Abstract
BACKGROUND: In a randomized clinical controlled trial (PA.3) conducted by the Canadian Cancer Trials Group, the effects of gemcitabine combined with the targeted drug erlotinib (GEM-E) versus gemcitabine alone (GEM) on patients with unresectable, locally advanced, or metastatic pancreatic cancer were studied. This trial statistically demonstrated that the GEM-E combination therapy moderately improves overall survival (OS) of patients. However, real-world analysis suggested that GEM-E for pancreatic cancer was not more effective than GEM. The heterogeneity in outcomes or treatment effect exist. Thus, we tried to find predictive biomarkers to identifying the heterogeneous patients. METHODS: Of the 569 eligible patients, 480 patients had plasma samples. Univariate and multivariate Cox proportional hazards model were used to identify baseline characteristics related to OS, and a risk adjusted Exponentially Weighted Moving Average (EWMA) control chart based on a weighted score test from the Cox model was constructed to monitor patients' survival risk. Maximally selected rank statistics were constructed to identifying the predictive biomarkers, in addition, a risk adjusted control chart based on a weighted score test from the Cox model was constructed to validating the predictive biomarkers, discover the patients who sensitive to the GEM-E or GEM. RESULTS: Three baseline characteristics (ECOG performance status, extent of disease, and pain intensity) were identified related to prognosis. A risk-adjusted EWMA control chart was constructed and showed that GEM-E did improve OS in a few patients. Three biomarkers (BMP2, CXCL6, and HER2) were identified as predictive biomarkers based on maximum selected rank test, and using the risk-adjusted EWMA control chart to validate the reality and discover some patients who are sensitive to the GEM-E therapy. CONCLUSION: In reality, GEM-E has not shown a significant advantage over GEM in the treatment of pancreatic cancer. However, we discovered some patients who are sensitive to the GEM-E therapy based on the predictive biomarkers, which suggest that the predictive biomarkers provide ideas for personalized medicine in pancreatic cancer.