scholarly journals Can CA-125 Predict Lymph Node Metastasis in Epithelial Ovarian Cancers in Turkish Population?

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Sinem Sudolmuş ◽  
Nadiye Köroğlu ◽  
Gökhan Yıldırım ◽  
Volkan Ülker ◽  
Ahmet Gülkılık ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Logistic Regression Analysis ◽  
Geometric Mean ◽  
Turkish Population ◽  
Ca 125 ◽  
Node Metastasis ◽  
Preoperative Serum

Objective. The role of single preoperative serum CA-125 levels in predicting pelvic or paraaortic lymph node metastasis in patients operated for epithelial ovarian cancer has been investigated.Methods. 176 patients diagnosed with epithelial ovarian carcinoma after staging laparotomy between January 2002 and May 2010 were evaluated retrospectively.Results. The mean, geometric mean, and median of preoperative serum CA-125 levels were 632,6, 200,29, and 191,5 U/mL, respectively. The cut-off value predicting lymph node metastases in the ROC curve was 71,92 U/mL, which is significant in logistic regression analysis (P=0.005). The preoperative log CA-125 levels were also statistically significant in predicting lymph node metastasis in logistic regression analysis (P=0.008).Conclusions. The tumor marker CA-125, which increases with grade independent of the effect of stage in EOC, is predictive of lymph node metastasis with a high rate of false positivity in Turkish population. The high false positive rate may obscure the predictive value of CA-125.

scholarly journals The prognostic value of tumor size in penile cancer: A Surveillance,Epidemiology, and End Results database study

2020 ◽  
Author(s):  
Wenwen Zheng ◽  
Zhiyu Zhang ◽  
Xilei Xie ◽  
Weiwei Zhu ◽  
Kangqi Li ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Logistic Regression Analysis ◽  
Tumor Size ◽  
Prognostic Value ◽  
Penile Cancer ◽  
Node Metastasis ◽  
End Results

Abstract Background: The objective of this study was to investigate the prognostic value of tumor size on cancer-specific mortality (CSM) and lymph node metastasis for patients with penile squamous cell carcinoma (PSCC).Method: The patients diagnosed with PSCC between 2004 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Restricted cubic spline functions were calculated to characterize the association between tumor size and the risk of CSM. The competing-risks model was used to evaluate the impact of tumor size on the cumulative incidence of CSM. The logistic regression analysis was performed to examine the association between tumor size and lymph node metastasis.Results: Totally, 1365 PSCC patients were analyzed, with 52.3% having tumors ≤30 mm, and 47.7% >30 mm. The restricted cubic splines showed that the risks of CSM increased as tumors enlarged. Following adjustment of competing events, the PSCC patients with tumors >30 mm were more likely to succumb to CSM in comparison with those with tumors ≤30 mm (hazard ratio [HR]=1.57, 95% confidence interval [CI]: 1.23-2.01, P<0.001). In subgroup analyses, tumor size >30 mm was significantly associated with an increased risk of CSM relative to tumor size ≤30 mm among patients with T1 (HR=1.56, 95%CI: 1.03-2.37, P=0.036) and T3 (HR=2.51, 95%CI: 1.41-4.45, P=0.002) classifications. On logistic regression analysis, tumors >30 mm were significantly associated with lymph node metastasis (odds ratio [OR]=1.46, 95% CI: 1.03-2.07, P=0.034).Conclusion: Larger tumors (>30 mm) were significantly associated with higher risks of CSM and increased likelihood of lymph node metastasis for PSCC patients, which could be integrated into the development of a staging system for penile cancer.

scholarly journals The prognostic value of tumor size in penile cancer: A Surveillance, Epidemiology, and End Results database study

2021 ◽  
Author(s):  
Wenwen Zheng ◽  
Zhiyu Zhang ◽  
Wei Jiang ◽  
Jiaojiao Chen ◽  
Shengqiang Yu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Logistic Regression Analysis ◽  
Tumor Size ◽  
Prognostic Value ◽  
Penile Cancer ◽  
Node Metastasis ◽  
End Results

Abstract Background The objective of this study was to investigate the prognostic value of tumor size on cancer-specific mortality (CSM) and lymph node metastasis for patients with penile squamous cell carcinoma (PSCC). Methods The patients diagnosed with PSCC between 2004 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Restricted cubic spline functions were calculated to characterize the association between tumor size and the risk of CSM. The competing-risks model was used to evaluate the impact of tumor size on the cumulative incidence of CSM. The logistic regression analysis was performed to examine the association between tumor size and lymph node metastasis. Results Totally, 1365 PSCC patients were analyzed, with 52.3% having tumors ≤ 30 mm, and 47.7% >30 mm. The restricted cubic splines showed that the risks of CSM increased as tumors enlarged. Following adjustment of competing events, the PSCC patients with tumors > 30 mm were more likely to succumb to CSM in comparison with those with tumors ≤ 30 mm (hazard ratio [HR] = 1.57, 95% confidence interval [CI]: 1.23–2.01, P < 0.001). In subgroup analyses, tumor size > 30 mm was significantly associated with an increased risk of CSM relative to tumor size ≤ 30 mm among patients with T1 (HR = 1.56, 95%CI: 1.03–2.37, P = 0.036) and T3 (HR = 2.51, 95%CI: 1.41–4.45, P = 0.002) classifications. On logistic regression analysis, tumors > 30 mm were significantly associated with lymph node metastasis (odds ratio [OR] = 1.46, 95% CI: 1.03–2.07, P = 0.034). Conclusions Larger tumors (> 30 mm) were significantly associated with higher risks of CSM and increased likelihood of lymph node metastasis for PSCC patients, which could be integrated into the development of a staging system for penile cancer.

scholarly journals A Novel RNA-Seq-Based Model for Preoperative Prediction of Lymph Node Metastasis in Oral Squamous Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Bo Qiao ◽  
Min Zhao ◽  
Jing Wu ◽  
Huan Wu ◽  
Yiming Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Seq ◽  
Node Metastasis ◽  
Preoperative Prediction

Objective. To develop and validate a novel RNA-seq-based nomogram for preoperative prediction of lymph node metastasis (LNM) for patients with oral squamous cell carcinoma (OSCC). Methods. RNA-seq data for 276 OSCC patients (including 157 samples with LNM and 119 without LNM) were downloaded from TCGA database. Differential expression analysis was performed between LNM and non-LNM of OSCC. These samples were divided into a training set and a test set by a ratio of 9 : 1 while the relative proportion of the non-LNM and LNM groups was kept balanced within each dataset. Based on clinical features and seven candidate RNAs, we established a prediction model of LNM for OSCC using logistic regression analysis. Tenfold crossvalidation was utilized to examine the accuracy of the nomogram. Decision curve analysis was performed to evaluate the clinical utility of the nomogram. Results. A total of 139 differentially expressed RNAs were identified between LNM and non-LNM of OSCC. Seven candidate RNAs were screened based on FPKM values, including NEURL1, AL162581.1 (miscRNA), AP002336.2 (lncRNA), CCBE1, CORO6, RDH12, and AC129492.6 (pseudogene). Logistic regression analysis revealed that the clinical N stage (p<0.001) was an important factor to predict LNM. Moreover, three RNAs including RDH12 (p value < 0.05), CCBE1 (p value < 0.01), and AL162581.1 (p value < 0.05) could be predictive biomarkers for LNM in OSCC patients. The average accuracy rate of the model was 0.7661, indicating a good performance of the model. Conclusion. Our findings constructed an RNA-seq-based nomogram combined with clinicopathology, which could potentially provide clinicians with a useful tool for preoperative prediction of LNM and be tailored for individualized therapy in patients with OSCC.

Inverse Correlation between Age and Risk of Lymph Node Metastasis in Bladder Cancer

2020 ◽  
Author(s):  
Wenchao Ma ◽  
Tiantian Wang ◽  
Yadong Guo ◽  
Ruiliang Wang ◽  
Ji Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bladder Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Marital Status ◽  
Inverse Correlation ◽  
Factors Affecting ◽  
Node Metastasis

Abstract Background Bladder cancer (BCa) is the most common malignant tumor in humans and brings about a huge burden on the international community and on the families of those it affects. Lymph node metastasis (LNM) is an important factor affecting the prognosis of BCa. This study aimed to investigate the risk factors affecting LNM.Patients and Methods This study involved 5517 patients who underwent BCa-related surgery between 2006 and 2015. The multivariate logistic regression analysis was used to evaluate the association between age and LNM. The overall survival (OS) and cancer-specific survival (CSS) were analyzed using the Kaplan–Meier method. The multivariable Cox regression model was used to evaluate independent risk factors affecting OS and CSS.Results We retrieved 5517 cases from SEER database, including 148 patients aged 40-49 years, 726 aged 50-59 years, 1541 aged 60-69 years, 1538 aged 70-79 years and 1564 aged 80+ years. The rates of LNM were 20.27%, 16.94%, 11.94%, 9.95% and 6.46% for patients aged 40-49, 50-59, 60-69, 70-79 and 80+ years. We found an inverse correlation between age at diagnosis and risk of LNM from the logistic regression analysis in three modules(Module 1: P-value for trend, crude, no adjustment < 0.001; Module 2: P-value for trend adjusted for sex, race, insurance status, and marital status < 0.001; Module 3: P-value for trend adjusted for sex, race, insurance, marital status, size, grade, and metastasis < 0.001). Compared with patients aged 40–49 years, patients aged 50–59 years (OR = 0.752; 95% CI, 0.470–1.204; P = 0.236), 60–69 years (OR = 0.517; 95% CI, 0.329–0.815; P = 0.004), 70–79 years (OR = 0.375; 95% CI, 0.237–0.595; P < 0.001), and 80+ years (OR = 0.248; 95% CI, 0.154–0.398; P < 0.001) had a lower risk of LNM.ConclusionsYounger age at diagnosis was associated with a higher risk of LNM in patients with BCa. Excepting this, grade and metastasis were also risk factors for LNM.

Significance of preoperative serum CA-125 levels in the prediction of lymph node metastasis in epithelial ovarian cancer

2008 ◽  
Vol 87 (11) ◽  
pp. 1136-1142 ◽  
Author(s):  
Hee Seung Kim ◽  
Noh Hyun Park ◽  
Hyun Hoon Chung ◽  
Jae Weon Kim ◽  
Yong Sang Song ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Epithelial Ovarian Cancer ◽  
Ca 125 ◽  
Node Metastasis ◽  
Preoperative Serum

Use of preoperative serum CA-125 levels for prediction of lymph node metastasis and prognosis in endometrial cancer

2006 ◽  
Vol 85 (12) ◽  
pp. 1501-1505 ◽  
Author(s):  
Hyun Hoon Chung ◽  
Jae Weon Kim ◽  
Noh-Hyun Park ◽  
Yong-Sang Song ◽  
Soon-Beom Kang ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Ca 125 ◽  
Node Metastasis ◽  
Preoperative Serum

scholarly journals Tumor size measured by multidetector CT in resectable colon cancer: correlation with regional lymph node metastasis and N stage

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Anna Mou ◽  
Hang Li ◽  
Xiao-li Chen ◽  
Yang-hua Fan ◽  
Hong Pu
Keyword(s):  
Colon Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Logistic Regression Analysis ◽  
Tumor Size ◽  
Odds Ratio ◽  
Univariate Logistic Regression Analysis ◽  
Node Metastasis ◽  
N Stage

Abstract Background Lymph node metastasis (LNM) is a risk factor for poor long-term outcomes and a prognostic factor for disease-free survival in colon cancer. Preoperative lymph node status evaluation remains a challenge. The purpose of this study is to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to predict LNM and N stage in colon cancer. Material and methods One hundred six patients with colon cancer who underwent radical surgery within 1 week of MDCT scan were enrolled. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), tumor maximum cross-sectional area (Tare), and tumor volume (Tvol) were measured to be correlated with pathologic LNM and N stage using univariate logistic regression analysis, multivariate logistic analysis, and receiver operating characteristic (ROC) curve analysis. Results The inter- and intraobserver reproducibility of Tlen (intraclass correlation coefficient [ICC] = 0.94, 0.95, respectively), Tdia (ICC = 0.81, 0.93, respectively), Tare (ICC = 0.97, 0.91, respectively), and Tvol (ICC = 0.99, 0.99, respectively) parameters measurement are excellent. Univariate logistic regression analysis showed that there were significant differences in Tlen, Tdia, Tare, and Tvol between positive and negative LNM (p < 0.001, 0.001, < 0.001, < 0.001, respectively). Multivariate logistic regression analysis revealed that Tvol was independent risk factor for predicting LNM (odds ratio, 1.082; 95% confidence interval for odds ratio, 1.039, 1.127, p<0.001). Tlen, Tdia, Tare, and Tvol could distinguish N0 from N1 stage (p < 0.001, 0.041, < 0.001, < 0.001, respectively), N0 from N2 (all p < 0.001), N0 from N1-2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively), and N0-1 from N2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively). The area under the ROC curve (AUC) was higher for Tvol than that of Tlen, Tdia, and Tare in identifying LNM (AUC = 0.83, 0.82, 0.69, 0.79), and distinguishing N0 from N1 stage (AUC = 0.79, 0.78, 0.63, 0.74), N0 from N2 stage (AUC = 0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 stage (AUC = 0.84, 0.79, 0.76, 0.83, respectively). Conclusion Tumor size was correlated with regional LNM in resectable colon cancer. In particularly, Tvol showed the most potential for noninvasive preoperative prediction of regional LNM and N stage.

Sign in / Sign up

Export Citation Format

Share Document