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Prognostic Factors for Survival in Inoperable Non-Small-Cell Lung Cancer: A Multivariate Regression Analysis of 456 Patients with Radiation TherapyOhlhauser C.a · Bülzebruck H.a · Ebert W.a · Drings P.a · Wannenmacher M.b
aThoraxklinik Heidelberg-Rohrbach der LVA Baden, Heidelberg bUniversitäts-Strahlenklinik Heidelberg
Background: The aim of the present analysis was to evaluate the dominating independent prognostic factors of patients with non-small-cell lung cancer (NSCLC) and radiation therapy. Based on these factors, a prognostic index for survival was created and used to divide the patient population into different prognostic groups. Patients and Methods: Prognostic factors for survival were prospectively evaluated between January 1, 1987 and December 31, 1990 at the Thoraxklinik Heidelberg-Rohrbach in 456 previously untreated patients with advanced NSCLC who had received radiation therapy. Data on 30 pretreatment variables were investigated including 5 tumor-associated, 5 host-associated and 20 initial laboratory parameters. Results: Univariate analysis demonstrated that 16 of these variables were favorable prognostic factors for survival. The subsequent multivariate analysis using Cox’s proportional hazard model revealed that a hemoglobin level greater than 12.7 g/dl (p = 0.006), a lactate dehydrogenase less than or equal to 200 U/l (p = 0.035), a serum gamma-glutamyl transpeptidase (GGT) less than or equal to 60 U/l (p = 0.032), a lymphocyte count greater than 2.0/nl (p = 0.008), and a low stage of disease (TNM stages I + II) (p < 0.001) contributed independently to survival. On the basis of these 5 independent prognostic factors, a prognostic index for survival of each patient was calculated to define 3 prognostic groupings (good, intermediate, poor). The median survival within these groups was 412 days vs. 260 days vs. 133 days (p = 0.001). Conclusions: By using prognostic factors for treatment evaluation, a better individual judgement of patients could be obtained and the treatment regimes within the prognostic different subgroups could be improved. The prognostic index could be used to identify more precisely, those patients, who profit from an aggressive therapy, in order to save patients with bad prognosis from invasive treatment that could impair their quality of life and shorten their survival time.
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