Large Multi-institutional Cohort Research Articles

Can Pelvic Lymph Node Dissection in Prostate Cancer Patients with a 5% Briganti Nomogram Cut-off Value Provide an Oncological Benefit? A Large Multi-Institutional Cohort Study in Japan.

The Briganti nomogram (cut-off value 5%) is commonly used to determine the indications for pelvic lymph node dissection (PLND) in patients with prostate cancer. We retrospectively analyzed the potential oncological benefit of PLND based on the 5% cut-off value on the Briganti nomogram. We obtained the data from the Medical Investigation Cancer Network (MICAN) Study, which included 3,463 patients who underwent a radical prostatectomy (RP) at nine institutions in Japan between 2010 and 2020. We included patients with Briganti scores ≥ 5% and a follow-up period ≥6 months and excluded patients categorized in the very high-risk group (based on NCCN categories); a final total of the cases of 1,068 patients were analyzed. The biochemical recurrence (BCR)-free survival was significantly worse in the patients who underwent PLND compared to those who did not (p=0.019). A multivariate analysis showed that high prostate-specific antigen (PSA) levels (p<0.001) and an advanced T-stage (p=0.018) were significant prognostic factors for BCR, whereas PLND had no effect on BCR (p=0.059). Thus, PLND in patients with prostate cancer whose Briganti score was 5% did not provide any oncological benefit. Further research is necessary to determine the indication criteria for conducting PLND.

LGG-60. DISTRIBUTION AND CLINICAL SIGNIFICANCE OF FGFR ALTERATIONS IN PEDIATRIC AND AYA GLIOMAS

Abstract Fibroblast growth factor receptor (FGFR) alterations are prevalent in human cancers. In a large Canadian population-based cohort, encompassing over 1,300 pediatric and Adolescent and young adult (AYA) gliomas, FGFR mutations occurred in 10% of pediatric low-grade gliomas (LGG) and 20% of IDH-WT AYA LGGs. Here we assembled a large multi-institutional cohort including more than 300 mutated gliomas, aged 6 months to 87 years, 53% of which were LGG. High-grade gliomas were more common with increasing age; over 90% of pediatric cases were LGGs, compared to 30% in the AYA group. Fusions, predominantly seen in the pediatric group (70% of LGGs), contrast with FGFR3-TACC3 fusions frequent found in adult high-grade gliomas. Interestingly, FGFR mutations sometimes existed as sole drivers or co-occurred with other alterations (~30%), it is unclear how this alters tumor behavior, although gain of additional alterations could be implied in malignant transformation and poor prognosis. Despite higher incidence of high-grade gliomas in AYAs, their progression-free survival was significantly better than that of pediatric LGGs (p=0.007), largely due to the prevalence of hemispheric tumors amenable to gross total resection. Approximately 30% of our LGG cohort underwent adjuvant therapy; with available data for 28 patients, objective responses were noted in 2/12 to chemotherapy, 2/9 to MEK inhibitors, and 3/7 to FGFR inhibitors, respectively. With the increasing promise of precision targeted therapy, molecular profiling and assessment for FGFR alterations is essential. Although encouraging, further studies are needed to assess the benefit of FGFR inhibition in these patients.

Prognosis and tumor-infiltrating lymphocytes (TILs) in estrogen receptor (ER)-low metastatic breast cancer (MBC): Analysis from a large multi-institutional cohort and the TONIC phase II trial with nivolumab.

1100 Background: Although 1% as ER cutoff to discriminate ER+/HER2- from triple-negative (TN) BC serves the purpose of maximizing access to endocrine therapy, it may be suboptimally informative in terms of prognosis and immune checkpoint inhibitor (ICI) benefit. In the early setting, we reported that ER-low BC (ER 1-9%/HER2-) is immunologically and prognostically similar to TN (ER 0%) [Massa, 2023]. Here we focus on MBC and aim to assess prognosis of ER-low BC, including the conversion from ER+(≥10%)/HER2- to ER-low at relapse. We also compared ER-low and TN in terms of outcome after ICI, and TILs. Methods: We included two cohorts of MBC patients (pts): a multicentric retrospective cohort and pts with ER&lt;10%/HER2- MBC enrolled in the TONIC trial testing nivolumab +/- induction therapy. All pts had ER and HER2 status assessed on metastatic tumor lesion; in the retrospective cohort ER and HER2 status on primary tumor was also available. Survival endpoints in the retrospective cohort: overall survival (OS, from BC diagnosis), post-relapse survival (PRS, from BC relapse). Exploratory endpoints from the TONIC trial: clinical benefit rate (CBR), OS and PFS (both from randomization). TILs were assessed on MBC samples (both cohorts) and on matched primary tumor (retrospective cohort). Results: We included 1112 pts in the retrospective cohort: the prevalence of ER-low BC was 3.6% in primary tumor and 5.9% in MBC lesions. In the TONIC trial, 15/110 pts had ER-low MBC. In the retrospective cohort, ER-low and TN MBC showed similar outcome, and significantly unfavorable vs ER+/HER2- MBC (Table). Among pts with ER+/HER2- primary BC, 6.7% converted to ER-low and 14.7% to TN at relapse. ER+/HER2- BC pts converting to ER-low had similar outcome than those converted to TN, and significantly poorer than pts with stable ER+/HER2- (Table). In the TONIC trial, ER-low MBC pts, compared to TN, showed similar response to ICI (CBR: 20.0% vs 22.1%, p=1), similar PFS and numerically worse OS (Table). TIL levels on MBC samples were similar between ER-low and TN both in the retrospective (median: 6% vs 5%, p=0.83) and the TONIC cohorts (median: 5.5% vs 5.0%, p=0.56) and were higher than ER+/HER2- (median: 3%). Conclusions: We confirmed that ER-low and TN MBC show similar poor outcome and the shift from ER+/HER2- to ER-low has a comparable unfavorable prognostic impact compared to conversion to TN. Our results support the hypothesis that ER-low and TN are immunologically akin and similarly prone to respond to ICI. [Table: see text]

Overall survival prediction and risk stratification in patients with neuroblastoma through machine learning in the large multi-institutional PRIMAGE cohort.

10054 Background: Neuroblastoma (NB) is the most prevalent solid cancer in childhood in which imaging plays a pivotal role at every step of the patient's journey. This investigation aimed to develop a machine learning model using clinical, molecular (MycN amplification), and magnetic resonance (MR) radiomics features at diagnosis to predict patient’s overall survival (OS) and improve their risk stratification. Methods: A database comprising clinical, molecular, and International Neuroblastoma Risk Group (INRG) staging on 513 patients with accessible MR imaging (discovery cohort) was employed for model training, validation, and testing. An additional 22 patients from non-discovery cohort hospitals served as an external validation group. Tumor segmentations of NB were manually and semi-automatically performed on corresponding T2-weighted MR images by an experienced radiologist. In total, 107 radiomics features were extracted and harmonized across MR scan manufacturers and magnetic field strengths using the nested ComBat methodology to correct both batch effects. These radiomics features, combined with clinical and molecular data, were utilized as input for the models. A nested cross-validation approach was employed for model development to determine the optimal preprocessing, machine learning algorithm, and model configuration. Results: The discovery cohort yielded a C-index of 0.788 ± 0.049 in the test partitions, with a random survival forest (RSF) exhibiting the best performance. In the validation cohort, a C-index of 0.934 was achieved. Interpretability analysis identified lesion heterogeneity, size, and molecular variables as crucial factors in OS prediction. The model demonstrated superior predictive performance and patient stratification compared to conventional staging systems in both cohorts. Conclusions: The RSF predictive model exhibited high performance, emphasizing the significant contribution of radiomics features and alignment with established clinical and molecular variables. The model stratified NB patients into low-, intermediate-, and high-risk categories and suggests that radiomics features potentially could improve current risk stratification systems. Additional external validation is warranted as this may present new evidence for enhancing patient care and clinical decision-making for NB patients.

Efficacy and survival of nivolumab treatment for recurrent/unresectable esophageal squamous-cell carcinoma: real-world clinical data from a large multi-institutional cohort

BackgroundReal-world clinical outcomes of and prognostic factors for nivolumab treatment for esophageal squamous-cell carcinoma (ESCC) remain unclear. This study aimed to evaluate real-world outcomes of nivolumab monotherapy in association with relevant clinical parameters in recurrent/unresectable advanced ESCC patients.MethodsThis population-based multicenter cohort study included a total of 282 patients from 15 institutions with recurrent/unresectable advanced ESCC who received nivolumab as a second-line or later therapy between 2014 and 2022. Data, including the best overall response, progression-free survival (PFS), and overall survival (OS), were retrospectively collected from these patients.ResultsObjective response and disease control rates were 17.0% and 47.9%, respectively. The clinical response to nivolumab treatment significantly correlated with development of overall immune-related adverse events (P < .0001), including rash (P < .0001), hypothyroidism (P = .03), and interstitial pneumonia (P = .004). Organ-specific best response rates were 20.6% in lymph nodes, 17.4% in lungs, 15.4% in pleural dissemination, and 13.6% in primary lesions. In terms of patient survival, the median OS and PFS was 10.9 and 2.4 months, respectively. Univariate analysis of OS revealed that performance status (PS; P < .0001), number of metastatic organs (P = .019), C-reactive protein-to-albumin ratio (CAR; P < .0001), neutrophil–lymphocyte ratio (P = .001), and PMI (P = .024) were significant. Multivariate analysis further identified CAR [hazard ratio (HR) = 1.61, 95% confidence interval (CI) 1.15–2.25, P = .0053)] in addition to PS (HR = 1.65, 95% CI 1.23–2.22, P = .0008) as independent prognostic parameters.ConclusionsCAR and PS before nivolumab treatment are useful in predicting long-term survival in recurrent/unresectable advanced ESCC patients with second-line or later nivolumab treatment.Trial RegistrationUMIN000040462

Abstract PO5-05-12: Loco-regional Treatment in De Novo Bone Only Metastatic Breast Cancer; Prospective, Multi-Institutional Real-World Data, BOMETIN, Protocol MF14-1a

Abstract Introduction: The impact of loco-regional treatment (LRT) on survival in de novo bone-only metastatic breast cancer (BC) is controversial. The aim of this study is to assess the effect of LRT on survival utilizing international, prospectively acquired data in this cohort of patients. Materials and Methods: Patients with de novo metastatic BC with bone-only metastases were divided into two groups: those receiving systemic therapy only (ST) and those undergoing LRT. Patients who received LRT were divided into two groups: those who received ST after LRT (LRT+ST arm) and those who received ST prior to LRT (ST+LRT arm). Solitary or multiple bone metastases were classified, and factors associated with disease progression were analyzed. Results: There were a total of 744 patients with de novo bone-only metastatic BC treated at each of the participating institutions between 2014 and 2022, with 372 (50%) participants in each arm. Median follow-up was 48 months (32-66, 25-75%). Patients in the LRT group were significantly younger than the ST group [50 (42, 60) vs 55 (44, 66), p=0.0001]. There were no significant differences in grade, Her2 neu and triple negative status, receipt of hormonal therapy and intervention to metastatic sites. During follow-up, 58% (n=217) of patients in ST arm and 32% (n=120) of patients in LRT arm died (p&amp;lt; 0.001). Local progression was observed in 20% of the patients in the ST arm whereas it was 9% in the LRT arm (p=0.0001). Systemic progression occurred more in ST arm; 66% (n=244) compared to 41% (n=152) of patients in LRT group (p&amp;lt; 0.001). The Hazard of death was 64% lower in LRT group than in ST group (HR: 0.36, 95% CI: 0.29-0.45), p&amp;lt;0.0001). The burden of metastatic disease was significantly different between groups with the solitary bone metastasis rate higher in LRT group than the ST only group (50% vs 24%, p&amp;lt; 0.001). However, the LRT group had better overall survival for both solitary (HR: 0.38, 95% Cl: 0.26-0.55) and multiple (HR: 0.38, 95% Cl: 0.29-0.51) bone metastases patients. Within the LRT group, survival rates were similar whether the breast surgery was performed before or after ST.Multivariate Cox analysis showed that LRT and ER/PR positivity significantly decrease the hazard of death (p&amp;lt; 0.05). Conclusion: Analysis of this large multi-institutional patient cohort provides further evidence that LRT improves overall survival and lowers loco-regional recurrence in patients with de novo bone-only metastatic BC. In breast cancer patients with bone-only metastases at presentation, the decision for LRT should be made through a multidisciplinary approach with consideration of surgical therapy at the primary tumor. Citation Format: Atilla Soran, Serdar Ozbas, Lutfi Dogan, Didem Can Trabulus, Jamila El-Azrhi, Kazim Senol, Berk Goktepe, Shruti Zaveri, Salyna Meas, Umut Demirci, Hasan Karanlik, Aykut Soyder, Ahmet Dağ, Ahmet Bilici, Mutlu Dogan, Mehmet Ali Nahit Sendur, Hande Koksal, Mehmet Ali Gulcelik, Neslihan Cabıoğlu, Levent Yeniay, N. Zafer Utkan, Nuri Karadurmus, Gul Daglar, Turgay Simsek, Birol Yildiz, Cihan Uras, Mustafa Tukenmez, Cihangir Ozaslan, Niyazi Karaman, Arda Isik, Berkay Demirors, Efe Sezgin, Vahit Ozmen, Anthony Lucci. Loco-regional Treatment in De Novo Bone Only Metastatic Breast Cancer; Prospective, Multi-Institutional Real-World Data, BOMETIN, Protocol MF14-1a [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-05-12.

Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases.

Radiation necrosis (RN) can be difficult to radiographically discern from tumor progression after stereotactic radiosurgery (SRS). The objective of this study was to investigate the utility of radiomics and machine learning (ML) to differentiate RN from recurrence in patients with brain metastases treated with SRS. Patients with brain metastases treated with SRS who developed either RN or tumor reccurence were retrospectively identified. Image preprocessing and radiomic feature extraction were performed using ANTsPy and PyRadiomics, yielding 105 features from MRI T1-weighted post-contrast (T1c), T2, and fluid-attenuated inversion recovery (FLAIR) images. Univariate analysis assessed significance of individual features. Multivariable analysis employed various classifiers on features identified as most discriminative through feature selection. ML models were evaluated through cross-validation, selecting the best model based on area under the receiver operating characteristic (ROC) curve (AUC). Specificity, sensitivity, and F1 score were computed. Sixty-six lesions from 55 patients were identified. On univariate analysis, 27 features from the T1c sequence were statistically significant, while no features were significant from the T2 or FLAIR sequences. For clinical variables, only immunotherapy use after SRS was significant. Multivariable analysis of features from the T1c sequence yielded an AUC of 76.2% (standard deviation [SD] ± 12.7%), with specificity and sensitivity of 75.5% (± 13.4%) and 62.3% (± 19.6%) in differentiating radionecrosis from recurrence. Radiomics with ML may assist the diagnostic ability of distinguishing RN from tumor recurrence after SRS. Further work is needed to validate this in a larger multi-institutional cohort and prospectively evaluate it's utility in patient care.

Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.

Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication, clinical adoption of the developed methodology still needs to be improved. To overcome this limitation, we set out to predict the prognosis of a large multi-institutional cohort of patients with COVID-19 using a DL-based model. This study aimed to evaluate the performance of deep privacy-preserving federated learning (DPFL) in predicting COVID-19 outcomes using chest CT images. After applying inclusion and exclusion criteria, 3055 patients from 19 centers, including 1599 alive and 1456 deceased, were enrolled in this study. Data from all centers were split (randomly with stratification respective to each center and class) into a training/validation set (70%/10%) and a hold-out test set (20%). For the DL model, feature extraction was performed on 2D slices, and averaging was performed at the final layer to construct a 3D model for each scan. The DensNet model was used for feature extraction. The model was developed using centralized and FL approaches. For FL, we employed DPFL approaches. Membership inference attack was also evaluated in the FL strategy. For model evaluation, different metrics were reported in the hold-out test sets. In addition, models trained in two scenarios, centralized and FL, were compared using the DeLong test for statistical differences. The centralized model achieved an accuracy of 0.76, while the DPFL model had an accuracy of 0.75. Both the centralized and DPFL models achieved a specificity of 0.77. The centralized model achieved a sensitivity of 0.74, while the DPFL model had a sensitivity of 0.73. A mean AUC of 0.82 and 0.81 with 95% confidence intervals of (95% CI: 0.79-0.85) and (95% CI: 0.77-0.84) were achieved by the centralized model and the DPFL model, respectively. The DeLong test did not prove statistically significant differences between the two models (p-value=0.98). The AUC values for the inference attacks fluctuate between 0.49 and 0.51, with an average of 0.50±0.003 and 95% CI for the mean AUC of 0.500 to 0.501. The performance of the proposed model was comparable to centralized models while operating on large and heterogeneous multi-institutional datasets. In addition, the model was resistant to inference attacks, ensuring the privacy of shared data during the training process.

(181) Prior Radiation Therapy is Associated with Increased Risk of Intra-Operative Complications in Patients Undergoing Primary Inflatable Penile Prosthesis Placement: Results from a Large Multi-Institutional Collaborative

Abstract Introduction Radiation therapy (RT) can predispose the onset of corporal fibrosis and microvasculopathy. The impact of RT on intra-operative complications is not well described in the literature. Objective In this study, we assess intra-operative and post-operative outcomes among patients with or without prior history of RT following primary Inflatable Penile Prosthesis (IPP) implantation. Methods We performed a multicenter, retrospective analysis of men undergoing primary IPP placement between January 2015 and December 2022. A total of 3530 patients were identified, of which 3319 had no prior history of RT and 211 patients had history of RT. After 1:1 propensity score matching for all confounding variables, 211 patients with a history of RT were compared to 211 nonradiated patients for intra-operative and post-operative outcomes. Chi-square and Mann-Whitney tests were used for statistical analysis for categorial and continuous variables respectively. For multivariable analysis, we used a forward stepwise model and included significant variables found on pre-operative characteristics of patients. Kaplan-Meier time to event analysis were compared with Mantel-Cox log-rank test. Results Patients with history of RT encountered more intra-operative complications (4.3% vs 0.9%, p=0.032); specifically, these men experienced more distal crossover events (1.9% vs 0, p=0.044). On multivariable analysis, history of prior RT (OR 5.29, 95% CI 1.07-26.3, p=0.041) and diabetes mellitus (OR 10.5, 95% CI 2.58-43.5, p=0.01) were associated with increased risk of intra-operative complications. History of obesity (OR 0.11, 95% CI 0.01-0.91, p=0.040) reduced risk of intra-operative complications. There was no significant difference in early or late post-operative non-infectious complications between both groups and there was also no significant difference in risk of post-operative complications within 24 months on Kaplan Meier analysis (log rank p=0.9). Conclusions In this large multi-institutional cohort, history of RT is an independent predictor of intra-operative complications but not post-operative complications during primary IPP placement. These findings may help inform patient-specific counseling while guiding surgical planning to prevent untoward morbidity following surgery. Disclosure No.

Impact of Maintenance Rituximab Following First-Line Systemic Therapy on Outcomes in Patients with Marginal Zone Lymphoma: Real-World Evidence from 10 US Centers

Introduction First-line treatment options for patients (pts) with marginal zone lymphoma (MZL) include rituximab monotherapy (R) and immunochemotherapy (IC), such as bendamustine with rituximab (BR) or RCHOP/RCVP. The efficacy of maintenance rituximab (M-R) has been studied in splenic (SMZL) and nodal (NMZL) MZL, showing a benefit in progression-free survival (PFS) when M-R is administered after BR (Rummel et al., ASCO 2018). However, the role of M-R in pts with extranodal MZL (EMZL) of the mucosa-associated lymphatic tissue (MALT), or those receiving R or RCHOP/RCVP, remains uncertain. In this study, we analyzed the outcomes of pts with MZL who received M-R after their first-line systemic therapy (R or IC) using data from a large multi-institutional retrospective cohort. Methods Adult pts with MZL (SMZL, NMZL, or EMZL) who were treated at 10 US medical centers from 2010 onwards were included. Pts who had received first-line treatment with either R or IC and achieved a partial (PR) or complete (CR) response to the initial therapy were divided into groups based on whether they subsequently received M-R or not. To avoid immortal-time bias, we required a minimum follow-up of 6 months from diagnosis. Outcomes included PFS, overall survival (OS) and cumulative incidence of histologic transformation (HT). Because of non-proportional hazards, Wilcoxon test was used to compare survival curves, and Cox models (augmented by multiple imputation to account for missing data) were bounded by 6 years of follow up. Multivariable models adjusted for prognostic factors including age, sex, performance status, stage, baseline hemoglobin, albumin, LDH, type of IC and CR/PR status at the end of therapy. Results The study included 427 pts with a median age of 63 years. Of these pts, 53% were women, and 49% had EMZL, 27% had NMZL, and 23% had SMZL. The first-line therapies received were R (54%), BR (36%), RCHOP (7%), or RCVP (3%). A CR was achieved by 70% (n=298) of pts after the initial therapy. Overall, 33% (n=140) received M-R with a median of 8 cycles. Among pts who initially had PR, 39% converted to a CR during M-R therapy. The median follow-up period was 5 years. Factors associated with a higher likelihood of receiving M-R included achieving a PR instead of a CR after the first-line therapy (41% vs 29% receiving M-R, respectively; p=0.02) and having the SMZL subtype (p=0.03, Fig 1A). Pts treated with RCHOP were less likely to receive M-R compared to those receiving other regimens (p=0.049). There was also evidence of hospital-level preference to either prescribe M-R or not. We analyzed survival outcomes separately for pts who received first-line IC or R monotherapy, stratified further by MZL subtype and the type of IC regimen. Among pts who received IC (n=197), M-R was associated with longer PFS (median of 9.0 vs. 6.8 years, p=0.008, Fig 1B). However, the statistical significance was lost in the multivariable model (adjusted HR=0.52, 95%CI=0.25-1.10). When evaluated by MZL subtype, pts with EMZL had a significantly longer PFS with M-R (p=0.01), while those with NMZL and SMZL did not (p=0.41 and 0.10, respectively). When examining the type of first-line IC, pts receiving RCHOP/RCVP had a prolonged PFS with M-R (p=0.03), whereas the difference was not statistically significant after BR (p=0.12). There was no difference in OS overall (p=0.09; adjusted HR=0.55, 95%CI=0.12-2.60) or in any subgroup. Among pts who received first-line R, there were no statistically significant differences in PFS (p=0.70; adjusted HR=0.99, 95%CI=0.59-1.66) or OS (p=0.17) based on the receipt of M-R, either in the entire cohort or any subset. A total of 14 transformation events occurred during the study, including 3 in the M-R group. The cumulative incidence of HT did not significantly differ between the two groups (sub-HR=0.76, 95%CI=0.21-2.82, p=0.68). Discussion In this large retrospective cohort study, the use of M-R in MZL was primarily influenced by local preferences, the quality of response after initial treatment, and the type of IC regimen. Receipt of M-R was associated with a longer PFS for pts receiving first-line IC, especially for those with EMZL and those receiving RCHOP/RCVP. These findings suggest a PFS advantage of M-R in EMZL, which is a novel observation. However, this advantage was not observed in terms of OS or the rate of HT. M-R after initial R did not show any significant differences in outcomes for MZL.

Leveraging Quantitative Imaging and Machine Learning to Differentiate Radionecrosis from Disease Recurrence in Patients with Brain Metastases

Radiation necrosis can be difficult to non-invasively discern from tumor progression after stereotactic radiosurgery (SRS). In this work, we investigate the utility of radiomics (computerized features) and machine learning to capture per-voxel lesion heterogeneity on routine MRI scans, to differentiate radionecrosis from tumor recurrence in patients with brain metastases treated with SRS. A retrospective analysis was conducted of patients with brain metastases treated with SRS. Eighty-three lesions (n = 56 intact; n = 27 surgical cavity) from 69 patients were identified with median age 68.8 years (range 40.2 - 91.0), of whom 53.6% were male and 33.3% received prior whole-brain radiotherapy (WBRT). Lesion histology included lung (60.2%), renal cell (15.7%), melanoma (10.8%), breast (9.6%), and other (3.6%). Pathologic confirmation was available in 73.5% of lesions. Both intact and resection cavity lesions were included and individually segmented. Image preprocessing and radiomic feature extraction were done using ANTsPy and open-source software. A total of 210 features were extracted from post-contrast T1-weighted (T1w) and T2/FLAIR MRIs. Highly correlated features were removed. Univariate logistic regression was conducted on the remaining T1w and T2/FLAIR features as well as on clinical variables. Multivariate analysis was implemented with various classifiers (Random Forest, Ridge, Lasso, Support Vector Machine [SVM]) on the top-performing features found on univariate logistic regression. Models were assessed using cross-validation to select the best model by area under ROC curve (AUC). Specificity and sensitivity were calculated. On univariate analysis, the top 10 radiomics features consisted of 6 T1w features and 4 T2/FLAIR features (4 GLCM, 3 first order, 1 GLSZM, 1 GLRLM, and 1 shape feature). Age, gender, disease site, prior WBRT, prior fractionated SRS, planning tumor volume, brain-GTV V12 Gy, and immunotherapy before or after SRS were not predictive (AUC less than 62.0%) on univariate analysis compared to radiomic features. Multivariate analysis of top performing radiomic features on both intact and surgical cavities yielded an AUC of 72.0% (standard deviation [SD] ±8.8%). Multivariate analysis of top features on intact lesions alone improved the AUC to 80.5% (SD ±10.8%), with sensitivity of 77.8%, specificity of 72.4%, and positive likelihood ratio of 2.82 in differentiating radionecrosis from recurrence. Radiomics and machine learning tools may improve diagnostic ability of distinguishing radiation necrosis from tumor recurrence after SRS. Further work is needed to deploy this in a larger multi-institutional cohort and prospectively evaluate its efficacy as a decision-support tool to personalize care in patients with brain metastases.

A multi-institutional study of 1,111 men with 4K score, multiparametric magnetic resonance imaging, and prostate biopsy

ObjectiveProstate magnetic resonance imaging (MRI) and biomarkers are often used in conjunction to enhance the selection process for prostate biopsy. However, the optimal sequence of ordering these tests has not been established. A comprehensive evaluation was conducted on a large multi-institutional cohort of patients who underwent MRI, 4K score, and biopsy of the prostate to examine the impact of utilizing both tests vs. either test alone and to determine if the order in which these tests are administered affects the ability to detect clinically significant prostate cancer (csCaP). Methods and materialsWe evaluated men from 8 different institutions who were referred for prostate cancer evaluation and underwent MRI, 4K score test, and prostate biopsy. The primary outcome was the presence of csCaP, defined as grade group 2 or higher cancer on a biopsy of the prostate. We used logistic regression, calibration plots, and decision curve analysis to evaluate using a 4K score or MRI alone vs. both tests together for detecting csCaP. In addition, we evaluated several strategies using one or both tests for selecting men for biopsy and compared them based on the proportion of biopsies avoided and the csCaP's missed. ResultsAmong the 1,111 men who formed the final cohort, 553 (49.8%) had prostate cancer, and 353 (31.8%) had csCaP. We found that using MRI and 4K score together had better discrimination, calibration, and a higher clinical utility on decision curve analysis compared to using either test individually. Using both tests together resulted in fewer biopsies avoided and missed cancers compared to using either test alone. Strategies that sequence MRI and 4K score tests resulted in the largest biopsy reduction, with no appreciable difference between starting with an MRI vs. a biomarker. ConclusionsWe found that using both an MRI and 4K score together was superior to using either test alone but found no appreciable difference between starting with an MRI vs. starting with a 4K score. Prospective studies are needed to identify the best strategy to sequence MRI and biomarkers in the evaluation of csCaP.

MP09-01 DETECTION OF CLINICALLY SIGNIFICANT PROSTATE CANCER ON MRI: A COMPARISON OF AN ARTIFICIAL INTELLIGENCE MODEL VERSUS RADIOLOGISTS

You have accessJournal of UrologyCME1 Apr 2023MP09-01 DETECTION OF CLINICALLY SIGNIFICANT PROSTATE CANCER ON MRI: A COMPARISON OF AN ARTIFICIAL INTELLIGENCE MODEL VERSUS RADIOLOGISTS Simon John Christoph Soerensen, Richard E. Fan, Indrani Bhattacharya, David S. Lim, Sarir Ahmadi, Xinran Li, Sulaiman Vesal, Mirabela Rusu, and Geoffrey A. Sonn Simon John Christoph SoerensenSimon John Christoph Soerensen More articles by this author , Richard E. FanRichard E. Fan More articles by this author , Indrani BhattacharyaIndrani Bhattacharya More articles by this author , David S. LimDavid S. Lim More articles by this author , Sarir AhmadiSarir Ahmadi More articles by this author , Xinran LiXinran Li More articles by this author , Sulaiman VesalSulaiman Vesal More articles by this author , Mirabela RusuMirabela Rusu More articles by this author , and Geoffrey A. SonnGeoffrey A. Sonn More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003224.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Automated detection of prostate cancer on magnetic resonance imaging (MRI) may help target biopsies and avoid unnecessary biopsies of false-positive lesions. We sought to develop an artificial intelligence (AI) model to rapidly and accurately identify cancer foci on MRI and compare its performance against radiologists. METHODS: A total of 1504 subjects underwent multiparametric MRI at more than 30 institutions in the US, followed by MRI-ultrasound fusion biopsy at one institution. We used T2-weighted images (T2WI), apparent diffusion coefficient maps (ADC), and diffusion-weighted imaging (DWI) from 1404 cases to train an AI model. MRI lesions were initially identified and outlined by a radiologist using T2WIs, DWIs, ADC, and contrast enhanced images (DCE). Cancers were confirmed by biopsy. Only lesions containing Gleason 3+3 (≥ 40% cancer core length) or Gleason ≥3+4 (any amount) in at least one targeted biopsy core were considered for training and testing the model. All other MRI lesions were removed. Systematic cores with significant cancer were also included for model training. We tested the AI model on 100 independent cases and compared it against trained radiologists. We computed lesion-level AUC, sensitivity, specificity, and negative predictive value (NPV). RESULTS: AI and radiologists had similar performances across all metrics, and all differences were non-significant. The AI model had an AUC of 0.79±0.22, NPV of 0.66±0.26, sensitivity of 0.34±0.41, and specificity of 0.99±0.05. Radiologists had an AUC of 0.81±0.22, NPV of 0.69±0.28, sensitivity of 0.37±0.45, and specificity of 0.99±0.05. CONCLUSIONS: In this study, we trained and tested an AI model on a large and diverse multi-institutional cohort of MRIs. The model matched the performance of radiologist experts. In future work, we envision comparing model performance against radiologists at different skill levels and comparing radiologist + AI vs radiologist performance alone. Source of Funding: Departments of Radiology and Urology, Stanford University, National Cancer Institute of the National Institutes of Health (R37CA260346 to M.R), and the generous philanthropic support of our patients (G.S.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e103 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Simon John Christoph Soerensen More articles by this author Richard E. Fan More articles by this author Indrani Bhattacharya More articles by this author David S. Lim More articles by this author Sarir Ahmadi More articles by this author Xinran Li More articles by this author Sulaiman Vesal More articles by this author Mirabela Rusu More articles by this author Geoffrey A. Sonn More articles by this author Expand All Advertisement PDF downloadLoading ...

MP29-03 MULTI-INSTITUTIONAL ANALYSIS OF METASTASIS DIRECTED THERAPY WITH OR WITHOUT ANDROGEN DEPRIVATION THERAPY IN OLIGOMETASTATIC CASTRATION SENSITIVE PROSTATE CANCER

MP29-03 MULTI-INSTITUTIONAL ANALYSIS OF METASTASIS DIRECTED THERAPY WITH OR WITHOUT ANDROGEN DEPRIVATION THERAPY IN OLIGOMETASTATIC CASTRATION SENSITIVE PROSTATE CANCER

MP80-14 EXTRAPERITONEAL SINGLE-PORT ROBOTIC RADICAL PROSTATECTOMY IN OVER 700 PATIENTS: UPDATED MULTI-INSTITUTIONAL COHORT STUDY FROM THE SPARC COLLABORATION

You have accessJournal of UrologyCME1 Apr 2023MP80-14 EXTRAPERITONEAL SINGLE-PORT ROBOTIC RADICAL PROSTATECTOMY IN OVER 700 PATIENTS: UPDATED MULTI-INSTITUTIONAL COHORT STUDY FROM THE SPARC COLLABORATION Ethan Ferguson, Jennifer L. Nguyen, Roxana Ramos, Grace Chen, Kennedy Okhawere, Samantha Wilder, Ruth Sanchez De La Rosa, Jaya Chavali, Indu Saini, James Peabody, Ketan K. Badani, Craig Rogers, Jeffrey Nix, Jean Joseph, Michael Stifelman, Simone Crivellaro, Mutahar Ahmed, Moses Kim, and Jihad Kaouk Ethan FergusonEthan Ferguson More articles by this author , Jennifer L. NguyenJennifer L. Nguyen More articles by this author , Roxana RamosRoxana Ramos More articles by this author , Grace ChenGrace Chen More articles by this author , Kennedy OkhawereKennedy Okhawere More articles by this author , Samantha WilderSamantha Wilder More articles by this author , Ruth Sanchez De La RosaRuth Sanchez De La Rosa More articles by this author , Jaya ChavaliJaya Chavali More articles by this author , Indu SainiIndu Saini More articles by this author , James PeabodyJames Peabody More articles by this author , Ketan K. BadaniKetan K. Badani More articles by this author , Craig RogersCraig Rogers More articles by this author , Jeffrey NixJeffrey Nix More articles by this author , Jean JosephJean Joseph More articles by this author , Michael StifelmanMichael Stifelman More articles by this author , Simone CrivellaroSimone Crivellaro More articles by this author , Mutahar AhmedMutahar Ahmed More articles by this author , Moses KimMoses Kim More articles by this author , and Jihad KaoukJihad Kaouk More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003357.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: An extraperitoneal approach to single-port (SP) robot-assisted radical prostatectomy has been demonstrated with proposed benefits in decreased morbidity, single incision, and same-day discharge. We sought to determine the perioperative and early postoperative outcomes in a large, multi-institutional setting. METHODS: SP extraperitoneal radical prostatectomy was performed in 712 patients between February 2019 and October 2022. All procedures were performed by experienced robotic surgeons from eight tertiary medical centers. Data from baseline demographics, perioperative and early postoperative outcomes were collected prospectively and analyzed retrospectively RESULTS: All reported procedures were completed without open conversion, blood transfusions, or intraoperative complications. The median follow-up time was 11.7 months for the entire cohort. The median age, BMI and preoperative PSA were 64 years, 27.9kg/m2, and 6.4 ng/mL, respectively. About 30% of the patients had at least one previous abdominal surgery. On pathology, high risk disease was noted in 12% and lymph node involvement on final pathology was present in 5.8%. Extraprostatic extension was noted in 38% and positive surgical margins were present in 30.2% of cases. Lymphadenectomy was performed in 85% of patients and the median lymph node yield was 5 nodes. There were no intraoperative complications and inadvertent peritoneal entry with insufflation was rare (0.6%) and managed conservatively. Postoperative complications occurred in 11.8%. The median length of stay and foley catheter duration were 8 hours and 7 days, respectively. Postoperative recovery of continence was 69% at 3 months and 88% at 6 months. Recovery of potency was 35.6% at 6 months. CONCLUSIONS: Single-port extraperitoneal robotic radical prostatectomy is safe and feasible for management of clinically localized prostate cancer. Analysis from a large multi-institutional cohort shows promising single incision and short hospital length of stay without compromise in early functional or oncologic outcomes. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1157 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ethan Ferguson More articles by this author Jennifer L. Nguyen More articles by this author Roxana Ramos More articles by this author Grace Chen More articles by this author Kennedy Okhawere More articles by this author Samantha Wilder More articles by this author Ruth Sanchez De La Rosa More articles by this author Jaya Chavali More articles by this author Indu Saini More articles by this author James Peabody More articles by this author Ketan K. Badani More articles by this author Craig Rogers More articles by this author Jeffrey Nix More articles by this author Jean Joseph More articles by this author Michael Stifelman More articles by this author Simone Crivellaro More articles by this author Mutahar Ahmed More articles by this author Moses Kim More articles by this author Jihad Kaouk More articles by this author Expand All Advertisement PDF downloadLoading ...

Outcomes for patients with dementia undergoing emergency and elective colorectal surgery: A large multi-institutional comparative cohort study

BackgroundAlzheimer's Disease and Related Dementias (ADRD) may result in poor surgical outcomes. The current study aims to characterize the risk of ADRD on outcomes for patients undergoing colorectal surgery. MethodsColorectal surgery patients with and without ADRD from 2007 to 2017 were identified using electronic health record-linked Medicare claims data from two large health systems. Unadjusted and adjusted analyses were performed to evaluate postoperative outcomes. Results5926 patients (median age 74) underwent colorectal surgery of whom 4.8% (n = 285) had ADRD. ADRD patients were more likely to undergo emergent operations (27.7% vs. 13.6%, p < 0.001) and be discharged to a facility (49.8% vs 28.9%, p < 0.001). After multi-variable adjustment, ADRD patients were more likely to have complications (61.1% vs 48.3%, p < 0.001) and required longer hospitalization (7.1 vs 6.1 days, p = 0.001). ConclusionsThe diagnosis of ADRD is an independent risk factor for prolonged hospitalization and postoperative complications after colorectal surgery.

P53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study.

Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR]=2.18, 95% confidence interval [CI] 1.36-3.47, p=0.0011) and with CCC (HR=1.57, 95% CI 1.11-2.22, p=0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

Impact of an Expanded Definition of Family History on Outcomes of Active Surveillance for Prostate Cancer.

Despite family history being an established risk factor for prostate cancer, the role of a broader definition of family history inclusive of not just prostate cancer but other genetically related malignancies has not been investigated in the active surveillance population. Here, we evaluate the impact of an expanded definition of family history on active surveillance outcomes. Patients undergoing active surveillance for prostate cancer at Massachusetts General Hospital from 1997-2019 with detailed data available on family cancer history were identified. Primary outcome was biopsy progression-free survival, and secondary outcomes were treatment-free survival, adverse pathological features at prostatectomy, and biochemical recurrence after treatment. Statistical analyses were conducted using the Kaplan-Meier method and Cox regression. Among 855 evaluable patients, 300 (35.1%) patients had any family history of prostate cancer, and 95 (11.1%) had a family history of related malignancies suggestive of a hereditary cancer syndrome. Family history of prostate cancer alone was not associated with biopsy progression, whereas family history suggestive of a hereditary cancer syndrome was associated with a significantly increased risk of biopsy progression (HR 1.43, 95%CI 1.01-2.02), independent of other known clinicopathological risk factors in multivariable analysis. Similarly, family history suggestive of a hereditary cancer syndrome was associated with significantly lower treatment-free survival (HR 1.58, 95%CI 1.14-2.18) in multivariable analysis. No significant association was found between family history and adverse features on surgical pathology or biochemical recurrence. An expanded family history suggestive of a hereditary cancer syndrome is an independent predictor of biopsy progression during active surveillance. Men with such a family history may still be offered active surveillance but should be counseled regarding the higher risk of disease progression.

Racial disparities in the pharmacological treatment of insomnia: A time-to-event analysis using real-world data

ObjectiveExamine the association between race and time to pharmacologic treatment of insomnia in a large multi-institutional cohort. MethodsRetrospective analysis of electronic medical records from a regional health information exchange. Eligible patients included adults with at least one healthcare visit per year from 2010 to 2019, a new insomnia diagnosis code during the study period, and no prior insomnia diagnosis codes or medications. A Cox frailty model was used to examine the association between race and time to an insomnia medication after diagnosis. ResultsIn total, 9557 patients were analyzed, 7773 (81.3%) of whom where White, 1294 (13.5%) Black, 238 (2.5%) Other, and 252 (2.6%) unknown race. About 6.2% of Black and 8% of Other race patients received an order for a Food and Drug Administration-approved insomnia medication after diagnosis compared with 13.5% of White patients. Black patients were significantly less likely to have an order for a Food and Drug Administration-approved insomnia medication at all time points (adjusted hazard ratio [aHR] range: 0.37-0.73), and patients reporting Other race were less likely to have received an order at 2 (aHR 0.51, 95% confidence interval [CI] 0.28-0.94), 3 (aHR 0.33, 95% CI 0.13-0.79), and 4 years (aHR 0.21, 95% CI 0.06-0.71) of follow-up. Similar results were observed in a sensitivity analysis including off-label medications. ConclusionsPatients belonging to racial minority groups are less likely to be prescribed an insomnia medication than White patients after accounting for sociodemographic and clinical factors. Further research is needed to determine the extent to which patient preferences and physician perceptions affect these prescribing patterns and investigate potential disparities in nonpharmacologic treatment.

RBIO-06. CLINICAL AND MOLECULAR PREDICTORS OF RADIATION RESPONSIVENESS IN MENINGIOMAS: A MULTICENTER RETROSPECTIVE COHORT STUDY

Abstract BACKGROUND Aside from surgery, radiotherapy (RT) remains the only standard of care treatment for meningiomas. However, few studies have identified clinical/molecular biomarkers associated with responsiveness to RT and the optimal timing of RT after surgery remains controversial. We aimed to assess outcomes in a large multi-institutional cohort of RT-treated meningiomas to identify clinical factors and DNA methylation and RNA expression markers associated with progression-free survival (PFS) post-RT. METHODS Patients with intracranial meningiomas who underwent treatment with fractionated RT between 1997-2018 were included. DNA-methylation using the Illumina 850K EPICArray and RNA-sequencing were performed on tumours with sufficient tissue. Primary endpoints were radiographic recurrence of progression and time to progression from the time of RT completion. RESULTS 404 meningiomas were included for analysis. Of these, 167 (41.3%) recurred post-RT, usually within 5-years of RT. Previous RT to the meningioma, having a WHO grade 3 meningioma, and older age at diagnosis were independently associated with poorer PFS post-RT. Following propensity score matching, patients that received adjuvant RT had significantly better PFS post-RT compared to those that received salvage RT after recurrence (p=0.04). DNA methylation on 220 of these meningiomas segregated tumours into two distinct methylation groups (RT-resistant and RT-sensitive) based on unsupervised consensus clustering. DNA methylation were able to independently predict PFS post-RT better than all clinical factors. Differential RNA-expression analysis of these groups showed up-regulation of pathways involved in chromosome segregation and mitotic cell cycle and down-regulation of fatty acid metabolism pathways in RT-resistant meningiomas. CONCLUSION While there are a paucity of clinical factors that can reliably predict a meningioma’s response to RT, DNA methylation and RNA expression biomarkers may aid in differentiating RT-resistant meningiomas from RT-sensitive tumours. Patients that receive adjuvant RT may have prolonged PFS post-RT compared to those that receive salvage RT only after recurrence has already occurred.