Prognostic value of tumor measurement parameters and SCC-Ag changes in patients with locally-advanced cervical cancer

Average log change rate of pretreatment squamous cell carcinoma antigen after concurrent chemoradiotherapy in stage IIIC1 cervical squamous cell carcinoma

We aimed to determine whether pretreatment squamous cell carcinoma antigen (SCC-Ag) levels and the average logarithmic change in SCC-Ag levels (Δ log SCC-Ag Δ time ) after concurrent chemoradiotherapy (CCRT) could predict treatment outcomes in patients with stage IIIC1 cervical squamous cell carcinoma (SCC). We analyzed 168 patients with stage IIIC1 cervical SCC who underwent primary CCRT and collected data on age, local extension, treatment details, hematological parameters, and tumor markers such as SCC-Ag and carcinoembryonic antigen 21-1 (Cyfra). Predictive performances of pretreatment SCC-Ag levels andΔ log SCC-Ag Δ time were assessed using receiver operating characteristic curves. Survival analysis was performed using the Cox regression model and Kaplan-Meier plots. The combination of pretreatment SCC-Ag levels andΔ log SCC-Ag Δ time showed higher area under the curve values than pretreatment SCC-Ag levels alone (area under the curve; 95% confidence interval [CI] 0.708 [0.581-0.836] vs. 0.666 [0.528-0.804], respectively). Pretreatment SCC-Ag (≥ 5 ng/ml and Cyfra levels (≥ 3.15 ng/ml) andΔ log SCC-Ag Δ time (≥ - 1.575) were significant predictors of disease-specific survival. The 5-year disease-specific survival rates significantly differed among the low-, intermediate-, and high-risk groups. Risk stratification using both pretreatment SCC-Ag levels andΔ log SCC-Ag Δ time may predict treatment outcomes of patients with stage IIIC1 SCC.

Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics Model for Preoperative Predicting the Deep Stromal Invasion in Patients with Early Cervical Cancer

Deep stromal invasion is an important pathological factor associated with the treatments and prognosis of cervical cancer patients. Accurate determination of deep stromal invasion before radical hysterectomy (RH) is of great value for early clinical treatment decision-making and improving the prognosis of these patients. Machine learning is gradually applied in the construction of clinical models to improve the accuracy of clinical diagnosis or prediction, but whether machine learning can improve the preoperative diagnosis accuracy of deep stromal invasion in patients with cervical cancer was still unclear. This cross-sectional study was to construct three preoperative diagnostic models for deep stromal invasion in patients with early cervical cancer based on clinical, radiomics, and clinical combined radiomics data using the machine learning method. We enrolled 229 patients with early cervical cancer receiving RH combined with pelvic lymph node dissection (PLND). The least absolute shrinkage and selection operator (LASSO) and the fivefold cross-validation were applied to screen out radiomics features. Univariate and multivariate logistic regression analyses were applied to identify clinical predictors. All subjects were divided into the training set (n = 160) and testing set (n = 69) at a ratio of 7:3. Three light gradient boosting machine (LightGBM) models were constructed in the training set and verified in the testing set. The radiomics features were statistically different between deep stromal invasion < 1/3 group and deep stromal invasion ≥ 1/3 group. In the training set, the area under the curve (AUC) of the prediction model based on radiomics features was 0.951 (95% confidence interval (CI) 0.922-0.980), the AUC of the prediction model based on clinical predictors was 0.769 (95% CI 0.703-0.835), and the AUC of the prediction model based on radiomics features and clinical predictors was 0.969 (95% CI 0.947-0.990). The AUC of the prediction model based on radiomics features and clinical predictors was 0.914 (95% CI 0.848-0.980) in the testing set. The prediction model for deep stromal invasion in patients with early cervical cancer based on clinical and radiomics data exhibited good predictive performance with an AUC of 0.969, which might help the clinicians early identify patients with high risk of deep stromal invasion and provide timely interventions.

The value of multiparametric MRI combined with clinical prognostic parameters in predicting the 5-year survival of stage IIIC1 cervical squamous cell carcinoma

OBJECTIVES

To explore the value of multiparametric magnetic resonance imaging（MRI）in predicting the 5-year progression-free survival (PFS) and overall survival (OS) of cervical squamous cell carcinoma (CSCC) in 2018 FIGO stage IIIC1.

METHODS

This retrospective study collected156 patients with CSCC from Dec. 2014 to Jul. 2018. Sixty-one patients underwent radical hysterectomy (RH), and 95 patients underwent concurrent chemoradiotherapy (CCRT). Clinical and MR parameters of primary tumours were analysed. A 1:1 ratio propensity score matching (PSM) was performed for the RH group and CCRT group according to T stage. The Cox proportional hazard model was used to evaluate the associations between imaging or clinical variables and PFS and OS.

RESULTS

The 5-year PFS and OS rates were 72.6% and 78.3%, respectively. The analysis results show that the treatment method, ADCmin < 0.604 × 10-3 mm2/s, and Ktrans < 0.699 min-1 correlated with worse PFS, while SCC-Ag > 6.7 ng/L, ADCmin < 0.604 × 10-3 mm2/s, and Ktrans < 0.699 min-1 correlated with worse OS. After PSM, we confirmed that the treatment methods did not affect the long-term survival of patients with stage IIIC1 disease, and a low Ktrans value was an independent poor prognostic factor.

CONCLUSION

Functional MRI parameters and SCC-Ag have potential predictive value for the 5-year survival of 2018 FIGOIIIC1 CSCC. There were no significant differences in survival between CCRT and RH + adjuvant therapy for IIIC1 stage CSCC if the T stage was earlier.

Definitive irradiation as a first treatment strategy for primary and metastatic sites of newly diagnosed IVB cervical cancer that presented with synchronous oligometastases

BACKGROUND

The present study identified survival and progression-free rates and evaluated prognostic factors for IVB stage cervical cancer in patients that presented with synchronous oligometastases (sync-oligometastases) who received definitive irradiation for primary and metastatic sites.

METHODS

The study retrospectively included 60 patients with newly diagnosed stage IVB cervical cancer. Patients received definitive radiation for both primary and metastatic sites through Volumetric Modulated Arc Therapy (VMAT) or intensity modulated radiation therapy (IMRT) followed by three dimensional-intracavitary/interstitial brachytherapy at our institution between July 2014 to December 2020. All patients were staged based on the International Federation of Gynecology and Obstetrics (FIGO) 2018 guidelines. Overall survival (OS), progression-free survival (PFS), and patient prognostic factors were analyzed.

RESULTS

The 60 patients who received curative-intent irradiation for primary and metastatic sites showed a 5-year OS rate of 51.4% and a 5-year PFS rate of 25.9%. The median PFS was 52.3 months, and the median OS had not been reached. Lymphatic metastases had a better OS compared with hematogenous metastases (3-year OS rates: 57.2% vs. 20%, p = 0.017). Patients with one metastasis site showed a more favorable prognosis than patients with ≥ 2 metastases sites (3-year OS rates: 60.4% vs. 20.6%, p = 0.003). Patients that presented with tumors larger than 4 cm in diameter before treatment demonstrated a poorer prognosis (5-year OS rates: 41.2% vs. 65.2%, p = 0.029; 5-year PFS rates: 10.4% vs. 53.7%, p = 0.021).

CONCLUSION

Definitive irradiation for both primary and oligo-metastatic sites for selected IVB patients is a feasible treatment strategy. Metastatic type, number of metastatic sites, and pre-treatment tumor diameter were significant prognostic factors. Neoadjuvant chemotherapy, the lymph nodal metastatic type (supraclavicular or inguinal), and number of lymphatic metastatic sites failed to reach statistical significance as prognostic factors.

Nomogram for prognosis of elderly patients with cervical cancer who receive combined radiotherapy

This retrospective study identified prognostic factors to help guide the clinical treatment of elderly patients (≥ 65 years) with cervical cancer who had undergone radiotherapy. A personalized model to predict 3- and 5-years survival was developed. A review was conducted of 367 elderly women with cervical cancer (staged II-III) who had undergone radiotherapy in our hospital between January 2012 and December 2016. The Cox proportional hazards regression model was used for survival analysis that considered age, hemoglobin, squamous cell carcinoma antigen, pathologic type, stage, pelvic lymph node metastasis status, and others. A nomogram was constructed to predict the survival rates. The median follow-up time was 71 months (4-118 months). The 3- (5-) years overall, progression-free, local recurrence-free, and distant metastasis-free survival rates were, respectively, 91.0% (84.4%), 92.3% (85.9%), 99.18% (99.01%), and 99.18% (97.82%). The following were significant independent prognostic factors for overall survival: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The C-index of the line chart was 0.699 (95% CI 0.652-0.746). The areas under the receiver operating characteristic curves for 3- and 5-years survival were 0.751 and 0.724. The nomogram was in good concordance with the actual survival rates. The independent prognostic factors for overall survival in elderly patients with cervical cancer after radiotherapy were: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The novel prognostic nomogram based on these factors showed good concordance with the actual survival rates and can be used to guide personalized clinical treatment.

Establishment of a nomogram model for prediction of postoperative heterochronous liver metastasis in young and middle-aged patients with rectal cancer

BACKGROUND

The incidence of rectal cancer is increasing year by year. Radical surgery is often used for the treatment of rectal cancer in clinical practice, but postoperative liver metastasis has become an important reason for the increase in mortality. Therefore, establishing a model to predict the trend of metachronous liver metastasis has become a research focus. Nomogram model has been widely used in the medical field, but there has been no widely accepted nomogram model available for prediction of metachronous liver metastasis after rectal cancer surgery.

AIM

To constuct a nomogram model based on the risk factors for postoperative metachronous liver metastasis in young and middle-aged patients with rectal cancer, and to evaluate the performance of the model for predicting the risk of postoperative metachronous liver metastasis, so as to provide some guidance for clinical prevention and treatment.

METHODS

A total of 120 young and middle-aged patients with rectal cancer admitted to our hospital from March 2019 to February 2022 were selected as research subjects to observe the incidence of postoperative heterochronous liver metastasis. Univariate and multivariate Logistic regression analyses were performed to identify the risk factors for postoperative heterochronous liver metastasis and to construct a nomogram model. ROC curve, decision curve, and correction curve analyses were used to verify the value of nomogram model for the prediction of postoperative heterochronous liver metastasis.

RESULTS

The incidence of anomalous liver metastasis 1 year after surgery was 23.33% in 120 young and middle-aged patients with rectal cancer. Low differentiation, lymph node metastasis, depth of invasion (T3/T4), margin width of primary cancer < 2 cm, high expression of peripheral blood telomerase reverse transcriptase (hTERT), and elevated serum levels of carcinoembryonic antigen (CEA), vascular endothelial growth factor (VEGF), lemur tyrosine kinase-3 (LMTK3), squamous cell carcinoma-associated antigen (SCC-Ag), and axon-guided factor-1 (Netrin-1) were identified to be risk factor for postoperative hetero-chronic liver metastasis (P < 0.05). The C-index and area under the curve of the nomogram model were 0.860 and 0.957, respectively, and the net benefit value was high (P < 0.05).

CONCLUSION

Low differentiation, lymph node metastasis, depth of invasion (T3/T4), margin width of primary cancer < 2 cm, high expression of hTERT in peripheral blood, and elevated levels of serum CEA, VEGF, LMTK3, SC-AG and Netrin-1 are risk factors for postoperative xenotemporal liver metastasis in young and middle-aged patients with rectal cancer. Based on the above risk factors, a nomogram model has been established to predict postoperative heterochronous liver metastasis in such patients.

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

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.

Nomogram for prognosis of elderly patients with cervical cancer who receive combined radiotherapy.. [DOI: 10.21203/rs.3.rs-2367005/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective: This retrospective study identified prognostic factors to help guide the clinical treatment of elderly patients (≥65 y) with cervical cancer who had undergone radiotherapy. A personalized model to predict 3- and 5-year survival was developed. Methods: A review was conducted of 367 elderly women with cervical cancer (staged II-III) who had undergone radiotherapy in our hospital between January 2012 and December 2016. The Cox proportional hazards regression model was used for survival analysis that considered age, hemoglobin, squamous cell carcinoma antigen, pathologic type, stage, pelvic lymph node metastasis status, and others. A nomogram was constructed to predict the survival rates. Results: The median follow-up time was 71 months (4-118 mo). The 3- (5-) year overall, progression-free, local recurrence-free, and distant metastasis-free survival rates were, respectively, 91.0% (84.4%), 92.3% (85.9%), 99.18% (99.01%), and 99.18% (97.82%). The following were significant independent prognostic factors for overall survival: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The C-index of the line chart was 0.699 (95% CI: 0.652-0.746). The areas under the receiver operating characteristic curves for 3- and 5-year survival were 0.751 and 0.724. The nomogram was in good concordance with the actual survival rates. Conclusions: The independent prognostic factors for overall survival in elderly patients with cervical cancer after radiotherapy were: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The novel prognostic nomogram based on these factors can be an asset for personalized clinical management.

Analysis of Treatment Outcomes and Prognosis After Concurrent Chemoradiotherapy for Locally Advanced Cervical Cancer

The aims of this study were to investigate the short-term and long-term efficacies and chronic radiotoxicity of concurrent chemoradiotherapy (CCRT) combined with image-guided adaptive brachytherapy (IGABT) in patients with locally advanced cervical cancer (LACC) and identify prognostic factors in this patient population. The clinical data of 204 patients with cervical cancer who completed CCRT and subsequent brachytherapy in our hospital between February 2015 and March 2017 were retrospectively analyzed. Short-term and long-term outcomes, chronic radiotoxicity, and prognostic factors were assessed. The median follow-up was 61.1 months. The short-term objective response (OR) rate was 85%. Lymph node metastasis before treatment was an independent predictor of OR (HR = 6.290, 95% CI: 2.211-17.897, p = 0.001). Fifty-two patients developed recurrence, with a median recurrence-free survival of 9.9 months (range, 2.4-52.2 months) and a post-recurrence survival of 12.1 months (range, 2.9-58.1 months). At 3 years, the cumulative incidence of overall recurrence was 26% (95% CI: 17-36). Multivariate analysis showed that Stage IIIB (HR = 2.332, 95% CI: 1.195-4.551, p = 0.013; reference, Stage IIB) and lymph node metastasis (HR = 4.462, 95% CI: 2.365-8.419, p < 0.001) were significant independent predictors of recurrence. Fifty-three patients developed chronic radiation proctitis (CRP). The incidence of severe CRP was approximately 5%, and the average rectal D2cm3 accumulation in patients with severe CRP was 73.4 Gy which is 3.9 Gy higher than that in patients without CRP (p = 0.013). At 4 years, the overall survival (OS) and disease-free survival rates were 65% and 62%, respectively, and lymph node metastasis before treatment was an independent prognostic risk factor for OS. The short-term and long-term efficacies of CCRT combined with IGABT for the treatment of LACC patients were relatively satisfactory. However, the short-term and long-term efficacies of patients with lymph node metastasis before treatment were poor. For patients with lymph node metastasis before treatment, more active individualized treatment strategies should be adopted. When designing a radiotherapy plan, it is necessary to strictly limit the rectal D2cm3 accumulation to prevent serious CRP.

Treatment Strategies and Prognostic Factors of 2018 FIGO Stage IIIC Cervical Cancer: A Review

Cervical cancer is the fourth most common malignant tumor globally in terms of morbidity and mortality. The presence of lymph node metastasis (LNM) is an independent prognostic factor for progression-free survival (PFS) and overall survival (OS) in cervical cancer patients. The International Federation of Gynecology and Obstetrics (FIGO) staging system was revised in 2018. An important revision designates patients with regional LNM as stage IIIC, pelvic LNM only as stage IIIC1, and para-aortic LNM as stage IIIC2. However, the current staging system is only based on the anatomical location of metastatic lymph nodes (LNs). It does not consider other LN status parameters, which may limit its prognostic significance to a certain extent and needs further exploration and confirmation in the future. The purpose of this review is to summarize the choice of treatment for stage IIIC cervical cancer and the effect of different LN status parameters on prognosis.