Thiel, David D.

Purpose: Planning for robotic-assisted partial nephrectomy requires surgeons to review two-dimensional CT or MRI scans to understand three-dimensional (3D) anatomy. We sought to determine the drivers of improvements in key surgical outcomes when using patient-specific 3D virtual reality (VR) models for operative planning. Materials and Methods: A multicenter, randomized, single-blind clinical trial was conducted from January 2019 to December 2020. Patients undergoing robotic-assisted partial nephrectomy were randomly assigned to a control group undergoing usual preoperative planning with CT and/or MRI only or to an intervention group where imaging was supplemented with a 3D VR model. A survey was administered to surgeons after review of the model and after the operation. The primary outcome measure was operative time, and secondary outcomes included clamp time, estimated blood loss, and hospital stay. Results: Qualitative data analysis of 44 cases in the treatment arm was performed. Surgeons reported seeing anatomic details much better in the 3D model 55% of the time and modified their preoperative plan based on anatomy shown in the 3D model 30% of the time. Cases in which the surgeon reported modifying their preoperative plan after viewing the model (30%) had significantly lower operative time, blood loss, and clamp time (P < .05). In addition, increased surgeon confidence after viewing the model significantly lowered operative time, estimated blood loss, and clamp time (P < .05). Conclusions: We demonstrate that surgeons who use 3D VR models for robotic kidney surgery are able to visualize anatomic structures and select the optimal approach, leading to better surgical outcomes. Trial Registration: ClinicalTrials.gov identifier NCT0333434.

PURPOSE A multi-cancer detection test using a targeted methylation assay and machine learning classifiers was validated and optimized for screening in prospective, case-controlled Circulating Cell-free Genome Atlas (ClinicalTrials.gov identifier: NCT02889978 ) substudy 3. Here, we report test performance in a subgroup of participants with symptoms suspicious for cancer to assess the test's ability to potentially facilitate efficient diagnostic evaluation in symptomatic individuals. METHODS We evaluated test performance (sensitivity, specificity, and accuracy of cancer signal origin [CSO] prediction accuracy) in participants with clinically presenting cancers (CPCs) and noncancer with underlying medical conditions and among two subgroups (65 years and older and GI cancers). Overall survival (OS) of participants who had a cancer signal detected/not detected was compared with SEER-based expected survival. RESULTS A total of 2,036 cancer and 1,472 noncancer participants were included. Specificity was high in all noncancer participants (99.5% [95% CI, 98.4 to 99.8]). In participants with CPCs, the overall sensitivity was 64.3% (95% CI, 62.2 to 66.4) and the overall accuracy of CSO prediction in true positives was 90.3%. For GI cancers, the overall sensitivity was 84.1% (95% CI, 80.6 to 87.1). In participants 65 years and older, test performance was similar to that of all participants. Individuals with cancers not detected had a significantly better OS than that expected from SEER ( P < .01). CONCLUSION This test detected a cancer signal with high specificity and CSO prediction accuracy and moderate sensitivity in symptomatic individuals, with especially high performance in participants with GI cancers. The survival analysis implied that the cancers not detected were less clinically aggressive than cancers detected by the test, providing prognostic insights to physicians. This multi-cancer detection test could facilitate efficient workup and stratify cancer risk in symptomatic individuals.

ObjectiveTo validate a new baseline estimated glomerular filtration rate (NB‐GFR) formula in a cohort of robotic‐assisted partial nephrectomies (RAPN).MethodsNB‐GFR = 35 + preoperative GFR (× 0.65) – 18 (if radical nephrectomy) – age (× 0.25) + 3 (if tumor size >7 cm) – 2 (if diabetes). NB‐GFR was calculated in 464 consecutive RAPN from a single surgeon cohort. 143 patients were excluded secondary to insufficient eGFR follow up. We analyzed NB‐GFR accuracy utilizing the last observed eGFR 3–12 months post RAPN. Categorical variables were summarized with the frequency and percentage of patients. Numerical variables were summarized with the median, 25th percentile, and 75th percentile.ResultsThe mean difference between observed and predicted NB‐GFR was 4.6 ml/min/1.73m2 (95% CI −6.9 to 16.1 ml/min/1.73m2). There was a pattern of higher observed NB‐GFRs being underestimated by the NB‐GFR equation while lower observed NB‐GFRs were overestimated by the NB‐GFR equation. The NB‐GFR formula had a high level of accuracy with 98.8% of predicted NB‐GFRs falling within 30% of the observed NB‐GFR (95% CI 86.8% to 99.5%). The median and interquartile range of the difference between observed and predicted NB‐GFR was 3.9 ml/min/1.73m2 (IQR 0.7 to 8.2 ml/min/1.73m2). The sensitivity, specificity, positive predictive value, and negative predictive value for the ability of predicted NB‐GFR to identify those with an observed NB‐GFR <60 ml/min/1.73m2 after RAPN was 98%, 92%, 88%, and 99%, respectively.ConclusionThe NB‐GFR equation developed with partial and radical nephrectomy cohorts is accurate in predicting post‐operative eGFR 3–12 months following RAPN.

Abstract Objective: To analyze operating room (OR) efficiency by evaluating fixed and variable OR times for open (OPN) and robotic-assisted partial nephrectomies (RAPN).Methods: We analyzed consecutive OPN and RAPN performed by one surgeon over a 24-month period. All patients were placed in the lateral decubitus position and secured with a beanbag regardless of approach. Fixed (nonprocedural) OR times were prospectively collected and defined as: in room to anesthesia release time (IRAT), anesthesia release to cut time (ARCT), and close to wheels out time (CTWO). Variable OR time was procedural cut to close time (CTCT). Comparison of fixed and variable OR time points between OPN and RAPN were performed using the Wilcoxon rank sum test. Results: 146 RAPN and 31 OPN were evaluated from 2019-2020. Median IRAT was similar for RAPN versus OPN [20 min (IQR: 16-25) vs. 20 min (IQR: 16-26), P=0.57]. Median ARCT was longer for RAPN than it was for OPN [40 min (IQR: 36-46) vs. 34 min (IQR: 30-39), P<0.001]. Median CTWO was similar for OPN (12 min, IQR: 9-14) and RAPN (11 min, IQR: 7-15) (P=0.89). Median CTCT was longer for RAPN (202 min, IQR: 170-236) compared to OPN (164 min, IQR: 154-184) (P<0.001).Conclusions: In a single surgeon partial nephrectomy series with the same patient positioning, utilization of robotic technology was associated with longer surgeon operating time as well as less efficient fixed OR times, specifically ARCT.

Objective: To evaluate the association between preoperative statin use with changes in estimated glomerular filtration rate (eGFR) after robot-assisted partial nephrectomy (RAPN). Methods: Three hundred eighty-nine consecutive patients undergoing RAPN were evaluated. Associations of preoperative statin use with change in eGFR from pre-RAPN to postoperative day 1 (POD1), 1, 6, and 12 months after RAPN were evaluated using longitudinal mixed-effects regression models with random patient-specific intercepts and slopes while accounting for imbalance of preoperative patient and tumor characteristics between groups with stabilized inverse propensity score weighting. Postoperative eGFR change from baseline was measured as total change, maintaining eGFR within 10% of baseline, and as going from eGFR >60 mL/min/1.73 m 2 to <60 mL/min/1.73 m 2 . Results: One hundred sixty-seven (43.0%) of 389 patients were on statin therapy preoperatively. Statin patients were older (66 vs 58 years) and had higher rates of comorbidities, including diabetes mellitus (31.7% vs 14.9%) and hypertension (82.6% vs 45%). Statin patients tended to have lower preoperative eGFR (mean ± standard deviation, 71.1 ± 17.6 vs 77.4 ± 19.4 mL/min/1.73 m 2 ). There was no evidence of an association of preoperative statin use with changes in eGFR at any time point after RAPN ( p = 0.66). Conclusion: Patients on preoperative statins undergoing RAPN had lower eGFR preoperatively compared with those not taking those medications. There was no evidence of an association between preoperative statin use and change in post-RAPN eGFR in the immediate postoperative period or at 1 year after surgery.

Abstract Introduction: A test that detects cancer signal across multiple cancer types and predicts signal (tissue) origin (SO) could aid in more efficient diagnostic workup and shorten time to cancer diagnosis in individuals with signs and symptoms.Methods: The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, longitudinal, multicenter, case-control study to develop and validate a multi-cancer detection test. The 2nd CCGA substudy utilized a targeted methylation-based cell-free DNA assay and machine learning algorithm and included assessment of test performance (sensitivity and SO prediction accuracy) in a subgroup of participants with clinically presenting cancers (CPCs) that were undiagnosed prior to blood draw. Specificity was assessed in the noncancer group and subgroups with confounding (nonmalignant) conditions (CCs; eg, cirrhosis) and noncancer participants enrolled in hematology clinics (HCs).Results: Specificity was 99.5% (95% confidence interval: 98.2-99.9%; 396/398), 93.8% (71.7-99.7%; 15/16), and 99.3% (96.0-100.0%; 136/137) for the noncancer group, CCs subgroup, and HCs subgroup, respectively. Overall sensitivity among those with CPCs was 66.4% (62.2-70.3%; 344/518). Sensitivity of cancer signal detection increased with increasing clinical stage (Table). SO prediction accuracy was 91.7% (88.3-94.3%; 300/327) among CPC participants with cancers detected, excluding those with multiple or unknown primaries. The test demonstrated prognostic value as detected cancer participants had worse survival probability than those not detected. Conclusions: This multi-cancer detection test detected cancer signals and predicted SO in individuals with CPCs with high specificity. These findings support further clinical development of this multi-cancer detection test that could accelerate the diagnostic resolution of symptomatic cancers. Table. Sensitivity by Clinical Stage Across Cancer Type in Clinically Presenting CancersClinical StagePositive Test/Total Cancer; Sensitivity (95% CI)All*344/518; 66.4% (62.2-70.3%)I33/122; 27.0% (20.0-35.5%)II60/102; 58.8% (49.1-67.9%)III103/121; 85.1% (77.7-90.4%)IV136/147; 92.5% (87.1-95.8%)Not expected to be staged9/21; 42.9% (24.5-63.5%)Non-informative2/4; 50.0% (15.0-85.0%)CI, confidence interval.*One participant who had a positive test result had multiple primaries with clinical stage I and not-expected-to-be-staged. Citation Format: Alan H. Bryce, Minetta C. Liu, Michael V. Seiden, David D. Thiel, Donald Richards, Carlos Becerra, Kathryn N. Kurtzman, Xiaoji Chen, Tony Wu, Quan Zhang, Jingjing Gao, Nan Zhang, Earl Hubbell, Arash Jamshidi, Eric T. Fung, Eric A. Klein. Performance of a cell-free DNA-based multi-cancer detection test as a tool for diagnostic resolution of symptomatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB058.

Abstract Non‐small cell lung cancer patients with anaplastic lymphoma kinase or c‐ros oncogene 1 mutations who are treated with the tyrosine kinase inhibitor crizotinib rarely develop crizotinib‐associated renal cysts (CARCs). Here, we present a case report and review of the literature supporting the hypothesis that CARCs may correlate positively with progression‐free survival.

Purpose: To investigate the potential for decreasing radiation dose when utilizing a third-generation vs second-generation dual-source dual-energy CT (dsDECT) scanner, while maintaining diagnostic image quality and acceptable image noise. Materials and Methods : Retrospective analysis of patients who underwent dsDECT for clinical suspicion of urolithiasis from October 2, 2017, to September 5, 2018. Patient demographics, body mass index, abdominal diameter, scanning parameters, and CT dose index volume (CTDIvol) were recorded. Image quality was assessed by measuring the attenuation and standard deviation (SD) regions of interest in the aorta and in the bladder. Image noise was determined by averaging the SD at both levels. Patients were excluded if they had not undergone both third- and second-generation dual-energy CT (DECT), time between DECT was more than 2 years, or scan parameters were outside the standard protocol. Results: A total of 117 patients met the inclusion criteria. Examinations performed on a third-generation DECT had an average CTDIvol 12.3 mGy, while examinations performed on a second-generation DECT had an average CTDIvol 13.3 mGy ( p < 0.001). Average image noise was significantly lower for the third-generation DECT (SD = 10.3) compared with the second-generation DECT (SD = 13.9) ( p < 0.001). Conclusions: The third-generation dsDECT scanners can simultaneously decrease patient radiation dose and decrease image noise compared with second-generation DECT. These reductions in radiation exposure can be particularly important in patients with urinary stone disease who often require repeated imaging to evaluate for stone development and recurrence as well as treatment assessment.