Landmark risk prediction of residual life for breast cancer survival

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Statistics in Medicine

• Publication date

  2013-09-10

• Fields of study

  Medicine

• Identifiers
  DOI 10.1002/sim.5776PMID 23494768PMCID PMC3744612
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Landmark Prediction of Long-Term Survival Incorporating Short-Term Event Time Information

  2012cited by this paper
• Incorporating short‐term outcome information to predict long‐term survival with discrete markers

  2011cited by this paper
• On the C‐statistics for evaluating overall adequacy of risk prediction procedures with censored survival data

  2011cited by this paper
• Dynamic Prediction in Clinical Survival Analysis

  2011cited by this paper
• Competing Risks and Time‐Dependent Covariates

  2009cited by this paper
• Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data

  2008cited by this paper
• Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond

  2008cited by this paper
• Robust combination of multiple diagnostic tests for classifying censored event times.

  2007cited by this paper
• Triple-Negative Breast Cancer: Clinical Features and Patterns of Recurrence

  2007cited by this paper
• Model evaluation based on the sampling distribution of estimated absolute prediction error

  2007cited by this paper
• Dynamic Prediction by Landmarking in Event History Analysis

  2007influential reference
• Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models

  2007cited by this paper
• A multi‐state model for joint modelling of terminal and non‐terminal events with application to Whitehall II

  2007cited by this paper
• Maximum likelihood estimation in semiparametric regression models with censored data

  2007cited by this paper
• Integrating the predictiveness of a marker with its performance as a classifier.

  2007cited by this paper
• Estimation and Prediction in a Multi‐State Model for Breast Cancer

  2006cited by this paper
• Efficient Bayesian inference for Gaussian copula regression models

  2006cited by this paper
• A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers

  2006cited by this paper
• The limitations of risk factors as prognostic tools.

  2006cited by this paper
• Semiparametric Analysis of Survival Data with Left Truncation and Dependent Right Censoring

  2005cited by this paper
• The sensitivity and specificity of markers for event times.

  2005cited by this paper
• Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors

  2005cited by this paper
• Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker.

  2004cited by this paper
• Estimating subject-specific survival functions under the accelerated failure time model

  2003cited by this paper
• Prediction of the long‐term survival in breast cancer patients according to the present oncological status

  2002cited by this paper
• Meeting highlights: International Consensus Panel on the treatment of primary breast cancer.

  2002cited by this paper
• Severity of chronic graft-versus-host disease: association with treatment-related mortality and relapse.

  2002cited by this paper
• A gene-expression signature as a predictor of survival in breast cancer.

  2002cited by this paper
• Combining Several Screening Tests: Optimality of the Risk Score

  2002influential reference
• Semiparametric Mixed-Effects Models for Clustered Failure Time Data

  2002cited by this paper
• On semi-competing risks data

  2001cited by this paper
• A simple resampling method by perturbing the minimand

  2001cited by this paper
• Hierarchical likelihood approach for frailty models

  2001cited by this paper
• Nonparametric Estimation for the Three‐Stage Irreversible Illness–Death Model

  2000cited by this paper
• Estimating average regression effect under non-proportional hazards.

  2000cited by this paper
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker

  2000cited by this paper
• Regression in a bivariate copula model

  2000cited by this paper
• Efficient estimation in the bivariate normal copula model: normal margins are least favourable

  1997cited by this paper
• Bacterial pneumonia in persons infected with the human immunodeficiency virus. Pulmonary Complications of HIV Infection Study Group.

  1995cited by this paper
• Frailty models for survival data

  1995cited by this paper
• Meeting highlights: international consensus panel on the treatment of primary breast cancer.

  1995cited by this paper
• Inferences on the association parameter in copula models for bivariate survival data.

  1995cited by this paper
• Plotting summary predictions in multistate survival models: probabilities of relapse and death in remission for bone marrow transplantation patients.

  1993cited by this paper
• Advances in statistical methodology for diagnostic medicine in the 1980's.

  1991cited by this paper
• Receiver operating characteristic (ROC) methodology: the state of the art.

  1989cited by this paper
• A Markov model for analysing cancer markers and disease states in survival studies.

  1986cited by this paper
• Evaluation of diagnostic systems : methods from signal detection theory

  1982cited by this paper

• Application of Landmark Analysis and Piecewise Cox Regression to Identify Features Associated with Prognosis: A National Retrospective Cohort Study of New Zealand Women

  2025cites this paper
• Prediction of early-onset bipolar using electronic health records.

  2025cites this paper
• Machine Learning Models for the Prediction of Early-Onset Bipolar Using Electronic Health Records

  2024cites this paper
• Dynamic prediction of survival via Landmark method using the asthma prevention trial in young children

  2023cites this paper
• An efficient landmark model for prediction of suicide attempts in multiple clinical settings.

  2023cites this paper
• Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods

  2020cites this paper
• Measuring the temporal prognostic utility of a baseline risk score

  2020cites this paper
• Dynamic risk prediction for diabetes using biomarker change measurements

  2019influential citation
• Dynamic prediction of repeated events data based on landmarking model: application to colorectal liver metastases data

  2019cites this paper
• Package ‘ SurrogateOutcome ’ April 9 , 2019 Type Package

  2019cites this paper
• Assessing the value of a censored surrogate outcome

  2019cites this paper
• Dynamic Methods for the Prediction of Survival Outcomes using Longitudinal Biomarkers

  2018cites this paper
• Smoking at diagnosis significantly decreases 5‐year cancer‐specific survival in a population‐based cohort of 18 166 colon cancer patients

  2017cites this paper
• Validation of Prognostic Marker Tests: Statistical Lessons Learned From Regulatory Experience

  2016cites this paper
• Turning the headlights on novel cancer biomarkers: Inspection of mechanics underlying intratumor heterogeneity.

  2015cites this paper
• Dynamic prediction of pre-transplant survival in a multi-center study of pediatric acute liver failure

  2014cites this paper
• Dynamic predictions with time‐dependent covariates in survival analysis using joint modeling and landmarking

  2013influential citation