The BILAG-2004 index is associated with development of new damage in SLE.

OBJECTIVE: To determine whether BILAG-2004 index is associated with the development of damage in a cohort of SLE patients. Mortality and development of damage were examined. METHODS: This was a multicentre longitudinal study. Patients were recruited within 12 months of achieving fourth ACR classification criterion for SLE. Data were collected on disease activity, damage, SLE-specific drug exposure, cardiovascular risk factors, antiphospholipid syndrome status and death at every visit. This study ran from 1 January 2005 to 31 December 2017. Descriptive statistics were used to analyse mortality and development of new damage. Poisson regression was used to examine potential explanatory variables for development of new damage. RESULTS: A total of 273 SLE patients were recruited with total follow-up of 1767 patient-years (median 73.4 months). There were 6348 assessments with disease activity scores available for analysis. During follow-up, 13 deaths and 114 new damage items (in 83 patients) occurred. The incidence rate for development of damage was higher in the first 3 years before stabilizing at a lower rate. Overall rate for damage accrual was 61.1 per 1000 person-years (95% CI: 50.6, 73.8). Analysis showed that active disease scores according to BILAG-2004 index (systems scores of A or B, counts of systems with A and BILAG-2004 numerical score) were associated with development of new damage. Low disease activity (LDA) states [BILAG-2004 LDA and BILAG Systems Tally (BST) persistent LDA] were inversely associated with development of damage. CONCLUSIONS: BILAG-2004 index is associated with new damage. BILAG-2004 LDA and BST persistent LDA can be considered as treatment targets.

Comparison of Responsiveness of British Isles Lupus Assessment Group 2004 Index, Systemic Lupus Erythematosus Disease Activity Index 2000, and British Isles Lupus Assessment Group 2004 Systems Tally.

OBJECTIVE: To compare the responsiveness of the British Isles Lupus Assessment Group 2004 index (BILAG-2004) and the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) disease activity indices and to determine whether there was any added value in combining BILAG-2004, BILAG-2004 system tally (BST), or simplified BST (sBST) with SLEDAI-2K. METHODS: This was a multicenter longitudinal study of SLE patients. Data were collected on BILAG-2004, SLEDAI-2K, and therapy on consecutive assessments in routine practice. The external responsiveness of the indices was assessed by determining the relationship between change in disease activity and change in therapy between 2 consecutive visits. Comparison of indices and their derivatives was performed by assessing the main effects of the indices using logistic regression. Receiver operating characteristic curves analysis was used to describe the performance of these indices individually and in various combinations, and comparisons of area under the curve were performed. RESULTS: There were 1,414 observations from 347 patients. Both BILAG-2004 and SLEDAI-2K maintained an independent relationship with change in therapy when compared. There was some improvement in responsiveness when continuous SLEDAI-2K variables (change in score and score of previous visit) were combined with BILAG-2004 system scores. Dichotomization of BILAG-2004 or SLEDAI-2K resulted in poorer performance. BST and sBST had similar responsiveness as the combination of SLEDAI-2K variables and BILAG-2004 system scores. There was little benefit in combining SLEDAI-2K with BST or sBST. CONCLUSION: The BILAG-2004 index had comparable responsiveness to SLEDAI-2K. There was some benefit in combining both indices. Dichotomization of BILAG-2004 and SLEDAI-2K leads to suboptimal performance. BST and sBST performed well on their own; sBST is recommended for its simplicity and clinical meaningfulness.

Partially hidden multi-state modelling of a prolonged disease state defined by a composite outcome.

For rheumatic diseases, Minimal Disease Activity (MDA) is usually defined as a composite outcome which is a function of several individual outcomes describing symptoms or quality of life. There is ever increasing interest in MDA but relatively little has been done to characterise the pattern of MDA over time. Motivated by the aim of improving the modelling of MDA in psoriatic arthritis, the use of a two-state model to estimate characteristics of the MDA process is illustrated when there is particular interest in prolonged periods of MDA. Because not all outcomes necessary to define MDA are measured at all clinic visits, a partially hidden multi-state model with latent states is used. The defining outcomes are modelled as conditionally independent given these latent states, enabling information from all visits, even those with missing data on some variables, to be used. Data from the Toronto Psoriatic Arthritis Clinic are analysed to demonstrate improvements in accuracy and precision from the inclusion of data from visits with incomplete information on MDA. An additional benefit of this model is that it can be extended to incorporate explanatory variables, which allows process characteristics to be compared between groups. In the example, the effect of explanatory variables, modelled through the use of relative risks, is also summarised in a potentially more clinically meaningful manner by comparing times in states, and probabilities of visiting states, between patient groups.

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

Correlated multistate models for multiple processes: an application to renal disease progression in systemic lupus erythematosus.

Bidirectional changes over time in the estimated glomerular filtration rate and in urine protein content are of interest for the treatment and management of patients with lupus nephritis. Although these processes may be modelled by separate multistate models, the processes are likely to be correlated within patients. Motivated by the lupus nephritis application, we develop a new multistate modelling framework where subject-specific random effects are introduced to account for the correlations both between the processes and within patients over time. Models are fitted by using bespoke code in standard statistical software. A variety of forms for the random effects are introduced and evaluated by using the data from the Systemic Lupus International Collaborating Clinics.

Exploring the existence of a stayer population with mover-stayer counting process models: application to joint damage in psoriatic arthritis.

Many psoriatic arthritis patients do not progress to permanent joint damage in any of the 28 hand joints, even under prolonged follow-up. This has led several researchers to fit models that estimate the proportion of stayers (those who do not have the propensity to experience the event of interest) and to characterize the rate of developing damaged joints in the movers (those who have the propensity to experience the event of interest). However, when fitted to the same data, the paper demonstrates that the choice of model for the movers can lead to widely varying conclusions on a stayer population, thus implying that, if interest lies in a stayer population, a single analysis should not generally be adopted. The aim of the paper is to provide greater understanding regarding estimation of a stayer population by comparing the inferences, performance and features of multiple fitted models to real and simulated data sets. The models for the movers are based on Poisson processes with patient level random effects and/or dynamic covariates, which are used to induce within-patient correlation, and observation level random effects are used to account for time varying unobserved heterogeneity. The gamma, inverse Gaussian and compound Poisson distributions are considered for the random effects.

Multiple Imputation of Missing Composite Outcomes in Longitudinal Data.

In longitudinal randomised trials and observational studies within a medical context, a composite outcome-which is a function of several individual patient-specific outcomes-may be felt to best represent the outcome of interest. As in other contexts, missing data on patient outcome, due to patient drop-out or for other reasons, may pose a problem. Multiple imputation is a widely used method for handling missing data, but its use for composite outcomes has been seldom discussed. Whilst standard multiple imputation methodology can be used directly for the composite outcome, the distribution of a composite outcome may be of a complicated form and perhaps not amenable to statistical modelling. We compare direct multiple imputation of a composite outcome with separate imputation of the components of a composite outcome. We consider two imputation approaches. One approach involves modelling each component of a composite outcome using standard likelihood-based models. The other approach is to use linear increments methods. A linear increments approach can provide an appealing alternative as assumptions concerning both the missingness structure within the data and the imputation models are different from the standard likelihood-based approach. We compare both approaches using simulation studies and data from a randomised trial on early rheumatoid arthritis patients. Results suggest that both approaches are comparable and that for each, separate imputation offers some improvement on the direct imputation of a composite outcome.

Study design.

A brief survey is provided of common designs for medical studies and important issues in their implementation. The designs discussed include those for laboratory studies, clinical trials, cohort studies, case-control and related studies, and diagnostic studies.

Trivariate mover-stayer counting process models for investigating joint damage in psoriatic arthritis.

In psoriatic arthritis, many patients do not develop permanent joint damage even after a prolonged follow-up. This has led several authors to consider the possibility of a subpopulation of stayers (those who do not have the propensity to experience the event of interest), as opposed to assuming the entire population consist of movers (those who have the propensity to experience the event of interest). In addition, it is recognised that the damaged joints process may act very differently across different joint areas, particularly the hands, feet and large joints. From a clinical perspective, interest lies in identifying possible relationships between the damaged joints processes in these joint areas for the movers and estimating the proportion of stayers in these joint areas, if they exist. For this purpose, this paper proposes a novel trivariate mover-stayer model consisting of mover-stayer truncated negative binomial margins, and patient-level dynamic covariates and random effects in the models for the movers and stayers, respectively. The model is then extended to have a two-level mover-stayer structure for its margins so that the nature of the stayer property can be investigated. A particularly attractive feature of the proposed models is that only an optimisation routine is required in their model fitting procedures. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally.

On Modelling Minimal Disease Activity.

OBJECTIVE: To explore methods for statistical modelling of minimal disease activity (MDA) based on data from intermittent clinic visits. METHODS: The analysis was based on a 2-state model. Comparisons were made between analyses based on "complete case" data from visits at which MDA status was known, and the use of hidden model methodology that incorporated information from visits at which only some MDA defining criteria could be established. Analyses were based on an observational psoriatic arthritis cohort. RESULTS: With data from 856 patients and 7,024 clinic visits, analysis was based on virtually all visits, although only 62.6% provided enough information to determine MDA status. Estimated mean times for an episode of MDA varied from 4.18 years to 3.10 years, with smaller estimates derived from the hidden 2-state model analysis. Over a 10-year period, the estimated expected times spent in MDA episodes of longer than 1 year was 3.90 to 4.22, and the probability of having such an MDA episode was estimated to be 0.85 to 0.91, with longer times and greater probabilities seen with the hidden 2-state model analysis. CONCLUSION: A 2-state model provides a useful framework for the analysis of MDA. Use of data from visits at which MDA status can not be determined provide more precision, and notable differences are seen in estimated quantities related to MDA episodes based on complete case and hidden 2-state model analyses. The possibility of bias, as well as loss of precision, should be recognized when complete case analyses are used.

Validation of the Toronto Psoriatic Arthritis Screen Version 2 (ToPAS 2).

OBJECTIVE: We previously developed and performed an initial validation of a screening questionnaire, the Toronto Psoriatic Arthritis Screen (ToPAS), for psoriatic arthritis (PsA). In our original analysis, we found that the index constructed appeared to discriminate well between those with a confirmed diagnosis of PsA and those without PsA in various clinical settings. However, it was suggested that ToPAS would benefit from additional refinement to the questions and the scoring system, because items pertaining to axial involvement were not included in our original index. Subsequently, a second version of ToPAS was developed, ToPAS 2, which incorporated the suggested refinements. We aimed to validate ToPAS 2 as a screening instrument for PsA. METHODS: ToPAS 2 was administered to 3 "diagnostic" groups of individuals - patients with PsA, patients with psoriasis, and healthy controls, and the data collected were analyzed. RESULTS: It was found that the new version of ToPAS, ToPAS 2, again performed well, with the axial domain now featuring in the new scoring system. The constructed index, ToPAS2_cap, had an overall area under the receiver-operation curve of 0.910, with overall values of sensitivity and specificity, at a cutpoint of 8 (or 7), of 87.2% (92.0%) and 82.7% (77.2%), respectively. CONCLUSION: ToPAS 2 shows much promise as a screening instrument for identifying PsA both in people with psoriasis and in individuals from the general population. Its performance against other proposed screening instruments for PsA should be evaluated in other clinics and for other study designs.

A likelihood-based two-part marginal model for longitudinal semicontinuous data.

Two-part models are an attractive approach for analysing longitudinal semicontinuous data consisting of a mixture of true zeros and continuously distributed positive values. When the population-averaged (marginal) covariate effects are of interest, two-part models that provide straightforward interpretation of the marginal effects are desirable. Presently, the only available approaches for fitting two-part marginal models to longitudinal semicontinuous data are computationally difficult to implement. Therefore, there exists a need to develop two-part marginal models that can be easily implemented in practice. We propose a fully likelihood-based two-part marginal model that satisfies this need by using the bridge distribution for the random effect in the binary part of an underlying two-part mixed model; and its maximum likelihood estimation can be routinely implemented via standard statistical software such as the SAS NLMIXED procedure. We illustrate the usage of this new model by investigating the marginal effects of pre-specified genetic markers on physical functioning, as measured by the Health Assessment Questionnaire, in a cohort of psoriatic arthritis patients from the University of Toronto Psoriatic Arthritis Clinic. An added benefit of our proposed marginal model when compared to a two-part mixed model is the robustness in regression parameter estimation when departure from the true random effects structure occurs. This is demonstrated through simulation.

The versatility of multi-state models for the analysis of longitudinal data with unobservable features.

Multi-state models provide a convenient statistical framework for a wide variety of medical applications characterized by multiple events and longitudinal data. We illustrate this through four examples. The potential value of the incorporation of unobserved or partially observed states is highlighted. In addition, joint modelling of multiple processes is illustrated with application to potentially informative loss to follow-up, mis-measured or missclassified data and causal inference.

Mixture distributions in multi-state modelling: some considerations in a study of psoriatic arthritis.

In many studies, interest lies in determining whether members of the study population will undergo a particular event of interest. Such scenarios are often termed 'mover-stayer' scenarios, and interest lies in modelling two sub-populations of 'movers' (those who have a propensity to undergo the event of interest) and 'stayers' (those who do not). In general, mover-stayer scenarios within data sets are accounted for through the use of mixture distributions, and in this paper, we investigate the use of various random effects distributions for this purpose. Using data from the University of Toronto psoriatic arthritis clinic, we present a multi-state model to describe the progression of clinical damage in hand joints of patients with psoriatic arthritis. We consider the use of mover-stayer gamma, inverse Gaussian and compound Poisson distributions to account for both the correlation amongst joint locations and the possible mover-stayer situation with regard to clinical hand joint damage. We compare the fits obtained from these models and discuss the extent to which a mover-stayer scenario exists in these data. Furthermore, we fit a mover-stayer model that allows a dependence of the probability of a patient being a stayer on a patient-level explanatory variable.

Dirichlet negative multinomial regression for overdispersed correlated count data.

A generic random effects formulation for the Dirichlet negative multinomial distribution is developed together with a convenient regression parameterization. A simulation study indicates that, even when somewhat misspecified, regression models based on the Dirichlet negative multinomial distribution have smaller median absolute error than generalized estimating equations, with a particularly pronounced improvement when correlation between observations in a cluster is high. Estimation of explanatory variable effects and sources of variation is illustrated for a study of clinical trial recruitment.

The BILAG-2004 systems tally--a novel way of representing the BILAG-2004 index scores longitudinally.

OBJECTIVE: This was an exploratory analysis to develop a new way of representing BILAG-2004 system scores longitudinally that would be clinically meaningful and easier to analyse in comparison with multiple categorical variables. METHODS: Data from a multicentre longitudinal study of SLE patients (the BILAG-2004 index and therapy collected at every visit) were used. External responsiveness analysis of the index suggested the possibility of using counts of systems with specified transitions in scores as a basis to analyse the system scores. Exploratory analyses with multinomial logistic regression were used to examine the appropriateness of this new method of analysing BILAG-2004 system scores. Receiver operating characteristic (ROC) curve analysis was used to assess the performance of this approach. RESULTS: There were 1414 observations from 347 patients. A novel method was devised based on counts of systems with defined transitions in score (BILAG-2004 systems tally, BST). It has six components (systems with major deterioration, systems with minor deterioration, systems with persistent significant activity, systems with major improvement, systems with minor improvement and systems with persistent minimal or no activity). This was further simplified (simplified BST, sBST) into three components (systems with active/worsening disease, systems with improving disease and systems with persistent minimal or no activity). Both versions had expected associations with change in therapy. ROC curve analyses demonstrated that both versions had similar good performance characteristics (areas under the curve >0.80) in predicting increase in therapy. CONCLUSION: The BST and sBST provide alternative approaches to representing BILAG-2004 disease activity longitudinally. Further validation of their use is required.

The BILAG2004-Pregnancy index is reliable for assessment of disease activity in pregnant SLE patients.

OBJECTIVE: To assess the inter-rater reliability of the BILAG2004-Pregnancy index for assessment of SLE disease activity in pregnancy. METHODS: Pregnant SLE patients were recruited from four centres and assessed separately by two raters/physicians in routine clinical practice. Disease activity was determined using the BILAG2004-Pregnancy index. Reliability was assessed using level of agreement, κ-statistics and analysis of disagreement. Major disagreement was defined as a score difference of A and C/D/E or B and D/E between the two raters, and minor disagreement was a score difference of A and B or B and C between raters. RESULTS: A total of 30 patients (63.3% Caucasian, 13.3% Afro-Caribbean, 16.7% South Asian) were recruited. The majority of patients had low-level disease activity according to the local rater's assessment, and there was no grade A activity, with grade B activity present in the following systems: mucocutaneous (nine patients), musculoskeletal (two patients), cardiorespiratory (one patient) and renal (one patient). The distribution of disease activity was similar to the external rater's assessment. Good levels of agreement (>70%) were achieved in all systems. κ-statistics were not appropriate for use in the gastrointestinal, ophthalmic, constitutional and neuropsychiatric systems, as there was minimal variation between patients but good levels of agreement otherwise. There were three major disagreements (0.1 per patient, all differences between B and D/E) and five minor disagreements (0.17 per patient). CONCLUSION: The BILAG2004-Pregnancy index is reliable for assessment of disease activity in pregnant SLE patients.

Screening for cognitive impairment in systemic lupus erythematosus.

OBJECTIVE: We examined the association between responses on a screening questionnaire and objective performance on a computer-administered test of cognitive abilities in systemic lupus erythematosus (SLE). METHODS: The Cognitive Symptom Inventory (CSI) and Hospital Anxiety and Depression Scales (HADS) questionnaires were compared in patients with SLE or rheumatoid arthritis (RA). The Automated Neuropsychological Assessment Metrics (ANAM) was used to evaluate cognitive performance in patients with SLE. Efficiency of performance was measured by "throughput" (number of correct responses per minute) and "inverse efficiency" (response speed/proportion of correct responses). Linear regression was applied to log-transformed CSI scores to examine their associations with ANAM scores and other factors. RESULTS: Patients with SLE (n = 68) or RA (n = 33) were similar in age, sex, ethnicity, and education status (p > 0.05). Patients with SLE had higher total CSI scores (33.6 ± 10.5 vs 29.4 ± 6.8, respectively; p = 0.041) and attention/concentration subscale CSI scores (15.7 ± 5.3 vs 13.3 ± 3.4; p = 0.016) compared to patients with RA. In patients with SLE there was a positive association between CSI scores and neuropsychiatric (NP) events at the time of testing (p = 0.0006), HADS anxiety (p < 0.0001), and depression (p < 0.0001) scores. After adjustment for age, education, disease duration, and NP events at the time of testing, there was no significant association (p > 0.05) between ANAM and CSI scores in patients with SLE. The results were similar using either "throughput" or "inverse efficiency" or the number of impaired ANAM subscales after adjustment for simple reaction time. CONCLUSION: The CSI self-report questionnaire of cognitive symptoms does not reliably screen for efficiency of cognitive processing in patients with SLE. Rather, cognitive complaints reported in the CSI are influenced by the presence of anxiety and depression.

Longitudinal study of the bidirectional association between pain and depressive symptoms in patients with psoriatic arthritis.

OBJECTIVE: To test the bidirectional hypothesis that depressive symptoms influence changes in pain over time, and pain influences changes in depressive symptoms. METHODS: A total of 394 patients attending the University of Toronto Psoriatic Arthritis clinic were followed over a mean period of 7.5 years with annual assessments, including number of swollen joints (SJC), Health Assessment Questionnaire (HAQ), and the Medical Outcomes Survey Short Form 36 (SF-36). Linear mixed-effects models were used to examine the cross- and lagged associations between the changes in HAQ pain and in the SF-36 mental component summary (MCS) score, adjusting for SJC and other covariates. RESULTS: The strongest predictors of changes in pain, SJC, and depressive symptoms between visits were scores of the corresponding variables at the previous visit, with standardized regression coefficients exceeding 0.75 in absolute value. There was, however, evidence of a small, but consequential, bidirectional relationship (i.e., standardized regression coefficients <0.3) between depressive symptoms and pain. Both previous MCS scores and change in MCS scores were associated with change in pain between visits; conversely, previous pain scores and change in pain scores were associated with change in depressive symptoms between visits. CONCLUSION: Even though cross-variable associations between pain and depressive symptoms exist, changes in pain and depressive symptoms appear to be strongly driven by their measurements at the previous visit. To optimize patient outcomes, a clinical approach that assesses and treats clinically significant depressive symptoms, as well as pain, is required.