRM monotherapy group (0.64%; 95% CI, 0.42%-0.95%), and the controls (0.66%; 95% CI, 0.52%-0.84%). Anakinra plus methotrexate showed lower odds compared with methotrexate alone (Peto odds ratio, 0.11; 95% CI, 0.03-0.45). No statistically significant risk was observed for specific cancer sites, although the Peto odds ratio for lymphoma was 2.1 (95% CI, 0.55-8.4) in patients receiving tumor necrosis factor inhibitors compared with controls. The use of BRMs among patients with RA included in RCTs of at least 6 months' duration was not significantly associated with an increased risk of malignancy compared with other disease-modifying antirheumatic drugs or with placebo.
Objectives: To investigate the incidence of cancer in arthritis patients treated with or without TNFα inhibitors (TNF-I). Methods: Arthritis patients from the DANBIO database were followed-up for cancer in the Danish Cancer Registry during 2000-2008. Results: Hazard ratio for cancer overall was 1.02 (95% confidence interval (CI) 0.80-1.30) in 3347 TNF-I-treated RA patients compared to non-treated. Excess among TNF-I-treated was found for colon cancer (HR 3.52 (95%CI 1.11-11.15), whereas 6 and 0 ovarian cancer cases were observed in treated and non-treated patients, respectively. Compared to the general population, TNF-I-treated RA patients had increased risk for cancer overall, cancer in lymphatic-haematopoietic tissue and non-melanoma skin cancer, while non-RA patients had no increase in overall cancer risk. Conclusions: Our results suggest that TNF-I therapy in routine care is not associated with an overall excess of cancer in arthritis patients, but observed increased risks of colon and ovarian cancer need further investigation.
Objective. The development and validation of Modified Disease Activity Scores (DAS) that include different 28-joint counts. Methods. These scores were developed by canonical discriminant analyses and validated for criterion, correlational, and construct validity. The influence of disease duration on the composition of the DAS was also investigated. Results. No influence of disease duration was found. The Modified DAS that included 28-joint counts were able to discriminate between high and low disease activity (as indicated by clinical decisions of rheumatologists). Conclusion. The Modified DAS are as valid as disease activity scores that include more comprehensive joint counts.