Hispanic Ethnicity Is Associated With Increased Hospital Charges After Radical Cystectomy in the United States

Objective: To examine the impact of race and ethnicity on financial charges associated with radical cystectomy (RC). Data Sources/Study Setting: The Nationwide Inpatient Sample was used to identify patients who underwent RC for bladder cancer between 1998 and 2010. Study Design: The primary outcome was total hospital charges adjusted for inflation. Multivariate analysis was performed using a generalized linear model on the logarithmically transformed outcome variable (total hospital charges) after adjusting for age, sex, race, Elixhauser comorbidities, surgical approach, year, primary payer, hospital and surgeon annual RC volume, hospital characteristics, and postoperative complications. Principle findings: A total of 14,873 patients were identified. Hispanic and black patients were more likely to be treated by low-volume surgeons and/or institutions (both P=.07). Conclusions: Hispanic ethnicity but not black race predicts higher hospital charges after RC

The Complexity of Combinations of Qualitative Constraint Satisfaction Problems

The CSP of a first-order theory $T$ is the problem of deciding for a given finite set $S$ of atomic formulas whether $T \cup S$ is satisfiable. Let $T_1$ and $T_2$ be two theories with countably infinite models and disjoint signatures. Nelson and Oppen presented conditions that imply decidability (or polynomial-time decidability) of $\mathrm{CSP}(T_1 \cup T_2)$ under the assumption that $\mathrm{CSP}(T_1)$ and $\mathrm{CSP}(T_2)$ are decidable (or polynomial-time decidable). We show that for a large class of $\omega$-categorical theories $T_1, T_2$ the Nelson-Oppen conditions are not only sufficient, but also necessary for polynomial-time tractability of $\mathrm{CSP}(T_1 \cup T_2)$ (unless P=NP).Comment: Version 2: stronger main result with better presentation of the proof; multiple improvements in other proofs; new section structure; new example

Randomized implementation of a primary human papillomavirus testing-based cervical cancer screening protocol for women 34 to 69 years in Norway

Background: Cervical cancer screening programs are facing a programmatic shift where screening protocol based on human papillomavirus testing (HPV-Screening protocol) is replacing the liquid-based cytology (LBC-Screening protocol). For safe technology transfer within the nationwide screening programme in Norway, HPV-Screening protocol was implemented randomized to compare the real-world effectiveness of HPV-Screening protocol and LBC-Screening protocol at the first screening round. Methods: Among 302,295 women ages 34 to 69 years scheduled to attend screening from February 2015 to June 2017, 157,447 attended. A total of 77,207 were randomly allocated to the HPV-Screening protocol and 80,240 were allocated to the LBC-Screening protocol. All women were followed up for 18 months. Results: The HPV-Screening protocol resulted in a relative increase of 60% in the detection of cervical intraepithelial neoplasia (CIN) grade 2 or worse [risk ratio (RR) = 1.6, 95% confidence interval (CI) = 1.5–1.7], 40% in CIN grade 3 or worse (RR = 1.4, 95% CI = 1.3–1.6), 40% in cancer (RR = 1.4, 95% CI = 1.0–2.1), and 60% in colposcopy referrals (RR = 1.6, 95% CI = 1.5–1.6) compared with LBC-Screening. The performance of both protocols was age dependent, being more effective in women ages under 50 years. Conclusions: The HPV-Screening protocol was well accepted by women in Norway and detected more CIN2, CIN3, and cancers compared with the LBC-Screening protocol. Impact: A randomized implementation of the HPV-Screening protocol with real-world assessment enabled a gradual, quality assured, and safe technology transition. HPV-based screening protocol may further be improved by using HPV genotyping and age-specific referral algorithms.publishedVersio

Viral coinfection analysis using a MinHash toolkit

Abstract: Background: Human papillomavirus (HPV) is a common sexually transmitted infection associated with cervical cancer that frequently occurs as a coinfection of types and subtypes. Highly similar sublineages that show over 100-fold differences in cancer risk are not distinguishable in coinfections with current typing methods. Results: We describe an efficient set of computational tools, rkmh, for analyzing complex mixed infections of related viruses based on sequence data. rkmh makes extensive use of MinHash similarity measures, and includes utilities for removing host DNA and classifying reads by type, lineage, and sublineage. We show that rkmh is capable of assigning reads to their HPV type as well as HPV16 lineage and sublineages. Conclusions: Accurate read classification enables estimates of percent composition when there are multiple infecting lineages or sublineages. While we demonstrate rkmh for HPV with multiple sequencing technologies, it is also applicable to other mixtures of related sequences

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment