フレミングハムCHDリスク評価ツールの中国人人口に対する予測価値は,中国の多省コホート研究と比較した
Jing Liu1, Yuling Hong, Ralph B D'Agostino
1Department of Epidemiology, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China. jingliu0516@yahoo.com.cn
JAMA
|June 3, 2004
まとめ
フレミングハム冠動脈疾患 (CHD) リスク関数の再調整により,中国人集団におけるその正確性が改善されました. この適応により,フレミングハムモデルは,全世界のCHDリスクを予測するのにより有用になります.
科学分野:
- 心臓病学 心臓病学
- エピデミオロジー エピデミオロジー
- 公衆衛生は公衆衛生である.
背景:
- フレミングハム心臓研究 (Framingham Heart Study) は,冠動脈疾患 (CHD) のリスク評価のための重要なツールを提供します.
- しかし,その均質な人口は,多様な地球の人口への直接的適用を制限しています.
- これらの機能を再調整することで,世界中のローカル用途に適応できます.
研究 の 目的:
- 大規模な中国人集団におけるオリジナルのFramingham CHDリスク関数のパフォーマンスと再校正のパフォーマンスを評価する.
- 中国の多省コホート研究 (CMCS) から派生した機能と彼らのパフォーマンスを比較するために.
主な方法:
- CMCS (1992-2002) の30121人の中国人成人と,Framingham Heart Study (1971-1984) の5251人の米国人住民のデータを活用した.
- 危険因子 (年齢,血圧,喫煙,糖尿病,コレステロール) と"ハード"CHDイベント (冠動脈死亡,心筋梗塞) を比較した.
- 評価されたフレミングハム関数は,再校正後,CMCSから派生した関数に対して直接評価されます.
主要な成果:
- ほとんどのCHDリスク因子の相対的なリスクは,中国人とフレーミングハム人群の間で,顕著な例外を除いて,類似していました.
- オリジナル・フレーミングハム機能は,CMCSコホートにおけるCHDの絶対リスクを大幅に過大評価した.
- CMCSデータを用いた再校正により,フレーミングハム関数の予測の精度が大幅に改善されました.
結論:
- 元のフレミングハムのCHDリスク関数は,中国人に対して不正確であり,リスクを過大評価している.
- 再校正は,中国人個人のフレミングハムモデルの有用性を高めます.
- リカリブレーションは,データに限られた地域で,局所的なCHDリスク予測ツールを開発するための実行可能な戦略を提供します.
関連する概念動画
Confidence Interval for Estimating Population Mean
7.7K
A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
7.7K
Distributions to Estimate Population Parameter
4.5K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.5K
Estimating Population Standard Deviation
2.5K
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
2.5K
Estimating Population Mean with Unknown Standard Deviation
6.4K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
William S. Gosset (1876–1937) of the...
6.4K
Hazard Rate
537
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
537
Hazard Ratio
785
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
785


