A model to guide the management and decision of re-planning during radiotherapy for cervical cancer

Wei Zhang; Xiuhua Li; Tingting Lin; Fang Ma; Xiaoyu Ma; Xiaoli Wu; Yingming Sun; Xiaoge Sun

doi:10.21037/tcr-21-2545

A model to guide the management and decision of re-planning during radiotherapy for cervical cancer

Transl Cancer Res. 2021 Dec;10(12):5352-5363. doi: 10.21037/tcr-21-2545.

Authors

Wei Zhang¹, Xiuhua Li², Tingting Lin³, Fang Ma⁴, Xiaoyu Ma⁴, Xiaoli Wu⁴, Yingming Sun³, Xiaoge Sun⁴

Affiliations

¹ Department of Radiation Oncology, Affiliated People's Hospital of Inner Mongolia Medical University, Hohhot, China.
² Department of Gynaecology, Fujian Cancer Hospital, The Affiliated Hospital of Fujian Medical University, Fuzhou, China.
³ Department of Radiation and Medical Oncology, Affiliated Sanming First Hospital of Fujian Medical University, Sanming, China.
⁴ Department of Radiation Oncology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.

Abstract

Background: To establish a model to predict whether re-planning is needed in the process of cervical cancer radiotherapy.

Methods: We collected the clinical indexes of 132 patients diagnosed with cervical cancer receiving concurrent chemotherapy and radiotherapy, including 33 factors about tumor markers [carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), squamous cell carcinoma antigen (SCC)], tumor volume, rectal volume, bladder volume, volumes receiving 30-50 Gy in organs-at-risk (OARs), and the maximum dose (Dmax) received by 1-2 cc in OARs. We established a multivariate model for re-planning evaluation via principal component analysis, and then verified the model based on the internal data.

Results: We identified the dose index (P1), tumor size index (P2), and volumes receiving 30-50 Gy in OARs and the tumor (P3) as the three most weighted factors of the re-planning model. We set the cut-off for the re-planning modification requirement at 1. The model was consistent with R = 0.12P1 + 0.21P2 + 0.31P3, and it performed accurately that area under the test set characteristics curve (AUC) =0.826].

Conclusions: Our proposed method can help to reduce image re-examination during treatment, decrease toxicities in OARs, shorten the radiotherapy course, lessen oncologists' efforts, and save medical resources.

Keywords: Cervical cancer; model; radiotherapy; re-planning.