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 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 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.

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.

scholarly journals High α B-crystallin and p53 co-expression is associated with poor prognosis in ovarian cancer

2019 ◽  
Vol 39 (6) ◽  
Author(s):  
Lin Tan ◽  
Ling Sha ◽  
Ning Hou ◽  
Mei Zhang ◽  
Qian Ma ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cancer Patients ◽  
Distant Metastasis ◽  
Tumor Size ◽  
Prognostic Value ◽  
Pathological Grade ◽  
P53 Expression ◽  
Node Metastasis

Abstract Objectives: The present study investigated the correlation between α B-crystallin (CRYAB, HSPB5) and p53 expression in ovarian cancer and further analyzed the relationship between their expression and clinicopathology and the prognostic value of their co-expression in ovarian cancer. Methods: CRYAB and p53 expression was assessed using immunohistochemistry on ovarian cancer tumor tissues from 103 cases and validated in an independent group of 103 ovarian cancer patients. Results: High CRYAB and p53 expression rates in ovarian cancer tissues were 61.17% (63/103) and 57.28% (59/103), respectively, and their expression was positively correlated (r = 0.525, P=0.000). High CRYAB expression was significantly correlated with tumor size (P=0.028), lymph node metastasis (P=0.000), distant metastasis (P=0.005), tumor node metastasis (TNM) stage (P=0.002), and survival (P=0.000), while high p53 expression was significantly correlated with tumor size (P=0.006), pathological grade (P=0.023), lymph node metastasis (P=0.001), and survival (P=0.000). Further studies found that the high CRYAB and p53 co-expression was also significantly correlated with pathological grade (P=0.024), lymph node metastasis (P=0.000), Distant metastasis (P=0.015), TNM stage (P=0.013), and survival (P=0.000). High expression of either CRYAB or p53 and high co-expression of CRYAB and p53 were significantly correlated with poor disease-free survival (DFS) and overall survival (OS), respectively (P<0.05). Patients with high CRYAB and p53 co-expression had the worst prognoses among the groups. In addition, multivariate Cox regression models showed that high expression of either CRYAB or p53 and high co-expression of CRYAB and p53 were independent prognostic factors for DFS and OS (P<0.05). Moreover, the positive correlation and prognostic value of CRYAB and p53 expression were verified in another independent dataset. Conclusions: We demonstrated that patients with high CRYAB and p53 co-expression in ovarian cancer have significantly increased risks of recurrence, metastasis, and death compared with other patients. Therefore, more frequent follow-up of patients with high CRYAB and p53 co-expression is required. Our results also suggest that combination therapy with CRYAB inhibitors and p53 blockers may benefit future treatment of ovarian cancer patients with high co-expression of CRYAB and p53.

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.

scholarly journals Development of a Novel Prognostic Model for Predicting Lymph Node Metastasis in Early Colorectal Cancer: Analysis Based on the Surveillance, Epidemiology, and End Results Database

2021 ◽  
Vol 11 ◽  
Author(s):  
Ji Hyun Ahn ◽  
Min Seob Kwak ◽  
Hun Hee Lee ◽  
Jae Myung Cha ◽  
Hyun Phil Shin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Predictive Model ◽  
Tumor Size ◽  
Prediction Models ◽  
Early Colorectal Cancer ◽  
Support Vector ◽  
Node Metastasis ◽  
End Results

BackgroundIdentification of a simplified prediction model for lymph node metastasis (LNM) for patients with early colorectal cancer (CRC) is urgently needed to determine treatment and follow-up strategies. Therefore, in this study, we aimed to develop an accurate predictive model for LNM in early CRC.MethodsWe analyzed data from the 2004-2016 Surveillance Epidemiology and End Results database to develop and validate prediction models for LNM. Seven models, namely, logistic regression, XGBoost, k-nearest neighbors, classification and regression trees model, support vector machines, neural network, and random forest (RF) models, were used.ResultsA total of 26,733 patients with a diagnosis of early CRC (T1) were analyzed. The models included 8 independent prognostic variables; age at diagnosis, sex, race, primary site, histologic type, tumor grade, and, tumor size. LNM was significantly more frequent in patients with larger tumors, women, younger patients, and patients with more poorly differentiated tumor. The RF model showed the best predictive performance in comparison to the other method, achieving an accuracy of 96.0%, a sensitivity of 99.7%, a specificity of 92.9%, and an area under the curve of 0.991. Tumor size is the most important features in predicting LNM in early CRC.ConclusionWe established a simplified reproducible predictive model for LNM in early CRC that could be used to guide treatment decisions. These findings warrant further confirmation in large prospective clinical trials.

scholarly journals Tumor size measured by multidetector CT in resectable colon cancer: Correlation with regional lymph node metastasis

2020 ◽  
Author(s):  
Anna Mou ◽  
Hang Li ◽  
Xiaoli Chen ◽  
Fanghua Fan ◽  
Hong Pu
Keyword(s):  
Colon Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Tumor Size ◽  
Univariate Analysis ◽  
Node Metastasis ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct

Abstract Background : The aim of our study was to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to evaluate lymph node metastasis (LNM) in patients with resectable colon cancer. Methods: This retrospective study consisted of 106 consecutive patients with colon cancer who underwent radical surgery within 1 week after contrast enhanced-CT scan. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), t umor maximum cross-sectional area (Tare) and tumor volume (Tvol) were measured on contrast enhanced-CT images and correlated with pathologic LNM and N stages using univariate analysis, logistic regression analysis and receiver operating characteristic (ROC) curve analysis. Results: The inter - (intraclass correlation coefficient [ICC]=0.94, 0.81, 0.97, 0.99) and intraobserver (ICC=0.95, 0.93, 0.91 and 0.99) reproducibility of Tlen, Tdia, Tare and Tvol parameters measurement is excellent. Univariate analysis showed Tlen, Tdia, Tare, and Tvol could predict LNM (all P <0.05), whereas Tvol was an independent risk factor for LNM (odds ratio =1.09; 95% confidence interval, 1.02-1.17; P =0.017) by logistic regression analysis. Tlen, Tdia, Tare and Tvol could distinguish between N0 and N1, N0 and N2, N0 and N1-2, and N0-1 and N2 disease (all P < 0.05). The area under the ROC (AUC) was higher for Tvol than for Tlen, Tdia and Tare in identifying LNM (AUC =0.83, 0.82, 0.69, 0.79, respectively) and distinguishing N0 from N1 (AUC =0.79, 0.78, 0.63, 0.74, respectively), N0 from N2 (AUC =0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 (AUC =0.84, 0.79, 0.76, 0.83, respectively). Conclusion: Tlen , Tdia, Tare and Tvol measured with MDCT correlated with regional LNM in resectable colon cancer. In particular, Tvol showed the most potential for noninvasive preoperative evaluation of regional LNM.

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