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https://www.selleckchem.com/products/hs-173.html Background To use competing analyses to estimate the prognostic value of KRAS mutation status in colorectal cancer (CRC) patients and to build nomogram for CRC patients who had KRAS testing. Method The cohort was selected from the Surveillance, Epidemiology, and End Results database. Cumulative incidence function model and multivariate Fine-Gray regression for proportional hazards modeling of the subdistribution hazard (SH) model were used to estimate the prognosis. An SH model based nomogram was built after a variable selection process. The validation of the nomogram was conducted by discrimination and calibration with 1,000 bootstraps. Results We included 8,983 CRC patients who had KRAS testing. SH model found that KRAS mutant patients had worse CSS than KRAS wild type patients in overall cohort (HR = 1.10 (95% CI [1.04-1.17]), p less then 0.05), and in subgroups that comprised stage III CRC (HR = 1.28 (95% CI [1.09-1.49]), p less then 0.05) and stage IV CRC (HR = 1.14 (95% CI [1.06-1.23]), p less then 0.05), left side colon cancer (HR = 1.28 (95% CI [1.15-1.42]), p less then 0.05) and rectal cancer (HR = 1.23 (95% CI [1.07-1.43]), p less then 0.05). We built the SH model based nomogram, which showed good accuracy by internal validation of discrimination and calibration. Calibration curves represented good agreement between the nomogram predicted CRC caused death and actual observed CRC caused death. The time dependent area under the curve of receiver operating characteristic curves (AUC) was over 0.75 for the nomogram. Conclusion This is the first population based competing risk study on the association between KRAS mutation status and the CRC prognosis. The mutation of KRAS indicated a poor prognosis of CRC patients. The current competing risk nomogram would help physicians to predict cancer specific death of CRC patients who had KRAS testing.Background Biobanking of cell lines is a promising tool of support for w

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