Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study

doi:10.3748/wjg.v31.i13.104466

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Apr 7, 2025 (publication date) through Apr 6, 2025

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Gastroenterol. Apr 7, 2025; 31(13): 104466
Published online Apr 7, 2025. doi: 10.3748/wjg.v31.i13.104466

Table 1 Comparison of the predictive performance of the xTRM-W staging system and the 8^th edition tumor node metastasis staging system

Group	Classification	Likelihood ratio χ²	C-index	AIC value
Training set	xTRM-W	668.580	0.742	12323.976
Training set	pTNM	479.560	0.714	12512.994
Validation set	xTRM-W	324.290	0.666	12489.603
Validation set	pTNM	275.700	0.655	12538.197

TNM: Tumor node metastasis.

Table 2 Comparison of the predictive performance of the xTRM-P staging system and the 8^th edition tumor node metastasis staging system

Group	Classification	Likelihood ratio χ²	C-index	AIC value
Training set	xTRM-P	732.740	0.723	15938.971
Training set	pTNM	559.260	0.704	16112.451
Validation set	xTRM-P	989.680	0.680	34678.546
Validation set	pTNM	893.260	0.680	34774.967

TNM: Tumor node metastasis.

Citation: Zhang YL, Song HB, Xue YW. Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study. World J Gastroenterol 2025; 31(13): 104466
URL: https://www.wjgnet.com/1007-9327/full/v31/i13/104466.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i13.104466