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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Mar 10, 2026
Open Peer Review Period: Mar 10, 2026 - May 10, 2026
Date Accepted: Jun 16, 2026
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Cost-Effectiveness Analysis of Age-Specific N-Terminal Pro-B-Type Natriuretic Peptide Thresholds for Heart Failure Diagnosis in China: Protocol for a Markov Model–Based Study

Liu C, Wang J, Ding S, Li Y

Cost-Effectiveness Analysis of Age-Specific N-Terminal Pro-B-Type Natriuretic Peptide Thresholds for Heart Failure Diagnosis in China: Protocol for a Markov Model–Based Study

JMIR Res Protoc 2026;15:e95071

DOI: 10.2196/95071

PMID: 42372254

PMCID: 13365891

Cost-Effectiveness Analysis of Age-Specific NT-proBNP Thresholds for Heart Failure Diagnosis in China: A Markov Model-Based Study Protocol

  • Changyuan Liu; 
  • Jing Wang; 
  • Shuangning Ding; 
  • Yongze Li

ABSTRACT

Background:

Heart failure (HF) represents a growing public health challenge in China, particularly for the aging population. Although N-terminal pro–B-type natriuretic peptide (NT-proBNP) is pivotal in HF diagnosis, current reference intervals used in China are largely based on manufacturer-derived cutoffs established in Western populations. Emerging evidence from Chinese studies suggests significant age-related variations in NT-proBNP levels, which may lead to diagnostic misclassification. This study aims to evaluate the cost-effectiveness of implementing age-specific NT-proBNP reference intervals compared with the conventional universal threshold for HF diagnosis in China.

Objective:

This study aims to evaluate the cost-effectiveness of implementing age-specific NT-proBNP reference intervals compared with the conventional universal threshold for HF diagnosis in China.

Methods:

A hybrid decision-analytic model, integrating a diagnostic decision tree with a 10-year Markov model, will be developed from the perspective of the Chinese healthcare system. The simulated cohort will comprise adults aged ≥45 years presenting with symptoms suggestive of HF, with demographic and biomarker profiles derived from the China Health and Retirement Longitudinal Study (CHARLS). Two diagnostic strategies will be compared: (1) age-specific thresholds (<100 ng/L for individuals <65 years; <248 ng/L for those ≥65 years) and (2) a universal cutoff of 125 ng/L. The decision tree will assess diagnostic accuracy, while the Markov model will simulate long-term HF progression, hospitalization, and mortality. Model inputs including transition probabilities, costs, and health utilities will be sourced from Chinese registries and published literature. The primary outcome is the incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses will be conducted to evaluate model uncertainty.

Results:

The model will estimate the primary outcome of the incremental cost-effectiveness ratio (ICER) of the age-specific strategy versus the universal cutoff. Secondary outputs will include total costs, quality-adjusted life years (QALYs), and the number of correct and missed diagnoses. Results from deterministic and probabilistic sensitivity analyses will be presented to characterize decision uncertainty.

Conclusions:

This study bridges laboratory medicine and health economics to examine the implications of adopting Chinese-specific, age-adjusted NT-proBNP thresholds. By linking diagnostic accuracy to long-term clinical and economic outcomes, the findings are expected to inform national guideline development, reduce diagnostic errors, and optimize resource allocation for HF management in China. Clinical Trial: Not applicable (this is a study protocol, not a clinical trial).


 Citation

Please cite as:

Liu C, Wang J, Ding S, Li Y

Cost-Effectiveness Analysis of Age-Specific N-Terminal Pro-B-Type Natriuretic Peptide Thresholds for Heart Failure Diagnosis in China: Protocol for a Markov Model–Based Study

JMIR Res Protoc 2026;15:e95071

DOI: 10.2196/95071

PMID: 42372254

PMCID: 13365891

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