Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy

BackgroundIn 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...

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Main Authors: Aijun Zhao, Dongsheng Tu, Ye He, Liu Liu, Bin Wu, Yixing Ren
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Genetics
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Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2024.1497254/full
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author Aijun Zhao
Dongsheng Tu
Ye He
Liu Liu
Bin Wu
Yixing Ren
author_facet Aijun Zhao
Dongsheng Tu
Ye He
Liu Liu
Bin Wu
Yixing Ren
author_sort Aijun Zhao
collection DOAJ
description BackgroundIn 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.MethodsOf 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.ResultsThree 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.ConclusionIn 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.
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spelling doaj-art-ccf4dde1c5dd448bb8b5ade95491726c2025-08-20T01:58:11ZengFrontiers Media S.A.Frontiers in Genetics1664-80212024-12-011510.3389/fgene.2024.14972541497254Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapyAijun Zhao0Dongsheng Tu1Ye He2Liu Liu3Bin Wu4Yixing Ren5School of Mathematical Science and Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, ChinaDepartment of Public Health Sciences, Canadian Cancer Trials Group, Queen’s University, Kingston, ON, CanadaVisual Computing and Virtual Reality Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, ChinaSchool of Mathematical Science and Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, ChinaCollege of Management Science, Chengdu University of Technology, Chengdu, ChinaDepartment of General Surgery, Institute of Hepato-Biliary-Pancreas and Intestinal Disease, Affiliated Hospital of North Sichuan Medical College, Nanchong, ChinaBackgroundIn 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.MethodsOf 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.ResultsThree 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.ConclusionIn 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.https://www.frontiersin.org/articles/10.3389/fgene.2024.1497254/fullpancreatic cancerCOX proportional hazards regression modelscore testrisk-adjusted control chartpredictive biomarkers
spellingShingle Aijun Zhao
Dongsheng Tu
Ye He
Liu Liu
Bin Wu
Yixing Ren
Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
Frontiers in Genetics
pancreatic cancer
COX proportional hazards regression model
score test
risk-adjusted control chart
predictive biomarkers
title Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
title_full Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
title_fullStr Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
title_full_unstemmed Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
title_short Identification and validation the predictive biomarkers based on risk-adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
title_sort identification and validation the predictive biomarkers based on risk adjusted control chart in gemcitabine with or without erlotinib for pancreatic cancer therapy
topic pancreatic cancer
COX proportional hazards regression model
score test
risk-adjusted control chart
predictive biomarkers
url https://www.frontiersin.org/articles/10.3389/fgene.2024.1497254/full
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