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 Sep 29:14:2933-2944.
doi: 10.2147/CMAR.S377784. eCollection 2022.

Combination of Changes in CEA and CA199 Concentration After Neoadjuvant Chemoradiotherapy Could Predict the Prognosis of Stage II/III Rectal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Followed by Total Mesorectal Excision

Affiliations

Combination of Changes in CEA and CA199 Concentration After Neoadjuvant Chemoradiotherapy Could Predict the Prognosis of Stage II/III Rectal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Followed by Total Mesorectal Excision

Jieyi Zhao et al. Cancer Manag Res. .

Abstract

Background: Previous studies have shown that the levels of serum tumor markers CEA and CA19-9 were related to chemoradiotherapy. Therefore, it has been assumed that dynamic monitoring of these markers could predict the prognosis of stage II/III rectal cancer (RC). Therefore, this study proposed to evaluate the prognostic value of changes in serum tumor biomarkers for stage II/III RC patients undergoing neoadjuvant chemoradiotherapy (NCRT) followed by total mesorectal excision (TME).

Methods: A total of 217 patients with stage II/III RC receiving NCRT followed by TME were retrospectively analyzed. Serum CEA and CA199 levels were measured within one week before NCRT and one week before TME. The optimal cut-off points of ∆CEA% and ∆CA199% for prognosis prediction were calculated by receiver operating characteristics (ROC) analysis. Independent prognostic predictors were identified by univariate and multivariate Cox regression analyses. To avoid the efficiency of ∆CEA% and ∆CA199% on serum tumor biomarker change (STBC) score, two models including and excluding ∆CEA% and ∆CA199% were established separately in multivariate analysis.

Results: The optimal cut-off point for ∆CEA% and ∆CA199% were -30.29% and 20.30%, respectively. Univariate analysis showed that ∆CEA%, ∆CA199%, STBC score, ypT staging and yN staging could predict OS. ypT staging and STBC score could predict DFS. In multivariate analysis, only ∆CA199% (HR = 0.468, 95% CI: 0.220-0.994, p = 0.048), ypT staging (HR = 0.420, 95% CI: 0.182-0.970, p = 0.042), and STBC score (HR = 0.204, 95% CI: 0.078-0.532, p = 0.001) were independently related to OS; and STBC score (HR = 0.412, 95% CI: 0.216-0.785, p=0.007) and ypT staging (HR = 0.421, 95% CI: 0.224-0.792, p = 0.007) were independently related to DFS.

Conclusion: We established a combined STBC score to predict the prognosis of stage II/III RC patients receiving NCRT followed by TME. The predictive value of the combined score was stronger than a single marker alone and even stronger than several pathological indicators.

Keywords: STBC score; neoadjuvant chemoradiotherapy; prognosis; stage II/III rectal cancer; total mesorectal excision.

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

None
Graphical abstract
Figure 1
Figure 1
Patients screening flow chart.
Figure 2
Figure 2
K-M curves depicting OS according to ∆CEA% status.
Figure 3
Figure 3
K-M curves depicting OS according to ∆CA199% status.
Figure 4
Figure 4
K-M curves depicting OS according to STBC score.
Figure 5
Figure 5
K-M curves depicting DFS according to ∆CEA% status.
Figure 6
Figure 6
K-M curves depicting DFS according to ∆CA199% status.
Figure 7
Figure 7
K-M curves depicting DFS according to STBC score.

Similar articles

Cited by

References

    1. Benson AB, Venook AP, Al-Hawary MM, et al. Rectal cancer, version 2.2018, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2018;16(7):874–901. doi:10.6004/jnccn.2018.0061 - DOI - PMC - PubMed
    1. Karagkounis G, Thai L, Mace AG, et al. Prognostic implications of pathological response to neoadjuvant chemoradiation in pathologic stage III rectal cancer. Ann Surg. 2019;269(6):1117–1123. doi:10.1097/SLA.0000000000002719 - DOI - PubMed
    1. Peng JY, Li ZN, Wang Y. Risk factors for local recurrence following neoadjuvant chemoradiotherapy for rectal cancers. World J Gastroenterol. 2013;19(32):5227–5237. doi:10.3748/wjg.v19.i32.5227 - DOI - PMC - PubMed
    1. Jiang D, Wang X, Wang Y, et al. Mutation in BRAF and SMAD4 associated with resistance to neoadjuvant chemoradiation therapy in locally advanced rectal cancer. Virchows Arch. 2019;475(1):39–47. doi:10.1007/s00428-019-02576-y - DOI - PubMed
    1. Meng X, Wang R, Huang Z, et al. Human epidermal growth factor receptor-2 expression in locally advanced rectal cancer: association with response to neoadjuvant therapy and prognosis. Cancer Sci. 2014;105(7):818–824. doi:10.1111/cas.12421 - DOI - PMC - PubMed