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J Thorac Cardiovasc Surg 2006;132:491-498
© 2006 The American Association for Thoracic Surgery
General Thoracic Surgery |
a Department of Cardio-Thoracic Surgery, Erasmus MC, Rotterdam, The Netherlands
c Department of Public Health, Erasmus MC, Rotterdam, The Netherlands
b Department of General Surgery, Leiden University Medical Center, Leiden, The Netherlands
d Department of Cardio-Thoracic Surgery, Leiden University Medical Center, Leiden, The Netherlands
Received for publication December 2, 2005; revisions received February 26, 2006; accepted for publication April 11, 2006. * Address for correspondence: Özcan Birim, MD, PhD, Department of Cardio-Thoracic Surgery, Room BD 156, Erasmus MC, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands (Email: o.birim{at}erasmusmc.nl).
OBJECTIVE: At present, there is no prognostic model that is specific for prediction of survival after nonsmall cell lung cancer surgery. We aimed to develop a prognostic model that can be used to estimate the postoperative survival of individual patients.
METHODS: A total of 766 patients underwent resection for primary nonsmall cell lung cancer. Comorbid conditions were scaled according to the Charlson comorbidity index (CCI). Cox proportional hazard analyses were used to determine risk factors for survival. A prognostic model for survival with a preoperative and postoperative mode was established. Performance of the prognostic model, the CCI, and pathologic tumor stage were quantified by a concordance statistic to indicate discriminative ability.
RESULTS: The factors associated with an impaired survival were male sex, age, chronic obstructive pulmonary disease, congestive heart failure, any prior tumor, moderate-to-severe renal disease (preoperative and postoperative mode), clinical tumor stage (preoperative mode), type of resection, and pathologic tumor stage (postoperative mode). The discriminative performance was poor for the CCI (c = 0.55), better for pathologic tumor stage (c = 0.60) and for the preoperative mode (c = 0.61), and best for the postoperative mode (c = 0.65). The discriminative performance of the postoperative mode was better than the discriminative performance of the CCI (P < .0001), the preoperative mode (P < .0002), and pathologic tumor stage (P < .0001). The discriminative performance of the preoperative mode was better than the discriminative performance of the CCI (P < .0001) and similar (P = .90) to a model that only included pathologic tumor stage.
CONCLUSIONS: The prognostic model, particularly the postoperative mode, successfully estimates long-term survival of individual patients and could help clinicians in clinical decision-making and treatment tailoring.
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