Development of clinical inflammatory models to predict the efficacy of neoadjuvant chemoradiotherapy and survival in patients with locally advanced rectal cancer: a retrospective study.

AIM

To assess the ability of clinical inflammatory models to predict tumor regression grade (TRG) in response to neoadjuvant chemoradiotherapy (NCRT) and survival in patients with locally advanced rectal cancer (LARC).

METHODS

We retrospectively analyzed 161 patients with LARC who underwent NCRT followed by total mesorectal excision at Beijing Hospital between May 2007 and March 2022. By using logistic and Cox regression analyses, we developed prediction models for TRG in response to NCRT and overall survival (OS), respectively.

RESULTS

Multivariable logistic regression analysis indicated that variations in neutrophil, lymphocyte, and monocyte counts and pre-NCRT (preneoadjuvant chemoradiotherapy) CA19 - 9 levels independently predicted TRG in response to NCRT (all P < 0.05). Multivariate Cox regression analysis revealed that clinical tumor (cT) stage, pre-NCRT platelet count, CA19 - 9 level, number of lymph node metastases, and TRG could independently predict OS (all P < 0.05). On the basis of these results, we developed models to predict TRG and OS, respectively. The final predictive model for predicting the response to NCRT had areas under the curve (AUCs) of 0.783 and 0.809 in the training and testing cohorts, respectively; for predicting the 5-year OS rate, the AUC rates were 0.842 and 0.930 in the training and test sets, respectively. The calibration and decision curves showed favorable performance in our prediction models.

CONCLUSION

We combined inflammatory markers with tumor characteristics and successfully developed clinical prediction models for TRG in response to NCRT and OS in patients with LARC. Our findings offer insights for optimizing treatment in patients with LARC.