The value of Ki-67 combined with Uroplakin-III in predicting the prognosis of bladder non-muscle invasive urothelial carcinoma

The value of Ki-67 combined with Uroplakin-III in predicting the prognosis of bladder non-muscle invasive urothelial carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The value of Ki-67 combined with Uroplakin-III in predicting the prognosis of bladder non-muscle invasive urothelial carcinoma Junchao Wu, Xuede Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5410808/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To assess the predictive significance of Ki-67, Uroplakin-III, and their combination in bladder non-muscle invasive urothelial cancer patients. Methods Retrospective analysis of 224 bladder non-muscle invasive urothelial carcinoma patients who had transurethral resection at the Kunming Medical University Second Affiliated Hospital from January 2017 until December 2019 was performed. Patients were separated into Ki-67 high and low expression groups and Uroplakin-III positive and negative expression groups. Predictive models were built using univariate binary logistic regression, Cox proportional hazards regression model for multivariate analysis, unary linear regression, Kaplan-Meier survival analysis, nomogram, and AUC. Results Recurrence was substantially linked with tumor grade, Ki-67, and UP-III in univariate binary logistic regression. Tumor progression was linked to tumor number, stage, grade, type, Ki-67, and UP-III. Age, tumor size, stage, grade, type, and Ki-67 affected cancer survival. Ki-67 and UP-III positivity significantly decreased recurrence-free survival (RFS) in multivariate Cox regression analysis. PFS was dramatically lowered by high Ki-67. Age and elevated Ki-67 substantially affected cancer-specific survival. In unary linear regression and Kaplan-Meier analysis, high Ki-67 coupled UP-III positive lowered RFS, PFS, and CSS. AUC = 0.912, 0.870, and 0.942 on the ROC curves demonstrated that the model predicted 5 year RFS, PFS, and CSS rates well. The internal validation sett also performed well. Conclusions This study found that Ki-67 and UP-III are independent predictive markers for bladder non-muscle invasive urothelial carcinoma recurrence, progression, and death. Positive Ki-67 and UP-III expression are related with poor prognosis. Ki-67 with UP-III demonstrated good predictive discrimination and stability. Bladder cancer Ki-67 Uroplakin III Prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction The 10th most frequent malignancy worldwide, bladder cancer (BC) has significant incidence and death 1 . At least 75% of BC cases are non-muscle invasive bladder cancer (NMIBC), which has a diverse risk of recurrence and progression to muscle invasive bladder cancer (MIBC) 2 .NMIBC possesses a remarkable 5-year survival rate (> 90%) 3 , but its recurrence rate is substantial, and most patients require long-term cystoscopic monitoring and various treatment procedures, lowering health-related quality of life 2 . Main therapy for NMIBC is transurethral resection of bladder tumor (TURBT) 4 , and the initial TURBT is crucial for diagnosis and prognosis 5 .The residual tumor rate following the initial TURBT was 4%-78%, depending on stage and quantity 6 . However, surgeon skill and specimen quality may underestimate tumor pathological stage. Patients with NMIBC have a higher chance of progression and recurrence, prompt radical cystectomy (RC) is crucial 7 . A 45% 5-year disease progression rate is possible in NMIBC patients 8 . NMIBC diagnosis, treatment, and follow-up should be tailored to each patient's unique risk due to the high recurrence and progression rates in low-risk patients, the high rate of progression in high-risk patients, the requirement for lifetime follow-up, and the high cost of treatment 8 . Recently, various molecular markers have been employed to assess NMIBC prognosis. Immunohistochemical staining for Ki-67, CK 20, UP-III, GATA-3, and p53 is prevalent for urothelial cancer, although their specificity is restricted 9 – 11 Ki-67 is a nuclear protein that is part of the DNA replicase complex that is encoded by the MKI67 gene on chromosome 10, as found by Gerdes 12 and Ho Kyung Seo 13 . It is required for cell proliferation and is articulated in the proliferative phase (G1, S, G2 and mitosis) but not in the stationary phase (G0) throughout the cell cycle 14 . Thus, Ki-67 can be used as a biomarker to measure cell proliferation. Otto et al 15 realised that higher Ki-67 expression in T1 UBC tissues was connected to poor recurrence-free, progression-free, and tumor-specific survival. Uroplakins (UPs) consist of four transmembrane proteins (UPs Ia, Ib, II and III), of which Uroplakin-III is an asymmetric unit 47KDa glycoprotein 16 . Using polyclonal antibodies, Moll et al 17 obtained UP-III in 53% of primary and 66% of metastatic urothelial carcinomas in paraffin-embedded immunohistochemistry (IHC). However, many non-urothelial carcinomas were consistently negative in the assay. It can be seen that UP-III is a urothelial cell-specific differentiation product. On this basis, the TURBT follow-up and clinical data of bladder non-muscle invasive urothelial carcinoma (NMIUC) patients were retrospectively analysed. To assess Ki-67 and Uroplakin-III expression in bladder NMIUC prognosis. 2 Materials and methods 2.1. Patients and clinical data This retrospective analysis examined TURBT patients with bladder NMIUC at Kunming Medical University Second Affiliated Hospital from January 2017 until December 2019. Age, sex, tumor number, size, pathological stage, histological grade, type, concurrent carcinoma in situ (CIS), Ki-67, Uroplakin III, RFS, PFS, and CSS are included. The WHO 2016 BC classification system was utilised for histological grading and the 2017 UICC TNM staging method (8th edition) for pathological staging. Inclusion criteria: (1) All patients underwent TURBT; (2) Patients with bladder urothelial carcinoma confirmed by pathological examination; (3) Pathological examination including Ki-67 and(or) Uroplakin III immunohistochemical staining; (4) Patient's clinical and follow-up information was complete. Exclusion criteria: (1) patients with secondary bladder tumors confirmed by imaging and pathological examination; (2) patients with tumor invading the muscular layer; (3) patients without postoperative intravesical chemotherapy using gemcitabine hydrochloride; (4) patients whose cause of death was not BC. 2.2. Operation method After the anesthesia was effective, the patients were taken to the lithotomy position and routinely disinfected with sterile towels. Normal saline was used as irrigation solution. The location and size of bladder tumor were observed under the plasma resectoscope under direct vision, and the tumor was resected by plasma resectoscope. The tumor was resected in different layers. The range of resection included normal tissue 2 cm around the tumor, and the depth of resection was the deep muscular layer. After excision, the bleeding was stopped carefully and the basal wound was electrocoagulated. Ellik irrigators flush out the electrocut tissue. The indwelling 3-lumen catheter was connected with normal saline for irrigation. 2.3. Immunohistochemical method After dewaximed and hydrated with xylene and 100% ethanol, paraffin sections were repaired in EDTA buffer under high pressure for 10 minutes, sealed for 10 minutes with 3% hydrogen peroxide, after overnight primary antibody incubation at 4℃, universal secondary antibody was applied at 37℃ for 30 minutes. The staining was observed under DAB light microscope. Hematoxylin counterstained, routinely dehydrated, clear, neutral resin sealed sections of bladder tumor were stored at room temperature in blocking solution containing 0.3% hydrogen peroxide. The Fujian Maixin Biotechnology Co. LTD.-purchased mouse anti-human monoclonal antibody (MIB-1) identified Ki-67 protein. Ki-67 labelling index was used to measure immune activity, identify locations with high immunoreactivity, and score 1000 cells to determine Ki-67-positive cell percentage. A rabbit anti-human UP-III polyclonal antibody (1/100 dilution, 1 hour at room temperature) from Lifespan, USA was used to count positive staining cells in 20 randomly selected high-power cells to determine expression. At least 5% of tumor cells were labelled for positive. 2.4. Follow-up of patients Patients' follow-up data was acquired via outpatient chemotherapy medication infusion, inpatient reexamination, and telephone. Patient postoperative follow-up was: In low-risk patients with negative results, a second cystoscopy was done 1 year after the first 3 months. Until the fifth year, B ultrasounds and pelvic magnetic resonance imaging were done every six months. High-risk patients got cystoscopy every 3 months for 2 years, 6 months from 3rd year, and yearly from 5th until life. After treatment, follow-up followed the protocol if recurrence occurred. The hospitalization reexamination investigated blood, tumor markers, urine, urine exfoliative cytology, CT urography, chest and abdominal CT, tumor recurrence, progression, causes of death, and event time. Follow-up extended from surgery to study conclusion. RFS was the period from full remission to recurrence or end of follow-up after transurethral resection. From randomisation to BC progression, death, or end of follow-up, PFS was calculated. BC CSS was the time from diagnosis to death or follow-up. November 2022 was the follow-up deadline. 2.5. Rule of classification Receiver operator characteristic (ROC) curve analysis used CSS as the outcome index and the Ki-67 expression with the highest Youden index as the best cut-off value. The optimal cut-off value divided patients into high and low Ki-67 expression groups. Uroplakin-III immunohistochemistry divided patients into positive and negative groups. The combined markers were split into four groups: Ki-67 high + Uroplakin-III positive, negative, positive, and negative. The nomogram patients were randomly assigned to training and validation sets 3:1. 2.6. Statistical method This paper used SPSS25.0 (SPSS Inc.; Armonk, NY, USA). χ2 test was used for data counting. If the sample size is ≥ 40 and the expected value is < 5, the correction χ2 test is employed. When the sample size is < 40 and at least one predicted value is < 1, Fisher exact test is used. T test assessed measuring data normality. Univariate binary logistic regression analyzed RFS, PFS, and CSS clinicopathological variables. Cox proportional hazards regression model was used for multivariate analysis of indicators with P < 0.05 in univariate analysis (reference indicators were negative outcome indicators). The two indicators' predictive potential is tested by multiple linear regression. RFS, PFS, and CSS median survival times were estimated using Kaplan–Meier analysis. Every factor's predictive potential was evaluated using the ROC curve. In Rstudio 1.4, joint indicator training and validation data was randomly partitioned. A nomogram was built to predict RFS, PFS, and CSS using P < 0.05 risk variables in multivariate Cox regression analysis. The area under the ROC curve measured training and validation set fit and model predictiveness. All statistical analyses were deemed significant at P < 0.05. 3 Result 3.1. Characteristics of patients The Second Affiliated Hospital of Kunming Medical University enrolled 259 bladder NMIUC patients who met inclusion and exclusion criteria and performed TURBT from January 2017 to December 2019. There were 23 incomplete clinical data cases, 12 lost to follow-up, and 94.6% follow-up success. This study includes 209 UP-III and 224 Ki-67 immunohistochemistry participants. The median follow-up was 36 months. Overall patient data is given in Table 1 . Table 1 General data characteristics 3.2. The ROC curve and optimal cut-off value of Ki-67 The outcome index was Ki-67 CSS, and the ROC curve is shown in Fig. 1 . The research variable's optimal cut-off value was the critical value corresponding to the greatest Youden index. The maximal Youden index was 0.577, corresponding to a 25% Ki-67, 95.0% sensitivity, and 62.7% specificity (Table 2 ). Patients with Ki-67 < 25% were categorised as low expression according to the best cut-off value, whereas those with Ki-67 ≥ 25% were classified as high expression. Table 2 ROC curve analysis of Ki-67 Variate Cut-off value AUC 95%CI P value Ki-67 0.25 0.833 0.756–0.910 <0.001 3.3. Analysis of clinicopathological data with Ki-67 and UP-III Clinicopathological data and Ki-67 demonstrated a significant difference (P = 0.035) between multiple tumor patients with high (22.1%) and low (11.6%) Ki-67. The difference in Ki-67 expression between 44.2% and 36.4% in T1 tumors was significant (P = 0.024). Significantly, strong-grade tumors with high Ki-67 expression were 75.8%, while those with low expression were 22.5% (P 0.05) (Table 3 ). Upon analyzing clinicopathological data and UP-III expression, 54.9% of high-grade tumors exhibited positive expression, while 26.3% showed negative expression (P 0.05) (Table 4 ). Table 3 Analysis between clinicopathological data and Ki-67 Parameter Ki-67 P value Low High Gender Male 111(86.0%) 80(84.2%) 0.702 Female 18(14.0%) 15(15.8%) Age 63.12 ± 12.28 65.64 ± 11.24 0.116 Tumor size <2cm 86(66.7%) 52(54.7%) 0.070 ≥2cm 43(33.3%) 43(45.3%) Tumor number Single 114(88.4%) 74(77.9%) 0.035 Multiple 15(11.6%) 21(22.1%) Tumor staging Ta 82(63.6%) 53(55.8%) 0.240 T 1 47(36.4%) 42(44.2%) Tumor grade Low 100(77.5%) 23(24.2%) <0.001 High 29(22.5%) 72(75.8%) Tumor type Papillary 91(70.5%) 55(57.9%) 0.050 Non-papillary 38(29.5%) 40(42.1%) CIS Yes 4(3.1%) 3(3.2%) 0.981 No 125(96.9%) 92(96.8%) Table 4 Analysis between clinicopathological data and UP-III Parameter UP-III P value Negative Positive Gender Male 65(85.5%) 112(84.2%) 0.799 Female 11(14.5%) 21(15.8%) Age 64.43 ± 10.08 63.89 ± 12.79 0.753 Tumor size <2cm 45(59.2%) 31(40.8%) 0.500 ≥2cm 85(63.9%) 48(36.1%) Tumor number Single 66(86.8%) 109(82.0%) 0.357 Multiple 10(13.2%) 24(18.0%) Tumor staging Ta 46(60.5%) 80(60.2%) 0.957 T 1 30(39.5%) 53(39.8%) Tumor grade Low 56(73.7%) 60(45.1%) <0.001 High 20(26.3%) 73(54.9%) Tumor type Papillary 53(69.7%) 84(63.2%) 0.336 Non-papillary 23(30.3%) 49(36.8%) CIS Yes 1(1.3%) 5(3.8%) 0.309 No 75(98.7%) 128(96.2%) 3.4. Analysisof clinicopathological data, Ki-67 and UP-III immunohisto-chemical expression in relation to tumor recurrence, progression and specific survival Tumor grade, Ki-67, and UP-III immunohistochemical expression were strongly linked with recurrence in univariate binary logistic regression (P = 0.007, P < 0.001, and P < 0.001, respectively). Several factors, including tumor number, stage, grade, type, Ki-67, and UP-III, were linked to progression (P-values < 0.001). Cancer-specific survival was linked with age (P = 0.003), tumor size (P = 0.014), stage (P = 0.02), grade (P = 0.003), type (P = 0.005), and Ki-67 (P = 0.001). Table 5 Univariate Logistic analysis between clinicopathological data and tumor recurrence, progression and specific survival Parameter Patients (n) Recurrence P value Progression P value Special survival P value Gender Male 191 0.537 0.862 0.972 Female 33 Age 0.613 0.225 0.003 Tumor size <2cm 138 0.693 0.108 0.014 ≥2cm 86 Tumor number Single 188 0.392 0.011 0.617 Multiple 36 Tumor staging Ta 135 0.776 0.039 0.020 T 1 89 Tumor grade Low 123 0.007 <0.001 0.003 High 101 Tumor type Papillary 146 0.635 0.004 0.005 Non-papillary 78 CIS Yes 7 0.688 0.699 0.999 No 217 Table 6 Univariate Logistic analysis of Ki-67 and UP-III immunohistochemical expression in relation to tumor recurrence, progression and specific survival Ki-67(224) UP-III(209) P value Low High Negative Positive Recurrence 12/129 38/95 5/76 40/133 <0.001, <0.001 Progression 3/129 42/95 9/76 34/133 <0.001, 0.021 Special survival 1/129 19/95 6/76 13/133 0.001, 0.650 High Ki-67 expression and UP-III positivity were strongly linked to lower RFS (Table 7 a) in multivariate Cox regression analysis (HR = 0.191; 95% CI:0.087–0.420; P < 0.001; HR = 0.280; 95%CI:0.106–0.740; P = 0.01). High Ki-67 expression (HR = 0.059; 95%CI:0.017–0.202; P < 0.001) was linked to decreased PFS (Table 7 b). CSS was substantially lowered by age (HR = 1.066; 95%CI :0.004–0.273; P = 0.001) and high Ki-67 expression (HR = 0.034; 95%CI :0.004–0.273; P = 0.001). Table 7 Multivariate Cox regression analysis for the association of patient risk factors with tumor RFS (a), PFS (b), and CSS (c) a Parameter Patients(n) HR 95%CI P value Age 0.991 0.967–1.015 0.452 Tumor size <2cm 138 1.212 0.668–2.197 0.527 ≥2cm 86 Tumor number Single 188 1.074 0.512–2.256 0.850 Multiple 36 Tumor staging Ta 135 0.434 0.127–1.479 0.182 T 1 89 Tumor grade Low 123 1.193 0.575–2.472 0.635 High 101 Tumor type Papillary 146 2.868 0.799–10.297 0.106 Non- Papillary 78 Ki-67 Low 129 0.191 0.087–0.420 <0.001 High 95 UP-III Negative 76 0.280 0.106–0.740 0.010 Positive 133 b Parameter Patients(n) HR 95%CI P value Age 1.002 0.976–1.030 0.859 Tumor size <2cm 138 0.895 0.493–1.623 0.714 ≥2cm 86 Tumor number Single 188 0.554 0.285–1.077 0.810 Multiple 36 Tumor staging Ta 135 0.694 0.000-1.330 0.900 T 1 89 Tumor grade Low 123 0.646 0.289–1.448 0.289 High 101 Tumor type Papillary 146 <0.001 0.000-3.924 0.892 Non-papillary 78 Ki-67 Low 129 0.059 0.017–0.202 <0.001 High 95 UP-III Negative 76 1.002 0.468–2.148 0.995 Positive 133 c Parameter Patients(n) HR 95%CI P value Age 1.066 0.004–0.273 0.001 Tumor size <2cm 138 0.397 0.145–1.086 0.072 ≥ 2cm 86 Tumor number Single 188 0.831 0.266–2.598 0.751 Multiple 36 Tumor staging Ta 135 1.640 0.000-1.583 0.948 T1 89 Tumor grade Low 123 1.132 0.321–3.988 0.847 High 101 Tumor type Papillary 146 <0.001 0.000-7.549 0.939 Non-papillary 78 Ki-67 Low 129 0.034 0.004–0.273 0.001 High 95 UP-III Negative 76 1.898 0.682–5.285 0.220 Positive 133 Ki-67 low expression group had 95.3% and 90.7% 1- and 3-year RFS rates, according to Kaplan-Meier (KM) analysis. The Ki-67 high expression group experienced 78.9% and 63.2% 1- and 3-year RFS. The RFS rate differed significantly between groups (P < 0.001) (Fig. 2 a). Ki-67 low expression group 1- and 3-yearPFS rates were 99.2% and 98.4%. The Ki-67 high expression group had 87.4% and 62.1% 1- and 3-year PFS. The difference between groups was significant (P < 0.001) (Fig. 2 b). The Ki-67 low expression group had 100.0% and 99.2% 1- and 3-year CSS rates. The Ki-67 high expression group showed 93.7% and 82.1% 1- and 3-year CSS rates. The difference between groups was significant (P < 0.001) (Fig. 2 c). KM analysis indicated UP-III negative group 1- and 3-year RFS rates of 93.4%. The 1- and 3-year RFS rate of UP-III positives was 83.5 and 69.9%. The difference in RFS rate between groups was considerable (P < 0.001) (Fig. 3a). 1 and 3 year PFS rates for UP-III negative group were 93.4% and 88.2%. The 1- and 3-year PFS rates for UP-III positive patients were 91.0% and 78.9%. The two groups had significantly different PFS rates (P = 0.026) (Fig. 3b). CSS rate did not differ between UP-III negative and positive groups (P = 0.693) (Fig. 3c). 3.5. Correlation of Ki-67 and UP-III joint indicator immunohistochemical expression in relation to RFS, PFS and CSS According to unary linear regression, RFS was longer in the Ki-67 low expression + UP-III negative (P < 0.001) and positive (P = 0.001) groups compared to the high expression + UP-III positive group. RFS was not statistically different between Ki-67 high expression + UP-III negative and positive groups (P = 0.076)(Table 8 a). Ki-67 low expression + UP-III negative (P = 0.009) and positive (P = 0.005) groups had longer PFS than Ki-67 high expression + UP-III positive group. There was no substantial difference in PFS between Ki-67 high expression + UP-III negative and positive groups (P = 0.343)(Table 8 b). CSS was longer in Ki-67 low expression + UP-III negative (P < 0.001) and positive (P <0.001) groups compared to Ki-67 high expression + UP-III positive group. The CSS was longer in Ki-67 high expression + UP-III positive than negative (P = 0.022) (Table 8 c). Table 8 UnaryLinear Regression of Ki-67 and UP-III joint indicator immunohistochemical expression in relation to RFS(a),PFS(b) and CSS(c) Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta a (Constant) 37.292 2.131 17.500 .000 Ki67<0.25 + UPIII(-) 15.001 3.190 0.355 4.702 .000 Ki67<0.25 + UPIII(+) 11.003 3.147 0.264 3.497 .001 Ki67 ≥ 0.25 + UPIII(-) 8.486 4.765 0.126 1.781 .076 Ki67 ≥ 0.25 + UPIII(+) 0 Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta b (Constant) 37.597 1.904 19.752 .000 Ki67<0.25 + UPIII(-) 15.455 2.850 0.383 5.423 .000 Ki67<0.25 + UPIII(+) 16.403 2.811 0.413 5.836 .000 Ki67 ≥ 0.25 + UPIII(-) -4.042 4.256 0.063 − .950 .343 Ki67 ≥ 0.25 + UPIII(+) 0 Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta c (Constant) 48.097 1.445 33.283 .000 Ki67<0.25 + UPIII(-) 5.713 2.164 .199 2.641 .009 Ki67<0.25 + UPIII(+) 6.116 2.134 .217 2.866 .005 Ki67 ≥ 0.25 + UPIII(-) -7.486 3.231 − .164 -2.317 .022 Ki67 ≥ 0.25 + UPIII(+) 0 KM analysis showed greater 1-year (76.4%) and 3-year (59.7%) RFS rates for the Ki-67 high expression + UP-III positive group compared to the low expression + UP-III negative and positive groups (P < 0.001, P =0.001, respectively). Figure 4 a shows no significant difference between groups (P = 0.059). The Ki-67 high expression + UP-III positive group had a considerably higher PFS rate (80.6% at 1 year and 59.5% at 3 years) compared to the low expression + UP-III negative and positive groups (P < The Ki-67 high expression + UP-III negative group did not vary (P = 0.766) (Fig. 4 b).The Ki-67 high expression + UP-III positive group had significantly higher 1- and 3-year CSS rates (86.1% and 82.3%, respectively) compared to the negative and positive groups (P = 0.001, P = 0.003). Figure 4 c shows no significant difference between the Ki-67 high expression + UP-III negative group (P = 0.071). 3.6. Establishment of a joint indicators prediction model based on nomogram Cox multifactor analysis determines three variables for the nomogram. The nomogram can predict BC recurrence, progression, and cancer-specific survival up to 5 years following main surgery. The model's AUC of 0.912, 0.870, and 0.942 indicated high predictive accuracy of the 5-year RFS, PFS, and CSS rates, respectively. The internal validation sett performed well with AUCs of 0.875, 1.000, and 0.945 (Fig. 7 ). 4 Discussion Lack of solid prognostic indicators makes clinical decision-making and therapy of bladder NMIUC challenging. Conventional evaluation protocols seem to be inadequate to provide accurate prognoses for patients with diverse and complex tumor backgrounds. Thus, molecular studies of BC biology may improve forecasts. This study assessed the pathological grading of bladder NMIUC using these molecular markers. 4.1. Correlation between clinicopathological parameters and BC patients About 60% of BCs present as superficial (pT1 or pTa) UBC, where the tumor is limited to the lamina propria or epithelium 18 . After TURBT, 40 to 80% of cases may have tumor recurrence, and 20 to 30% of cases may have tumor progression with muscularis propria invasion 19 . Tumor size, grade, depth of invasion, numerous tumor foci, and CIS all affect tumor recurrence or progression 20 . In this study, bladder NMIUC investigation, univariate logistic regression showed a strong association between tumor grade and recurrence. Tumor progression was substantially linked with tumor number, stage, grade, and type. Age, tumor size, stage, grade, and type substantially affected cancer-specific survival. Ageing dramatically decreased CSS in multivariate cox regression analysis. Our findings roughly match those of earlier researchers. 4.2. Correlation between Ki-67 expression and BC patients Tumors with fast cell division and high growth fraction display Ki-67, an indicator of the growth of cells. Thus, Ki-67 expression monitoring can predict recurrence and progression. Few unvalidated UBC Ki-67 cutoffs have been reported internationally, but they are valuable in diagnosis, indicating relative trends and their specificity and sensitivity, and guiding future study. Wang et al 21 discovered that big and numerous tumors expressed Ki67 more. Related investigations found that high-grade and aggressive UBCs had much more Ki-67 expression than low-grade and superficial UBC. Related studies have shown that the average Ki-67 expression was significantly greater in high-grade and aggressive UBCs compared to low-grade and superficial UBC 22 . Yang's research 11 found that T1 stage UBC patients with Ki-67 > 15% had a 13.989 times greater incidence of high-grade tumors compared to those with Ki-67 < 15% (95% CI = 3.691–53.022, P < 0.05). Many investigations have linked Ki-67 to high grade, stage, and submucosal invasion 20 , 21 , 23 , 24 .These data indicate that UBC aggressiveness and malignancy are positively linked with Ki-67 expression. Ki-67 > 20% predicted superficial low-grade BC recurrence, according to Gontero’s study 25[23] . Chen 26 identified that the 25% Ki-67 expression threshold has 73.52% sensitivity and 73.53% specificity for predicting recurrence. Goyal et al 22 found that Ki-67 ≥ 59% had 100% specificity for invasive BC, which has practical implications for tumor staging and treatment in cases where morphological evidence of muscle invasion is not clear. Jeon 27 and José 28 observed that Ki-67 predicted recurrence and progression in pTa and pT1 BC patients. In a later meta-analysis of 13,053 BC patients 29 , increased Ki-67 expression at 20% was substantially linked with poorer univariate RFS, PFS, DFS, CSS, and OS. Otto et al 15 showed that high Ki-67 expression in tissues of UBC patients with T1 stage had poor RFS, PFS, and CSS. The study of et al March 28 also confirmed that Ki-67 could improve the predictive efficacy of RFS and PFS in pTa/pT 1 papillary UBC with intermediate differentiation (grade 2,G2). Lei et al. 30 conducted a meta-analysis found that increased Ki-67 expression in urothelial carcinoma was related with shorter 5-year DFS and OS, and worse cancer-specific mortality. This study employed ROC curve to find the optimal Ki-67 cutoff value of 25%, which was also found in numerous studies 24 , 26 . High Ki-67 expression was linked with numerous, T1, high-grade, and non-papillary tumors in clinicopathological analysis. RFS, PFS, and CSS were substantially linked with Ki-67 in univariate logistic regression. High Ki-67 expression substantially lowered RFS, PFS, and CSS in multivariate Cox regression analysis. KM survival analysis indicated that elevated Ki-67 expression significantly lowered 1-, 3-, and 5-year RFS, PFS, and CSS rates. It mostly agrees with earlier research. Multiple studies have shown that aberrant Ki-67 expression is a separate forecasting predictor for bladder NMIUC recurrence, progression, and cancer-specific survival. 4.3. Correlation between UP-III expression and BC patients Urothelial plaques, two-dimensional crystals made of integral membrane proteins termed uroplakins, cover 90% of the apical surface 31 . The only urothelial plaque containing a 50-amino-acid cytosolic domain was UP-III, which may attach plaques to the cytoskeleton 32 . The only urothelial plaque containing a 50-amino-acid cytosolic domain was UP-III, which may attach plaques to the cytoskeleton Earlier studies confirmed UP III as a specific and sensitive marker of urothelial carcinoma in dogs, detecting 91% of urothelial cell carcinomas 33 . And one investigations have shown that UP-III is important for urothelial permeability barrier modulation, surface area stabilisation, and urinary tract development 34 Tsumura et al. 35 found that BC patients had higher serum UP-III levels, which were associated with myometrial invasion, strong differentiation, and lymphatic invasion, and high serum UP-III also significantly increased tumor-specific mortality. The study of Szymańska 36 further showed that patients with BC had significantly increased UP-III expression in their plasma and urine, with a notable distinction between low-grade and high-grade groups. Matsumoto et al 37 reported that UP-III depletion linked with lymphovascular invasion, clinical stage, and grade. Kaufmann 9 found that Au 1, a monoclonal antibody against UP-III, is a highly specific IHC marker for urothelial carcinoma and has moderate sensitivity for distinguishing primary and metastatic urothelial carcinoma, but tumor grade and stage do not significantly affect UP-III expression. Tadin 38 discovered that UP-III positive expression was connected with tumor recurrence, tumor size, disease stage, and tumor infiltrating lymphocytes in NMIBC. In this study, clinicopathological results showed that high-grade tumors have UP-III positive expression. In univariate logistic regression, UP-III was linked with bladder NMIUC recurrence and progression but not cancer-specific survival. In multivariate Cox regression analysis, UP-III high expression was associated with shortened RFS time but not PFS or CSS. High UP-III expression was related with lower 1 year, 3 year, and 5 year RFS and PFS rates, but not CSS rates, according to KM survival analysis. The study found no significant link between UP-III and CSS, possibly due to the little amount of data on disease-related fatalities, which increases prediction bias. Our study agrees with Tadin et al., but there are few and different conclusions about UP-III and bladder tumors at home and abroad, especially on tumor progression and disease-related death, so more research is needed to confirm their correlation. 4.4 Correlation between combined indicators and prognosis of BC patients Several studies have indicated that a multiparameter diagnostic approach is better than a single test for T1 stage UBC pathological grading. Ding et al 24 demonstrated that the European Organization for Research and Treatment of Cancer (EORTC) risk score and Ki-67 expression can better predict NMIBC recurrence and progression. Especially for those with EORTC moderate risk scores. Chen et al 26 presented evidence that a unique model of molecular grading in Ki-67 and Vascular Endothelial Growth Factor(VEGF) score may accurately predict results and optimise therapy. Bertz et al 39 examined Ki-67 and CK20 as joint variables that may enhance T1 stage UBC risk classification. Early radical cystectomy for T1G3 UBC patients with Ki-67 and CK20 expression is recommended. Combining Mitotic Index (MI), Ki-67 index, and P504S can enhance pathological grading of T1 stage UBC in a multivariate diagnostic model 11 . Rubino 40 also found that Ki-67 positive expression was significantly correlated with PD-L1 positive expression (P = 0.001), and the combination of the two could assess OS and CSS in MIBC patients undergoing RC after neoadjuvant chemotherapy. Patients with positive PD-L1 and Ki-67 expression had substantially poorer CSS and OS rates than those with negative expression. Yoshida 41 observed that Apparent Diffusion Coefficient (ADC) was adversely linked with Ki-67 expression in bladder tumor tissues. Bladder tumors with lower ADC and greater Ki-67 respond better to CRT. Tsumura et al 42 confirmed that aberrant expression of E-cadherin, Coxsackievirus receptor, S100A4, and UP-III in NMIBC tumor tissues following TURBT increased tumor-specific survival (P = 0.016). The 5-year CSS for patients with 0–1 and ≥ 2 molecular markers was 91% and 66%, respectively. No researchers have combined Ki-67 and UP-III to evaluate BC prognosis. In this study, KM survival analysis of bladder NMIUC with Ki-67 and UP-III showed that patients with low Ki-67 expression and negative UP-III were divided into two groups. In the Ki-67 high expression + UP-III positive group, the risk of recurrence, progression, and death was higher, and the 1-, 3-, and 5-year RFS, PFS, and CSS rates were lower. This suggests that the two indicators can better predict the prognosis of bladder NMIUC patients. 4.5 Comparison of prognostic models Li Ding et al 4 created an RFS nomogram using NMIBC previous recurrence status, intravesical instillation, and systemic immune inflammation index. 0.835, 0.833, and 0.871 were the area under the curve for 1, 2, and 3-year RFS predictions. Jorge Daza, M.D. et al 43 suggested that patients with multifocal, single, or tumor ≥ 4cm NMIBC had the worst RFS. Maria et al 44 indicates that the nomogram based on pathological stages and positive surgical margins to predict the specific mortality in MIBC patients. Model area under curve is 0.65. Model AUC for 5-year BC specific mortality was 0.75. Our model predicts RFS,PFS, and CSS better than the others. 4.6. Limitation This study also has flaws. First, this work is retrospective, thus further high-quality prospective or randomised controlled trials are needed to corroborate the experimental results. Second, this study is single-center, and CSS research is few, making outcomes untrustworthy. There may be selection bias in the process of patient visit, which may lead to inaccurate experimental results. The cut-off value of Ki-67 may change according to research data tampering, however there is enough evidence to link it to BC patients' prognoses. 5 Conclusion This study indicated that bladder NMIUC patients with Ki-67 and UP-III had independent prognostic markers for tumor recurrence, progression, and mortality. Positive Ki-67 and UP-III expression are related with poor prognosis, which helps enhance patient risk classification. Ki-67 with UP-III demonstrated good predictive discrimination and stability. Declarations Ethics approval After discussion and decision by the Ethics Committee of the Second Affiliated Hospital of Kunming Medical University, the study was approved to be conducted in the center. This study is a retrospective study, and informed consent exemption has been obtained. The ethics approval number is FEY-BG-39-2.0on 01/05/2023. Funding There are no funding for this study. References Zimpfer A, Kdimati S, Mosig M, et al. ERBB2 Amplification as a Predictive and Prognostic Biomarker in Upper Tract Urothelial Carcinoma. Cancers (Basel) . 2023;15. Lobo N, Afferi L, Moschini M, et al. Epidemiology, Screening, and Prevention of Bladder Cancer. Eur Urol Oncol . 2022;5: 628-639. Catto JWF, Downing A, Mason S, et al. Quality of Life After Bladder Cancer: A Cross-sectional Survey of Patient-reported Outcomes. Eur Urol . 2021;79: 621-632. Ding L, Deng X, Xia W, et al. Development and external validation of a novel nomogram model for predicting postoperative recurrence-free survival in non-muscle-invasive bladder cancer. Front Immunol . 2022;13: 1070043. Herr HW, Donat SM. Quality control in transurethral resection of bladder tumors. BJU Int . 2008;102: 1242-1246. Brauers A, Buettner R, Jakse G. Second resection and prognosis of primary high risk superficial bladder cancer: is cystectomy often too early? J Urol . 2001;165: 808-810. Ding S, Xing N, Lu J, et al. Overexpression of Eg5 predicts unfavorable prognosis in non-muscle invasive bladder urothelial carcinoma. Int J Urol . 2011;18: 432-438. Sylvester RJ, van der Meijden AP, Oosterlinck W, et al. Predicting recurrence and progression in individual patients with stage Ta T1 bladder cancer using EORTC risk tables: a combined analysis of 2596 patients from seven EORTC trials. Eur Urol . 2006;49: 466-465; discussion 475-467. Kaufmann O, Volmerig J, Dietel M. Uroplakin III is a highly specific and moderately sensitive immunohistochemical marker for primary and metastatic urothelial carcinomas. Am J Clin Pathol . 2000;113: 683-687. Miettinen M, McCue PA, Sarlomo-Rikala M, et al. GATA3: a multispecific but potentially useful marker in surgical pathology: a systematic analysis of 2500 epithelial and nonepithelial tumors. Am J Surg Pathol . 2014;38: 13-22. Yang J, Li C, Tang Y, et al. Diagnostic roles of proliferative markers in pathological Grade of T1 Urothelial Bladder Cancer. J Cancer . 2021;12: 2498-2506. Gerdes J. Ki-67 and other proliferation markers useful for immunohistological diagnostic and prognostic evaluations in human malignancies. Semin Cancer Biol . 1990;1: 199-206. Seo HK, Cho KS, Chung J, et al. Prognostic value of p53 and Ki-67 expression in intermediate-risk patients with nonmuscle-invasive bladder cancer receiving adjuvant intravesical mitomycin C therapy. Urology . 2010;76: 512.e511-517. Özyalvaçli G, Özyalvaçli ME, Astarci HM, et al. Evaluation of different p16 immunostaining methods and the prognostic role of p16/Ki-67 combined expression in non-muscle invasive bladder cancers. Pol J Pathol . 2015;66: 57-66. Otto W, Denzinger S, Fritsche HM, et al. Introduction and first clinical application of a simplified immunohistochemical validation system confirms prognostic impact of KI-67 and CK20 for stage T1 urothelial bladder carcinoma: single-center analysis of eight biomarkers in a series of three hundred six patients. Clin Genitourin Cancer . 2013;11: 537-544. Wu XR, Lin JH, Walz T, et al. Mammalian uroplakins. A group of highly conserved urothelial differentiation-related membrane proteins. J Biol Chem . 1994;269: 13716-13724. Moll R, Wu XR, Lin JH, et al. Uroplakins, specific membrane proteins of urothelial umbrella cells, as histological markers of metastatic transitional cell carcinomas. Am J Pathol . 1995;147: 1383-1397. Colombel M, Soloway MS, Akaza H, et al. Epidemiology, Staging, Grading, and Risk Stratification of Bladder Cancer. European Urology Supplements . 2008;7: 618-626. Oosterlinck W, Kurth KH, Schröder F, et al. A prospective European Organization for Research and Treatment of Cancer Genitourinary Group randomized trial comparing transurethral resection followed by a single intravesical instillation of epirubicin or water in single stage Ta, T1 papillary carcinoma of the bladder. J Urol . 1993;149: 749-752. Elkady N, Sultan M, Elkhouly E. Evaluation of topoisomerase II, ki-67, and P53 expression in non-muscle-invasive urothelial carcinoma and their clinical significance. Indian J Pathol Microbiol . 2018;61: 526-531. Wang L, Feng C, Ding G, et al. Ki67 and TP53 expressions predict recurrence of non-muscle-invasive bladder cancer. Tumor Biol . 2014;35: 2989-2995. Goyal S, Singh UR, Sharma S, et al. Correlation of mitotic indices, AgNor count, Ki-67 and Bcl-2 with grade and stage in papillary urothelial bladder cancer. Urol J . 2014;11: 1238-1247. Quintero A, Alvarez-Kindelan J, Luque RJ, et al. Ki-67 MIB1 labelling index and the prognosis of primary TaT1 urothelial cell carcinoma of the bladder. J Clin Pathol . 2006;59: 83-88. Ding W, Gou Y, Sun C, et al. Ki-67 is an independent indicator in non-muscle invasive bladder cancer (NMIBC); combination of EORTC risk scores and Ki-67 expression could improve the risk stratification of NMIBC. Urol Oncol . 2014;32: 42.e13-49. Gontero P, Casetta G, Zitella A, et al. Evaluation of P53 protein overexpression, Ki67 proliferative activity and mitotic index as markers of tumor recurrence in superficial transitional cell carcinoma of the bladder. Eur Urol . 2000;38: 287-296. Chen JX, Deng N, Chen X, et al. A novel molecular grading model: combination of Ki67 and VEGF in predicting tumor recurrence and progression in non-invasive urothelial bladder cancer. Asian Pac J Cancer Prev . 2012;13: 2229-2234. Jeon C, Kim M, Kwak C, et al. Prognostic role of survivin in bladder cancer: a systematic review and meta-analysis. PLoS One . 2013;8: e76719. March-Villalba JA, Ramos-Soler D, Soriano-Sarrió P, et al. Immunohistochemical expression of Ki-67, Cyclin D1, p16INK4a, and Survivin as a predictive tool for recurrence and progression-free survival in papillary urothelial bladder cancer pTa / pT1 G2 (WHO 1973). Urol Oncol . 2019;37: 158-165. Luo Y, Zhang X, Mo M, et al. High Ki-67 Immunohistochemical Reactivity Correlates With Poor Prognosis in Bladder Carcinoma: A Comprehensive Meta-Analysis with 13,053 Patients Involved. Medicine (Baltimore) . 2016;95: e3337. Lei Y, Li Z, Qi L, et al. The Prognostic Role of Ki-67/MIB-1 in Upper Urinary-Tract Urothelial Carcinomas: A Systematic Review and Meta-Analysis. J Endourol . 2015;29: 1302-1308. Hu P, Deng FM, Liang FX, et al. Ablation of uroplakin III gene results in small urothelial plaques, urothelial leakage, and vesicoureteral reflux. J Cell Biol . 2000;151: 961-972. Wu XR, Sun TT. Molecular cloning of a 47 kDa tissue-specific and differentiation-dependent urothelial cell surface glycoprotein. J Cell Sci . 1993;106 ( Pt 1): 31-43. Ramos-Vara JA, Miller MA, Boucher M, et al. Immunohistochemical detection of uroplakin III, cytokeratin 7, and cytokeratin 20 in canine urothelial tumors. Vet Pathol . 2003;40: 55-62. Huang HY, Shariat SF, Sun TT, et al. Persistent uroplakin expression in advanced urothelial carcinomas: implications in urothelial tumor progression and clinical outcome. Hum Pathol . 2007;38: 1703-1713. Tsumura H, Matsumoto K, Ikeda M, et al. High expression level of preoperative serum Uroplakin III is associated with biologically aggressive bladder cancer. Asian Pac J Cancer Prev . 2015;16: 1539-1543. Szymańska B, Matuszewski M, Dembowski J, et al. Uroplakin IIIa Is a Marker in Bladder Cancer but Seems Not to Reflect Chemical Carcinogenesis. Biomed Res Int . 2018;2018: 8315410. Matsumoto K, Satoh T, Irie A, et al. Loss expression of uroplakin III is associated with clinicopathologic features of aggressive bladder cancer. Urology . 2008;72: 444-449. Tadin T, Krpina K, Štifter S, et al. Significance of uroplakin III expression in recurrence of solitary muscle non-invasive bladder cancer. Pathol Res Pract . 2014;210: 279-284. Bertz S, Otto W, Denzinger S, et al. Combination of CK20 and Ki-67 immunostaining analysis predicts recurrence, progression, and cancer-specific survival in pT1 urothelial bladder cancer. Eur Urol . 2014;65: 218-226. Rubino S, Kim Y, Zhou J, et al. Positive Ki-67 and PD-L1 expression in post-neoadjuvant chemotherapy muscle-invasive bladder cancer is associated with shorter overall survival: a retrospective study. World J Urol . 2021;39: 1539-1547. Yoshida S, Koga F, Kobayashi S, et al. Role of diffusion-weighted magnetic resonance imaging in predicting sensitivity to chemoradiotherapy in muscle-invasive bladder cancer. Int J Radiat Oncol Biol Phys . 2012;83: e21-27. Tsumura H, Matsumoto K, Sato Y, et al. Abnormal expression of multiple proteins predicts cancer-specific mortality in patients with high-grade non-muscle-invasive bladder cancer treated with transurethral resection. Mol Clin Oncol . 2013;1: 473-479. Daza J, Grauer R, Chen S, et al. Development of a predictive model for recurrence-free survival in pTa low-grade bladder cancer. Urol Oncol . 2023;41: 256.e259-256.e215. Mir MC, Marchioni M, Zargar H, et al. Nomogram Predicting Bladder Cancer-specific Mortality After Neoadjuvant Chemotherapy and Radical Cystectomy for Muscle-invasive Bladder Cancer: Results of an International Consortium. Eur Urol Focus . 2021;7: 1347-1354. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5410808","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":377508759,"identity":"da3123f1-764a-41ca-83ae-a2a8abd74591","order_by":0,"name":"Junchao Wu","email":"","orcid":"","institution":"Second Affiliated Hospital of Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Junchao","middleName":"","lastName":"Wu","suffix":""},{"id":377508760,"identity":"de85be6b-9a16-4091-83a0-c10e933cd0c5","order_by":1,"name":"Xuede 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06:12:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":92122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curve of the best intercept value of Ki-67\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/62ed7877ba29b5a9537487bb.png"},{"id":71605901,"identity":"3a02fcc1-af0e-45cd-94e5-d543bf8f8fd5","added_by":"auto","created_at":"2024-12-17 06:12:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":665138,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKi-67 expression with RFS(a), PFS(b) and CSS(c) survival graphs\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/e4041b9a124d315d7fcd7775.png"},{"id":71605911,"identity":"244c7b1d-90a2-4b4b-89e5-4a4458e7fc20","added_by":"auto","created_at":"2024-12-17 06:13:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":470223,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUP-III expression with RFS(a), PFS(b) and CSS(c) survival graphs\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/26ac3460c689f06418dccbe0.png"},{"id":71605909,"identity":"fcec71f2-1f8c-4aef-b697-ec88fc3dd717","added_by":"auto","created_at":"2024-12-17 06:13:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1208726,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJoint indicators with RFS(a), PFS(b) and CSS(c) survival graphs\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/c64381d66b45895538d151ec.png"},{"id":71605904,"identity":"8cf433bd-e25c-4af0-8af8-087db028c045","added_by":"auto","created_at":"2024-12-17 06:12:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":593662,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe\u003c/strong\u003e \u003cstrong\u003eJoint indicators nomogram of RFS(a), PFS(b) and CSS(c)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/fc36474977a39c8a7022b514.png"},{"id":71605902,"identity":"7630034b-a961-4bd8-804c-a1e23d5bac77","added_by":"auto","created_at":"2024-12-17 06:12:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":530989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves of the RFS(a), PFS(b) and CSS(C) nomogram in the training set\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/1f9e7318fa370a30610074f5.png"},{"id":71605903,"identity":"a9a0de5d-ead8-45a1-86a4-91bf5884631c","added_by":"auto","created_at":"2024-12-17 06:12:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":520176,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves of the RFS(a), PFS(b) and CSS(C) nomogram in the validation set\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/0806796bffed7be1c18c3e64.png"},{"id":72957457,"identity":"516a0fb1-f8be-4756-8bf5-f96e221f5534","added_by":"auto","created_at":"2025-01-04 11:31:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5848173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5410808/v1/526ada83-64c9-4179-8aaf-2dad40134556.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The value of Ki-67 combined with Uroplakin-III in predicting the prognosis of bladder non-muscle invasive urothelial carcinoma","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe 10th most frequent malignancy worldwide, bladder cancer (BC) has significant incidence and death\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. At least 75% of BC cases are non-muscle invasive bladder cancer (NMIBC), which has a diverse risk of recurrence and progression to muscle invasive bladder cancer (MIBC)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.NMIBC possesses a remarkable 5-year survival rate (\u0026gt;\u0026thinsp;90%)\u003csup\u003e3\u003c/sup\u003e, but its recurrence rate is substantial, and most patients require long-term cystoscopic monitoring and various treatment procedures, lowering health-related quality of life\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Main therapy for NMIBC is transurethral resection of bladder tumor (TURBT)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and the initial TURBT is crucial for diagnosis and prognosis\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.The residual tumor rate following the initial TURBT was 4%-78%, depending on stage and quantity\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, surgeon skill and specimen quality may underestimate tumor pathological stage. Patients with NMIBC have a higher chance of progression and recurrence, prompt radical cystectomy (RC) is crucial\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. A 45% 5-year disease progression rate is possible in NMIBC patients\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. NMIBC diagnosis, treatment, and follow-up should be tailored to each patient's unique risk due to the high recurrence and progression rates in low-risk patients, the high rate of progression in high-risk patients, the requirement for lifetime follow-up, and the high cost of treatment\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Recently, various molecular markers have been employed to assess NMIBC prognosis. Immunohistochemical staining for Ki-67, CK 20, UP-III, GATA-3, and p53 is prevalent for urothelial cancer, although their specificity is restricted\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eKi-67 is a nuclear protein that is part of the DNA replicase complex that is encoded by the MKI67 gene on chromosome 10, as found by Gerdes\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and Ho Kyung Seo\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. It is required for cell proliferation and is articulated in the proliferative phase (G1, S, G2 and mitosis) but not in the stationary phase (G0) throughout the cell cycle\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Thus, Ki-67 can be used as a biomarker to measure cell proliferation. Otto et al\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e realised that higher Ki-67 expression in T1 UBC tissues was connected to poor recurrence-free, progression-free, and tumor-specific survival. Uroplakins (UPs) consist of four transmembrane proteins (UPs Ia, Ib, II and III), of which Uroplakin-III is an asymmetric unit 47KDa glycoprotein\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Using polyclonal antibodies, Moll et al\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e obtained UP-III in 53% of primary and 66% of metastatic urothelial carcinomas in paraffin-embedded immunohistochemistry (IHC). However, many non-urothelial carcinomas were consistently negative in the assay. It can be seen that UP-III is a urothelial cell-specific differentiation product.\u003c/p\u003e \u003cp\u003eOn this basis, the TURBT follow-up and clinical data of bladder non-muscle invasive urothelial carcinoma (NMIUC) patients were retrospectively analysed. To assess Ki-67 and Uroplakin-III expression in bladder NMIUC prognosis.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Patients and clinical data\u003c/h2\u003e \u003cp\u003eThis retrospective analysis examined TURBT patients with bladder NMIUC at Kunming Medical University Second Affiliated Hospital from January 2017 until December 2019. Age, sex, tumor number, size, pathological stage, histological grade, type, concurrent carcinoma in situ (CIS), Ki-67, Uroplakin III, RFS, PFS, and CSS are included. The WHO 2016 BC classification system was utilised for histological grading and the 2017 UICC TNM staging method (8th edition) for pathological staging.\u003c/p\u003e \u003cp\u003eInclusion criteria: (1) All patients underwent TURBT; (2) Patients with bladder urothelial carcinoma confirmed by pathological examination; (3) Pathological examination including Ki-67 and(or) Uroplakin III immunohistochemical staining; (4) Patient's clinical and follow-up information was complete.\u003c/p\u003e \u003cp\u003eExclusion criteria: (1) patients with secondary bladder tumors confirmed by imaging and pathological examination; (2) patients with tumor invading the muscular layer; (3) patients without postoperative intravesical chemotherapy using gemcitabine hydrochloride; (4) patients whose cause of death was not BC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Operation method\u003c/h2\u003e \u003cp\u003eAfter the anesthesia was effective, the patients were taken to the lithotomy position and routinely disinfected with sterile towels. Normal saline was used as irrigation solution. The location and size of bladder tumor were observed under the plasma resectoscope under direct vision, and the tumor was resected by plasma resectoscope. The tumor was resected in different layers. The range of resection included normal tissue 2 cm around the tumor, and the depth of resection was the deep muscular layer. After excision, the bleeding was stopped carefully and the basal wound was electrocoagulated. Ellik irrigators flush out the electrocut tissue. The indwelling 3-lumen catheter was connected with normal saline for irrigation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Immunohistochemical method\u003c/h2\u003e \u003cp\u003eAfter dewaximed and hydrated with xylene and 100% ethanol, paraffin sections were repaired in EDTA buffer under high pressure for 10 minutes, sealed for 10 minutes with 3% hydrogen peroxide, after overnight primary antibody incubation at 4℃, universal secondary antibody was applied at 37℃ for 30 minutes. The staining was observed under DAB light microscope. Hematoxylin counterstained, routinely dehydrated, clear, neutral resin sealed sections of bladder tumor were stored at room temperature in blocking solution containing 0.3% hydrogen peroxide. The Fujian Maixin Biotechnology Co. LTD.-purchased mouse anti-human monoclonal antibody (MIB-1) identified Ki-67 protein. Ki-67 labelling index was used to measure immune activity, identify locations with high immunoreactivity, and score 1000 cells to determine Ki-67-positive cell percentage. A rabbit anti-human UP-III polyclonal antibody (1/100 dilution, 1 hour at room temperature) from Lifespan, USA was used to count positive staining cells in 20 randomly selected high-power cells to determine expression. At least 5% of tumor cells were labelled for positive.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Follow-up of patients\u003c/h2\u003e \u003cp\u003ePatients' follow-up data was acquired via outpatient chemotherapy medication infusion, inpatient reexamination, and telephone. Patient postoperative follow-up was: In low-risk patients with negative results, a second cystoscopy was done 1 year after the first 3 months. Until the fifth year, B ultrasounds and pelvic magnetic resonance imaging were done every six months. High-risk patients got cystoscopy every 3 months for 2 years, 6 months from 3rd year, and yearly from 5th until life. After treatment, follow-up followed the protocol if recurrence occurred. The hospitalization reexamination investigated blood, tumor markers, urine, urine exfoliative cytology, CT urography, chest and abdominal CT, tumor recurrence, progression, causes of death, and event time. Follow-up extended from surgery to study conclusion. RFS was the period from full remission to recurrence or end of follow-up after transurethral resection. From randomisation to BC progression, death, or end of follow-up, PFS was calculated. BC CSS was the time from diagnosis to death or follow-up. November 2022 was the follow-up deadline.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Rule of classification\u003c/h2\u003e \u003cp\u003eReceiver operator characteristic (ROC) curve analysis used CSS as the outcome index and the Ki-67 expression with the highest Youden index as the best cut-off value. The optimal cut-off value divided patients into high and low Ki-67 expression groups. Uroplakin-III immunohistochemistry divided patients into positive and negative groups. The combined markers were split into four groups: Ki-67 high\u0026thinsp;+\u0026thinsp;Uroplakin-III positive, negative, positive, and negative. The nomogram patients were randomly assigned to training and validation sets 3:1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical method\u003c/h2\u003e \u003cp\u003eThis paper used SPSS25.0 (SPSS Inc.; Armonk, NY, USA). χ2 test was used for data counting. If the sample size is \u0026ge;\u0026thinsp;40 and the expected value is \u0026lt;\u0026thinsp;5, the correction χ2 test is employed. When the sample size is \u0026lt;\u0026thinsp;40 and at least one predicted value is \u0026lt;\u0026thinsp;1, Fisher exact test is used. T test assessed measuring data normality. Univariate binary logistic regression analyzed RFS, PFS, and CSS clinicopathological variables. Cox proportional hazards regression model was used for multivariate analysis of indicators with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis (reference indicators were negative outcome indicators). The two indicators' predictive potential is tested by multiple linear regression. RFS, PFS, and CSS median survival times were estimated using Kaplan\u0026ndash;Meier analysis. Every factor's predictive potential was evaluated using the ROC curve. In Rstudio 1.4, joint indicator training and validation data was randomly partitioned. A nomogram was built to predict RFS, PFS, and CSS using P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 risk variables in multivariate Cox regression analysis. The area under the ROC curve measured training and validation set fit and model predictiveness. All statistical analyses were deemed significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Characteristics of patients\u003c/h2\u003e\n \u003cp\u003eThe Second Affiliated Hospital of Kunming Medical University enrolled 259 bladder NMIUC patients who met inclusion and exclusion criteria and performed TURBT from January 2017 to December 2019. There were 23 incomplete clinical data cases, 12 lost to follow-up, and 94.6% follow-up success. This study includes 209 UP-III and 224 Ki-67 immunohistochemistry participants. The median follow-up was 36 months. Overall patient data is given in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1 \u0026nbsp;General data characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1732896465.png\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. The ROC curve and optimal cut-off value of Ki-67\u003c/h2\u003e\n \u003cp\u003eThe outcome index was Ki-67 CSS, and the ROC curve is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The research variable\u0026apos;s optimal cut-off value was the critical value corresponding to the greatest Youden index. The maximal Youden index was 0.577, corresponding to a 25% Ki-67, 95.0% sensitivity, and 62.7% specificity (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Patients with Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;25% were categorised as low expression according to the best cut-off value, whereas those with Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;25% were classified as high expression.\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eROC curve analysis of Ki-67\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCut-off value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi-67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.756\u0026ndash;0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Analysis of clinicopathological data with Ki-67 and UP-III\u003c/h2\u003e\n \u003cp\u003eClinicopathological data and Ki-67 demonstrated a significant difference (P\u0026thinsp;=\u0026thinsp;0.035) between multiple tumor patients with high (22.1%) and low (11.6%) Ki-67. The difference in Ki-67 expression between 44.2% and 36.4% in T1 tumors was significant (P\u0026thinsp;=\u0026thinsp;0.024). Significantly, strong-grade tumors with high Ki-67 expression were 75.8%, while those with low expression were 22.5% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A 57.9% high and 70.5% low Ki-67 expression differential across papillary cancers (P\u0026thinsp;=\u0026thinsp;0.05). Gender, age, tumor size, and carcinoma in situ did not alter Ki-67 expression (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Upon analyzing clinicopathological data and UP-III expression, 54.9% of high-grade tumors exhibited positive expression, while 26.3% showed negative expression (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Gender, age, tumor size, number, stage, type, and carcinoma in situ did not alter UP-III expression (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis between clinicopathological data and Ki-67\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eKi-67\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e111(86.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80(84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e18(14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e63.12\u0026thinsp;\u0026plusmn;\u0026thinsp;12.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.64\u0026thinsp;\u0026plusmn;\u0026thinsp;11.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e86(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52(54.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e43(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43(45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e114(88.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74(77.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e15(11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21(22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e82(63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53(55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e47(36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42(44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e100(77.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29(22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72(75.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e91(70.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e38(29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40(42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4(3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e125(96.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92(96.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis between clinicopathological data and UP-III\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eUP-III\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e65(85.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112(84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e11(14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21(15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e64.43\u0026thinsp;\u0026plusmn;\u0026thinsp;10.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.89\u0026thinsp;\u0026plusmn;\u0026thinsp;12.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e45(59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31(40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e85(63.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48(36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e66(86.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109(82.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e10(13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e46(60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80(60.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30(39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53(39.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e56(73.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(45.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e20(26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73(54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e53(69.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23(30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1(1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e75(98.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128(96.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003e3.4. Analysisof clinicopathological data, Ki-67 and UP-III immunohisto-chemical expression in relation to tumor recurrence, progression and specific survival\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTumor grade, Ki-67, and UP-III immunohistochemical expression were strongly linked with recurrence in univariate binary logistic regression (P\u0026thinsp;=\u0026thinsp;0.007, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). Several factors, including tumor number, stage, grade, type, Ki-67, and UP-III, were linked to progression (P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cancer-specific survival was linked with age (P\u0026thinsp;=\u0026thinsp;0.003), tumor size (P\u0026thinsp;=\u0026thinsp;0.014), stage (P\u0026thinsp;=\u0026thinsp;0.02), grade (P\u0026thinsp;=\u0026thinsp;0.003), type (P\u0026thinsp;=\u0026thinsp;0.005), and Ki-67 (P\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate Logistic analysis between clinicopathological data and tumor recurrence, progression and specific survival\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRecurrence\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProgression\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecial survival\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate Logistic analysis of Ki-67 and UP-III immunohistochemical expression in relation to tumor recurrence, progression and specific survival\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKi-67(224)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUP-III(209)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecurrence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12/129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38/95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40/133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001, \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProgression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42/95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34/133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001, 0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecial survival\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19/95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13/133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001, 0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eHigh Ki-67 expression and UP-III positivity were strongly linked to lower RFS (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea) in multivariate Cox regression analysis (HR\u0026thinsp;=\u0026thinsp;0.191; 95% CI:0.087\u0026ndash;0.420; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; HR\u0026thinsp;=\u0026thinsp;0.280; 95%CI:0.106\u0026ndash;0.740; P\u0026thinsp;=\u0026thinsp;0.01). High Ki-67 expression (HR\u0026thinsp;=\u0026thinsp;0.059; 95%CI:0.017\u0026ndash;0.202; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was linked to decreased PFS (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eb). CSS was substantially lowered by age (HR\u0026thinsp;=\u0026thinsp;1.066; 95%CI :0.004\u0026ndash;0.273; P\u0026thinsp;=\u0026thinsp;0.001) and high Ki-67 expression (HR\u0026thinsp;=\u0026thinsp;0.034; 95%CI :0.004\u0026ndash;0.273; P\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate Cox regression analysis for the association of patient risk factors with tumor RFS (a), PFS (b), and CSS (c)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ea Parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients(n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.967\u0026ndash;1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.668\u0026ndash;2.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.512\u0026ndash;2.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.127\u0026ndash;1.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.575\u0026ndash;2.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e2.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.799\u0026ndash;10.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon- Papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi-67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.087\u0026ndash;0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUP-III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.106\u0026ndash;0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eb Parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients(n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.976\u0026ndash;1.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.493\u0026ndash;1.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.285\u0026ndash;1.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000-1.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.289\u0026ndash;1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000-3.924\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi-67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.017\u0026ndash;0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUP-III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.468\u0026ndash;2.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ec Parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients(n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u0026ndash;0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.145\u0026ndash;1.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;2cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.266\u0026ndash;2.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor staging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000-1.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.321\u0026ndash;3.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePapillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000-7.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-papillary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi-67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.004\u0026ndash;0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUP-III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.682\u0026ndash;5.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eKi-67 low expression group had 95.3% and 90.7% 1- and 3-year RFS rates, according to Kaplan-Meier (KM) analysis. The Ki-67 high expression group experienced 78.9% and 63.2% 1- and 3-year RFS. The RFS rate differed significantly between groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). Ki-67 low expression group 1- and 3-yearPFS rates were 99.2% and 98.4%. The Ki-67 high expression group had 87.4% and 62.1% 1- and 3-year PFS. The difference between groups was significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb). The Ki-67 low expression group had 100.0% and 99.2% 1- and 3-year CSS rates. The Ki-67 high expression group showed 93.7% and 82.1% 1- and 3-year CSS rates. The difference between groups was significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e\n \u003cp\u003eKM analysis indicated UP-III negative group 1- and 3-year RFS rates of 93.4%. The 1- and 3-year RFS rate of UP-III positives was 83.5 and 69.9%. The difference in RFS rate between groups was considerable (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;3a). 1 and 3 year PFS rates for UP-III negative group were 93.4% and 88.2%. The 1- and 3-year PFS rates for UP-III positive patients were 91.0% and 78.9%. The two groups had significantly different PFS rates (P\u0026thinsp;=\u0026thinsp;0.026) (Fig.\u0026nbsp;3b). CSS rate did not differ between UP-III negative and positive groups (P\u0026thinsp;=\u0026thinsp;0.693) (Fig.\u0026nbsp;3c).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3.5. Correlation of Ki-67 and UP-III joint indicator immunohistochemical expression in relation to RFS, PFS and CSS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAccording to unary linear regression, RFS was longer in the Ki-67 low expression\u0026thinsp;+\u0026thinsp;UP-III negative (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and positive (P\u0026thinsp;=\u0026thinsp;0.001) groups compared to the high expression\u0026thinsp;+\u0026thinsp;UP-III positive group. RFS was not statistically different between Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III negative and positive groups (P\u0026thinsp;=\u0026thinsp;0.076)(Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ea). Ki-67 low expression\u0026thinsp;+\u0026thinsp;UP-III negative (P\u0026thinsp;=\u0026thinsp;0.009) and positive (P\u0026thinsp;=\u0026thinsp;0.005) groups had longer PFS than Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group. There was no substantial difference in PFS between Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III negative and positive groups (P\u0026thinsp;=\u0026thinsp;0.343)(Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eb). CSS was longer in Ki-67 low expression\u0026thinsp;+\u0026thinsp;UP-III negative (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and positive (P \u0026lt;0.001) groups compared to Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group. The CSS was longer in Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive than negative (P\u0026thinsp;=\u0026thinsp;0.022) (Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ec).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnaryLinear Regression of Ki-67 and UP-III joint indicator immunohistochemical expression in relation to RFS(a),PFS(b) and CSS(c)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tabc\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.343\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tabd\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003ec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026lt;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;0.25\u0026thinsp;+\u0026thinsp;UPIII(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eKM analysis showed greater 1-year (76.4%) and 3-year (59.7%) RFS rates for the Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group compared to the low expression\u0026thinsp;+\u0026thinsp;UP-III negative and positive groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P =0.001, respectively). Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea shows no significant difference between groups (P\u0026thinsp;=\u0026thinsp;0.059). The Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group had a considerably higher PFS rate (80.6% at 1 year and 59.5% at 3 years) compared to the low expression\u0026thinsp;+\u0026thinsp;UP-III negative and positive groups (P\u0026thinsp;\u0026lt;\u0026thinsp;The Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III negative group did not vary (P\u0026thinsp;=\u0026thinsp;0.766) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb).The Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group had significantly higher 1- and 3-year CSS rates (86.1% and 82.3%, respectively) compared to the negative and positive groups (P\u0026thinsp;=\u0026thinsp;0.001, P\u0026thinsp;=\u0026thinsp;0.003). Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec shows no significant difference between the Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III negative group (P\u0026thinsp;=\u0026thinsp;0.071).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6. Establishment of a joint indicators prediction model based on nomogram\u003c/h2\u003e\n \u003cp\u003eCox multifactor analysis determines three variables for the nomogram. The nomogram can predict BC recurrence, progression, and cancer-specific survival up to 5 years following main surgery. The model\u0026apos;s AUC of 0.912, 0.870, and 0.942 indicated high predictive accuracy of the 5-year RFS, PFS, and CSS rates, respectively. The internal validation sett performed well with AUCs of 0.875, 1.000, and 0.945 (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n"},{"header":"4 Discussion","content":"\u003cp\u003eLack of solid prognostic indicators makes clinical decision-making and therapy of bladder NMIUC challenging. Conventional evaluation protocols seem to be inadequate to provide accurate prognoses for patients with diverse and complex tumor backgrounds. Thus, molecular studies of BC biology may improve forecasts. This study assessed the pathological grading of bladder NMIUC using these molecular markers.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Correlation between clinicopathological parameters and BC patients\u003c/h2\u003e \u003cp\u003eAbout 60% of BCs present as superficial (pT1 or pTa) UBC, where the tumor is limited to the lamina propria or epithelium\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. After TURBT, 40 to 80% of cases may have tumor recurrence, and 20 to 30% of cases may have tumor progression with muscularis propria invasion\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Tumor size, grade, depth of invasion, numerous tumor foci, and CIS all affect tumor recurrence or progression\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, bladder NMIUC investigation, univariate logistic regression showed a strong association between tumor grade and recurrence. Tumor progression was substantially linked with tumor number, stage, grade, and type. Age, tumor size, stage, grade, and type substantially affected cancer-specific survival. Ageing dramatically decreased CSS in multivariate cox regression analysis. Our findings roughly match those of earlier researchers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Correlation between Ki-67 expression and BC patients\u003c/h2\u003e \u003cp\u003eTumors with fast cell division and high growth fraction display Ki-67, an indicator of the growth of cells. Thus, Ki-67 expression monitoring can predict recurrence and progression. Few unvalidated UBC Ki-67 cutoffs have been reported internationally, but they are valuable in diagnosis, indicating relative trends and their specificity and sensitivity, and guiding future study.\u003c/p\u003e \u003cp\u003eWang et al\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e discovered that big and numerous tumors expressed Ki67 more. Related investigations found that high-grade and aggressive UBCs had much more Ki-67 expression than low-grade and superficial UBC. Related studies have shown that the average Ki-67 expression was significantly greater in high-grade and aggressive UBCs compared to low-grade and superficial UBC\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Yang's research\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e found that T1 stage UBC patients with Ki-67\u0026thinsp;\u0026gt;\u0026thinsp;15% had a 13.989 times greater incidence of high-grade tumors compared to those with Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;15% (95% CI\u0026thinsp;=\u0026thinsp;3.691\u0026ndash;53.022, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Many investigations have linked Ki-67 to high grade, stage, and submucosal invasion\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.These data indicate that UBC aggressiveness and malignancy are positively linked with Ki-67 expression. Ki-67\u0026thinsp;\u0026gt;\u0026thinsp;20% predicted superficial low-grade BC recurrence, according to Gontero\u0026rsquo;s study\u003csup\u003e25[23]\u003c/sup\u003e. Chen\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e identified that the 25% Ki-67 expression threshold has 73.52% sensitivity and 73.53% specificity for predicting recurrence. Goyal et al\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e found that Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;59% had 100% specificity for invasive BC, which has practical implications for tumor staging and treatment in cases where morphological evidence of muscle invasion is not clear. Jeon\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and Jos\u0026eacute;\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e observed that Ki-67 predicted recurrence and progression in pTa and pT1 BC patients. In a later meta-analysis of 13,053 BC patients\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, increased Ki-67 expression at 20% was substantially linked with poorer univariate RFS, PFS, DFS, CSS, and OS. Otto et al\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e showed that high Ki-67 expression in tissues of UBC patients with T1 stage had poor RFS, PFS, and CSS. The study of et al March\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e also confirmed that Ki-67 could improve the predictive efficacy of RFS and PFS in pTa/pT\u003csub\u003e1\u003c/sub\u003e papillary UBC with intermediate differentiation (grade 2,G2). Lei et al.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e conducted a meta-analysis found that increased Ki-67 expression in urothelial carcinoma was related with shorter 5-year DFS and OS, and worse cancer-specific mortality. This study employed ROC curve to find the optimal Ki-67 cutoff value of 25%, which was also found in numerous studies\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHigh Ki-67 expression was linked with numerous, T1, high-grade, and non-papillary tumors in clinicopathological analysis. RFS, PFS, and CSS were substantially linked with Ki-67 in univariate logistic regression. High Ki-67 expression substantially lowered RFS, PFS, and CSS in multivariate Cox regression analysis. KM survival analysis indicated that elevated Ki-67 expression significantly lowered 1-, 3-, and 5-year RFS, PFS, and CSS rates. It mostly agrees with earlier research. Multiple studies have shown that aberrant Ki-67 expression is a separate forecasting predictor for bladder NMIUC recurrence, progression, and cancer-specific survival.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Correlation between UP-III expression and BC patients\u003c/h2\u003e \u003cp\u003eUrothelial plaques, two-dimensional crystals made of integral membrane proteins termed uroplakins, cover 90% of the apical surface\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The only urothelial plaque containing a 50-amino-acid cytosolic domain was UP-III, which may attach plaques to the cytoskeleton\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The only urothelial plaque containing a 50-amino-acid cytosolic domain was UP-III, which may attach plaques to the cytoskeleton Earlier studies confirmed UP III as a specific and sensitive marker of urothelial carcinoma in dogs, detecting 91% of urothelial cell carcinomas\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. And one investigations have shown that UP-III is important for urothelial permeability barrier modulation, surface area stabilisation, and urinary tract development\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTsumura et al.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e found that BC patients had higher serum UP-III levels, which were associated with myometrial invasion, strong differentiation, and lymphatic invasion, and high serum UP-III also significantly increased tumor-specific mortality. The study of Szymańska\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e further showed that patients with BC had significantly increased UP-III expression in their plasma and urine, with a notable distinction between low-grade and high-grade groups. Matsumoto et al\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e reported that UP-III depletion linked with lymphovascular invasion, clinical stage, and grade. Kaufmann\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e found that Au 1, a monoclonal antibody against UP-III, is a highly specific IHC marker for urothelial carcinoma and has moderate sensitivity for distinguishing primary and metastatic urothelial carcinoma, but tumor grade and stage do not significantly affect UP-III expression. Tadin\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e discovered that UP-III positive expression was connected with tumor recurrence, tumor size, disease stage, and tumor infiltrating lymphocytes in NMIBC.\u003c/p\u003e \u003cp\u003eIn this study, clinicopathological results showed that high-grade tumors have UP-III positive expression. In univariate logistic regression, UP-III was linked with bladder NMIUC recurrence and progression but not cancer-specific survival. In multivariate Cox regression analysis, UP-III high expression was associated with shortened RFS time but not PFS or CSS. High UP-III expression was related with lower 1 year, 3 year, and 5 year RFS and PFS rates, but not CSS rates, according to KM survival analysis. The study found no significant link between UP-III and CSS, possibly due to the little amount of data on disease-related fatalities, which increases prediction bias. Our study agrees with Tadin et al., but there are few and different conclusions about UP-III and bladder tumors at home and abroad, especially on tumor progression and disease-related death, so more research is needed to confirm their correlation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Correlation between combined indicators and prognosis of BC patients\u003c/h2\u003e \u003cp\u003eSeveral studies have indicated that a multiparameter diagnostic approach is better than a single test for T1 stage UBC pathological grading. Ding et al\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e demonstrated that the European Organization for Research and Treatment of Cancer (EORTC) risk score and Ki-67 expression can better predict NMIBC recurrence and progression. Especially for those with EORTC moderate risk scores. Chen et al\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e presented evidence that a unique model of molecular grading in Ki-67 and Vascular Endothelial Growth Factor(VEGF) score may accurately predict results and optimise therapy. Bertz et al\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e examined Ki-67 and CK20 as joint variables that may enhance T1 stage UBC risk classification. Early radical cystectomy for T1G3 UBC patients with Ki-67 and CK20 expression is recommended. Combining Mitotic Index (MI), Ki-67 index, and P504S can enhance pathological grading of T1 stage UBC in a multivariate diagnostic model\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Rubino\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e also found that Ki-67 positive expression was significantly correlated with PD-L1 positive expression (P\u0026thinsp;=\u0026thinsp;0.001), and the combination of the two could assess OS and CSS in MIBC patients undergoing RC after neoadjuvant chemotherapy. Patients with positive PD-L1 and Ki-67 expression had substantially poorer CSS and OS rates than those with negative expression. Yoshida\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e observed that Apparent Diffusion Coefficient (ADC) was adversely linked with Ki-67 expression in bladder tumor tissues. Bladder tumors with lower ADC and greater Ki-67 respond better to CRT. Tsumura et al\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e confirmed that aberrant expression of E-cadherin, Coxsackievirus receptor, S100A4, and UP-III in NMIBC tumor tissues following TURBT increased tumor-specific survival (P\u0026thinsp;=\u0026thinsp;0.016). The 5-year CSS for patients with 0\u0026ndash;1 and \u0026ge;\u0026thinsp;2 molecular markers was 91% and 66%, respectively. No researchers have combined Ki-67 and UP-III to evaluate BC prognosis.\u003c/p\u003e \u003cp\u003eIn this study, KM survival analysis of bladder NMIUC with Ki-67 and UP-III showed that patients with low Ki-67 expression and negative UP-III were divided into two groups. In the Ki-67 high expression\u0026thinsp;+\u0026thinsp;UP-III positive group, the risk of recurrence, progression, and death was higher, and the 1-, 3-, and 5-year RFS, PFS, and CSS rates were lower. This suggests that the two indicators can better predict the prognosis of bladder NMIUC patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Comparison of prognostic models\u003c/h2\u003e \u003cp\u003eLi Ding et al\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e created an RFS nomogram using NMIBC previous recurrence status, intravesical instillation, and systemic immune inflammation index. 0.835, 0.833, and 0.871 were the area under the curve for 1, 2, and 3-year RFS predictions.\u003c/p\u003e \u003cp\u003eJorge Daza, M.D. et al\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e suggested that patients with multifocal, single, or tumor\u0026thinsp;\u0026ge;\u0026thinsp;4cm NMIBC had the worst RFS. Maria et al\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e indicates that the nomogram based on pathological stages and positive surgical margins to predict the specific mortality in MIBC patients. Model area under curve is 0.65. Model AUC for 5-year BC specific mortality was 0.75. Our model predicts RFS,PFS, and CSS better than the others.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Limitation\u003c/h2\u003e \u003cp\u003eThis study also has flaws. First, this work is retrospective, thus further high-quality prospective or randomised controlled trials are needed to corroborate the experimental results. Second, this study is single-center, and CSS research is few, making outcomes untrustworthy. There may be selection bias in the process of patient visit, which may lead to inaccurate experimental results. The cut-off value of Ki-67 may change according to research data tampering, however there is enough evidence to link it to BC patients' prognoses.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study indicated that bladder NMIUC patients with Ki-67 and UP-III had independent prognostic markers for tumor recurrence, progression, and mortality. Positive Ki-67 and UP-III expression are related with poor prognosis, which helps enhance patient risk classification. Ki-67 with UP-III demonstrated good predictive discrimination and stability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter discussion and decision by the Ethics Committee of the Second Affiliated Hospital of Kunming Medical University, the study was approved to be conducted in the center. This study is a retrospective study, and informed consent exemption has been obtained. The ethics approval number is FEY-BG-39-2.0on 01/05/2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no funding for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZimpfer A, Kdimati S, Mosig M, et al. ERBB2 Amplification as a Predictive and Prognostic Biomarker in Upper Tract Urothelial Carcinoma. \u003cem\u003eCancers (Basel)\u003c/em\u003e. 2023;15.\u003c/li\u003e\n\u003cli\u003eLobo N, Afferi L, Moschini M, et al. Epidemiology, Screening, and Prevention of Bladder Cancer. \u003cem\u003eEur Urol Oncol\u003c/em\u003e. 2022;5: 628-639.\u003c/li\u003e\n\u003cli\u003eCatto JWF, Downing A, Mason S, et al. Quality of Life After Bladder Cancer: A Cross-sectional Survey of Patient-reported Outcomes. \u003cem\u003eEur Urol\u003c/em\u003e. 2021;79: 621-632.\u003c/li\u003e\n\u003cli\u003eDing L, Deng X, Xia W, et al. 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Development of a predictive model for recurrence-free survival in pTa low-grade bladder cancer. \u003cem\u003eUrol Oncol\u003c/em\u003e. 2023;41: 256.e259-256.e215.\u003c/li\u003e\n\u003cli\u003eMir MC, Marchioni M, Zargar H, et al. Nomogram Predicting Bladder Cancer-specific Mortality After Neoadjuvant Chemotherapy and Radical Cystectomy for Muscle-invasive Bladder Cancer: Results of an International Consortium. \u003cem\u003eEur Urol Focus\u003c/em\u003e. 2021;7: 1347-1354.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bladder cancer, Ki-67, Uroplakin III, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-5410808/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5410808/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo assess the predictive significance of Ki-67, Uroplakin-III, and their combination in bladder non-muscle invasive urothelial cancer patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective analysis of 224 bladder non-muscle invasive urothelial carcinoma patients who had transurethral resection at the Kunming Medical University Second Affiliated Hospital from January 2017 until December 2019 was performed. Patients were separated into Ki-67 high and low expression groups and Uroplakin-III positive and negative expression groups. Predictive models were built using univariate binary logistic regression, Cox proportional hazards regression model for multivariate analysis, unary linear regression, Kaplan-Meier survival analysis, nomogram, and AUC.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRecurrence was substantially linked with tumor grade, Ki-67, and UP-III in univariate binary logistic regression. Tumor progression was linked to tumor number, stage, grade, type, Ki-67, and UP-III. Age, tumor size, stage, grade, type, and Ki-67 affected cancer survival. Ki-67 and UP-III positivity significantly decreased recurrence-free survival (RFS) in multivariate Cox regression analysis. PFS was dramatically lowered by high Ki-67. Age and elevated Ki-67 substantially affected cancer-specific survival. In unary linear regression and Kaplan-Meier analysis, high Ki-67 coupled UP-III positive lowered RFS, PFS, and CSS. AUC\u0026thinsp;=\u0026thinsp;0.912, 0.870, and 0.942 on the ROC curves demonstrated that the model predicted 5 year RFS, PFS, and CSS rates well. The internal validation sett also performed well.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study found that Ki-67 and UP-III are independent predictive markers for bladder non-muscle invasive urothelial carcinoma recurrence, progression, and death. Positive Ki-67 and UP-III expression are related with poor prognosis. Ki-67 with UP-III demonstrated good predictive discrimination and stability.\u003c/p\u003e","manuscriptTitle":"The value of Ki-67 combined with Uroplakin-III in predicting the prognosis of bladder non-muscle invasive urothelial carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-17 06:12:51","doi":"10.21203/rs.3.rs-5410808/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98d48ca6-a0bd-4bed-8fd2-9d19c6552cd9","owner":[],"postedDate":"December 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-04T11:23:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-17 06:12:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5410808","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5410808","identity":"rs-5410808","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}