Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis

Apmis ◽  
2017 ◽  
Vol 125 (5) ◽  
pp. 431-436 ◽  
Author(s):  
Ebru Cakir ◽  
Ulku Kucuk ◽  
Emel Ebru Pala ◽  
Ozlem Sezer ◽  
Rahmi Gokhan Ekin ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Urothelial Carcinoma ◽  
Logistic Regression Analysis ◽  
Low Grade

scholarly journals The Value of Preoperative Alpha-L-Fucosidase Levels in Evaluation of Malignancy and Differential Diagnosis of Urothelial Neoplasms

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Dongshan Chen ◽  
Naidong Xing ◽  
Zhanwu Cui ◽  
Cong Zhang ◽  
Zhao Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Urothelial Carcinoma ◽  
Logistic Regression Analysis ◽  
Roc Curve ◽  
Curve Analysis ◽  
Clinicopathological Parameters ◽  
Roc Curve Analysis ◽  
Urothelial Tumors

Purpose. To evaluate the role of Alpha-L-fucosidase (AFU) in diagnosis and differential diagnosis of pure urothelial carcinoma (UC), urothelial carcinoma with squamous differentiation (UCSD), and squamous cell carcinoma (SqCC). Methods. A retrospective study was performed for 599 patients who were histologically confirmed with urothelial tumor. Preoperative AFU levels were compared across the distinct subgroups with different clinicopathological parameters. ROC curve analysis and logistic regression analysis were performed to further evaluate the clinical application value of serum AFU levels in diagnosis and differential diagnosis of urothelial tumors. Results. There were no statistically significant differences in the AFU levels between different groups with different malignant degrees (UC versus papilloma and papillary urothelial neoplasm of low malignant potential [PUNLMP], high-grade UC versus low-grade UC, invasive versus noninvasive malignant uroepithelial tumor) and different pathological types (UC, UCSD, and SqCC) (all P>0.05). ROC curve analysis and logistic regression analysis showed that there was no statistically significant association between AFU levels and the tumor characteristics (all P>0.05). Conclusions. Preoperative AFU levels cannot serve as a reliable predictor for malignant degree and differential diagnosis, including pure UC, UCSD, and SqCC of urothelial tumors.

scholarly journals Preoperative positive voided urine cytology predicts poor clinical outcomes in patients with upper tract urothelial carcinoma undergoing nephroureterectomy

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wen Liu ◽  
Zhankun Wang ◽  
Shuai Liu ◽  
Yu Yao ◽  
Yong Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Urothelial Carcinoma ◽  
Logistic Regression Analysis ◽  
Tumor Grade ◽  
Urine Cytology ◽  
Upper Tract Urothelial Carcinoma ◽  
Urinary Cytology ◽  
Upper Tract ◽  
The Impact

Abstract Background Performance of urinary cytology is recommended as the part of a standard diagnostic workup and base surveillance regimens in upper tract urothelial carcinoma (UTUC). However, the effect of positive voided urine cytology (VUC) on UTUC prognosis, compared with negative VUC, has not been fully demonstrated. This study aimed to evaluate the impact of preoperative VUC on predicting intravesical recurrence, disease recurrence, and mortality in patients with UTUC who underwent nephroureterectomy (RNU). Methods Clinicopathological information was collected from 315 UTUC patients treated with RNU. The association between VUC and oncological outcomes was analyzed using the Kaplan–Meier method with log-rank test and Cox proportional hazards regression models. Multiple logistic regression analysis was performed to identify the influence of VUC on tumor grade. Results Preoperative positive VUC, presenting in 101 patients (32%), was significantly associated with tumor multifocality (P = 0.017) and higher tumor grade (P = 0.010). On multivariable Cox regression analyses, preoperative positive VUC was an independent prognostic factor of intravesical recurrence-free survival (RFS) (hazard ratio [HR] = 2.21, 95% confidence interval [CI] 1.06–4.64; P = 0.035), RFS (HR = 1.80, 95% CI 1.08–2.99; P = 0.023), and cancer-specific survival (CSS) (HR = 1.87, 95% CI 1.10–3.18; P = 0.020), but not overall survival (HR = 1.32, 95% CI 0.80–2.18; P = 0.28). Logistic regression analysis revealed that VUC was related to high tumor grade in UTUC (odds ratio = 2.23, 95%CI 1.15–4.52). Conclusion Preoperative positive VUC significantly increases the risk of intravesical recurrence in UTUC patients undergoing RNU. In addition, positive VUC is an adverse predictor of RFS and CSS, which might be due to the association between positive VUC and high tumor grade.

scholarly journals Endoscopic ultrasound in diagnosis of solid pancreatic lesions: Elastography or contrast-enhanced harmonic alone versus the combination

2017 ◽  
Vol 05 (11) ◽  
pp. E1136-E1143 ◽  
Author(s):  
Tanyaporn Chantarojanasiri ◽  
Yoshiki Hirooka ◽  
Hiroki Kawashima ◽  
Eizaburo Ohno ◽  
Takamichi Kuwahara ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Endoscopic Ultrasound ◽  
Inflammatory Pseudotumor ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Contrast Enhanced ◽  
The Individual

Abstract Background and study aims Endoscopic ultrasound (EUS) elastography (EUS-E) and contrast-enhanced harmonic EUS (CH-EUS) are useful methods for the diagnosis of pancreatic lesions. This study aims to compare the accuracy of combined EUS-E and CH-EUS with that of EUS-E or CH-EUS alone in the differential diagnosis of pancreatic solid lesions. Patients and methods One hundred thirty-six patients with solid pancreatic lesions underwent EUS with both EUS-E and CH-EUS were included. Diagnoses were classified as adenocarcinoma, neuroendocrine tumor (NET), and inflammatory pseudotumor in 95, 22, and 19 patients, respectively. EUS records in each case were rearranged into 3 groups: EUS-E, CH-EUS, and combination. Each modality was randomly reviewed by 3 reviewers with different levels of clinical experience. Sensitivity, specificity, and accuracy of each modality according to each diagnosis group were evaluated. For the combined diagnosis populations, the proportions of correct diagnoses among the 3 modalities were compared by using the multivariate logistic regression analysis. Results The accuracies of EUS-E, CH-EUS, and the combination of them were 68.4 %, 65.4 %, and 75.7 %, respectively, for adenocarcinoma group; 83.8 %, 82.4 %, and 86.8 % for NET group; 80.1 %, 78.7 %, and 81.6 % for inflammatory pseudotumor group. The multivariate logistic regression analysis for the combined diagnosis populations showed that the proportion of correct diagnoses when EUS-E and CH-EUS were combined was slightly higher than with the other 2 modalities, although the significant differences among them were not observed. Conclusion EUS-E and CH-EUS combined may improve differential diagnosis of solid pancreatic lesions compared with use of the individual modalities.

scholarly journals Preoperative positive voided urine cytology predicts poor clinical outcomes in patients with upper tract urothelial carcinoma undergoing nephroureterectomy

2020 ◽  
Author(s):  
Wen Liu ◽  
Zhankun Wang ◽  
Shuai Liu ◽  
Yu Yao ◽  
Yong Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Urothelial Carcinoma ◽  
Logistic Regression Analysis ◽  
Tumor Grade ◽  
Urine Cytology ◽  
Upper Tract Urothelial Carcinoma ◽  
Urinary Cytology ◽  
Upper Tract ◽  
The Impact

Abstract Background: Performance of urinary cytology is recommended as the part of a standard diagnostic workup and base surveillance regimens in upper tract urothelial carcinoma (UTUC). However, the effect of positive voided urine cytology (VUC) on UTUC prognosis, compared with negative VUC, has not been fully demonstrated. This study aimed to evaluate the impact of preoperative VUC on predicting intravesical recurrence, disease recurrence, and mortality in patients with UTUC who underwent nephroureterectomy (RNU).Methods: Clinicopathological information was collected from 315 UTUC patients treated with RNU. The association between VUC and oncological outcomes was analyzed using the Kaplan–Meier method with log-rank test and Cox proportional hazards regression models. Multiple logistic regression analysis was performed to identify the influence of VUC on tumor grade.Results: Preoperative positive VUC, presenting in 101 patients (32%), was significantly associated with tumor multifocality (P = 0.017) and higher tumor grade (P = 0.010). On multivariable Cox regression analyses, preoperative positive VUC was an independent prognostic factor of intravesical recurrence-free survival (RFS) (hazard ratio [HR] = 2.21, 95% confidence interval [CI] 1.06–4.64; P = 0.035), RFS (HR = 1.80, 95% CI 1.08–2.99; P = 0.023), and cancer-specific survival (CSS) (HR = 1.87, 95% CI 1.10–3.18; P = 0.020), but not overall survival (HR = 1.32, 95% CI 0.80–2.18; P = 0.28). Logistic regression analysis revealed that VUC was related to high tumor grade in UTUC (odds ratio = 2.23, 95%CI 1.15–4.52).Conclusion: Preoperative positive VUC significantly increases the risk of intravesical recurrence in UTUC patients undergoing RNU. In addition, positive VUC is an adverse predictor of RFS and CSS, which might be due to the association between positive VUC and high tumor grade.

Logistic Regression Analysis of Low Grade Spindle Cell Lesions

1999 ◽  
Vol 43 (2) ◽  
pp. 143-152 ◽  
Author(s):  
Katharine Liu ◽  
Richard K. Dodge ◽  
Leslie G. Dodd ◽  
Lester J. Layfield
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Spindle Cell ◽  
Low Grade

scholarly journals The Value of MRI Findings Combined With Texture Analysis in the Differential Diagnosis of Primary Ovarian Granulosa Cell Tumors and Ovarian Thecoma–Fibrothecoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Nai-yu Li ◽  
Bin Shi ◽  
Yu-lan Chen ◽  
Pei-pei Wang ◽  
Chuan-bin Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Texture Analysis ◽  
Granulosa Cell ◽  
Logistic Regression Analysis ◽  
Texture Features ◽  
Intratumoral Hemorrhage ◽  
Granulosa Cell Tumors ◽  
Ovarian Granulosa Cell

ObjectiveThis study aims to explore the value of magnetic resonance imaging (MRI) and texture analysis (TA) in the differential diagnosis of ovarian granulosa cell tumors (OGCTs) and thecoma-fibrothecoma (OTCA–FTCA).MethodsThe preoperative MRI data of 32 patients with OTCA–FTCA and 14 patients with OGCTs, confirmed by pathological examination between June 2013 and August 2020, were retrospectively analyzed. The texture data of three-dimensional MRI scans based on T2-weighted imaging and clinical and conventional MRI features were analyzed and compared between tumor types. The Mann–Whitney U-test, χ2 test/Fisher exact test, and multivariate logistic regression analysis were used to identify differences between the OTCA–FTCA and OGCTs groups. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic curve analysis was carried out to evaluate diagnostic efficiency.ResultsA multivariate analysis of the imaging-based features combined with TA revealed that intratumoral hemorrhage (OR = 0.037), log-sigma-20mm-3D_glszm_SmallAreaEmphasis (OR = 4.40), and log-sigma-2-0mm-3D_glszm_SmallAreaHighGrayLevelEmphasis (OR = 1.034) were independent features for discriminating between OGCTs and OTCA–FTCA (P < 0.05). An imaging-based diagnosis model, TA-based model, and combination model were established. The areas under the curve of the three models in predicting OGCTs and OTCA–FTCA were 0.935, 0.944, and 0.969, respectively; the sensitivities were 93.75, 93.75, and 96.87%, respectively; and the specificities were 85.71, 92.86, and 92.86%, respectively. The DeLong test indicated that the combination model had the highest predictive efficiency (P < 0.05), with no significant difference among the three models in differentiating between OGCTs and OTCA–FTCA (P > 0.05).ConclusionsCompared with OTCA–FTCA, intratumoral hemorrhage may be characteristic MR imaging features with OGCTs. Texture features can reflect the microheterogeneity of OGCTs and OTCA–FTCA. MRI signs and texture features can help differentiate between OGCTs and OTCA–FTCA and provide a more comprehensive and accurate basis for clinical treatment.

scholarly journals How to Identify White Coat Hypertension at The First Diagnosis: Establishment of A Scoring Model for The Differential Diagnosis of White Coat Hypertension and Sustained Hypertension

2020 ◽  
Author(s):  
Peng Cai ◽  
Yan Peng ◽  
YuXi Chen ◽  
Yan Wang ◽  
Xukai Wang
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
White Coat ◽  
White Coat Hypertension ◽  
Multivariate Logistic Regression ◽  
Training Set ◽  
Scoring Model

Abstract Background: To establish a scoring model for the differential diagnosis of white coat hypertension (WCH) and sustained hypertension (SHT). Methods: 553 adults with elevated office blood pressure, normal renal function and no antihypertensive drugs were included in this study. 17 parameters, such as gender and age, were obtained by questionnaire investigation and biochemical index detection. WCH and SHT were distinguished by 24-hour ambulatory blood pressure monitoring. Participants were randomly divided into a training set (445 cases) and a verification set (108 cases). In the training set, the above parameters were screened by LASSO regression and univariate logistic regression analysis, then, the scoring model was constructed through multivariate logistic regression analysis. ROC curve and calibration curve were used to discuss the discrimination and calibration of this scoring model respectivelyResults: 6 parameters were finally selected, namely isolated systolic hypertension, systolic blood pressure, diastolic blood pressure, triglyceride, serum creatinine, and cardiovascular and cerebrovascular diseases. Multivariate logistic regression was used to establish the scoring model. The R2 and AUC of the scoring model in the training set were 0.163 and 0.705, respectively. In the verification set, the R2 of the scoring model was 0.206, and AUC was 0.718. The calibration test results showed that the scoring model had good stability in both training set and verification set (MSE=0. 001, MAE=0. 014; MSE=0. 001, MAE=0. 025, respectively).Conclusion: A stable scoring model for distinguishing WCH can be established, which can assist clinical medical workers to identify WCH at the first diagnosis.

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