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Items: 1 to 20 of 63

1.

Modeling risk stratification in human cancer.

Rème T, Hose D, Theillet C, Klein B.

Bioinformatics. 2013 May 1;29(9):1149-57. doi: 10.1093/bioinformatics/btt124. Epub 2013 Mar 14.

PMID:
23493321
2.

Gene expression profiling in multiple myeloma--reporting of entities, risk, and targets in clinical routine.

Meissner T, Seckinger A, Rème T, Hielscher T, Möhler T, Neben K, Goldschmidt H, Klein B, Hose D.

Clin Cancer Res. 2011 Dec 1;17(23):7240-7. doi: 10.1158/1078-0432.CCR-11-1628. Epub 2011 Oct 10.

3.

Mixture classification model based on clinical markers for breast cancer prognosis.

Zeng T, Liu J.

Artif Intell Med. 2010 Feb-Mar;48(2-3):129-37. doi: 10.1016/j.artmed.2009.07.008. Epub 2009 Dec 14.

PMID:
20005686
4.

Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome.

Decaux O, Lodé L, Magrangeas F, Charbonnel C, Gouraud W, Jézéquel P, Attal M, Harousseau JL, Moreau P, Bataille R, Campion L, Avet-Loiseau H, Minvielle S; Intergroupe Francophone du Myélome.

J Clin Oncol. 2008 Oct 10;26(29):4798-805. doi: 10.1200/JCO.2007.13.8545. Epub 2008 Jun 30.

PMID:
18591550
5.

RecurrenceOnline: an online analysis tool to determine breast cancer recurrence and hormone receptor status using microarray data.

Győrffy B, Benke Z, Lánczky A, Balázs B, Szállási Z, Timár J, Schäfer R.

Breast Cancer Res Treat. 2012 Apr;132(3):1025-34. doi: 10.1007/s10549-011-1676-y. Epub 2011 Jul 16.

PMID:
21773767
6.

Assessment of performance of survival prediction models for cancer prognosis.

Chen HC, Kodell RL, Cheng KF, Chen JJ.

BMC Med Res Methodol. 2012 Jul 23;12:102. doi: 10.1186/1471-2288-12-102.

7.

Racial disparities in cancer survival among randomized clinical trials patients of the Southwest Oncology Group.

Albain KS, Unger JM, Crowley JJ, Coltman CA Jr, Hershman DL.

J Natl Cancer Inst. 2009 Jul 15;101(14):984-92. doi: 10.1093/jnci/djp175. Epub 2009 Jul 7.

8.
9.

A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis.

Wang DY, Done SJ, McCready DR, Boerner S, Kulkarni S, Leong WL.

Breast Cancer Res. 2011 Sep 22;13(5):R92. doi: 10.1186/bcr3017.

10.

Combining gene signatures improves prediction of breast cancer survival.

Zhao X, Rødland EA, Sørlie T, Naume B, Langerød A, Frigessi A, Kristensen VN, Børresen-Dale AL, Lingjærde OC.

PLoS One. 2011 Mar 10;6(3):e17845. doi: 10.1371/journal.pone.0017845.

11.

Comparison of prognostic gene expression signatures for breast cancer.

Haibe-Kains B, Desmedt C, Piette F, Buyse M, Cardoso F, Van't Veer L, Piccart M, Bontempi G, Sotiriou C.

BMC Genomics. 2008 Aug 21;9:394. doi: 10.1186/1471-2164-9-394.

12.

Integration of pathway knowledge into a reweighted recursive feature elimination approach for risk stratification of cancer patients.

Johannes M, Brase JC, Fröhlich H, Gade S, Gehrmann M, Fälth M, Sültmann H, Beissbarth T.

Bioinformatics. 2010 Sep 1;26(17):2136-44. doi: 10.1093/bioinformatics/btq345. Epub 2010 Jun 30.

PMID:
20591905
13.

A prognostic model for lymph node-negative breast cancer patients based on the integration of proliferation and immunity.

Oh E, Choi YL, Park T, Lee S, Nam SJ, Shin YK.

Breast Cancer Res Treat. 2012 Apr;132(2):499-509. doi: 10.1007/s10549-011-1626-8. Epub 2011 Jun 11.

PMID:
21667120
14.
15.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

Sánchez-Navarro I, Gámez-Pozo A, Pinto A, Hardisson D, Madero R, López R, San José B, Zamora P, Redondo A, Feliu J, Cejas P, González Barón M, Angel Fresno Vara J, Espinosa E.

BMC Cancer. 2010 Jun 28;10:336. doi: 10.1186/1471-2407-10-336.

16.

The molecular portraits of breast tumors are conserved across microarray platforms.

Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Ruiz Orrico A, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS, Perou CM.

BMC Genomics. 2006 Apr 27;7:96.

17.

A high-risk signature for patients with multiple myeloma established from the molecular classification of human myeloma cell lines.

Moreaux J, Klein B, Bataille R, Descamps G, Maïga S, Hose D, Goldschmidt H, Jauch A, Rème T, Jourdan M, Amiot M, Pellat-Deceunynck C.

Haematologica. 2011 Apr;96(4):574-82. doi: 10.3324/haematol.2010.033456. Epub 2010 Dec 20.

18.

bc-GenExMiner: an easy-to-use online platform for gene prognostic analyses in breast cancer.

Jézéquel P, Campone M, Gouraud W, Guérin-Charbonnel C, Leux C, Ricolleau G, Campion L.

Breast Cancer Res Treat. 2012 Feb;131(3):765-75. doi: 10.1007/s10549-011-1457-7. Epub 2011 Mar 31.

PMID:
21452023
19.

The role of fluorescence in situ hybridization and gene expression profiling in myeloma risk stratification.

Hose D, Seckinger A, Jauch A, Rème T, Moreaux J, Bertsch U, Neben K, Klein B, Goldschmidt H.

Srp Arh Celok Lek. 2011 Dec;139 Suppl 2:84-9.

20.

Population-based molecular prognosis of breast cancer by transcriptional profiling.

Ma Y, Qian Y, Wei L, Abraham J, Shi X, Castranova V, Harner EJ, Flynn DC, Guo L.

Clin Cancer Res. 2007 Apr 1;13(7):2014-22.

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