Interpretable multiphasic CT-based radiomic analysis for preoperatively differentiating benign and malignant solid renal tumors: a multicenter study.

BACKGROUND: To develop and compare machine learning models based on triphasic contrast-enhanced CT (CECT) for distinguishing between benign and malignant renal tumors. MATERIALS AND METHODS: In total, 427 patients were enrolled from two medical centers: Center 1 (serving as the training set) and Center 2 (serving as the external validation set). First, 1781 radiomic features were individually extracted from corticomedullary phase (CP), nephrographic phase (NP), and excretory phase (EP) CECT images, after which 10 features were selected by the minimum redundancy maximum relevance method. Second, random forest (RF) models were constructed from single-phase features (CP, NP, and EP) as well as from the combination of features from all three phases (TP). Third, the RF models were assessed in the training and external validation sets. Finally, the internal prediction mechanisms of the models were explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: A total of 266 patients with renal tumors from Center 1 and 161 patients from Center 2 were included. In the training set, the AUCs of the RF models constructed from the CP, NP, EP, and TP features were 0.886, 0.912, 0.930, and 0.944, respectively. In the external validation set, the models achieved AUCs of 0.860, 0.821, 0.921, and 0.908, respectively. The "original_shape_Flatness" feature played the most important role in the prediction outcome for the RF model based on EP features according to the SHAP method. CONCLUSIONS: The four RF models efficiently differentiated benign from malignant solid renal tumors, with the EP feature-based RF model displaying the best performance.

Dysregulation and implications of N6-methyladenosine modification in renal cell carcinoma.

Increasing evidence indicates that N6-methyladenosine (m6A) methylation modification serves important functions in biological metabolism. Dysregulation of m6A regulators is related to the progression of different malignancies, including renal cell carcinoma (RCC). Recent studies have reported preliminary findings on the influence of m6A regulator dysregulation on RCC tumorigenesis and development. However, no comprehensive review that integrates and analyzes the roles of m6A modification in RCC has been published to date. In this review, we focus on the dysregulation of m6A regulators as it relates to RCC tumorigenesis and development, as well as possible applications of m6A modification in RCC diagnosis and therapeutics.

Developing a validated nomogram for predicting ovarian metastasis in endometrial cancer patients: a retrospective research.

OBJECTIVE: To explore risk factors and develop a prediction model for ovarian metastasis in endometrial cancer (EC), as well as providing provide a reference for clinical ovarian preservation. METHODS: We conducted a retrospective observational study enrolling 1496 EC patients having received complete staging surgery from Qilu Hospital of Shandong University from 2012 to 2018. These patients were randomly divided into two cohorts: training cohort (n = 1046) and validation cohort (n = 448). A nomogram prediction model was developed based on univariate, least absolute shrinkage and selection operator (Lasso), and multivariate logistic regression. Then, the nomogram model's performance was evaluated in discrimination, calibration, and clinical utility three aspects. RESULTS: Parametrium invasion, lymph node metastasis, and oviduct metastasis were finally contained in the nomogram prediction model. The AUC of the model in the training cohort was 0.85 compared with 0.72 in the validation cohort. It also behaved well in calibration and had good clinical utility. With a threshold probability of 20% ~ 80%, the nomogram increased the net benefit by 0 ~ 13.6 per 100 patients than surgery for all patients upon validation. CONCLUSIONS: We develop a nomogram with good performances for predicting ovarian metastasis in EC patients, which may help clinicians identify candidate patients appropriate for ovarian preservation in premenopausal EC patients.

Development and validation of prognostic nomograms and a web-based survival rate calculator for sarcomatoid renal cell carcinoma in pre- and post-treatment patients.

BACKGROUND: To develop a clinical prediction model and web-based survival rate calculator to predict the overall survival (OS) and cancer-specific survival (CSS) of sarcomatoid renal cell carcinoma (SRCC) for clinical diagnosis and treatment. METHODS: SRCC patient data were retrieved from Surveillance, Epidemiology, and End Results (SEER) database. Factors independently associated with survival were identified by a Cox regression analysis. Nomograms of the prediction model were constructed using a SEER training cohort and validated with a SEER validation cohort. At the same time, the decision analysis curve, receiver operating characteristic curve, and calibration curve were also used to examine and evaluate the model. A web-based survival rate calculator was constructed to help assist in the assessment of the disease condition and clinical prognosis. RESULTS: The records of 2,742 SRCC cases were retrieved from SEER, while 1,921 cases with a median OS of 14 and CSS of 32 months were used as the training cohort. The developed nomograms were more accurate than that of the American Joint Committee on Cancer staging (C-indexes of 0.767 versus 0.725 for OS and 0.775 versus 0.715 for CSS), with better discrimination than that of the American Joint Committee on Cancer (AJCC) stage model and the calibration was validated in the SEER validation cohort. The model's 3- and 5-year OS and CSS were superior to AJCC and T staging on the analysis decision curve. The prognosis prediction of SRCC established by the prediction model could be evaluated through the web-based survival rate calculator, which plays a guiding role in clinical treatment. CONCLUSIONS: Nomograms and a web-based survival rate calculator predicting the OS and CSS of SRCC patients with better discrimination and calibration were developed.

Metastatic renal cell carcinoma patients of T4 stage who are in status of N1 stage or older than 76 years cannot benefit from cytoreductive nephrectomy.

BACKGROUND: We aimed to identify which part of the patients with metastatic renal cell carcinoma (mRCC) is not suitable for cytoreductive nephrectomy (CN). METHODS: The data of mRCC patients was acquired from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate cox regression analysis and nomogram were performed for selecting factors independently associated with survival. Propensity score matching (PSM) was applied to reduce potential bias when comparing survival of mRCC patients treated by CN or non-surgery (NS). The survival analysis of subgroups was estimated by the Kaplan-Meier method and compared by log-rank testing. The summary of subgroup analysis was showed by forest plots. RESULTS: The records of 21,411 patients with mRCC were obtained from the SEER database. After screening, a total of 6532 patients were included for further analysis, of which 6043 underwent CN and 489 underwent NS. Age, T stage, N stage and tumor size were involved in subgroup analysis by PSM according to the result of multivariate cox regression analysis and clinical experience. Survival benefit was not found in T4 stage patients. Further analysis showed that T4&N1 and T4&age ≥ 76 yr subgroups could not obtain survival benefit from CN. CONCLUSION: CN should not be performed in T4 stage mRCC patients who were in status of N1 stage or older than 76 years, because surgery cannot take significant survival benefit for them.

A Population Study to Identify Candidates for Cytoreductive Nephrectomy in Patients with Metastatic Sarcomatoid Renal Cell Carcinoma from the Surveillance, Epidemiology, and End Results (SEER) Database.

BACKGROUND This population study aimed to identify suitable candidates for cytoreductive nephrectomy in patients with metastatic sarcomatoid renal cell carcinoma (RCC) from the US Surveillance, Epidemiology, and End Results (SEER) database. MATERIAL AND METHODS Demographic and clinical data from 1,229 patients with metastatic sarcomatoid RCC were retrieved from the SEER database. Patients were divided into the cytoreductive nephrectomy group (n=937) and the no surgery group (n=292). Multivariate Cox regression analysis identified factors associated with overall survival (OS) and propensity score matching identified factors that significantly impacted the OS. Survival of propensity score-matched subgroups of patients with metastatic sarcomatoid RCC treated by cytoreductive nephrectomy or no surgery was determined by the Kaplan-Meier method and compared by the log-rank test. RESULTS Of the 1,229 patients with metastatic sarcomatoid RCC retrieved from the SEER database, age, tumor size, T stage, and N stage were independent risk factors for patient survival. There were no significant differences in age, N stage, and tumor size between the cytoreductive nephrectomy-treated and non-surgically treated T stage cases following propensity score matching. OS benefits were found in cases with stage T1 (12 months increase), T2 (7.5 months increase), T3a (2 months increase), and T4 (3 months increase), but not in the T3b or T3c subgroups treated by cytoreductive nephrectomy, compared with patients with no surgical treatment. CONCLUSIONS Data from the SEER database showed that cytoreductive nephrectomy improved OS in patients with T1 and T2 metastatic sarcomatoid RCC with a significant long-term survival benefit of >6 months.

Propensity-score matched comparison of partial versus radical nephrectomy for T1N0M0 sarcomatoid renal cell carcinoma.

BACKGROUND: Sarcomatoid renal cell carcinoma is a rare variant of renal cell carcinoma associated with poor clinical outcomes. Currently no reliable evidence indicates whether partial nephrectomy can be an effective treatment for patients with T1N0M0 sarcomatoid renal cell carcinoma. The present study was conducted to compare the overall and cancer-specific survival with partial and radical nephrectomy for such cases. METHODS: Data of sarcomatoid renal cell carcinoma were retrieved from Surveillance, Epidemiology, and End Results database. Factors independently associated with the overall or cancer-specific survival were identified by Cox regression analysis. The overall and cancer-specific survival of propensity-score matched T1N0M0 sarcomatoid renal cell carcinoma patients treated by partial and radical nephrectomy were estimated by the Kaplan-Meier method. RESULTS: The records of 452 T1N0M0 sarcomatoid renal cell carcinoma cases were retrieved. One hundred and fifty-five of these patients underwent partial nephrectomy, while the remaining 297 underwent radical nephrectomy. The median follow-up period in partial-treated group was 38 months (ranging from 2 to 132 months), while that in RN-treated was 39 months (ranging from 0 to 150 months). Age, sex, marital status and tumor size were independent risk factors for the overall and cancer-specific survival. There were no significant differences among age, sex, marital status and tumor size in the PN- and RN-treated T1N0M0 cases according to propensity-score matching. The estimated median overall survival of partial-treated group was 132 months, while that for RN-treated cases was 100 months (P=0.11). The median cancer-specific survival was not reached in both groups (P=0.092). CONCLUSIONS: The overall and cancer-specific survival of T1N0M0 patients treated by partial nephrectomy was not inferior to that of patients treated by radical nephrectomy.