JP2019512082A - 早産のリスクを予測するためのツール - Google Patents
早産のリスクを予測するためのツール Download PDFInfo
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- JP2019512082A JP2019512082A JP2018540707A JP2018540707A JP2019512082A JP 2019512082 A JP2019512082 A JP 2019512082A JP 2018540707 A JP2018540707 A JP 2018540707A JP 2018540707 A JP2018540707 A JP 2018540707A JP 2019512082 A JP2019512082 A JP 2019512082A
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Abstract
Description
a)複数のリスク指標が被験者において評価される;
b)リスク指標評価が、被験者におけるPTBのリスクを予測する予測モデルに入力される;および
c)上昇したPTBリスクが評価される場合、PTB治療介入を被験者に施す。
リスク指標に関して、いくつかの症例では、リスク指標は、脂質、タンパク質、および核酸を含む、被験者内に存在する生物由来物質である、バイオマーカーを含む。選択されたバイオマーカーは、様々なカテゴリから引き出され得、カテゴリは異なる代謝プロセスおよび経路と関連付けられている。一実施態様では、リスク指標は、次のカテゴリ:胎盤機能;脂質状態;ホルモン状態;および免疫活性、から引き出される。
本発明の方法は、母体因子のPTBリスク指標としての使用をさらに含み得る。母体因子は、本明細書では、母体被験者の任意の特質を含み得る。例えば、母体因子は、年齢、人種または民族性、収入状態などの、被験者の様々な人口統計学的特性を包含し得る。1つの母体因子は、「支援状態」であり、政府の医療支援プログラム(例えば、メディケア)の利用を意味する。母体因子は、被験者と関連付けられた健康状態因子をさらに包含し得る。一実施形態では、体重または肥満度指数は、PTBリスクの指標として、例えば、被験者が30を超える肥満度指数を有するかどうか、使用され得る。同様に、高血圧、糖尿病、貧血、または他の条件の有無および/または重症度が、PTBリスク指標因子として使用され得る。母体因子は、妊娠段階、例えば、妊娠期間などの、妊娠因子をさらに包含し得る。別の母体因子は、出産数、女性が以前に成育可能な妊娠期間まで妊娠していた回数である。
一態様では、本発明は、個々の被験者におけるPTBのリスクをその被験者のリスク指標に基づいて評価するための予測モデルを生成する方法を提供する。本モデルは、一般的なプロセスによって次のように生成される:第1に、リスク指標のパネルが選択される。次に、妊娠中にPTBを経験した女性の第1のプール、および妊娠中にPTBを経験しなかった女性の第2のプールに対するリスク指標値が次いで分析されて、リスク指標値とPTBを経験する確率との間の数学的関係を導出する。
本明細書で提供する予測ツールは、様々な方法で使用され得る。第1の態様では、本発明は、次のステップ:
選択されたパネル内の各リスク指標に対する被験者のリスク指標値を取得すること;
取得したリスク指標値を、リスク指標の選択されたパネルに基づいて、予測モデルに入力すること;および
予測モデルを使用して被験者に対するPTBリスク評価を計算すること
を含む、被験者に対するPTBリスクを評価する方法を含む。
モデル1は、中央値の倍数として表現されたAFP、hCG、およびLDL測定値を利用する。離散母体指標は、次のように数値を割り当てられる:医療支援を使用している被験者=1、医療支援を使用していない被験者=0;BMI>30の被験者=1、BMI<30の被験者=0;既存の高血圧=1、既存の高血圧なし=0;および既存の糖尿病=1、既存の糖尿病なし=0。他の全ての変数は、胎盤マーカー、脂質、およびプロゲステロンに対するpg/mlとしてのバイオマーカー血清濃度測定値、ならびにサイトカイン、ケモカインおよび受容体に対する中央蛍光強度(MFI)値として表現される。
式中、AFP、hCG、INH値は中央値の倍数として表され、被験者が何らかの高血圧である場合、高血圧値=1で、被験者が高血圧ではない場合、高血圧値=0であり;被験者が何らかの糖尿病である場合、糖尿病値=1で、被験者が糖尿病ではない場合、糖尿病値=0であり;被験者が何らかの貧血である場合、貧血値=1で、被験者が貧血ではない場合、貧血値=0であり;また、被験者が何らかの公的保険給付を受けている場合、支援値=1で、被験者が公的保険給付を受けていない場合、支援値=0である。他の全ての変数は、胎盤マーカー、脂質、およびプロゲステロンに対するpg/mlとしてのバイオマーカー血清濃度測定値、ならびにサイトカイン、ケモカインおよび受容体に対する中央蛍光強度(MFI)値として表現される。
本明細書で提供するのは、PTBリスクを予測するリスク指標のセットである。その結果、これらの発見は、単一の試料において複数のPTBリスク指標を同時に測定するための統合測定法の設計を可能にする。本明細書で提供するのは、試料中のPTBバイオマーカープロファイルの迅速で、安価で、簡便な評価を容易にするために使用できる新規の測定キットである。本明細書では、「測定キット(assay kit)」は、一試料中の2つ以上のPTBバイオマーカーを定量化するために使用できる製品の集約された集合を指す。
例1.モデル1およびパネルAの生成
モデル1を、双方向相互作用を考慮して、多変量逆方向段階的ロジスティック回帰を使用して生成した。胎盤機能に関連した4つのマーカーを将来を見越して検査して、保存された15〜20妊娠週の血清試料中の69の脂質、ホルモン、および免疫関連マーカーを、自然PTBの200人(100人が<34週、100人が34〜36週)の女性、および200人の妊娠末期対照(term control)における日常的な出生前診断の一部として収集した。
将来を見越して測定された利用可能な第1および第2の三半期血清マーカーを有する単胎妊娠のサブセットを選択した。この調査のため、200の症例を、より厳密な分析および潜在的な検体を引き出すためにランダムに選択した。PTBという結果になった173の妊娠(74のPPROM、99の早期分娩)を選択した。対照は、30以上の肥満度指数(BMI)について症例と対照が頻繁に一致している満期出産から1:1の比率でランダムに選択した。
ここでは、PTBリスク指標のさらなる解明を実行した。
目的:この調査では、目的は、胎盤機能、脂質、ホルモン機能、および免疫系に関連した第2の三半期血清マーカーが早期PTBに対するリスクを評価するために使用できるかどうか評価することであった。
Claims (25)
- 被験者におけるPTBのリスクを評価するための予測モデルを生成する方法であって、
リスク指標のパネルの選択と、
リスク指標値とPTBを経験する確率との間の数学的関係を導出するための、妊娠中にPTBを経験した女性の第1のプールに対する前記リスク指標値および妊娠中にPTBを経験しなかった女性の第2のプールに対する前記リスク指標値への統計的分析の適用と
を含む、方法。 - 指標の前記選択されたパネルは、胎盤機能、脂質状態、ホルモン状態、および免疫活性のカテゴリの各々から1つ以上の指標を含む、
請求項1に記載の方法。 - リスク指標の前記選択されたパネルは、AFP、hCG、LDL、プロゲステロン、IL−1A、IL−1RA、GP130、IL−7、IL−10、Il−15、IFNA、IFNB、MIP1B、MCP3、ENA78、IL−8、MIG、IP−10、CD40L、TNFR1、TRAIL、sFASL、PDGFBB、NGF、VEGF、VEGFR2、支援状態、肥満度指数、高血圧状態、および糖尿病状態から成る群から選択された2つ以上のリスク指標を含む、
請求項1に記載の方法。 - リスク指標の前記選択されたパネルは、出産数、糖尿病状態、高血圧状態、PAPP−A、AFP、TRAIL、IL−4、IL−5、IFNA、LIF、NGF、VEGF、VEGFR1、IP−10、MIP1A、RANTES、およびCRPから成る群から選択された2つ以上のリスク指標を含む、
請求項1に記載の方法。 - リスク指標の前記選択されたパネルは、高血圧状態、糖尿病状態、貧血状態、支援状態、プロゲステロン、PAPP−A、hCG、AFP、HDL、トリグリセリド、トリグリセリド:HDL、IL−6、CD40L、TRAIL、IL−13、LIF、MCSF、VEGFR1、VEGFR3、EOTAXIN、MCP−3、およびMIGから成る群から選択された2つ以上のリスク指標を含む、
請求項1に記載の方法。 - リスク指標の前記選択されたパネルは、AFP、hCG、INH、コレステロール、LDL、TNFR1、HGF、IL1R1、IL4R、VEGFR2、EOTAXIN、MIG、MIP1A、およびICAM1から成る群から選択された2つ以上のリスク指標を含む、
請求項1に記載の方法。 - 前記統計的分析は、ロジスティック回帰分析、線形判別分析、部分最小二乗判別分析、多重線形回帰分析、多変量非線形回帰、逆方向段階的回帰、閾値に基づく方法、ツリーベース法、ピアソンの相関係数、サポートベクターマシン、一般化加法モデル、教師ありおよび教師なし学習モデル、ならびにクラスター分析から成る群から選択される、
請求項1に記載の方法。 - 被験者に対するPTBリスクを評価する方法であって、次のステップ:
選択されたパネル内の各リスク指標に対して前記被験者のリスク指標値を取得することと、
前記取得されたリスク指標値を、リスク指標の前記選択されたパネルに基づく予測モデルに入力することと、
前記予測モデルを使用して、前記被験者に対するPTBリスク評価を計算することと
を含む、方法。 - 指標の前記選択されたパネルは、胎盤機能、脂質状態、ホルモン状態、および免疫活性のカテゴリの各々から1つ以上の指標を含む、
請求項8に記載の方法。 - リスク指標の前記選択されたパネルは、AFP、hCG、LDL、プロゲステロン、IL−1A、IL−1RA、GP130、IL−7、IL−10、Il−15、IFNA、IFNB、MIP1B、MCP3、ENA78、IL−8、MIG、IP−10、CD40L、TNFR1、TRAIL、sFASL、PDGFBB、NGF、VEGF、VEGFR2、支援状態、肥満度指数、高血圧状態、および糖尿病状態から成る群から選択された2つ以上のリスク指標を含む、
請求項8に記載の方法。 - リスク指標の前記選択されたパネルは、出産数、糖尿病状態、高血圧状態、PAPP−A、AFP、TRAIL、IL−4、IL−5、IFNA、LIF、NGF、VEGF、VEGFR1、IP−10、MIP1A、RANTES、およびCRPから成る群から選択された2つ以上のリスク指標を含む、
請求項8に記載の方法。 - リスク指標の前記選択されたパネルは、高血圧状態、糖尿病状態、貧血状態、支援状態、プロゲステロン、PAPP−A、hCG、AFP、HDL、トリグリセリド、トリグリセリド:HDL、IL−6、CD40L、TRAIL、IL−13、LIF、MCSF、VEGFR1、VEGFR3、EOTAXIN、MCP−3、およびMIGから成る群から選択された2つ以上のリスク指標を含む、
請求項8に記載の方法。 - リスク指標の前記選択されたパネルは、AFP、hCG、INH、コレステロール、LDL、TNFR1、HGF、IL1R1、IL4R、VEGFR2、EOTAXIN、MIG、MIP1A、およびICAM1から成る群から選択された2つ以上のリスク指標を含む、
請求項8に記載の方法。 - 前記予測モデルは、式:
PTB確率スコア=−8.1283+(1.4469*log AFP MoM)+(−0.3991*log hCG MoM)+(−0.7104*log LDL MoM)+(4.8981*logプロゲステロン)+(−1.1834*log Il−1A)+(0.6207*log IL−1RA)+(−1.1990*log GP130)+(−1.6212*log IL−7)+(1.0055*log IL−10)+(1.9563*log IL−15)+(0.1631*log INFA)+(−0.4121*log INFB)+(−0.0767*log MIP1B)+(−1.6237*log MCP3)+(0.4761*log ENA78)+(0.2408*log IL−8)+(0.8217*log MIG)+(1.5658*log IP−10)+(0.8339*log TNFR1)+(−5.0613*log CD40L)+(9.0228*log TRAIL)+(−0.5493*log sFASL)+(1.0309*log PDGFBB)+(−17.9255*log VEGF)+(1.0385*log VEGFR2)+(3.7481*支援)+(0.5289*BMI)+(−12.5091*高血圧)+(1.8859*糖尿病)+(1.8505*log TNFR1*logプロゲステロン)+((1.3174*log CD40L*logプロゲステロン)+(−5.1778*log VEGF*logプロゲステロン)+(−0.7364*log TRAIL*支援)+(−1.4070*IL−8*高血圧)+(5.2669*log VEGF*高血圧)
を含み、
式中、医療支援を使用している被験者=1、医療支援を使用していない被験者=0;BMI>30の被験者=1、BMI<30の被験者=0;既存の高血圧=1、既存の高血圧なし=0;および既存の糖尿病=1、既存の糖尿病なし=0、MoM=中央値の倍数であり、かつバイオマーカー血清濃度測定値は、胎盤マーカー、脂質、およびプロゲステロンに対してpg/ml、ならびにサイトカイン、ケモカインおよび受容体に対して中央蛍光強度(MFI)値である、
請求項10に記載の方法。 - 前記予測モデルは、式:
PTB確率スコア=−6.7601+0.9949(log AFP MoM)−0.3583(log hCG MoM)+0.2165(log INH MoM)−0.5084(log TNFR1)+0.7793(logプロゲステロン)−0.7101(logコレステロール)+0.9711(log LDL MoM)−0.2369(log HGF)+0.3425(log IL1R1)−0.2802(log IL4R)+0.0822(log VEGFR2)+0.5048(log EOTAXIN)+0.1232(log MIG)−0.2914(log MIP1A)+0.5077(log ICAM1)+1.3842(高血圧値)+0.8358(糖尿病値)+0.5719(支援値)+0.5426(貧血値)
を含み、
式中、MoMは中央値の倍数を示し、被験者が何らかの高血圧である場合、高血圧状態=1で、被験者が高血圧ではない場合、高血圧状態=0であり;被験者が何らかの糖尿病である場合、糖尿病値=1で、被験者が糖尿病ではない場合、糖尿病値=0であり;被験者が何らかの貧血である場合、貧血値=1で、被験者が貧血ではない場合、貧血値=0であり;被験者が何らかの公的保険給付を受けている場合、支援値=1で、被験者が公的保険給付を受けていない場合、支援値=0であり、バイオマーカー値は、胎盤マーカー、脂質、およびプロゲステロンに対してpg/ml、ならびにサイトカイン、ケモカインおよび受容体に対して中央蛍光強度(MFI)値である、
請求項13に記載の方法。 - 前記被験者のPTBのリスクが上昇している場合、前記被験者に治療介入を施す、
追加のステップをさらに含む、請求項13に記載の方法。 - 上昇は、10%を超えるとPTBリスクがあるとして定義される、
請求項16に記載の方法。 - 上昇は、70%を超えるとPTBリスクがあるとして定義される、
請求項17に記載の方法。 - 前記治療介入は、モニタリングの増加、ライフスタイルの制限、プロゲステロンの投与、感染症のモニタリング、抗生物質の投与、抗炎症薬の投与、締結の設置、および子宮頸部ペッサリーの設置から成る群から選択される、
請求項18に記載の方法。 - 試料中の早産リスクバイオマーカーを評価するためのキットであって、
AFP、hCG、LDL、プロゲステロン、IL−1A、IL−1RA、GP130、IL−7、IL−10、Il−15、IFNA、IFNB、MIP1B、MCP3、ENA78、IL−8、MIG、IP−10、CD40L、TNFR1、TRAIL、sFASL、PDGFBB、NGF、VEGF、およびVEGFR2から成る群から選択された2つ以上のバイオマーカーを検出可能な要素を含む、キット。 - 試料中の早産リスクバイオマーカーを評価するためのキットであって、
PAPP−A、AFP、TRAIL、IL−4、IL−5、IFNA、LIF、NGF、VEGF、VEGFR1、IP−10、MIP1A、RANTES、およびCRPから成る群から選択された2つ以上のバイオマーカーを検出可能な要素を含む、キット。 - 試料中の早産リスクバイオマーカーを評価するためのキットであって、
プロゲステロン、PAPP−A、hCG、AFP、HDL、トリグリセリド、トリグリセリド:HDL、IL−6、CD40L、TRAIL、IL−13、LIF、MCSF、VEGFR1、VEGFR3、EOTAXIN、MCP−3、およびMIGから成る群から選択された2つ以上のバイオマーカーを検出可能な要素を含む、キット。 - 試料中の早産リスクバイオマーカーを評価するためのキットであって、
AFP、hCG、INH、コレステロール、LDL、TNFR1、HGF、IL1R1、IL4R、VEGFR2、EOTAXIN、MIG、MIP1A、およびICAM1から成る群から選択された2つ以上のバイオマーカーを検出可能な要素を含む、キット。 - 前記キットが免疫測定法要素を含む、
請求項20〜請求項23のいずれかに記載のキット。 - 前記免疫測定法要素が定量的ELISAアッセイを含む、
請求項24に記載のキット。
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