A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy
Abstract Background Uterine cervical carcinoma is a severe health threat worldwide, especially in China. The International Federation of Gynecology and Obstetrics (FIGO) has revised the staging system, emphasizing the strength of magnetic resonance imaging (MRI). We aimed to investigate long-term pr...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-07-01
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| Series: | World Journal of Surgical Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12957-023-03116-4 |
| _version_ | 1797774187961516032 |
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| author | Lele Zang Qin Chen An Lin Jian Chen Xiaozhen Zhang Yi Fang Min Wang |
| author_facet | Lele Zang Qin Chen An Lin Jian Chen Xiaozhen Zhang Yi Fang Min Wang |
| author_sort | Lele Zang |
| collection | DOAJ |
| description | Abstract Background Uterine cervical carcinoma is a severe health threat worldwide, especially in China. The International Federation of Gynecology and Obstetrics (FIGO) has revised the staging system, emphasizing the strength of magnetic resonance imaging (MRI). We aimed to investigate long-term prognostic factors for FIGO 2018 stage II–IIIC2r uterine cervical squamous cell carcinoma following definitive radiotherapy and establish a prognostic model using MRI-derived tumor volume. Methods Patients were restaged according to the FIGO 2018 staging system and randomly grouped into training and validation cohorts (7:3 ratio). Optimal cutoff values of squamous cell carcinoma antigen (SCC-Ag) and tumor volume derived from MRI were generated for the training cohort. A nomogram was constructed based on overall survival (OS) predictors, which were selected using univariate and multivariate analyses. The performance of the nomogram was validated and compared with the FIGO 2018 staging system. Risk stratification cutoff points were generated, and survival curves of low-risk and high-risk groups were compared. Results We enrolled 396 patients (training set, 277; validation set, 119). The SCC-Ag and MRI-derived tumor volume cutoff values were 11.5 ng/mL and 28.85 cm3, respectively. A nomogram was established based on significant prognostic factors, including SCC-Ag, poor differentiation, tumor volume, chemotherapy, and FIGO 2018 stage. Decision curve analysis indicated that the net benefits of our model were higher. The high-risk group had significantly shorter OS than the low-risk group in both the training (p < 0.0001) and validation sets (p = 0.00055). Conclusions Our nomogram predicted long-term outcomes of patients with FIGO 2018 stage II–IIIC2r uterine cervical squamous cell carcinoma. This tool can assist gynecologic oncologists and patients in treatment planning and prognosis. |
| first_indexed | 2024-03-12T22:17:22Z |
| format | Article |
| id | doaj.art-ecd1c5a6c49b4a8eb8e0e7c1bdf473e7 |
| institution | Directory Open Access Journal |
| issn | 1477-7819 |
| language | English |
| last_indexed | 2024-03-12T22:17:22Z |
| publishDate | 2023-07-01 |
| publisher | BMC |
| record_format | Article |
| series | World Journal of Surgical Oncology |
| spelling | doaj.art-ecd1c5a6c49b4a8eb8e0e7c1bdf473e72023-07-23T11:16:15ZengBMCWorld Journal of Surgical Oncology1477-78192023-07-0121111510.1186/s12957-023-03116-4A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapyLele Zang0Qin Chen1An Lin2Jian Chen3Xiaozhen Zhang4Yi Fang5Min Wang6Department of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalDepartment of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalDepartment of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalDepartment of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalDepartment of Radiology, The Affiliated People’s Hospital of Fujian University of Traditional Chinese MedicineDepartment of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalDepartment of Gynecology, Fujian Medical University Cancer Hospital, FujianCancer HospitalAbstract Background Uterine cervical carcinoma is a severe health threat worldwide, especially in China. The International Federation of Gynecology and Obstetrics (FIGO) has revised the staging system, emphasizing the strength of magnetic resonance imaging (MRI). We aimed to investigate long-term prognostic factors for FIGO 2018 stage II–IIIC2r uterine cervical squamous cell carcinoma following definitive radiotherapy and establish a prognostic model using MRI-derived tumor volume. Methods Patients were restaged according to the FIGO 2018 staging system and randomly grouped into training and validation cohorts (7:3 ratio). Optimal cutoff values of squamous cell carcinoma antigen (SCC-Ag) and tumor volume derived from MRI were generated for the training cohort. A nomogram was constructed based on overall survival (OS) predictors, which were selected using univariate and multivariate analyses. The performance of the nomogram was validated and compared with the FIGO 2018 staging system. Risk stratification cutoff points were generated, and survival curves of low-risk and high-risk groups were compared. Results We enrolled 396 patients (training set, 277; validation set, 119). The SCC-Ag and MRI-derived tumor volume cutoff values were 11.5 ng/mL and 28.85 cm3, respectively. A nomogram was established based on significant prognostic factors, including SCC-Ag, poor differentiation, tumor volume, chemotherapy, and FIGO 2018 stage. Decision curve analysis indicated that the net benefits of our model were higher. The high-risk group had significantly shorter OS than the low-risk group in both the training (p < 0.0001) and validation sets (p = 0.00055). Conclusions Our nomogram predicted long-term outcomes of patients with FIGO 2018 stage II–IIIC2r uterine cervical squamous cell carcinoma. This tool can assist gynecologic oncologists and patients in treatment planning and prognosis.https://doi.org/10.1186/s12957-023-03116-4FIGO 2018Prognostic modelMRIUterine cervical squamous cell carcinomaRadiotherapy |
| spellingShingle | Lele Zang Qin Chen An Lin Jian Chen Xiaozhen Zhang Yi Fang Min Wang A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy World Journal of Surgical Oncology FIGO 2018 Prognostic model MRI Uterine cervical squamous cell carcinoma Radiotherapy |
| title | A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| title_full | A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| title_fullStr | A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| title_full_unstemmed | A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| title_short | A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| title_sort | prognostic model using figo 2018 staging and mri derived tumor volume to predict long term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy |
| topic | FIGO 2018 Prognostic model MRI Uterine cervical squamous cell carcinoma Radiotherapy |
| url | https://doi.org/10.1186/s12957-023-03116-4 |
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