The relationship between hospital lung cancer resection volume and patient mortality risk

Ann Surg. 2011 Dec;254(6):1032-7. doi: 10.1097/SLA.0b013e31821d4bdd.


Objective: To evaluate the volume-outcome relationship after lung cancer resection using 3 alternative measures of the effect of volume.

Summary background data: Many studies of lung cancer resection indicate that hospital volume predicts mortality. However, controversy exists regarding the strength and validity of this association. Because thresholds of procedure volume are used to recommend the regionalization of care, investigation of the validity of the volume-outcome relationship is necessary.

Methods: Lung cancer resection patients were identified in the 2007 Nationwide Inpatient Sample. Hospital volume was measured using 3 different methods: as a continuous linear function, as a nonlinear function using restricted cubic splines, and as the frequently used method of quintile categories. The statistical significance of the relationship between hospital volume and mortality risk was assessed, adjusted for patient age, comorbid disease, and for correlated events within hospitals.

Results: Forty thousand four hundred and sixty lung cancer resection patients from 436 hospitals were identified. All 3 models demonstrated excellent performance characteristics (C index = 0.92, Nagelkerke R = 0.37). No significant association was demonstrated between hospital procedure volume and in-hospital mortality when measured as a linear or nonlinear function using splines. However, a statistically significant relationship was found for volume categorized into quintiles, although its relative contribution to the predictive capacity of the model was very small (likelihood ratio = 2.55, P = 0.04).

Conclusions: The apparent impact of hospital lung cancer resection volume on mortality is dependent on how volume is defined and entered into the regression equation. Hospital lung cancer resection volume is not a predictor of mortality and should not be used as a proxy measure for surgical quality.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Comorbidity
  • Health Facility Size*
  • Hospital Mortality*
  • Humans
  • Likelihood Functions
  • Linear Models
  • Lung Neoplasms / mortality*
  • Lung Neoplasms / surgery*
  • Pneumonectomy / mortality*
  • Postoperative Complications / mortality*
  • Quality Indicators, Health Care / statistics & numerical data
  • Regression Analysis
  • Statistics as Topic
  • United States