725 related articles for article (PubMed ID: 28532387)
1. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials.
Ternès N; Rotolo F; Michiels S
BMC Med Res Methodol; 2017 May; 17(1):83. PubMed ID: 28532387
[TBL] [Abstract][Full Text] [Related]
2. Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces.
Ternès N; Rotolo F; Heinze G; Michiels S
Biom J; 2017 Jul; 59(4):685-701. PubMed ID: 27862181
[TBL] [Abstract][Full Text] [Related]
3. Favoring the hierarchical constraint in penalized survival models for randomized trials in precision medicine.
Belhechmi S; Le Teuff G; De Bin R; Rotolo F; Michiels S
BMC Bioinformatics; 2023 Mar; 24(1):96. PubMed ID: 36927444
[TBL] [Abstract][Full Text] [Related]
4. High-dimensional Cox models: the choice of penalty as part of the model building process.
Benner A; Zucknick M; Hielscher T; Ittrich C; Mansmann U
Biom J; 2010 Feb; 52(1):50-69. PubMed ID: 20166132
[TBL] [Abstract][Full Text] [Related]
5. biospear: an R package for biomarker selection in penalized Cox regression.
Ternès N; Rotolo F; Michiels S
Bioinformatics; 2018 Jan; 34(1):112-113. PubMed ID: 28927242
[TBL] [Abstract][Full Text] [Related]
6. Identification of clinically relevant features in hypertensive patients using penalized regression: a case study of cardiovascular events.
Garcia-Carretero R; Barquero-Perez O; Mora-Jimenez I; Soguero-Ruiz C; Goya-Esteban R; Ramos-Lopez J
Med Biol Eng Comput; 2019 Sep; 57(9):2011-2026. PubMed ID: 31346948
[TBL] [Abstract][Full Text] [Related]
7. L1 penalized estimation in the Cox proportional hazards model.
Goeman JJ
Biom J; 2010 Feb; 52(1):70-84. PubMed ID: 19937997
[TBL] [Abstract][Full Text] [Related]
8. NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.
Zou M; Liu Z; Zhang XS; Wang Y
Bioinformatics; 2015 Oct; 31(20):3330-8. PubMed ID: 26092859
[TBL] [Abstract][Full Text] [Related]
9. A plea for taking all available clinical information into account when assessing the predictive value of omics data.
Volkmann A; De Bin R; Sauerbrei W; Boulesteix AL
BMC Med Res Methodol; 2019 Jul; 19(1):162. PubMed ID: 31340753
[TBL] [Abstract][Full Text] [Related]
10. Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models.
Belhechmi S; Bin R; Rotolo F; Michiels S
BMC Bioinformatics; 2020 Jul; 21(1):277. PubMed ID: 32615919
[TBL] [Abstract][Full Text] [Related]
11. Herceptin® (trastuzumab) in HER2-positive early breast cancer: protocol for a systematic review and cumulative network meta-analysis.
Wilson FR; Coombes ME; Wylie Q; Yurchenko M; Brezden-Masley C; Hutton B; Skidmore B; Cameron C
Syst Rev; 2017 Oct; 6(1):196. PubMed ID: 29017563
[TBL] [Abstract][Full Text] [Related]
12. Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.
Ternès N; Rotolo F; Michiels S
Stat Med; 2016 Jul; 35(15):2561-73. PubMed ID: 26970107
[TBL] [Abstract][Full Text] [Related]
13. Biomarker-based Bayesian randomized phase II clinical trial design to identify a sensitive patient subpopulation.
Morita S; Yamamoto H; Sugitani Y
Stat Med; 2014 Oct; 33(23):4008-16. PubMed ID: 24820639
[TBL] [Abstract][Full Text] [Related]
14. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.
Guinney J; Wang T; Laajala TD; Winner KK; Bare JC; Neto EC; Khan SA; Peddinti G; Airola A; Pahikkala T; Mirtti T; Yu T; Bot BM; Shen L; Abdallah K; Norman T; Friend S; Stolovitzky G; Soule H; Sweeney CJ; Ryan CJ; Scher HI; Sartor O; Xie Y; Aittokallio T; Zhou FL; Costello JC;
Lancet Oncol; 2017 Jan; 18(1):132-142. PubMed ID: 27864015
[TBL] [Abstract][Full Text] [Related]
15. Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer.
Kim D; Li R; Dudek SM; Ritchie MD
J Biomed Inform; 2015 Aug; 56():220-8. PubMed ID: 26048077
[TBL] [Abstract][Full Text] [Related]
16. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
Gui J; Li H
Bioinformatics; 2005 Jul; 21(13):3001-8. PubMed ID: 15814556
[TBL] [Abstract][Full Text] [Related]
17. Validation of the CPS+EG and Neo-Bioscore staging systems after preoperative systemic therapy for breast cancer in a single center in China.
Xu L; Duan X; Zhou B; Liu Y; Ye J; Liu Z; Ma C; Zhang H; Zhang S; Zhang L; Zhao J; Cheng Y
Breast; 2018 Aug; 40():29-37. PubMed ID: 29677568
[TBL] [Abstract][Full Text] [Related]
18. Bayesian two-step Lasso strategy for biomarker selection in personalized medicine development for time-to-event endpoints.
Gu X; Yin G; Lee JJ
Contemp Clin Trials; 2013 Nov; 36(2):642-50. PubMed ID: 24075829
[TBL] [Abstract][Full Text] [Related]
19. Gradient lasso for Cox proportional hazards model.
Sohn I; Kim J; Jung SH; Park C
Bioinformatics; 2009 Jul; 25(14):1775-81. PubMed ID: 19447787
[TBL] [Abstract][Full Text] [Related]
20. Association of Stromal Tumor-Infiltrating Lymphocytes With Recurrence-Free Survival in the N9831 Adjuvant Trial in Patients With Early-Stage HER2-Positive Breast Cancer.
Perez EA; Ballman KV; Tenner KS; Thompson EA; Badve SS; Bailey H; Baehner FL
JAMA Oncol; 2016 Jan; 2(1):56-64. PubMed ID: 26469139
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
