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. 2007 Nov;62(11):991-7.
doi: 10.1136/thx.2007.079145. Epub 2007 Jun 15.

Risk factors for 30-day mortality after resection of lung cancer and prediction of their magnitude

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Risk factors for 30-day mortality after resection of lung cancer and prediction of their magnitude

Trond-Eirik Strand et al. Thorax. 2007 Nov.

Abstract

Background: There is considerable variability in reported postoperative mortality and risk factors for mortality after surgery for lung cancer. Population-based data provide unbiased estimates and may aid in treatment selection.

Methods: All patients diagnosed with lung cancer in Norway from 1993 to the end of 2005 were reported to the Cancer Registry of Norway (n = 26 665). A total of 4395 patients underwent surgical resection and were included in the analysis. Data on demographics, tumour characteristics and treatment were registered. A subset of 1844 patients was scored according to the Charlson co-morbidity index. Potential factors influencing 30-day mortality were analysed by logistic regression.

Results: The overall postoperative mortality rate was 4.4% within 30 days with a declining trend in the period. Male sex (OR 1.76), older age (OR 3.38 for age band 70-79 years), right-sided tumours (OR 1.73) and extensive procedures (OR 4.54 for pneumonectomy) were identified as risk factors for postoperative mortality in multivariate analysis. Postoperative mortality at high-volume hospitals (> or = 20 procedures/year) was lower (OR 0.76, p = 0.076). Adjusted ORs for postoperative mortality at individual hospitals ranged from 0.32 to 2.28. The Charlson co-morbidity index was identified as an independent risk factor for postoperative mortality (p = 0.017). A prediction model for postoperative mortality is presented.

Conclusions: Even though improvements in postoperative mortality have been observed in recent years, these findings indicate a further potential to optimise the surgical treatment of lung cancer. Hospital treatment results varied but a significant volume effect was not observed. Prognostic models may identify patients requiring intensive postoperative care.

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Conflict of interest statement

Competing interests: None.

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