Faculty Bibliography

Background Missing data due to drop-out and loss to followup is a common problem in SLE trials. The usual approachesfor handling this issue include analyzing only subjects withcomplete data (complete case analysis; CC), last observationcarried forward (LOCF), or imputing non-responses for missing outcomes (non-responder imputation; NRI). However, thevalidity of these methods depends on strong assumptionsabout the missing data mechanism. Multiple imputation (MI)is a flexible model-based technique that accounts for uncertainty in the imputation process by generating several possiblevalues for the missing data, resulting in multiple completedata sets. These are analyzed separately and results are combined. MI is being used more widely in different disease settings but has not been applied to analyze the primaryoutcome in a SLE trial. We explored the use of MI to addressmissing data in the composite outcome, SLE Responder Index(SRI)-5, using data from patients assigned to standard of care(SoC) in a 52 week trial.Methods Data on 279 SLE patients randomized to SoC for 52weeks who were receiving mycophenolate mofetil (MMF), azathioprine, or methotrexate at entry were obtained from theLupus Foundation of America-Collective Data Analysis Initiative database. Multiple imputation using chained equationswas applied to handle missing data in an analysis to evaluatedifferences in SRI-5 response rates at 52 weeks betweenpatients on MMF and the other immunosuppressants (nonMMF). Three different imputation models were consideredthat included various combinations of longitudinal measures ofdisease activity (both composite and individual measures) andpatient characteristics. Results were compared to estimatesusing the CC, LOCF, and NRI.Results Missing data rates were 32% in the MMF and 23%in the non-MMF groups. As expected, the NRI missing dataapproach yielded the lowest response rates; the smallest andleast significant estimates of between group differences wereobserved with LOCF (table 1). Group differences were magnified with all three MI models compared to results of othermethods. Imputing SRI-5 directly (MI-1) versus the individualcomponents (MI-2) yielded nearly identical results.Conclusions Given the limitations of conventional approachesfor handling missing data, the MI method should also be considered in SLE trials. However, results can vary depending onthe imputation model that is used, and the assumptionsrequired for validity of this and other missing data methodsmust be justified. Sensitivity analysis using different approachesis important to demonstrate robustness of results especiallywhen missing data rates are non-negligible

Background Although hydroxychloroquine (HCQ) is a mainstay of treatment for patients with Systemic Lupus Erythematosus (SLE), ocular toxicity can result from accumulatedexposure. The introduction of highly sensitive tools has engendered even more concern. As the longevity of patients withSLE improves, additional data will help physicians accuratelybalance the risk of ocular toxicity and the risk of diseaseflare, especially in older patients who have stable/quiescent disease. Accordingly, this study was initiated to examine thesafety of HCQ withdrawal in older SLE patients.Methods Data were obtained by retrospective chart review atthree lupus centers. Twenty-seven patients met the following inclusion criteria:-4 ACR criteria, disease duration-5 years, HCQuse of 200 400 mg per day-5 years, and discontinuation ofhydroxychloroquine at-age 55 years. The comparator groupcomprised 39 age, gender and racial/ethnic matched patients whoremained on HCQ. The primary outcome was a clinically meaningful flare within one year of HCQ withdrawal, defined asmoderate or severe, using a revised version of the SELENA-SLEDAI Flare composite that separates mild from moderate flares,evaluates each organ system separately, and incorporates increasesin corticosteroid dose and/or addition of immunosuppressiveagents. Mild flares were considered secondary outcomes.Results Demographics are provided in table 1. There was atrend toward longer disease duration in the HCQ withdrawalgroup but no difference in prevalence of prior lupus nephritisbetween the groups. The reasons for HCQ withdrawal weremaculopathy (n=13), presumed/biopsy proven cardiomyopathy(n=2), patient request (n=4), and miscellaneous other reasons(n=8). There was no difference in the primary or secondaryoutcomes between the groups (table 1). Two patients had amoderate flare after discontinuing HCQ, of whom one hadarthritis treated with methotrexate and one had thrombocytopenia (>30K) and proteinuria of 2 grams/d (baseline 700 mg).Three patients had severe flares while continuing HCQ, ofwhom two were hospitalized, one for seizures and one forpericarditis; the third had worsening nephritis (urinaryprotein >4 g/d, requiring treatment). Two patients had moderate flares while remaining on HCQ, one of whom had a rashand arthritis treated with tofacitinib and one a rash treatedwith prednisone.Conclusions In this retrospective study of older patients withSLE on long-term HCQ, withdrawal did not increase the riskof moderate or severe flares. These data provide reassuranceregarding the safety of withdrawing HCQ in stable older SLEpatients

Nonadherence to treatment is a major cause of lupus flares. Hydroxychloroquine (HCQ), a major medication in systemic lupus erythematosus, has a long half-life and can be quantified by HPLC. This international study evaluated nonadherence in 305 lupus patients with flares using drug levels (HCQ<200ng/ml or undetectable desethylchloroquine), and self-administered questionnaires (MASRI<80% or MMAS-8<6). Drug levels defined 18.4% of the patients as severely nonadherent. In multivariate analyses, younger age, non-use of steroids, higher BMI and unemployment were associated with nonadherence by drug level. Questionnaires classified 39.9% of patients as nonadherent. Correlations between adherence measured by questionnaires, drug level, and physician assessment were moderate. Both methods probably measured two different patterns of nonadherence: self-administered questionnaires mostly captured relatively infrequently missed tablets, while drug levels identified severe nonadherence (i.e., interruption or erratic tablet intake). The frequency with which physicians miss nonadherence, together with under-reporting by patients, suggests that therapeutic drug monitoring is useful in this setting.

OBJECTIVES: The presence of tubulointerstitial damage (TID) on renal biopsy is considered to be a late sequela of lupus nephritis (LN). The objective of this study was to determine if TID predicts progression to end stage renal disease (ESRD) in LN patients without advanced kidney disease. METHODS: All SLE patients with an index biopsy consistent with LN between January 2005 and July 2015, and eGFR >/= 30mL/min/1.73m2 were included. Moderate-to-severe TID was defined as the presence of moderate-to-severe tubular atrophy and/or interstitial fibrosis. Time to ESRD was defined as time from the index biopsy date to incident ESRD date; non-ESRD patients were censored at the time of death or the last visit before December 2015. Time-dependent analyses were conducted to evaluate whether moderate-to-severe TID was predictive of ESRD progression. RESULTS: Of the 131 LN patients with eGFR >/= 30mL/min/1.73m2, 17 (13%) patients progressed to ESRD. Moderate-to-severe TID was present in 13% of biopsies with eGFR >/= 60mL/min/1.73m2 and in 33% of biopsies with eGFR between 30 and 60mL/min/1.73m2. Moderate-to-severe TID was associated with a higher risk of ESRD progression: adjusted hazard ratio (HR) = 4.1, 95% CI: 1.4-12.1, p = 0.01 for eGFR >/= 30mL/min/1.73m2; HR = 6.2, 95% CI: 1.7-23.2, p = 0.008 for eGFR >/= 60mL/min/1.73m2. There was no association between tubulointerstitial inflammation (TII) and ESRD progression. CONCLUSIONS: Moderate-to-severe TID, but not TII, was a strong predictor of ESRD progression independent of eGFR or glomerular findings, therefore, providing an important window for potential early interventions.

Objective/UNASSIGNED:To evaluate response duration and identify predictors of transitioning into and out of the response state in patients with SLE receiving standard of care (SoC) in 52-week clinical trials. Methods/UNASSIGNED:A multistate model (MSM) allowing for bidirectional transitions between response and non-response states was fit to data on 759 patients with SLE with active disease randomised to SoC. The probability of being in response at 52 weeks, average duration of response (sojourn time) and mean total time in response for SLE Responder Index (SRI-4, SRI-5, SRI-6) and BILAG-based Composite Lupus Assessment (BICLA) were estimated. Predictors of attainment and loss of SRI-5 response were also assessed. Results/UNASSIGNED:The MSM estimated probability of being in response at 52 weeks ranged from 42% (SRI-6) to 61% (SRI-4). Mean duration of response ranged from 20.4 weeks (BICLA) to 31.5 weeks (SRI-4). Mean total time in response was 16.4-24.8 weeks. Baseline characteristics predictive of shorter SRI-5 response duration were African descent (p=0.005), longer history of disease (p=0.03), higher anti-dsDNA antibody titres (p=0.039), lower lymphocyte count (p=0.008) and lower haemoglobin (p=0.006). Younger age (p<0.001) and higher protein/creatinine ratio (p<0.001) were associated with higher likelihood of achieving SRI-5 but also shorter response duration. Conclusion/UNASSIGNED:Factors associated with disease severity were more predictive of shorter response duration than of 52-week response status. Analysing landmark response rates and response duration using MSM may be a more powerful way to distinguish effective investigational treatments from background SoC, although this remains to be evaluated in future trials.