Monaldi Archives for Chest Disease (Jul 2023)

Assessment of the 90-day mortality risk score after video-assisted thoracoscopic lobectomy in the Italian VATS Group cohort

  • Andrea Imperatori,
  • Maria Cattoni,
  • Luca Bertolaccini,
  • Mario Nosotti,
  • Lorenzo Rosso,
  • Lucio Cagini,
  • Jacopo Vannucci,
  • Alessandro Brunelli,
  • Roberto Crisci,
  • Carlo Curcio,
  • Nicola Rotolo

DOI
https://doi.org/10.4081/monaldi.2023.2569

Abstract

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A five classes (A-E) aggregate risk score predicting 90-day mortality after video-assisted thoracoscopic lobectomy for lung cancer, including as independent factors male sex (3 points), DLCO 150 minutes (1 point), has been recently published. This study aims to assess the effectiveness and reliability of this risk model in a large, independent cohort of patients, to confirm its generalizability. From the Italian VATS Group Database, we selected 2,209 patients [60% males; median age 69 years (IQR:63-74)] who underwent video-assisted thoracoscopic lobectomy for non-small cell lung cancer. We calculated the aggregate risk score and the corresponding class of 90-day mortality risk for each patient. The correlation between risk classes and mortality rates was tested by Spearman’s r-test. Model calibration was evaluated by Hosmer-Lemeshow goodness-of-fit test. Class A-E 90-day mortality rates were 0.33%, 0.51%, 1.39%, 1.31% and 2.56%, respectively. A strong uphill correlation was identified between risk classes and 90-day mortality (r=0.90; p=0.037), showing a positive correlation between increased mortality rate and class A to E. Hosmer-Lemeshow chi-squared value was 67.47 (p<0.001) with overall, Class D and E significantly lower 90-day mortality in our cohort than in the original one [1.04% vs 2.5% (p=0.018), 1.31% vs 5.65% (p=0.005) and 2.56% vs 18.75% (p=0.007), respectively]. Despite our data show a positive correlation between 90-day mortality and risk classes from A to E with modest discriminatory performance, the poor calibration suggests the need for model recalibration using local data to better manage and counsel lung cancer patients eligible for video-assisted thoracoscopic lobectomy.

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