ArticleThe international journal of biostatistics2014
An approach to evaluating and comparing biomarkers for patient treatment selection.
Article in The international journal of biostatistics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 55 citations in OpenAlex.
- Sample size methods for evaluation of predictive biomarkers.Statistics in medicine · 2022Trial
- Evaluating biomarkers for treatment selection from reproducibility studies.Biostatistics (Oxford, England) · 2022Trial
- A comparison of approaches for combining predictive markers for personalised treatment recommendations.Trials · 2021Trial
- Adjusting for covariates in evaluating markers for selecting treatment, with application to guiding chemotherapy for treating estrogen-receptor-positive, node-positive breast cancer.Contemporary clinical trials · 2017Trial
- Trial
- Treatment-aware deep learning enables counterfactual prediction of individual benefit from PARP inhibitors in ovarian cancer.NPJ digital medicine · 2026Article
- Nonparametric Biomarker Based Treatment Selection With Reproducibility Data.Statistics in medicine · 2024Article
- Standardized statistical framework for comparison of biomarkers: Techniques from ADNI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Physicians' Hierarchy of Tumor Biomarkers for Optimizing Chemotherapy in Breast Cancer Care.The oncologist · 2024Article
- Finding the (biomarker-defined) subgroup of patients who benefit from a novel therapy: No time for a game of hide and seek.Clinical trials (London, England) · 2023Article
- A scoping review of statistical methods in studies of biomarker-related treatment heterogeneity for breast cancer.BMC medical research methodology · 2023Article
- BioPETsurv: Methodology and open source software to evaluate biomarkers for prognostic enrichment of time-to-event clinical trials.PloS one · 2020Article
- Constructing treatment selection rules based on an estimated treatment effect function: different approaches to take stochastic uncertainty into account have a substantial effect on performance.BMC medical research methodology · 2019Article
- Article
- Auxiliary variable-enriched biomarker-stratified design.Statistics in medicine · 2018Article
- Development and evaluating multimarker models for guiding treatment decisions.BMC medical informatics and decision making · 2018Article
- Case-only approach to identifying markers predicting treatment effects on the relative risk scale.Biometrics · 2018Article
- Evaluation of biomarkers for treatment selection using individual participant data from multiple clinical trials.Statistics in medicine · 2018Article
- On Enrichment Strategies for Biomarker Stratified Clinical Trials.Journal of biopharmaceutical statistics · 2018Article
- Value-based and benefit-based strategies in deciding to bring a test into use should be distinguished.Diagnostic and prognostic research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Despite the heightened interest in developing biomarkers predicting treatment response that are used to optimize patient treatment decisions, there has been relatively little development of statistical methodology to evaluate these markers. There is currently no unified statistical framework for marker evaluation. This paper proposes a suite of descriptive and inferential methods designed to evaluate individual markers and to compare candidate markers. An R software package has been developed which implements these methods. Their utility is illustrated in the breast cancer treatment context, where candidate markers are evaluated for their ability to identify a subset of women who do not benefit from adjuvant chemotherapy and can therefore avoid its toxicity.
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Identifiers
What 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.