ArticleGenome biology2019
I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
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.
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Who cites it
10 citing papers in PubMed.
- Molecular evaluation of residual disease following neoadjuvant chemotherapy in triple-negative breast cancer CALGB 40603 (Alliance).The Journal of clinical investigation · 2026Trial
- CALGB 40603 (Alliance): Long-Term Outcomes and Genomic Correlates of Response and Survival After Neoadjuvant Chemotherapy With or Without Carboplatin and Bevacizumab in Triple-Negative Breast Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022Trial
- Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer.medRxiv : the preprint server for health sciences · 2025Article
- A comprehensive review of cancer survival prediction using multi-omics integration and clinical variables.Briefings in bioinformatics · 2025Review
- Integrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning.Scientific reports · 2025Article
- PENALIZED REGRESSION FOR MULTIPLE TYPES OF MANY FEATURES WITH MISSING DATA.Statistica Sinica · 2023Article
- Elucidating the Influence of MPT-driven necrosis-linked LncRNAs on immunotherapy outcomes, sensitivity to chemotherapy, and mechanisms of cell death in clear cell renal carcinoma.Frontiers in oncology · 2023Article
- A meta-learning approach for genomic survival analysis.Nature communications · 2020Article
- Consistency and overfitting of multi-omics methods on experimental data.Briefings in bioinformatics · 2020Article
- I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms.Genome biology · 2019Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
We propose a statistical boosting method, termed I-Boost, to integrate multiple types of high-dimensional genomics data with clinical data for predicting survival time. I-Boost provides substantially higher prediction accuracy than existing methods. By applying I-Boost to The Cancer Genome Atlas, we show that the integration of multiple genomics platforms with clinical variables improves the prediction of survival time over the use of clinical variables alone; gene expression values are typically more prognostic of survival time than other genomics data types; and gene modules/signatures are at least as prognostic as the collection of individual gene expression data.
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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.