Predicting Lymph Node Invasion Research Articles

Multitask prediction models for serous ovarian cancer by preoperative CT image assessments based on radiomics.

High-grade serous ovarian cancer (HGSOC) has the highest mortality rate among female reproductive system tumors. Accurate preoperative assessment is crucial for treatment planning. This study aims to develop multitask prediction models for HGSOC using radiomics analysis based on preoperative CT images. This study enrolled 112 patients diagnosed with HGSOC. Laboratory findings, including serum levels of CA125, HE-4, and NLR, were collected. Radiomic features were extracted from manually delineated ROI on CT images by two radiologists. Classification models were developed using selected optimal feature sets to predict R0 resection, lymph node invasion, and distant metastasis status. Model evaluation was conducted by quantifying receiver operating curves (ROC), calculating the area under the curve (AUC), De Long's test. The radiomics models applied to CT images demonstrated superior performance in the testing set compared to the clinical models. The area under the curve (AUC) values for the combined model in predicting R0 resection were 0.913 and 0.881 in the training and testing datasets, respectively. De Long's test indicated significant differences between the combined and clinical models in the testing set (p = 0.003). For predicting lymph node invasion, the AUCs of the combined model were 0.868 and 0.800 in the training and testing datasets, respectively. The results also revealed significant differences between the combined and clinical models in the testing set (p = 0.002). The combined model for predicting distant metastasis achieved AUCs of 0.872 and 0.796 in the training and test datasets, respectively. The combined model displayed excellent agreement between observed and predicted results in predicting R0 resection, while the radiomics model demonstrated better calibration than both the clinical model and combined model in predicting lymph node invasion and distant metastasis. The decision curve analysis (DCA) for predicting R0 resection favored the combined model over both the clinical and radiomics models, whereas for predicting lymph node invasion and distant metastasis, DCA favored the radiomics model over both the clinical model and combined model. The identified radiomics signature holds potential value in preoperatively evaluating the R0, lymph node invasion and distant metastasis in patients with HGSC. The radiomics nomogram demonstrated the incremental value of clinical predictors for surgical outcome and metastasis estimation.

Is Systemic Immune-Inflammation Index a Real Non-Invasive Biomarker to Predict Oncological Outcomes in Patients Eligible for Radical Cystectomy?

Background and Objectives: To assess the potential prognostic role of the systemic immune-inflammation index (SII) in predicting oncological outcomes in a cohort of patients treated with radical cystectomy (RC). Materials and Methods: From 2016 to 2022, a retrospective monocentric study enrolled 193 patients who were divided into two groups based on their SII levels using the optimal cutoff determined by the Youden index. The SII was obtained from a preoperative blood test approximately one month before RC. Univariable and multivariable logistic regression analyses were conducted to investigate the capacity of SII to predict lymph node invasion (N), advanced pT stage (pT3/pT4), and locally advanced condition at the time of RC. Multivariable Cox regression models adjusted for preoperative and postoperative features were used to analyze the prognostic effect of SII on recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Results: The optimal cutoff value of the SII was 640.27. An elevated SII was seen in 113 (58.5%) patients. Using the multivariable preoperative logistic regression models, an elevated SII was correlated with nodal invasion (N; p = 0.03), advanced pT stage (p = 0.04), and locally advanced disease (p = 0.005), with enhancement of AUCs for predicting locally advanced disease (p = 0.04). In multivariable Cox regression models that considered preoperative clinicopathologic factors, an elevated SII was linked to poorer RFS (p = 0.005) and OS (p = 0.01). Moreover, on multivariable Cox regression postoperative models, a high SII was linked to RFS (p = 0.004) and to OS (p = 0.01). Conclusions: In this monocentric retrospective study, higher preoperative SII values predicted worse oncological outcomes in patients with bladder cancer (BCa) who underwent RC.

Benefit and harm of lymphadenectomy in intermediate risk prostate cancer: comparison of five nomograms

BackgroundPelvic lymph node dissection (PLND) is recommended method for detecting prostate cancer (PCa) nodal metastases although associated with serious complications. In this study, we aimed to assess benefit/harm of routine PLND in intermediate risk PCa patients and to compare diagnostic yield of five different nomograms in predicting lymph node invasion (LNI).MethodsRetrospective analysis of consecutive PCa patients with intermediate risk of biochemical recurrence who underwent open radical prostatectomy (RP) with bilateral PLND between January 2017 and December 2019 at our institution. Partin, 2012-Briganti, 2018-Briganti, Cagiannos and Memorial Sloan Kettering Cancer Center (MSKCC) values were calculated. To compare accuracy, sensitivity, specificity, and area under receiver-operating curve (AUC) were calculated and then optimal cutoff values were estimated, analyses repeated and compared. To assess benefit and harm of PLND, relative risk (RR) and number need to treat (NNT) with LNI and complications set as outcome were calculated.ResultsTotal 309 subjects. Average age 62.2 years, average PSA 7.2 ng/mL; 18 (5.8%) had LNI; 88 (28.5%) suffered Clavien-Dindo grade 3–5 complication. AUC for predicting LNI: 0.729 for 2012-Briganti, 0.660 for MSKCC, 0.521 for 2018-Briganti, 0.486 for Cagiannos, and 0.424 for Partin. None of pairwise AUC comparisons based on default and newly established cutoff values were statistically significant. Lowest NNT was for Partin and Cagiannos with default cutoff (≥ 5%). Risks of serious complications between higher/lower than cutoff values were non-significant across nomograms.Conclusions2012-Briganti nomogram outperforms, although not significantly, MSKCC, 2018-Briganti, Cagiannos, and Partin nomograms in classifying LNI in intermediate risk PCa patients. Routine PLND in these patients should be avoided, due to high rate and severity of complications.

Transperineal template saturation and conventional biopsy for stage prediction in prostate cancer.

To evaluate the performance of risk calculators (RCs) predicting lymph node invasion (LNI) and extraprostatic extension (EPE) in men undergoing transperineal magnetic resonance imaging/transrectal ultrasound (TRUS)-fusion template saturation biopsy (TTSB) and conventional systematic TRUS-guided biopsy (SB). The RCs were tested in a consecutive cohort of 645 men undergoing radical prostatectomy with extended pelvic LN dissection between 2005 and 2019. TTSB was performed in 230 (35.7%) and SB in 415 (64.3%) men. Risk of LNI and EPE was calculated using the available RCs. Discrimination, calibration, and clinical usefulness stratified by different biopsy techniques were assessed. Lymph node invasion was observed in 23 (10%) and EPE in 73 (31.8%) of cases with TTSB and 53 (12.8%) and 158 (38%) with SB, respectively. RCs showed an excellent discrimination and acceptable calibration for prediction of LNI based on TTSB (area under the curve [AUC]/risk estimation: Memorial Sloan Kettering Cancer Center [MSKCC]-RC 0.79/-4%, Briganti (2012)-RC 0.82/-4%, Gandaglia-RC 0.81/+6%). These were comparable in SB (MSKCC-RC 0.78/+2%; Briganti (2012)-RC 0.77/-3%). Decision curve analysis (DCA) revealed a net benefit at threshold probabilities between 3% and 6% when TTSB was used. For prediction of EPE based on TTSB an inferior discrimination and variable calibration were observed (AUC/risk estimation: MSKCC-RC 0.71/+8% and Martini (2018)-RC 0.69/+2%) achieving a net benefit on DCA only at risk thresholds of >17%. Performance of RCs for prediction of LNI and EPE based on SB showed comparable results with a better performance in the DCA for LNI (risk thresholds 1-2%) and poorer performance for EPE (risk threshold >20%). This study is limited by its retrospective single-institution design. The potentially more accurate grading ability of TTSB did not result in improved performance of preoperative RCs. Prediction tools for LNI proved clinical usefulness while RCs for EPE did not.

Use of artificial intelligence in the management of T1 colorectal cancer: a new tool in the arsenal or is deep learning out of its depth?

The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.

PE022 - Comparison of four validated nomograms (Memorial Sloan Kettering Cancer Center, Briganti 2012, 2017, and 2019) predicting lymph node invasion in patients with high-risk prostate cancer candidates for radical prostatectomy and extended pelvic lymph node di

PE022 - Comparison of four validated nomograms (Memorial Sloan Kettering Cancer Center, Briganti 2012, 2017, and 2019) predicting lymph node invasion in patients with high-risk prostate cancer candidates for radical prostatectomy and extended pelvic lymph node di

Impact of the time elapsed between prostate biopsy and surgery on the accuracy of nomograms predicting lymph node invasion in patients with clinically localized prostate cancer.

We aimed to investigate whether the performance characteristics of available nomograms predicting lymph node invasion (LNI) in prostate cancer patients undergoing radical prostatectomy (RP) change according to the time elapsed between diagnosis and surgery. We identified 816 patients who underwent RP with extended pelvic lymph node dissection (ePLND) after combined prostate biopsy at 6 referral centers. We plotted the accuracy (ROC-derived area under the curve [AUC]) of each Briganti nomogram according to the time elapsed between biopsy ad RP. We then tested whether discrimination of the nomograms improved after accounting for the time elapsed between biopsy ad RP. The median time between biopsy and RP was 3 months. The LNI rate was 13%. The discrimination of each nomogram decreased with increasing time elapsed between biopsy and surgery, where the AUC of the 2019 Briganti nomogram was 88% vs. 70% for men undergoing surgery <2 vs. >6 months from the biopsy. The addition of the time elapsed between biopsy ad RP improved the accuracy of all available nomograms (P < 0.003), with the Briganti 2019 nomogram showing the highest discrimination. Clinicians should be aware that the discrimination of available nomograms decreases according to the time elapsed between diagnosis and surgery. The indication of ePLND should be carefully evaluated in men below the LNI cut-off who had a diagnosis more than 6 months before RP. This has important implications when considering the longer waiting lists related to the impact of COVID-19 on healthcare systems.

Development and external validation of a multivariable [68Ga]Ga-PSMA-11 PET-based prediction model for lymph node involvement in men with intermediate or high-risk prostate cancer

PurposeTo develop and evaluate a lymph node invasion (LNI) prediction model for men staged with [68Ga]Ga-PSMA-11 PET.MethodsA consecutive sample of intermediate to high-risk prostate cancer (PCa) patients undergoing [68Ga]Ga-PSMA-11 PET, extended pelvic lymph node dissection (ePLND), and radical prostatectomy (RP) at two tertiary referral centers were retrospectively identified. The training cohort comprised 173 patients (treated between 2013 and 2017), the validation cohort 90 patients (treated between 2016 and 2019). Three models for LNI prediction were developed and evaluated using cross-validation. Optimal risk-threshold was determined during model development. The best performing model was evaluated and compared to available conventional and multiparametric magnetic resonance imaging (mpMRI)-based prediction models using area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis (DCA).ResultsA combined model including prostate-specific antigen, biopsy Gleason grade group, [68Ga]Ga Ga-PSMA-11 positive volume of the primary tumor, and the assessment of the [68Ga]Ga-PSMA-11 report N-status yielded an AUC of 0.923 (95% CI 0.863–0.984) in the external validation. Using a cutoff of  ≥ 17%, 44 (50%) ePLNDs would be spared and LNI missed in one patient (4.8%). Compared to conventional and MRI-based models, the proposed model showed similar calibration, higher AUC (0.923 (95% CI 0.863–0.984) vs. 0.700 (95% CI 0.548–0.852)—0.824 (95% CI 0.710–0.938)) and higher net benefit at DCA.ConclusionsOur results indicate that information from [68Ga]Ga-PSMA-11 may improve LNI prediction in intermediate to high-risk PCa patients undergoing primary staging especially when combined with clinical parameters. For better LNI prediction, future research should investigate the combination of information from both PSMA PET and mpMRI for LNI prediction in PCa patients before RP.

Identification of the Optimal Candidates for Nodal Staging with Extended Pelvic Lymph Node Dissection Among Prostate Cancer Patients Who Underwent Preoperative Prostate-specific Membrane Antigen Positron Emission Tomography. External Validation of the Memorial Sloan Kettering Cancer Center and Briganti Nomograms and Development of a Novel Tool

BackgroundAlthough the therapeutic role of extended pelvic lymph node dissection (ePLND) in patients with prostate cancer (PCa) is still under debate, this procedure is recommended for staging purposes in selected cases. Nomograms for predicting lymph node invasion (LNI) do not account for prostate-specific membrane antigen (PSMA) positron emission tomography (PET) imaging, which is characterized by a high negative predictive value for nodal metastases. ObjectiveTo externally validate models predicting LNI in patients with miN0M0 PCa at PSMA PET and to develop a novel tool in this setting. Design, setting, and participantsOverall, 458 patients with miN0M0 disease undergoing radical prostatectomy (RP) and ePLND at 12 centers between 2017 and 2022 were identified. Outcome measurements and statistical analysesAvailable tools were externally validated using calibration plots, the area under the receiver operating characteristic curve (AUC), and decision curve analyses to assess calibration, discrimination, and the net benefit. A novel coefficient-based model was developed, internally validated, and compared with available tools. Results and limitationsOverall, 53 patients (12%) had LNI. The AUC was 69% for the Briganti 2012, 64% for the Briganti 2017, 73% for the Briganti 2019, and 66% for the Memorial Sloan Kettering Cancer Center nomogram. Multiparametric magnetic resonance imaging stage, biopsy grade group 5, the diameter of the index lesion, and the percentage of positive cores at systematic biopsy were independent predictors of LNI (all p ≤ 0.04). Internal cross-validation confirmed a coefficient-based model with AUC of 78%, better calibration, and a higher net benefit in comparison to the other nomograms assessed. Use of a 5% cutoff would have spared 47% ePLND procedures (vs 13% for the Briganti 2019 nomogram) at the cost of missing only 2.1% LNI cases . The lack of central review of imaging and pathology represents the main limitation. ConclusionsTools for predicting LNI are associated with suboptimal performance for men with miN0M0 PCa. We propose a novel model for predicting LNI that outperforms available tools in this population. Patient summaryTools currently used to predict lymph node invasion (LNI) in prostate cancer are not optimal for men with negative node findings on PET (positron emission tomography) scans, leading to a high number of unnecessary extended pelvic lymph node dissection (ePLND) procedures. A novel tool should be used in clinical practice to identify candidates for ePLND to reduce the risk of unnecessary procedures without missing LNI cases.

Development and internal validation of a novel nomogram for predicting lymph node invasion for prostate cancer patients undergoing extended pelvic lymph node dissection.

Few studies have focused on the performance of Briganti 2012, Briganti 2017 and MSKCC nomograms in the Chinese population in assessing the risk of lymph node invasion(LNI) in prostate cancer(PCa) patients and identifying patients suitable for extended pelvic lymph node dissection(ePLND). We aimed to develop and validate a novel nomogram based on Chinese PCa patients treated with radical prostatectomy(RP) and ePLND for predicting LNI. We retrospectively retrieved clinical data of 631 patients with localized PCa receiving RP and ePLND at a Chinese single tertiary referral center. All patients had detailed biopsy information from experienced uropathologist. Multivariate logistic-regression analyses were performed to identify independent factors associated with LNI. The discrimination accuracy and net-benefit of models were quantified using the area under curve(AUC) and Decision curve analysis(DCA).The nonparametric bootstrapping were used to internal validation. A total of 194(30.7%) patients had LNI. The median number of removed lymph nodes was 13(range, 11-18). In univariable analysis, preoperative prostate-specific antigen(PSA), clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa, percentage of positive cores, percentage of positive cores with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy differed significantly. The multivariable model that included preoperative PSA, clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy represented the basis for the novel nomogram. Based on a 12% cutoff, our results showed that 189(30%) patients could have avoided ePLND while only 9(4.8%) had LNI missing ePLND. Our proposed model achieved the highest AUC (proposed model vs Briganti 2012 vs Briganti 2017 vs MSKCC model: 0.83 vs 0.8 vs 0.8 vs 0.8, respectively) and highest net-benefit via DCA in the Chinese cohort compared with previous nomograms. In internal validation of proposed nomogram, all variables had a percent inclusion greater than 50%. We developed and validated a nomogram predicting the risk of LNI based on Chinese PCa patients, which demonstrated superior performance compared with previous nomograms.

Unilateral Pelvic Lymph Node Dissection in Prostate Cancer Patients Diagnosed in the Era of Magnetic Resonance Imaging-targeted Biopsy: A Study That Challenges the Dogma.

Bilateral extended pelvic lymph node dissection at the time of radical prostatectomy is the current standard of care if pelvic lymph node dissection is indicated; often, however, pelvic lymph node dissection is performed in pN0 disease. With the more accurate staging achieved with magnetic resonance imaging-targeted biopsies for prostate cancer diagnosis, the indication for bilateral extended pelvic lymph node dissection may be revised. We aimed to assess the feasibility of unilateral extended pelvic lymph node dissection in the era of modern prostate cancer imaging. We analyzed a multi-institutional data set of men with cN0 disease diagnosed by magnetic resonance imaging-targeted biopsy who underwent prostatectomy and bilateral extended pelvic lymph node dissection. The outcome of the study was lymph node invasion contralateral to the prostatic lobe with worse disease features, ie, dominant lobe. Logistic regression to predict lymph node invasion contralateral to the dominant lobe was generated and internally validated. Overall, data from 2,253 patients were considered. Lymph node invasion was documented in 302 (13%) patients; 83 (4%) patients had lymph node invasion contralateral to the dominant prostatic lobe. A model including prostate-specific antigen, maximum diameter of the index lesion, seminal vesicle invasion on magnetic resonance imaging, International Society of Urological Pathology grade in the nondominant side, and percentage of positive cores in the nondominant side achieved an area under the curve of 84% after internal validation. With a cutoff of contralateral lymph node invasion of 1%, 602 (27%) contralateral pelvic lymph node dissections would be omitted with only 1 (1.2%) lymph node invasion missed. Pelvic lymph node dissection could be omitted contralateral to the prostate lobe with worse disease features in selected patients. We propose a model that can help avoid contralateral pelvic lymph node dissection in almost one-third of cases.

PD10-09 A NOVEL MODEL INTEGRATING CLINICAL, MP-MRI, AND EPIGENOMIC FEATURES TO PREDICT LYMPH NODE INVASION IN PROSTATE CANCER PATIENTS UNDERGOING RADICAL PROSTATECTOMY AND PELVIC LYMPH NODE DISSECTION

You have accessJournal of UrologyCME1 Apr 2023PD10-09 A NOVEL MODEL INTEGRATING CLINICAL, MP-MRI, AND EPIGENOMIC FEATURES TO PREDICT LYMPH NODE INVASION IN PROSTATE CANCER PATIENTS UNDERGOING RADICAL PROSTATECTOMY AND PELVIC LYMPH NODE DISSECTION Marco Bandini, Roberta Lucianò, Francesca Giannese, Giulia Maria Scotti, Caterina Oneto, Francesco Barletta, Giuseppe Ottone Cirulli, Vito Cucchiara, Armando Stabile, Elio Mazzone, Gabriele Sorce, Nazario Tenace, Federico Scarfò, Giorgio Brembilla, Antonio Esposito, Marco Morelli, Dejan Lazarevic, Francesco De Cobelli, Claudio Doglioni, Giovanni Tonon, Giorgio Gandaglia, Francesco Montorsi, and Alberto Briganti Marco BandiniMarco Bandini More articles by this author , Roberta LucianòRoberta Lucianò More articles by this author , Francesca GianneseFrancesca Giannese More articles by this author , Giulia Maria ScottiGiulia Maria Scotti More articles by this author , Caterina OnetoCaterina Oneto More articles by this author , Francesco BarlettaFrancesco Barletta More articles by this author , Giuseppe Ottone CirulliGiuseppe Ottone Cirulli More articles by this author , Vito CucchiaraVito Cucchiara More articles by this author , Armando StabileArmando Stabile More articles by this author , Elio MazzoneElio Mazzone More articles by this author , Gabriele SorceGabriele Sorce More articles by this author , Nazario TenaceNazario Tenace More articles by this author , Federico ScarfòFederico Scarfò More articles by this author , Giorgio BrembillaGiorgio Brembilla More articles by this author , Antonio EspositoAntonio Esposito More articles by this author , Marco MorelliMarco Morelli More articles by this author , Dejan LazarevicDejan Lazarevic More articles by this author , Francesco De CobelliFrancesco De Cobelli More articles by this author , Claudio DoglioniClaudio Doglioni More articles by this author , Giovanni TononGiovanni Tonon More articles by this author , Giorgio GandagliaGiorgio Gandaglia More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , and Alberto BrigantiAlberto Briganti More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003250.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Multivariable models should be used to identify prostate cancer (PCa) patients candidates for extended pelvic lymph node dissection (ePLND) during radical prostatectomy (RP) to spare unnecessary ePLNDs without missing lymph node invasion (LNI). Improving LNI detection in PCa is key in reducing ePLND-related morbidity. We hypothesized that LNI can be better predicted by integrating clinical, radiologic and epigenomic information. METHODS: We recruited 172 PCa patients with a risk of LNI >5% diagnosed by target+systematic biopsy undergoing RP+ePLND between 2014-2021. Epigenetic profiles of tumor DNA biopsy cores were sequenced via reduced representation bisulfite conversion. MethylKit R package assessed the percentage methylation differences among CpG sites of patients with and without LNI. A 50% cut-off methylation difference (50-MD) identified significant (False Discovery Rate <0.001) CpGs. Enrichment analysis tested for gene pathways that were expressed among patients with and without LNI by using differentially methylated (50-MD) CpGs. Analyses were performed for target and systematic biopsy samples independently. Two signatures were created from hypermethylated CpGs from target + systematic samples and integrated with PSA, mpMRI stage, and grade group at target biopsy to develop two models predicting LNI which underwent 500 internal train-test validations and were compared with existing tools. RESULTS: Overall, 37 patients (21.5%) had LNI. We identified 508 and 511 CpGs sites within target and systematic samples that were differentially methylated among patients with and without LNI. Gene pathways involved in the transcription of potassium channels were associated with LNI in target samples. The epigenetic signatures including only hypermethylated CpGs were correlated with LNI on univariable regression (target samples LogOdds 0.12, p<0.001; systematic samples LogOdds 0.08, p<0.001). Clinical and mpMRI variables (PSA, mpMRI stage, and ISUP grade group at target biopsy) were associated with LNI (all p≤0.01). An AUC of 86% and 83% was achieved for the target model and systematic model. Both models outperformed the previous versions of the Briganti nomogram at any LNI threshold risk. CONCLUSIONS: We developed two LNI prediction models that integrated clinical, mpMRI and epigenetic features which outperformed available tools. Epigenetic features from target tumor samples appeared to better predict LNI compared to their systematic counterparts. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e329 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Marco Bandini More articles by this author Roberta Lucianò More articles by this author Francesca Giannese More articles by this author Giulia Maria Scotti More articles by this author Caterina Oneto More articles by this author Francesco Barletta More articles by this author Giuseppe Ottone Cirulli More articles by this author Vito Cucchiara More articles by this author Armando Stabile More articles by this author Elio Mazzone More articles by this author Gabriele Sorce More articles by this author Nazario Tenace More articles by this author Federico Scarfò More articles by this author Giorgio Brembilla More articles by this author Antonio Esposito More articles by this author Marco Morelli More articles by this author Dejan Lazarevic More articles by this author Francesco De Cobelli More articles by this author Claudio Doglioni More articles by this author Giovanni Tonon More articles by this author Giorgio Gandaglia More articles by this author Francesco Montorsi More articles by this author Alberto Briganti More articles by this author Expand All Advertisement PDF downloadLoading ...

Comparison of Four Validated Nomograms (Memorial Sloan Kettering Cancer Center, Briganti 2012, 2017, and 2019) Predicting Lymph Node Invasion in Patients with High-Risk Prostate Cancer Candidates for Radical Prostatectomy and Extended Pelvic Lymph Node Dissection: Clinical Experience and Review of the Literature.

The indication for extended pelvic lymph node dissection (ePLND) at the time of radical prostatectomy (RP) is based on nomograms predicting the risk of lymph node invasion (LNI). However, limited data are available on the comparison of these predictive models in high-risk prostate cancer (PC) patients. Therefore, we compared the accuracy of the most used nomograms (MSKCC, Briganti 2012, 2017, and 2019) in the setting of high-risk PC patients submitted to ePLND. 150 patients with high-risk PC disease treated from 2019 to 2022 were included. Before RP + ePLND, we assessed the MSKCC, Briganti 2012, 2017, and 2019 nomograms for each patient, and we compared the prediction of LNI with the final histopathological analysis of the ePLND using pathologic results as a reference. LNI was found in 39 patients (26%), and 71.3% were cT2. The percentage of patients with estimated LNI risk above the cut-off was significantly higher in pN+ cases than in pN0 for all Briganti nomograms. The percentage of patients at risk of LNI, according to Briganti Nomogram (2012, 2017, and 2019), was significantly higher in pN+ cases than in pN0 (p < 0.04), while MSKCC prediction didn't vary significantly between pN0 and pN+ groups (p = 0.2). All nomograms showed high sensitivity (Se > 0.90), low specificity (Sp < 0.20), and similar AUC (range: 0.526-0.573) in predicting pN+. Particularly, 74% of cases patients with MSKCC estimated risk > 7% showed pN0 compared to 71% with Briganti 2012 > 5%, 69% with Briganti 2017 > 7%, and 70% with Briganti 2019 > 7%. Despite the high-risk disease, in our patients treated with ePLND emerges a still high number of pN0 cases and a similar low specificity of nomograms in predicting LNI.

External Validation of Briganti and Memorial Sloan-Kettering Cancer Centre Nomograms for Predicting Lymph Node Invasion in the Indian Cohort of Patients with Prostate Cancer

External Validation of Briganti and Memorial Sloan-Kettering Cancer Centre Nomograms for Predicting Lymph Node Invasion in the Indian Cohort of Patients with Prostate Cancer

Comparison of the diagnostic accuracy of PSMA PET/CT scan and Briganti nomogram to predict lymph node invasion in candidates to robot-assisted radical prostatectomy: A single institutional analysis

Comparison of the diagnostic accuracy of PSMA PET/CT scan and Briganti nomogram to predict lymph node invasion in candidates to robot-assisted radical prostatectomy: A single institutional analysis

A novel model Integrating clinical, mp-MRI, and epigenomic features to predict lymph node invasion in prostate cancer patients undergoing radical prostatectomy and pelvic lymph node dissection

A novel model Integrating clinical, mp-MRI, and epigenomic features to predict lymph node invasion in prostate cancer patients undergoing radical prostatectomy and pelvic lymph node dissection

Management of Bladder Cancer Patients with Clinical Evidence of Lymph Node Invasion (cN+).

The purpose of this review is to present the current knowledge about the diagnostic and treatment options for bladder cancer (BCa) patients with clinically positive lymph nodes (cN+). This review shows compaction of CT and MRI performance in preoperative prediction of lymph node invasion (LNI) in BCa patients, along with other diagnostic methods. Most scientific societies do not distinguish cN+ patients in their guidelines; recommendations concern muscle-invasive bladder cancer (MIBC) and differ between associations. The curative treatment that provides the best long-term survival in cN+ patients is a multimodal approach, with a combination of neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) with extended pelvic lymph node dissection (ePLND). The role of adjuvant chemotherapy (AC) remains uncertain; however, emerging evidence indicates comparable outcomes to NAC. Therefore, in cN+ patients who have not received NAC, AC should be implemented. The response to ChT is a crucial prognostic factor for cN+ patients. Recent studies demonstrated the growing importance of immunotherapy, especially in ChT-ineligible patients. Moreover, immunotherapy can be suitable as adjuvant therapy in selected cases. In cN+ patients, the extended template of PLND should be utilized, with the total resected node count being less important than the template. This review is intended to draw special attention to cN+ BCa patients, as the oncological outcomes are significantly worse for this group.

MP57-06 EXTERNAL VALIDATION AND COMPARISON OF TWO NOMOGRAMS PREDICTING THE PROBABILITY OF LYMPH NODE INVASION IN PATIENTS SUBJECTED TO ROBOTIC RADICAL PROSTATECTOMY AND CONCOMITANT LYMPH NODE DISSECTION

You have accessJournal of UrologyCME1 May 2022MP57-06 EXTERNAL VALIDATION AND COMPARISON OF TWO NOMOGRAMS PREDICTING THE PROBABILITY OF LYMPH NODE INVASION IN PATIENTS SUBJECTED TO ROBOTIC RADICAL PROSTATECTOMY AND CONCOMITANT LYMPH NODE DISSECTION Nicola Frego, Paciotti Marco, Davide Maffei, Pier Paolo Avolio, Roberto Contieri, Alessandro Uleri, Massimo Lazzeri, Alberto Saita, Paolo Casale, Nicolò Maria Buffi, and Giovanni Lughezzani Nicola FregoNicola Frego More articles by this author , Paciotti MarcoPaciotti Marco More articles by this author , Davide MaffeiDavide Maffei More articles by this author , Pier Paolo AvolioPier Paolo Avolio More articles by this author , Roberto ContieriRoberto Contieri More articles by this author , Alessandro UleriAlessandro Uleri More articles by this author , Massimo LazzeriMassimo Lazzeri More articles by this author , Alberto SaitaAlberto Saita More articles by this author , Paolo CasalePaolo Casale More articles by this author , Nicolò Maria BuffiNicolò Maria Buffi More articles by this author , and Giovanni LughezzaniGiovanni Lughezzani More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002640.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Current guidelines recommend an extended Pelvic Lymph Node Dissection (ePLND) in Prostate Cancer (PCa) patients with a non negligible risk of Lymph Node Invasion (LNI), according to available nomograms. The Briganti 2012 nomogram has been recently updated in Briganti 2019, to include information on Magnetic Resonance Imaging (MRI) and targeted biopsy (TB). The aim of the study is to validate and compare Briganti 2012 and 2019 nomograms in an external cohort of contemporary patients. METHODS: We retrospectively collected data of consecutive patients treated with Robot Assisted Radical Prostatectomy and ePLND at our center, between December 2014 and August 2021. Data included clinical, MRI, and pathological characteristics. The risk of LNI was calculated with the published regression coefficients. The Receiver Operator Characteristics (ROC) curve and Area Under the Curve (AUC) were used to evaluate the accuracy, while deLong method was used to compare models' accuracy. Calibration plot was used to evaluate the extend of over and under estimation of the models. Multivariate Logistic Regression Analysis (MVA) was performed to evaluate potential predictive factors of LNI. RESULTS: Overall, we analyzed data on 842 patients. Of them, 377 (44.8%) underwent MRI and TB. Median age at surgery was 64 years (IQR 59-69) and median tPSA was 7.04 ng/mL (IQR 5.11-10.4). Extra Capsular Extension and Seminal Vesicles Invasion (SVI) at MRI were observed in 15.4% and 5.4% of patients, respectively. The median primary and secondary GS were 3 and 4, respectively. The median percentage of positive cores was 35% (IQR 21.4-50). Finally, median Gleason Group at TB was 2 (IQR 2-3) and the median percentage of clinically significant random cores was 21% (IQR 0-42). A median of 13 (IQR 9-18) nodes per patient were removed, and 85 (10.1%) patients had LNI at final pathology. The AUCs for Briganti 2012 and 2019 were 0.84 and 0.79, respectively. The calibration plots showed a good correlation between the predicted probabilities and the observed proportion of LNI for both models. In patients with both SB and TB, Briganti 2012 accuracy was 0.815, and no significant difference was found between the two nomograms (p = 0.66). At MVA only PSA >20 ng/mL and the evidence of SVI at MRI were independent predictors of LNI. CONCLUSIONS: The direct comparison of the two nomograms showed that Briganti 2019 nomogram was no more accurate than Briganti 2012, and that the role of MRI and MRI TB may be negligible in the prediction of LNI. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e983 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nicola Frego More articles by this author Paciotti Marco More articles by this author Davide Maffei More articles by this author Pier Paolo Avolio More articles by this author Roberto Contieri More articles by this author Alessandro Uleri More articles by this author Massimo Lazzeri More articles by this author Alberto Saita More articles by this author Paolo Casale More articles by this author Nicolò Maria Buffi More articles by this author Giovanni Lughezzani More articles by this author Expand All Advertisement PDF DownloadLoading ...

PD59-07 NEGLECTED LYMPH NODAL METASTASES IN PATIENTS WITH RENAL CANCER: WHEN TO EXTEND THE ANATOMICAL TEMPLATE OF LYMPH NODE DISSECTION DURING NEPHRECTOMY

You have accessJournal of UrologyCME1 May 2022PD59-07 NEGLECTED LYMPH NODAL METASTASES IN PATIENTS WITH RENAL CANCER: WHEN TO EXTEND THE ANATOMICAL TEMPLATE OF LYMPH NODE DISSECTION DURING NEPHRECTOMY Giuseppe Rosiello, Giuseppe Fallara, Giuseppe Basile, Daniele Cignoli, Alberto Martini, Francesco De Cobelli, Giorgio Brembilla, Luigi Nocera, Federico Belladelli, Gianmarco Colandrea, Daniela Canibus, Chiara Re, Giacomo Musso, Francesco Cei, Rayan Matloob, Alberto Briganti, Roberto Bertini, Andrea Necchi, Daniele Raggi, Pierre I. Karakiewicz, Francesco Montorsi, Andrea Salonia, Alessandro Larcher, and Umberto Capitanio Giuseppe RosielloGiuseppe Rosiello More articles by this author , Giuseppe FallaraGiuseppe Fallara More articles by this author , Giuseppe BasileGiuseppe Basile More articles by this author , Daniele CignoliDaniele Cignoli More articles by this author , Alberto MartiniAlberto Martini More articles by this author , Francesco De CobelliFrancesco De Cobelli More articles by this author , Giorgio BrembillaGiorgio Brembilla More articles by this author , Luigi NoceraLuigi Nocera More articles by this author , Federico BelladelliFederico Belladelli More articles by this author , Gianmarco ColandreaGianmarco Colandrea More articles by this author , Daniela CanibusDaniela Canibus More articles by this author , Chiara ReChiara Re More articles by this author , Giacomo MussoGiacomo Musso More articles by this author , Francesco CeiFrancesco Cei More articles by this author , Rayan MatloobRayan Matloob More articles by this author , Alberto BrigantiAlberto Briganti More articles by this author , Roberto BertiniRoberto Bertini More articles by this author , Andrea NecchiAndrea Necchi More articles by this author , Daniele RaggiDaniele Raggi More articles by this author , Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , Andrea SaloniaAndrea Salonia More articles by this author , Alessandro LarcherAlessandro Larcher More articles by this author , and Umberto CapitanioUmberto Capitanio More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002644.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The role of lymph node dissection (LND) in patients with renal cell carcinoma (RCC) is still controversial. For the first time, we tested the hypothesis that occulted lymph node invasion can be predicted according to the presence and the characteristics of lymphadenopathies at preoperative imaging. METHODS: Within a prospectively maintained database, we identified 797 patients with RCC and treated with partial or radical nephrectomy with or without LND at a single tertiary centre between 2000 and 2021. Lymphadenopathy (cN1) was defined as a suspicious lymph node with axial size >1 cm. Anatomical location of cN1 was categorized as follows: 1) hilar; 2) interaortocaval; 3) paraortic; 4) retrocaval. Extended LND (eLND) was defined as LND performed also outside the cN1 anatomical area. Multivariable logistic regression analyses tested for predictors of lymph node invasion (pN1) outside the anatomical field at imaging. A local polynomial smoother weighted function was used to graphically depict the effect of clinical lymph node size on the probability of pN1 outside the suspicious anatomical field, after accounting for tumor size and number of lymph node removed. RESULTS: Overall, 283 (35%) patients underwent LND. Median clinical tumor size was 5 (IQR: 3-7) cm. Proportion of pN1 was 46% vs. 4% in cN1 vs cN0 patients (p<0.001). LND was extended outside cN1 anatomical location in 43% of the cases. Of these, 11% were pN0 and 3.2% vs. 22% vs. 6.4% had pN1 only inside vs. in and outside vs. only outside the suspicious area at preoperative imaging (p<0.001), respectively. At multivariable analyses, lymph node size at imaging independently predicted the risk of lymph node invasion outside the suspicious area (Odds ratio: 1.05, 95%CI 1.02-.1.11; p=0.02 - Figure 1). CONCLUSIONS: Approximately, one out of ten patients surgically treated for kidney cancer harbour suspicious LNI at preoperative imaging (cN1). In those cases, roughly 30% of the patients have occult lymph node metastases outside the anatomical area of cN1, as well. Lymph node size independently predict the risk of finding occult lymph node metastases outside the anatomical area cN1, indicating the need for a more extended LND in case of larger lymphadenopathies. Source of Funding: No © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e1021 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Giuseppe Rosiello More articles by this author Giuseppe Fallara More articles by this author Giuseppe Basile More articles by this author Daniele Cignoli More articles by this author Alberto Martini More articles by this author Francesco De Cobelli More articles by this author Giorgio Brembilla More articles by this author Luigi Nocera More articles by this author Federico Belladelli More articles by this author Gianmarco Colandrea More articles by this author Daniela Canibus More articles by this author Chiara Re More articles by this author Giacomo Musso More articles by this author Francesco Cei More articles by this author Rayan Matloob More articles by this author Alberto Briganti More articles by this author Roberto Bertini More articles by this author Andrea Necchi More articles by this author Daniele Raggi More articles by this author Pierre I. Karakiewicz More articles by this author Francesco Montorsi More articles by this author Andrea Salonia More articles by this author Alessandro Larcher More articles by this author Umberto Capitanio More articles by this author Expand All Advertisement PDF DownloadLoading ...

Biomarkers Associated with Lymph Nodal Metastasis in Endometrioid Endometrial Carcinoma.

Simple SummaryIn endometrial cancer, lymph node invasion assessed through surgical lymphadenectomy or sentinel lymph node biopsy is a determinant factor for the prognosis and planification of adjuvant treatment. Those surgical procedures are associated with short- and long-term complications. Recent advances in molecular characterization of endometrial cancer have provided important insights into the biological nature of tumors but have not improved the pre-operative prediction of LND. This study is a description of the transcriptomic landscape associated with lymph node metastases in endometroid endometrial carcinomas. A 54-genes expression signature was generated at analysis of the primary tumor. Differential gene expression was found between patients with and without lymph node metastasis, with an 87% accuracy. Our findings provide a basis for the development of a gene expression-based signature that can be used to pre-operatively select patients for whom surgical assessment of lymph node status is of little value, and, consequently, an unfavorable risk–benefit balance.Introduction. Lymph node metastasis is determinant in the prognosis and treatment of endometrioid endometrial cancer (EEC) but the risk–benefit balance of surgical lymph node staging remains controversial. Objective. Describe the pathways associated with lymph node metastases in EEC detected by whole RNA sequencing. Methods. RNA-sequencing was performed on a retrospective series of 30 non-metastatic EEC. N+ and N− patients were matched for tumoral size, tumoral grade and myometrial invasion. Results. Twenty-eight EECs were analyzable (16 N+ and 12 N−). Bioinformatics Unsupervised analysis revealed three patterns of expression, enriched in N+, mix of N+/N− and enriched in N−, respectively. The cluster with only N+ patient overexpressed extra cellular matrix, epithelial to mesenchymal and smooth muscle contraction pathways with respect to the N− profile. Differential expression analysis between N+ and N− was used to generate a 54-genes signature with an 87% accuracy. Conclusion. RNA-expression analysis provides a basis to develop a gene expression-based signature that could pre-operatively predict lymph node invasion.