A total of 490 patients from our institutional Society of Thoracic Surgeons data from 2009 to 2013 underwent resection for clinical stage I lung cancer. High-risk patients were identified by ACOSOG z4032/z4099 criteria: major: forced expiratory volume in 1 second (FEV1) 50% or less or diffusing capacity of lung for carbon monoxide (Dclass="smallcaps">lco) 50% or less; and minor: (two of the following), age 75 years or more, FEV1 51% to 60%, or Dclass="smallcaps">lco 51% to 60%. Demographics, perioperative outcomes, and survival between high-risk and standard-risk patients undergoing lobectomy and sublobar resection were compared. Univariate analysis was performed using the χ2 test/Fisher’s exact test and the t test/Mann-Whitney U test. Survival was studied using a Cox regression model to calculate hazard ratios, and Kaplan-Meier survival curves were drawn.
In all, 180 patients (37%) were classified as high risk. These patients were older than standard-risk patients (70 years versus 65 years, respectively; p < 0.0001) and had worse FEV1 (57% versus 85%, p < 0.0001), and Dclass="smallcaps">lco (47% versus 77%, p < 0.0001). High-risk patients also had more smoking pack-years than standard-risk patients (46 versus 30, p < 0.0001) and a greater incidence of chronic obstructive pulmonary disease (72% versus 32%, p < 0.0001), and were more likely to undergo sublobar resection (32% versus 20%, p = 0.001). Length of stay was longer in the high-risk group (5 versus 4 days, p < 0.0001), but there was no difference in postoperative mortality (2% versus 1%, p = 0.53). Nodal upstaging occurred in 20% of high-risk patients and 21% of standard-risk patients (p = 0.79). Three-year survival was 59% for high-risk patients and 76% for standard-risk patients (p < 0.0001).
Good clinical outcomes after surgery for early stage lung cancer can be achieved in patients classified as high risk. In our study, surgery led to upstaging in 20% of patients and acceptable 1-, 2-, and 3-year survival as compared with historical rates for nonsurgical therapies. This study suggests that empiric selection criteria may deny patients optimal oncologic therapy.