PURPOSE:To explore the relationship between surfactant protein B (SFTPB) gene expression and multiple biological processes in lung adenocarcinoma (LUAD) and construct a SFTPB-related gene signature for predicting LUAD prognosis. METHODS:Utilizing open-access datasets, we systematically investigated the association of SFTPB expression with patient prognosis, clinicopathological characteristics, immunoinfiltration, drug sensitivity, gene mutations, and methylation levels using the publicly available data. Pathway analysis revealed SFTPB-related signaling cascades, with distinct gene expression profiles being discerned when comparing groups exhibiting high versus low SFTPB expression levels. Additionally, we screened for optimal gene combinations for identifying prognostic signature and generated a nomogram using independent prognostic factors. RESULTS:SFTPB was significantly downregulated in LUAD samples, and patients with high SFTPB expression exhibited favorable survival. The high-SFTPB expression group exhibited lower tumor immune dysfunction and exclusion scores, IC50 values for eight chemotherapy drugs, and tumor mutation burden values. SFTPB expression was associated with multiple immune cells, including macrophages and activated CD4 T cells. Furthermore, we identified seven pathways, including such as PI3K-AKT-mTOR, associated with SFTPB. A risk model with high predictive value for the prognosis of patients with LUAD was constructed using ANLN, LYPD3, and IRX5. CONCLUSIONS:SFTPB expression was correlated with multiple biological processes in LUAD and may therefore serve as a valuable prognostic marker for LUAD.

Accurate differentiation between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) is essential for guiding treatment decisions and predicting outcomes for non-small cell lung cancer (NSCLC). However, CT-based subtype discrimination remains challenging due to overlapping imaging features and inter-observer variability. We developed an improved deep learning framework integrating residual connections, attention mechanisms, and a bidirectional feature pyramid network (BiFPN), combined with an ensemble strategy, to classify NSCLC subtypes on annotated CT slices. A total of 290 patients were retrospectively enrolled from two centers, with 200 used for training and internal validation, and 90 for external testing. Ablation experiments were conducted to evaluate the contribution of each architectural component. Model performance was assessed using F1-score, precision, accuracy, and the area under the receiver operating characteristic curve (AUC). Grad-CAM was applied to provide visual interpretability. In the internal validation cohort, the proposed model achieved an F1-score of 0.9973, precision of 0.9946, accuracy of 0.995, and an AUC of 1.0000, outperforming all benchmark models. In the external test cohort, the model maintained robust generalizability with an F1-score of 0.9508, precision of 0.9667, accuracy of 0.9333, and an AUC of 0.9891, surpassing competing methods. Grad-CAM visualizations demonstrated that the model predominantly focused on radiologically relevant regions, aligning with known imaging features of LUAD and LUSC. This study presents a segmentation-guided, interpretable deep learning model for CT-based NSCLC subtype classification. The model may serve as an adjunctive tool for pre-treatment subtype assessment, while further validation using fully automated lesion localization and larger multicenter datasets is warranted before clinical implementation.

To investigate the predictive value of MRI-derived tumor volume (TV) of biochemical recurrence (BCR) and adverse pathology (AP) in patients following radical prostatectomy (RP). The data of 565 patients receiving RP in a single institution between 2010 and 2021 were retrospectively analyzed. All suspicious tumor foci were delineated manually using ITK-SNAP software as the regions of interest (ROIs). The sum of the TV of all lesions was calculated automatically based on the voxel in the ROIs to acquire the final TV parameter. TV was categorized as low-volume (≤ 6.5 cm3) and high-volume (> 6.5 cm3) based on the cut-off value. Univariate and multivariate Cox and logistic regression analyses were performed to identify independent predictors of BCR and AP. The Kaplan–Meier with the log-rank test was conducted to compare the BCR-free survival (BFS) between the low and high-volume groups. All the included patients were divided into the low-volume group (n = 337) and the high-volume group (n = 228). The TV was an independent predictor of BFS in the multivariate Cox regression analysis (Hazard Ratio (HR) [95

The rapid development of computational pathology has brought new opportunities for prognosis prediction using histopathological images. However, the existing deep learning frameworks lack exploration of the relationship between images and other prognostic information, resulting in poor interpretability. Tumor mutation burden (TMB) is a promising biomarker for predicting the survival outcomes of cancer patients, but its measurement is costly. Its heterogeneity may be reflected in histopathological images. Here, we report a two-step framework for prognostic prediction using whole-slide images (WSIs). First, the framework adopts a deep residual network to encode the phenotype of WSIs and classifies patient-level TMB by the deep features after aggregation and dimensionality reduction. Then, the patients' prognosis is stratified by the TMB-related information obtained during the classification model development. Deep learning feature extraction and TMB classification model construction are performed on an in-house dataset of 295 Haematoxylin & Eosin stained WSIs of clear cell renal cell carcinoma (ccRCC). The development and evaluation of prognostic biomarkers are performed on The Cancer Genome Atlas-Kidney ccRCC (TCGA-KIRC) project with 304 WSIs. Our framework achieves good performance for TMB classification with an area under the receiver operating characteristic curve (AUC) of 0.813 on the validation set. Through survival analysis, our proposed prognostic biomarkers can achieve significant stratification of patients' overall survival (P 0.05) and outperform the original TMB signature in risk stratification of patients with advanced disease. The results indicate the feasibility of mining TMB-related information from WSI to achieve stepwise prognosis prediction.

Context: The role of tumor size in predicting prognosis in upper tract urothelial carcinoma (UTUC) patients remains poorly defined. Objective: To assess the prognostic value of tumor size in patients with UTUC through a systematic review and meta-analysis. Evidence acquisition: A comprehensive literature search of the PubMed and Embase databases were performed to identify all relevant articles published up to December 2021 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Available hazard ratios (HRs) and corresponding 95% confidence intervals (95% CIs) were analyzed to evaluate the association between tumor size and survival outcomes. Evidence synthesis: A total of 35 articles representing 32 292 patients met the eligibility criteria and were finally included for the meta-analysis. Tumor size was significantly associated with poor outcomes in terms of overall survival (HR = 1.42, 95% CI = 1.28–1.58), cancer-specific survival (HR = 1.66, 95% CI = 1.47–1.88), recurrence-free survival (HR = 1.25, 95% CI = 1.13–1.38), and intravesical recurrence (HR = 1.12, 95% CI = 1.04–1.20). There was between-study heterogeneity in the effect of tumor size on all these meta-analyses, with p < 0.10 and I2 generally >50%. Subgroup analyses illustrated that the association of tumor size with adverse prognosis in UTUC patients is not affected by treatment modalities. Segmental resection of ureter, whether receiving lymph node dissection, cutoff of tumor size, and region of population were potential sources of heterogeneity. The funnel plot test indicated no significant publication bias in the meta-analysis of survival outcomes. Conclusions: This study shows that larger tumor size is associated with an increased risk of overall and cancer-specific mortality, and disease recurrence in UTUC. Integration of tumor size with other prognostic indicators may help in risk stratification and individualized treatment of UTUC. Patient summary: Through a systematic review and meta-analysis, this study found that larger tumor size is associated with an increased risk of overall and cancer-specific mortality, and disease recurrence in patients with upper tract urothelial carcinoma.

There are many potential immunotherapeutic targets for cancer immunotherapy, which should be assessed for efficacy before they enter clinical trials. Here we established an ex vivo cultured patient-derived tumor tissue model to evaluate antitumor effectiveness of one VISTA inhibitor, given that our previous study showed that VISTA was selectively highly expressed in human clear cell renal cell carcinoma (ccRCC) tumors. We observed that all the tested patients responded to the anti-VISTA monoclonal antibody as manifested by TNF-α production, but only a small fraction were responders to the anti-PD-1 antibody. Co-blockade of VISTA and PD-1 resulted in a synergistic effect in 20% of RCC patients. Taken together, these findings indicate that this ex vivo tumor slice culture model represents a viable tool to evaluate antitumor efficacies for the inhibitors of immune checkpoints and further supports that VISTA could serve as a promising target for immunotherapy in ccRCC.

You have accessJournal of UrologyCME1 May 2022MP57-05 ONE NOVEL NOMOGRAM TO PREDICT BIOCHEMICAL RECURRENCE MORE ACCURATE IN RADICAL PROSTATECTOMY Jian Lu, Ji De He, Ye Yan, Xue Hua Zhu, Ze Nan Liu, Hai Zhui Xia, Hai Bi, Bin Yang, Run Zhuo Ma, Wei He, Zhi Ying Zhang, Yu Ting Zhang, Lu Lin Ma, and Xiao Fei Hou Jian LuJian Lu More articles by this author , Ji De HeJi De He More articles by this author , Ye YanYe Yan More articles by this author , Xue Hua ZhuXue Hua Zhu More articles by this author , Ze Nan LiuZe Nan Liu More articles by this author , Hai Zhui XiaHai Zhui Xia More articles by this author , Hai BiHai Bi More articles by this author , Bin YangBin Yang More articles by this author , Run Zhuo MaRun Zhuo Ma More articles by this author , Wei HeWei He More articles by this author , Zhi Ying ZhangZhi Ying Zhang More articles by this author , Yu Ting ZhangYu Ting Zhang More articles by this author , Lu Lin MaLu Lin Ma More articles by this author , and Xiao Fei HouXiao Fei Hou More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002640.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Various prediction tools have been developed to predict biochemical recurrence (BCR) after radical prostatectomy (RP), however, few of the previous prediction tools used serum prostate specific antigen (PSA) nadir after RP and maximum tumor diameter (MTD) at the same time. In this study, a nomogram incorporating MTD and PSA nadir was developed to predict BCR-free survival. METHODS: 337 patients who underwent RP were retrospectively enrolled in this study. The maximum diameter of the index lesion was measured on magnetic resonance imaging (MRI). Cox regression analysis was performed to evaluate independent predictors of BCR. A nomogram was subsequently developed for the prediction of BCR-free survival at 3 and 5 years after RP. Time-dependent receiver operating characteristic (ROC) curve and decision curve analysis were performed to identify the advantage of the new nomogram in comparison with the CAPRA-S score. RESULTS: A novel nomogram was developed to predict BCR by including PSA nadir, MTD, Gleason score, surgical margin (SM), and seminal vesicle invasion (SVI), since these variables were significantly associated with BCR in both univariate and multivariate analysis (p <0.05). In addition, a basic model including Gleason score, SM, and SVI was developed and used as a control to assess the incremental predictive power of the new model. The concordance index of our model was slightly higher than CAPRA-S model (0.76 vs. 0.70, p=0.02) and it was significantly higher than that of the basic model (0.76 vs. 0.66, p=0.001). Time-dependent ROC curves and decision curve analyses also demonstrated the advantages of the new nomogram. CONCLUSIONS: PSA nadir after RP and MTD based on MRI before surgery are independent predictors of BCR. By incorporating PSA nadir and MTD into the conventional predictive model, our newly developed nomogram significantly improved the accuracy in predicting BCR-free survival after RP. Source of Funding: This work was supported by grants from the National Natural Science Foundation of China (No. 61871004); National key research and development program of China (No. 2018YFC0115900) and Peking University Medicine Fund of Fostering Young Scholars’ Scientific & Technological Innovation and the Fundamental Research Funds for the Central Universities (No. BMU2020PYB002). Funds were used for the collection and analysis of data © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e982 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jian Lu More articles by this author Ji De He More articles by this author Ye Yan More articles by this author Xue Hua Zhu More articles by this author Ze Nan Liu More articles by this author Hai Zhui Xia More articles by this author Hai Bi More articles by this author Bin Yang More articles by this author Run Zhuo Ma More articles by this author Wei He More articles by this author Zhi Ying Zhang More articles by this author Yu Ting Zhang More articles by this author Lu Lin Ma More articles by this author Xiao Fei Hou More articles by this author Expand All Advertisement PDF DownloadLoading ...

肾细胞癌(renal cell carcinoma, RCC)是泌尿系常见的肿瘤之一,肾脏肿瘤发病率在全美男性及女性分别排名第7、8 位,近5 年呈持续上升趋势[1].在我国,RCC同样呈现明显增长的趋势[2].早期诊断及治疗对肿瘤的控制尤为重要,随着精准医学时代的来临,传统影像学检查方法再也无法满足新的需求,液体活检的价值逐渐提高,循环肿瘤 DNA (circulating tumor DNA, ctDNA)检测技术提供了新的思路.本文对ctDNA在RCC中的应用进行文献总结.

ObjectiveTo investigate the prognostic significance of metabolic syndrome (MetS) and its components in patients with bladder cancer (BCa) treated with radical cystectomy (RC).MethodsA total of 335 BCa patients who underwent RC between 2004 and 2019 at Peking University Third Hospital (PUTH) were analyzed retrospectively. The Kaplan-Meier method with the log-rank test was performed to assess overall survival (OS) and progression-free survival (PFS). Univariate and multivariate Cox proportional hazard models were conducted to identify the prognostic factors of OS and PFS before and after propensity score matching (PSM).ResultsEnrolled patients were allocated into two groups according to the presence or absence of MetS (n=84 MetS vs n=251 non-MetS), and 82 new matched pairs were identified to balance the baseline characteristics after 1:1 PSM. In the Kaplan-Meier analysis, MetS was associated with better OS (P=0.031) than the group without MetS. In addition, a body mass index (BMI) ≥ 25 was associated with better OS (P=0.011) and PFS (P=0.031), while low high-density lipoprotein cholesterol (HDL-C) was associated with worse OS (P=0.033) and PFS (P=0.010). In all patients, multivariate Cox analysis showed that hemoglobin, pathologic tumor stage and lymph node status were identified as independent prognostic factors for both OS and PFS, while age, MetS and HDL-C were independent prognostic factors only for OS. Reproducible results of multivariate analysis can still be observed in propensity matched patients. The results of further subgroup analysis revealed that the association of MetS with increased OS (P=0.043) and BMI ≥25 with increased OS (P=0.015) and PFS (P=0.029) was observed in non-muscle invasive bladder cancer (NMIBC) patients.ConclusionsMetS was independently associated with better OS in BCa patients after RC, and HDL-C was the only component of MetS that was independently associated with worse OS. MetS and HDL-C may become reliable prognostic biomarkers of OS in BCa patients after RC to provide individualized prognostication and assist in the formulation of clinical treatment strategies.

BACKGROUND: The incidence of small renal mass (SRM) increases, and the prognosis of SRM is poor once metastasized. Therefore, we conducted this study to assess the clinical and pathological characteristics of SRM to determine the risk factors that influence the metastasis and prognosis of SRM. METHODS: A small renal mass is defined as a solid tumor mass with the largest diameter of 4 cm or less on the pathological diagnosis. The metastasis is confirmed by imaging or pathological examination. We retrospectively included 40 patients with metastatic SRM (mSRM) treated in the department of urology of Peking University Third Hospital from October 2002 to October 2020. Meanwhile, 358 patients with nonmetastatic SRM treated in our hospital from January 2015 to December 2017 were selected as controls. Clinicopathologic features were compiled. RESULTS: Multivariate logistic regression analysis showed that age (P = .027, odds ratio [OR] = 1.037, 95% confidence interval [CI] 1.004-1.070), clinical symptoms (P < .001, OR = 4.311, 95% CI 1.922-9.672), World Health Organization/International Society of Urological Pathology (WHO/ISUP) nuclear grade 3/4 (P = .004, OR = 7.637, 95% CI 1.943-30.012; P = .004, OR = 20.523, 95% CI 2.628-160.287), and lymphatic invasion (P = .030, OR = 15.844, 95% CI 1.314-191.033) were risk factors for distant metastasis of SRM. Once metastasis occurs, the prognosis of SRM is poor. Multivariate Cox regression analysis of the prognosis of mSRM showed that age (P = .016, hazard ratio [HR] = 1.125, 95% CI 1.022-1.239), preoperative serum creatinine (P = .041, HR = 1.003, 95% CI 1.000-1.005), vascular invasion (P = .041, HR = 1.003, 95% CI 1.000-1.005), and metastasis (P < .001, HR = 24.069, 95% CI 4.549-127.356) were risk factors for overall survival (OS), and only metastasis (P < .001, HR = 9.52, 95% CI 5.43-16.7) was a risk factor for progression-free survival (PFS) of SRM. CONCLUSIONS: SRM with advanced age, clinical symptoms, high pathological nuclear grade, and lymphatic invasion are more likely to have distant metastasis. And SRM with older age, poor preoperative basic renal function, pathological vascular invasion, and metastasis have worse OS.

Purpose: This study aims to develop and validate a nomogram based on a novel platelet index score (PIS) to predict prognosis in patients with renal cell carcinoma (RCC). Patients and methods: We retrospectively analyzed the data of 759 consecutive patients with RCC. The Kaplan-Meier curves were performed to analyze the platelet parameters and PIS was established. The patients were randomly divided into training (N=456, 60%) and validation cohorts (N=303, 40%). The nomogram was created based on the factors determined by multivariable Cox proportional hazard regression of the training cohort. We assessed the discrimination and calibration of our nomogram in both training and validation cohorts. And then the nomogram was compared with other reported models. Results: High platelet count (PLT>285×109/L) and low platelet distribution width (PDW≤10.95fL) were associated with shorter progression-free survival (PFS). Thus, PLT and PDW were incorporated in a novel score system called PIS. On multivariable analysis of training cohort, PIS, American Joint Committee on Cancer (AJCC) stage, and sarcomatoid differentiation were independent prognostic factors, which were all selected into the nomogram. The nomogram exhibited good discrimination in both training (C-index: 0.835) and validation cohorts (C-index: 0.883). The calibration curves also showed good agreement between prediction and observation in both cohorts. The C-index of the nomogram (C-index: 0.810~0.902) for predicting 2-year, 3-year, and 4-year PFS were significantly higher than Leibovich (C-index: 0.772~0.813), SSIGN (C-index: 0.775~0.876), Cindolo (C-index: 0.642~0.798), Yaycioglu (C-index: 0.648~0.804), MSKCC (C-index: 0.761~0.862), Karakiewicz (C-index: 0.747~0.851), and AJCC stage models (C-index: 0.759~0.864). Conclusion: The nomogram based on a novel PIS could offer better risk stratification in patients with RCC.

Biochemical recurrence (BCR) occurs in up to 27% of patients after radical prostatectomy (RP) and often compromises oncologic survival. To determine whether imaging signatures on clinical prostate magnetic resonance imaging (MRI) could noninvasively characterize biochemical recurrence and optimize treatment. We retrospectively enrolled 485 patients underwent RP from 2010 to 2017 in three institutions. Quantitative and interpretable features were extracted from T2 delineated tumors. Deep learning-based survival analysis was then applied to develop the deep-radiomic signature (DRS-BCR). The model’s performance was further evaluated, in comparison with conventional clinical models. The model achieved C-index of 0.802 in both primary and validating cohorts, outweighed the CAPRA-S score (0.677), NCCN model (0.586) and Gleason grade group systems (0.583). With application analysis, DRS-BCR model can significantly reduce false-positive predictions, so that nearly one-third of patients could benefit from the model by avoiding overtreatments. The deep learning-based survival analysis assisted quantitative image features from MRI performed well in prediction for BCR and has significant potential in optimizing systemic neoadjuvant or adjuvant therapies for prostate cancer patients.

Although chemotherapy is an important treatment for advanced prostate cancer, its efficacy is relatively limited. Ultrasound-induced cavitation plays an important role in drug delivery and gene transfection. However, whether cavitation can improve the efficacy of chemotherapy for prostate cancer remains unclear. In this study, we treated RM-1 mouse prostate carcinoma cells with a combination of ultrasound-mediated microbubble cavitation and paclitaxel. Our results showed that combination therapy led to a more pronounced inhibition of cell viability and increased cell apoptosis. The enhanced efficacy of chemotherapy was attributed to the increased cell permeability induced by cavitation. Importantly, compared with chemotherapy alone (nab-paclitaxel), chemotherapy combined with ultrasound-mediated microbubble cavitation significantly inhibited tumor growth and prolonged the survival of tumor-bearing mice in an orthotopic mouse model of RM-1 prostate carcinoma, indicating the synergistic effects of combined therapy on tumor reduction. Furthermore, we analyzed tumor-infiltrating lymphocytes and found that during chemotherapy, the proportions of CTLA4+ cells and PD-1+/CTLA4+ cells in CD8+ T cells slightly increased after cavitation treatment.

The grade groups (GGs) of Gleason scores (Gs) is the most critical indicator in the clinical diagnosis and treatment system of prostate cancer. End-to-end method for stratifying the patient-level pathological appearance of prostate cancer (PCa) in magnetic resonance (MRI) are of high demand for clinical decision. Existing methods typically employ a statistical method for integrating slice-level results to a patient-level result, which ignores the asymmetric use of ground truth (GT) and overall optimization. Therefore, more domain knowledge (e.g., diagnostic logic of radiologists) needs to be incorporated into the design of the framework. The patient-level GT is necessary to be logically assigned to each slice of a MRI to achieve joint optimization between slice-level analysis and patient-level decision-making. In this paper, we propose a framework (PCa-GGNet-v2) that learns from radiologists to capture signs in a separate two-dimensional (2-D) space of MRI and further associate them for the overall decision, where all steps are optimized jointly in an end-to-end trainable way. In the training phase, patient-level prediction is transferred from weak supervision to supervision with GT. An association route records the attentional slice for reweighting loss of MRI slices and interpretability. We evaluate our method in an in-house multi-center dataset (N = 570) and PROSTATEx (N = 204), which yields five-classification accuracy over 80% and AUC of 0.804 at patient-level respectively. Our method reveals the state-of-the-art performance for patient-level multi-classification task to personalized medicine.

后肾腺瘤是一种罕见的肾脏良性肿瘤,由于缺乏特异性的临床表现及影像学特征,常被误诊为肾恶性肿瘤,目前的相关文献报道较少,且多为个案报道[1].北京大学第三医院泌尿外科于2010年7月至2018年9月收治了3例后肾腺瘤病例,手术治疗效果好,现总结如下,以提高临床医生对后肾腺瘤的认识.

Introductions: The objective of this study was to determine the prognostic value of positive lymph nodes (LNs) in patients with renal cell carcinoma (RCC) and tumor thrombus (TT) and to explore risk factors predicting LNs metastasis. Methods: We retrospectively analyzed 216 patients with RCC and TT treated at a single institution from January 2015 to December 2019. Overall survival (OS) and progression-free survival (PFS) was estimated using the Kaplan-Meier curves divided by pathological LN status. Associations between clinicopathological features and survival outcomes were evaluated using Cox regression models. Logistic regression model was performed to determine risk factors associated with LN metastasis. Results: We identified 216 patients with RCC and TT including 85 (39.4%) who did and 131 (60.6%) who did not undergo lymph node dissection. Pathologically positive LNs were found in 18 (8.3%) cases. pN1 had significant worse OS (median: 21 vs. 41 and 56 months, p < 0.001) and PFS (median:14 vs. 29 and 33 months, p < 0.001) than pN0 and pNx respectively. However, survival outcomes of OS and PFS were similar between pNx-0/M1 and pN1/M0 group and between 1- and ≥2-node-positive group. Non-CCRCC (p = 0.001), sarcomatoid differentiation (p < 0.001), and pathologically positive LNs (p = 0.025) were independent prognostic predictors predicting worse OS while distance metastasis (p = 0.009), non-CCRCC (p = 0.023), necrosis (p = 0.014), sarcomatoid differentiation (p = 0.003), and pathologically positive LNs (p = 0.007) were independent prognostic indicators predicting worse PFS. Clinically positive LNs (p = 0.014) and sarcomatoid differentiation (p = 0.009) were predictors of positive LNs. Conclusions: LNs metastasis independently associated with worse survival outcomes in RCC and TT populations, with similar survival outcomes compared to distance metastasis. Therefore, more accurate risk stratification is warranted for guiding postoperative surveillance and adjuvant therapy.

Renal primitive neuroectodermal tumors with inferior vena cava (IVC) tumor thrombus is an extremely rare entity that poses a massive challenge to diagnosis and treatments. Histopathology remains the gold standard for definite diagnosis. Radical nephrectomy with NC tumor thrombectomy is a challenging procedure requiring vascular management techniques and experience. Adjuvant chemotherapy contributes to improved progression-free, but not overall, survival. Objective: To investigate the clinicopathological characteristics, treatments, and prognosis of patients with renal primitive neuroectodermal ectodermal tumors (rPNETs) with inferior vena cava (IVC) tumor thrombus. Patients and Methods: We retrospectively reviewed 6 patients with rPNETs and IVC tumor thrombus between January 2005 and December 2019, and identified 39 published cases through a literature review. The clinicopathological characteristics, treatments, and survival data were analyzed. Results: The median patient age patients was 26 years, and the male to female ratio was approximately 1:1. The average tumor diameter was 12.5 cm. Seventeen patients (37.8%) showed metastasis at diagnosis. Forty-three cases (95.6%) were managed with surgical resection, and 35 (77.8%) received adjuvant chemotherapy after surgery. Follow-up data were available for 41 patients (median follow-up, 10 months; range, 4.5-13.0). The median overall survival (OS) and median progression-free survival (PFS) were both 30.0 months. Patients who received adjuvant chemotherapy had better PFS than those who underwent surgery only (30.0 months [95% confidence interval [CI], 4.3-55.7] vs 5.0 months [95% CI, 1.0-9.0]; P = .036). In terms of OS, however, the difference between the 2 groups was not significant (30.0 months [95% CI, 8.4-52.6] vs 7.0 months [95% CI, 4.5-9.5]; P = .244). Conclusions: rPNET with IVCTT is an extremely rare entity that mostly occurs in young adults. Although multidisciplinary treatment is used, the prognosis of this disease remains unclear. RN with IVC tumor thrombectomy is a challenging procedure requiring vascular management techniques and experience. Adjuvant chemotherapy contributes to improved PFS, but not OS. Thus, early diagnosis and treatment play a key role in improving prognosis. (C) 2021 Elsevier Inc. All rights reserved.

BACKGROUND:Collecting duct renal cell carcinoma (CDRCC) is a rare type of renal cancer characterized by a poor prognosis. The aim of this work was to develop a nomogram predicting the overall survival (OS) and cancer-specific survival (CSS) for patients with CDRCC. METHODS:A total of 324 eligible patients diagnosed with CDRCC from 2004 to 2015 were identified using the data from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier curve was used to estimate the 1-, 3-, and 5-year OS and CSS of these patients. Univariate and multivariate Cox regression models were performed to identify the independent risk factors associated with OS and CSS. The nomogram was developed based on these factors and evaluated by the concordance index (C-index) and calibration curves using the bootstrap resample method. The predictive accuracy of the nomogram was also compared with the manual of the American Joint Committee on Cancer (AJCC). RESULTS:The estimated 1-, -3, and 5-year OS and CSS rates in the analytic cohorts were 56.4% and 60%, 32.5% and 37.3%, and 28.7% and 33.6%, respectively. The multivariate model revealed that age, tumor size, tumor grade, N stage, M stage, surgical type, and chemotherapy were independent predicted factors for OS, while tumor size, tumor grade, N stage, M stage, surgical type, and chemotherapy were independently linked to CSS. A nomogram was developed using these factors with relatively good discrimination and calibration. The C-index for OS and CSS was 0.764 (95% CI: 0.735~0.793) and 0.783 (95% CI: 0.754~0.812), which was superior to the AJCC stage (C-index: 0.685 (95% CI: 0.654~0.716) and 0.703 (95% CI: 0.672~0.734)). Patients were divided into low-risk, intermediate-risk, and high-risk groups according to the total points calculated by the nomogram. Patients in the low-risk group (97 mo and not reached) experienced significantly long median OS and CSS compared to the intermediate-risk (17 mo and 18 mo) and high-risk groups (5 mo for both). The calibration curves showed a good agreement between the predicted and actual probability related to OS and CSS. CONCLUSION:CDRCC has an aggressively biologic behavior with relatively poor prognosis. A survival prediction nomogram making an individualized evaluation of OS and CSS in patients with CDRCC was presented, potentially helping urologists to make a better risk stratification.

目的 探讨双侧散发性肾癌(bilateral sporadic renal cell carcinoma,BSRCC)的手术治疗策略.方法 回顾分析我院2000年6月～2020年6月37例BSRCC的临床资料.全麻下建立腹膜后操作空间,行后腹腔镜保留肾单位手术(nephron-sparing surgery,NSS)或根治性肾切除术(radical nephrectomy,RN).对肿瘤体积大、与周围组织粘连严重、复杂囊性肿瘤,行后腹腔镜探查、中转开放手术或直接行开放手术切除.结果 37例均成功行双侧手术治疗,其中22例行双侧NSS,15例行一侧NSS、对侧RN.1例行同期NSS+RN后出现ClaveinⅣa级肾功能不全,行血液透析治疗,其余36例术后恢复良好,未发生并发症.14枚囊性肿瘤中,除2枚行腹腔镜探查、中转开放NSS外,其余12枚成功行完全后腹腔镜下NSS.82枚肿瘤中,肾透明细胞癌66枚,肾嗜酸/嫌色细胞混合性肿瘤7枚,低度恶性潜能多房囊性肾肿瘤3枚,乳头状肾细胞癌(renal cell carcinoma,RCC)Ⅰ型2枚,RCC未分类型2枚,肾嫌色细胞癌1枚,管状囊性RCC 1枚.术后病理核分级:G17例,G218例,G310例,G42例.35例随访4～194个月,中位时间30个月.30例存活,5例死亡,10例术后发生远处转移.2年总生存率91.3％,2年无进展生存率82.6％.结论 BSRCC积极行双侧手术治疗效果良好,双侧腹腔镜NSS是较为理想的选择.对囊性RCC行腹腔镜NSS难度较大,常需手术经验丰富的医师进行操作.BSRCC具有多灶性、易复发的特点,术后应严密随访.

Background: Various prediction tools have been developed to predict biochemical recurrence (BCR) after radical prostatectomy (RP); however, few of the previous prediction tools used serum prostate-specific antigen (PSA) nadir after RP and maximum tumor diameter (MTD) at the same time. In this study, a nomogram incorporating MTD and PSA nadir was developed to predict BCR-free survival (BCRFS). Methods: A total of 337 patients who underwent RP between January 2010 and March 2017 were retrospectively enrolled in this study. The maximum diameter of the index lesion was measured on magnetic resonance imaging (MRI). Cox regression analysis was performed to evaluate independent predictors of BCR. A nomogram was subsequently developed for the prediction of BCRFS at 3 and 5 years after RP. Time-dependent receiver operating characteristic (ROC) curve and decision curve analyses were performed to identify the advantage of the new nomogram in comparison with the cancer of the prostate risk assessment post-surgical (CAPRA-S) score. Results: A novel nomogram was developed to predict BCR by including PSA nadir, MTD, Gleason score, surgical margin (SM), and seminal vesicle invasion (SVI), considering these variables were significantly associated with BCR in both univariate and multivariate analyses (P < 0.05). In addition, a basic model including Gleason score, SM, and SVI was developed and used as a control to assess the incremental predictive power of the new model. The concordance index of our model was slightly higher than CAPRA-S model (0.76 vs. 0.70, P = 0.02) and it was significantly higher than that of the basic model (0.76 vs. 0.66, P = 0.001). Time-dependent ROC curve and decision curve analyses also demonstrated the advantages of the new nomogram. Conclusions: PSA nadir after RP and MTD based on MRI before surgery are independent predictors of BCR. By incorporating PSA nadir and MTD into the conventional predictive model, our newly developed nomogram significantly improved the accuracy in predicting BCRFS after RP.