Elevated plasma B-type natriuretic peptide (BNP) levels have been reported to be related to a high risk for cardiovascular (CV) disease in the general population. However, there has been no accurate determination of the threshold levels of plasma BNP that indicate an increased potential for the development of general CV events (i.e., heart failure, stroke, and myocardial infarction) and the validity of these levels for predicting CV events compared to classic risk markers. To establish gender-specific thresholds of plasma BNP levels associated with increased risk for CV disease in the general population, baseline BNP levels were determined in community-dwelling adults (n = 13,209, mean age 62 ± 10 years,) and CV events in the cohort were captured prospectively. The cohort was divided by deciles of plasma BNP level in each gender. A Cox proportional-hazards model was used to determine the relative hazard ratios among the deciles. In addition, to compare the utility of plasma BNP to the Framingham 10-year risk score for predicting general CV events, receiver-operating characteristic analysis was performed. During follow-up, CV events were identified in 429 patients in the cohort. Compared to the reference decile level (first to fourth), the hazard ratio was significantly increased from the ninth decile in men (greater than approximately 37 pg/ml) and the highest decile in women (greater than approximately 55 pg/ml). The area under the curve generated on receiver-operating characteristic analysis of plasma BNP testing was comparable to that for the Framingham risk scoring system (0.67 vs 0.68 in men, 0.63 vs 0.68 in women; p = NS for both). In conclusion, within a community-based general population with no CV history, plasma BNP levels higher than defined thresholds show increased risk for general CV events, and the predictive ability for CV events occurring within several years may be comparable to that of an established long-standing risk score.
In the present study, we measured plasma B-type natriuretic peptide (BNP) in a large-scale population-based sample of >13,000 men and women. This cohort was followed prospectively for >5 years to ascertain the incidence of cardiovascular (CV) events, including heart failure, stroke, and myocardial infarction. To determine gender-specific threshold levels of plasma BNP, the relation between plasma BNP deciles and risk for CV events was determined. In addition, to validate plasma BNP testing for the prediction of general CV events, its predictive ability was compared to an established CV risk scoring system.
Methods
This study is part of the Iwate-KENCO study, a population-based prospective cohort study to investigate heath status and CV risks in Japanese residents living in the Iwate prefecture, northeast Honsyu, Japan. Details about this cohort are provided elsewhere. In brief, the original cohort (n = 26,469) was recruited from April 2002 and January 2005 in 3 districts (Ninohe, Kuji, and Miyako in the Iwate prefecture). The baseline survey included routine anthropometric measurements, blood pressure measurement, electrocardiography, routine laboratory assessment, and a self-administered lifestyle questionnaire. This study protocol was approved by our institutional ethics committee. All participants gave written informed consent.
Of the original cohort living in the Ninohe and Kuji districts (n = 15,927), 15,394 subjects (96.6%) agreed to provide additional blood samples for the measurement of plasma BNP levels, and these are designated as the BNP cohort in the present study. Subjects were excluded from this cohort on the basis of the following characteristics: age <40 years (n = 575) or >80 years (n = 330), serum creatinine level ≥2.0 mg/dl (n = 10), and missing data for blood pressure (n = 3), anthropometrics (n = 47), and/or routine blood tests (n = 4). The final statistical analysis was therefore performed on 13,209 subjects (4,365 men, 8,844 women; mean age 62.1 years).
A follow-up survey assessing mortality, migration, and the incidence of CV events was carried out after the baseline study. We defined CV events as stroke, congestive heart failure, and myocardial infarction requiring hospitalization. Hospital admissions for congestive heart failure and myocardial infarction in the cohort were identified by accessing data from the Northern Iwate Heart Disease Registry Consortium, which has been collecting data since 2002. Heart failure was defined by Framingham criteria, and registration of myocardial infarction was based on criteria used in the Monitoring Trends and Determinants in Cardiovascular Disease (MONICA) study. Stroke events were identified by accessing the prefecture stroke registration program conducted by the Iwate Medical Association. Stroke diagnostic criteria in this registry are based on those published by the World Health Organization and defined as the sudden onset of neurologic symptoms. To ensure that nearly all appropriate cases had been identified, researchers in each registration study periodically retrieved and reviewed medical charts and/or discharge summaries for patients admitted to the cardiology, neurology, neurosurgery, and internal medicine wards of all hospitals located within the study district.
In the baseline survey, all participants underwent routine anthropometric measurements, electrocardiography, blood pressure measurements, and laboratory assessments. In addition, a self-administered questionnaire was used to ascertain lifestyle factors such as smoking habits and medical history, including stroke, congestive heart failure, and myocardial infarction. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Systolic and diastolic blood pressure were determined with an automatic device with the subject in a sitting position for ≥5 minutes before measurement. Measurement was performed twice, with the mean value used for statistical analysis. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or current antihypertensive therapy. Diabetes was defined as a nonfasting glucose concentration ≥200 mg/dl, and/or a glycosylated hemoglobin value ≥6.5%, and/or current antidiabetic therapy. Hypercholesterolemia was defined as total cholesterol level ≥240 mg/dl and/or current lipid-lowering therapy. Enzymatic methods were used to measure serum total cholesterol levels, serum creatinine, and blood glucose. Glycosylated hemoglobin was measured quantitatively using high-performance liquid chromatography. Smoking was defined as current smoking. Estimated glomerular filtration rate was calculated using an equation (estimated glomerular filtration rate [ml/min/1.73 m ] = 194 × serum creatinine −1.094 × age −0.287 ) from the Modification of Diet in Renal Disease (MDRD) study for the Japanese population. The 10-year risk for general CV disease was calculated using the Framingham 10-year risk score, including age, gender-specific cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, diabetes, and cigarette smoking.
Blood samples for routine laboratory testing were drawn from the antecubital vein with the subject in a sitting position. While blood samples were being collected into vacuum tubes, an additional 2-ml sample of venous blood was collected into a test tube containing ethylenediaminetetraacetic acid sodium. Tubes were stored immediately after sampling in an icebox and were transported to the laboratory <8 hours after collection. They were then centrifuged at 1,500g for 10 minutes. After separation, the plasma samples were stored frozen at −20°C until the time of assay. Plasma BNP levels were measured by direct radioimmunoassay using monoclonal antibodies specific for human BNP (Shionogi, Osaka, Japan) <4 months after blood sampling. Cross-reactivity of the antibodies was 100% for human BNP and 0.001% for human atrial natriuretic peptide. Intra- and interassay coefficients of variation were 5% and 6%, respectively. The lower detection limit of the assay was 0.05 pg/ml.
Continuous variables are expressed as mean ± SD. The cohort was divided into deciles according to baseline plasma BNP levels. To compare baseline data among the BNP deciles, 1-way analysis of variance and chi-square tests were used as appropriate. Differences in clinical characteristics between men and women were tested using unpaired Student’s t test or Mann-Whitney U tests. We defined the end point as general CV events (i.e., a composite of stroke, heart failure, and myocardial infarction). The association between baseline plasma BNP levels and the end point was evaluated using a Cox proportional-hazards regression model. The gender-specific hazard ratios (HR) for each BNP decile’s end point were assessed. In this multivariate regression model, adjustments were made in the analysis for age, BMI, diabetes, hypertension, hypercholesterolemia, atrial fibrillation, estimated glomerular filtration rate, and current smoking. For analyses of CV incidence, person-years were censored at the date of CV events, the date of emigration from the study area, the date of death, or the end of the follow-up period, whichever came first. To compare the predictive abilities of plasma BNP testing to the Framingham 10-year risk scoring system, receiver-operating-characteristic curves were constructed. The area under the curve (AUC) and 95% confidence interval (CI) for each ROC curve were calculated to provide a measure of the overall diagnostic accuracy of the test. The follow-up survey for congestive heart failure, stroke, and myocardial infarction was carried out after the baseline study through to March 2009. Migrations were confirmed by official resident registration data issued by the local government offices (October 2009). All statistical analyses were performed using SPSS version 11.0.1J (SPSS, Inc., Chicago, Illinois). A significant difference was defined as p <0.05.
Results
Mean ages were 63.3 ± 9.8 years in men and 61.6 ± 9.7 years in women ( Tables 1 and 2 ). The number of women was approximately twice the number of men. Plasma BNP levels and BMI were higher in women than in men (median BNP 16.9 vs 14.2 pg/ml, p <0.001; mean BMI 24.2 ± 3.4 vs 23.9 ± 2.9 kg/m 2 , p <0.001). The prevalence of hypertension (44% vs 38%), atrial fibrillation (2.9% vs 0.6%), diabetes (9.6% vs 5.4%), and current smoking (33.9% vs 2.5%) was higher in men. The incidence of hypercholesterolemia was higher in women (10.5% vs 20.3%). The administration rates for hypertensive drugs was 23.3% in men and 23.8% in women (p = 0.232). The mean Framingham risk score in men was higher than that in women (13.8 ± 4.4 vs 11.9 ± 4.6).
| Variable | Total | D1–D4 | D5 | D6 | D7 | D8 | D9 | D10 |
|---|---|---|---|---|---|---|---|---|
| Number | 4,365 | 1,741 | 441 | 441 | 434 | 436 | 436 | 436 |
| BNP (pg/ml) | 14.2 (6.3–28.3) | 5 (2.1–7.6) | 12.3 (11.4–13.2) | 16.3 (15.3–17.5) | 21.3 (19.8–22.8) | 28.3 (26.5–30.5) | 41.4 (37.5–46.5) | 76.5 (63.4–116.7) |
| Age (years) | 63.3 ± 9.8 | 58.3 ± 10.0 | 62.9 ± 9.0 | 65.5 ± 8.4 | 65.8 ± 8.1 | 67.6 ± 7.2 | 68.1 ± 7.4 | 69.7 ± 6.2 |
| BMI (kg/m 2 ) | 23.9 ± 2.9 | 24.1 ± 2.9 | 24.0 ± 3.0 | 23.9 ± 2.8 | 23.7 ± 2.9 | 23.6 ± 2.8 | 23.5 ± 2.9 | 23.7 ± 3.0 |
| Hypertension | 43.8% | 35.1% | 41.0% | 46.5% | 45.6% | 49.8% | 56.6% | 57.6% |
| Diabetes mellitus | 9.6% | 9.8% | 8.2% | 11.6% | 9.0% | 10.1% | 8.9% | 9.2% |
| Smoker | 33.9% | 39.1% | 33.1% | 30.2% | 32.7% | 31.7% | 28.0% | 27.1% |
| Hypercholesterolemia | 10.5% | 14.5% | 9.1% | 9.3% | 7.1% | 8.5% | 7.6% | 5.7% |
| eGFR (ml/min/1.73 m 2 ) | 77.2 ± 15.3 | 80.0 ± 15.3 | 77.3 ± 15.1 | 76.4 ± 15.6 | 76.5 ± 15.0 | 74.8 ± 14.7 | 75.8 ± 15.2 | 71.3 ± 13.3 |
| Antihypertensive drugs | 23.3% | 15.8% | 21.8% | 25.9% | 26.0% | 27.5% | 32.8% | 35.3% |
| Framingham risk score | 13.8 ± 4.4 | 12.8 ± 4.5 | 13.7 ± 4.3 | 14.5 ± 4.3 | 14.5 ± 4.1 | 14.8 ± 4.1 | 14.9 ± 4.2 | 15.1 ± 4.1 |
| Variable | Total | D1–D4 | D5 | D6 | D7 | D8 | D9 | D10 |
|---|---|---|---|---|---|---|---|---|
| Number | 8,844 | 3,539 | 880 | 880 | 893 | 882 | 885 | 885 |
| BNP (pg/ml) | 16.9 (8.8–29.8) | 7.3 (3.8–10.4) | 15.0 (14.1–15.9) | 18.7 (17.8–19.7) | 23.5 (22.2–25.0) | 29.8 (28.0–31.9) | 40.4 (37.1–43.8) | 66.1 (55.1–88.0) |
| Age (years) | 61.6 ± 9.7 | 58.1 ± 9.5 | 60.7 ± 9.4 | 60.9 ± 9.6 | 63.2 ± 9.0 | 64.3 ± 8.7 | 65.3 ± 8.3 | 68.7 ± 7.2 |
| BMI (kg/m 2 ) | 24.2 ± 3.4 | 24.2 ± 3.4 | 24.0 ± 3.3 | 24.0 ± 3.4 | 24.1 ± 3.4 | 24.0 ± 3.3 | 24.0 ± 3.5 | 24.4 ± 3.7 |
| Hypertension | 38.2% | 29.5% | 35.1% | 36.0% | 43.8% | 43.2% | 47.2% | 59.0% |
| Diabetes mellitus | 5.4% | 5.3% | 4.7% | 4.8% | 5.0% | 6.2% | 5.2% | 7.2% |
| Smoker | 2.5% | 3.5% | 1.7% | 2.5% | 1.9% | 2.0% | 2.3% | 0.8% |
| Hypercholesterolemia | 20.3% | 23.3% | 18.0% | 18.9% | 21.2% | 19.7% | 14.5% | 17.2% |
| eGFR (ml/min/1.73 m 2 ) | 75.8 ± 15.0 | 78.6 ± 14.9 | 76.5 ± 14.8 | 76 ± 13.9 | 74.7 ± 14.1 | 73.9 ± 15.2 | 73.2 ± 14.7 | 69.5 ± 14.8 |
| Antihypertensive drugs | 23.8% | 16.8% | 22.8% | 21.5% | 28.4% | 27.4% | 29.9% | 41.2% |
| Framingham risk score | 11.9 ± 4.6 | 10.8 ± 4.6 | 11.2 ± 4.5 | 11.7 ± 4.5 | 12.4 ± 4.5 | 12.6 ± 4.4 | 13.1 ± 4.4 | 14.3 ± 4.0 |
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