ReviewPrecision clinical medicine2019
Quantile regression for survival data in modern cancer research: expanding statistical tools for precision medicine.
Review in Precision clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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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
14 citing papers in PubMed.
- Joint Associations of Outdoor Nitrogen Dioxide and Temperature with Incident Adult-Onset Asthma in the United States.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Sinkhorn Distributionally Robust Conditional Quantile Prediction with Fixed Design.Entropy (Basel, Switzerland) · 2025Article
- Response: Commentary: Quantile treatment effect of zinc lozenges on common cold duration: a novel approach to analyze the effect of treatment on illness duration.Frontiers in pharmacology · 2024Article
- Quantile forward regression for high-dimensional survival data.Lifetime data analysis · 2023Article
- High-Dimensional Survival Analysis: Methods and Applications.Annual review of statistics and its application · 2023Article
- Adherence to the Atrial Fibrillation Better Care (ABC) pathway and the risk of major outcomes in patients with atrial fibrillation: A post-hoc analysis from the prospective GLORIA-AF Registry.EClinicalMedicine · 2023Article
- Inference for High-Dimensional Censored Quantile Regression.Journal of the American Statistical Association · 2023Article
- Article
- Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression.Breast cancer : basic and clinical research · 2022Article
- Quantile Treatment Effect of Zinc Lozenges on Common Cold Duration: A Novel Approach to Analyze the Effect of Treatment on Illness Duration.Frontiers in pharmacology · 2022Review
- Carrageenan nasal spray may double the rate of recovery from coronavirus and influenza virus infections: Re-analysis of randomized trial data.Pharmacology research & perspectives · 2021Article
- Competing interplay between systemic and periodontal inflammation: obesity overrides the impact of oral periphery.Clinical oral investigations · 2021Article
- Vitamin C May Increase the Recovery Rate of Outpatient Cases of SARS-CoV-2 Infection by 70%: Reanalysis of the COVID A to Z Randomized Clinical Trial.Frontiers in immunology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Quantile regression links the whole distribution of an outcome to the covariates of interest and has become an important alternative to commonly used regression models. However, the presence of censored data such as survival time, often the main endpoint in cancer studies, has hampered the use of quantile regression techniques because of the incompleteness of data. With the advent of the precision medicine era and availability of high throughput data, quantile regression with high-dimensional predictors has attracted much attention and provided added insight compared to traditional regression approaches. This paper provides a practical guide for using quantile regression for right censored outcome data with covariates of low- or high-dimensionality. We frame our discussion using a dataset from the Boston Lung Cancer Survivor Cohort, a hospital-based prospective cohort study, with the goals of broadening the scope of cancer research, maximizing the utility of collected data, and offering useful statistical alternatives. We use quantile regression to identify clinical and molecular predictors, for example CpG methylation sites, associated with high-risk lung cancer patients, for example those with short survival.
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