ELIZA cgi-bash version rev. 1.91
- Medical English LInking keywords finder for the PubMed Zipped Archive (ELIZA) -

return kwic search for treatment out of >500 occurrences
677804 occurrences (No.8 in the rank) during 5 years in the PubMed. [cache]
319) For high-risk patients, the treatment that minimizes the risk of relapse in 2 years is Natalizumab, whereas Dimethyl Fumarate might be a better option for low-risk patients.
--- ABSTRACT ---
PMID:34048066 DOI:10.1002/sim.9034
2021 Statistics in medicine
* A two-stage prediction model for heterogeneous effects of treatments.
- Treatment effects vary across different patients, and estimation of this variability is essential for clinical decision-making. We aimed to develop a model estimating the benefit of alternative treatment options for individual patients, extending a risk modeling approach in a network meta-analysis framework. We propose a two-stage prediction model for heterogeneous treatment effects by combining prognosis research and network meta-analysis methods where individual patient data are available. In the first stage, a prognostic model to predict the baseline risk of the outcome. In the second stage, we use the baseline risk score from the first stage as a single prognostic factor and effect modifier in a network meta-regression model. We apply the approach to a network meta-analysis of three randomized clinical trials comparing the relapses in Natalizumab, Glatiramer Acetate, and Dimethyl Fumarate, including 3590 patients diagnosed with relapsing-remitting multiple sclerosis. We find that the baseline risk score modifies the relative and absolute treatment effects. Several patient characteristics, such as age and disability status, impact the baseline risk of relapse, which in turn moderates the benefit expected for each of the treatments. For high-risk patients, the treatment that minimizes the risk of relapse in 2 years is Natalizumab, whereas Dimethyl Fumarate might be a better option for low-risk patients. Our approach can be easily extended to all outcomes of interest and has the potential to inform a personalized treatment approach.
--- ABSTRACT END ---
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[frequency of next (right) word to treatment]
(1)68 of (13)7 planning (25)3 outcome (37)2 efficacy
(2)50 *null* (14)6 to (26)3 protocols (38)2 goals
(3)29 and (15)4 approaches (27)3 that (39)2 group
(4)23 for (16)4 methods (28)2 a (40)2 groups
(5)22 with (17)4 option (29)2 as (41)2 may
(6)15 options (18)4 options, (30)2 at (42)2 ranks
(7)13 in (19)4 ranking (31)2 being (43)2 reduced
(8)9 effect (20)4 regimens (32)2 compared (44)2 resistance
(9)9 effects (21)4 strategies (33)2 decisions, (45)2 screening,
(10)8 is (22)3 adherence (34)2 development (46)2 through
(11)8 on (23)3 approach (35)2 did (47)2 were
(12)7 outcomes (24)3 or (36)2 dose

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--- WordNet output for treatment --- =>1.取り扱い, 扱い, 治療, 待遇, 処理, 処置, 2.台本, シナリオ Overview of noun treatment The noun treatment has 4 senses (first 4 from tagged texts) 1. (28) treatment, intervention -- (care provided to improve a situation (especially medical procedures or applications that are intended to relieve illness or injury)) 2. (25) treatment, handling -- (the management of someone or something; "the handling of prisoners"; "the treatment of water sewage"; "the right to equal treatment in the criminal justice system") 3. (4) treatment -- (a manner of dealing with something artistically; "his treatment of space borrows from Italian architecture") 4. (2) discussion, treatment, discourse -- (an extended communication (often interactive) dealing with some particular topic; "the book contains an excellent discussion of modal logic"; "his treatment of the race question is badly biased") --- WordNet end ---