Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Nov 23:12:932853.
doi: 10.3389/fonc.2022.932853. eCollection 2022.

A novel prediction model for pathological complete response based on clinical and blood parameters in locally advanced rectal cancer

Siyi Lu  1 , Zhenzhen Liu  2 , Yuxia Wang  3 , Yan Meng  1 , Ran Peng  3 , Ruize Qu  1 , Zhipeng Zhang  1 , Wei Fu  1   4 , Hao Wang  3   4
Affiliations

A novel prediction model for pathological complete response based on clinical and blood parameters in locally advanced rectal cancer

Siyi Lu et al. Front Oncol. .

Abstract

Background: The aim of this study was to investigate whether clinical and blood parameters can be used for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).

Methods: We retrospectively enrolled 226 patients with LARC [allocated in a 7:3 ratio to a training (n = 158) or validation (n = 68) cohort] who received nCRT before radical surgery. Backward stepwise logistic regression was performed to identify clinical and blood parameters associated with achieving pCR. Models based on clinical parameters (CP), blood parameters (BP), and clinical-blood parameters (CBP) were constructed for comparison with previously reported Tan's model. The performance of the four models was evaluated by receiver operating characteristic (ROC) curve analysis, calibration, and decision curve analysis (DCA) in both cohorts. A dynamic nomogram was constructed for the presentation of the best model.

Results: The CP and BP models based on multivariate logistic regression analysis showed that interval, Grade, CEA and fibrinogen-albumin ratio index (FARI), sodium-to-globulin ratio (SGR) were the independent clinical and blood predictors for achieving pCR, respectively. The area under the ROC curve of the CBP model achieved a score of 0.818 and 0.752 in both cohorts, better than CP (0.762 and 0.589), BP (0.695 and 0.718), Tan (0.738 and 0.552). CBP also showed better calibration and DCA than other models in both cohorts. Moreover, CBP revealed significant improvement compared with other models in training cohort (P < 0.05), and CBP showed significant improvement compared with CP and Tan's model in validation cohort (P < 0.05).

Conclusion: We demonstrated that CBP predicting model have potential in predicting pCR to nCRT in patient with LARC.

Keywords: locally advanced rectal cancer; neoadjuvant chemotherapy; nomogram; pathological complete response; prediction model.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of the study.
Figure 2
Figure 2
Distribution of the FARI (A) and SGR (B) in both cohorts.
Figure 3
Figure 3
ROC curves of the CP, BP, CBP and Tan in Training cohort (A) and Validation cohort (B). Delong test P-value of Training cohort (C) and Validation cohort (D). CP clinical parameters model, BP blood parameters model, CBP clinical-blood parameters model.
Figure 4
Figure 4
DCA for the four models in Training cohort (A) and Validation cohort (B). The orange line represents the assumption that all patients showed PCR. The black line represents the assumption that no patients showed pCR. (C) Dynamic nomogram of CBP.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Glynne-Jones R, Wyrwicz L, Tiret E, Brown G, Rodel C, Cervantes A, et al. . Rectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol (2018) 29(Suppl 4):iv263. doi: 10.1093/annonc/mdy161 - DOI - PubMed
    1. Hoendervangers S, Burbach JPM, Lacle MM, Koopman M, van Grevenstein WMU, Intven MPW, et al. . Pathological complete response following different neoadjuvant treatment strategies for locally advanced rectal cancer: A systematic review and meta-analysis. Ann Surg Oncol (2020) 27(11):4319–36. doi: 10.1245/s10434-020-08615-2 - DOI - PMC - PubMed
    1. Polanco PM, Mokdad AA, Zhu H, Choti MA, Huerta S. Association of adjuvant chemotherapy with overall survival in patients with rectal cancer and pathologic complete response following neoadjuvant chemotherapy and resection. JAMA Oncol (2018) 4(7):938–43. doi: 10.1001/jamaoncol.2018.0231 - DOI - PMC - PubMed
    1. van der Valk MJM, Hilling DE, Bastiaannet E, Meershoek-Klein Kranenbarg E, Beets GL, Figueiredo NL, et al. . Long-term outcomes of clinical complete responders after neoadjuvant treatment for rectal cancer in the international watch & wait database (IWWD): an international multicentre registry study. Lancet (2018) 391(10139):2537–45. doi: 10.1016/S0140-6736(18)31078-X - DOI - PubMed
    1. Dattani M, Heald RJ, Goussous G, Broadhurst J, Sao Juliao GP, Habr-Gama A, et al. . Oncological and survival outcomes in watch and wait patients with a clinical complete response after neoadjuvant chemoradiotherapy for rectal cancer: A systematic review and pooled analysis. Ann Surg (2018) 268(6):955–67. doi: 10.1097/SLA.0000000000002761 - DOI - PubMed