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OBJECTIVE: To investigate whether there are differential effects of disease activity and damage on physical functioning as measured by the Health Assessment Questionnaire (HAQ) over the course of psoriatic arthritis (PsA). METHODS: Between June 1993 and March 2005, 382 patients attending the University of Toronto PsA clinic had completed >/=2 HAQs on an annual basis. At the time of each HAQ assessment, clinical and laboratory measures of disease activity and damage were recorded. Generalized linear mixed-effects models were used to investigate the longitudinal relationship between disease activity, damage, and the HAQ score. To avoid floor effects that would arise in a single mixed-effects model, we adopted a 2-part model. RESULTS: The number of actively inflamed joints (measure of disease activity) and the number of clinically deformed joints (measure of damage) were positively and significantly related to the HAQ score. Furthermore, interaction terms for illness duration with the number of actively inflamed joints were statistically significant, with or without inclusion of the erythrocyte sedimentation rate and morning stiffness in the model (P = 0.029 and P < 0.001, respectively). The positive effects of actively inflamed joints on the level of the HAQ score decreased over increasing duration of PsA. There was less evidence to suggest that the positive effect of joint damage on the HAQ score increased over time. CONCLUSION: Our results support the view that the influence of disease activity on HAQ scores declines with increased disease duration. We could not demonstrate strong evidence that the effect of clinical damage increases over the course of illness. [ABSTRACT FROM AUTHOR]

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., (© 2021 American College of Rheumatology.)

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.

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.

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.

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.

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution.

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., (©2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.)

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., (© The Author(s) 2013.)

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.

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., (© 2016 The Authors. Arthritis Care & Research published by Wiley Periodicals, Inc. on behalf of the American College of Rheumatology.)

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.

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&#95;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.

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 Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

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.

In July 1914 Dr John Brownlee was appointed head of the Statistical Department of the newly established Medical Research Committee. He had qualified in mathematics, natural philosophy and medicine at the University of Glasgow, and by 1914 had established a reputation as a public health officer, an expert in infectious diseases, and as a proponent of the Pearsonian school of the application of statistics and mathematics to medicine: an ideal background for his new position. In celebration of the centenary anniversary of the Medical Research Council and as a tribute to John Brownlee's involvement at the start, the International Journal of Epidemiology is reprinting in this issue one of his early papers on genetics. We comment on this paper, as well as Brownlee's background, achievements, research and his somewhat enigmatic though likeable character.

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.

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., (Copyright © 2012 John Wiley & Sons, Ltd.)

Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030-3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level., (Copyright © 2012 John Wiley & Sons, Ltd.)

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.

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.

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.

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., (Copyright © 2012 by the American College of Rheumatology.)

Motivated by investigations of factors related to various patient-reported outcome measures in psoriatic arthritis patients, after controlling for the effect of disease activity on these outcomes, we outline an approach for dealing with a rapidly fluctuating explanatory variable in a multistate model. On the basis of a representation of this variable as an ordinal classification, we suggest the use of an expanded multistate model. We examine the bias in estimating effects associated with other variables via simulation for different modelling choices. We present an analysis of a motivating data set on physical functional disability in psoriatic arthritis patients., (Copyright © 2011 John Wiley & Sons, Ltd.)

In psoriatic arthritis, permanent joint damage characterizes disease progression and represents a major debilitating aspect of the disease. Understanding the process of joint damage will assist in the treatment and disease management of patients. Multistate models provide a means to examine patterns of disease, such as symmetric joint damage. Additionally, the link between damage and the dynamic course of disease activity (represented by joint swelling and stress pain) at both the individual joint level and otherwise can be represented within a correlated multistate model framework. Correlation is reflected through the use of random effects for progressive models and robust variance estimation for non-progressive models. Such analyses, undertaken with data from a large psoriatic arthritis cohort, are discussed and the extent to which they permit causal reasoning is considered. For this, emphasis is given to the use of the Bradford Hill criteria for causation in observational studies and the concept of local (in)dependence to capture the dynamic nature of the relationships.

About 30% of patients with psoriasis have psoriatic arthritis (PsA), an inflammatory arthritis that can affect both axial and peripheral joints. Major histocompatibility complex class I chain-related A (MICA) alleles have previously been shown to be associated with PsA; however it is unclear whether there is a differential association of MICA alleles with skin and joint manifestations of PsA. Here, we describe a case-control study that aims to validate previously reported MICA allele associations with PsA and determine whether MICA alleles differentiate patients with PsA from those with psoriasis without PsA. Two hundred forty-nine unrelated Caucasian PsA patients, 243 psoriasis patients without arthritis, and 248 healthy controls were genotyped for 55 MICA alleles using PCR-SSP, and for human leucocyte antigen (HLA)-B and HLA-C alleles by PCR-SSO reverse line blot. Allele frequencies were calculated and logistic regressions were performed, adjusting for HLA-B and HLA-C alleles previously shown to be associated with psoriasis and/or PsA. Several MICA alleles were associated with psoriatic disease, PsA, and psoriasis compared with controls, and PsA compared with psoriasis in univariate analyses. Haplotype analysis showed evidence of strong linkage disequilibrium (LD) between PsA and psoriasis risk alleles of HLA-C, HLA-B, and MICA. After adjusting for significant HLA-B and HLA-C alleles in multivariate analyses, MICA*016 remained significantly associated with psoriasis [odds ratio (OR) = 5.5, P = 0.008]. MICA*00801 homozygosity was associated with susceptibility to PsA when compared with patients with psoriasis alone (OR = 2.26, P = 0.009). We conclude that most MICA allele associations with psoriasis and PsA are dependent on LD with HLA-B and HLA-C risk alleles. Independent of HLA, only MICA*016 influences the risk of developing psoriasis without arthritis, and homozygosity for MICA*00801 increases the risk of developing PsA in patients with psoriasis., (© 2011 John Wiley & Sons A/S.)

Objectives: To examine SLEDAI-2000 cut-off scores for definition of active SLE and to determine the sensitivity to change of SLEDAI-2000 for the assessment of SLE disease activity and minimal clinically meaningful changes in score., Methods: Data from two multi-centre studies were used in the analysis: in a cross-sectional and a longitudinal fashion. At every assessment, data were collected on SLEDAI-2000 and treatment. The cross-sectional analysis with receiver operating characteristic (ROC) curves was used to examine the appropriate SLEDAI-2000 score to define active disease and increase in therapy was the reference standard. In the longitudinal analysis, sensitivity to change of SLEDAI-2000 was assessed with multinomial logistic regression. ROC curves analysis was used to examine possible cut-points in score changes associated with change in therapy, and mean changes were estimated., Results: In the cross-sectional analysis, the most appropriate cut-off scores for active disease were 3 or 4. In the longitudinal analysis, the best model for predicting treatment increase was with the change in SLEDAI-2000 score and the score from the previous visit as continuous variables. The use of cut-points was less predictive of treatment change than the use of continuous score. The mean difference in the change in SLEDAI-2000 scores, adjusted for prior score, between patients with treatment increase and those without was 2.64 (95% CI 2.16, 3.14)., Conclusions: An appropriate SLEDAI-2000 score to define active disease is 3 or 4. SLEDAI-2000 index is sensitive to change. The use of SLEDAI-2000 as a continuous outcome is recommended for comparative purposes.

Objective: The authors have previously reported on the relationship between activity and subsequent damage at the patient level for patients with psoriatic arthritis (PsA). The aim of this study was to identify key predictors of damage to individual joints in the hands and feet of patients with PsA, in particular those that capture previous activity., Methods: Data from patients followed prospectively at the University of Toronto PsA clinic between 1978 and 2006 were available for analysis. Logistic regression was used to relate the probability of a joint developing damage, within a specified time interval after the most recent clinic visit, to potential predictor variables. The predictor variables considered encompassed the history of disease activity of the joint and elsewhere, previous damage and the timing of clinical assessments., Results: 511 patients with no hand damage at clinic entry and 552 patients with no foot damage at clinic entry were included in the analysis of the hand and foot joints, respectively. The analysis of the hand and foot joints demonstrated that the activity (tenderness and/or swelling) history of the specific joint is associated with subsequent damage. For the joints of the feet, activity observations elsewhere in the same foot, and in particular the same toe, were also shown to be associated with subsequent damage., Conclusions: Both joint tenderness and swelling are important predictors of joint damage in PsA.

Semi-competing risks data occur frequently in medical research when interest is in simultaneous modelling of two or more processes, one of which may censor the others. We consider the analysis of semi-competing risks data in the presence of interval-censoring and informative loss-to-followup. The work is motivated by a data set from the MRC UK Cognitive Function and Ageing Study, which we use to model two processes, cognitive impairment and death. Analysis is carried out using a multi-state model, which is an extension of that used by Siannis et al. (Statist. Med. 2007; 26:426–442) to model semi-competing risks data with exact transition times, to data which is interval-censored. Model parameters are estimated using maximum likelihood. The role of a sensitivity parameter k, which influences the nature of informative censoring, is explored., (Copyright © 2010 John Wiley & Sons, Ltd.)

Time-to-event and similar analyses can be problematic if the event of interest is operationally defined by some condition being true for a prolonged period of time. A particular example of this, remission in psoriatic arthritis, is considered in detail for illustration. A 3-state model is proposed for characterizing the transition rates into and out of remission. Remission is linked to an initial and subsequent state for the purpose of introducing the condition that remission must be of some duration to be clinically meaningful. The model is compared with alternative approaches that have been used in such situations. These involve 2-state models where the duration of remission is allowed for through different definitions for the time of entry into remission. Both definitions are linked to prolonged observation of a particular clinical state.

Methodology for the meta-analysis of individual patient data with survival end-points is proposed. Motivated by questions about the reliance on hazard ratios as summary measures of treatment effects, a parametric approach is considered and percentile ratios are introduced as an alternative to hazard ratios. The generalized log-gamma model, which includes many common time-to-event distributions as special cases, is discussed in detail. Likelihood inference for percentile ratios is outlined. The proposed methodology is used for a meta-analysis of glioma data that was one of the studies which motivated this work. A simulation study exploring the validity of the proposed methodology is available electronically., (Copyright © 2010 John Wiley & Sons, Ltd.)

Objective: To develop a recommended measure of response for use in psoriatic arthritis (PsA) clinical trials and observational cohort studies reflecting joint involvement., Methods: Previously, we used data from phase III randomized placebo-controlled trials of anti-tumor necrosis factor (TNF) agents to determine models, based primarily on statistical considerations but with some clinical input when necessary, that best distinguish drug-treated from placebo-treated patients. For the same data, we examine response criteria currently used for PsA and logistic regression models based on the individual components of these response criteria. Comparison with our previously developed models, based primarily on statistical consideration, is made., Results: A simplified score, the PsA Joint Activity Index (PsAJAI), based on components of the ACR30, performed better than the ACR20 and PsARC, and comparable to our previously developed models. The PsAJAI is a weighted sum of 30% improvement in core measures with weights of 2 given to the joint count measure, the C-reactive protein laboratory measure, and the physician global assessment of disease activity measure. Weights of 1 should be given to the remaining 30% improvement measures including pain, patient global assessment of disease activity, and the Health Assessment Questionnaire., Conclusion: We recommend the PsAJAI be used as an outcome measure for assessing joint disease response in PsA clinical trials.

Objective: To develop statistical models, based on the analysis of data from phase III randomized placebo-controlled trials of tumor necrosis factor-alpha (TNF-alpha) inhibitors over a 24-week period, that may inform the definition of response measures for clinical trials in psoriatic arthritis (PsA)., Methods: Data from phase III randomized controlled trials with anti-TNF agents were used. A training set using baseline and 24-week data from 2 trials was used to derive the models, which were then tested on a dataset using baseline and interim data from the third trial, and baseline and interim data from the first 2 trials. Logistic regression, tree analysis, and factor analysis were considered in the development of the models. Receiver-operating characteristic curves were constructed and area under the curve (AUC) calculated to assess performance of the models., Results: Two models were derived. One was based on differences between baseline and last-visit values, which identified the current 68 tender joint count (TJC68), baseline and change in C-reactive protein (CRP), and the measure with the highest difference among the patient and physician global assessment of disease activity (GDA), patient assessment of pain and the Health Assessment Questionnaire (HAQ). The second model was based on percentage change from baseline and included TJC68, CRP, physician GDA, patient global assessment of arthritis pain, and HAQ. Both models provided high AUC of at least 0.8 for both the training and testing sets., Conclusion: Models for discriminating joint disease response patterns in PsA were derived from data from randomized controlled trials. These models can now be used to inform further consideration of response measures for trials.

Objective: To describe the longitudinal course of fatigue in psoriatic arthritis (PsA)., Methods: Our study included 390 patients who attended the University of Toronto Psoriatic Arthritis Clinic between 1998 and 2006 and who completed 2 or more administrations of the modified Fatigue Severity Scale (mFSS) at yearly intervals. Clinical data were used that corresponded to visits in which mFSS was administered. We used linear mixed effects models to examine the relationships of disease-related and nondisease-related variables with mFSS scores across multiple clinic visits, and linear regression models to investigate the association between change in mFSS scores (DeltamFSS) and changes in covariates between visits., Results: Clinical measures of disease activity were related to fatigue over time; however, these relationships disappeared in the context of patient-reported physical disability and pain. Patient-reported measures of physical disability, pain, and psychological distress were most closely related to higher mFSS scores (greater fatigue) across clinic assessments. Fatigue was found to vary over time, at least when assessed at yearly intervals. In general, measures of clinical and functional status at the current visit were more predictive of DeltamFSS in between previous and current visits than change scores in these measures between visits. Comorbid fibromyalgia or hypertension were also associated with greater fatigue across multiple visits and with change in fatigue between visits., Conclusion: A combination of factors is associated with fatigue in PsA. The full effect of comorbidities on fatigue warrants further study to better understand the effective management of fatigue in PsA.

Objective: To determine the association between folate pathway gene polymorphisms and the effectiveness, toxicity, and drug survival of methotrexate (MTX) in psoriatic arthritis (PsA)., Methods: Data were obtained from a longitudinal cohort of PsA patients evaluated according to a standard protocol. Data on duration of drug therapy, dose, side effects, and reasons for discontinuation are systematically recorded. Patients treated with MTX after clinic admission who had > or = 3 swollen joints prior to initiating MTX therapy were selected for evaluation of effectiveness. Response to MTX treatment was assessed at 6 months. Data from all patients treated in the clinic with MTX were used in evaluation of toxicity and drug survival. The following single-nucleotide polymorphisms (SNP) were measured using the Sequenom platform: MTHFR 677C>T (rs1801133), MTHFR 1298A>C (rs1801131), DHFR -473T>C (rs1650697), DHFR 35289A>G (rs1232027), and RFC 80G>A (rs1051266). Fisher's exact test, logistic regression, and Cox proportional hazard analyses were used to determine association., Results: Two hundred eighty-one patients were identified from the database. All patients were included in the analysis for side effects and drug survival, and 119 patients were included in the effectiveness analysis. The minor A allele of DHFR gene at +35289 was the only SNP demonstrating association with response to MTX therapy (OR 2.99, p = 0.02). Patients homozygous for the minor allele of MTHFR 677C/T (677TT) had more liver toxicity (Fisher exact test, p = 0.04)., Conclusion: Polymorphisms of the DHFR gene may be associated with MTX efficacy. MTHFR 677TT may have a relationship with MTX-induced liver toxicity in PsA.

In many chronic diseases it is important to understand the rate at which patients progress from infection through a series of defined disease states to a clinical outcome, e.g. cirrhosis in hepatitis C virus (HCV)-infected individuals or AIDS in HIV-infected individuals. Typically data are obtained from longitudinal studies, which often are observational in nature, and where disease state is observed only at selected examinations throughout follow-up. Transition times between disease states are therefore interval censored. Multi-state Markov models are commonly used to analyze such data, but rely on the assumption that the examination times are non-informative, and hence the examination process is ignorable in a likelihood-based analysis. In this paper we develop a Markov model that relaxes this assumption through the premise that the examination process is ignorable only after conditioning on a more regularly observed auxiliary variable. This situation arises in a study of HCV disease progression, where liver biopsies (the examinations) are sparse, irregular, and potentially informative with respect to the transition times. We use additional information on liver function tests (LFTs), commonly collected throughout follow-up, to inform current disease state and to assume an ignorable examination process. The model developed has a similar structure to a hidden Markov model and accommodates both the series of LFT measurements and the partially latent series of disease states. We show through simulation how this model compares with the commonly used ignorable Markov model, and a Markov model that assumes the examination process is non-ignorable., (Copyright 2010 John Wiley & Sons, Ltd.)

With specific reference to studies of growth hormone therapies, this chapter re-examines some basic principles in clinical research and considers some of the more complex aspects of trial design. The statistical structure which underpins trial design is characterized with specific attention given to samples size, subgroup analyses, multicentre trials and the role and implementation of randomization. Topics related to outcomes in studies of growth hormone therapy are discussed, including the possible value of surrogate responses, longitudinal outcomes and their analysis, and multiple outcomes. Additional design issues addressed are multiarmed trials, factorial designs and study monitoring. Brief comments are offered on the interpretation of negative trials and on non-inferiority trials., (Copyright 2010 S. Karger AG, Basel.)

Objective: To evaluate changes in symptoms, spinal mobility, and radiographic features in patients with axial psoriatic arthritis (AxPsA)., Methods: Patients with AxPsA were identified from the University of Toronto Psoriatic Arthritis clinic database. Axial symptoms, metrology, and radiographic features at study entry were compared to 5-year and 10-year followup assessments. Data were analyzed using continuity adjusted McNemar's test, an exact binomial test, or logistic regression., Results: Of 297 patients (mean age 42.5 yrs, PsA duration 8 yrs) in the study, 56% had axial symptoms, 43% had radiographic evidence of sacroiliitis, and 13% had syndesmophytes at entry. The number of patients with neck/back pain, neck/back stiffness, and clinical sacroiliitis declined significantly at both 5- and 10-year followup periods. There was a significant increase in the number of patients with restricted cervical spinal mobility at both 5- and 10-year visits and significant reduction in lateral flexion at both timepoints. At 5 (10) years, of those without sacroiliitis at baseline, 36.6% (51.7%) developed at least grade 2 sacroiliitis; 46.5% (52.0%) of those who presented with grade 2 progressed to a higher grade; and 15.6% (25.0%) with grade 3 progressed to grade 4 sacroiliitis. Of the patients without cervical/thoracic/lumbar syndesmophytes at study entry, 11%/16%/14% (14%/21%/20%) developed syndesmophytes in these regions at 5 (10) year followup. Similar results were obtained when analyses were restricted to patients satisfying radiographic criteria alone., Conclusion: Over a 10-year period, patients with AxPsA had improvement in neck and back pain, but lateral spinal flexion and cervical mobility deteriorated.

Objective: To determine the relationship between fatigue and disease-related and psychosocial variables in psoriatic arthritis (PsA)., Method: 499 patients attending the University of Toronto PsA Clinic were administered the modified fatigue severity scale (mFSS). At the time of mFSS administration, clinical and laboratory measures of disease activity and damage were recorded. Linear regression models were used to examine the cross-sectional relationship between disease-related and psychosocial variables and mFSS scores., Results: At least moderate fatigue occurred in 49.5% of patients and severe fatigue in 28.7%. Univariately the vast majority of variables were significantly associated with mFSS scores. The final multivariate model was composed of female sex, the medical outcome survey short form 36 (SF-36) pain and mental health scales, the number of fibromyalgia tender points, the health assessment questionnaire (HAQ) and "ever used" methotrexate, and explained 54.5% of the variation in mFSS scores. The SF-36 mental health scale played the largest role in the multivariate model, uniquely accounting for 6.6% of the variation in the fatigue severity scale. The disease-related factors significant at the univariate level did not achieve statistical significance in the context of HAQ and pain measures., Conclusion: Fatigue is a common symptom in PsA, and is associated, in a multivariate model, with pain, female sex, physical functional disability, medication status and psychological distress. Fatigue appears to provide some information that does not overlap with the core set of outcome domains in PsA.

Joint damage in psoriatic arthritis can be measured by clinical and radiological methods, the former being done more frequently during longitudinal follow-up of patients. Motivated by the need to compare findings based on the different methods with different observation patterns, we consider longitudinal data where the outcome variable is a cumulative total of counts that can be unobserved when other, informative, explanatory variables are recorded. We demonstrate how to calculate the likelihood for such data when it is assumed that the increment in the cumulative total follows a discrete distribution with a location parameter that depends on a linear function of explanatory variables. An approach to the incorporation of informative observation is suggested. We present analyses based on an observational database from a psoriatic arthritis clinic. Although the use of the new statistical methodology has relatively little effect in this example, simulation studies indicate that the method can provide substantial improvements in bias and coverage in some situations where there is an important time varying explanatory variable.

Background: Increasing evidence for cardiovascular mortality among patients with psoriasis and psoriatic arthritis (PsA) has accumulated, together with evidence for increased prevalence of risk factors for cardiovascular disease (CVD)., Objectives: To describe cardiovascular morbidity in PsA, determine its prevalence and identify risk factors for its development., Methods: At the University of Toronto, patients were followed up prospectively according to a standard protocol, including disease-related features and comorbidities. Patients with CVD, including myocardial infarction (MI), angina, hypertension and cerebrovascular accident (CVA), were identified. The prevalence of CVD morbidities in these patients was compared with data from the Canadian Community Health Survey through standardised prevalence ratios (SPRs). Cox relative risk regression analysis was used to analyse risk factors., Results: At the time of analysis, 648 patients were registered in the database. After clinic entry, 122 developed hypertension, 38 had an MI and 5, 21 and 11 had CVA, angina and congestive heart failure (CHF), respectively. 155 patients had at least one of these conditions. The SPRs for MI (2.57; 95% CI 1.73 to 3.80), angina (1.97; 95% CI 1.24 to 3.12) and hypertension (1.90; 95% CI 1.59 to 2.27) were statistically significant, whereas the SPRs for CHF (1.19; 95% CI 0.50 to 2.86) and CVA (0.91; 95% CI 0.34 to 2.43) were not. Factors associated with CVD included diabetes, hyperlipidaemia and high Psoriasis Area and Severity Index scores., Conclusion: Patients with PsA are at increased risk of cardiovascular morbidities compared with the general population. In addition to known risk factors for CVD, severe psoriasis is an important predictor in patients with PsA.