PROGNOSTIC MODEL OF RECURRENCE AND DEATH IN STAGE-I NONSMALL CELL LUNG-CANCER UTILIZING PRESENTATION, HISTOPATHOLOGY, AND ONCOPROTEIN EXPRESSION

In order to construct a multivariate model for predicting early recurr ence and cancer death for patients with stage I non-small cell lung ca ncer, 271 consecutive patients (mean age, 63 +/- 8 years) who mere dia gnosed, treated, and followed at one institution were studied. All pat ients were clinical stage I with head and chest/abdominal computed tom ograms and radionuclide bone scans without evidence of metastatic dise ase, Pathological material after resection was reviewed to verify hist ological staging, Follow-up documented the time and location of any re currence, was a median 56 months in duration, and was complete in all cases. Data recorded included age, sex, smoking history, presenting sy mptoms, pathological description, and oncoprotein staining for erbB-2 (HER-2/neu), p53, and KI-67 proliferation protein. Immunohistochemistr y of oncogene expression was performed on two separate archived paraff in tumor blocks for each patient, with normal lung as control. All ana lyses were blinded and included Kaplan-Meier survival estimates with C ox proportional hazards regression modeling. Data, including immunohis tochemistry, were complete for all 271 patients, Actual 5-year surviva l was 63% and actuarial 10-year survival was 58%. Significant univaria te predictors (P < 0.05) of early recurrence and cancer-death were: ma le sex; the presence of symptoms; chest pain; type of cough; hemoptysi s; tumor size > 3 cm diameter (T-2); poor differentiation; vascular in vasion; erbB-2 expression; p53 expression; and a higher KI-67 prolifer ation index (>5%). An additive oncogene expression curve demonstrated a 5-year survival of 72% for 136 patients without p53 or erbB-2, 58% f or 108 patients who expressed either oncogene, and 38% for 27 who expr essed both (P < 0.001), Multivariate independent predictors of early r ecurrence and cancer death (P < 0.05) were symptomatic presentation, e rbB-2 expression, T-2 size, vascular invasion, p53 expression, and poo r differentiation. These data allowed the creation of a multivariate m odel which quantified the risk of recurrence and cancer death for pati ents with stage I non-small cell lung cancer, This model, based on com plete data from 271 patients, represents the largest analysis of its t ype in the literature and can form the basis for multi-institutional r andomized adjuvant trials for ''high risk'' patients.