Development And Validation Of A Nomogram To Predict Survival After Curative Resection Of Nonmetastatic Colorectal Cancer

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A gene expression signature‐based nomogram model in

five‐gene‐based prognostic model for colorectal cancer based on four gene expression datasets while Meng et al16 constructed a four‐long non‐coding RNA signature in pre-dicting breast cancer survival based on 887 patients from three microarray datasets. In the current study, we reviewed a total of 572 BC pa-

Annals of Oncology abstracts

survival, 10e75% for 3-year survival, 35e80% for 5-year survival. Conclusion: We combined the CD163 expression level in macrophage, TNM stages, age, and gender to develop and validate a nomogram as a useful tool in predicting 5-yearoverall survival aftercurative resection for gastric cancer.This model may provide

Development and validation of a nomogram to predict survival

predict OS after curative resection for nonmetastatic colorectal cancer (CRC). The nomogram outperformed the 8th AJCC staging and the MSKCC model and could aid in personalized treatment and follow-up strategy for CRC patients. KEYWORDS curative resection, nomogram, nonmetastatic colorectal cancer, overall survival

Journal articles using LTR data published in the year of 2017

ZW, Wang F, and Xu RH, Development and Validation of a Nomogram to Predict the Benefit of Adjuvant Radiotherapy for Patients with Resected Gastric Cancer. J Cancer, 2017. 8(17): p. 3498-3505. PMID: 29151934. PMC5687164. 39. Zeidan AM, Long JB, Wang R, Hu X, Yu JB, Huntington SF, Abel GA, Mougalian SS,

Choosing the right strategy based on individualized treatment

sectable metastatic colorectal cancer (mCRC) patients. Material and methods: We used data from 803 patients included in CAIRO for prediction model development and internal validation, and data from 1423 patients included in FOCUS for external val-idation. A Weibull model with pre-specified patient and tumour characteristics was developed for a

ACKNOWLEDGEMENT - ENETS

ACKNOWLEDGEMENT ENETS would like to give thanks and applause to the Abstract Reviewing Committee 2017 for their superb and hard work and contribution regarding reading, reviewing, discussing and