Cargando…

The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates

OBJECTIVE: To examine the direct and indirect impact of comorbidity on the survival. DESIGN: A historical cohort study. SETTING: Denmark. PARTICIPANTS: All patients with non-small cell lung cancer who were registered in the Danish Lung Cancer Registry in 2010. MAIN OUTCOME MEASURES: The influence of...

Descripción completa

Detalles Bibliográficos
Autores principales:	Iachina, Maria, Green, Anders, Jakobsen, Erik
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BMJ Publishing Group 2014
Materias:	Research Methods
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927932/ https://www.ncbi.nlm.nih.gov/pubmed/24523421 http://dx.doi.org/10.1136/bmjopen-2013-003846

Ejemplares similares

Indirect genomic effects on survival from gene expression data
por: Ferkingstad, Egil, et al.
Publicado: (2008)

Transfer between hospitals as a predictor of delay in diagnosis and treatment of patients with Non-Small Cell Lung Cancer – a register based cohort-study
por: Iachina, Maria, et al.
Publicado: (2017)

A Bayesian Approach Towards Missing Covariate Data in Multilevel Latent Regression Models
por: Aßmann, Christian, et al.
Publicado: (2022)

Covariation Is a Poor Measure of Molecular Coevolution
por: Talavera, David, et al.
Publicado: (2015)

COCOA: coordinate covariation analysis of epigenetic heterogeneity
por: Lawson, John T., et al.
Publicado: (2020)

Decomposing heritability and genetic covariance by direct and indirect effect paths
por: Song, Jie, et al.
Publicado: (2023)

Selecting Optimal Subgroups for Treatment Using Many Covariates
por: VanderWeele, Tyler J., et al.
Publicado: (2019)

Survival Differences by Comorbidity Burden among Patients with Stage I/II Non-Small-Cell Lung Cancer after Thoracoscopic Resection
por: Wheeler, Meghann, et al.
Publicado: (2023)

Survival of patients with small cell lung cancer undergoing lung resection in England, 1998–2009
por: Lüchtenborg, Margreet, et al.
Publicado: (2014)

Evaluating Additive Interaction Using Survival Percentiles
por: Bellavia, Andrea, et al.
Publicado: (2016)

Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations
por: Hartwig, Fernando Pires, et al.
Publicado: (2021)

Survival models with preclustered gene groups as covariates
por: Kammers, Kai, et al.
Publicado: (2011)

Covariate-adjusted measures of discrimination for survival data
por: White, Ian R., et al.
Publicado: (2014)

Logistic regression with missing values in the covariates
por: Vach, Werner
Publicado: (1994)

Missing covariates in competing risks analysis
por: Bartlett, Jonathan W., et al.
Publicado: (2016)

The ‘dnet’ approach promotes emerging research on cancer patient survival
por: Fang, Hai, et al.
Publicado: (2014)

Marginal measures and causal effects using the relative survival framework
por: Syriopoulou, Elisavet, et al.
Publicado: (2020)

Direct and Indirect Effects of Androgens on Survival of Hematopoietic Progenitor Cells In Vitro
por: Kim, Seong-Woo, et al.
Publicado: (2005)

Diagnosing and Handling Common Violations of Missing at Random
por: Ji, Feng, et al.
Publicado: (2023)

Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan
por: Elgoraish, Amanda, et al.
Publicado: (2022)

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach
por: Barbieri, Sebastiano, et al.
Publicado: (2021)

Survival Bias in Mendelian Randomization Studies: A Threat to Causal Inference
por: Smit, Roelof A. J., et al.
Publicado: (2019)

Mismeasured Covariate in the Long-Term Survival of Colorectal Cancer
por: Azizmohammad Looha, Mehdi, et al.
Publicado: (2019)

Effects of Demographic and Socio-Economic Factors on Investigation Time of Lung Cancer Patients in Denmark: A Retrospective Cohort Study
por: Iachina, Maria, et al.
Publicado: (2023)

MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules
por: Martini, Paolo, et al.
Publicado: (2019)

ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions
por: Rashid, Naim U, et al.
Publicado: (2011)

A two-step estimator for multilevel latent class analysis with covariates
por: Di Mari, Roberto, et al.
Publicado: (2023)

Imputing missing covariate values for the Cox model
por: White, Ian R, et al.
Publicado: (2009)

Comparison of Methods for Handling Missing Covariate Data
por: Johansson, Åsa M., et al.
Publicado: (2013)

Later is not necessarily better: limitations of survival analysis in studies of long-term drug treatment of psychiatric conditions
por: Moncrieff, Joanna, et al.
Publicado: (2022)

Characteristics and overall survival of patients with early‐stage non‐small cell lung cancer: A cohort study in Denmark
por: Ehrenstein, Vera, et al.
Publicado: (2022)

Disease mapping of early- and late-stage cancer to monitor inequalities in early detection: a study of cutaneous malignant melanoma
por: Strömberg, Ulf, et al.
Publicado: (2020)

Importance of rare gene copy number alterations for personalized tumor characterization and survival analysis
por: Seifert, Michael, et al.
Publicado: (2016)

I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms
por: Wong, Kin Yau, et al.
Publicado: (2019)

Associating somatic mutations to clinical outcomes: a pan-cancer study of survival time
por: Little, Paul, et al.
Publicado: (2019)

Impact of Adjuvant Therapy on Survival in Surgically Resected Limited-Stage Small Cell Lung Cancer
por: Li, Di, et al.
Publicado: (2021)

Clinicopathological variables influencing overall survival, recurrence and post-recurrence survival in resected stage I non-small-cell lung cancer
por: Wang, Chengdi, et al.
Publicado: (2020)

Strategies for Handling Missing Data in Electronic Health Record Derived Data
por: Wells, Brian J., et al.
Publicado: (2013)

Accounting for missing data in statistical analyses: multiple imputation is not always the answer
por: Hughes, Rachael A, et al.
Publicado: (2019)

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content
por: Kling, Teresia, et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_66v1vr6oug4e7rj8o8d83dupfq