Probability Of Lymph Node Involvement Research Articles

Machine Learning for the Prediction of Lymph Node Metastasis in Patients with Prostate Cancer

<h3>Purpose/Objective(s)</h3> Many tools are used to predict the probability of lymph node involvement (LNI) in patients with prostate cancer before radical prostatectomy (RP) and to select patients for lymph node dissection. Our goal was to externally validate common prediction tools and to create a machine learning model for the prediction of LNI in patients with prostate cancer referred for RP. <h3>Materials/Methods</h3> Patients treated at two academic institutions between 1990 and 2020 with RP followed by pelvic lymph node dissection were included. We trained a gradient boosted tree on data from one institution and the model was validated on the other dataset. Variables incorporated into the model are patient's age, percentage of cores positive on biopsy, Gleason scores, preoperative PSA, and clinical T-stage (cT). The area under curve of the receiver operator characteristic curve (AUC) served as the performance metric. We further compared our model's performance to that of established nomograms, namely the Roach formula, the online Memorial Sloan Kettering Center (MSKCC) nomogram, and the 2012 Briganti nomogram. <h3>Results</h3> The combined dataset consisted of 19,090 patients with median age of 65, median PSA at diagnosis of 7.60 ng/mL, and median percentage of positive cores at biopsy of 44%. 14,252 patients (74.6%) had a Gleason score (GS) of 7, and 4,841 (25.4%) had a GS of ≥ 8. Most patients (18,570 or 97.3%) had cT-stage ≤cT2 disease, and 523 (2.7%) had cT3-4 disease. 3,058 patients (16%) were found to have lymph node involvement. The external validation dataset had 1,093 patients, with 10.7% having lymph node positive disease. After training and on external validation, the AUC of our model was 0.79 (CI: 0.7465-0.83), compared to 0.69 (0.64-0.7455), 0.73 (0.6813-0.7742), and 0.74 (0.6931 - 0.7914) when using the Roach formula, MSKCC nomogram, and Briganti 2012 nomogram, respectively. Furthermore, our model's improved performance was statistically significant, with p-value <0.05 when comparing its AUC to that of all other models. <h3>Conclusion</h3> Our machine learning model can be used to estimate an individual patient's risk of LNI and serves as an additional tool with improved performance compared to established prediction models.

SC33 - The impact of variant histology on the probability of lymph node involvement at imaging: CT scan vs FDG PET

SC33 - The impact of variant histology on the probability of lymph node involvement at imaging: CT scan vs FDG PET

PD60-10 A MORE EXTENDED PELVIC LYMPH NODE DISSECTION DECREASES RECURRENCE RATES IN SELECTED PROSTATE CANCER PATIENTS UNDERGOING RADICAL PROSTATECTOMY

You have accessJournal of UrologyCME1 May 2022PD60-10 A MORE EXTENDED PELVIC LYMPH NODE DISSECTION DECREASES RECURRENCE RATES IN SELECTED PROSTATE CANCER PATIENTS UNDERGOING RADICAL PROSTATECTOMY Giorgio Gandaglia, Giuseppe Rosiello, Francesco Pellegrino, Antony Pellegrino, Marco Bandini, Andrea Salonia, Manuela Tutolo, Mario De Angelis, Gabriele Sorce, Elio Mazzone, Armando Stabile, Vito Cucchiara, Emanuele Zaffuto, Pierre I. Karakiewicz, Shahrokh F. Shariat, Vincenzo Mirone, Francesco Montorsi, and Alberto Briganti Giorgio GandagliaGiorgio Gandaglia More articles by this author , Giuseppe RosielloGiuseppe Rosiello More articles by this author , Francesco PellegrinoFrancesco Pellegrino More articles by this author , Antony PellegrinoAntony Pellegrino More articles by this author , Marco BandiniMarco Bandini More articles by this author , Andrea SaloniaAndrea Salonia More articles by this author , Manuela TutoloManuela Tutolo More articles by this author , Mario De AngelisMario De Angelis More articles by this author , Gabriele SorceGabriele Sorce More articles by this author , Elio MazzoneElio Mazzone More articles by this author , Armando StabileArmando Stabile More articles by this author , Vito CucchiaraVito Cucchiara More articles by this author , Emanuele ZaffutoEmanuele Zaffuto More articles by this author , Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat More articles by this author , Vincenzo MironeVincenzo Mirone 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.0000000000002645.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The impact of the pelvic lymph node dissection (PLND) on the outcome of patients with prostate cancer (pCa) is still a matter of debate. We hypothesized that the extent of PLDN on the risk of developing biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP) varies according to patient baseline characteristics and the probability of lymph node involvement (LNI). METHODS: Overall, 2,542 patients with localized PCa treated with RARP with PLDN at a tertiary referral center between 2010 and 2021 were included. All patients underwent an anatomically-defined extended PLND which included at least the obturatory, external and internal iliac stations and was extended to the common iliac and presacral regions according to each patient profile. Kaplan-Meier analyses assessed time to BCR, which was defined as two consecutive PSA values ≥0.2ng/ml and rising. An interaction test assessed whether the impact of the number of nodes removed on BCR-free survival varied according to the risk of LNI calculated by the Briganti nomogram. RESULTS: Median age was 64 years. The median risk of LNI according to the Briganti nomogram was 10%. The median number of removed lymph nodes was 15 (IQR: 7-19) and LNI rate was 10%. Overall, 314 patients experienced BCR at a median follow-up of 36 months. The 5-year BCR-free survival rate was 74%. The impact of the number of nodes removed on BCR-free survival varied according to the LNI risk (p=0.03). A more extended PLND was associated with decreased rates of BCR in men with a risk of LNI between 11-20% and, above 20 nodes, in those with a risk >20%. Conversely, the effect of PLND was virtually null in those with a lower risk of LNI. CONCLUSIONS: The benefits associated with removing a higher number of nodes appears scarce in patients with low probability of LNI. Patients with a LNI risk >11% may benefit from more extended PLND due to decreasing probability of BCR. These patients represent the ideal candidates for prospective trials testing the role of PLND on patient outcomes. Source of Funding:. © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e1029 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Giorgio Gandaglia More articles by this author Giuseppe Rosiello More articles by this author Francesco Pellegrino More articles by this author Antony Pellegrino More articles by this author Marco Bandini More articles by this author Andrea Salonia More articles by this author Manuela Tutolo More articles by this author Mario De Angelis More articles by this author Gabriele Sorce More articles by this author Elio Mazzone More articles by this author Armando Stabile More articles by this author Vito Cucchiara More articles by this author Emanuele Zaffuto More articles by this author Pierre I. Karakiewicz More articles by this author Shahrokh F. Shariat More articles by this author Vincenzo Mirone More articles by this author Francesco Montorsi More articles by this author Alberto Briganti More articles by this author Expand All Advertisement PDF DownloadLoading ...

External Validation and Comparison of Two Nomograms Predicting the Probability of Lymph Node Involvement in Patients subjected to Robot-Assisted Radical Prostatectomy and Concomitant Lymph Node Dissection: A Single Tertiary Center Experience in the MRI-Era.

IntroductionTo externally validate and directly compare the performance of the Briganti 2012 and Briganti 2019 nomograms as predictors of lymph node invasion (LNI) in a cohort of patients treated with robot-assisted radical prostatectomy (RARP) and extended pelvic lymph node dissection (ePLND).Materials and MethodsAfter the exclusion of patients with incomplete biopsy, imaging, or clinical data, 752 patients who underwent RARP and ePLND between December 2014 to August 2021 at our center, were included. Among these patients, 327 (43.5%) had undergone multi-parametric MRI (mpMRI) and mpMRI-targeted biopsy. The preoperative risk of LNI was calculated for all patients using the Briganti 2012 nomogram, while the Briganti 2019 nomogram was used only in patients who had performed mpMRI with the combination of targeted and systematic biopsy. The performances of Briganti 2012 and 2019 models were evaluated using the area under the receiver-operating characteristics curve analysis, calibrations plot, and decision curve analysis.ResultsA median of 13 (IQR 9–18) nodes per patient was removed, and 78 (10.4%) patients had LNI at final pathology. The area under the curves (AUCs) for Briganti 2012 and 2019 were 0.84 and 0.82, respectively. The calibration plots showed a good correlation between the predicted probabilities and the observed proportion of LNI for both models, with a slight tendency to underestimation. The decision curve analysis (DCA) of the two models was similar, with a slightly higher net benefit for Briganti 2012 nomogram. In patients receiving both systematic- and targeted-biopsy, the Briganti 2012 accuracy was 0.85, and no significant difference was found between the AUCs of 2012 and 2019 nomograms (p = 0.296). In the sub-cohort of 518 (68.9%) intermediate-risk PCa patients, the Briganti 2012 nomogram outperforms the 2019 model in terms of accuracy (0.82 vs. 0.77), calibration curve, and net benefit at DCA.ConclusionThe direct comparison of the two nomograms showed that the most updated nomogram, which included MRI and MRI-targeted biopsy data, was not significantly more accurate than the 2012 model in the prediction of LNI, suggesting a negligible role of mpMRI in the current population.

A0657 - External validation and comparison of two nomograms predicting the probability of lymph node involvement in patients subjected to robotic radical prostatectomy and concomitant lymph node dissection

A0657 - External validation and comparison of two nomograms predicting the probability of lymph node involvement in patients subjected to robotic radical prostatectomy and concomitant lymph node dissection

Extension of Prophylactic Surgery in Medullary Thyroid Carcinoma. Differences Between Sporadic and Hereditary Tumours According to Calcitonin Levels and Lymph Node Involvement

IntroductionCurrently, there is no consensus on the indication of prophylactic surgery of the nodal compartments in the treatment of medullary thyroid carcinoma (MTC). The aim of our study was to perform a correlation study between preoperative calcitonin (basalCT) values and lymph node involvement to establish a criterion on which to base prophylactic surgery in these patients.Material and MethodsWe conducted an observational, retrospective and multicentre study with 29 hospitals. Patients over 18 years of age with a diagnosis of MTC with a pre-surgical calcitonin registry were included. The minimum surgery in all patients had to have been total thyroidectomy (TT) with central compartment lymph node dissection (CCLND). Receiver operating characteristic (ROC) curve analysis was used to establish basalCT cut-off values as predictors of postoperative lymph node involvement.ResultsA total of 244 patients were included. Baseline calcitonin (basalCT) was a good predictor of nodal involvement (AUC 0.718 and 95%CI 0.66–0.978). Heritability was identified as a preoperative factor correlated with baseline tumour CT values (p = 0.000). With a probability of lymph node involvement below 10%, new cut-off points were established. A prophylactic bilateral lateral lymph node dissection in sporadic tumours should be performed at a basalCT > 600 pg/mL; in the case of RET-mutated tumours this value would be 200 pg/mL.ConclusionThe baseline CT value is a good predictor of postoperative lymph node involvement in MTC, however, cut-off points should depent on the hereditary nature of the tumour.

Predicting the Probability of Lymph Node Involvement with Prostate Cancer Nomograms: Can We Trust the Prediction Models?

Abstract Introduction Prediction of lymph node involvement (LNI) is of paramount importance for patients with prostate cancer (PCa) undergoing radical prostatectomy (RP). Multiple statistical models predicting LNI have been developed to support clinical decision-making regarding the need of extended pelvic lymph node dissection (ePLND). Our aim is to evaluate the prediction ability of the best-performing prediction tools for LNI in PCa in a Latin-American population. Methods Clinicopathological data of 830 patients with PCa who underwent RP and ePLND between 2007 and 2018 was obtained. Only data from patients who had ≥ 10 lymph nodes (LNs) harvested were included (n = 576 patients). Four prediction models were validated using this cohort: The Memorial Sloan Kettering Cancer Center (MSKCC) web calculator, Briganti v.2017, Yale formula and Partin tables v.2016. The performance of the prediction tools was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). Results The median age was 61 years old (interquartile range [IQR] 56–66), the median Prostate specific antigen (PSA) was 6,81 ng/mL (IQR 4,8–10,1) and the median of LNs harvested was 17 (IQR 13–23), and LNI was identified in 53 patients (9.3%). Predictions from the 2017 Briganti nomogram AUC (0.85) and the Yale formula AUC (0.85) were the most accurate; MSKCC and 2016 Partin tables AUC were both 0,84. Conclusion There was no significant difference in the performance of the four validated prediction tools in a Latin-American population compared with the European or North American patients in whom these tools have been validated. Among the 4 models, the Briganti v.2017 and Yale formula yielded the best results, but the AUC overlapped with the other validated models.

Statistical approach to mediastinal staging in NSCLC with M.E.S.S.i.a. software.

The exclusion of pathological involvement of mediastinal lymph nodes in patients affected by NSCLC plays a central role in assessing their prognosis and operability. Ceron et al. developed a software - called M.E.S.S.i.a (Mediastinal Evaluation with Statistical Support; instan approach) - that allows the calculation of the residual probability of lymph node involvement after a certain number of tests has been done, by integrating every test result with the pre-test prevalence. M.E.S.S.i.a. bridges a gap of current American College of Chest Physicians (ACCP) guidelines, providing probability values of mediastinal metastasis for a correct clinical decision. We conducted a preliminary retrospective study in a series of 108 patients affected by non small cell lung cancer (NSCLC). Pathological staging was compared to the probability of nodal involvement calculated by M.E.S.S.i.a. software. Forty-two out of 108 subjects (39%) had a calculated post-test probability <8%; none of these had proven N2/N3 metastasis at surgical staging (negative predictive value, NPV: 100%). In 12/41 cases M.E.S.S.i.a. was able to avoid invasive procedures. The remaining 66 (61%) patients did not reach the surgical threshold; among these, 11 displayed N2 positivity at pathological staging. Receiving operator curve (ROC) analysis produced an area under curve (AUC) value of 0.773 (p<0.001). These preliminary data show high accuracy of M.E.S.S.i.a. software in excluding N2/N3 lymph node involvement in NSCLC. We have therefore promoted a prospective multicenter study in order to to get a validation of the calculator at different levels of probability of lymph node involvement. The recruitable subjects are potentially operable NSCLC patients; the gold standard for detection of mediastinal disease is the surgical lymph node dissection.

External Validation of Models Predicting the Probability of Lymph Node Involvement in Prostate Cancer Patients

BackgroundMultiple statistical models predicting lymph node involvement (LNI) in prostate cancer (PCa) exist to support clinical decision-making regarding extended pelvic lymph node dissection (ePLND). ObjectiveTo validate models predicting LNI in Dutch PCa patients. Design, setting, and participantsSixteen prediction models were validated using a patient cohort of 1001 men who underwent ePLND. Patient characteristics included serum prostate specific antigen (PSA), cT stage, primary and secondary Gleason scores, number of biopsy cores taken, and number of positive biopsy cores. Outcome measurements and statistical analysisModel performance was assessed using the area under the receiver operating characteristic curve (AUC). Calibration plots were used to visualize over- or underestimation by the models. Results and limitationsLNI was identified in 276 patients (28%). Patients with LNI had higher PSA, higher primary Gleason pattern, higher Gleason score, higher number of nodes harvested, higher number of positive biopsy cores, and higher cT stage compared to patients without LNI. Predictions generated by the 2012 Briganti nomogram (AUC 0.76) and the Memorial Sloan Kettering Cancer Center (MSKCC) web calculator (AUC 0.75) were the most accurate. Calibration had a decisive role in selecting the most accurate models because of overlapping confidence intervals for the AUCs. Underestimation of LNI probability in patients had a predicted probability of <20%. The omission of model updating was a limitation of the study. ConclusionsModels predicting LNI in PCa patients were externally validated in a Dutch patient cohort. The 2012 Briganti and MSKCC nomograms were identified as the most accurate prediction models available. Patient summaryIn this report we looked at how well models were able to predict the risk of prostate cancer spreading to the pelvic lymph nodes. We found that two models performed similarly in predicting the most accurate probabilities.

Abstract P4-09-10: Nomogram for predicting lymph node involvement in patients with invasive micropapillary carcinoma of breast: A SEER population-based study

Abstract Background: Invasive micropapillary carcinoma (IMPC) is an unusual and distinct subtype of invasive breast tumor with high propensity for regional lymph node metastases. Because of its lymphotropic nature at initial presentation, IMPC is considered to have an unfavorable prognosis when compared with invasive ductal carcinoma (IDC). The aim of this study was to identify risk factors accounting for its lymphotropic features and to develop a nomogram to predict the probability of lymph node involvement in IMPC. Patients and Methods: A retrospective review of the clinical and pathology records was performed in patients diagnosed with IMPC between 2003 and 2014 from Surveillance, Epidemiology, and End Results (SEER) database. Training set comprised patients diagnosed between 2003 and 2009, while validation set included patients diagnosed thereafter. Ethical approval of the study was granted by the Institutional Review Board of Fudan University Shanghai Cancer Center. Multiple logistic regression analysis was conducted. A logistic regression model was used to construct the nomogram in the training set and then validated in the validation set. Nomogram performance was quantified with respect to discrimination and calibration. Results: Overall, 1407 patients diagnosed with IMPC were enrolled, of which 527 in training set and 880 in validation set. The demographic characteristics were comparable within sets. Larger lesion, younger age at diagnosis, black ethnic and lack of hormone receptor expression were significantly related to regional nodes involvement. The AUC of the nomogram was 0.735 (95 percent confidence interval 0.692 to 0.777), demonstrating a good prediction performance. A calibration curve for the nomogram was plotted to evaluate the agreement between actual (observed) outcomes and expected probabilities. The slope of the calibration curve was close to 1, which indicated excellent calibration of the nomogram. The performance of the nomogram was further validated in the validation set, in which AUC was 0.734 (95 percent confidence interval 0.701 to 0.767). Conclusions: The striking difference between IMPC and IDC remains the increased lymph node involvement in IMPC and therefore merits aggressive treatment. The nomogram based on the clinical parameters was established, which could accurately predict regional lymph node status. This nomogram would facilitate evaluating lymph node state preoperatively and thus treatment decision-making of individual patients, especially in neoadjuvant settings. Citation Format: Ye F, Hu X, Shao Z. Nomogram for predicting lymph node involvement in patients with invasive micropapillary carcinoma of breast: A SEER population-based study [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-09-10.

Abstract 3920: Tumor volume as a predictor of lymph node metastases in prostate cancer

Abstract Introduction: Pelvic lymph node dissection (PLND) is recommended during radical prostatectomy (RP) in patients with high risk prostate cancer (PCa). Guidelines recommend extended PLND in patients who have &amp;gt;5% probability of lymph node involvement, calculated from pre-operative parameters. PLND increases procedure time and potential morbidity to patients. Tumour size has been reported to be predictive of biochemical recurrence after RP. We analysed the utility of several parameters including tumour size in predicting lymph node metastases in order to further refine the population who require PLND during RP. Materials &amp; Methods: We maintained a prospective database of Robotic Assisted Radical Prostatectomy (RARP) from July 2012 to August 2016 consisting of a cohort of 531 patients. Patients with &amp;gt;5% calculated probability of lymph node metastasis had PLND during RARP. We performed multiple linear regression using age, PSA, D’Amico risk score, ISUP prognostic group, clinical T-stage, radiological T-stage, tumour volume, tumour volume relative to prostate size (relative tumour volume), and number of nodes excised during PLND to determine if any of these parameters could predict the presence of lymph node metastases. Results: Of the cohort of 531 patients, 154 had PLND during RARP. Of the PLND cohort, 15 (10%) had pN1 disease. Tumour volume (r2 0.044, p= 0.0098), relative tumour volume (r2 0.033, p=0.026) and number of lymph nodes excised (r2 0.046, p=0.0075) were independent predictors of pN1 disease. D’Amico risk score (r2 0.019, p=0.089) approached but did not reach statistical significance. Patients with pN1 disease all had primary tumours ≥6cc. Conclusions: In our cohort of PLND patients, tumour volume was an independent risk factor for pN1 disease. With the increasing availability of multi-parametric MRI, tumour volume can be measured pre-operatively as an adjunct to PIRADS scoring. The role of tumour volume and relative tumour volume in predicting lymph node metastasis in conjunction with other pre-operative parameters requires further investigation. The use of tumour volume in determining the need for PLND in patients undergoing RP may help to further refine the population at highest risk for pN1 disease and avoid the additional morbidity of PLND in those at low risk. In addition, our findings support the recommendation of performing an extended PLND to maximise regional lymph node clearance. Citation Format: Chidi N. Molokwu, Keith Yuen, Sanjay Addla, Rajindra Singh, Rohit Chahal. Tumor volume as a predictor of lymph node metastases in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3920. doi:10.1158/1538-7445.AM2017-3920

Extended pelvic lymphadenectomy in patients with clinically localized prostate cancer: A prospective observational study

ObjectiveTo determine the frequency of lymph node involvement in patients with clinically localized prostate adenocarcinoma who had radical prostatectomy and extended pelvic lymphadenectomy. Material and methodsA prospective observational study was conducted on 137 patients with clinically localized prostate cancer of low, intermediate or high risk according to the D’Amico classification. All participants underwent radical prostatectomy plus extended pelvic lymphadenectomy in 3 reference centers in Bogota, Colombia, between 2013 and 2014. The following variables were assessed: age, prostate specific antigen levels, Gleason score of the biopsy, probability of lymph node involvement calculated with Partin tables and the histopathology result of the surgical specimen, with the definitive Gleason pattern and the total number of resected and involved lymph nodes per tumor, according to the territory of the dissection. ResultsA total of 2876 lymph nodes were extracted (an average of 20.99 lymph nodes per patient). There was lymph node involvement in 14 (10.22%) patients. The high-risk and intermediate-risk group presented lymph node metastases in 28.57% and 5.25%, respectively. There was no lymph node involvement in the low-risk group. Of the patients at risk of lymph node involvement (≥2% according to the Partin tables), 19.40% had lymph node metastases. ConclusionLymph node involvement in our population is similar to that reported in the worldwide literature. Extended pelvic lymphadenectomy increased the probability of detecting lymph node metastases in our community.

Linfadenectomía pélvica extendida en pacientes con cáncer de próstata clínicamente localizado: estudio observacional prospectivo

ObjectiveTo determine the frequency of lymph node involvement in patients with clinically localised prostate adenocarcinoma who had radical prostatectomy and extended pelvic lymphadenectomy. Material and methodsA prospective observational study was conducted on 137 patients with clinically localised prostate cancer of low, intermediate or high risk according to the D’Amico classification. All participants underwent radical prostatectomy plus extended pelvic lymphadenectomy in 3 reference centres in Bogota, Colombia, between 2013 and 2014. The following variables were assessed: age, prostate specific antigen levels, Gleason score of the biopsy, probability of lymph node involvement calculated with Partin tables and the histopathology result of the surgical specimen, with the definitive Gleason pattern and the total number of resected and involved lymph nodes per tumour, according to the territory of the dissection. ResultsA total of 2,876 lymph nodes were extracted (an average of 20.99 lymph nodes per patient). There was lymph node involvement in 14 (10.22%) patients. The high-risk and intermediate-risk group presented lymph node metastases in 28.57% and 5.25%, respectively. There was no lymph node involvement in the low-risk group. Of the patients at risk of lymph node involvement (≥2% according to the Partin tables), 19.40% had lymph node metastases. ConclusionLymph node involvement in our population is similar to that reported in the worldwide literature. Extended pelvic lymphadenectomy increased the probability of detecting lymph node metastases in our community.

Is the Probability of Lymph Node Involvement a Prognostic Indicator in Stage III Rectal Cancer Patients?

METHODS: Retrospective analysis of the University of Wisconsin CRC database from 1995 to 2013 was used to identify patients diagnosed with stage III rectal cancer. Patients were divided into 3 lymph node ratio (LNR) and LODDS groups, based on the range of calculated values. Demographic and survival analyses were performed. The Kaplan-Meier method was used for survival analyses. Log-rank test and Cox regression analyses were used to identify potential differences among groups.

Regional Lymphadenectomy Is Indicated in the Surgical Treatment of Pancreatic Neuroendocrine Tumors (PNETs)

To explore the prognostic importance and preoperative predictors of lymph node metastasis in an effort to guide surgical decision making in patients with pancreatic neuroendocrine tumors (PNETs). PNETs are uncommon, and the natural history of the disease is not well described. As a result, there remains controversy regarding the optimal management of regional lymph nodes during resection of the primary tumor. A retrospective review of a prospectively maintained database of patients who underwent surgery for locoregional PNET between 1994 and 2012 was performed. Logistic regression was used to identify predictors of nodal metastasis. Overall survival and disease-free survival were calculated using Kaplan-Meier method. Results were expressed as P values and odds ratio estimates, with 95% confidence intervals. One hundred thirty-six patients were identified, of whom 50 (38%) patients had nodal metastasis. The frequency of lymph node metastasis was higher for larger tumors [> 1.5 cm (odds ratio [OR] = 4.7)], tumors of the head as compared with body-tail of the pancreas (OR = 2.8), tumors with Ki-67 greater than 20% (OR = 6.7), and tumors with lymph vascular invasion (OR = 3.6) (P < 0.05). Median disease-free survival was lower for patients with nodal metastases (4.5 vs 14.6 years, P < 0.0001). Lymph node metastasis is predictive of poor outcomes in patients with PNETs. Preoperative variables are not able to reliably predict patients where the probability of lymph node involvement was less than 12%. These data support inclusion of regional lymphadenectomy in patients undergoing pancreatic resections for PNET.

Validation of Nomograms Predicting Lymph Node Involvement in Patients with Prostate Cancer Undergoing Extended Pelvic Lymph Node Dissection

Our aim was to validate Briganti's nomograms predicting the probability of lymph node involvement (LNI) in prostate cancer (PCa). Clinicopathological data of 256 PCa patients who underwent extended pelvic lymph node dissection (ePLND) and radical prostatectomy (RP) were obtained from two Bulgarian institutions. Predicted probabilities of LNI were assessed using Briganti's nomograms based on ePLND. In addition to the established basic LNI predictors, Briganti's nomograms included the number of lymph nodes removed (version 2006) and the number and percentage of positive biopsy cores (versions 2007 and 2012). The accuracy of these nomograms was compared with the updated Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram (version 2011). Receiver-operating characteristics analysis was done to assess the discriminative ability of each of the nomograms applied. All of Briganti's nomograms showed a higher predictive accuracy as compared with the updated MSKCC nomogram. The respective AUC values were calculated as 0.847, 0.837, 0.858 and 0.875 for the four Briganti nomograms, and 0.770 for the updated MSKCC nomogram, respectively. Despite the potential for heterogeneity in patient selection and management, all predictions demonstrated high concordance with actual observations. Compared with other similar prognostic tools the updated Briganti nomogram (version 2012) showed the highest predictive accuracy and should therefore be preferred.

Sentinel lymph node dissection in more than 1200 prostate cancer cases: Rate and prediction of lymph node involvement depending on preoperative tumor characteristics

To stratify the rate and prediction of lymph node involvement in prostate cancer patients undergoing sentinel-lymphadenectomy depending on preoperative tumor characteristics, and to compare the outcome with the European Association of Urology Guideline indication for lymphadenectomy. A total of 1229 patients (median age 66 years) were treated with open sentinel-lymphadenectomy and prostatectomy between 2005 and 2009. Median preoperative prostate-specific antigen was 7.4 ng/mL. The rate of lymph node involvement was analyzed for D'Amico risk groups. Multivariable logistic regression was used to estimate the probability of lymph node involvement. Predictor variables included preoperative prostate-specific antigen, clinical T-category and biopsy Gleason sum. Predictive accuracy has been quantified (area under the curve) and lymph node positive patients were verified under consideration of the recommended European threshold for lymphadenectomy (nomogram-predicted lymph node invasion risk of >7%). The median number of lymph nodes removed was 10 (interquartile range 7-13). Overall, 17.1% of patients had lymph node involvement; 3.2% in low-, 14.8% in intermediate- and 37.4% in high-risk disease. The predicted risk for lymph node involvement ranged from 2% (prostate-specific antigen ≤4 ng/mL, T1, Gleason sum ≤6) to 87% (prostate-specific antigen >20 ng/mL, T3, Gleason sum ≥8). The predictive accuracy was 82.1%. According to the European guidelines, 15.9% of all lymph node involved cases would not have been detected. The rate of lymph node involvement seems to be higher in the examined sentinel collective than expected according to the European Guideline nomogram. The first sentinel-based lymph node involvement prediction model can assist in deciding on the indication for sentinel-lymphadenectomy. The validation of a corresponding sentinel-based nomogram is still missing.

Lymph node involvement in T1 non-small-cell lung cancer: could glucose uptake and maximal diameter be predictive criteria?☆

The introduction of modern staging systems such as computed tomography (CT) and positron emission tomography/CT (PET/CT) with fluorodeoxyglucose ([(18)F]FDG) has increased the detection of small peripheral lung cancers at an early stage. We analyzed the behavior of pathological T1 non-small-cell lung cancer (NSCLC) to identify criteria predictive of nodal involvement, and the role of cancer size in lymph node metastases. We retrospectively analyzed 219 patients with pathological T1 NSCLC. All patients were staged by high-resolution CT and PET as stage I, and underwent anatomical resection and radical lymphadenectomy. Our data were collected based on pathological nodule size (0-10 mm; 11-20 mm; and 21-30 mm); morphological features of lung nodule and FDG uptake of the tumor measured by standardized uptake value (SUV). A total of 190 patients (87%) were pN0, 14 (6%) pN1, and 15 (7%) pN2. No nodal involvement was observed in any of the 62 patients with nodule size less than 10 mm, in 20 out of 120 patients (17%) with nodule size 11-20 mm, and in nine out of 37 tumors (28%) 21-30 mm in size (p=0.0007). All 55 patients with nodule SUV<2.0 and all 26 non-solid lesions were pN0 (respectively, p=0.0001 and p=0.03). All nodal metastases occurred among the group of 132 patients with size larger than 10 mm and SUV higher than 2.0 with a 22% rate of nodal involvement of (29 patients) (p<0.0001). The low probability of lymph node involvement in NSCLC <1 cm or showing glucose uptake <2 suggests lymphadenectomy could be avoided. A randomized trial should be performed to validate our data.

Probit regression in prediction analysis

To avoid diagnostic surgery, the probability of nodal involvement of prostate cancer is modeled using the pobit link function to determine whether the lymph nodes of a patients are infected. X-ray status and level of acid phosphatase in the blood serum of patients are considered as preoperative explanatory variables with the number of patients having nodal involvement as response variable. Within the framework of the probit regression model, the level of nodal involvement is predicted and the probability of nodal involvement obtained. KEYWORDS: Probit model, Nodal involvement, Standard cumulative normal distribution, Latent variable, Logistic regression.

TU‐D‐352‐04: Novel Decision Aid for IMRT Treatment Plans Generated Using Multiobjective Optimization

Purpose: To develop the decision making component of a multiobjective IMRT optimization procedure for prostate cancer that incorporates disparate sources of information used in clinical decision making, the uncertain outcomes inherent in radiation therapy and the preferences of the patient. Method and Materials: Currently, many IMRT plans are developed for each patient without indication of which plan provides the optimal balance between tumor control and complication probability. Coupled with the typical number of objectives, plan selection is difficult. We chose a Bayesian Network (BN) coupled with a Markov Model (MM) and utility theory to calculate Quality Adjusted Life Expectancy (QALE) for IMRT treatment of prostate cancer. The BN was constructed with the advice of experts; conditional probabilities were obtained from research and clinical trial publications and expert opinion. Local, regional, and distant control were included as were complications to bladder and rectum. The MM relied on transition probabilities derived from the BN, published clinical trials and life expectancy tables. Utilities were obtained from the literature. Plan ranking was based on QALE or any of the components, e.g. local control or complications. Results: Probabilities of local and distant control as a function of disease state matched published values well, as did life expectancies. Sensitivity analyses highlighted the critical nodes in the network. Analysis of outcomes versus probability of lymph node involvement provided a basis for decisions regarding pelvic irradiation. A BN is well‐suited to handle rigorously conditional probabilities and the disparate nature of clinical variables. QALE provides a method for ranking plans based on clinically relevant criteria that incorporates the probabilistic nature of the outcome. Conclusion: A decision aid was constructed using a Bayesian Network coupled to a Markov Model. This resulted in the ability to rank competing plans based either on QALE or specific outcomes.