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A Multidimensional Array Representation of State-Transition Model Dynamics.

ABSTRACT: Cost-effectiveness analyses often rely on cohort state-transition models (cSTMs). The cohort trace is the primary outcome of cSTMs, which captures the proportion of the cohort in each health state over time (state occupancy). However, the cohort trace is an aggregated measure that does not capture information about the specific transitions among health states (transition dynamics). In practice, these transition dynamics are crucial in many applications, such as incorporating transition rewards or computing various epidemiological outcomes that could be used for model calibration and validation (e.g., disease incidence and lifetime risk). In this article, we propose an alternative approach to compute and store cSTMs outcomes that capture both state occupancy and transition dynamics. This approach produces a multidimensional array from which both the state occupancy and the transition dynamics can be recovered. We highlight the advantages of the multidimensional array over the traditional cohort trace and provide potential applications of the proposed approach with an example coded in R to facilitate the implementation of our method.

SUBMITTER: Krijkamp EM

PROVIDER: S-EPMC7065927 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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A Multidimensional Array Representation of State-Transition Model Dynamics.

Krijkamp Eline M EM Alarid-Escudero Fernando F Enns Eva A EA Pechlivanoglou Petros P Hunink M G Myriam MGM Yang Alan A Jalal Hawre J HJ

Medical decision making : an international journal of the Society for Medical Decision Making 20200128 2

Cost-effectiveness analyses often rely on cohort state-transition models (cSTMs). The cohort trace is the primary outcome of cSTMs, which captures the proportion of the cohort in each health state over time (state occupancy). However, the cohort trace is an aggregated measure that does not capture information about the specific transitions among health states (transition dynamics). In practice, these transition dynamics are crucial in many applications, such as incorporating transition rewards o ...[more]

PMID: 31989862

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Project description:Linus Pauling proposed that the large rate accelerations for enzymes are caused by the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogues of the transition states for enzymatic reactions often act as tight-binding inhibitors provided early support for this simple and elegant proposal. We review experimental results that support the proposal that Pauling's model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high-energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies that aimed to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-coenzyme A:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of coenzyme A (CoA) are responsible for a rate increase of 3 × 10(12)-fold, which is close to the estimated total 5 × 10(13)-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide an ~12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5'-monophosphate decarboxylase, and ?-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6-8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared with that of the free enzyme. Evidence is presented that supports a model in which the binding energy of the phosphite dianion piece, or the phosphodianion group of the whole substrate, is utilized to drive an enzyme conformational change from an inactive open form E(O) to an active closed form E(C), by closure of a phosphodianion gripper loop. Members of the enolase and haloalkanoic acid dehalogenase superfamilies use variable capping domains to interact with nonreacting portions of the substrate and sequester the substrate from interaction with bulk solvent. Interactions of this capping domain with the phenyl group of mandelate have been shown to activate mandelate racemase for catalysis of deprotonation of ?-carbonyl carbon. We propose that an important function of these capping domains is to utilize the binding interactions with nonreacting portions of the substrate to activate the enzyme for catalysis.

Dataset Information

A Multidimensional Array Representation of State-Transition Model Dynamics.

Publications

A Multidimensional Array Representation of State-Transition Model Dynamics.

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