scholarly journals Predictive value of preoperative serum squamous cell carcinoma antigen level for lymph node metastasis in early-stage cervical squamous cell carcinoma

Medicine ◽  
2021 ◽  
Vol 100 (33) ◽  
pp. e26960
Author(s):  
Chenggong Zhu ◽  
Wenqing Zhang ◽  
Xiuying Wang ◽  
Lanzhou Jiao ◽  
Liyan Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Cervical Squamous Cell Carcinoma ◽  
Antigen Level ◽  
Squamous Cell Carcinoma Antigen ◽  
Node Metastasis ◽  
Preoperative Serum

scholarly journals Predictive significance of CYFRA21-1, squamous cell carcinoma antigen and carcinoembryonic antigen for lymph node metastasis in patients with esophageal squamous cancer

2019 ◽  
Vol 34 (2) ◽  
pp. 200-204 ◽  
Author(s):  
Xinyu Mei ◽  
Xiaodong Zhu ◽  
Lei Zuo ◽  
Hanran Wu ◽  
Mingfa Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cell Carcinoma ◽  
Carcinoembryonic Antigen ◽  
Squamous Cell ◽  
Cytokeratin 19 ◽  
Squamous Cell Carcinoma Antigen ◽  
Node Metastasis ◽  
Preoperative Serum

From January 2018 to May 2018, 108 patients with thoracic esophageal cancer underwent esophagectomy with two- to three-field lymph node dissection. Serum cytokeratin 19 fragment antigen 21-1 (CYFRA21-1), squamous cell carcinoma antigen, and carcinoembryonic antigen levels were detected before surgery. Preoperative serum levels of CYFRA21-1 and squamous cell carcinoma antigen were correlated closely with pN stage ( P = 0.000 and P = 0.045). CYFRA21-1 and pathological T status were independent predictors of lymph node metastasis ( P = 0.000). The area under the curve values of CYFRA21-1 and squamous cell carcinoma antigen for predicting lymph node metastasis were 0.731 ( P =0.000) and 0.650 ( P =0.007), respectively. Our study demonstrated that serum CYFRA21-1 and squamous cell carcinoma antigen levels were associated with lymph node metastasis in esophageal squamous cell carcinoma, especially in patients at the early T stage. The preoperative serum CYFRA21-1 level was an independent predictor of lymph node metastasis.

scholarly journals A preoperative radiomics model for the identification of lymph node metastasis in patients with early-stage cervical squamous cell carcinoma

2020 ◽  
Vol 93 (1116) ◽  
pp. 20200358
Author(s):  
Lifen Yan ◽  
Huasheng Yao ◽  
Ruichun Long ◽  
Lei Wu ◽  
Haotian Xia ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Deep Learning ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Cervical Squamous Cell Carcinoma ◽  
Node Metastasis ◽  
Deep Learning Features ◽  
Radiomics Signature

Objectives: To develop and validate a radiomics model for preoperative identification of lymph node metastasis (LNM) in patients with early-stage cervical squamous cell carcinoma (CSCC). Methods: Total of 190 eligible patients were randomly divided into training (n = 100) and validation (n = 90) cohorts. Handcrafted features and deep-learning features were extracted from T2W fat suppression images. The minimum redundancy maximum relevance algorithm and LASSO regression with 10-fold cross-validation were used for key features selection. A radiomics model that incorporated the handcrafted-signature, deep-signature, and squamous cell carcinoma antigen (SCC-Ag) levels was developed by logistic regression. The model performance was assessed and validated with respect to its calibration, discrimination, and clinical usefulness. Results: Three handcrafted features and three deep-learning features were selected and used to build handcrafted- and deep-signature. The model, which incorporated the handcrafted-signature, deep-signature, and SCC-Ag, showed satisfactory calibration and discrimination in the training cohort (AUC: 0.852, 95% CI: 0.761–0.943) and the validation cohort (AUC: 0.815, 95% CI: 0.711–0.919). Decision curve analysis indicated the clinical usefulness of the radiomics model. The radiomics model yielded greater AUCs than either the radiomics signature (AUC = 0.806 and 0.779, respectively) or the SCC-Ag (AUC = 0.735 and 0.688, respectively) alone in both the training and validation cohorts. Conclusion: The presented radiomics model can be used for preoperative identification of LNM in patients with early-stage CSCC. Its performance outperforms that of SCC-Ag level analysis alone. Advances in knowledge: A radiomics model incorporated radiomics signature and SCC-Ag levels demonstrated good performance in identifying LNM in patients with early-stage CSCC.

Correlation Between Squamous Cell Carcinoma Antigen Level and the Clinicopathological Features of Early-Stage Cervical Squamous Cell Carcinoma and the Predictive Value of Squamous Cell Carcinoma Antigen Combined With Computed Tomography Scan for Lymph Node Metastasis

2017 ◽  
Vol 27 (9) ◽  
pp. 1935-1942 ◽  
Author(s):  
Dianbo Xu ◽  
Danbo Wang ◽  
Shuo Wang ◽  
Ye Tian ◽  
Zaiqiu Long ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cervical Squamous Cell Carcinoma ◽  
International Federation ◽  
Tumor Diameter ◽  
Squamous Cell Carcinoma Antigen ◽  
Node Metastasis ◽  
Gynecology And Obstetrics

ObjectiveThe aim of this study was to analyze the relationship between serum squamous cell carcinoma antigen (SCC-Ag) and the clinicopathological features of cervical squamous cell carcinoma. The value of SCC-Ag and computed tomography (CT) for predicting lymph node metastasis (LNM) was evaluated.MethodsA total of 197 patients with International Federation of Gynecology and Obstetrics stages IB to IIA cervical squamous cell carcinoma who underwent radical surgery were enrolled in this study. The SCC-Ag was measured, and CT scans were used for the preoperative assessment of lymph node status.ResultsIncreased preoperative SCC-Ag levels were associated with International Federation of Gynecology and Obstetrics stage (P = 0.001), tumor diameter of greater than 4 cm (P < 0.001), lymphovascular invasion (P = 0.001), LNM (P < 0.001), and greater than one half stromal infiltration (P < 0.001). Multivariate analysis identified LNM (P < 0.001, odds ratio [OR] = 4.399), tumor diameter of greater than >4 cm (P = 0.001, OR = 4.019), and greater than one half stromal infiltration (P = 0.002, OR = 3.680) as independent factors affecting SCC-Ag greater than or equal to 2.35 ng/mL. In the analysis of LNM, SCC-Ag greater than or equal to 2.35 ng/mL (P < 0.001, OR = 4.825) was an independent factor for LNM. The area under the receiver operator characteristic curve (AUC) of SCC-Ag was 0.763 for all patients, and 0.805 and 0.530 for IB1 + IIA1 and IB2 + IIA2 patients, respectively; 2.35 ng/mL was the optimum cutoff for predicting LNM. The combination of CT and SCC-Ag showed a sensitivity and specificity of 82.9% and 66% in parallel tests, and 29.8% and 93.3% in serial tests, respectively.ConclusionsThe increase of SCC-Ag level in the preoperative phase means that there may be a pathological risk factor for postoperative outcomes. The SCC-Ag (≥2.35 ng/mL) may be a useful marker for predicting LNM of cervical cancer, especially in stages IB1 and IIA1, and the combination of SCC-Ag and CT may help identify patients with LNM to provide them with the most appropriate therapeutic approach.

scholarly journals A nomogram to predict lymph node metastasis risk for early esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofeng Duan ◽  
Xiaobin Shang ◽  
Jie Yue ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Derivation Cohort ◽  
Node Metastasis

Abstract Background A nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC). Methods We used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection. The risk of LNM was stratified based on the nomogram model. The nomogram was validated by an independent cohort which included early ESCC patients underwent esophagectomy between July 2018 and December 2019. Results Of the 223 patients, 36 (16.1%) patients had LNM. The following three variables were confirmed as LNM risk factors and were included in the nomogram model: tumor differentiation (odds ratio [OR] = 3.776, 95% confidence interval [CI] 1.515–9.360, p = 0.004), depth of tumor invasion (OR = 3.124, 95% CI 1.146–8.511, p = 0.026), and tumor size (OR = 2.420, 95% CI 1.070–5.473, p = 0.034). The C-index was 0.810 (95% CI 0.742–0.895) in the derivation cohort (223 patients) and 0.830 (95% CI 0.763–0.902) in the validation cohort (80 patients). Conclusions A validated nomogram can predict the risk of LNM via risk stratification. It could be used to assist in the decision-making process to determine which patients should undergo esophagectomy and for which patients with a low risk of LNM, curative endoscopic resection would be sufficient.

Pretreatment serum squamous cell carcinoma antigen: a newly identified prognostic factor in early-stage cervical carcinoma.

1996 ◽  
Vol 14 (1) ◽  
pp. 111-118 ◽  
Author(s):  
J M Duk ◽  
K H Groenier ◽  
H W de Bruijn ◽  
H Hollema ◽  
K A ten Hoor ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Vascular Invasion ◽  
Early Stage ◽  
Lesion Size ◽  
Squamous Cell Carcinoma Antigen ◽  
Clinicopathologic Characteristics ◽  
Pretreatment Serum

PURPOSE To investigate the prognostic value of pretreatment serum squamous cell carcinoma antigen (SCC-ag) levels in patients with cervical squamous cell carcinoma in relation to well-established conventional risk factors. PATIENTS AND METHODS Sera from 653 women treated for squamous cervical cancer between 1978 and 1994 were analyzed for the presence of SCC-ag and related to clinicopathologic characteristics and patient outcome using univariate and multivariate analyses. RESULTS Increased pretreatment SCC-ag levels correlated strongly with unfavorable clinicopathologic characteristics (International Federation of Gynecology and Obstetrics [FIGO] stages IB to IV [P < or = .00005]; stages IB and IIA: tumor size [P = .0236], deep stromal infiltration [P = .00009], and lymph node metastasis [P = .0001]). After multivariate analysis, elevated pretreatment serum SCC-ag levels (P = .001), lesion size (P = .043), and vascular invasion by tumor cells (P = .001) were independent predictors for the presence of lymph node metastases. In Cox regression analysis, controlling for SCC-ag, lesion size, grade, vascular invasion, depth of stromal infiltration, and lymph node status only the initial SCC-ag level had a significant independent effect on survival (P = .0152). Even in node-negative patients, the risk of recurrence was three times higher if the SCC-ag level was elevated before therapy. CONCLUSION The determination of pretreatment serum SCC-ag level provides a new prognostic factor in early-stage disease, particularly in patients with small tumor size. In future trials to assess the value of new treatment strategies, pretreatment serum SCC-ag levels can be used to help identify patients with a poor prognosis.

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