MAICSMidwest Artificial Intelligence and Cognitive Science (conference)
MAICSMaster of Arts in Intercultural Studies (various universities)
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References in periodicals archive ?
Matching-adjusted indirect comparison (MAIC) is a statistical technique that simulates a direct comparison of two therapies (4, 5) by matching individual patient data (IPD) from one trial to published aggregate data from another trial (6, 7).
Health technology assessment agencies have acknowledged MAIC as a robust analysis method (9), and the UK's National Institute for Health and Care Excellence (NICE) has published methodological guidelines on its use (5, 8).
The MAIC methodology comprises four main steps and has been described in detail in previous studies (5, 11).
Rates of methotrexate use at baseline were higher for patients in the FUTURE 2, 3, and 5 trials than for those in the NCT00317499 trial, and PsA duration, number of patients with psoriasis >3% of their body surface area, swollen joint count, and CRP levels were all lower, suggesting comparatively less severe disease in these patients (Table 1); this highlights the requirement for MAIC to avoid such potential confounding factors.
All published outcomes included in this MAIC were from the intention-to-treat population.
A systematic literature review (conducted: September 2014; updated: September 2015) identified three relevant clinical trials for use in this MAIC: MEASURE 1 (18), MEASURE 2 (18), and ATLAS (19, 20).
Three MAIC analyses against ATLAS were developed: pooled MEASURE 1/2, MEASURE 1 individually, and MEASURE 2 individually.
This unanchored (non-placebo-adjusted) MAIC methodology is recommended by NICE in cases when anchored comparisons are not possible (14, 17, 22-24).
Individual MEASURE 1 and MEASURE 2 MAIC study analyses versus ATLAS
This MAIC demonstrated no significant differences in placebo-adjusted ASAS 20 and 40 responses up to 12 weeks between secukinumab-and adalimumab-treated patients with AS who were matched for treatment effect modifiers (age, sex, BASFI, CRP, and prior TNFi exposure).