When data are collected longitudinally, measurement times often vary among patients. This is of particular concern in clinic-based studies, for example retrospective chart reviews. Here, typically no two patients will share the same set of measurement times and moreover, it is likely that the timing of the measurements is associated with disease course; for example, patients may visit more often when unwell. While there are statistical methods that can help overcome the resulting bias, these make assumptions about the nature of the dependence between visit times and outcome processes, and the assumptions differ across methods. The purpose of this paper is to review the methods available with a particular focus on how the assumptions made line up with visit processes encountered in practice. Through this we show that no one method can handle all plausible visit scenarios and suggest that careful analysis of the visit process should inform the choice of analytic method for the outcomes. Moreover, there are some commonly encountered visit scenarios that are not handled well by any method, and we make recommendations with regard to study design that would minimize the chances of these problematic visit scenarios arising.

Background: Observational longitudinal data often feature irregular, informative visit times. We propose descriptive measures to quantify the extent of irregularity to select an appropriate analytic outcome approach. Methods: We divided the study period into bins and calculated the mean proportions of individuals with 0, 1, and > 1 visits per bin. Perfect repeated measures features everyone with 1 visit per bin. Missingness leads to individuals with 0 visits per bin while irregularity leads to individuals with > 1 visit per bin. We applied these methods to: 1) the TARGet Kids! study, which invites participation at ages 2, 4, 6, 9, 12, 15, 18, 24 months, and 2) the childhood-onset Systemic Lupus Erythematosus (cSLE) study which recommended at least 1 visit every 6 months. Results: The mean proportions of 0 and > 1 visits per bin were above 0.67 and below 0.03 respectively in the TARGet Kids! study, suggesting repeated measures with missingness. For the cSLE study, bin widths of 6 months yielded mean proportions of 1 and > 1 visits per bin of 0.39, suggesting irregular visits. Conclusions: Our methods describe the extent of irregularity and help distinguish between protocol-driven visits and irregular visits. This is an important step in choosing an analytic strategy for the outcome.

Objective The goal was to characterize short‐term kidney status and describe variation in early care utilization in a multicenter cohort of patients with childhood‐onset systemic lupus erythematosus (cSLE) and nephritis. Methods We analyzed previously collected prospective data from North American patients with cSLE with kidney biopsy‐proven nephritis enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry from March 2017 through December 2019. We determined the proportion of patients with abnormal kidney status at the most recent registry visit and applied generalized linear mixed models to identify associated factors. We also calculated frequency of medication use, both during induction and ever recorded. Results We identified 222 patients with kidney biopsy–proven nephritis, with 64% class III/IV nephritis on initial biopsy. At the most recent registry visit at median (interquartile range) of 17 (8–29) months from initial kidney biopsy, 58 of 106 patients (55%) with available data had abnormal kidney status. This finding was associated with male sex (odds ratio [OR] 3.88, 95% confidence interval [95% CI] 1.21–12.46) and age at cSLE diagnosis (OR 1.23, 95% CI 1.01–1.49). Patients with class IV nephritis were more likely than class III to receive cyclophosphamide and rituximab during induction. There was substantial variation in mycophenolate, cyclophosphamide, and rituximab ever use patterns across rheumatology centers. Conclusion In this cohort with predominately class III/IV nephritis, male sex and older age at cSLE diagnosis were associated with abnormal short‐term kidney status. We also observed substantial variation in contemporary medication use for pediatric lupus nephritis between pediatric rheumatology centers. Additional studies are needed to better understand the impact of this variation on long‐term kidney outcomes.

Background Follow-up frequency is an important design parameter in longitudinal studies. We quantified the impact of reducing follow-up frequency on the precision of estimated regression parameters, and investigated the impact of incorrectly assuming an exchangeable correlation structure on estimates of the loss of precision resulting from reduced follow-up. Methods We estimated the loss in precision on deleting every second observation from three longitudinal cohorts: patients with Childhood Systemic Lupus Erythematosus (cSLE), the Canadian Haemophilia Prophylaxis Study (CHPS), and patients with Juvenile Dermatomyositis (JDM). We compared these results with those from a theoretical formula assuming an exchangeable correlation structure. Results The increase in sample size needed to compensate for halving follow-up frequency was 9%, 6% and 28% for the cSLE, CHPS and JDM cohorts respectively. Under the assumption of an exchangeable correlation, the estimated increases in sample size were 22%, 11% and 10% respectively. Conclusions Reducing follow-up frequency can result in minimal loss of information, as seen in the CHPS cohort. While using a theoretical formula based on an exchangeable correlation structure is convenient, it can be inaccurate when the true correlation structure is not exchangeable.