Copyright
©The Author(s) 2026.
World J Clin Oncol. Jan 24, 2026; 17(1): 114238
Published online Jan 24, 2026. doi: 10.5306/wjco.v17.i1.114238
Published online Jan 24, 2026. doi: 10.5306/wjco.v17.i1.114238
Figure 1 Kaplan-Meier analysis of progression-free survival by risk stratification and immunological status.
A: Estimates of progression-free survival according to risk group; B: Progression-free survival stratified by tumor stage and CD16+CD56+ natural killer cell percentage. PFS: Progression-free survival; NK: Natural killer.
Figure 2 Time-dependent receiver operating characteristic curves for prediction of progression-free survival at 1 year, 3 years, and 5 years.
ROC: Receiver operating characteristic; AUC: Area under the curve; CI: Confidence interval.
Figure 3 Distribution of risk scores according to tumor stage and CD16+CD56+ natural killer cell groups.
NK: Natural killer.
- Citation: Chen X, Wang Y, Shen HY, Wu R, Fu Z. Development and internal validation of an immune-based prognostic modeling of early-onset colorectal cancer via machine learning. World J Clin Oncol 2026; 17(1): 114238
- URL: https://www.wjgnet.com/2218-4333/full/v17/i1/114238.htm
- DOI: https://dx.doi.org/10.5306/wjco.v17.i1.114238
