Key result
Genotype-phenotype model stratifies women with LQTS into tiers reaching ~51% cardiac event risk per decade.
Why the study?
Personalized risk estimates for cardiac events and life-threatening events were needed for women with type 1 or type 2 long QT syndrome.
Does a personalized genotype-phenotype risk prediction model accurately estimate the risk of cardiac and life-threatening events in women with type 1 or type 2 long QT syndrome?
Cohort (n=1,234)
Yes
Does a personalized genotype-phenotype risk prediction model accurately estimate the risk of cardiac and life-threatening events in women with type 1 or type 2 long QT syndrome?
A personalized genotype-phenotype risk prediction model can provide absolute risk estimates for cardiac and life-threatening events to guide female-specific management in long QT syndrome.
Answers are grounded in this paper and cite their sources.
May support risk stratification in women with LQTS; hypothesis-generating and requires prospective validation.
Background We aimed to provide personalized risk estimates for cardiac events (CEs) and life-threatening events in women with either type 1 or type 2 long QT. Methods and Results The prognostic model was derived from the Rochester Long QT Syndrome Registry, comprising 767 women with type 1 long QT (n=404) and type 2 long QT (n=363) from age 15 through 60 years. The risk prediction model included the following variables: genotype/mutation location, QTc-specific thresholds, history of syncope, and β-blocker therapy. A model was developed with the end point of CEs (syncope, aborted cardiac arrest, or long QT syndrome-related sudden cardiac death), and was applied with the end point of life-threatening events (aborted cardiac arrest, sudden cardiac death, or appropriate defibrillator shocks). External validation was performed with data from the Mayo Clinic Genetic Heart Rhythm Clinic (N=467; type 1 long QT [n=286] and type 2 long QT [n=181]). The cumulative follow-up duration among the 767 enrolled women was 22 243 patient-years, during which 323 patients (42%) experienced ≥1 CE. Based on genotype-phenotype data, we identified 3 risk groups with 10-year projected rates of CEs ranging from 15%, 29%, to 51%. The corresponding 10-year projected rates of life-threatening events were 2%, 5%, and 14%. C statistics for the prediction model for the 2 respective end points were 0.68 (95% CI 0.65-0.71) and 0.71 (95% CI 0.66-0.76). Corresponding C statistics for the model in the external validation Mayo Clinic cohort were 0.65 (95% CI 0.60-0.70) and 0.77 (95% CI 0.70-0.84). Conclusions This is the first risk prediction model that provides absolute risk estimates for CEs and life-threatening events in women with type 1 or type 2 long QT based on personalized genotype-phenotype data. The projected risk estimates can be used to guide female-specific management in long QT syndrome.
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Goldenberg et al. (2021) conducted a cohort in Congenital Long QT Syndrome (n=1,234). Personalized risk prediction model was evaluated on Cardiac events (syncope, aborted cardiac arrest, or long QT syndrome-related sudden cardiac death) (C statistic 0.68, 95% CI 0.65-0.71).
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