QC_SANE: Robust Control in DRL Using Quantile Critic With Spiking Actor and Normalized Ensemble.

Recently introduced deep reinforcement learning (DRL) techniques in discrete-time have resulted in significant advances in online games, robotics, and so on. Inspired from recent developments, we have proposed an approach referred to as Quantile Critic with Spiking Actor and Normalized Ensemble (QC_SANE) for continuous control problems, which uses quantile loss to train critic and a spiking neural network (NN) to train an ensemble of actors. The NN does an internal normalization using a scaled exponential linear unit (SELU) activation function and ensures robustness. The empirical study on multijoint dynamics with contact (MuJoCo)-based environments shows improved training and test results than the state-of-the-art approach: population coded spiking actor network (PopSAN).

Machine Learning approach to Predict net radiation over crop surfaces from global solar radiation and canopy temperature data.

As the ground-based instruments for measuring net radiation are costly and need to be handled skillfully, the net radiation data at spatial and temporal scales over Indian subcontinent are scanty. Sometimes, it is necessary to use other meteorological parameters to estimate the value of net radiation, although the prediction may vary based on season, ground cover and estimation method. In this context, artificial intelligence can be used as a powerful tool for predicting the data considering past observed data. This paper proposes a novel method to predict the net radiation for five crop surfaces using global solar radiation and canopy temperature. This contribution includes the generation of real-time data for five crops grown in West Bengal state of India. After manual analysis and data preprocessing, data normalization has been done before applying machine learning approaches for training a robust model. We have presented the comparison in various machine learning algorithm such as ridge and spline regression, random forest, ensemble and deep neural networks. The result shows that the gradient boosting regression and ridge regression are outperforming other ML approaches. The estimated predictors enable to reduce the number of resources in terms of time, cost and manpower for proper net radiation estimation. Thus, the problem of predicting net radiation over various crop surfaces can be sorted out through ML algorithm.

Oncogene-specific differences in tumor mutational burden, PD-L1 expression, and outcomes from immunotherapy in non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) patients bearing targetable oncogene alterations typically derive limited benefit from immune checkpoint blockade (ICB), which has been attributed to low tumor mutation burden (TMB) and/or PD-L1 levels. We investigated oncogene-specific differences in these markers and clinical outcome. METHODS: Three cohorts of NSCLC patients with oncogene alterations (n=4189 total) were analyzed. Two clinical cohorts of advanced NSCLC patients treated with ICB monotherapy [MD Anderson (MDACC; n=172) and Flatiron Health-Foundation Medicine Clinico-Genomic Database (CGDB; n=894 patients)] were analyzed for clinical outcome. The FMI biomarker cohort (n=4017) was used to assess the association of oncogene alterations with TMB and PD-L1 expression. RESULTS: High PD-L1 expression (PD-L1 ≥50%) rate was 19%-20% in classic EGFR, EGFR exon 20 and HER2-mutant tumors, and 34%-55% in tumors with ALK, BRAF V600E, ROS1, RET, or MET alterations. Compared with KRAS-mutant tumors, BRAF non-V600E group had higher TMB (9.6 vs KRAS 7.8 mutations/Mb, p=0.003), while all other oncogene groups had lower TMB (p<0.001). In the two clinical cohorts treated with ICB, molecular groups with EGFR, HER2, ALK, ROS1, RET, or MET alterations had short progression-free survival (PFS; 1.8-3.7 months), while BRAF V600E group was associated with greater clinical benefit from ICB (CGDB cohort: PFS 9.8 months vs KRAS 3.7 months, HR 0.66, p=0.099; MDACC cohort: response rate 62% vs KRAS 24%; PFS 7.4 vs KRAS 2.8 months, HR 0.36, p=0.026). KRAS G12C and non-G12C subgroups had similar clinical benefit from ICB in both cohorts. In a multivariable analysis, BRAF V600E mutation (HR 0.58, p=0.041), PD-L1 expression (HR 0.57, p=0.022), and high TMB (HR 0.66, p<0.001) were associated with longer PFS. CONCLUSIONS: High TMB and PD-L1 expression are predictive for benefit from ICB treatment in oncogene-driven NSCLCs. NSCLC harboring BRAF mutations demonstrated superior benefit from ICB that may be attributed to higher TMB and higher PD-L1 expression in these tumors. Meanwhile EGFR and HER2 mutations and ALK, ROS1, RET, and MET fusions define NSCLC subsets with minimal benefit from ICB despite high PD-L1 expression in NSCLC harboring oncogene fusions. These findings indicate a TMB/PD-L1-independent impact on sensitivity to ICB for certain oncogene alterations.

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non-small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. SIGNIFICANCE: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected "Goldilocks" relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development.This article is highlighted in the In This Issue feature, p. 211.

Prevalence of High Tumor Mutational Burden and Association With Survival in Patients With Less Common Solid Tumors.

Importance: Tumor mutational burden (TMB) is a potential biomarker associated with response to immune checkpoint inhibitor therapies. The prognostic value associated with TMB in the absence of immunotherapy is uncertain. Objective: To assess the prevalence of high TMB (TMB-H) and its association with overall survival (OS) among patients not treated with immunotherapy with the same 10 tumor types from the KEYNOTE-158 study. Design, Setting, and Participants: This retrospective cohort study evaluated the prognostic value of TMB-H, assessed by Foundation Medicine (FMI) and defined as at least 10 mutations/megabase (mut/Mb) in the absence of immunotherapy. Data were sourced from the deidentified Flatiron Health-FMI clinicogenomic database collected up to July 31, 2018. Eligible patients were aged 18 years or older with any of the following solid cancer types: anal, biliary, endometrial, cervical, vulvar, small cell lung, thyroid, salivary gland, mesothelioma, or neuroendocrine tumor. Patients with microsatellite instability-high tumors were excluded from primary analysis. For OS analysis, patients were excluded if immunotherapy started on the FMI report date or earlier or if patients died before January 1, 2012, and patients were censored if immunotherapy was started later than the FMI report date. Data were analyzed from November 2018 to February 2019. Main Outcomes and Measures: Overall survival was analyzed using the Kaplan-Meier method and Cox proportional hazards model, adjusting for age, sex, cancer types, practice type, and albumin level. Results: Of 2589 eligible patients, 1671 (64.5%) were women, and the mean (SD) age was 63.7 (11.7) years. Median (interquartile range) TMB was 2.6 (1.7-6.1) mut/Mb, and 332 patients (12.8%) had TMB-H (≥10 mut/Mb). Prevalence of TMB-H was highest among patients with small cell lung cancer (40.0%; 95% CI, 34.7%-45.6%) and neuroendocrine tumor (29.3%; 95% CI, 22.8%-36.6%) and lowest was among patients with mesothelioma (1.2%; 95% CI, 0.3%-4.4%) and thyroid cancer (2.7%; 95% CI, 1.2%-5.7%). Adjusted hazard ratio for OS of patients not treated with immunotherapy with TMB-H vs those without TMB-H was 0.94 (95% CI, 0.77-1.13). Comparable results were observed when including patients with high microsatellite instability tumors and calculating OS from first observed antineoplastic treatment date. Conclusions and Relevance: These findings suggest that prevalence of TMB-H varies widely depending on tumor type and TMB-H does not appear to be a factor associated with OS among patients across these cancer types treated in the absence of immunotherapy.

Retrospective analysis of real-world data to determine clinical outcomes of patients with advanced non-small cell lung cancer following cell-free circulating tumor DNA genomic profiling.

OBJECTIVES: Liquid biopsy and comprehensive genomic profiling (CGP) of circulating tumor DNA (ctDNA) are increasingly used for detection of targetable genomic alterations (GA) in non-small cell lung cancer (NSCLC). To examine the clinical outcomes for patients following CGP using liquid biopsy versus tissue biopsy, receipt of matched targeted therapy post-CGP and associated outcomes were evaluated in the real-world setting. METHODS: 6491 patients with NSCLC and liquid biopsy (N = 937 tests) and/or tissue (N = 5582 tests) CGP were included in a de-identified commercial clinico-genomic database. Targetable GAs included National Comprehensive Cancer Network NSCLC guideline biomarkers. Clinical characteristics, real-world progression, and real-world response (rwR) were obtained via technology-enabled abstraction of clinician notes and radiology/pathology reports. RESULTS: At the time of liquid biopsy CGP, 53% (496/937) of patients were documented to have received ≥1 line of prior therapy (tissue CGP: 13%, 735/5582). 90% (832/928) of liquid biopsy cases had evidence of ctDNA. A targetable GA was detected in 20% (188/937) of liquid biopsy and 22% (1215/5582) of tissue CGP cases. Use of matched targeted therapy overall was similar post-liquid biopsy or post-tissue CGP but varied considerably across emerging (25%, 79/317) versus standard of care (SOC) (74%, 475/640) GA. Real-world-progression free survival for patients receiving SOC first line matched targeted therapy administered following liquid biopsy (n = 33) and tissue (n = 229) CGP were similar (13.8 vs 10.6 months; aHR = 0.68 [0.36-1.26]). Among patients evaluated for rwR, overall response rate (partial/complete response) to matched targeted therapy post-liquid biopsy CGP was 75% (39/52) versus 66% post-tissue CGP (254/385, P = 0.51). CONCLUSION: Retrospective analysis of real-world clinico-genomic data demonstrated that clinical outcomes on matched targeted therapy were similar following liquid biopsy and tissue CGP in NSCLC, which suggests routine clinical use of liquid biopsy CGP can reliably guide therapy selection.

Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database.

Importance: Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. Objective: To assess whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non-small cell lung cancer (NSCLC). Design, Setting, and Participants: Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. Exposures: Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. Main Outcomes and Measures: Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. Results: Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration in EGFR, ALK, or ROS1 (701 [17.2%] with EGFR, 128 [3.1%] with ALK, and 42 [1.0%] with ROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months [95% CI, 15.2-21.7] vs 11.4 months [95% CI, 9.7-12.5] from advanced diagnosis; P < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 [IQR, 4.4-14.8] vs 2.6 [IQR, 1.7-5.2]; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 [IQR, 1.76-6.1] vs 7.8 [IQR, 3.5-13.9]; P < .001), ALK (2.1 [IQR, 0.9-4.0] vs 7.0 [IQR, 3.5-13.0]; P < .001), RET (4.6 [IQR, 1.7-8.7] vs 7.0 [IQR, 2.6-13.0]; P = .004), or ROS1 (4.0 [IQR, 1.2-9.6] vs 7.0 [IQR, 2.6-13.0]; P = .03). In patients treated with anti-PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months [95% CI, 11.6-24.9] vs 8.5 months [95% CI, 7.6-9.7]; P < .001), longer time receiving therapy (7.8 months [95% CI, 5.5-11.1] vs 3.3 months [95% CI, 2.8-3.7]; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. Conclusions and Relevance: Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.

STK11/LKB1 Mutations and PD-1 Inhibitor Resistance in KRAS-Mutant Lung Adenocarcinoma.

KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine the efficacy of PD-1 inhibitors in these subgroups. Objective response rates to PD-1 blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) subgroups (P < 0.001) in the Stand Up To Cancer (SU2C) cohort (174 patients) with KRAS-mutant LUAC and in patients treated with nivolumab in the CheckMate-057 phase III trial (0% vs. 57.1% vs. 18.2%; P = 0.047). In the SU2C cohort, KL LUAC exhibited shorter progression-free (P < 0.001) and overall (P = 0.0015) survival compared with KRASMUT;STK11/LKB1WT LUAC. Among 924 LUACs, STK11/LKB1 alterations were the only marker significantly associated with PD-L1 negativity in TMBIntermediate/High LUAC. The impact of STK11/LKB1 alterations on clinical outcomes with PD-1/PD-L1 inhibitors extended to PD-L1-positive non-small cell lung cancer. In Kras-mutant murine LUAC models, Stk11/Lkb1 loss promoted PD-1/PD-L1 inhibitor resistance, suggesting a causal role. Our results identify STK11/LKB1 alterations as a major driver of primary resistance to PD-1 blockade in KRAS-mutant LUAC.Significance: This work identifies STK11/LKB1 alterations as the most prevalent genomic driver of primary resistance to PD-1 axis inhibitors in KRAS-mutant lung adenocarcinoma. Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets. Cancer Discov; 8(7); 822-35. ©2018 AACR.See related commentary by Etxeberria et al., p. 794This article is highlighted in the In This Issue feature, p. 781.

Real-World Evidence In Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study.

The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.

Mutational Landscapes of Smoking-Related Cancers in Caucasians and African Americans: Precision Oncology Perspectives at Wake Forest Baptist Comprehensive Cancer Center.

Background: Cancers related to tobacco use and African-American ancestry are under-characterized by genomics. This gap in precision oncology research represents a major challenge in the health disparities in the United States. Methods: The Precision Oncology trial at the Wake Forest Baptist Comprehensive Cancer Center enrolled 431 cancer patients from March 2015 to May 2016. The composition of these patients consists of a high representation of tobacco-related cancers (e.g., lung, colorectal, and bladder) and African-American ancestry (13.5%). Tumors were sequenced to identify mutations to gain insight into genetic alterations associated with smoking and/or African-American ancestry. Results: Tobacco-related cancers exhibit a high mutational load. These tumors are characterized by high-frequency mutations in TP53, DNA damage repair genes (BRCA2 and ATM), and chromatin remodeling genes (the lysine methyltransferases KMT2D or MLL2, and KMT2C or MLL3). These tobacco-related cancers also exhibit augmented tumor heterogeneities. Smoking related genetic mutations were validated by The Cancer Genome Atlas dataset that includes 2,821 cases with known smoking status. The Wake Forest and The Cancer Genome Atlas cohorts (431 and 7,991 cases, respectively) revealed a significantly increased mutation rate in the TP53 gene in the African-American subgroup studied. Both cohorts also revealed 5 genes (e.g. CDK8) significantly amplified in the African-American population. Conclusions: These results provide strong evidence that tobacco is a major cause of genomic instability and heterogeneity in cancer. TP53 mutations and key oncogene amplifications emerge as key factors contributing to cancer outcome disparities among different racial/ethnic groups.

Endoscopic Features and Eosinophil Density Are Associated with Food Impaction in Adults with Esophageal Eosinophilia.

BACKGROUND AND AIMS: Food impaction has been described in both eosinophilic esophagitis and proton pump inhibitor-responsive esophageal eosinophilia. The association between endoscopic/histologic features of esophageal eosinophilia and food impaction remains unclear. We aimed to identify clinical, endoscopic, and histologic findings associated with a history of food impaction in esophageal eosinophilia. METHODS: This was a retrospective cohort study of adult esophageal eosinophilia patients at a tertiary center in 6/2005-10/2014. Only patients with ≥15 eosinophils/high-power field on mucosal biopsies were included. Demographics, comorbidities, symptoms, endoscopic/histologic findings on initial endoscopy, and history of food impaction were reviewed. Statistical analyses were performed using Fisher's exact test (univariate) and forward stepwise logistic regression (multivariate). RESULTS: 400 patients (42 ± 14 years, 61 % male) were included, with 78 (20 %) having food impaction history. On univariate analyses, rings (62 vs 42 %, p = 0.003), erosions (12 vs 5 %, p = 0.03), eosinophil density on biopsy (40 [IQR = 30-50] vs 30 [IQR = 15-50], p = 0.004), and dysphagia (88 vs 62 %, p < 0.0001) were more prevalent among patients with food impaction history, while heartburn (10 vs 33 %, p < 0.0001) and abdominal pain (1 vs 12 %, p = 0.002) were less common. On multivariate analysis, rings (OR 2.6, p = 0.002), erosions (OR 3.2, p = 0.02), and eosinophil density (ß-coefficient = 0.01, p = 0.04) remained associated with food impaction. CONCLUSIONS: Findings of rings and erosions on endoscopy and increased eosinophil density on histology were independently associated with a history of food impaction in adult esophageal eosinophilia patients. Food impaction may result from both active inflammation (erosions and increased eosinophil density) and chronic fibrostenotic changes (rings).

Enhancing the Prediction of 30-Day Readmission After Percutaneous Coronary Intervention Using Data Extracted by Querying of the Electronic Health Record.

BACKGROUND: Early readmission after percutaneous coronary intervention is an important quality metric, but prediction models from registry data have only moderate discrimination. We aimed to improve ability to predict 30-day readmission after percutaneous coronary intervention from a previously validated registry-based model. METHODS AND RESULTS: We matched readmitted to non-readmitted patients in a 1:2 ratio by risk of readmission, and extracted unstructured and unconventional structured data from the electronic medical record, including need for medical interpretation, albumin level, medical nonadherence, previous number of emergency department visits, atrial fibrillation/flutter, syncope/presyncope, end-stage liver disease, malignancy, and anxiety. We assessed differences in rates of these conditions between cases/controls, and estimated their independent association with 30-day readmission using logistic regression conditional on matched groups. Among 9288 percutaneous coronary interventions, we matched 888 readmitted with 1776 non-readmitted patients. In univariate analysis, cases and controls were significantly different with respect to interpreter (7.9% for cases and 5.3% for controls; P=0.009), emergency department visits (1.12 for cases and 0.77 for controls; P<0.001), homelessness (3.2% for cases and 1.6% for controls; P=0.007), anticoagulation (33.9% for cases and 22.1% for controls; P<0.001), atrial fibrillation/flutter (32.7% for cases and 28.9% for controls; P=0.045), presyncope/syncope (27.8% for cases and 21.3% for controls; P<0.001), and anxiety (69.4% for cases and 62.4% for controls; P<0.001). Anticoagulation, emergency department visits, and anxiety were independently associated with readmission. CONCLUSIONS: Patient characteristics derived from review of the electronic health record can be used to refine risk prediction for hospital readmission after percutaneous coronary intervention.

Renal Response in Patients with Chronic Kidney Disease Predicts Outcome Following Cardiac Resynchronization Therapy.

BACKGROUND: Chronic kidney disease (CKD) severity is associated with increased morbidity and mortality in congestive heart failure. There is a paucity of data regarding renal improvement after cardiac resynchronization therapy (CRT) and its potential impact on clinical outcomes, especially in patients with severe CKD. METHOD: This was a retrospective analysis of a prospectively collected cohort of 260 patients with CKD undergoing CRT at a single center. Renal function was compared before and after CRT. The primary end point was a composite of death, heart transplant, and left ventricular assist device (LVAD), assessed at 5 years. RESULTS: Patients with more severe CKD demonstrated increased risk of death, transplant, or LVAD following CRT (P = 0.015). Renal response (estimated glomerular filtration rate improvement ≥10 mL/min/1.73 m(2) ) was observed in 14% of all patients and 28% of patients with stage IV CKD. Independent predictors of renal response included left ventricular ejection fraction improvement (odds ratio [OR] 1.06, confidence interval [CI] 1.01-1.10), angiotensin-converting enzyme inhibitor/angiotensin receptor blocker use (OR 4.31, CI 1.08-17.23), and advanced CKD stage (OR 2.19, CI 1.14-4.23). Renal response independently decreased hazard of the primary outcome (HR 0.24, CI 0.08-0.73, P = 0.01). Renal responders with stage IV CKD had 80% 5-year event-free survival, compared to 0% for nonrenal responders in stage IV (P = 0.03). CONCLUSION: Although severity of CKD is associated with poorer outcome after CRT, improvement in renal function can occur in patients across all CKD stages. Renal responders, including those with stage IV CKD, demonstrate favorable 5-year outcomes. Assessment of renal response may help better prognostic outcomes following CRT.

Predicting Non-Adherence with Outpatient Colonoscopy Using a Novel Electronic Tool that Measures Prior Non-Adherence.

BACKGROUND: Accurately predicting the risk of no-show for a scheduled colonoscopy can help target interventions to improve compliance with colonoscopy, and thereby reduce the disease burden of colorectal cancer and enhance the utilization of resources within endoscopy units. OBJECTIVES: We aimed to utilize information available in an electronic medical record (EMR) and endoscopy scheduling system to create a predictive model for no-show risk, and to simultaneously evaluate the role for natural language processing (NLP) in developing such a model. DESIGN: This was a retrospective observational study using discovery and validation phases to design a colonoscopy non-adherence prediction model. An NLP-derived variable called the Non-Adherence Ratio ("NAR") was developed, validated, and included in the model. PARTICIPANTS: Patients scheduled for outpatient colonoscopy at an Academic Medical Center (AMC) that is part of a multi-hospital health system, 2009 to 2011, were included in the study. MAIN MEASURES: Odds ratios for non-adherence were calculated for all variables in the discovery cohort, and an Area Under the Receiver Operating Curve (AUC) was calculated for the final non-adherence prediction model. KEY RESULTS: The non-adherence model included six variables: 1) gender; 2) history of psychiatric illness, 3) NAR; 4) wait time in months; 5) number of prior missed endoscopies; and 6) education level. The model achieved discrimination in the validation cohort (AUC= =70.2 %). At a threshold non-adherence score of 0.46, the model's sensitivity and specificity were 33 % and 92 %, respectively. Removing the NAR from the model significantly reduced its predictive power (AUC = 64.3 %, difference = 5.9 %, p < 0.001). CONCLUSIONS: A six-variable model using readily available clinical and demographic information demonstrated accuracy for predicting colonoscopy non-adherence. The NAR, a novel variable developed using NLP technology, significantly strengthened this model's predictive power.

Pre-capillary pulmonary hypertension and right ventricular dilation predict clinical outcome in cardiac resynchronization therapy.

OBJECTIVES: This study examined the prognostic significance of pre- and post-capillary components of pulmonary hypertension (PH) in patients receiving cardiac resynchronization therapy (CRT). BACKGROUND: PH is common in patients with left ventricular systolic dysfunction (LVSD) receiving CRT. The impact of PH subtype on clinical outcome in CRT is unknown. METHODS: The study population consisted of 101 patients (average age 66 ± 13 years, left ventricular ejection fraction 0.23 ± 0.07, and New York Heart Association functional class 3.2 ± 0.4) who underwent right heart catheterization in the 6 months before CRT. PH was defined as a mean pulmonary artery pressure ≥25 mm Hg; a significant pre-capillary contribution to elevated mean pulmonary artery pressure was defined as a transpulmonary gradient (TPG) ≥12 mm Hg. Clinical endpoints were assessed at 2 years and included all-cause mortality and a composite of death, left ventricular assist device, or cardiac transplantation. RESULTS: Patients with TPG ≥12 mm Hg were more likely to experience all-cause mortality (hazard ratio [HR]: 3.2; 95% confidence interval [CI]: 1.3 to 7.4; p = 0.009) and the composite outcome (HR: 3.0; 95% CI: 1.4 to 6.3; p = 0.004) compared with patients with TPG <12 mm Hg. After multivariate adjustment for hemodynamic, clinical, and echocardiographic variables, only TPG ≥12 mm Hg and baseline right ventricular (RV) dilation (RV end-diastolic dimension >42 mm) were associated with the composite clinical outcome (p = 0.05 and p = 0.04, respectively). CONCLUSIONS: High TPG PH and RV dilation are independent predictors of adverse outcomes in patients with LVSD who are receiving CRT. RV pulmonary vascular dysfunction may be a therapeutic target in select patients receiving CRT.

Usefulness and consequences of cardiac resynchronization therapy in dialysis-dependent patients with heart failure.

Cardiac resynchronization therapy (CRT) is often deferred in dialysis-dependent patients with heart failure (HF) because of a perceived lack of benefit and potentially higher risks, although the outcomes associated with CRT in dialysis have not been reported. We therefore studied our center's experience with CRT in dialysis-dependent patients. We constructed a descriptive assessment of these patients (n = 15) and performed a case-control analysis matching for age, gender, bundle branch morphology, diabetes mellitus, cardiomyopathy origin, and ß-blocker and angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker use. Baseline and 6-month echocardiograms were assessed for evidence of reverse remodeling. No periprocedural or long-term complications were observed among dialysis patients. Heterogenous improvement in ejection fraction (+3.1 ± 9.2%) was noted and 2 patients derived absolute improvements of 8% and 22%, respectively. Dialysis patients demonstrated the following 3-year event rates: HF hospitalization, 31%; all-cause hospitalization, 100%; mortality, 73%; and HF hospitalization or death, 82%. In the case-control analysis, controls demonstrated superior reverse remodeling (+9.2 ± 9.5% increase in ejection fraction), decreased mortality (73% vs 44%, p = 0.038), and all-cause hospitalizations (76% vs 100%, p = 0.047), with no difference in HF hospitalizations (p = 0.39), compared with dialysis patients. In conclusion, at our center, the dialysis-dependent patients with HF who underwent CRT implantation did so safely and no serious complications were observed. Certain dialysis patients demonstrated compelling improvement after device implantation. Compared with matched controls, dialysis patients were at increased risk for adverse events and worsened echocardiographic outcomes.

Lateralization of face processing in the human brain.

Are visual face processing mechanisms the same in the left and right cerebral hemispheres? The possibility of such 'duplicated processing' seems puzzling in terms of neural resource usage, and we currently lack a precise characterization of the lateral differences in face processing. To address this need, we have undertaken a three-pronged approach. Using functional magnetic resonance imaging, we assessed cortical sensitivity to facial semblance, the modulatory effects of context and temporal response dynamics. Results on all three fronts revealed systematic hemispheric differences. We found that: (i) activation patterns in the left fusiform gyrus correlate with image-level face-semblance, while those in the right correlate with categorical face/non-face judgements. (ii) Context exerts significant excitatory/inhibitory influence in the left, but has limited effect on the right. (iii) Face-selectivity persists in the right even after activity on the left has returned to baseline. These results provide important clues regarding the functional architecture of face processing, suggesting that the left hemisphere is involved in processing 'low-level' face semblance, and perhaps is a precursor to categorical 'deep' analyses on the right.