Citations

Key Points Identifying ways to prevent AKI may reduce mortality further in the setting of intensive BP control. Creatinine-based ascertainment of AKI, enabled by electronic health record data, may be more sensitive and less biased than traditional serious adverse event adjudication. Background Adjudication of inpatient AKI in the Systolic Blood Pressure Intervention Trial (SPRINT) was based on billing codes and admission and discharge notes. The purpose of this study was to evaluate the effect of intensive versus standard BP control on creatinine-based inpatient and outpatient AKI, and whether AKI was associated with cardiovascular disease (CVD) and mortality. Methods We linked electronic health record (EHR) data from 47 clinic sites with trial data to enable creatinine-based adjudication of AKI. Cox regression was used to evaluate the effect of intensive BP control on the incidence of AKI, and the relationship between incident AKI and CVD and all-cause mortality. Results A total of 3644 participants had linked EHR data. A greater number of inpatient AKI events were identified using EHR data (187 on intensive versus 155 on standard treatment) as compared with serious adverse event (SAE) adjudication in the trial (95 on intensive versus 61 on standard treatment). Intensive treatment increased risk for SPRINT-adjudicated inpatient AKI (HR, 1.51; 95% CI, 1.09 to 2.08) and for creatinine-based outpatient AKI (HR, 1.40; 95% CI, 1.15 to 1.70), but not for creatinine-based inpatient AKI (HR, 1.20; 95% CI, 0.97 to 1.48). Irrespective of the definition (SAE or creatinine based), AKI was associated with increased risk for all-cause mortality, but only creatinine-based inpatient AKI was associated with increased risk for CVD. Conclusions Creatinine-based ascertainment of AKI, enabled by EHR data, may be more sensitive and less biased than traditional SAE adjudication. Identifying ways to prevent AKI may reduce mortality further in the setting of intensive BP control.

Abstract This study describes a generalized cross‐patient seizure‐forecasting approach using recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings. Data from six patients diagnosed with refractory epilepsy and monitored with an sqEEG device were used to develop a generalized algorithm for seizure forecasting using long short‐term memory (LSTM) deep‐learning classifiers. Electrographic seizures were identified by a board‐certified epileptologist. One‐minute data segments were labeled as preictal or interictal based on their relationship to confirmed seizures. Data were separated into training and testing data sets, and to compensate for the unbalanced data ratio in training, noise‐added copies of preictal data segments were generated to expand the training data set. The mean and standard deviation (SD) of the training data were used to normalize all data, preserving the pseudo‐prospective nature of the analysis. Different architecture classifiers were trained and tested using a leave‐one‐patient‐out cross‐validation method, and the area under the receiver‐operating characteristic (ROC) curve (AUC) was used to evaluate the performance classifiers. The importance of each input signal was evaluated using a leave‐one‐signal‐out method with repeated training and testing for each classifier. Cross‐patient classifiers achieved performance significantly better than chance in four of the six patients and an overall mean AUC of 0.602 ± 0.126 (mean ± SD). A time in warning of 37.386% ± 5.006% (mean ± std) and sensitivity of 0.691 ± 0.068 (mean ± std) were observed for patients with better than chance results. Analysis of input channels showed a significant contribution ( p < .05) by the Fourier transform of signals channels to overall classifier performance. The relative contribution of input signals varied among patients and architectures, suggesting that the inclusion of all signals contributes to robustness in a cross‐patient classifier. These early results show that it is possible to forecast seizures training with data from different patients using two‐channel ultra‐long‐term sqEEG.

Abstract Geriatric assessment (GA) predicts survival among older adults with acute myeloid leukemia (AML) treated intensively. We evaluated the predictive utility of GA among older adults treated with low-intensity therapy on a multisite trial. We conducted a companion study (CALGB 361101) to a randomized phase 2 trial (CALGB 11002) of adults ≥60 years and considered “unfit” for intensive therapy, testing the efficacy of adding bortezomib to decitabine therapy. On 361101, GA and quality of life (QOL) assessment was administered prior to treatment and every other subsequent cycle. Relationships between baseline GA and QOL measures with survival were evaluated using Kaplan-Meier estimation and Cox proportional hazards models. One-hundred sixty-five patients enrolled in CALGB 11002, and 96 (52%) of them also enrolled in 361101 (median age, 73.9 years). Among participants, 85.4% completed ≥1 baseline assessment. In multivariate analyses, greater comorbidity (hematopoietic cell transplantation-specific comorbidity index &gt;3), worse cognition (Blessed Orientation-Memory-Concentration score &gt;4), and lower European Organization for Research and Treatment of Cancer global QOL scores at baseline were significantly associated with shorter overall survival (P &lt; .05 each) after adjustment for Karnofsky Performance Status, age, and treatment arm. Dependence in instrumental activities of daily living and cognitive impairment were associated with 6-month mortality (hazard ratio [HR], 3.5; confidence interval [CI], 1.2-10.4; and HR, 3.1; CI, 1.1-8.6, respectively). GA measures evaluating comorbidity, cognition, and self-reported function were associated with survival and represent candidate measures for screening older adults planned to receive lower-intensity AML therapies. This trial was registered at www.clinicaltrials.gov as #NCT01420926 (CALGB 11002).

Abstract Objective One of the most disabling aspects of living with chronic epilepsy is the unpredictability of seizures. Cumulative research in the past decades has advanced our understanding of the dynamics of seizure risk. Technological advances have recently made it possible to record pertinent biological signals, including electroencephalogram (EEG), continuously. We aimed to assess whether patient‐specific seizure forecasting is possible using remote, minimally invasive ultra‐long‐term subcutaneous EEG. Methods We analyzed a two‐center cohort of ultra‐long‐term subcutaneous EEG recordings, including six patients with drug‐resistant focal epilepsy monitored for 46–230 days with median 18 h/day of recorded data, totaling >11 000 h of EEG. Total electrographic seizures identified by visual review ranged from 12 to 36 per patient. Three candidate subject‐specific long short‐term memory network deep learning classifiers were trained offline and pseudoprospectively on preictal (1 h before) and interictal (>1 day from seizures) EEG segments. Performance was assessed relative to a random predictor. Periodicity of the final forecasts was also investigated with autocorrelation. Results Depending on each architecture, significant forecasting performance was achieved in three to five of six patients, with overall mean area under the receiver operating characteristic curve of .65–.74. Significant forecasts showed sensitivity ranging from 64% to 80% and time in warning from 10.9% to 44.4%. Overall, the output of the forecasts closely followed patient‐specific circadian patterns of seizure occurrence. Significance This study demonstrates proof‐of‐principle for the possibility of subject‐specific seizure forecasting using a minimally invasive subcutaneous EEG device capable of ultra‐long‐term at‐home recordings. These results are encouraging for the development of a prospective seizure forecasting trial with minimally invasive EEG.

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Abstract Donation after circulatory death (DCD) liver transplantation (LT) outcomes have been attributed to multiple variables, including procurement surgeon recovery techniques. Outcomes of 196 DCD LTs at Mayo Clinic Arizona were analyzed based on graft recovery by a surgeon from our center (transplant procurement team [TPT]) versus a local procurement surgeon (non‐TPT [NTPT]). A standard recovery technique was used for all TPT livers. The recovery technique used by the NTPT was left to the discretion of that surgeon. A total of 129 (65.8%) grafts were recovered by our TPT, 67 (34.2%) by the NTPT. Recipient age (p = 0.43), Model for End‐Stage Liver Disease score (median 17 vs. 18; p = 0.22), and donor warm ischemia time (median 21.0 vs. 21.5; p = 0.86) were similar between the TPT and NTPT groups. NTPT livers had longer cold ischemia times (6.5 vs. 5.0 median hours; p < 0.001). Early allograft dysfunction (80.6% vs. 76.1%; p = 0.42) and primary nonfunction (0.8% vs. 0.0%; p = 0.47) were similar. Ischemic cholangiopathy (IC) treated with endoscopy occurred in 18.6% and 11.9% of TPT and NTPT grafts (p = 0.23). At last follow‐up, approximately half of those requiring endoscopy were undergoing a stent‐free trial (58.3% TPT; 50.0% NTPT; p = 0.68). IC requiring re‐LT in the first year occurred in 0.8% (n = 1) of TPT and 3.0% (n = 2) of NTPT grafts (p = 0.23). There were no differences in patient (hazard ratio [HR], 1.95; 95% confidence interval [CI], 0.76–5.03; p = 0.23) or graft (HR, 1.99; 95% CI, 0.98–4.09; p = 0.10) survival rates. Graft survival at 1 year was 91.5% for TPT grafts and 95.5% for NTPT grafts. Excellent outcomes can be achieved using NTPT for the recovery of DCD livers. There may be an opportunity to expand the use of DCD livers in the United States by increasing the use of NTPT.

Approximately one‐third of patients with metastatic castration‐resistant prostate cancer (CRPC) exhibited primary abiraterone resistance. To identify alternative treatment for abiraterone nonresponders, we performed drug discovery analyses using the L1000 database using differentially expressed genes identified in tumor biopsies and patient‐derived xenograft (PDX) tumors between abiraterone responders and nonresponders enrolled in PROMOTE trial. This approach identified 3 drugs, including topoisomerase II (TOP2) inhibitor mitoxantrone, CDK4/6 inhibitor palbociclib, and pan‐CDK inhibitor PHA‐793887. These drugs significantly suppressed the growth of abiraterone‐resistant cell lines and PDX models. Moreover, we identified 11 genes targeted by all 3 drugs that were associated with worse outcomes in both the PROMOTE and Stand Up To Cancer cohorts. This 11‐gene panel might also function as biomarkers to select the 3 alternative therapies for this subgroup of patients with CRPC, warranting further clinical investigation.

AbstractBackgroundHospitalization in older age is associated with accelerated cognitive decline, typically preceded by neuropathologic changes. We assess the association between indication for hospitalization and brain neurodegeneration.MethodsIncluded were participants from the Mayo Clinic Study of Aging, a population-based longitudinal study, with ≥1 brain imaging available in those older than 60 years of age between 2004 and 2017. Primary analyses used linear mixed-effects models to assess association of hospitalization with changes in longitudinal trajectory of cortical thinning, amyloid accumulation, and white matter hyperintensities (WMH). Additional analyses were performed with imaging outcomes dichotomized (normal vs abnormal) using Cox proportional hazards regression.ResultsOf 2 480 participants, 1 966 had no hospitalization and 514 had ≥1 admission. Hospitalization was associated with accelerated cortical thinning (annual slope change −0.003 mm [95% confidence interval (CI) −0.005 to −0.001], p = .002), but not amyloid accumulation (0.003 [95% CI −0.001 to 0.006], p = .107), or WMH increase (0.011 cm3 [95% CI −0.001 to 0.023], p = .062). Interaction analyses assessing whether trajectory changes are dependent on admission type (medical vs surgical) found interactions for all outcomes. While surgical hospitalizations were not, medical hospitalizations were associated with accelerated cortical thinning (−0.004 mm [95% CI −0.008 to −0.001, p = .014); amyloid accumulation (0.010, [95% CI 0.002 to 0.017, p = .011), and WMH increase (0.035 cm3 [95% CI 0.012 to 0.058, p = .006). Hospitalization was not associated with developing abnormal cortical thinning (p = .407), amyloid accumulation (p = .596), or WMH/infarctions score (p = .565).ConclusionsMedical hospitalizations were associated with accelerated cortical thinning, amyloid accumulation, and WMH increases. These changes were modest and did not translate to increased risk for crossing the abnormality threshold.

Conventional imaging has been the standard imaging modality for assessing prostate cancer recurrence and is utilized to determine treatment response to therapy. Molecular imaging with PSMA PET–CT has proven to be more accurate, sensitive, and specific at identifying pelvic or distant metastatic disease, resulting in earlier diagnosis of advanced disease. Since advanced disease may not be seen on conventional imaging, due to its lower sensitivity, but can be identified by molecular imaging, this reveals that metastatic prostate cancer occurs on a continuum from negative PSMA PET–CT and negative conventional imaging to positive PSMA PET–CT and positive conventional imaging. Understanding this continuum, the accuracy of these modalities, and treatment related outcomes based on imaging, will allow the clinician to counsel patients on management. This review will highlight the differences in conventional and molecular imaging in prostate cancer and how PSMA PET–CT can be used for the management of prostate cancer patients in different clinical scenarios, while providing cautionary notes for overtreatment.

176 Background: Despite androgen deprivation therapy, prostate cancer will develop resistance known as castrate resistant prostate cancer (CRPC). Androgen signaling is associated with pathways that influence cell proliferation and survival via cell cycle regulation. AR signaling results in inactivation of Rb tumor suppressor by way of AKT and reduction in intrinsic CDK4/6 inhibitors. Since PTEN loss is found in 40% of mCRPC and AKT pathway is a mechanism of CDK4/6 inhibitor resistance, we hypothesize adding an AKT inhibitor to a CDK4/6 inhibitor will have synergistic activity while delaying CDK4/6 inhibitor resistance. Preclinical xenografts have been shown to recapitulate patient response, therefore, can be used to guide clinical trials using novel combinations. Methods: We have established patient derived tumor xenograft models (GUR-017M, TMA-027 and PRJ-88T) from patients with mCRPC with each having a unique genomic alteration profile. In the clinical setting, GUR-017M was resistant to abiraterone, enzalutamide, cabazitaxel and had exposure to docetaxel. TMA-027 and PRJ-88T were resistant to enzalutamide. We combined a CDK4/6 inhibitor with an AKT inhibitor and treated each of these patient tumors in NOD-SCID mice for a total duration of 40 days. Mice were implanted and separated into 4 groups (placebo, CDK4/6 inhibitor, AKT inhibitor and CDK4/6 + AKT inhibitor) with 10-13 mice in each group. Tumor volumes were measured twice a week. For GUR-017M, abemaciclib (50 mg/kg) was combined with MK2206 (120 mg/kg) and was compared to each placebo and each single agent alone. For TMA-027, palbociclib (50 mg/kg) was combined with ipatasertib (50 mg/kg). After 40 days, tumors were harvested for immunohistochemistry analysis. PRJ-88T was grown as 3D spheroids in ultra-low attachment plates and treated with palbociclib + ipatasertib (10 uM-100uM) to evaluate for synergy. Results: GUR-017M and TMA-027 showed significant delayed tumor growth compared to placebo or either single agent alone. In the GUR-017M group, the final mean tumor volume for the combination group was 149 mm3, compared to 377 mm3 (abemaciclib), 358 mm3 (MK2206) and 527 mm3 placebo group, representing a percent decrease compared to control by 72%, 29%, and 32%, respectively. For TMA-027, the final mean tumor volume for the combination group was 102 mm3, compared to 259 mm3 (palbociclib), 416 mm3 (ipatasertib), and 402 mm3 placebo group, representing a percent decrease compared to control by 75%, 36%, and 4%, respectively. PRJ-88T 3D spheroids showed synergy with palbociclib + ipatasertib. In vivo experiments using PRJ-88T are in progress. Conclusions: The preclinical results show combining CDK4/6 inhibitors with AKT inhibitors is a promising treatment strategy and provides the basis for a clinical trial in patients with mCRPC.