When pain is also taken into account as a clinical decision index, Boolean remission is considered to be a rational index configuration. The pain is an important decision index for the RA patient, and it cannot be judged that the RA treatment is good for the patient, if it is not improved. On the other hand, PGA correlates well with patient pain, and PGA minimization works well for pain relief 13. ![]() However, it cannot be denied that PGA alone deviates from the three other indicators that are often encountered in clinical practice and confuses the assessment of the efficacy of RA therapy 7, 12. SJC, TJC, and CRP reflect inflammatory status, and their trends are often associated 11. Of the four components of the Boolean remission criteria, only PGA is a patient-related outcome, and the assessment is patient subjective. Recent reports have argued that even with PGA ≤ 2, a patient's ADL after 1 year of acquired remission changes only slightly compared with PGA ≤ 1, and PGA ≤ 2 may serve as a remission criterion 10. It is difficult to achieve a PGA score of ≤ 1, and it has been argued that even mildly lax criteria can be regarded as a clinical remission, which may lead to assurance of maintenance of activities of daily living (ADL) 8, 9. The reason for the difficulty in achieving a Boolean remission is the PGA score 7. ACR/EULAR Boolean remission is the most stringent measure of disease activity 3, and it is known that patients who achieve Boolean remission, which is defined as to attain one or less in all of tenderness joint count (TJC), swollen joint count (SJC), patient's comprehensive evaluation (PGA), and C-reactive protein (CRP) 4, 5, can maintain stable disease activity control and activities of daily living for a long period after achieving remission 6. One of the main points is to aim for early clinical remission and to set the basic disease activity index and to monitor patients 2. Treat-to-target (T2T) strategies are now the global mainstay of treatment for rheumatoid arthritis (RA) 1. We concluded that setting PGA ≤ 2 as a remission criteria may not have statistical difference in disease activity from PGA ≤ 1, however, there was an determinant risk to misread that includes patient who losses clinical remission after acquisition. The mean SDAI score at month 6 in the Boolean-2 was not SDAI remission at all. Mean SDAI score at acquisition, 6 months after, and 1 year after of patients who attained Boolean-2 first and then Boolean-1, was significantly inferior to that of patients who attained the remissions at the same time. The trend was evident in the patients who attained Boolean-1 remission. Mean SDAI score of patients with Boolean-1 was significantly lower than that of patients with Boolean-2 at acquisition. Simplified disease activity index (SDAI) score was compared according to the criteria variations. Patients were recruited from an area cohort, of whom attained Boolean remission (Boolean-1) or near remission with PGA ≤ 2 and the rest components were ≤ 1 (Boolean-2). It is part of the SAGE University Press series "Quantitative Applications in the Social Sciences" ISBN 0-8039-4177-3.Validity and risk of setting patient’s global assessment (PGA) ≤ 2 as a Boolean remission criteria substituting PGA ≤ 1 in treating rheumatoid arthritis (RA) was investigated. I also like "Multiple Comparison Procedures" by Larry E. If you just want to compare multiple comparison procedures I would suggest reading about them in the SAS documentation (you don't need to buy the program to read the documentation). A copy can be purchased through for about $70 US dollars. If you are mathematically inclined and have taken at least one class in statistics I might suggest: "Analysis of generalized linear mixed models in the agricultural and natural resources sciences" by Gbur et al.2012. The choice here is to spend several weeks/months with various textbooks that we could (collectively) suggest, or to talk to a statistician. ![]() There are also options like REML methods to avoid issues on non-normally distributed data. There are a large number of multiple comparison procedures. It would be well worth the effort to talk to a statistician at your university. There may also be critical features in your data and methods that we cannot see. There are many other options, especially if my guess is wrong.
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