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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

Objective

To examine the threshold in disease activity associated with switching biologic treatment regimens in rheumatoid arthritis (RA) patients in real-world clinical practice.

Methods

Using data from a prospective observational North American cohort of RA patients through December 30, 2009, patients who initiated a new anti–tumor necrosis factor α (anti-TNFα) agent with ≥6 months of followup were identified. Patients were classified as switchers or maintainers depending on whether they continued their anti-TNF treatment or switched (including discontinuation) within 12 months. Level of disease activity measured by the Clinical Disease Activity Index (CDAI) and Disease Activity Score in 28 joints (DAS28) at the time of the switch (corresponding followup visit for maintainers) was examined and random-effect multivariable logistic regression was used to adjust for covariates.

Results

Mean age and RA duration among 1,549 eligible patients were 56.1 and 9.6 years, respectively, 80% were women, 62% were initiating their first biologic, and 30% were initiating their second biologic. At the time of the switch, the median DAS28 and CDAI score were 3.1 and 8.4 among maintainers and 4.0 and 15.2 among switchers, respectively. Maintainers also experienced a greater amount of reduction in disease activity compared with switchers (CDAI: −7.7 versus −2.3, DAS28: −1.1 versus −0.3). The threshold to switch decreased over calendar time, with the greatest amount of reduction observed among patients with moderate disease activity.

Conclusion

On average, physicians and patients were willing to continue biologic treatment for patients who were at or near low disease activity. The threshold to switch decreased over time, especially among partial responders.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

Tumor necrosis factor α (TNFα) inhibitors (anti-TNF therapies) and other biologic agents represent a significant advance in the treatment of patients with rheumatoid arthritis (RA). In clinical trials, these agents have been shown to reduce joint inflammation and radiographic damage and to produce clinical response in up to 70–80% of patients with RA (1). Additionally, based upon available data, a number of trials and observational studies have suggested that among those who failed to respond to the first or second anti-TNF agent, switching to yet another anti-TNF agent or a biologic agent with a different mechanism of action may result in an improved clinical response without an apparent increase in the risk of adverse events/toxicity (2–10).

Despite the favorable profile of anti-TNF agents and other biologics, considerable proportions of patients may discontinue their initial treatment and/or switch to a different agent due to a number of reasons. Within 1 year of treatment initiation, up to 30% of RA patients discontinue their treatment, and the percentage increases to up to 50% at 2 years (4, 7, 11–13). The most common reasons for switching are lack of efficacy and an adverse event/toxicity; together they account for more than 80% of all such cases (4, 7, 12, 14).

Currently, the absence of a well-accepted threshold for “lack of efficacy” presents a major gap in the evidence base to help clinicians to decide whether or not to change therapy, although some data and recommendations exist. For example, the BeSt study, a randomized trial, mandated adjustment of treatment if the target of a Disease Activity Score in 44 joints of ≤2.4 was not met (15). A task force of rheumatologists conducted a systematic literature review of treat to target (T2T) studies and recommended remission as an optimal treatment target, but it acknowledged that low disease activity was a reasonable target for patients with longstanding RA. The task force also acknowledged that other factors, such as comorbidities, may impact target disease activity, and that individualized treatment plans remain important (16). Despite the data and the recent recommendations described above, understanding the current practices of rheumatologists in their threshold for switching remains an evidence gap that is particularly important in light of growing interest in quantifying disease activity and adopting T2T strategies, which mandate treatment acceleration if a predefined level of disease activity has not been reached (17). The key issue is that if the level of disease activity for a T2T protocol is lower than the usual threshold for clinicians and patients to switch patients' biologic treatments, physicians may find such T2T protocols unacceptable.

In addition to levels of disease activity, other factors also play a role in the decision-making process. Yazici and colleagues showed that that the median duration of etanercept and infliximab treatment decreased from 454 days to 237 days once adalimumab became available in the US (13). Likewise, an inverse association between time on treatment and calendar year of treatment initiation was observed based on data from a population-based RA registry containing more than 2,300 courses of anti-TNF treatment (11). The observation of increased switching among biologic agents suggests that the threshold to switch may have lowered over time, a temporal trend that has not been examined in these studies.

We used data from a large North American cohort of patients with RA to assess the level of disease activity associated with switching the biologic treatment regimen and to evaluate the impact of calendar time on the threshold in disease activity to switch. In addition, we explored factors associated with continuing the biologic treatment regimen despite a suboptimal treatment response.

Significance & Innovations

  • We found that in real-world clinical practice, approximately one-half of rheumatoid arthritis (RA) patients who still had a Disease Activity Score in 28 joints of 3.2 or greater after 6–12 months on anti–tumor necrosis factor therapy were continued on the same biologic treatment regimen and did not switch. This finding may inform treat-to-target protocols that recommend switching for all patients not in low disease activity.

  • The magnitude of improvement that was sufficient for physicians not to switch was strongly related to patients' starting disease activity. For this reason, selecting only a single improvement threshold to recommend switching may be infeasible.

  • We observed that over the last several years, the threshold in disease activity to switch has decreased and the likelihood to switch has increased, especially among RA patients with moderate disease activity despite biologic therapy.

  • Physician-related factors were significantly and independently associated with the decision to switch, even after controlling for patients' disease activity.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

Study population.

Study participants consisted of RA patients enrolled in the Consortium of Rheumatology Researchers of North America (CORRONA) registry from October 1, 2001, to December 30, 2009. Details of the CORRONA registry have been published previously (18, 19). Briefly, RA patients satisfying the 1987 American College of Rheumatology diagnosis criteria (20) were enrolled from academic and community rheumatology practices. Data from both physicians and patients were prospectively collected at enrollment and followup clinical encounters at approximately 3–4-month intervals; at each visit, common measures of RA disease activity, functional status, and use of RA medications were collected. When changes in treatment were made, physicians were encouraged but not mandated to report the reason (e.g., lack of efficacy, adverse event). All of the subjects gave written informed consent. The study protocol was approved both by central and local institutional review boards.

Patients who started a new anti-TNF agent and had at least 1 followup visit within 1 year of treatment initiation were eligible to be included in this analysis. A “new” anti-TNF treatment episode required that they had not previously been receiving that particular anti-TNF agent but did not necessarily mean that they had never taken biologics. Patients could contribute more than 1 treatment episode if they sequentially initiated different anti-TNF agents. The visit at which treatment initiation was recorded was considered the “index” visit and baseline covariates of interest were assessed at that visit.

Because response to treatment consists of 2 components, i.e., absolute disease activity and the amount of reduction in disease activity since treatment initiation, we defined patients with “suboptimal clinical response” as those whose Clinical Disease Activity Index (CDAI) score at the time of the followup visit was >10 (moderate disease activity) and who did not have at least a 10-point improvement in their CDAI score compared to baseline, using validated cut points to measure treatment response (21, 22). Among these patients who had neither achieved low disease activity nor had a substantial improvement in their disease activity, we explored factors associated with maintaining (versus switching) their anti-TNF treatment regimen.

Outcomes of interest.

The outcome of the study was whether a patient switched the biologic treatment regimen within 1–6 and 6–12 months after initiation. In the main analysis, switching included either discontinuation of the anti-TNF agent and/or changing to a different biologic agent for reasons other than safety/tolerability. Outcome was evaluated for the 2 time periods separately: patients who switched were classified as early switchers (switched within 6 months) or late switchers (switched between 6 and 12 months) and patients who continued on the initial anti-TNF agents during the 6- and 12-month time periods were classified as maintainers. Therefore, a patient may contribute 2 treatment episodes (e.g., maintainer for the ≤6-month period and the 6–12-month period, maintainer for the ≤6-month period and switcher for the 6–12-month period). For patients with multiple visits within 1–6 and 6–12 months after initiation (most of the eligible patients), the latest visit in each timeframe was used. Because the observations were not independent, the statistical analyses accounted for the clustered nature of the data. Treatment episodes for patients who discontinued and/or changed biologic therapies for reasons of safety/tolerability were excluded from this analysis because switching for these reasons would likely be less discretionary.

Covariates.

Covariates of interest included age, body mass index (BMI), RA disease duration, number of prior disease-modifying antirheumatic drugs (DMARDs), measures of RA disease activity, including the CDAI (22) and Disease Activity Score in 28 joints (DAS28), comorbidities (dichotomized variable: if the patients had at least 1 of the following medical conditions, including hypertension, unstable angina/myocardial infarction/coronary artery disease procedure, congestive heart failure, stroke/transient ischemic attack, cancer, ulcer/gastroesophageal reflux disease/dyspepsia, liver disorder, depression/psychiatric disorder, pulmonary fibrosis/asthma/chronic obstructive pulmonary disease, diabetes mellitus, deep vein thrombosis, elevated creatinine, psoriasis [not arthritis], and anemia/hematologic disorder), physician global assessment of disease activity (100-mm visual analog scale), and laboratory tests (C-reactive protein [CRP] level, erythrocyte sedimentation rate [ESR]). Since laboratory data were not required to be collected within CORRONA and were present for only approximately 50% of all visits represented in this analysis, results for CRP level, ESR, and the DAS28 reflect only the observations for which these data were available. The ratio of swollen joint count (SJC) to tender joint count (TJC) was calculated, and patients were categorized into 2 groups (SJC/TJC <0.4 or ≥0.4) (23). If the TJC was 0, the ratio was assigned the value of 1. Calendar year was grouped to reflect the availability of new biologic agents as follows: 2002–2005 (etanercept, infliximab, adalimumab available), 2006–2007 (abatacept and rituximab available), and 2008–2009 (golimumab and certolizumab available).

Statistical analysis.

For each calendar year, the point prevalence of biologic agent use on April 1 and October 1 and the average CDAI score at the time of switching were calculated. We then compared the descriptive statistics of covariates of interest at baseline visit (the index visit) and the followup visit when the patients were categorized as a “maintainer” or a “switcher.” The same descriptive statistics were calculated in patient subgroups stratified by disease duration (2 years or less versus more than 2 years) and disease activity level measured by the CDAI at baseline: low (CDAI <10), medium (10 ≤ CDAI < 22), and high (CDAI ≥22) (21).

Random-effect logistic regression was used to model the multivariable association between CDAI score at followup visit, change in CDAI score since treatment initiation, calendar year, previous anti-TNF agent use, age at RA onset, number of prior nonbiologic DMARDs, BMI, and time to switch (1–6 months or 6–12 months) with switching (versus maintaining) biologic treatment regimen. Physician preference was estimated by assessing the extent to which switching clustered at the physician level. To examine the interaction between calendar year of treatment initiation and the threshold to switch, a separate multivariable random-effect logistic regression model was built consisting solely of calendar year, disease activity (patients with moderate disease activity [10 ≤ CDAI < 22] versus patients with high or low disease activity), and the interaction term between the two. Finally, random-effect logistic regression was used to model the multivariable association between CDAI score, physician global assessment of disease activity, SJC/TJC, and calendar year at followup visit with switching (versus maintaining) biologic treatment regimen among the subgroup of patients with a suboptimal response (CDAI >10 and change in CDAI <10). SEs were adjusted appropriately to account for the clustered nature of the data.

Sensitivity analysis.

Because reporting a reason for switching was optional, a sensitivity analysis was performed that included only patients who switched explicitly for the reason of lack of efficacy, designated by the treating physician. Also, because results might differ for patients switching to a new biologic versus simply discontinuing the previous biologic, a second sensitivity analysis was performed that defined switching only as changing to a new agent; discontinuations where the patient did not initiate a new biologic within 1 year of starting the previous biologic were excluded.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

Based on CORRONA data through December 30, 2009, a total of 22,966 RA patients were enrolled with 136,738 visits accrued. Overall, the prevalence of biologic agent use within CORRONA increased from 40% in 2003 to 62% in 2009 (Figure 1). When subjects were categorized based on whether they are on their first, second, third, or more biologic agents, the greatest amount of increase in the prevalence was observed among subjects receiving their second through seventh biologic agents. The level of disease activity at which patients switched gradually decreased over time (Figure 2). In 2008–2009, patients who switched had a median CDAI score between 10 and 15, slightly above the CDAI threshold for low disease activity.

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Figure 1. Prevalence of biologic agent use in a large North American cohort of rheumatoid arthritis patients by calendar year and history of previous biologic agent use.

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Figure 2. Level of disease activity (measured by the Clinical Disease Activity Index [CDAI]; the thresholds for low, moderate, and high disease activity for CDAI are <10, between ≥10 and 22, and ≥22, respectively) at which rheumatoid arthritis patients switched their biologic treatment regimen, by calendar year. IQR = interquartile range.

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We identified 3,351 RA patients who initiated a new anti-TNF agent, and after applying the inclusion and exclusion criteria, 1,549 patients were eligible and they contributed 2,302 treatment episodes that were included in this analysis. Among these patients, 1,247 continued on the same treatment and 302 discontinued and/or switched to a different biologic agent within 1 year. Most (62%) of these patients were receiving their first anti-TNF treatment, 30% were receiving their second anti-TNF treatment, and 8% were receiving their third. At the time of treatment initiation, the mean ± SD age was 56.1 ± 12.9 years, the mean RA duration was 9.6 years, and 80% were women.

At the followup visit within 1 year, maintainers had lower disease activity compared to switchers (median CDAI score 8.4 versus 15.2, median DAS28 3.1 versus 4.0) (Table 1). Maintainers also experienced a greater amount of improvement (reduction) in disease activity since treatment initiation (median change in CDAI score −7.7 versus −2.3, median change in DAS28 −1.1 versus −0.3). Significant differences were also observed in TJC and SJC, patient and physician global, pain, and modified Health Assessment Questionnaire (M-HAQ). On average, maintainers received a greater number of prior DMARDs compared to switchers. None of the laboratory measures (i.e., CRP level and ESR) were significantly different between maintainers and switchers (Table 1).

Table 1. Comparison of patient characteristics measured at the time of the biologic treatment regimen switch or the corresponding visit for those maintained on therapy*
 Maintainers (n = 2,000)Switchers (n = 302)P
NMedian (IQR)NMedian (IQR)
  • *

    IQR = interquartile range; RA = rheumatoid arthritis; BMI = body mass index; DMARDs = disease-modifying antirheumatic drugs; CDAI = Clinical Disease Activity Index; DAS28 = Disease Activity Score in 28 joints; TJC = tender joint count; SJC = swollen joint count; MD global = physician global assessment of disease activity; VAS = visual analog scale; M-HAQ = modified Health Assessment Questionnaire; CRP = C-reactive protein; ESR = erythrocyte sedimentation rate.

At time of switch     
 Age at onset of RA, years1,98346.0 (19.0)29748.0 (19.0)0.08
 BMI, kg/m21,99227.8 (8.8)30129.1 (9.2)0.01
 Duration of RA, years1,9927.0 (11.0)3006.0 (11.0)0.91
 Number of prior DMARDs used2,0001.0 (2.0)3022.0 (2.0)< 0.001
 CDAI score1,9018.4 (14.1)29015.2 (19.2)< 0.001
 DAS289253.1 (2.0)1184.0 (1.7)< 0.001
 TJC1,9911.0 (4.0)2992.0 (8.0)< 0.001
 SJC1,9922.0 (6.0)2994.0 (10.0)< 0.001
 Patient global1,91023.0 (42.0)29442.5 (44.0)< 0.001
 MD global1,99613.0 (20.0)30023.0 (33.5)< 0.001
 Subject pain VAS1,94125.0 (40.0)29840.0 (52.0)< 0.001
 M-HAQ1,9600.3 (0.6)2980.5 (0.9)< 0.001
 CRP level, mg/dl7880.5 (1.5)1020.7 (2.3)0.90
 ESR, mm/hour97616.0 (25.0)12217.5 (21)0.93
Change from baseline     
 Change in CDAI1,798−7.7 (17.6)272−2.3 (14.0)< 0.001
 Change in DAS28570−1.1 (2.0)66−0.3 (1.9)< 0.001
 Change in TJC1,963−2.0 (7.0)2960.0 (6.0)< 0.001
 Change in SJC1,964−2.0 (6.0)2960.0 (4.0)< 0.001
 Change in patient global1,817−8.0 (33.0)277−2.0 (33.0)< 0.001
 Change in MD global1,980−13 (26.0)298−5.0 (25.0)< 0.001
 Change in subject pain VAS1,866−9 (32.0)283−2.0 (29.0)< 0.001
 Change in M-HAQ1,8960.0 (0.3)2860.0 (0.3)< 0.001
 Change in CRP level461−0.1 (1.5)580.0 (0.5)0.19
 Change in ESR609−3.0 (15.0)69−1.0 (15)0.31

Stratifying patients by their baseline level of disease activity and RA disease duration, descriptive statistics measured at the followup visit suggested that the level of disease activity and the amount of improvement acceptable enough to continue patients on the biologic treatment regimen was dependent on the patients' initial disease activity (Table 2). For example, for patients with a disease duration ≥2 years, the median change in CDAI score measured at the followup visit for patients who switched was 1.7 units (i.e., slight worsening), −1.3 units (slight improvement), and −9.6 units (some improvement) for those who started in low, moderate, and high baseline disease activity, respectively. Among those who remained on therapy, the median changes in CDAI score at the corresponding visits were −1.9, −7.1, and −20.0 units, respectively, demonstrating that physicians required differing levels of response in order to continue patients on therapy, conditional on where the patient started. Similar trends were observed with respect to patient and physician global and pain. Results were similar for those with an RA disease duration of <2 years (data not shown).

Table 2. Comparison of selected patient characteristics at the time of the biologic treatment regimen switch or the corresponding visit for those who were maintained on therapy among those with a disease duration of ≥2 years, by baseline disease activity level*
 CDAI <1010 ≤ CDAI < 22CDAI ≥22
NMedian (IQR)NMedian (IQR)NMedian (IQR)
  • *

    CDAI = Clinical Disease Activity Index; IQR = interquartile range; MD global = physician global assessment of disease activity; VAS = visual analog scale.

CDAI      
 Switchers448.0 (8.5)7613.8 (13.1)11023.8 (19.6)
 Maintainers2934.3 (6.3)5518.9 (11.5)67912.8 (18.1)
Change in CDAI      
 Switchers441.7 (7.8)76−1.3 (13.4)110−9.6 (17.6)
 Maintainers293−1.9 (5.8)551−7.1 (10.6)679−20.0 (17.5)
Patient global      
 Switchers4535 (45)7745 (40)11050 (45)
 Maintainers29517 (29)55425 (40)68330 (42)
MD global      
 Switchers4815 (20)7724 (22)11330 (30)
 Maintainers3059 (15)56814 (19)71616 (28)
Subject pain VAS      
 Switchers4535 (35)7840 (51)11350 (45)
 Maintainers29820 (28)55625 (40)69732 (42)

After controlling for both the level of disease activity and the amount of improvement from baseline, calendar year was significantly associated with switching (Table 3). Compared to patients who initiated anti-TNF treatment between 2002 and 2005, the likelihood of switching was more than 2-fold greater in 2005–2006 (odds ratio [OR] 2.62, 95% CI confidence interval [95% CI] 1.64–4.19); this effect was even greater in 2008–2009 (OR 6.05, 95% CI 3.72–9.86). There was a significant clustering effect by physician in the decision to switch (OR 1.32, 95% CI 1.16–1.95). Additionally, a significant interaction between calendar year at treatment initiation and disease activity was observed: the likelihood to switch among patients with moderate disease activity (CDAI score between 10 and 22) was greater over calendar time compared to those with low or high disease activity (OR 2.4, 95% CI 1.0–6.0).

Table 3. Multivariable adjusted association between absolute disease activity, change in disease activity, and calendar time with switching the biologic treatment regimen within the first year (a total of 2,070 treatment episodes; 272 switched and 1,798 maintained treatment)*
CovariatesOR (95% CI)
  • *

    There was a significant clustering effect at the physician level in the decision to switch (OR 1.32, 95% CI 1.16–1.95). OR = odds ratio; 95% CI = 95% confidence interval; CDAI = Clinical Disease Activity Index; anti-TNF = anti–tumor necrosis factor.

  • Measured at the visit where the patient either switched or was maintained on therapy.

Disease activity (measured as CDAI) 
 <10 (mild)Referent
 10–22 (moderate)1.94 (1.36–2.75)
 ≥22 (high)3.39 (2.27–5.06)
Improvement in disease activity (change in CDAI from baseline)1.02 (1.01–1.04)
Calendar year 
 2002–2005Referent
 2006–20072.62 (1.64–4.19)
 2008–20096.05 (3.72–9.86)
Number of previous anti-TNF agents used 
 0Referent
 ≥11.43 (1.08–1.89)
Timing of the followup visit 
 ≤6 monthsReferent
 6–12 months1.26 (0.93–1.69)

To examine whether the observed association between calendar time and switching biologics may be explained by changing patient characteristics over time, we have compared baseline patient characteristics across the 3 cohorts of patients, including age, age at RA onset, disease duration, M-HAQ, DAS28, CDAI, patient and physician global, and glucocorticoid use. The distributions of these characteristics were comparable (data not shown).

The sensitivity analysis that restricted the study population to only those who switched for physician-designated reasons of lack of efficacy yielded a similar effect of calendar year (data not shown). The interaction between moderate disease activity and calendar year at treatment initiation was likewise stronger (OR 3.4, 95% CI 1.1–10.2). When those who did not initiate another biologic agent after discontinuing the initial anti-TNF agent were excluded, the results were consistent with those from the main analysis, and the interaction between calendar time and moderate disease activity was similar (OR 5.7, 95% CI 1.1–30.4).

We identified a subgroup of 667 treatment episodes (159 switched and 508 maintained therapy) with suboptimal response to their anti-TNF treatment (CDAI >10 and change in CDAI greater than −10). After adjusting for comorbidities, level of disease activity, and calendar year, patients with a SJC/TJC ratio of <0.4 and higher (better) physician global were more likely to be maintained on the same therapy (Table 4).

Table 4. Multivariable adjusted association between CDAI, MD global, SJC/TJC, and calendar year at followup visit with switching (versus maintaining) biologic treatment regimen among patients with a suboptimal response (a total of 648,140 switched and 508 maintained treatment)*
CovariatesOR (95% CI)
  • *

    Patients with a suboptimal response were defined as patients whose CDAI at the time of the switch was >10 and reduction in CDAI since treatment initiation was <10. CDAI = Clinical Disease Activity Index; MD global = physician global assessment of disease activity; SJC = swollen joint count; TJC = tender joint count; OR = odds ratio; 95% CI = 95% confidence interval.

  • Measured at the visit where the patient either switched or was maintained on therapy.

  • Scaled from 0–100, with higher numbers representing better disease control.

MD global (rescaled, in units of 5 points)0.93 (0.88–0.99)
SJC/TJC ratio 
 ≥0.4Referent
 <0.40.56 (0.33–0.96)
CDAI (in units of 10 points)1.02 (1.00–1.04)
Calendar year (grouped to reflect the availability of newer biologics) 
 2002–2005Referent
 2006–20073.11 (1.70–5.68)
 2008–20096.29 (3.54–11.18)
Comorbidities 
 NoReferent
 Yes1.32 (0.87–2.00)

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

We found that within 1 year of starting new anti-TNF therapy, patients who were continued on their initial anti-TNF treatment regimen had, on average, 3–4 tender/swollen joints, a median DAS28 of 3.1, and a median CDAI score of 8.4. The results suggest that in this large North American RA cohort, a disease state close to low disease activity is considered “good enough” to continue anti-TNF therapy. Additionally, the results of our study support the hypothesis that, in addition to level of disease activity and the amount of improvement since treatment initiation, more recent calendar time is strongly and significantly associated with a 3- to 6-fold increase in the likelihood to switch among biologic agents. We found a significant clustering effect at the physician level, suggesting that physicians have quantifiable differences in their proclivity to switch patients. Finally, we observed that among partial responders, physician perception of disease activity, as measured by physician global and the SJC/TJC ratio, played a role in the decision to switch, independent of the measurement of disease activity quantified by the CDAI.

The amount of residual RA disease activity that is sufficient to continue therapy in our study is similar to that from a cross-sectional survey of more than 200 RA patients that found that a DAS28 of 3.5 was satisfactory enough to stay on their current treatment regimen (24). The threshold for switching in our study is higher than those mandated in T2T studies and proposed by the task force, suggesting that a singular nonflexible target for T2T guidelines regardless of individual patient characteristics, e.g., level of disease activity at treatment initiation, may not be feasible or widely accepted in routine practice. As we have hypothesized, the threshold in disease activity at the time of the switch, rather than staying static, has lowered over calendar years. Perhaps most important is the finding of a significant interaction between disease activity and calendar year; we found that the effect of calendar time was greater for those with moderate disease activity compared with those with low or high disease activity at the time of the switch, suggesting that the availability and penetration of newer biologic agents makes the greatest impact on the treatment of these patients for whom the threshold to switch is perhaps more subjective.

The finding that calendar time was significantly associated with switching is consistent with the report in 2 separate studies that the time patients stayed on their anti-TNF agents became shorter over time (11, 13). Although discordant results have reported that no difference in 1-year drug survival rate and threshold to switch was observed over time, those findings may not be comparable to ours because they looked at an earlier and shorter calendar time, while our study data spanned a longer and more recent time period where the number of alternative biologic agents was greater (7, 12). This discrepancy suggests a fast-changing pattern in the utilization of biologic agents among RA patients and that in future studies examining biologic agent use, the timeframe should be clearly defined and calendar time adjusted for.

We observed a significant clustering effect by physician associated with switching, consistent with the idea that there are individual physician-specific factors that affect treatment choices. Physician preference to switch may be one of these factors. Other physician- or practice-associated factors may also contribute to this effect (e.g., insurance status, formulary status of particular biologics, case mix of the physician's RA patients). This “natural variability” allows for examination of outcomes associated with switching versus maintaining in future comparative effectiveness research analyses.

Previous data from a large population-based RA cohort showed that a sizable proportion of RA patients was maintained on the same treatment despite suboptimal treatment response (3). We observed the same finding; among 667 treatment episodes with suboptimal response, 508 were not changed to a new therapy. A higher (better) physician global and an SJC/TJC ratio of <0.4 were significantly associated with not switching. These two measures are helpful in as much as they may assist in identifying limitations of the CDAI, which in certain patients may be influenced (through the patient global score) by factors other than RA (e.g., low back pain, fibromyalgia). A low SJC/TJC ratio has been suggested to reflect a discrepancy between a low level of disease activity perceived by the physician and a higher level of disease activity perceived by the patient that may be influenced by chronic pain syndromes (23). Even after multivariable adjustment for CDAI and other covariates, an SJC/TJC ratio of <0.4 was associated with maintaining therapy among patients who continued to have moderate or high disease activity and had not had a substantial improvement measured by the CDAI.

Among this subgroup of patients, it is possible that other factors that we did not assess may contribute to a reluctance to switch. For example, Wolfe and Michaud found that many RA patients were satisfied with their treatment despite continued moderate disease activity (25). Another limitation of our study is that we did not have the physician-designated reason for treatment switching for all treatment episodes, as this question was optional and only started being collected in 2007. To address this issue, we conducted a sensitivity analysis including only those who switched with a physician-designated reason related to a lack of efficacy. The results from the sensitivity analysis were similar to those from the main analysis. Additionally, our findings were further supported by similar results from the sensitivity analysis in which switching referred to only when the patient changed to a different biologic. Another limitation is that our results may not be generalizable to patient populations outside the US, e.g., countries that do not allow for biologic treatment for RA patients with low or moderate disease activity or where other restrictions (e.g., insurance) strongly affect biologic use.

Our study has a number of strengths. We used data collected through the end of 2009 and therefore were able to study the treatment patterns in recent years. Anti-TNF agents and other biologics in general are quickly evolving to more ubiquitous use, and patients who fail to respond to anti-TNF agents now have a number of alternatives to try. Additionally, the CORRONA cohort collects data at routine clinical encounters from a large number of physicians and patients drawn from both community and academic practices and has few inclusion criteria other than established RA. Therefore, the data represent diverse patient populations and treatment patterns from many practices in the US.

In conclusion, the results of our study suggest that low disease activity is a sufficient target for most clinicians and patients to be satisfied enough to continue biologic therapy. Moreover, we observed increased switching and likely a lowered threshold to switch in recent years. This temporal trend is significantly more pronounced among those with moderate disease activity, who account for a large proportion of all RA patients (26). The discrepancy between levels of disease activity as measured and perceived by physicians and patients may partially explain why treatment was not accelerated in patients with a seemingly suboptimal treatment response measured by the CDAI. Additional research is needed to determine the optimal level of disease activity above which switching is justified, and the best sequence of biologic agents to use in order to achieve favorable long-term outcomes. Finally, given large disparities in the access and rate of utilization of biologic agents throughout the world, it is likely that observational data from country-specific registries will be needed to characterize and generate data useful to inform more optimal switching regimens (27).

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Curtis had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Zhang, Reed, Baumgartner, Curtis.

Acquisition of data. Shan, Kremer, Greenberg.

Analysis and interpretation of data. Zhang, Shan, Reed, Kremer, Baumgartner, Curtis.

ROLE OF THE STUDY SPONSOR

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES

The Consortium of Rheumatology Researchers of North America receives support from Abbott, Amgen, BMS, Centocor, Genentech, Lilly, and Roche in the form of contracted subscriptions to the database. Amgen contributed to the design of this analysis and was involved in the early stage of protocol development as part of its subscription contract. The final analysis plan and interpretation of the results were solely those of the authors. Publication of the article was not contingent on the approval of Amgen.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ROLE OF THE STUDY SPONSOR
  9. REFERENCES