Comparison of a risk calculator with frailty indices in patients undergoing lung cancer resection.
frailty
lung cancer
lung resection
risk calculator
thoracic oncology
Journal
Journal of surgical oncology
ISSN: 1096-9098
Titre abrégé: J Surg Oncol
Pays: United States
ID NLM: 0222643
Informations de publication
Date de publication:
29 Aug 2024
29 Aug 2024
Historique:
received:
22
05
2024
accepted:
20
07
2024
medline:
31
8
2024
pubmed:
31
8
2024
entrez:
29
8
2024
Statut:
aheadofprint
Résumé
Perioperative risk stratification is an essential component of preoperative planning for cancer surgery. While frailty has gained attention for its utility in risk stratification, no studies have directly compared it to existing risk calculators. Therefore, the objective of this study was to compare the risk stratification of the American College of Surgeons Surgical Risk Calculator (ACS-SRC), the Revised Risk Analysis Index (RAI-rev), and the Modified Frailty Index (5-mFI). The primary outcomes were 30-day postoperative morbidity, 30-day postoperative mortality, unplanned readmission, unplanned reoperation, and discharge disposition other-than-home. Patients undergoing anatomic lung resection for primary, non-small cell lung cancer were identified within the American College of Surgeons National Quality Improvement Program (ACS NSQIP) database. The ACS-SRC, RAI-rev, and 5-mFI tools were used to predict adverse postoperative events. Tools were compared for discrimination in the primary outcomes. 9663 patients undergoing anatomic lung resection for cancer between 2012 and 2014 were included. The cohort was 53.1% female. Median age at diagnosis was 67 (interquartile range = 59-74) years. Cardiothoracic surgeons performed 89% and general surgeons performed 11.0% of the operations. Perioperative morbidity and mortality rates were 10.9% (n = 1048) and 1.6% (n = 158). Rates of 30-day postoperative unplanned readmission and reoperation were 7.5% (n = 725) and 4.8% (n = 468). The ACS-SRC had the highest discrimination for all measured outcomes, as measured by the area under the receiver operating curve (AUC) and corresponding confidence interval (95% confidence interval [CI]). This included perioperative mortality (AUC = 0.74, 95% CI = 0.71-0.78), compared to RAI-rev (AUC = 0.66, 95% CI = 0.62-0.69) and 5-mFI (AUC = 0.61, 95% CI = 0.57-0.65; p < 0.001). The RAI-rev and 5-mFI had similar discrimination for all measured outcomes. ACS-SRC was the perioperative risk stratification tool with the highest predictive discrimination for adverse, 30-day, postoperative events for patients with cancer treated with anatomic lung resection.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : 5R38CA245095
Pays : United States
Organisme : NIH HHS
ID : T37MD014248
Pays : United States
Organisme : Health Services Research and Development Service of the Veterans Affairs
ID : IIR 16-232
Informations de copyright
© 2024 The Author(s). Journal of Surgical Oncology published by Wiley Periodicals LLC.
Références
Markus PM, Martell J, Leister I, Horstmann O, Brinker J, Becker H. Predicting postoperative morbidity by clinical assessment. Br J Surg. 2005;92(1):101‐106. doi:10.1002/bjs.4608
Ko FC. Preoperative frailty evaluation: a promising risk‐stratification tool in older adults undergoing general surgery. Clin Ther. 2019;41(3):387‐399. doi:10.1016/j.clinthera.2019.01.014
Lipsitz LA. Physiological complexity, aging, and the path to frailty. Sci Aging Knowledge Environ. 2004;2004(16):pe16. doi:10.1126/sageke.2004.16.pe16
Lipsitz LA. Dynamics of stability: the physiologic basis of functional health and frailty. J Gerontol A Biol Sci Med Sci. 2002;57(3):B115‐B125. doi:10.1093/gerona/57.3.B115
Bilimoria KY, Liu Y, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833‐842.e3. doi:10.1016/j.jamcollsurg.2013.07.385
Liu Y, Ko CY, Hall BL, Cohen ME. American College of Surgeons NSQIP Risk Calculator Accuracy Using a Machine Learning Algorithm Compared with Regression. J Am Coll Surg. 2023;236(5):1024‐1030. doi:10.1097/XCS.0000000000000556
Chudgar N, Yan S, Hsu M, et al. The American College of Surgeons surgical risk calculator performs well for pulmonary resection: a validation study. J Thorac Cardiovasc Surg. 2022;163(4):1509‐1516.e1. doi:10.1016/j.jtcvs.2021.01.036
Kojima G, Iliffe S, Walters K. Frailty index as a predictor of mortality: a systematic review and meta‐analysis. Age Ageing. 2018;47(2):193‐200. doi:10.1093/ageing/afx162
Hall DE, Arya S, Schmid KK, et al. Development and initial validation of the risk analysis index for measuring frailty in surgical populations. JAMA Surg. 2017;152(2):175‐182. doi:10.1001/jamasurg.2016.4202
Ng Cheong Chung KJ, Wilkinson C, Veerasamy M, Kunadian V. Frailty scores and their utility in older patients with cardiovascular disease. Interv Cardiol Rev. 2021;16:e05. doi:10.15420/icr.2020.18
Arya S, Varley P, Youk A, et al. Recalibration and external validation of the risk analysis index: a surgical frailty assessment tool. Ann Surg. 2020;272(6):996‐1005. doi:10.1097/SLA.0000000000003276
Hall DE, Arya S, Schmid KK, et al. Association of a frailty screening initiative with postoperative survival at 30, 180, and 365 Days. JAMA Surg. 2017;152(3):233‐240. doi:10.1001/jamasurg.2016.4219
Ehlert BA, Najafian A, Orion KC, Malas MB, Black JH, Abularrage CJ. Validation of a modified Frailty Index to predict mortality in vascular surgery patients. J Vasc Surg. 2016;63(6):1595‐1601.e2. doi:10.1016/j.jvs.2015.12.023
Subramaniam S, Aalberg JJ, Soriano RP, Divino CM. New 5‐factor modified frailty index using American College of Surgeons NSQIP data. J Am Coll Surg. 2018;226(2):173‐181.e8. doi:10.1016/j.jamcollsurg.2017.11.005
Varley PR, Borrebach JD, Arya S, et al. Clinical utility of the risk analysis index as a prospective frailty screening tool within a multi‐practice, multi‐hospital Integrated healthcare system. Ann Surg. 2021;274(6):e1230. doi:10.1097/SLA.0000000000003808
Wan MA, Clark JM, Nuño M, Cooke DT, Brown LM. Can the risk analysis index for frailty predict morbidity and mortality in patients undergoing high‐risk surgery? Ann Surg. 2022;276(6):e721. doi:10.1097/SLA.0000000000004626
Rothenberg KA, George EL, Trickey AW, et al. Assessment of the risk analysis index for prediction of mortality, major complications, and length of stay in patients who underwent vascular surgery. Ann Vasc Surg. 2020;66:442‐453. doi:10.1016/j.avsg.2020.01.015
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiology. 2007;18(6):800‐804. doi:10.1097/EDE.0b013e3181577654
Chudgar NP, Yan S, Hsu M, et al. Performance comparison between SURPAS and ACS NSQIP surgical risk calculator in pulmonary resection. Ann Thorac Surg. 2021;111(5):1643‐1651. doi:10.1016/j.athoracsur.2020.08.021
Beyrer J, Nelson DR, Sheffield KM, Huang YJ, Lau YK, Hincapie AL. Development and validation of coding algorithms to identify patients with incident non‐small cell lung cancer in United States healthcare claims data. Clin Epidemiol. 2023;15:73‐89. doi:10.2147/CLEP.S389824
Phillips JD, Bostock IC, Hasson RM, et al. National practice trends for the surgical management of lung cancer in the CMS population: an atlas of care. J Thorac Dis. 2019;11(Suppl 4):S500‐S508. doi:10.21037/jtd.2019.01.05
Shinall MC, Arya S, Youk A, et al. Association of preoperative patient frailty and operative stress with postoperative mortality. JAMA Surg. 2020;155(1):e194620. doi:10.1001/jamasurg.2019.4620
Cykert S, Kissling G, Hansen CJ. Patient preferences regarding possible outcomes of lung resection. Chest. 2000;117(6):1551‐1559. doi:10.1378/chest.117.6.1551
Wiesen BM, Bronsert MR, Aasen DM, et al. Use of Surgical Risk Preoperative Assessment System (SURPAS) and patient satisfaction during informed consent for surgery. J Am Coll Surg. 2020;230(6):1025‐1033.e1. doi:10.1016/j.jamcollsurg.2020.02.049
Bronsert MR, Lambert‐Kerzner A, Henderson WG, et al. The value of the “Surgical Risk Preoperative Assessment System” (SURPAS) in preoperative consultation for elective surgery: a pilot study. Patient Saf Surg. 2020;14(1):31. doi:10.1186/s13037-020-00256-4