ArticleLifetime data analysis2017
Penalized variable selection in competing risks regression.
Article in Lifetime data analysis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed.
- An evaluation of variable selection methods in competing risks with one rare event: a simulation study.BMC medical research methodology · 2026Article
- Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704.Blood advances · 2025Observational
- Biosensors, Artificial Intelligence Biosensors, False Results and Novel Future Perspectives.Diagnostics (Basel, Switzerland) · 2025Review
- Development and validation of PRE-FRA (PREdiction of FRAilty risk in community older adults) frailty prediction model.Frontiers in public health · 2025Article
- Tutorial on survival modeling with applications to omics data.Bioinformatics (Oxford, England) · 2024Article
- The analysis of multiple outcomes, multiple variables and variables selection in hematopoietic cell transplantation studies.Best practice & research. Clinical haematology · 2023Review
- High-dimensional feature selection in competing risks modeling: A stable approach using a split-and-merge ensemble algorithm.Biometrical journal. Biometrische Zeitschrift · 2023Article
- Gene Screening for Prognosis of Non-Muscle-Invasive Bladder Carcinoma under Competing Risks Endpoints.Cancers · 2023Article
- Early inflammatory markers as prognostic indicators following allogeneic stem cell transplantation.Frontiers in immunology · 2023Article
- Posttreatment FDG-PET/CT Hopkins criteria predict locoregional recurrence after definitive radiotherapy for oropharyngeal squamous cell carcinoma.Head & neck · 2022Article
- Fast Lasso-type safe screening for Fine-Gray competing risks model with ultrahigh dimensional covariates.Statistics in medicine · 2022Article
- Predictive Model to Guide Brain Magnetic Resonance Imaging Surveillance in Patients With Metastatic Lung Cancer: Impact on Real-World Outcomes.JCO precision oncology · 2022Article
- Article
- Development of a 5-year risk prediction model for type 2 diabetes in individuals with incident HbA1c-defined pre-diabetes in Denmark.BMJ open diabetes research & care · 2022Article
- Severe cytokine release syndrome is associated with hematologic toxicity following CD19 CAR T-cell therapy.Blood advances · 2022Article
- On correlation rank screening for ultra-high dimensional competing risks data.Journal of applied statistics · 2022Article
- Risk factor of pneumonitis on dose-volume relationship for chemoradiotherapy with durvalumab: Multi-institutional research in Japan.Clinical and translational radiation oncology · 2021Article
- Risk Factor Identification in Heterogeneous Disease Progression with L1-Regularized Multi-state Models.Journal of healthcare informatics research · 2021Article
- Scalable Algorithms for Large Competing Risks Data.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2021Article
- Regularized Weighted Nonparametric Likelihood Approach for High-Dimension Sparse Subdistribution Hazards Model for Competing Risk Data.Computational and mathematical methods in medicine · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Penalized variable selection methods have been extensively studied for standard time-to-event data. Such methods cannot be directly applied when subjects are at risk of multiple mutually exclusive events, known as competing risks. The proportional subdistribution hazard (PSH) model proposed by Fine and Gray (J Am Stat Assoc 94:496-509, 1999) has become a popular semi-parametric model for time-to-event data with competing risks. It allows for direct assessment of covariate effects on the cumulative incidence function. In this paper, we propose a general penalized variable selection strategy that simultaneously handles variable selection and parameter estimation in the PSH model. We rigorously establish the asymptotic properties of the proposed penalized estimators and modify the coordinate descent algorithm for implementation. Simulation studies are conducted to demonstrate the good performance of the proposed method. Data from deceased donor kidney transplants from the United Network of Organ Sharing illustrate the utility of the proposed method.
Indexed as
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27016934What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.