Evaluation of a fast‐and‐frugal clinical decision algorithm (‘pathways’) on clinical outcomes in hospitalised patients with COVID‐19 treated with anticoagulants

Djulbegoviĉ, Benjamin; Hozo, Iztok; Lizarraga, David; Thomas, Joseph; Barbee, Michael; Shah, Nupur; Rubeor, Tyler; Dale, Jordan; Reiser, Jochen; Guyatt, Gordon

doi:10.1111/jep.13780

Cited by 7 publications

(12 citation statements)

References 58 publications

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“…However, CPs are theory‐free constructs that require further modifications to allow the quantitative analysis of delivery healthcare interventions 27,31 . Indeed, we have previously demonstrated that this is possible by converting CPs into FFT—the latter have a strong theoretical basis to facilitate the calculation of the correct delivery of a given management strategy 28,31,32 . Note that we somewhat simplified the pathway/FFT for high prior PE.…”

Section: Methodsmentioning

confidence: 99%

“…27,31 Indeed, we have previously demonstrated that this is possible by converting CPs into FFT-the latter have a strong theoretical basis to facilitate the calculation of the correct delivery of a given management strategy. 28,31,32 Note that we somewhat simplified the pathway/FFT for high prior PE. That is, the ASH considers PE ruled in if CTPA is positive.…”

Section: Decision-theoretical Approachesmentioning

confidence: 99%

“…Based on the assessment of the efficacy of extended direct oral anticoagulants (DOAC) therapy in patients with VTE in patients who completed at least 3 months of initial anticoagulation therapy, then received either extended anticoagulation for 6−12 months with any DOAC or placebo beyond the initial anticoagulation therapy 32 …”

Section: Evidence and Assumptionsmentioning

confidence: 99%

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Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

Djulbegoviĉ

Hozo

Lizarraga

et al. 2023

Evaluation Clinical Practice

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Rationale, Aims and Objectives The development of clinical practice guidelines (CPG) suffers from the lack of an explicit and transparent framework for synthesising the key elements necessary to formulate practice recommendations. We matched deliberations of the American Society of Haematology (ASH) CPG panel for the management of pulmonary embolism (PE) with the corresponding decision‐theoretical constructs to assess agreement of the panel recommendations with explicit decision modelling. Methods Five constructs were identified of which three were used to reformulate the panel's recommendations: (1) standard, expected utility threshold (EUT) decision model; (2) acceptable regret threshold model (ARg) to determine the frequency of tolerable false negative (FN) or false positive (FP) recommendations, and (3) fast‐and‐frugal tree (FFT) decision trees to formulate the entire strategy for management of PE. We compared four management strategies: withhold testing versus d‐dimer → computerized pulmonary angiography (CTPA) (‘ASH‐Low’) versus CTPA→ d‐dimer (‘ASH‐High’) versus treat without testing. Results Different models generated different recommendations. For example, according to EUT, testing should be withheld for prior probability PE < 0.13%, a clinically untenable threshold which is up to 15 times (2/0.13) below the ASH guidelines threshold of ruling out PE (at post probability of PE ≤ 2%). Three models only agreed that the ‘ASH low’ strategy should be used for the range of pretest probabilities of PE between 0.13% and 13.27% and that the ‘ASH high’ management should be employed in a narrow range of the prior PE probabilities between 90.85% and 93.07%. For all other prior probabilities of PE, choosing one model did not ensure coherence with other models. Conclusions CPG panels rely on various decision‐theoretical strategies to develop its recommendations. Decomposing CPG panels' deliberation can provide insights if the panels' deliberation retains a necessary coherence in developing guidelines. CPG recommendations often do not agree with the EUT decision analysis, widely used in medical decision‐making modelling.

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Section: Methodsmentioning

confidence: 99%

Section: Decision-theoretical Approachesmentioning

confidence: 99%

Section: Evidence and Assumptionsmentioning

confidence: 99%

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Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

Djulbegoviĉ

Hozo

Lizarraga

et al. 2023

Evaluation Clinical Practice

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“…Translating pathways into FFT can enable such evaluation. 7,16,26 An FFT decision tree consists of a series of sequential predictors or "cues" that are most relevant to categorising each patient (or a group of patients) into binary outcomes. Every cue throughout the tree has a single exit ("yes" [y] or "no" [n]) except the last cue.…”

Section: A Conceptual Outlinementioning

confidence: 99%

“…The standard FFT deals with classifying outcomes but does not consider the consequences of decisions, which FFTT does. 7,16,26 FFTT stipulates that rational administration of treatment or diagnostic tests occurs when the expected treatment benefits outweigh its expected harms at a given probability of disease or clinical outcome. 7,16,26 The accuracy of FFT and FFTT is defined by their exit structure, which determines the ratio between false negatives and false positives (see Supporting Information: Appendix Figure S1 for details).…”

Section: A Conceptual Outlinementioning

confidence: 99%

Improving methods of clinical practice guidelines: From guidelines to pathways to fast‐and‐frugal trees and decision analysis to develop individualised patient care

Djulbegovic,

Hozo,

Cuker

et al. 2023

Evaluation Clinical Practice

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BackgroundCurrent methods for developing clinical practice guidelines have several limitations: they are characterised by the “black box” operation—a process with defined inputs and outputs but an incomplete understanding of its internal workings; they have “the integration problem”—a lack of framework for explicitly integrating factors such as patient preferences and trade‐offs between benefits and harms; they generate one recommendation at a time that typically are not connected in a coherent analytical framework; and they apply to “average” patients, while clinicians and their patients seek advice tailored to individual circumstances.MethodsWe propose augmenting the current guideline development method by converting evidence‐based pathways into fast‐and‐frugal decision trees (FFTs) and integrating them with generalised decision curve analysis to formulate clear, individualised management recommendations.ResultsWe illustrate the process by developing recommendations for the management of heparin‐induced thrombocytopenia (HIT). We converted evidence‐based pathways for HIT, developed by the American Society of Hematology, into an FFT. Here, we consider only thrombotic complications and major bleeding. We leveraged the predictive potential of FFTs to compare the effects of argatroban, bivalirudin, fondaparinux, and direct oral anticoagulants (DOACs) using generalised decision curve analysis. We found that DOACs were superior to other treatments if the FFT‐predicted probability of HIT exceeded 3%.ConclusionsThe proposed analytical framework connects guidelines, pathways, FFTs, and decision analysis, offering risk‐tailored personalised recommendations and addressing current guideline development critiques.

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Formulating Management Strategies Using Fast-and-Frugal Trees (A Decision Tool to Transform Clinical Practice Guidelines and Clinical Pathways into Decision Support at the Point of Care)

Djulbegovic,

Hozo

2023

Cancer Treatment and Research

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Evaluation of a fast‐and‐frugal clinical decision algorithm (‘pathways’) on clinical outcomes in hospitalised patients with COVID‐19 treated with anticoagulants

Cited by 7 publications

References 58 publications

Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

Improving methods of clinical practice guidelines: From guidelines to pathways to fast‐and‐frugal trees and decision analysis to develop individualised patient care

Formulating Management Strategies Using Fast-and-Frugal Trees (A Decision Tool to Transform Clinical Practice Guidelines and Clinical Pathways into Decision Support at the Point of Care)

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