Survival and risk model for stage IB non-small cell lung cancer

Background: The aim of this work is to estimate the prognostic value of a set of clinical–pathological factors in patients resected for non-small cell lung cancer (NSCLC) and classified as stage IB, in order to create a prognostic model for establishing risk groups, and to validate that model. Metho...

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Veröffentlicht in:Lung cancer (Amsterdam, Netherlands) Netherlands), 2002-04, Vol.36 (1), p.43-48
Hauptverfasser: Padilla, J, Calvo, V, Peñalver, J.C, Zarza, A.Garcı́a, Pastor, J, Blasco, E, Parı́s, F
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container_issue 1
container_start_page 43
container_title Lung cancer (Amsterdam, Netherlands)
container_volume 36
creator Padilla, J
Calvo, V
Peñalver, J.C
Zarza, A.Garcı́a
Pastor, J
Blasco, E
Parı́s, F
description Background: The aim of this work is to estimate the prognostic value of a set of clinical–pathological factors in patients resected for non-small cell lung cancer (NSCLC) and classified as stage IB, in order to create a prognostic model for establishing risk groups, and to validate that model. Methods: Among 637 patients resected and classified as stage IB, we analyzed sex, age, symptoms, location, type of resection, cell type, histology, and tumor size. The Kaplan–Meier method was used to estimate the survival. The results were compared using the log-rank test. All the significant variables from this univariable method were then included in a multivariable method of estimation of the proportional risk for survival data developed by Cox, using the variables selected, a regression model was developed for accurately predicting survival. To validate the predictive capability of the regression model, we randomly divided our patients into training and test subsets, containing 322 and 315 cases, respectively. Results: The overall 5-year survival rate of the series was 60%. The cell type, the squamous or non-squamous and the tumor size showed a significant influence on survival in the univariable analysis, while, according to the Cox model, only the tumor size and the squamous or non-squamous type entered into regression. Hazard rates were calculated for each patient. The mean risk was 0.87±0.25 (range 30–1.94). The series was divided into three risk groups (low, intermediate, and high risk) according to the fitted hazard rates, using cut-off points (one standard deviation from the mean). The 5-year survival rates were 85, 59, and 44%, respectively. To validate the model, we repeated the analysis for training and test subsets. Only the tumor size had a significant influence on survival in the univariable analysis. Using the Cox model, also the tumor size entered into regression. The mean risk was 0.79±0.29 (range 0.09–2.12). Cut-off points were 0.50 and 1.08 for the low, intermediate, and high-risk groups. The 5-year survival rates were 83, 58, and 40%, respectively. We validated the regression model obtained in the training subset by demonstrating its capacity in identifying risk groups in the test subset. The 5-year survival rates were 83, 61, and 49.5% for the low, intermediate, and high-risk groups, respectively ( P=0.0104). Conclusions: Stage IB does not succeed in configuring a group of patients with a homogeneous prognosis, as there is a wide variability i
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Methods: Among 637 patients resected and classified as stage IB, we analyzed sex, age, symptoms, location, type of resection, cell type, histology, and tumor size. The Kaplan–Meier method was used to estimate the survival. The results were compared using the log-rank test. All the significant variables from this univariable method were then included in a multivariable method of estimation of the proportional risk for survival data developed by Cox, using the variables selected, a regression model was developed for accurately predicting survival. To validate the predictive capability of the regression model, we randomly divided our patients into training and test subsets, containing 322 and 315 cases, respectively. Results: The overall 5-year survival rate of the series was 60%. The cell type, the squamous or non-squamous and the tumor size showed a significant influence on survival in the univariable analysis, while, according to the Cox model, only the tumor size and the squamous or non-squamous type entered into regression. Hazard rates were calculated for each patient. The mean risk was 0.87±0.25 (range 30–1.94). The series was divided into three risk groups (low, intermediate, and high risk) according to the fitted hazard rates, using cut-off points (one standard deviation from the mean). The 5-year survival rates were 85, 59, and 44%, respectively. To validate the model, we repeated the analysis for training and test subsets. Only the tumor size had a significant influence on survival in the univariable analysis. Using the Cox model, also the tumor size entered into regression. The mean risk was 0.79±0.29 (range 0.09–2.12). Cut-off points were 0.50 and 1.08 for the low, intermediate, and high-risk groups. The 5-year survival rates were 83, 58, and 40%, respectively. We validated the regression model obtained in the training subset by demonstrating its capacity in identifying risk groups in the test subset. The 5-year survival rates were 83, 61, and 49.5% for the low, intermediate, and high-risk groups, respectively ( P=0.0104). Conclusions: Stage IB does not succeed in configuring a group of patients with a homogeneous prognosis, as there is a wide variability in a 5-year survival. The estimation of prognosis derived from a multivariable analysis can obviate the limitations of the actual staging system for NSCLC.</description><identifier>ISSN: 0169-5002</identifier><identifier>EISSN: 1872-8332</identifier><identifier>DOI: 10.1016/S0169-5002(01)00450-0</identifier><identifier>PMID: 11891032</identifier><identifier>CODEN: LUCAE5</identifier><language>eng</language><publisher>Shannon: Elsevier Ireland Ltd</publisher><subject>Adenocarcinoma - mortality ; Adenocarcinoma - pathology ; Adenocarcinoma - surgery ; Adult ; Aged ; Aged, 80 and over ; Biological and medical sciences ; Carcinoma, Large Cell - mortality ; Carcinoma, Large Cell - pathology ; Carcinoma, Large Cell - surgery ; Carcinoma, Non-Small-Cell Lung - mortality ; Carcinoma, Non-Small-Cell Lung - pathology ; Carcinoma, Non-Small-Cell Lung - surgery ; Carcinoma, Squamous Cell - mortality ; Carcinoma, Squamous Cell - pathology ; Carcinoma, Squamous Cell - surgery ; Female ; Humans ; Lung cancer ; Lung Neoplasms - mortality ; Lung Neoplasms - pathology ; Lung Neoplasms - surgery ; Male ; Medical sciences ; Middle Aged ; Models, Biological ; Neoplasm Staging ; Pneumology ; Risk Factors ; Risk model ; Stage IB ; Survival ; Survival Rate ; Tumors of the respiratory system and mediastinum</subject><ispartof>Lung cancer (Amsterdam, Netherlands), 2002-04, Vol.36 (1), p.43-48</ispartof><rights>2002 Elsevier Science Ireland Ltd</rights><rights>2002 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c391t-a4492349abb67b0770deba2f2bec3aaa8306019ccea25dba6a99cebba422543f3</citedby><cites>FETCH-LOGICAL-c391t-a4492349abb67b0770deba2f2bec3aaa8306019ccea25dba6a99cebba422543f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S0169-5002(01)00450-0$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=13584220$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11891032$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Padilla, J</creatorcontrib><creatorcontrib>Calvo, V</creatorcontrib><creatorcontrib>Peñalver, J.C</creatorcontrib><creatorcontrib>Zarza, A.Garcı́a</creatorcontrib><creatorcontrib>Pastor, J</creatorcontrib><creatorcontrib>Blasco, E</creatorcontrib><creatorcontrib>Parı́s, F</creatorcontrib><title>Survival and risk model for stage IB non-small cell lung cancer</title><title>Lung cancer (Amsterdam, Netherlands)</title><addtitle>Lung Cancer</addtitle><description>Background: The aim of this work is to estimate the prognostic value of a set of clinical–pathological factors in patients resected for non-small cell lung cancer (NSCLC) and classified as stage IB, in order to create a prognostic model for establishing risk groups, and to validate that model. Methods: Among 637 patients resected and classified as stage IB, we analyzed sex, age, symptoms, location, type of resection, cell type, histology, and tumor size. The Kaplan–Meier method was used to estimate the survival. The results were compared using the log-rank test. All the significant variables from this univariable method were then included in a multivariable method of estimation of the proportional risk for survival data developed by Cox, using the variables selected, a regression model was developed for accurately predicting survival. To validate the predictive capability of the regression model, we randomly divided our patients into training and test subsets, containing 322 and 315 cases, respectively. Results: The overall 5-year survival rate of the series was 60%. The cell type, the squamous or non-squamous and the tumor size showed a significant influence on survival in the univariable analysis, while, according to the Cox model, only the tumor size and the squamous or non-squamous type entered into regression. Hazard rates were calculated for each patient. The mean risk was 0.87±0.25 (range 30–1.94). The series was divided into three risk groups (low, intermediate, and high risk) according to the fitted hazard rates, using cut-off points (one standard deviation from the mean). The 5-year survival rates were 85, 59, and 44%, respectively. To validate the model, we repeated the analysis for training and test subsets. Only the tumor size had a significant influence on survival in the univariable analysis. Using the Cox model, also the tumor size entered into regression. The mean risk was 0.79±0.29 (range 0.09–2.12). Cut-off points were 0.50 and 1.08 for the low, intermediate, and high-risk groups. The 5-year survival rates were 83, 58, and 40%, respectively. We validated the regression model obtained in the training subset by demonstrating its capacity in identifying risk groups in the test subset. The 5-year survival rates were 83, 61, and 49.5% for the low, intermediate, and high-risk groups, respectively ( P=0.0104). Conclusions: Stage IB does not succeed in configuring a group of patients with a homogeneous prognosis, as there is a wide variability in a 5-year survival. The estimation of prognosis derived from a multivariable analysis can obviate the limitations of the actual staging system for NSCLC.</description><subject>Adenocarcinoma - mortality</subject><subject>Adenocarcinoma - pathology</subject><subject>Adenocarcinoma - surgery</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Biological and medical sciences</subject><subject>Carcinoma, Large Cell - mortality</subject><subject>Carcinoma, Large Cell - pathology</subject><subject>Carcinoma, Large Cell - surgery</subject><subject>Carcinoma, Non-Small-Cell Lung - mortality</subject><subject>Carcinoma, Non-Small-Cell Lung - pathology</subject><subject>Carcinoma, Non-Small-Cell Lung - surgery</subject><subject>Carcinoma, Squamous Cell - mortality</subject><subject>Carcinoma, Squamous Cell - pathology</subject><subject>Carcinoma, Squamous Cell - surgery</subject><subject>Female</subject><subject>Humans</subject><subject>Lung cancer</subject><subject>Lung Neoplasms - mortality</subject><subject>Lung Neoplasms - pathology</subject><subject>Lung Neoplasms - surgery</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>Neoplasm Staging</subject><subject>Pneumology</subject><subject>Risk Factors</subject><subject>Risk model</subject><subject>Stage IB</subject><subject>Survival</subject><subject>Survival Rate</subject><subject>Tumors of the respiratory system and mediastinum</subject><issn>0169-5002</issn><issn>1872-8332</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1PHDEMhqOKqmwpPwGUC1V7GHCSyc7ktKIraJGQOGw5R07Gg0LngyY7K_Xfk_0QHHuxL4_t1w9jZwIuBYj51SoXU2gA-Q3Ed4BSQwEf2EzUlSxqpeQRm70hx-xzSs8AohJgPrFjIWojQMkZW6ymuAkb7DgODY8h_eH92FDH2zHytMYn4nc_-DAOReqx67inXLppeOIeB0_xC_vYYpfo9NBP2OPtze_lr-L-4efd8vq-8MqIdYFlaaQqDTo3rxxUFTTkULbSkVeIWCuYgzDeE0rdOJyjMZ6cw1JKXapWnbCv-70vcfw7UVrbPqRtGBxonJKthBa6rnUG9R70cUwpUmtfYugx_rMC7Nac3ZmzWy0WhN2Zs5Dnzg8HJtdT8z51UJWBiwOAyWPXxvx_SO-c0nUOu1202HOUdWwCRZt8oOyqCZH82jZj-E-UV3xpiXU</recordid><startdate>20020401</startdate><enddate>20020401</enddate><creator>Padilla, J</creator><creator>Calvo, V</creator><creator>Peñalver, J.C</creator><creator>Zarza, A.Garcı́a</creator><creator>Pastor, J</creator><creator>Blasco, E</creator><creator>Parı́s, F</creator><general>Elsevier Ireland Ltd</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20020401</creationdate><title>Survival and risk model for stage IB non-small cell lung cancer</title><author>Padilla, J ; Calvo, V ; Peñalver, J.C ; Zarza, A.Garcı́a ; Pastor, J ; Blasco, E ; Parı́s, F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c391t-a4492349abb67b0770deba2f2bec3aaa8306019ccea25dba6a99cebba422543f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Adenocarcinoma - mortality</topic><topic>Adenocarcinoma - pathology</topic><topic>Adenocarcinoma - surgery</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Biological and medical sciences</topic><topic>Carcinoma, Large Cell - mortality</topic><topic>Carcinoma, Large Cell - pathology</topic><topic>Carcinoma, Large Cell - surgery</topic><topic>Carcinoma, Non-Small-Cell Lung - mortality</topic><topic>Carcinoma, Non-Small-Cell Lung - pathology</topic><topic>Carcinoma, Non-Small-Cell Lung - surgery</topic><topic>Carcinoma, Squamous Cell - mortality</topic><topic>Carcinoma, Squamous Cell - pathology</topic><topic>Carcinoma, Squamous Cell - surgery</topic><topic>Female</topic><topic>Humans</topic><topic>Lung cancer</topic><topic>Lung Neoplasms - mortality</topic><topic>Lung Neoplasms - pathology</topic><topic>Lung Neoplasms - surgery</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Models, Biological</topic><topic>Neoplasm Staging</topic><topic>Pneumology</topic><topic>Risk Factors</topic><topic>Risk model</topic><topic>Stage IB</topic><topic>Survival</topic><topic>Survival Rate</topic><topic>Tumors of the respiratory system and mediastinum</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Padilla, J</creatorcontrib><creatorcontrib>Calvo, V</creatorcontrib><creatorcontrib>Peñalver, J.C</creatorcontrib><creatorcontrib>Zarza, A.Garcı́a</creatorcontrib><creatorcontrib>Pastor, J</creatorcontrib><creatorcontrib>Blasco, E</creatorcontrib><creatorcontrib>Parı́s, F</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Lung cancer (Amsterdam, Netherlands)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Padilla, J</au><au>Calvo, V</au><au>Peñalver, J.C</au><au>Zarza, A.Garcı́a</au><au>Pastor, J</au><au>Blasco, E</au><au>Parı́s, F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Survival and risk model for stage IB non-small cell lung cancer</atitle><jtitle>Lung cancer (Amsterdam, Netherlands)</jtitle><addtitle>Lung Cancer</addtitle><date>2002-04-01</date><risdate>2002</risdate><volume>36</volume><issue>1</issue><spage>43</spage><epage>48</epage><pages>43-48</pages><issn>0169-5002</issn><eissn>1872-8332</eissn><coden>LUCAE5</coden><abstract>Background: The aim of this work is to estimate the prognostic value of a set of clinical–pathological factors in patients resected for non-small cell lung cancer (NSCLC) and classified as stage IB, in order to create a prognostic model for establishing risk groups, and to validate that model. Methods: Among 637 patients resected and classified as stage IB, we analyzed sex, age, symptoms, location, type of resection, cell type, histology, and tumor size. The Kaplan–Meier method was used to estimate the survival. The results were compared using the log-rank test. All the significant variables from this univariable method were then included in a multivariable method of estimation of the proportional risk for survival data developed by Cox, using the variables selected, a regression model was developed for accurately predicting survival. To validate the predictive capability of the regression model, we randomly divided our patients into training and test subsets, containing 322 and 315 cases, respectively. Results: The overall 5-year survival rate of the series was 60%. The cell type, the squamous or non-squamous and the tumor size showed a significant influence on survival in the univariable analysis, while, according to the Cox model, only the tumor size and the squamous or non-squamous type entered into regression. Hazard rates were calculated for each patient. The mean risk was 0.87±0.25 (range 30–1.94). The series was divided into three risk groups (low, intermediate, and high risk) according to the fitted hazard rates, using cut-off points (one standard deviation from the mean). The 5-year survival rates were 85, 59, and 44%, respectively. To validate the model, we repeated the analysis for training and test subsets. Only the tumor size had a significant influence on survival in the univariable analysis. Using the Cox model, also the tumor size entered into regression. The mean risk was 0.79±0.29 (range 0.09–2.12). Cut-off points were 0.50 and 1.08 for the low, intermediate, and high-risk groups. The 5-year survival rates were 83, 58, and 40%, respectively. We validated the regression model obtained in the training subset by demonstrating its capacity in identifying risk groups in the test subset. The 5-year survival rates were 83, 61, and 49.5% for the low, intermediate, and high-risk groups, respectively ( P=0.0104). Conclusions: Stage IB does not succeed in configuring a group of patients with a homogeneous prognosis, as there is a wide variability in a 5-year survival. The estimation of prognosis derived from a multivariable analysis can obviate the limitations of the actual staging system for NSCLC.</abstract><cop>Shannon</cop><pub>Elsevier Ireland Ltd</pub><pmid>11891032</pmid><doi>10.1016/S0169-5002(01)00450-0</doi><tpages>6</tpages></addata></record>
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subjects Adenocarcinoma - mortality
Adenocarcinoma - pathology
Adenocarcinoma - surgery
Adult
Aged
Aged, 80 and over
Biological and medical sciences
Carcinoma, Large Cell - mortality
Carcinoma, Large Cell - pathology
Carcinoma, Large Cell - surgery
Carcinoma, Non-Small-Cell Lung - mortality
Carcinoma, Non-Small-Cell Lung - pathology
Carcinoma, Non-Small-Cell Lung - surgery
Carcinoma, Squamous Cell - mortality
Carcinoma, Squamous Cell - pathology
Carcinoma, Squamous Cell - surgery
Female
Humans
Lung cancer
Lung Neoplasms - mortality
Lung Neoplasms - pathology
Lung Neoplasms - surgery
Male
Medical sciences
Middle Aged
Models, Biological
Neoplasm Staging
Pneumology
Risk Factors
Risk model
Stage IB
Survival
Survival Rate
Tumors of the respiratory system and mediastinum
title Survival and risk model for stage IB non-small cell lung cancer
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