多遺伝子リスクスコア強化予測モデルと冠動脈疾患の臨床リスクスコアの予測精度
Joshua Elliott1, Barbara Bodinier1, Tom A Bond1
1Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.
JAMA
|February 19, 2020
まとめ
冠動脈疾患 (CAD) の予測モデルに多遺伝子リスクスコアを追加すると,精度がわずかに改善されます. この遺伝的リスクの情報が臨床的に広く利用される前に,さらなる研究が必要である.
科学分野:
- 心血管疾患の疫学
- 遺伝学とゲノミクス
- 予測モデリング
背景:
- 既存のリスク予測モデルと並行して冠動脈疾患 (CAD) のポリジェニックリスクスコア (PRS) の臨床的有用性は不明である.
- リスク評価の基礎となるのは,集合コホート方程式のような確立されたモデルです.
研究 の 目的:
- CADのPRSが現在の集団コホート方程式を超えてリスク予測の精度を向上させるかどうかを判断する.
- 大規模で多様な集団におけるPRSのインクリメンタル予測値を評価する.
主な方法:
- 観察研究では,PRSの最適化のためのケース・コントロールサンプルと予測精度評価のためのより大きなコホートを含む2006年から2010年の英国バイオバンクデータを利用した.
- この研究では,PRS,プールされたコホート方程式,およびそれらの組み合わせを使用して,差別 (C統計),校正,およびインシデントCADリスクの再分類を評価した.
- 再分類の分析には7.5%のリスク基準が適用された.
主要な成果:
- PRSと集団コホート方程式を組み合わせると,集団コホート方程式のみ (0. 76) よりもわずかに改善したC統計が得られました.
- PRSの追加により,7.5%のリスク値でインシデントCADの4.0%の純再分類改善がもたらされました.
- 統計的に有意だが,予測の精度とリスクの階層化の改善は控えめで,少数の個人に適用された.
結論:
- 群集されたコホート方程式にCADのPRSを組み込むことは,インシデントCADを予測する上で統計的に有意な,しかし控えめな改善を提供します.
- 現在の証拠は,広範な実施のための限られた臨床効果を示唆し,さらなる調査を正当化します.
- この研究は 遺伝情報の可能性を強調していますが 臨床採用前に 慎重に評価する必要性を強調しています
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