A multistate model for events defined by prolonged observation

Neuropsychiatric events in systemic lupus erythematosus: a longitudinal analysis of outcomes in an international inception cohort using a multistate model approach

OBJECTIVES

Using a reversible multistate model, we prospectively examined neuropsychiatric (NP) events for attribution, outcome and association with health-related quality of life (HRQoL), in an international, inception cohort of systemic lupus erythematosus (SLE) patients.

METHODS

Annual assessments for 19 NP events attributed to SLE and non-SLE causes, physician determination of outcome and patient HRQoL (short-form (SF)-36 scores) were measured. Time-to-event analysis and multistate modelling examined the onset, recurrence and transition between NP states.

RESULTS

NP events occurred in 955/1827 (52.3%) patients and 592/1910 (31.0%) unique events were attributed to SLE. In the first 2 years of follow-up the relative risk (95% CI) for SLE NP events was 6.16 (4.96, 7.66) and non-SLE events was 4.66 (4.01, 5.43) compared with thereafter. Patients without SLE NP events at initial assessment had a 74% probability of being event free at 10 years. For non-SLE NP events the estimate was 48%. The majority of NP events resolved over 10 years but mortality was higher in patients with NP events attributed to SLE (16%) versus patients with no NPSLE events (6%) while the rate was comparable in patients with non-SLE NP events (7%) compared with patients with no non-SLE events (6%). Patients with NP events had lower SF-36 summary scores compared with those without NP events and resolved NP states (p<0.001).

CONCLUSIONS

NP events occur most frequently around the diagnosis of SLE. Although the majority of events resolve they are associated with reduced HRQoL and excess mortality. Multistate modelling is well suited for the assessment of NP events in SLE.

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.

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.

Randomised controlled trial of tumour necrosis factor inhibitors against combination intensive therapy with conventional disease-modifying antirheumatic drugs in established rheumatoid arthritis: the TACIT trial and associated systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is initially treated with methotrexate and other disease-modifying antirheumatic drugs (DMARDs). Active RA patients who fail such treatments can receive tumour necrosis factor inhibitors (TNFis), which are effective but expensive.

OBJECTIVE

We assessed whether or not combination DMARDs (cDMARDs) give equivalent clinical benefits at lower costs in RA patients eligible for TNFis.

DESIGN

An open-label, 12-month, pragmatic, randomised, multicentre, two-arm trial [Tumour necrosis factor inhibitors Against Combination Intensive Therapy (TACIT)] compared these treatment strategies. We then systematically reviewed all comparable published trials.

SETTING

The TACIT trial involved 24 English rheumatology clinics.

PARTICIPANTS

Active RA patients eligible for TNFis.

INTERVENTIONS

The TACIT trial compared cDMARDs with TNFis plus methotrexate or another DMARD; 6-month non-responders received (a) TNFis if in the cDMARD group; and (b) a second TNFi if in the TNFi group.

MAIN OUTCOME MEASURES

The Heath Assessment Questionnaire (HAQ) was the primary outcome measure. The European Quality of Life-5 Dimensions (EQ-5D), joint damage, Disease Activity Score for 28 Joints (DAS28), withdrawals and adverse effects were secondary outcome measures. Economic evaluation linked costs, HAQ changes and quality-adjusted life-years (QALYs).

RESULTS

In total, 432 patients were screened; 104 started on cDMARDs and 101 started on TNFis. The initial demographic and disease assessments were similar between the groups. In total, 16 patients were lost to follow-up (nine in the cDMARD group, seven in the TNFi group) and 42 discontinued their intervention but were followed up (23 in the cDMARD group and 19 in the TNFi group). Intention-to-treat analysis with multiple imputation methods used for missing data showed greater 12-month HAQ score reductions with initial cDMARDs than with initial TNFis [adjusted linear regression coefficient 0.15, 95% confidence interval (CI) -0.003 to 0.31; p = 0.046]. Increases in 12-month EQ-5D scores were greater with initial cDMARDs (adjusted linear regression coefficient -0.11, 95% CI -0.18 to -0.03; p = 0.009) whereas 6-month changes in HAQ and EQ-5D scores and 6- and 12-month changes in joint damage were similar between the initial cDMARD group and the initial TNFi group. Longitudinal analyses (adjusted general estimating equations) showed that the DAS28 was lower in the initial TNFi group in the first 6 months (coefficient -0.63, 95% CI -0.93 to -0.34; p < 0.001) but there were no differences between the groups in months 6-12. In total, 36 patients in the initial cDMARD group and 44 in the initial TNFi group achieved DAS28 remission. The onset of remission did not differ between groups (p = 0.085 on log-rank test). In total, 10 patients in the initial cDMARD group and 18 in the initial TNFi group experienced serious adverse events; stopping therapy because of toxicity occurred in 10 and six patients respectively. Economic evaluation showed that the cDMARD group had similar or better QALY outcomes than TNFi with significantly lower costs at 6 and 12 months. In the systematic reviews we identified 32 trials (including 20-1049 patients) on early RA and 19 trials (including 40-982 patients) on established RA that compared (1) cDMARDs with DMARD monotherapy; (2) TNFis/methotrexate with methotrexate monotherapy; and (3) cDMARDs with TNFis/methotrexate. They showed that cDMARDs and TNFis had similar efficacies and toxicities.

CONCLUSIONS

Active RA patients who have failed methotrexate and another DMARD achieve equivalent clinical benefits at a lower cost from starting cDMARDs or from starting TNFis (reserving TNFis for non-responders). Only a minority of patients achieve sustained remission with cDMARDs or TNFis; new strategies are needed to maximise the frequency of remission.

TRIAL REGISTRATION

Current Control Trials ISRCTN37438295.

FUNDING

This project was funded by the National Institute for Health Research Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 18, No. 66. See the NIHR Journals Library website for further project information.

Joint assessment of dependent discrete disease state processes

In multiple sclerosis, the primary clinical measure of disability level is an ordinal score, the expanded disability severity scale score. In relapsing-remitting multiple sclerosis, measures of relapse are additionally of interest. Multiple sclerosis patients are typically assessed with regard to both the expanded disability severity scale and relapse state at each follow-up visit. As both are discrete measures, the two can be viewed as jointly dependent Markov processes. One of the main goals of multiple sclerosis research is to accurately model, over time, both transitions between expanded disability severity scale states and change in relapse state. This objective requires a number of significant modeling decisions, including decisions about whether or not the combination of specific disease states is warranted and assessment of the dependence structure between the two disease processes. Historically, such decisions are often made in an ad hoc manner and are not formally justified. We propose novel use of Bayes factors and Bayesian variable selection in the assessment of jointly dependent Markovian processes in multiple sclerosis. Methods are assessed using both simulated data and data collected from the Partners Multiple Sclerosis Center in Boston, MA.

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.