Article Text
Abstract
Objective Tofacitinib is an oral Janus kinase for the treatment of rheumatoid arthritis (RA). This post hoc analysis assessed whether baseline body mass index (BMI) impacts tofacitinib efficacy in patients with RA.
Methods Pooled data from six phase 3 studies in patients receiving tofacitinib 5 mg (N=1589) or 10 mg (N=1611) twice daily or placebo (advancing to active treatment at months 3 or 6; N=680), ±conventional synthetic disease-modifying antirheumatic drugs, were stratified by baseline BMI (<25, 25 to <30, ≥30 kg/m2). Endpoints (through to month 6) were assessed descriptively: American College of Rheumatology 20/50/70 response rates; changes from baseline (∆) in Disease Activity Score in 28 joints, erythrocyte sedimentation rate (DAS28-4(ESR)), DAS28-4(C-reactive protein), Clinical Disease Activity Index (CDAI), Health Assessment Questionnaire-Disability Index (HAQ-DI) and pain; and proportions of patients achieving DAS28-4(ESR) ≥1.2 and HAQ-DI ≥0.22 decreases from baseline, low disease activity (DAS28-4(ESR) ≤3.2 or CDAI ≤10) and radiographic non-progression (Δmodified Total Sharp Score ≤0.5; months 12 and 24). Estimates were adjusted using multivariable models for selected outcomes. Univariate/multivariable regression analyses determined predictors of month 6 outcomes.
Results Of 3880 patients included, 1690 (43.6%), 1173 (30.2%) and 1017 (26.2%) had baseline BMI <25, 25 to <30 and ≥30 kg/m2, respectively. Tofacitinib showed greater efficacy improvements versus placebo in each BMI category. Differences in efficacy outcomes (adjusted and unadjusted) were generally not clinically meaningful across BMI categories within treatment groups. In regression analyses, BMI was not consistently associated with selected outcomes.
Conclusions Baseline BMI did not consistently affect tofacitinib response suggesting that tofacitinib is an effective oral treatment option for adults with moderate to severe RA regardless of baseline BMI, including patients with BMI ≥30 kg/m2.
Trial registration numbers NCT00814307, NCT01039688; NCT00960440; NCT00847613; NCT00856544; NCT00853385.
- antirheumatic agents
- arthritis, rheumatoid
- therapeutics
Data availability statement
Upon request, and subject to review, Pfizer will provide the data that support the findings of this study. Subject to certain criteria, conditions and exceptions, Pfizer may also provide access to the related individual deidentified participant data. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Key messages
What is already known about this subject?
Previous analyses have shown that some biologic therapies (eg, tumour necrosis factor inhibitors) for rheumatoid arthritis (RA) are associated with an attenuated clinical response in patients with obesity.
What does this study add?
In contrast to what is known for some biologic therapies, this analysis of pooled data from six phase 3 randomised trials of tofacitinib in patients with RA demonstrates that differences in clinical efficacy outcomes with tofacitinib were generally negligible across baseline body mass index (BMI) categories.
Treatment with tofacitinib 5 and 10 mg twice daily led to improvements in efficacy outcomes versus placebo irrespective of baseline BMI.
How might this impact on clinical practice or further developments?
The results of this analysis further inform clinical decision-making of tofacitinib as a treatment option for patients with moderate to severe RA by showing that the efficacy of tofacitinib was comparable across BMI categories.
Introduction
Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). The efficacy and safety of tofacitinib 5 and 10 mg twice daily administered as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), mainly methotrexate (MTX), in adult patients with moderately to severely active RA, have been demonstrated in phase 2,1–5 phase 36–11 and phase 3b/412 13 randomised controlled trials (RCTs) with up to 72 months of follow-up and in long-term extension studies with up to 9.5 years of observation.14–16
Evidence suggests that the efficacy of some RA treatments is impacted by body mass index (BMI). Lower response and/or remission rates with increasing BMI have been reported with csDMARDs (including MTX), sarilumab and some tumour necrosis factor inhibitors (TNFi; eg, adalimumab, etanercept and infliximab), with outcomes most affected in patients with obesity (generally defined as a BMI ≥30 kg/m2).17–20 Obesity is characterised by low-grade systemic inflammation, and is associated with increased production of proinflammatory cytokines, including TNF and interleukin-6,21 and altered expression of adipokines, such as leptin, resistin and adiponectin.22 In patients with RA, obesity appears to be associated with less radiographic progression and structural damage, which may be due to various factors, including body mass and adipokine levels.23–26
This post hoc analysis of data from the tofacitinib RA clinical development programme assessed whether baseline BMI impacts the efficacy of tofacitinib 5 mg twice daily (the recommended dosage for RA) and 10 mg twice daily in adult patients with moderate to severe RA.
Patients and methods
Study design
Data were pooled from six double-blind phase 3 RCTs from the tofacitinib RA clinical development programme (online supplemental table 1). Full eligibility criteria have been reported for each study.6–11
Supplemental material
Patients
Eligible patients were aged ≥18 years with a diagnosis of RA and met the American College of Rheumatology (ACR) 1987 Revised RA Classification Criteria. Patients were randomised to receive tofacitinib 5 or 10 mg twice daily, placebo (advancing to tofacitinib at months 3 or 6), or the active controls MTX (ORAL Start) or adalimumab (ORAL Standard).
Assessments and outcomes
BMI was calculated for each patient as weight (in kilograms (kg))/height (in metres (m)2) at baseline only. Patients were stratified by baseline BMI: <25 (underweight/normal); 25 to <30 (overweight); and ≥30 kg/m2 (obese).
Endpoints assessed included: ACR ≥20%, ≥50%, or ≥70% response criteria (ACR20/50/70 response rates) at months 3 and 6; mean changes from baseline through to month 6 in Disease Activity Score in 28 joints, erythrocyte sedimentation rate (DAS28-4(ESR)), DAS28-4, C-reactive protein (DAS28-4(CRP)), Clinical Disease Activity Index (CDAI), Health Assessment Questionnaire-Disability Index (HAQ-DI) and pain (Visual Analogue Scale (VAS)); the proportion of patients reporting improvements ≥minimum clinically important difference (MCID) in DAS28-4 (ESR) (decrease from baseline ≥1.2) and HAQ-DI (decrease from baseline ≥0.22) at months 3 and 6; proportions of patients achieving low disease activity (LDA) at months 3 and 6 as defined by DAS28-4(ESR) ≤3.2 or CDAI≤10; and the proportion of patients with no radiographic progression, defined as change from baseline in modified Total Sharp Score ≤0.5 at months 12 and 24 (pooled data from ORAL Scan and ORAL Start only).
An additional analysis of select outcomes (ACR20/50/70 response rates, changes from baseline in DAS28-4(ESR), CDAI and HAQ-DI, and DAS28-4(ESR)-defined and CDAI-defined LDA) was performed in which patients were stratified by baseline body weight: <60, 60 to <90 and ≥90 kg.
Statistical analysis
Descriptive analyses
Analyses were performed on the full analysis set, which included patients who were randomised and received ≥1 dose of study treatment. Efficacy analyses at month 3 used a ‘pure’ placebo group (ie, all patients received placebo), whereas the placebo group at month 6 included patients receiving placebo through to month 3 but who advanced to tofacitinib from month 3 to month 6 per protocol.
ACR response rates were assessed using both non-responder imputation (NRI) and observed data. NRI was also used for the rates of achievement of improvements ≥MCID and LDA, while observed data were used for rates of radiographic non-progression and for continuous endpoints. For binary endpoints, comparisons between active treatment groups and placebo were conducted using a normal approximation for binomial proportions with Z-scores to test for statistical significance; continuous endpoints are presented descriptively. No multiplicity adjustment was performed in this post hoc analysis.
Statistical modelling
Regression models were run with treatment group, BMI and treatment by BMI interaction terms to assess consistency of the relationship between BMI and efficacy response across treatments.
Univariate logistic regression analyses (for ACR50 response) and univariate regression analyses (for changes from baseline in DAS28-4(ESR), DAS28-4(CRP), CDAI and HAQ-DI) were performed to determine the relationship between each baseline covariate (described below) and each efficacy endpoint. Multivariable logistic regression analyses (for ACR50 response) and multivariable regression analyses (for changes from baseline in DAS28-4(ESR), DAS28-4(CRP), CDAI, and HAQ-DI) were performed to determine potential predictors for each efficacy endpoint based on a stepwise selection method using 5% level of significance. In both univariate and multivariable analyses, baseline BMI was assessed as both a categorical (ie, BMI <25, 25 to <30, and ≥30 kg/m2) and a continuous variable.
Baseline BMI, age, gender and baseline value of the response variable (for continuous response variables) were forced to be included in the multivariable models. Other baseline covariates considered as candidates for the model selection included glucocorticoid use, history of myocardial infarction, MTX use, race, smoking history, prior TNFi failure, seropositivity (positive for rheumatoid factor and/or anti-cyclic citrullinated peptide antibody), HAQ-DI score, pain (VAS), swollen joint count (SJC), tender joint count (TJC), opioid use and somatisation comorbidity phenotype. The somatisation comorbidity phenotype was defined by the use of concomitant medications for the treatment of depression, anxiety or neuropathic pain, or an ongoing baseline medical diagnosis of depression, chronic pain, fibromyalgia or myalgias. It indicates patients who may have at least one condition, other than RA, that may contribute to chronic pain (eg, fibromyalgia) or that could have influenced pain and the patient’s self-management of their RA (eg, depression).27
Adjusted estimates for specified outcomes by baseline BMI category were calculated based on the multivariable regression analyses. For binary outcomes (ACR20/50/70 response rates at month 6, and radiographic non-progression at month 24), a fitted logistic regression model28 was used to predict the response rate for every patient in the BMI categories being compared (≥25 to <30 and ≥30 kg/m2, compared with BMI <25 kg/m2) as if they had been in a specified BMI category or the reference BMI category, and the differences in the average of the rates by BMI category were computed. For continuous outcomes (change from baseline at month 6 in HAQ-DI, DAS28-4(ESR), DAS28-4(CRP) and CDAI), an analysis of covariance model was run for each endpoint for each tofacitinib dose, with least squares means, mean differences of BMI 25 to <30 and ≥30 kg/m2 from BMI <25 kg/m2, and 95% CIs calculated. All models used the covariates described above, except somatisation comorbidity phenotype, which was not associated with any outcome for either tofacitinib dose in the regression analyses; baseline value of the response variable included for continuous response variables only. Observed data were used and missing values were not imputed.
Additionally, sensitivity analyses were performed using the stepwise multivariable regression analysis and the least absolute shrinkage and selection operator (Lasso) regression method with the lambda plus 1se criterion (ie, the largest value of the tuning parameter lambda such that the error is within one SE of the minimum),29 where no variables were forced into both models.
For all analyses, clinical relevance was defined based on the magnitude of the published MCID for each outcome measure; a difference from the baseline BMI <25 kg/m2 category (reference) of: ≥10% for binary outcomes (eg, ACR50); ≥1.2 units for DAS28-4(ESR)30; ≥1.0 units for DAS28-4(CRP)30; ≥12 units for CDAI30 31; ≥20 units in pain (0–100 mm VAS)30 and ≥0.22 units for HAQ-DI.32
Results
Patients
This post hoc analysis included 3880 patients receiving tofacitinib 5 mg twice daily (n=1589; 41.0%), tofacitinib 10 mg twice daily (n=1611; 41.5%) and placebo (n=680; 17.5%) stratified by baseline BMI; of these, 1690 (43.6%), 1173 (30.2%) and 1017 (26.2%) patients had baseline BMI values of <25, 25 to <30, and ≥30 kg/m2, respectively.
Baseline demographics and disease characteristics (table 1; online supplemental table 2) were generally similar within each BMI category across treatment groups; however, numeric differences were observed between BMI categories. Irrespective of treatment group, patients in the BMI <25 kg/m2 category were younger and were more likely to be Asian and to never have smoked, compared with the higher BMI categories (25 to <30 and ≥30 kg/m2). In contrast, a higher proportion of patients with BMI ≥30 kg/m2 were Caucasian, from the USA, and were ex-smokers, versus patients with BMI <25 and 25 to <30 kg/m2; patients with BMI ≥30 kg/m2 were also slightly less likely to be seropositive. Baseline mean TJC, SJC, HAQ-DI and pain (VAS) scores were higher as BMI category increased.
Higher rates of diabetes, hypertension and prior use of TNFi were observed in patients with BMI ≥30 kg/m2 than patients in the lower BMI categories.
Efficacy outcomes stratified by BMI
Covariate-adjusted estimates for ACR20/50/70 response rates with both tofacitinib doses at month 6 were not significantly different in the BMI 25 to <30 and ≥30 kg/m2 categories compared with the BMI <25 kg/m2 category (figure 1). An exception was the estimated ACR70 response rate in the tofacitinib 5 mg twice daily group, which was significantly lower in the BMI 25 to <30 kg/m2 category, but this difference was <10% and therefore was not considered clinically relevant.
Additionally, at months 3 and 6, ACR20/50/70 response rates (assessed using NRI) were significantly higher in patients receiving either tofacitinib dose versus placebo (p<0.05), regardless of baseline BMI category (online supplemental figure 1). In general, there appeared to be a numeric trend towards somewhat lower ACR20/50/70 response rates at both months 3 and 6 with increasing baseline BMI in patients receiving tofacitinib 5 and 10 mg twice daily; however, the differences between BMI categories were generally <10% and were not considered clinically meaningful (online supplemental figure 1). Similar trends were observed when ACR20/50/70 response rates were assessed using observed data (data not shown). Overall, the trends were less clear for patients receiving placebo, particularly for ACR50/70 response rates.
In general, adjusted estimates for the least squares mean changes from baseline in DAS28-4(ESR), DAS28-4(CRP), CDAI and HAQ-DI with both tofacitinib doses at month 6 were not significantly different with BMI 25 to <30 and ≥30 versus <25 kg/m2 (figure 2). Exceptions included mean decreases in DAS28-4(ESR) and DAS28-4(CRP) (with tofacitinib 10 mg twice daily) and HAQ-DI (with tofacitinib 5 mg twice daily), which were significantly smaller in patients with baseline BMI ≥30 versus <25 kg/m2; these differences were not clinically relevant.
Regardless of BMI category, mean changes from baseline (using descriptive analyses of observed data) at months 3 and 6 in DAS28-4(ESR), DAS28-4(CRP), CDAI, HAQ-DI and pain (VAS) were greater for patients receiving either tofacitinib dose versus placebo (online supplemental figures 2 and 3). Differences in mean changes from baseline through to month 6 in each efficacy endpoint were small and not clinically relevant, based on the definitions used in this analysis, across baseline BMI categories for patients receiving tofacitinib 5 or 10 mg twice daily, or placebo (online supplemental figures 2 and 3).
The proportions of patients receiving tofacitinib 5 and 10 mg twice daily who achieved improvements ≥MCID in DAS28-4(ESR) and HAQ-DI (decreases ≥1.2 and ≥0.22, respectively) at months 3 and 6 were generally similar regardless of baseline BMI (online supplemental figure 4A,B). The proportion of patients achieving DAS28-4(ESR)-defined and CDAI-defined LDA (≤3.2 and ≤10, respectively) with tofacitinib 5 and 10 mg twice daily and placebo, were generally similar across baseline BMI categories at months 3 and 6 (online supplemental figure 4C,D).
Adjusted estimates for the differences in rates of radiographic non-progression with tofacitinib 5 mg twice daily at month 24 were not significantly different in the baseline BMI 25 to <30 and ≥30 kg/m2 categories versus the BMI <25 kg/m2 category. In the tofacitinib 10 mg twice daily group, significantly higher rates of non-progression were observed in patients with baseline BMI ≥30 versus <25 kg/m2 (figure 1D).
In unadjusted analyses, the proportions of patients with radiographic non-progression at months 12 and 24 (based on patients pooled from ORAL Scan and ORAL Start studies) showed a trend towards higher rates of non-progression with higher baseline BMI in patients treated with tofacitinib 10 mg twice daily (online supplemental figure 5).
Efficacy outcomes stratified by weight
An analysis was performed whereby patients were stratified by weight (<60, 60 to 90, ≥90 kg) rather than BMI, and assessed proportions of patients achieving ACR20/50/70 responses, DAS28-4(ESR)-defined and CDAI-defined LDA, and changes from baseline in DAS28-4(ESR), CDAI and HAQ-DI. Results were similar to the analyses of efficacy stratified by BMI (data not shown).
Univariate modelling analyses
Results of the univariate modelling analyses (online supplemental table 3) showed that categorical BMI was a significant predictor for ACR50 response and change from baseline in DAS28-4(ESR) (both for tofacitinib 10 mg twice daily only), whereas continuous BMI was a significant predictor for ACR50 response (both tofacitinib doses), and changes from baseline in DAS28-4(ESR) (both tofacitinib doses), DAS28-4(CRP) (tofacitinib 10 mg twice daily only) and HAQ-DI (tofacitinib 5 mg twice daily only). Neither categorical nor continuous BMI were significant predictors for change from baseline in CDAI. Where BMI was a significant predictor for response, the response generally worsened with increasing BMI, although the effect was small.
Multivariable regression analyses
The models that included BMI by treatment interaction showed insufficient evidence to conclude that there was inconsistency in the relationship between BMI and efficacy response across treatments (data not shown), thus an interaction term was not included in subsequent models. Results of the stepwise multivariable-adjusted regression analyses showed little evidence that categorical BMI was a significant predictor for most response variables for either tofacitinib dose. Continuous BMI was a significant predictor for several outcomes although this was of small magnitude (table 2). Generally, BMI (both as categorical and continuous variable) was not a significant predictor for most of the response variables, with the exception of change from baseline in HAQ-DI for tofacitinib 5 mg twice daily and change from baseline in DAS28-4(CRP) for tofacitinib 10 mg twice daily, although changes were small. Additionally, continuous BMI was a significant predictor for ACR50 response and change from baseline in DAS28-4(ESR) for tofacitinib 10 mg twice daily. Where BMI was a significant predictor for response, the response generally worsened with increasing BMI. Continuous baseline response variables (which had been forced into the model) and seropositivity were significant for all efficacy endpoints; somatisation comorbidity phenotype was not a significant predictor for any endpoint (table 2).
Sensitivity analysis results of the stepwise multivariable regression analyses (with no forced variables) showed that in most cases, BMI was not selected in the final model (online supplemental table 4). In cases where it was selected, the magnitude of the effect was not clinically significant, and was smaller than the MCID of the outcome. Lasso regression with a lambda 1se selection criterion produced generally similar results to the stepwise regression model with regard to selection of BMI in the final model (ie, BMI was usually not selected). In the few models where the Lasso model did select BMI, the magnitude of its effect was negligible.
Discussion
This post hoc analysis of pooled data from six phase 3 RCTs aimed to assess the impact of baseline BMI (<25, 25 to <30 and ≥30 kg/m2) on the efficacy of tofacitinib in patients with moderate to severe RA. These findings showed that treatment with tofacitinib 5 and 10 mg twice daily led to improvements in efficacy outcomes versus placebo, irrespective of baseline BMI. Moreover, in adjusted analyses, differences in efficacy outcomes (ACR20/50/70 response rates, changes from baseline in DAS28-4(ESR), DAS28-4(CRP), CDAI and HAQ-DI) in patients with baseline BMI 25 to <30 and ≥30 versus <25 kg/m2 were not clinically relevant. For the purposes of this analysis, thresholds for clinically relevant differences based on commonly used definitions and consistent with those used for MCIDs and in non-inferiority studies were considered.12 30 32 33 In unadjusted analyses, these efficacy outcomes, as well as pain (VAS) and rates of achieving ≥MCID in DAS28-4(ESR) (decreases ≥1.2) and HAQ-DI (decreases ≥0.22), and DAS28-4(ESR)-defined and CDAI-defined LDA were generally similar across baseline BMI categories within treatment groups, with some small numeric differences noted that were clinically irrelevant.
By contrast, patients with baseline BMI ≥30 kg/m2 who received tofacitinib 10 mg twice daily showed higher rates of radiographic non-progression versus those with baseline BMI <25 kg/m2 in both adjusted and unadjusted analyses; these results were considered clinically relevant as the difference between groups exceeded the threshold defined for this analysis. Across treatments, patients with baseline BMI ≥30 kg/m2 were less likely to be seropositive than those with lower BMI; seropositivity is associated with progression of structural damage.34 35 Additionally, a protective effect for synovitis and osteitis in patients with RA and obesity has previously been noted,23 36 although the reasons for this are unclear; this may be due to effects of adipokines such as adiponectin, levels of which are known to decrease with increased fat mass, and which may have proinflammatory activity in joints.24 However, further research is warranted in this area.
In addition to these analyses, univariate and multivariable regression analyses were performed to investigate the relationship between selected baseline covariates and efficacy endpoints, and to identify potential predictors for these endpoints. Continuous BMI was selected in the final model for more variables than categorical BMI, which is not surprising given that the continuous model would be expected to be more sensitive. While BMI was selected in the multivariable regression analysis as a predictor for changes from baseline in HAQ-DI for tofacitinib 5 mg twice daily, and ACR50 response and changes from baseline in DAS28-4(ESR) and DAS28-4(CRP) for tofacitinib 10 mg twice daily, baseline BMI was not found to have a clinically significant relationship with selected efficacy outcomes, and there was no clear trend between tofacitinib doses. A sensitivity analysis of stepwise multivariable regression analyses and Lasso regression produced similar results, providing further confirmation of the findings. Together with the descriptive analyses, these results suggest that tofacitinib is an effective treatment option for patients with moderate to severe RA regardless of baseline BMI.
The literature has shown mixed results for efficacy among various advanced therapies based on BMI status. For example, ACR response rates have been reported as lower, and less radiographic progression has been noted, in sarilumab-treated patients with higher versus lower BMI.17 37 Some studies have also shown differences in rates of clinical remission or response to treatments when patients are stratified by BMI.17–20 More recently, the impact of BMI on CDAI-defined remission was investigated in patients with RA receiving csDMARDs, primarily MTX, alone or with tocilizumab and, in adjusted analyses, BMI ≥30 kg/m2 was associated with significantly lower rates of remission than lower BMI categories, regardless of DMARD type.38 Other studies of csDMARDs, TNFi (eg, adalimumab, etanercept and infliximab), and sarilumab have also shown that failure to achieve clinical remission or response to treatment or shorter treatment survival is more likely in patients with obesity versus those with normal BMI.17–20 39 The impact of obesity on TNFi may be due to increased levels of circulating TNF, or increased clearance of the drugs.40–42 Accordingly, clinical response to the non-TNFi biologic DMARDs abatacept and rituximab does not generally appear to be affected by BMI,43 44 although it should be noted that intravenous abatacept is dosed by weight; however, the impact of BMI on the response to tocilizumab is less clear.38 45 46
The impact of tofacitinib based on baseline BMI status has recently been evaluated in other post hoc analyses in patients with active psoriatic arthritis (PsA),47 and moderate to severe ulcerative colitis (UC).48 Consistent with this analysis, tofacitinib demonstrated greater efficacy than placebo irrespective of baseline BMI. In patients with UC, efficacy was similar regardless of baseline BMI. However, in patients with PsA, reduced efficacy was observed in patients with baseline BMI ≥35 kg/m2 versus other BMI categories. It should be noted that there are no recommendations to dose-adjust tofacitinib by weight for PsA. Additionally, the analysis of data in patients with PsA included four BMI categories (<25, ≥25 to <30, ≥30 to <35, and ≥35 kg/m2) rather than the three BMI categories used in this analysis.
Limitations of this analysis include that it was performed post hoc, and individual studies were not designed or powered to show differences between baseline BMI categories. Pure placebo data were not available after month 6; further, the placebo data at month 6 were mixed (ie, included patients who switched from placebo at month 3), and therefore, meaningful improvements from baseline may have been observed at month 6 in the placebo group. Additionally, BMI was used as a surrogate for adiposity. The study designs did not include waist circumference measurements which provide a better measure of abdominal obesity, and no metabolic biomarker data (eg, adipokines such as leptin) were collected during the conduct of the phase 3 studies to further support this analysis. Treatment effectiveness was also only assessed in the three common BMI categories (<25, 25 to <30, and ≥30 kg/m2) and did not include further analyses for BMI <18.5 or ≥35 kg/m2.
In addition, some treatments for RA, including TNFi and tocilizumab, are known to affect body composition.49 For example, a recent analysis in patients with RA demonstrated that tocilizumab was associated with significant increases in lean mass without changes in fat mass.50 Future research, therefore, could evaluate the effects of tofacitinib on changes in adiposity, lean mass, and fat mass.
In summary, this post hoc analysis demonstrated that the efficacy of tofacitinib was comparable across baseline BMI categories (<25, 25 to <30 and ≥30 kg/m2). Tofacitinib resulted in greater improvements in RA outcomes versus placebo, irrespective of baseline BMI category. In general, no clinically meaningful differences were observed, although patients with baseline BMI ≥30 kg/m2 who received tofacitinib 10 mg twice daily showed higher rates of radiographic non-progression compared with those with baseline BMI <25 kg/m2. Overall, BMI was not a consistent affecting factor in either the descriptive or regression analyses. The results of this analysis provide information that will inform clinical decision-making of tofacitinib as a treatment option for adult patients with moderate to severe RA regardless of BMI category, including patients in the obese category (BMI ≥30 kg/m2). Further analyses of patients with RA in the real-world setting may provide additional insights into the impact of baseline BMI on the efficacy of tofacitinib.
Data availability statement
Upon request, and subject to review, Pfizer will provide the data that support the findings of this study. Subject to certain criteria, conditions and exceptions, Pfizer may also provide access to the related individual deidentified participant data. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information.
Ethics statements
Patient consent for publication
Ethics approval
This was a post hoc analysis of six randomised controlled studies. All studies were conducted in accordance with the Declaration of Helsinki and Good Clinical Practice Guidelines of the International Council for Harmonisation, and were approved by the relevant Institutional Review Board and/or Independent Ethics Committee of the investigational centres. Patients provided written informed consent. No further ethical approval was required for this post hoc analysis.
Acknowledgments
This study was sponsored by Pfizer Inc. Medical writing support, under the guidance of the authors, was provided by Christina Viegelmann, PhD, CMC Connect, McCann Health Medical Communications, and was funded by Pfizer Inc, New York, NY, USA in accordance with Good Publication Practice (GPP3) guidelines (Ann Intern Med 2015;163:461–464).
References
Supplementary materials
Supplementary Data
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Footnotes
Contributors AHD, FW, LT, LS, JP, HS and JRC conceived or designed the study. JP, HS and ST acquired and analysed the data. All authors had access to the data, were involved in interpretation of data, reviewed and approved the manuscript’s content before submission, and agreed to be accountable for all aspects of the work. AHD accepts final responsibility for the work and controlled the decision to publish.
Funding This study was sponsored by Pfizer Inc.
Competing interests AHD has received consulting fees or other remuneration from AbbVie, Crescendo, Gilead, Mallinckrodt, Pfizer Inc, Regeneron and Sanofi-Genzyme, and is on the speakers bureau for AbbVie, Amgen, Bristol-Myers Squibb, Crescendo, Genentech, Eli Lilly, Mallinckrodt, Pfizer Inc, and Sanofi-Genzyme. MAG-G has received grants/research support from AbbVie, MSD and Roche, and has received consultation fees/participation in company-sponsored speakers bureau from AbbVie, Celgene, MSD, Pfizer Inc, Roche and Sanofi. FW has received research grants from AbbVie, Bristol-Myers Squibb, Eli Lilly, Genzyme, Pfizer Inc, Regeneron, and Sanofi, has received consulting fees or other remuneration from AbbVie, Bristol-Myers Squibb, Genzyme, Novartis, Pfizer Inc, Regeneron, and Sanofi, and is on the speakers bureau for AbbVie, Boehringer Ingelheim, Bristol-Myers Squibb, Genzyme, Novartis, Pfizer Inc, Regeneron, and Sanofi. JMAG has received consulting or speaking fees from AbbVie, Bristol-Myers Squibb, Eli Lilly, Galapagos, MSD, Pfizer Inc, Roche and UCB. LT, LS, HS and ST are employees and shareholders of Pfizer Inc. JP is an employee of Syneos Health, who were paid contractors to Pfizer Inc in the development of this manuscript and for the provision of statistical support. JRC has received research grants from Amgen, Corrona, Crescendo Bio, and Pfizer Inc, and has received consulting fees or other remuneration from AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Eli Lilly, Janssen, Myriad, Pfizer Inc, Roche/Genentech and UCB.
Provenance and peer review Not commissioned; externally peer reviewed.
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