Performance Comparison Between SURPAS and ACS NSQIP Surgical Risk Calculator in Pulmonary Resection

Area of Science:

• Thoracic Surgery
• Surgical Outcomes Research
• Predictive Analytics in Medicine

Background:

• Accurate preoperative risk assessment is crucial for surgical decision-making.
• The Surgical Risk Preoperative Assessment System (SURPAS) and the National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator (SRC) are tools for predicting postoperative complications.
• This study aimed to compare the predictive performance of SURPAS and NSQIP SRC for pulmonary resection outcomes.

Purpose of the Study:

• To compare the observed and predicted postoperative complication rates between the SURPAS and NSQIP SRC models.
• To evaluate the discrimination and calibration of both risk assessment tools in a cohort undergoing pulmonary resection.

Main Methods:

• A retrospective analysis of 2514 patients undergoing pulmonary resection between January 2016 and December 2018.
• Inputting patient demographics, preoperative risk factors, and procedural details into both NSQIP SRC and SURPAS prediction models.
• Assessing model performance using discrimination (C-index) and calibration metrics.

Main Results:

• Both SURPAS and NSQIP SRC demonstrated comparable discrimination for 30-day mortality, urinary tract infection, readmission, and discharge disposition.
• NSQIP SRC showed significantly better discrimination for renal failure risk compared to SURPAS (C-index, 0.798 vs 0.694; P = .003).
• Calibration curves indicated similar performance for both models, with a general tendency towards overestimation of risk, except for renal failure.

Conclusions:

• SURPAS and NSQIP SRC exhibit similar predictive performance for pulmonary resection outcomes in a large, single-center validation study.
• SURPAS utilizes a more concise set of input variables.
• Incorporating thoracic-specific variables into risk assessment models may enhance predictive accuracy.