The lupus impact tracker is responsive to changes in clinical activity measured by the systemic lupus erythematosus responder index

Abstract

Objective

The lupus impact tracker (LIT) is a 10-item patient reported outcome tool to measure the impact of systemic lupus erythematosus or its treatment on patients’ daily lives. Herein, we describe the responsiveness of the LIT and LupusQoL to changes in disease activity, using the systemic lupus erythematosus responder index (SRI).

Methods

A total of 325 adult systemic lupus erythematosus patients were enrolled in an observational, longitudinal, multicentre study, conducted across the USA and Canada. Data (demographics, LIT, LupusQoL, BILAG, SELENA–SLEDAI) were obtained three months apart. Modified SRI was defined as: a decrease in SELENA–SLEDAI (4 points); no new BILAG A, and no greater than one new BILAG B; and no increase in the physician global assessment. Standardised response mean and effect size for LIT and LupusQoL domains were calculated among SRI responders and non-responders. Wilcoxon’s test was used to compare the LIT and LupusQoL variation by SRI responder status.

Results

Of the participants 90% were women, 53% were white, 33% were of African descendant and 17% were Hispanic. Mean (SD) age and SELENA–SLEDAI at baseline were 42.3 (16.2) years and 4.3 (3.8), respectively. Mean (SD) LIT score at baseline was 39.4 (22.9). LIT standardised response mean (effect size) among SRI responders and non-responders were −0.69 (−0.36) and −0.20 (−0.12), respectively (P = 0.02). For LupusQoL, two domains were responsive to SRI: standardised response mean (effect size) for physical health and pain domains were 0.42 (0.23) and 0.65 (0.44), respectively.

Conclusions

LIT is moderately responsive to SRI in patients with systemic lupus erythematosus. Inclusion of this tool in clinical care and clinical trials may provide further insights into its responsiveness. This is the first systemic lupus erythematosus patient reported outcome tool to be evaluated against composite responder index (SRI) used in clinical trials.

Keywords

Systemic lupus erythematosus lupus impact tracker patient reported outcome LupusQoL

Introduction

Because systemic lupus erythematosus (SLE) is a chronic disabling disease, a comprehensive assessment of patients has to include quality of life (QoL), as measured by patient reported outcomes (PROs) alongside disease activity and damage. Disease-specific PROs in SLE have only been developed in the past 10 years, but data on their responsiveness are not yet fully available. It is important to know the ability of these questionnaires to capture any significant change, for better or for worse, in SLE-related health status, before their use in clinical trials. Moreover, as SLE is characterised by periods of flares and remission, knowing the responsiveness of the measurement tool is also necessary for their use in clinical practice and epidemiological studies. One of the most important factors limiting the use of existing PROs or QoL questionnaires in clinical practice or in clinical trials is the length of the questionnaires. Most lupus PRO questionnaires include 30–40 questions and therefore impose a significant survey burden on the patient. They are thus not feasible for use in busy practices either. To respond to this need, the lupus impact tracker (LIT) was designed for use in routine clinical practice.¹ It is a short questionnaire, derived from the LupusPRO, a validated SLE-specific PRO.² The 10 questions in the LIT include the concept of cognition, lupus medications, physical health, the impact of pain/fatigue, emotional health, body image and planning/desire/goals. The LIT was shown to be reliable, valid and responsive to patient-reported changes in health status.¹ The systemic lupus erythematosus responder index (SRI) is a composite disease activity tool now being increasingly used as the primary endpoint in recent SLE trials.³ Post-hoc analysis of the Belimumab trial suggested an improvement in the vitality domain of the medical outcomes study short form 36 (SF-36) among SRI responders as compared to SRI non-responders.⁴ Thus far, the responsiveness of generic or disease-specific patient-reported outcome tools against SRI has not been assessed in SLE. We aimed to determine the responsiveness to change in SLE-related disease activity, as recorded by the SRI, of a short SLE impact questionnaire, the LIT,¹ and a specific health-related QoL questionnaire (LupusQoL)⁵ in SLE.

Patients and methods

Study design

To study responsiveness of a PRO tool against the composite response index (SRI), we utilised existing de-identified data collected from 20 sites from within USA and Canada to validate longitudinally the LIT (GHO-09-1621).⁶ Inclusion criteria for the study were age 18 years or greater, SLE according to American College of Rheumatology classification criteria and an informed consent. Patients meeting the criteria for rheumatoid arthritis or another connective tissue disease were excluded.

SLE patients attended two clinical study visits: a baseline visit and a 3-month (±2 weeks) follow-up visit. Demographic information and laboratory specimens were collected prior to the meeting with the physician. Patients completed the LIT, the medical outcomes study SF-36 version 2 (SF-36v2),⁷ and the LupusQoL at baseline. At the 3-month follow-up visit, patients completed the LIT and the LupusQoL. At baseline and the 3-month follow-up, rheumatologists conducted a series of assessments that included the safety of estrogens in lupus erythematosus national assessment–lupus systemic lupus erythematosus disease activity index (SELENA–SLEDAI, including the physician global activity (PGA) and SELENA flare index)⁸ and British Island Lupus Assessment Group (BILAG) index.⁹

Data collection

Clinical outcome measures

All disease activity assessments were conducted by a rheumatologist trained in the use of the specific instruments using SELENA–SLEDAI and BILAG. SELENA–SLEDAI is a 24-item weighted scale based on the physician’s assessment of SLE symptoms, examination and laboratory values at the time of the visit or in the preceding 10 days. The BILAG is an SLE disease activity measure of flares and the improvement or worsening of lupus disease in various organs. In addition to classic A (active) to E (inactive and never been) scoring in each organ, an additive numerical scoring system has been developed.¹⁰ The SRI is a composite assessment that aims to define responders to a given treatment. It has been increasingly used in clinical trials, as it captures the strengths of both tools. A responder, according to the SRI, is defined as a person with a 4-point or greater reduction from baseline in the SELENA–SLEDAI score, no new BILAG A score and no more than one new BILAG B organ domain score compared with baseline, and no worsening in PGA (<0.3 points increase from baseline). We separated non-responders into stable active and stable inactive patients. Stable active had a baseline SLEDAI of 6 or greater and/or at least one BILAG A or B, and did not meet the SRI for remission criteria at 3 months. Stable inactive patients had a baseline SLEDAI less than 6 and no BILAG A or B. Baseline disease activity in this group was too low to allow them to meet the SRI criteria at 3 months. Both groups were combined for the SRI non-responder comparisons against the SRI responder group.

Patient reported outcome measures

The LIT has 10 items and is scored by summing the item responses and linearly transforming the summed score into a 0–100 scale (see supplementary material). Higher LIT scores indicate a greater impact of lupus on the patient’s life.¹ The SF-36v2 is a 36-item, self-report survey of functional health and wellbeing, with a 4-week recall period. Responses to 35 of the 36 items are used to score an eight-domain profile of functional health and wellbeing scores: Physical functioning (PF), role limitations due to physical health (RP), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE) and mental health (MH). In addition, physical and mental health summary component scores (PCS and MCS, respectively) are computed from scale scores.⁷ The LupusQoL is a 34-item SLE-specific health-related QoL instrument consisting of eight health-related domains: physical health, pain, planning, intimate relations, burden to others, emotional health, body image and fatigue. A higher score on SF-36v2 and the LupusQoL scores indicate better health-related QoL.⁵

Statistical methods

Quantitative variables were described in terms of mean ± standard deviation (SD) or median (interquartile range; IQR) depending on the distribution. Baseline characteristics of SRI responder and non-responder patients were compared using non-parametric Wilcoxon tests or Chi-square tests, when appropriate. Variations in QoL domain scores between baseline and M3 were compared across groups defined by age, sex, disease activity and ethnicity using Wilcoxon tests. Responsiveness was studied by: comparing the mean variation in QoL domain scores between SRI responders and non-responders with Wilcoxon tests; and computing standardised response mean (SRM) and effect size (ES), with corresponding confidence intervals for SRI responders and non-responders. The SRM statistic was obtained by dividing the observed total change in the QoL score, by the SD of the change in the QoL score. ES was defined as the ratio of observed total change in the QoL score to the SD of the baseline QoL score. For reference, we used SRM and ES values of 0.20, 0.50 and 0.80 to denote small, moderate and large changes, respectively. We hypothesised that the ES and SRM among responders would be less compared to non-responders for a given QoL score. A bootstrap method was used to compute confidence intervals. SAS software 9.3 was used.

Results

Demographics and disease activity

Complete SRI data were obtained in 295 (calculated from both baseline and M3 disease activity scores) of the 325 SLE patients enrolled at the baseline visit. Patients’ mean age was 42 years, range 17–75 years. The majority of patients were women (90%), just over half were Caucasian (53%) and one-third were African descendants (33%). The baseline median total SELENA–SLEDAI score and PGA ratings were 4.0 (IQR 2–6) and 1.0 (IQR 0–1), respectively. At 3 months, 40 patients met the SRI responder criteria and 255 patients were considered SRI non-responders (71 stable active and 184 stable inactive). Baseline demographics were similar between SRI responders and non-responders. Mean LIT (±SD) was not significantly different at baseline between SRI responders and non-responders (39.2 ± 23.2 and 40.3 ± 21.7, respectively, P = 0.35) (Table 1). No significant variation in disease activity was observed among ‘stable active’ and ‘stable inactive’ groups (mean SELENA–SLEDAI variation +0.8 and +0.4 in stable active and stable inactive groups, respectively, P > 0.05, mean numerical BILAG −2.6 and +1.8 in stable active and inactive groups, respectively, P > 0.05). Mean baseline disease activity was significantly higher in SRI responders, according to numerical BILAG (12.7 ± 9 versus 8.5 ± 8.1, P = 0.002), but neither total SELENA–SLEDAI (9.0 ± 3.6 versus 3.6 ± 3.4, P = 0.58) nor PGA (1.6 ± 0.7 versus 1.0 ± 0.8, P = 0.36) were significantly different at baseline (Table 1). Baseline QoL of SRI responders was significantly more impaired than that of SRI non-responders in the SF-36 GH, SF and PCS domains, and in the LupusQoL ‘burden to others’ domain. The difference was not significant in other LupusQoL and SF-36 domains.

Table 1

Comparison of baseline demographics, disease activity and quality of life among SRI responders and non-responders

	Overall (n = 295)	Clinical response according to SRI
		SRI non-responders (n = 255)		SRI responders (n = 40)
		Stable inactive (n = 71)	Stable active (n = 184)		P value^c
Age (SD)	42.8 (16.6)	43.7 (13.0)	43.4 (18.4)	38.2 (12.5)	0.18
Women, n (%)	265 (90%)	65 (92%)	164 (89%)	36 (90%)	0.85
Disease activity ^a
Physician global activity (PGA)	1.0 (1.0, 2.0)	1.0 (0.0, 1.0)	1.0^b (1.0, 2.0)	1.5 (1.0, 2.0)	<0.001
SELENA–SLEDAI	4.0 (2.0, 6.0)	0.0 (0.0, 2.0)	4.0^b (2.0, 6.0)	8.0 (6.0, 12.0)	<0.001
Total numerical BILAG	8.0 (1.0, 13.0)	0.0 (0.0, 1.0)	9.0^b (8.0, 16.0)	12.0 (8.0, 18.5)	<0.001
Quality of life ^a
a. Lupus impact tracker ^a	35.0 (15.0, 52.5)	35.0 (17.5, 52.5)	40.0^b (22.5, 57.5)	35.0 (26.3, 57.5)	0.31
b. SF-36 ^a
Physical functioning (PF)	60.0 (35.0, 85.0)	70.0 (40.0, 95.0)	55.0^b (30.0, 80.0)	65.0 (37.5, 85.0)	0.17
Role physical (RP)	50.0 (31.3, 81.3)	62.5 (37.5, 93.8)	50.0^b (28.1, 75.0)	50.0 (31.3, 71.9)	0.17
Global health (GH)	37.0 (22.0, 62.0)	45.0 (30.0, 67.0)	35.0^b (20.0, 62.0)	35.0 (22.0, 47.0)	0.037
Social functioning (SF)	62.5 (37.5, 75.0)	62.5 (50.0, 87.5)	56.3^b (37.5, 75.0)	50.0 (37.5, 75.0)	0.024
Role emotional (RE)	66.7 (50.0, 91.7)	75.0 (50.0, 100.0)	66.7 (50.0, 91.7)	66.7 (50.0, 95.8)	0.52
Mental health (MH)	65.0 (50.0, 80.0)	70.0 (50.0, 85.0)	65.0^b (50.0, 80.0)	60.0 (50.0, 80.0)	0.41
Physical component summary (PCS)	40.7 (33.2, 49.9)	43.1 (34.5, 54.2)	39.0^b (32.2, 47.7)	40.0 (33.7, 46.6)	0.05
Mental component summary (MCS)	44.9 (36.8, 53.7)	48.0 (38.6, 55.0)	44.0 (36.0, 53.3)	44.5 (36.8, 52.9)	0.44
SF-6D	0.6 (0.5, 0.7)	0.6 (0.6, 0.8)	0.6^b (0.5, 0.7)	0.6 (0.6, 0.6)	0.08
c. LupusQoL ^a
Physical health	68.8 (46.9, 87.5)	71.9 (50.0, 90.6)	65.6^b (46.9, 87.5)	68.8 (48.4, 79.7)	0.38
Pain	66.7 (41.7, 91.7)	75.0 (50.0, 100.0)	66.7^b (41.7, 91.7)	58.3 (41.7, 83.3)	0.18
Planning	75.0 (50.0, 100.0)	83.3 (66.7, 100.0)	75.0^b (50.0, 100.0)	75.0 (41.7, 95.8)	0.10
Intimate relationship	75.0 (50.0, 100.0)	75.0 (50.0, 100.0)	75.0 (50.0, 100.0)	75.0 (50.0, 100.0)	0.72
Burden to others	66.7 (33.3, 83.3)	75.0 (50.0, 91.7)	66.7^b (25.0, 83.3)	50.0 (25.0, 79.2)	0.028
Emotional health	79.2 (65.0, 91.7)	83.3 (70.8, 100.0)	79.2^b (63.8, 91.7)	79.2 (56.3, 91.7)	0.06
Body image	80.6 (55.0, 95.0)	87.5 (58.3, 95.0)	80.0 (55.0, 95.0)	70.0 (45.0, 90.0)	0.29
Fatigue	56.3 (37.5, 75.0)	62.5 (37.5, 81.3)	56.3^b (31.3, 75.0)	56.3 (40.6, 75.0)	0.48

Values are median (Q1, Q3) unless specified.

P value for comparison between stable inactive and stable active <0.05.

P value for global comparison between the three groups (stable active, stable inactive and responders).

The LIT showed no ceiling or floor effects. Significant floor effects were seen with LupusQoL domains of intimate relationship (28.5%) and planning (29%), while ceiling effects for these two domains were 9% and 4%, respectively.

Factors influencing QoL between baseline and 3 months

No baseline characteristic was significantly associated with the variation in LIT, SF-36 or LupusQoL domains scores between baseline and the 3-month visit, including country of origin (Canada or USA), age, sex, ethnicity, or high disease activity, as assessed by SELENA–SLEDAI or BILAG.

Responsiveness

The decrease in the impact of lupus, as measured by the LIT score was significantly greater among SRI responders than non-responders (−7.9 ± 14.4 versus −2.9 ± 11.4 in non-responders, P = 0.023) (Table 2). This variation represented a moderate SRM and ES for the variation in LIT scores in SRI responders (Table 2). The improvement in ‘physical health’ and ‘pain’ QoL domains, as measured by LupusQoL, was significantly higher among SRI responders than non-responders, respectively (PH + 5.7 ± 13.6 versus + 0.6 ± 16.5, P = 0.042 and pain + 12.6 ± 19.2 versus + 1.6 ± 19.3, P = 0.002). These differences translated into small (‘physical health’ LupusQoL) and moderate (‘pain’ LupusQoL) SRM and ES among SRI responders (Table 2). No significant differences in other LupusQoL domains were noted between responders and non-responders. The variation in LIT did not differ significantly between patients with a new A/B (n = 32) and patients who were stable or improving.

Table 2

Responsiveness of LIT and LupusQoL stratified by SRI status

	SRI responders (n = 40)					SRI non-responders (n = 255)
	Mean variation	SRM	95% CI	ES	95% CI	Mean variation	SRM	95% CI	ES	95% CI	P value^a
LIT	−7.9	−0.68	[−1.05; −0.28]	−0.36	[−0.54; −0.16]	−2.9	−0.19	[−0.32; −0.06]	−0,12	[−0.2; −0.04]	0.023
LupusQoL
Physical health	+5.7	+0.42	[0.07; 0.74]	+0.23	[0.04; 0.41]	+0.5	+0.03	[−0.09; 0.15]	+0.02	[−0.05; 0.09]	0.042
Pain	+12.6	+0.65	[0.36; 0.91]	+0.44	[0.19; 0.66]	+1.6	+0.08	[−0.04; 0.20]	+0.06	[−0.03; 0.13]	0.002
Planning	+3.5	+0.18	[−0.16; 0.50]	+0.13	[−0.10; 0.37]	+1.2	+0.07	[−0.06; 0.19]	+0.04	[−0.03; 0.12]	NS
Intimate relationship	−0.7	−0.06	[−0.41; 0.27]	−0.05	[−0.32; 0.24]	+0.4	+0.02	[−0.09; 0.08]	+0.01	[−0.16; 0.14]	NS
Burden to others	+6.0	+0.24	[−0.05; 0.55]	+0.20	[−0.05; 0.44]	+3.9	+0.18	[0.04; −0.31]	+0.12	[0.04−0.21]	NS
Emotional health	+4.5	+0.38	[0.07; 0.68]	+0.17	[0.03; 0.32]	+0.3	+0.01	[−0.11; 0.14]	+0.01	[−0.09; 0.11]	NS
Body image	+4.7	+0.29	[−0.30; 0.27]	+0.15	[−0.12; 0.34]	+2.7	+0.13	[−0.10; 0.37]	+0.09	[−0.02; 0.26]	NS
Fatigue	+3.5	+0.26	[−0.07; 0.56]	+0.16	[−0.05; 0.36]	+2.5	+0.13	[0.01; 0.25]	+0.09	[0.01; 0.17]	NS

P value comparing mean variation in responders and non-responders using non-parametric test.

Discussion

The current study was proposed to assess the responsiveness of a PRO tool against composite disease activity measures, as none of the PRO tools have evaluated that as of yet. The LIT is a 10-item, unidimensional PRO tool that is used to encourage patient–physician communication about the impact of SLE or its treatment.¹ It has been found to be responsive to changes in disease activity and patient reported changes in health.^1,11–14

In the validation study,⁶ the LIT failed to show responsiveness against a three-point improvement in SLEDAI or a one-point improvement in the 0–3 PGA. The current study demonstrated the responsiveness of LIT against the SRI, a composite clinical anchor that has been used in recent SLE-related therapeutic trials. The SRI response may represent a larger decrease in SLE activity. This definition of remission was already shown to correlate with a significant improvement in PROs.⁴ Moreover, the associated SRM for LIT was close to 0.7, which is higher than previously reported in studies concerning other PRO tools in SLE.^15,16 Interestingly, none of the items of the LIT showed individually significant responsiveness (data not shown) except for the item related to depression, which improved to a significantly greater degree in responders. The responsiveness, however, was much smaller than that for the global score, indicating that the global concept reflected by the LIT was responsive to change against disease activity, whereas individual items taken separately were not. In this study, LIT failed to show responsiveness against worsening disease activity, as measured by SLEDAI⁶ and BILAG. It may be explained by the lack of power (32 worsening patients) or to the previously described lack of responsiveness of disease-specific PROs in patients with worsening activity.¹⁵ Only two of the eight domains of the 34-item tool, LupusQoL, namely ‘physical health’ and ‘pain’ showed a difference in QoL scores when comparing SRI responders and non-responders by contrast. Two of the LupusQoL domains also showed significant floor effects.

No study thus far has evaluated the responsiveness of a PRO to a composite responder index as the primary outcome measure. LIT is the first study to undertake this evaluation. Few studies have investigated the responsiveness of QoL questionnaires used in SLE. No clear distinction was made in terms of SRM between the SF-36 and disease-specific questionnaires.^{15,16,17,18,19}

The strengths of this study include the large amount of data collected from multiple sites and the inclusion of the LupusQoL along with the LIT. The brevity of the LIT is an advantage that may lead to greater uptake by patients and care providers in routine patient care. Limitations of the study include the relatively small number of SRI responders. In addition, the PGA used in SELENA–SLEDAI was categorical, and hence the need to use a modified SRI. Because the impact of treatment is one of the concerns measured by the LIT, changes in treatment may have influenced patients’ scores. Unfortunately, these data were not recorded in this study and this question has to be addressed in future studies.

Conclusion

The LIT is moderately responsive to the SRI in patients with SLE. The inclusion of this tool in clinical care and clinical trials may provide further insights into its responsiveness.

Key messages

The LIT is a 10-question validated lupus-specific PRO.

The LIT score is responsive to changes in the SRI.

LIT is usable in clinical practice and in clinical trials.

This is the first study in SLE on PRO measures evaluating the responsiveness to a composite disease activity measure.

Footnotes

Author contributions

Study conception and design: Meenakshi Jolly and Hervé Devilliers. Acquisition of data: Meenakshi Jolly and 19 other US and Canada study sites for GHO-09-1621. Analysis and interpretation of data: Meenakshi Jolly, Hervé Devilliers and Claire Bonithon-Kopp. Drafting of manuscript: Hervé Devilliers and Claire Bonithon Kopp. Critical revision: Meenakshi Jolly.

Acknowledgements

The author(s) wish to thank the patients and study staff who participated in this study, and the following investigators:

Dr Rohit Aggarwal, University of Pittsburgh Medical Center, Pittsburgh, PA

Dr Stanley Ballou, Division of Rheumatology MetroHealth Medical Center, Cleveland, OH

Dr Seth Berney, Medicine LSU Health Sciences Center, Shreveport, LA

Dr Ann Clarke, McGill University Health Centre, Montreal, QC

Dr Dilrukshie Cooray, Harbor UCLA Medical Center RHU, Torrance, CA

Dr Mary Cronin, Medical College of Wisconsin, Milwaukee, WI

Dr Mary Anne Dooley, UNC Chapel Hill, NC

Dr Michelene Hearth-Holmes, University of Nebraska, Omaha, IL

Dr Diane Kamen, Medical University of South Carolina, Charleston, SC

Dr Sam Lim, Division of Rheumatology Emory University, Atlanta, GA

Dr Augustine Manadan, University Rheumatologist, Chicago, IL

Dr Maureen McMahon, UCLA, Los Angeles, CA

Dr Joan Merrill, Oklahoma Medical Research Foundation, Oklahoma City, OK

Dr Tim Niewold, Gwen Knapp Center for Lupus & Immunology Research, Chicago, IL

Dr Ann Parke, University of Connecticut, Hartford, CT

Dr Rosalind Ramsey-Goldman, Lupus Research Group, Chicago, IL

Dr Elizabeth Ortiz, Health Research Association, Los Angeles, CA

Dr Suncica Volkov, Outpatient Care Center, Chicago, IL

Dr Daniel Wallace, UCLA, Los Angeles, CA

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Hervé Devilliers received honoraria from GSK (less than €1000 in the past year). Claire Bonithon Kopp: nothing to disclose. Meenakshi Jolly received a grant from Pfizer of US$200,000; UCB consultancy ($2000); GSK consultancy; intellectual property royalties from lupusPRO and LIT.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by funding from GlaxoSmithKline and Human Genome Sciences.

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