論文No1344
A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL
Oisin J. O’Connell , Francisco A. Almeida , Michael J. Simoff , Lonny Yarmus , Ray Lazarus , Benjamin Young , Yu Chen , Roy Semaan , Timothy M. Saettele , Joseph Cicenia , Harmeet Bedi
AJRCCM, Vol. 195, No. 12 | Jun 15, pp. 1651–1660, 2017
https://doi.org/10.1164/rccm.201607-1397OC PubMed: 28002683
＜背景＞
非小細胞肺癌のN2 or N3 の可能性(prN2/3)を気管支内視鏡超音波ガイド経気管支針生検(EBUS-TBNA)で評価することはその後の治療戦略選択を容易にすることができる。
＜目的＞
prN2/3の評価を予測する臨床モデルを開発する。
＜方法＞
AQuIRE (American College of Chest Physicians Quality Improvement Registry, Evaluation, and Education)レジストリによるNSCLCの放射線的ステージ T1–3, N0–3, M0でEBUS-TBNAを使用した。
依存変数はN2, N3の存在(vs. N0 or N1)をEBUS-TBNAで評価した。
ロジスティック回帰分析で単変量、多変量解析を行い、pr N2/3を評価する臨床モデルを開発した。
＜結果＞
導出コホート(633名）のうち25%がN2/N3に該当した。
pr N2/3が高いことと関連したのは、若年、中枢病変、腺がん、PETによるN病変であった。
AUCのROC曲線は0.85(95% confidence interval, 0.82–0.89)であり、モデルの一致率は許容範囲であった (Hosmer-Lemeshow, P = 0.62; Brier score, 0.125)。
検証モデルを722名におこなった。
AUC-ROC曲線は0.88(95% confidence interval, 0.85–0.90)であった。
一般的なキャリブレーション方式で補正して一致率は良好であった(Hosmer-Lemeshow test, P = 0.54; Brier score, 0.132)。
＜感想＞
NSCLCのpr N2/3の予測に若年、中枢病変、腺がん、PETによるN病変を使用したモデルは有用だったようです。
Rationale: Estimating the probability of finding N2 or N3 (prN2/3) malignant nodal disease on endobronchial ultrasound–guided transbronchial needle aspiration (EBUS-TBNA) in patients with non–small cell lung cancer (NSCLC) can facilitate the selection of subsequent management strategies.
Objectives: To develop a clinical prediction model for estimating the prN2/3.
Methods: We used the AQuIRE (American College of Chest Physicians Quality Improvement Registry, Evaluation, and Education) registry to identify patients with NSCLC with clinical radiographic stage T1–3, N0–3, M0 disease that had EBUS-TBNA for staging. The dependent variable was the presence of N2 or N3 disease (vs. N0 or N1) as assessed by EBUS-TBNA. Univariate followed by multivariable logistic regression analysis was used to develop a parsimonious clinical prediction model to estimate prN2/3. External validation was performed using data from three other hospitals.
Measurements and Main Results: The model derivation cohort (n = 633) had a 25% prevalence of malignant N2 or N3 disease. Younger age, central location, adenocarcinoma histology, and higher positron emission tomography–computed tomography N stage were associated with a higher prN2/3. Area under the receiver operating characteristic curve was 0.85 (95% confidence interval, 0.82–0.89), model fit was acceptable (Hosmer-Lemeshow, P = 0.62; Brier score, 0.125). We externally validated the model in 722 patients. Area under the receiver operating characteristic curve was 0.88 (95% confidence interval, 0.85–0.90). Calibration using the general calibration model method resulted in acceptable goodness of fit (Hosmer-Lemeshow test, P = 0.54; Brier score, 0.132).
Conclusions: Our prediction rule can be used to estimate prN2/3 in patients with NSCLC. The model has the potential to facilitate clinical decision making in the staging of NSCLC.