Gray’s Time-Varying Coefficients Model for Posttransplant Survival of Pediatric Liver Transplant Recipients with a Diagnosis of Cancer
Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate...
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| Veröffentlicht in: | Computational and mathematical methods in medicine 2013-01, Vol.2013 (2013), p.1-13 |
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| creator | Ren, Yi Chang, Chung-Chou H. Zenarosa, Gabriel L. Tomko, Heather E. Donnell, Drew Michael S. Kang, Hyung-joo Roberts, Mark S. Bryce, Cindy L. |
| description | Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray’s piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable (P |
| doi_str_mv | 10.1155/2013/719389 |
| format | Article |
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Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray’s piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable (P<0.15) and multivariable models with forward selection (P<0.05) for the Cox PH and Gray PC-TVC models, which coincide. While the Cox PH model provided reasonable average results in estimating covariate effects on posttransplant survival, the Gray model using piecewise constant penalized splines showed more details of how those effects change over time.</description><identifier>ISSN: 1748-670X</identifier><identifier>EISSN: 1748-6718</identifier><identifier>DOI: 10.1155/2013/719389</identifier><identifier>PMID: 23762197</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Puplishing Corporation</publisher><subject>Child ; Child, Preschool ; Computational Biology ; End Stage Liver Disease - mortality ; End Stage Liver Disease - surgery ; Female ; Histocompatibility Testing ; Humans ; Infant ; Kaplan-Meier Estimate ; Liver Neoplasms - mortality ; Liver Neoplasms - surgery ; Liver Transplantation - mortality ; Male ; Models, Statistical ; Multivariate Analysis ; Proportional Hazards Models ; Survival Analysis ; Tissue and Organ Procurement - statistics & numerical data ; Tissue Donors ; United States - epidemiology</subject><ispartof>Computational and mathematical methods in medicine, 2013-01, Vol.2013 (2013), p.1-13</ispartof><rights>Copyright © 2013 Yi Ren et al.</rights><rights>Copyright © 2013 Yi Ren et al. 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-e73c1f39e02e86024634832206661f9e3ba53eb617f41be13652f1522b22783c3</citedby><cites>FETCH-LOGICAL-c438t-e73c1f39e02e86024634832206661f9e3ba53eb617f41be13652f1522b22783c3</cites><orcidid>0000-0001-8077-6391 ; 0000-0003-1096-3559 ; 0000-0001-6765-7603</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3665233/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3665233/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23762197$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Chang, Shu-hui</contributor><creatorcontrib>Ren, Yi</creatorcontrib><creatorcontrib>Chang, Chung-Chou H.</creatorcontrib><creatorcontrib>Zenarosa, Gabriel L.</creatorcontrib><creatorcontrib>Tomko, Heather E.</creatorcontrib><creatorcontrib>Donnell, Drew Michael S.</creatorcontrib><creatorcontrib>Kang, Hyung-joo</creatorcontrib><creatorcontrib>Roberts, Mark S.</creatorcontrib><creatorcontrib>Bryce, Cindy L.</creatorcontrib><title>Gray’s Time-Varying Coefficients Model for Posttransplant Survival of Pediatric Liver Transplant Recipients with a Diagnosis of Cancer</title><title>Computational and mathematical methods in medicine</title><addtitle>Comput Math Methods Med</addtitle><description>Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray’s piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable (P<0.15) and multivariable models with forward selection (P<0.05) for the Cox PH and Gray PC-TVC models, which coincide. While the Cox PH model provided reasonable average results in estimating covariate effects on posttransplant survival, the Gray model using piecewise constant penalized splines showed more details of how those effects change over time.</description><subject>Child</subject><subject>Child, Preschool</subject><subject>Computational Biology</subject><subject>End Stage Liver Disease - mortality</subject><subject>End Stage Liver Disease - surgery</subject><subject>Female</subject><subject>Histocompatibility Testing</subject><subject>Humans</subject><subject>Infant</subject><subject>Kaplan-Meier Estimate</subject><subject>Liver Neoplasms - mortality</subject><subject>Liver Neoplasms - surgery</subject><subject>Liver Transplantation - mortality</subject><subject>Male</subject><subject>Models, Statistical</subject><subject>Multivariate Analysis</subject><subject>Proportional Hazards Models</subject><subject>Survival Analysis</subject><subject>Tissue and Organ Procurement - statistics & numerical data</subject><subject>Tissue Donors</subject><subject>United States - epidemiology</subject><issn>1748-670X</issn><issn>1748-6718</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><recordid>eNqFkc9uEzEQhy0Eon_gxBnkI6Ja6rF37d0LEgqlIAVRQUDcLK8zTow262BvUvXGsa_Q1-uT4GhLgBOnsTSfv5nRj5AnwF4CVNUpZyBOFTSibu6RQ1BlXUgF9f39m307IEcpfWesAlXBQ3LAhZIcGnVIrs-jubr9eZPozK-w-Grile8XdBLQOW899kOiH8IcO-pCpBchDUM0fVp3ph_o503c-q3paHD0AufeDNFbOvVbjHT2B_uE1q9H1aUfltTQN94s-pB82v2cmN5ifEQeONMlfHxXj8mXt2ezybti-vH8_eT1tLClqIcClbDgRIOMYy0ZL6Uoa8E5k1KCa1C0phLYSlCuhBZByIo7qDhvOVe1sOKYvBq96027wrnNa0XT6XX0q3y7Dsbrfzu9X-pF2Gohs0qILHh-J4jhxwbToFc-WezyqRg2SeeRqlaqkSyjJyNqY0gpotuPAaZ32elddnrMLtPP_t5sz_4OKwMvRmDp-7m59P-xPR1hzAg6s4fLRoAE8Qte0q23</recordid><startdate>20130101</startdate><enddate>20130101</enddate><creator>Ren, Yi</creator><creator>Chang, Chung-Chou H.</creator><creator>Zenarosa, Gabriel L.</creator><creator>Tomko, Heather E.</creator><creator>Donnell, Drew Michael S.</creator><creator>Kang, Hyung-joo</creator><creator>Roberts, Mark S.</creator><creator>Bryce, Cindy L.</creator><general>Hindawi Puplishing Corporation</general><general>Hindawi Publishing Corporation</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</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><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8077-6391</orcidid><orcidid>https://orcid.org/0000-0003-1096-3559</orcidid><orcidid>https://orcid.org/0000-0001-6765-7603</orcidid></search><sort><creationdate>20130101</creationdate><title>Gray’s Time-Varying Coefficients Model for Posttransplant Survival of Pediatric Liver Transplant Recipients with a Diagnosis of Cancer</title><author>Ren, Yi ; Chang, Chung-Chou H. ; Zenarosa, Gabriel L. ; Tomko, Heather E. ; Donnell, Drew Michael S. ; Kang, Hyung-joo ; Roberts, Mark S. ; Bryce, Cindy L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-e73c1f39e02e86024634832206661f9e3ba53eb617f41be13652f1522b22783c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Child</topic><topic>Child, Preschool</topic><topic>Computational Biology</topic><topic>End Stage Liver Disease - mortality</topic><topic>End Stage Liver Disease - surgery</topic><topic>Female</topic><topic>Histocompatibility Testing</topic><topic>Humans</topic><topic>Infant</topic><topic>Kaplan-Meier Estimate</topic><topic>Liver Neoplasms - mortality</topic><topic>Liver Neoplasms - surgery</topic><topic>Liver Transplantation - mortality</topic><topic>Male</topic><topic>Models, Statistical</topic><topic>Multivariate Analysis</topic><topic>Proportional Hazards Models</topic><topic>Survival Analysis</topic><topic>Tissue and Organ Procurement - statistics & numerical data</topic><topic>Tissue Donors</topic><topic>United States - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ren, Yi</creatorcontrib><creatorcontrib>Chang, Chung-Chou H.</creatorcontrib><creatorcontrib>Zenarosa, Gabriel L.</creatorcontrib><creatorcontrib>Tomko, Heather E.</creatorcontrib><creatorcontrib>Donnell, Drew Michael S.</creatorcontrib><creatorcontrib>Kang, Hyung-joo</creatorcontrib><creatorcontrib>Roberts, Mark S.</creatorcontrib><creatorcontrib>Bryce, Cindy L.</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational and mathematical methods in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ren, Yi</au><au>Chang, Chung-Chou H.</au><au>Zenarosa, Gabriel L.</au><au>Tomko, Heather E.</au><au>Donnell, Drew Michael S.</au><au>Kang, Hyung-joo</au><au>Roberts, Mark S.</au><au>Bryce, Cindy L.</au><au>Chang, Shu-hui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gray’s Time-Varying Coefficients Model for Posttransplant Survival of Pediatric Liver Transplant Recipients with a Diagnosis of Cancer</atitle><jtitle>Computational and mathematical methods in medicine</jtitle><addtitle>Comput Math Methods Med</addtitle><date>2013-01-01</date><risdate>2013</risdate><volume>2013</volume><issue>2013</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>1748-670X</issn><eissn>1748-6718</eissn><abstract>Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray’s piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable (P<0.15) and multivariable models with forward selection (P<0.05) for the Cox PH and Gray PC-TVC models, which coincide. While the Cox PH model provided reasonable average results in estimating covariate effects on posttransplant survival, the Gray model using piecewise constant penalized splines showed more details of how those effects change over time.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Puplishing Corporation</pub><pmid>23762197</pmid><doi>10.1155/2013/719389</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-8077-6391</orcidid><orcidid>https://orcid.org/0000-0003-1096-3559</orcidid><orcidid>https://orcid.org/0000-0001-6765-7603</orcidid><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Wiley Online Library Open Access; PubMed Central; Alma/SFX Local Collection |
| subjects | Child Child, Preschool Computational Biology End Stage Liver Disease - mortality End Stage Liver Disease - surgery Female Histocompatibility Testing Humans Infant Kaplan-Meier Estimate Liver Neoplasms - mortality Liver Neoplasms - surgery Liver Transplantation - mortality Male Models, Statistical Multivariate Analysis Proportional Hazards Models Survival Analysis Tissue and Organ Procurement - statistics & numerical data Tissue Donors United States - epidemiology |
| title | Gray’s Time-Varying Coefficients Model for Posttransplant Survival of Pediatric Liver Transplant Recipients with a Diagnosis of Cancer |
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