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CPH has been widely used to identify prognostic markers of the transcriptome. However, the comprehensive investigation on PH assumption in transcriptomic data has lacked.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The whole transcriptomic data of the 9,056 patients from 32 cohorts of The Cancer Genome Atlas and the 3 lung cancer cohorts from Gene Expression Omnibus were collected to construct CPH model for each gene separately for fitting the overall survival. An average of 8.5% gene CPH models violated the PH assumption in TCGA pan-cancer cohorts. In the gene interaction networks, both hub and non-hub genes in CPH models were likely to have non-proportional hazards. Violations of PH assumption for the same gene models were not consistent in 5 non-small cell lung cancer datasets (all kappa coefficients\u00a0&lt;\u00a00.2), indicating that the non-proportionality of gene CPH models depended on the datasets. Furthermore, the introduction of log(t) or sqrt(t) time-functions into CPH improved the performance of gene models on overall survival fitting in most tumors. The time-dependent CPH changed the significance of log hazard ratio of the 31.9% gene variables.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our analysis resulted that non-proportional hazards should not be ignored in transcriptomic data. Introducing time interaction term ameliorated performance and interpretability of non-proportional hazards of transcriptome data in CPH.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1016\/j.csbj.2022.01.004","type":"journal-article","created":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T11:49:34Z","timestamp":1641556174000},"page":"496-507","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":24,"title":["Violations of proportional hazard assumption in Cox regression model of transcriptomic data in TCGA pan-cancer cohorts"],"prefix":"10.34133","volume":"20","author":[{"given":"Zihang","family":"Zeng","sequence":"first","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanping","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiali","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoxing","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuji","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China"},{"name":"Tumor Precision Diagnosis and Treatment Technology and Translational Medicine, Hubei Engineering Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Conghua","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","unstructured":"R. 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