What question did this study set out to answer?

To evaluate predictive models for stable warfarin maintenance dosing by combining clinical variables and candidate genetic polymorphisms.

March 1, 2007Clinical Medicine & ResearchOpen Access

Evaluation of Genetic Factors for Warfarin Dose Prediction

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Population

8,101 adults aged ≥50 years, alive on December 31, 2002, seen at Marshfield Clinic between January 1, 2000…

Comparison

Electronic case-finding algorithm utilizing… vs Manual data abstraction by trained research…

Design

Cross-sectional

Authors

MCMichael D. CaldwellGroundwater Center RBRichard L. BergMarshfield Clinic KZK. Q. ZhangChina-Japan Friendship Hospital

Discussion

Member takes

Implication

May enhance EHR-based diabetes phenotyping in research; leaves open prospective validation and clinical impact.

Key Points

To evaluate predictive models for stable warfarin maintenance dosing by combining clinical variables and candidate genetic polymorphisms.
Constructed a baseline dose-prediction model using clinical parameters: age, gender, body surface area, prosthetic heart valves, and diabetes status.
Sequentially incorporated polymorphisms in CYP2C9, VKORC1, gamma carboxylase, factor VII, and Apo E genes into the model to evaluate their contribution to dose variability.
CYP2C9 and VKORC1 variants contributed substantially to dosing variability, together accounting for 56% of individual variation in stable warfarin dose alongside clinical factors.
Polymorphisms in gamma carboxylase, factor VII, and Apo E genes provided negligible additional contribution to dose prediction.

Structured PICO

Population

8,101 adults aged ≥50 years, alive on December 31, 2002, seen at Marshfield Clinic between January 1, 2000 and December 31, 2002, and residing in ZIP code 54449 (Marshfield, Wisconsin).

Intervention

Electronic case-finding algorithm utilizing diabetic diagnostic codes (ICD-9), clinical laboratory data (glucose, HbA1c), and medication history via natural language processing.

Comparator

Manual data abstraction by trained research coordinators (for validation subsets).

Outcome

Identification of research subjects with diabetes mellitus and estimation of disease prevalence.

Limitations

Does not discriminate between major forms of the disease (e.g., type 1 versus type 2 diabetes)
Retrospective chart review does not allow discrimination of false negative cases within the sub-sample of subjects with no laboratory data

Cite This Study

Caldwell et al. (2007) studied this question.

synapsesocial.com/papers/6a70bcd231a3df824328fcc7 https://doi.org/10.3121/cmr.2007.724

Topics

Women and heart disease

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Evaluation of Genetic Factors for Warfarin Dose Prediction

Discussion

Member takes

Implication

Key Points

Structured PICO

Limitations

Cite This Study

Topics

Evaluation of Genetic Factors for Warfarin Dose Prediction

Discussion

Member takes

Implication

Key Points

Structured PICO

Limitations

Cite This Study

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Topics

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