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On Modelling Minimal Disease Activity
Author(s) -
Jackson Christopher H.,
Su Li,
Gladman Dafna D.,
Farewell Ver T.
Publication year - 2016
Publication title -
arthritis care and research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.032
H-Index - 163
eISSN - 2151-4658
pISSN - 2151-464X
DOI - 10.1002/acr.22687
Subject(s) - statistics , medicine , observational study , statistical analysis , cohort , demography , mathematics , sociology
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.