Prognostic significance of p53 mutations in non-small cell lung cancer: a meta-analysis of 829 cases from eight published studies.

Mutation of the p53 tumor suppressor gene is considered a possible marker of poor survival among patients with non-small cell lung cancer (NSCLC). This report presents the results of a meta-analysis of the available data addressing this issue. Using previously described methods, a protocol was developed for a meta-analysis examining the prognostic significance of p53 mutations in NSCLC. Two-year survival data derived from 829 patients in eight published studies were analyzed using a general variance-based method employing confidence intervals described by Greenland (Epidemiol. Rev. 9 (1986) 1-30). The outcome of interest was a summary relative risk (RRs) reflecting the risk of death at 2 years associated with p53 mutation positive versus p53 negative disease. Prior to calculation of a RRs, an analysis for homogeneity (Q) showed Q to equal 22.3. With 8 degrees of freedom, this yielded a P value corresponding to P<0.005. This indicated substantial heterogeneity across studies in terms of their estimate of effect. Although a RRs of 1.52 was found when all eight studies were combined (favoring a negative prognostic role for p53 mutation), the validity of this estimate is questionable since the existing heterogeneity indicates that factors other than p53 mutation account for the variability in RRs across studies. Sensitivity analyses suggested that selection bias might represent an important source of variability in that p53 mutations may differ in their effects on biological behavior of NSCL tumors. Other possible confounders include smoking history, race, geographic location of study and socio-economic status. The available data do not support a clear role for p53 mutation as a prognostic marker in NSCLC. It appears that multiple sources of bias may contribute to spurious association of p53 mutation status and survival. Future analyses must control for possible confounders in order to determine whether certain p53 mutations are truly associated with poor clinical outcome.