AUTHOR=Hu Chenhao , Shi Feiyu , Zhang Zhe , Zhang Lei , Liu Ruihan , Sun Xuejun , Zheng Liansheng , She Junjun TITLE=Development and validation of a new stage-specific nomogram model for predicting cancer-specific survival in patients in different stages of colon cancer: A SEER population-based study and external validation JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1024467 DOI=10.3389/fonc.2022.1024467 ISSN=2234-943X ABSTRACT=Background

The effects of laterality of the primary tumor on survival in patients in different stages of colon cancer are contradictory. We still lack a strictly evaluated and validated survival prediction tool, considering the different roles of tumor laterality in different stages.

Methods

A total of 101,277 and 809 colon cancer cases were reviewed using the Surveillance, Epidemiology, and End Results database and the First Affiliated Hospital of Xi ‘an Jiaotong University database, respectively. We established training sets, internal validation sets and external validation sets. We developed and evaluated stage-specific prediction models and unified prediction models to predict cancer-specific survival and compared the prediction abilities of these models.

Results

Compared with right-sided colon cancers, the risk of cancer-specific death of left-sided colon cancer patients was significantly higher in stage I/II but was markedly lower in stage III patients. We established stage-specific prediction models for stage I/II and stage III separately and established a unified prediction model for all stages. By evaluating and validating the validation sets, we reported high prediction ability and generalizability of the models. Furthermore, the stage-specific prediction models had better predictive power and efficiency than the unified model.

Conclusions

Right-sided colon cancer patients have better cancer-specific survival than left-sided colon cancer patients in stage I/II and worse cancer-specific survival in stage III. Using stage-specific prediction models can further improve the prediction of cancer-specific survival in colon cancer patients and guide clinical decisions.