TY - JOUR
T1 - Performance Comparison Between SURPAS and ACS NSQIP Surgical Risk Calculator in Pulmonary Resection
AU - Chudgar, Neel P.
AU - Yan, Shi
AU - Hsu, Meier
AU - Tan, Kay See
AU - Gray, Katherine D.
AU - Molena, Daniela
AU - Nobel, Tamar
AU - Adusumilli, Prasad S.
AU - Bains, Manjit
AU - Downey, Robert J.
AU - Huang, James
AU - Park, Bernard J.
AU - Rocco, Gaetano
AU - Rusch, Valerie W.
AU - Sihag, Smita
AU - Jones, David R.
AU - Isbell, James M.
N1 - Funding Information:
The authors wish to thank David Sewell for his editorial assistance and Joe Dycoco for his database expertise. This work was supported by National Institutes of Health National Cancer Institute Cancer Center Support Grant P30 CA008748 .
Publisher Copyright:
© 2021 The Society of Thoracic Surgeons
PY - 2021/5
Y1 - 2021/5
N2 - Background: Accurate preoperative risk assessment is critical for informed decision making. The Surgical Risk Preoperative Assessment System (SURPAS) and the National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator (SRC) predict risks of common postoperative complications. This study compares observed and predicted outcomes after pulmonary resection between SURPAS and NSQIP SRC. Methods: Between January 2016 and December 2018, 2514 patients underwent pulmonary resection and were included. We entered the requisite patient demographics, preoperative risk factors, and procedural details into the online NSQIP SRC and SURPAS formulas. Performance of the prediction models was assessed by discrimination and calibration. Results: No statistically significant differences were found between the 2 models in discrimination performance for 30-day mortality, urinary tract infection, readmission, and discharge to a nursing or rehabilitation facility. The ability to discriminate between a patient who will develop a complication and a patient who will not was statistically indistinguishable between NSQIP and SURPAS, except for renal failure. With a C index closer to 1.0, the NSQIP performed significantly better than the SURPAS SRC in discriminating risk of renal failure (C index, 0.798 vs 0.694; P = .003). The calibration curves of predicted and observed risk for each model demonstrate similar performance with a tendency toward overestimation of risk, apart from renal failure. Conclusions: Overall, SURPAS and NSQIP SRC performed similarly in predicting outcomes for pulmonary resections in this large, single-center validation study with moderate to good discrimination of outcomes. Notably, SURPAS uses a smaller set of input variables to generate the preoperative risk assessment. The addition of thoracic-specific input variables may improve performance.
AB - Background: Accurate preoperative risk assessment is critical for informed decision making. The Surgical Risk Preoperative Assessment System (SURPAS) and the National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator (SRC) predict risks of common postoperative complications. This study compares observed and predicted outcomes after pulmonary resection between SURPAS and NSQIP SRC. Methods: Between January 2016 and December 2018, 2514 patients underwent pulmonary resection and were included. We entered the requisite patient demographics, preoperative risk factors, and procedural details into the online NSQIP SRC and SURPAS formulas. Performance of the prediction models was assessed by discrimination and calibration. Results: No statistically significant differences were found between the 2 models in discrimination performance for 30-day mortality, urinary tract infection, readmission, and discharge to a nursing or rehabilitation facility. The ability to discriminate between a patient who will develop a complication and a patient who will not was statistically indistinguishable between NSQIP and SURPAS, except for renal failure. With a C index closer to 1.0, the NSQIP performed significantly better than the SURPAS SRC in discriminating risk of renal failure (C index, 0.798 vs 0.694; P = .003). The calibration curves of predicted and observed risk for each model demonstrate similar performance with a tendency toward overestimation of risk, apart from renal failure. Conclusions: Overall, SURPAS and NSQIP SRC performed similarly in predicting outcomes for pulmonary resections in this large, single-center validation study with moderate to good discrimination of outcomes. Notably, SURPAS uses a smaller set of input variables to generate the preoperative risk assessment. The addition of thoracic-specific input variables may improve performance.
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U2 - 10.1016/j.athoracsur.2020.08.021
DO - 10.1016/j.athoracsur.2020.08.021
M3 - Article
C2 - 33075322
AN - SCOPUS:85103381273
SN - 0003-4975
VL - 111
SP - 1643
EP - 1651
JO - Annals of Thoracic Surgery
JF - Annals of Thoracic Surgery
IS - 5
ER -