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Large-scale, multi-site collaboration is becoming indispensable for a wide range of research and clinical activities in oncology. To facilitate the next generation of advances in cancer biology, precision oncology and the population sciences it will be necessary to develop and implement data management and analytic tools that empower investigators to reliably and objectively detect, characterize and chronicle the phenotypic and genomic changes that occur during the transformation from the benign to cancerous state and throughout the course of disease progression. To facilitate these efforts it is incumbent upon the informatics community to establish the workflows and architectures that automate the aggregation and organization of a growing range and number of clinical data types and modalities ranging from new molecular and laboratory tests to sophisticated diagnostic imaging studies. In an attempt to meet those challenges, leading health care centers across the country are making steep investments to establish enterprise-wide, data warehouses. A significant limitation of many data warehouses, however, is that they are designed to support only alphanumeric information. In contrast to those traditional designs, the system that we have developed supports automated collection and mining of multimodal data including genomics, digital pathology and radiology images. In this paper, our team describes the design, development and implementation of a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide actionable insight into the underlying characteristics of the tumor environment that would not be revealed using standard methods and tools. The System features a flexible Extract, Transform and Load (ETL) interface that enables it to adapt to aggregate data originating from different clinical and research sources depending on the specific EHR and other data sources utilized at a given deployment site., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Introduction: Pediatric and young adult brain tumors (PYBT) account for a large share of cancer-related morbidity and mortality among children in the United States, but their etiology is not well understood. Previous research suggests the Appalachian region of Kentucky has high rates of PYBT. This study explored PYBT incidence over 25 years in Kentucky to identify geographic and temporal trends and generate hypotheses for future research., Methods: The Kentucky Cancer Registry contributed data on all PYBT diagnosed among those aged 0-29 during years 1995-2019. Age- and sex-adjusted spatio-temporal scan statistics-one for each type of PYBT, and one for all types-comprised the primary analysis. These results were mapped along with environmental and occupational data., Results: Findings indicated that north-central Kentucky and the Appalachian region experienced higher rates of some PYBT. High rates of astrocytomas were clustered in a north-south strip of central Kentucky toward the end of the study period, while high rates of other specified types of intracranial and intraspinal neoplasms were significantly clustered in eastern Kentucky. The area where these clusters overlapped, in north-central Kentucky, had significantly higher rates of PYBT generally., Discussion: This study demonstrates north-central Kentucky and the Appalachian region experienced higher PYBT risk than the rest of the state. These regions are home to some of Kentucky's signature industries, which should be examined in further research. Future population-based and individual-level studies of genetic factors are needed to explore how the occupations of parents, as well as prenatal and childhood exposures to pesticides and air pollutants, impact PYBT incidence., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The purpose of this study was to assess the occupational SARS-CoV-2 infection risk among health care workers (HCW) at University of Kentucky HealthCare (UKHC) by evaluating the prevalence of SARS-CoV-2 antibodies., Methods: This is a prospective cohort study of HCW at UKHC. SARS-CoV-2 IgG antibody seropositivity was measured in a CLIA-certified laboratory utilizing the Abbott Architect SARS-CoV-2 IgG antibody assay. Demographics and work type were self-reported by study participants via an emailed survey., Results: The overall antibody positivity rate of HCW was 1.55% (5/322; 95% confidence interval: 0.65%-3.71%) at cohort entry. There were no differences in antibody positivity between those that worked directly with SARS-CoV-2 infected patients and those that did not. The antibody rate of positivity of patients during the same time period was similar, 1.8% (9/499; 95% confidence interval 0.94%-3.45%)., Conclusions: Antibody positivity was low and similar between HCW and patients tested during a similar time period. HCW positivity rates did not appear to be impacted by caring for known SARS-CoV-2 infected patients suggesting that appropriate use of personal protective equipment is effective in protecting individuals from transmission., (Copyright © 2021 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies., Patients and Methods: Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients)., Results: A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality., Conclusions: Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies., Clinical Trial Identifier: NCT04354701., Competing Interests: Disclosure JDA reports research funding to the institution from Tesaro, outside the submitted work. ZB reports nonfinancial support from Bristol Myers Squibb and grants from Genentech/imCORE, outside the submitted work. BB reports research funding to the institution from Boehringer Ingelheim, Bicycle Therapeutics, Syros Pharmaceuticals, and Ikena Oncology, all outside the submitted work. TB-S reports research funding to the institution from Agios, Arys, Boston Biomedical, Bayer, Amgen, Merck, Celgene, Lilly, Ipsen, Clovis, Seattle Genetics, Array Biopharma, Genentech, Novartis, Mirati, Merus, AbGenomics, Incyte, Pfizer, BMS; consulting (to institution) for Ipsen, Array Biopharma, Pfizer, Seattle Genetics, Bayer, Genentech, Incyte, and Merck; consulting (to self) for AbbVie, Boehringer Ingelheim, Janssen, Eisai, Daiichi Sankyo, Natera, Treos Bio, Celularity, Exact Science, Sobi, BeiGene, Xilis, Astra Zeneca, and Foundation Medicine; serving on Independent Data Monitoring Committee/Data and Safety Monitoring Board (to self) for AstraZeneca, Exelixis, Lilly, PanCAN, and 1Globe; positions on Scientific Advisory Board for Imugene, Immuneering, and Sun Biopharma; and inventions/patents (WO/2018/183488 and WO/2019/055687), all outside the submitted work. SB reports being on advisory boards for Bristol Meyers Squibb and Seattle Genetics. MAB reports personal fees from Exelixis, Bristol-Myers Squibb, Bayer, Eisai, Pfizer, AstraZeneca, Janssen, Genomic Health, Nektar, and Sanofi; grants from Xencor, Bayer, Bristol-Myers Squibb, Genentech/Roche, Seattle Genetics, Incyte, Nektar, AstraZeneca, Tricon Pharmaceuticals, Peloton Therapeutics, and Pfizer, outside the submitted work. NB reports honoraria from Novartis, Pfizer, Roche, and Lilly, outside the submitted work. DWB reports research funding to the institution from Exelixis, Ayala, Merck, and Elevar, all outside the submitted work. DDC declares consulting or advisory role with Exelixis, outside the submitted work. TKC reports institutional and personal research support from Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers-Squibb/ER Squibb and sons LLC, Calithera, Cerulean, Corvus, Eisai, Exelixis, F. Hoffmann-La Roche, Foundation Medicine Inc., Genentech, GlaxoSmithKline, Ipsen, Lilly, Merck, Novartis, Peloton, Pfizer, Prometheus Labs, Roche, Roche Products Limited, Sanofi/Aventis, Takeda, Tracon; consulting/honoraria or advisory role with Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers-Squibb/ER Squibb and sons LLC, Cerulean, Corvus, Eisai, EMD Serono, Exelixis, Foundation Medicine Inc., Genentech, GlaxoSmithKline, Heron Therapeutics, Infinity Pharma, Ipsen, Jansen Oncology, IQVIA, Lilly, Merck, NCCN, Novartis, Peloton, Pfizer, Pionyr, Prometheus Labs, Roche, Sanofi/Aventis, Surface Oncology, Tempest, Up-to-Date; CME-related events (e.g. OncLive, PVI, MJH Life Sciences); stock ownership in Pionyr, Tempest; patents filed, royalties, or other intellectual properties related to biomarkers of immune checkpoint blockers; fees for travel, accommodations, expenses, medical writing in relation to consulting, advisory roles, or honoraria; and no speaker's bureau; also supported in part by the Dana-Farber/Harvard Cancer Center Kidney SPORE and Program, the Kohlberg Chair at Harvard Medical School and the Trust Family, Michael Brigham, and Loker Pinard Funds for Kidney Cancer Research at DFCI. DBD reports consulting for Ipsen, Boehringer Ingelheim; ASCO Young Investigator Award from Conquer Cancer Foundation, outside the submitted work. AE reports grant support from AstraZeneca, outside the submitted work. DF reports research funding to the institution from Viracor-Eurofins and Astellas, all outside the submitted work. LAF reports clinical trial funding to the institution from BMS, EMD Serono, Pfizer, Merck KGaA, Array, Kartos, Merck, and Incyte, ECOG-ACRIN study funding from Array; and personal fees from Elsevier and Via Oncology, outside the submitted work. DBF reports honoraria from Castle Biosciences. SMG reports Honoraria from AstraZeneca, Merck, Genentech/Roche; consulting or advisory role with Genentech/Roche, AstraZeneca, Bristol-Myers Squibb, Takeda, Xcovery, Boehringer Ingelheim, Novocure, Daiichi Sankyo, Novartis, Jazz Pharmaceuticals, Blueprint Medicines, Eli Lilly, Pfizer, Janssen Oncology; research funding (to self) from Merck, AstraZeneca; research funding (to institution) from Genentech/Roche, Merck, Blueprint Medicines, ARIAD/Takeda, Astellas Pharma, Lycera, Daiichi Sankyo, IMAB, Nektar, AstraZeneca, Pfizer, Amgen; travel, accommodations, expenses from Genentech/Roche, Merck; and other relationship from AstraZeneca, all outside the submitted work. MDG reports personal fees from Genentech, Pfizer, Astra Zeneca, Merck, Bristol Myers Squib, Dragonfly, Dracen, Seattle Genetics, and Astellas, outside the submitted work. PG reports consulting fees from AstraZeneca, Bayer, Bristol-Myers Squibb, Clovis Oncology, Dyania Health, Driver, EMD Serono, Exelixis, Foundation Medicine, Genentech/Roche, Genzyme, GlaxoSmithKline, Heron Therapeutics, Immunomedics, Infinity Pharmaceuticals, Janssen, Merck, Mirati Therapeutics, Pfizer, Seattle Genetics, QED Therapeutics; research funding to institution from Merck, Mirati Therapeutics, Pfizer, Clovis Oncology, Bavarian Nordic, Immunomedics, Debiopharm, Bristol-Myers Squibb, QED Therapeutics, GlaxoSmithKline, and Kure It Cancer Research, all outside the submitted work. SG reports research funding to the institution from AstraZeneca and consulting/advisory role with Puma Biotechnology. SG reports consultancy fees from BMS, Merck, AstraZeneca, Seattle Genetics, Pfizer; and speaker fees from Seattle Genetics and Janssen, all outside the submitted work. TRH reports consulting or advisory role with Curium, ScioScientific, TERUMO, Lexicon, Ipsen, Advanced Accelerator; research funding from Ipsen, ArQule, Agios, Thermo Fisher Scientific, Basilea. BH reports research funding to the institution from Amgen, AbbVie, BI, Mirati, Merck, Eli-Lilly, AstraZeneca, BMS, Novartis, GSK, Pfizer, Advaxis, and Guardant Health; consulting/advisory role with Merck, BMS, Genentech, AstraZeneca, Amgen, Novartis, TPT, VI, Guardant Health; and honoraria from PER and OncLive, all outside the submitted work. JEH reports research funding from Regeneron and Dendreon; and travel, accommodations, and expenses from Genzyme. CH reports funding from the Henry Ford Cancer Institute supporting the current work; research funding to institution from Merck, Exelixis, Bayer, AstraZeneca, Genentech, Dendreon and Bausch; personal fees from Sanofi/Genzyme, Dendreon, Exelixis, Bristol Myers Squibb, Astellas, Medivation, Bayer, and Janssen Scientific, all outside the submitted work; and stock ownership by an immediate family member in Johnson and Johnson. DBJ reports advisory board participation for Array Biopharma, BMS, Catalyst Biopharma, Iovance, Jansen, Merck, Novartis, and OncoSec, and receives research funding from BMS and Incyte, all outside the submitted work. AK reports support to his institution from TESARO, Halozyme, Geistlich Pharma, Astellas Pharma, and Rafael Pharmaceuticals; and honoraria from OncLive, outside the submitted work. ARK (or an immediate family member) has currently or during the past 2 years owned stock or held an ownership interest in Merck, Sanofi, and BMS. VSK reports personal fees from Pfizer, Janssen, Dendreon, AstraZeneca, Seattle Genetics, and Clovis; grants (for institution) from Nektar, Novartis/Endocyte, Janssen, Clovis, and Prostate Cancer Foundation, all outside the submitted work. NMK reports personal fees from G1 Therapeutics, Invitae, Beyond Spring, Spectrum, BMS, Janssen, and Total Health, all outside the submitted work. PEL reports consulting/advisory role with Pfizer, Merck, Teva, BI, and Astra Zeneca, all outside the submitted work. AL-B reports personal fees from PSI CRO, Bayer, Blueprint, Astra-Zeneca, Medidata, Taiho, QED, Cardinal Health, BrightInsight, The Lynx Group, Boston Biomedical, Amgen, Bayer, Guardant, Natera, Eisai, Ipsen, and Merck; and stock options from Massive Bio, outside the submitted work. GdLL reports honoraria from Boehringer Ingelheim; consulting or advisory role for Pfizer and AstraZeneca; research funding from AstraZeneca; funding to his institution from Merck Sharp & Dohme, EMD Serono, AstraZeneca, Blueprint Medicines, Tesaro, Bavarian Nordic, NOVARTIS, G1 Therapeutics, Adaptimmune, BMS, GSK, AbbVie, Rgenix, Pfizer, Roche, Genentech, Lilly, and Janssen; travel, accommodations, and expenses from Boehringer Ingelheim, Pfizer, E.R. Squibb Sons, LLC, Janssen. GHL reports grants from AMGEN (institution); personal fees from G1 Therapeutics, TEVA, Samsung Bioepis, Beyond Spring, and Merck, outside the submitted work. RRM reports research funding from Bayer, Pfizer, Tempus; serves on Advisory Board for AstraZeneca, Bayer, Bristol Myers Squibb, Calithera, Exelixis, Janssen, Merck, Novartis, Pfizer, Sanofi, Tempus; is a consultant for Dendreon, Vividion; and serves on the molecular tumor board at Caris. RAM grants from Incyte, CTI, AbbVie, and Celgene; personal fees from Novartis, Genentech, Sierra Oncology, La Jolla, and Samus, outside the submitted work. VM has currently or during the past 2 years employment and stock or other ownership interest with Johnson & Johnson, all outside the submitted work. GN reports research funding to the institution from Novartis, all outside the submitted work. JN reports personal fees from AstraZeneca, Clovis Oncology; all outside the submitted work. CAP (or an immediate family member) has currently or during the past 2 years owned stock or held an ownership interest in Pfizer, Epizyme, Inovio, OPKO Health Inc, Roche. JMP reports grant from Dana-Farber/Harvard Cancer Center Breast SPORE Program, outside the submitted work. PP reports receiving payment for speakers' bureau from Novartis, Daichi Sankyo, Genentech, Seattle Genetics, and Pfizer, all outside the submitted work. NAP reports personal fees from Eli Lilly, Merck, BMS, Genentech, AstraZeneca, Inivata, and Regeneron, outside the submitted work. SP reports personal fees from AbbVie, Amgen, AstraZeneca, Bayer, Biocartis, Boehringer-Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, F. Hoffmann-La Roche, Foundation Medicine, Illumina, Janssen, Merck Sharp and Dohme, Merck Serono, Merrimack, Novartis, Pharma Mar, Pfizer, Regeneron, Sanofi, Seattle Genetics and Takeda, AstraZeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Eli Lilly, F. Hoffmann-La Roche, Merck Sharp and Dohme, Novartis, Pfizer, and Takeda; nonfinancial support from Amgen, AstraZeneca, Boehringer-Ingelheim, Bristol-Meyers Squibb, Clovis, F. Hoffmann-La Roche, Illumina, Merck Sharp and Dohme, Merck Serono, Novartis, Pfizer, and Sanofi; and personal fees from BioInvent (all fees to institution), outside the submitted work. DYR reports consulting/advisory role with and coverage of travel/accommodation expenses by Castle Biosciences, all outside the submitted work. BIR reports grants, personal fees, and nonfinancial support from Merck; grants and personal fees from BMS, Pfizer, Aveo, and Genentech; grants from Astra Zeneca; personal fees from Synthorx, 3D Medicines, Aravive, Surface Oncology, and Arrowhead Therapeutics; and other from PTC Therapeutics, outside the submitted work. RPR reports research grants to her institution from BMS and Janssen and has worked as a consultant/advisor and received honoraria from BMS and Janssen, all of which are outside the scope of submitted work. ALS reports travel support provided by Pfizer and Astellas. GKS reports personal fees from Apexigen, Array, Epizyme, GenCirq, Daiichi Sankyo, Fortress, Iovance Biotherapeutics, Bayer Pharmaceuticals, Pfizer Oncology, Array Advisory Board, Oncogenuity, Puretech, PTC Therapeutics, Ellipses Pharma, Concarlo; advisory board for Bionaut; grants from Astex; stock ownership in Pfizer, all outside the submitted work. SS reports stock and other ownership interests in Grand Rounds, Janssen, and Natera. YS reports honoraria from Boehringer Ingelheim, AstraZeneca, Novartis, and Eisai; consulting or advisory role with Pfizer, AstraZeneca, Novartis, Roche, Genentech, and Janssen, all outside the submitted work. MAT reports travel support from Syapse, Royalties from UpToDate, Connect MDS/AML Registry in Celgene (now owned by BMS), Myeloma Registry in Takeda; stock ownership in Doximity; personal fees from VIA Oncology (now owned by Elsevier ClinicalPath), Adaptive Advisory Board, and GSK; he is the local PI for Clinical Trials in AbbVie, BMS, CRAB CTC, Denovo, Research Network, Eli Lilly, LynxBio, Strata Oncology, and TG Therapeutics, all outside the submitted work. AKV reports research funding to the institution from BMS, MedPacto, Prelude, iOnctura, and Janssen; honoraria from Acceleron and Novartis; consulting/advisory role with Stelexis and Janssen; stock or other ownership in Stelexis; and an immediate family member with employment/leadership with CereXis, all outside the submitted work. DCV reports honoraria and speakers' bureau fees from CSL Behring, Merck Canada, Novartis Canada, Takeda, and UCB Biosciences GmbH, and travel accommodations from CSL Behring, and Avir Pharma, all outside the submitted work. He is supported by the Fonds de la recherche en santé du Québec (FRQS) Clinician-Scientist Junior 2 program. JLW reports grants from the National Cancer Institute during the conduct of the study; personal fees from Westat and IBM Watson Health; and other from HemOnc.org LLC, outside the submitted work. TMW-D reports stock and other ownership interests in High Enroll; honoraria from Physicians' Education Resource; consulting or advisory roles with Shattuck Labs, Rakuten Medical, Exicure; research funding from Merck, AstraZeneca/MedImmune, Bristol-Myers Squibb, GlaxoSmithKline, Caris Life Sciences, GlaxoSmithKline; travel, accommodations, expenses from Merck, Bristol-Myers Squibb, Bexion, AstraZeneca/MedImmune, Caris Life Sciences, Lilly, and Tesaro, all outside the submitted work. EW-B reports work in a consultant/advisor role for Astellas and BMS; funding support from Pfizer Global Medical Grants; other for Exelixis; and an immediate family member with stock ownership in Immunomedics and Nektar, all outside the submitted work. TZ reports research funding (to Duke) from Pfizer, Janssen, Acerta, AbbVie, Novartis, Merrimack, OmniSeq, PGDx, Merck, Mirati, Astellas, and Regeneron; consulting/speaking role with Genentech Roche, Exelixis, Genomic Health, and Sanofi Aventis; and serves on the consulting/advisory board for AstraZeneca, Bayer, Pfizer, Foundation Medicine, Janssen, Amgen, BMS, Calithera, Dendreon, and MJH Associates; stock ownership/employment (spouse) from Capio Biosciences, Archimmune Therapeutics, and Nanorobotics. AYZ has currently or during the past 2 years owned stock or held an ownership interest in Gilead Sciences. LZ reports personal fees from MERCK, outside the submitted work. All others have declared no conflicts of interest., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The state of Kentucky has the highest cancer incidence and mortality in the United States. High-risk populations such as this are often underrepresented in clinical trials. The study aims to do a comprehensive analysis of molecular landscape of metastatic cancers among these patients with detailed evaluation of factors affecting response and outcomes to immune checkpoint inhibitor (ICI) therapy. We performed a retrospective analysis of metastatic solid tumor patients who received ICI and underwent molecular profiling at our institution. Sixty nine patients with metastatic solid tumors who received ICI were included in the study. Prevalence of smoking and secondhand tobacco exposure was 78.3% and 14.5%, respectively. TP53 (62.3%), CDKN1B/2A (40.5%), NOTCH and PIK3 (33.3%) were the most common alterations in tumors. 67.4% were PDL1 positive and 59.4% had intermediate-high tumor mutational burden (TMB). Median TMB (12.6) was twofold to fourfold compared to clinical trials. The prevalence of mutations associated with smoking, homologous recombinant repair and PIK3/AKT/mTOR pathway mutations was higher compared to historic cohorts. PDL1 expression had no significant effect on radiologic response, but PFS improvement in patients with tumors expressing PDL1 trended toward statistical significance (median 18 vs. 40 weeks. HR = 1.43. 95%CI 0.93, 4.46). Median PFS was higher in the high-TMB cohort compared to low-intermediate TMB (median not reached vs. 26 weeks; HR = 0.37. 95%CI 0.13, 1.05). A statistically significant improvement in PFS was observed in the PIK3 mutated cohort (median 123 vs. 23 weeks. HR = 2.51. 95%CI 1.23, 5.14). This was independent of tumor mutational burden (TMB) status or PDL1 expression status. PIK3 mutants had a higher overall response rate than the wild type (69.6% vs. 43.5%, OR 0.34; p = 0.045). The results should prompt further evaluation of these potential biomarkers and more widespread real-world data publications which might help determine biomarkers that could benefit specific populations., (© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Purpose: To examine smoking and use of smoking cessation aids among tobacco-associated cancer (TAC) or non-tobacco-associated cancer (nTAC) survivors. Understanding when and if specific types of cessation resources are used can help with planning interventions to more effectively decrease smoking among all cancer survivors, but there is a lack of research on smoking cessation modalities used among cancer survivors., Methods: Kentucky Cancer Registry data on incident lung, colorectal, pancreatic, breast, ovarian, and prostate cancer cases diagnosed 2007-2011, were linked with health administrative claims data (Medicaid, Medicare, private insurers) to examine the prevalence of smoking and use of smoking cessation aids 1 year prior and 1 year following the cancer diagnosis. TACs included colorectal, pancreatic, and lung cancers; nTAC included breast, ovarian, and prostate cancers., Results: There were 10,033 TAC and 13,670 nTAC survivors. Smoking before diagnosis was significantly higher among TAC survivors (p < 0.0001). Among TAC survivors, smoking before diagnosis was significantly higher among persons who: were males (83%), aged 45-64 (83%), of unknown marital status (84%), had very low education (78%), had public insurance (89%), Medicaid (85%) or were uninsured (84%). Smoking cessation counseling and pharmacotherapy were more common among TAC than nTAC survivors (p < 0.01 and p = 0.05, respectively)., Discussion: While smoking cessation counseling and pharmacotherapy were higher among TAC survivors, reducing smoking among all cancer survivors remains a priority, given cancer survivors are at increased risk for subsequent chronic diseases, including cancer. Tobacco cessation among all cancer survivors (not just those with TAC) can help improve prognosis, quality of life and reduce the risk of further disease. Health care providers can recommend for individual, group and telephone counseling and/or pharmacotherapy recommendations. These could also be included in survivorship care plans.

Purpose: Linkage of cancer registry data with complementary data sources can be an informative way to expand what is known about patients and their treatment and improve delivery of care. The purpose of this study was to explore whether patient smoking status and smoking-cessation modalities data in the Kentucky Cancer Registry (KCR) could be augmented by linkage with health claims data., Methods: The KCR conducted a data linkage with health claims data from Medicare, Medicaid, state employee insurance, Humana, and Anthem. Smoking status was defined as documentation of personal history of tobacco use (International Classification of Diseases, Ninth Revision [ICD-9] code V15.82) or tobacco use disorder (ICD-9 305.1) before and after a cancer diagnosis. Use of smoking-cessation treatments before and after the cancer diagnosis was defined as documentation of smoking-cessation counseling (Healthcare Common Procedure Coding System codes 99406, 99407, G0375, and G0376) or pharmacotherapy (eg, nicotine replacement therapy, bupropion, varenicline)., Results: From 2007 to 2011, among 23,703 patients in the KCR, we discerned a valid prediagnosis smoking status for 78%. KCR data only (72%), claims data only (6%), and a combination of both data sources (22%) were used to determine valid smoking status. Approximately 4% of patients with cancer identified as smokers (n = 11,968) and were provided smoking-cessation counseling, and 3% were prescribed pharmacotherapy for smoking cessation., Conclusion: Augmenting KCR data with medical claims data increased capture of smoking status and use of smoking-cessation modalities. Cancer registries interested in exploring smoking status to influence treatment and research activities could consider a similar approach, particularly if their registry does not capture smoking status for a majority of patients.

Objective: The purpose of this study was to assess for any associations between individual and social factors and late-stage melanoma in Kentucky from 1995 to 2013., Methods: The study combines three datasets: individual-level data from the Kentucky Cancer Registry, census tract-level data from the US Census, and county-level physician licensure data from the Kentucky Department for Public Health. The study population is described by all cases, early stage, and late stage. Logistic regression was used to evaluate the unadjusted associations between each covariate and early-stage and late-stage disease groups. All of the significant variables were assessed for interaction effect, and the significant interaction terms were used in the final model. Multiple logistic regression provided the final model of late-stage disease., Results: In this study population, a dramatic increase in melanoma incidence is seen from 1995 to 2013 with a threefold increase in the number of cases per year. Of the 10,109 cases reported, 13.6% have late-stage disease, with a mean age for all cases at 56.9 years and the majority being men. Late-stage cases are more commonly uninsured or insured with Medicaid or Medicare compared with cases with early-stage lesions. Having a spouse or partner is clearly protective from being diagnosed as having late-stage melanoma, whereas being uninsured or having Medicaid increases the odds of late-stage melanoma., Conclusions: The incidence of melanoma is increasing dramatically. With no screening recommendation for the general population from the US Preventive Task Force, clinicians should focus on those at increased risk of late-stage melanoma: unmarried men who are uninsured or receiving Medicaid.

Objective: Personality traits related to negative emotionality and low constraint are strong correlates of alcohol use disorder (AUD), but few studies have evaluated the prospective interplay between these traits and AUD symptoms from adolescence to young adulthood., Method: The Minnesota Twin Family Study (N = 2,769) was used to examine the developmental interplay between AUD symptoms and three personality measures of constraint, negative emotionality, and aggressive undercontrol from ages 17 to 29., Results: Results from random-intercept, cross-lagged panel models showed that low constraint and aggressive undercontrol predicted subsequent rank-order increases in AUD symptoms from ages 17 to 24. AUD symptoms did not predict rank-order change in these traits from ages 17 to 24. There was support for both cross-effects from ages 24 to 29. Biometric analysis of the twin data showed genetic influences accounted for most of the phenotypic correlations over time., Conclusion: Results are consistent with the notion that personality traits related to low constraint and aggressive undercontrol are important vulnerability/predisposition factors for the development of early adult AUD. In later young adulthood, there is more evidence for the simultaneous codevelopment of personality and AUD. Implications are addressed with attention to personality-based risk assessments and targeted AUD prevention approaches., (© 2017 Wiley Periodicals, Inc.)

Temperament is a core aspect of children's psychological functioning and is assumed to be at least somewhat stable across childhood. However, little research has assessed the stability of temperament from early childhood to early adolescence. Moreover, few studies have examined the influence of measurement and analytic methods on the stability of early temperament over periods of more than a few years. We obtained laboratory observations and mother and father reports of temperamental negative and positive emotionality and effortful control from 559 three-year olds. Approximately 9 years later, children and both parents completed questionnaire measures of similar temperament constructs. Zero-order correlations revealed greater within- than cross-informant stability. In addition, compared to parent reports, early childhood laboratory measures showed greater convergent and divergent validity with child, mother, and father reports at age 12. Finally, latent temperament variables at age 3 composed of laboratory and parent-report measures and latent variables at age 12 composed of parent and child reports showed moderate stability. There was also a weak but significant association of early effortful control with later negative and positive emotionality. Results have implications for assessing temperament and knowledge of the stability of temperament across childhood.

Combination therapy will soon become a reality, particularly for those patients requiring poly-therapy to treat co-existing disease states. This becomes all the more important with the increasing cost, time and complexity of the drug discovery process prompting one to look at new delivery systems to increase the efficacy, safety and patient compliance of existing drugs. Along this line, we attempted to design nano-scale systems for simultaneous encapsulation of cyclosporine A (CsA) and coenzyme Q10 (CoQ10) and model their encapsulation and release kinetics. The in vitro characterization of the co-encapsulated nanoparticles revealed that the surfactant nature, concentration, external phase volume, droplet size reduction method and drug loading concentration can all influence the overall performance of the nanoparticles. The semi-quantitative solubility study indicates the strong influence of CoQ10 on CsA entrapment which was thought to be due to an increase in the lipophilicity of the overall system. The in vitro dissolution profile indicates the influence of CoQ10 on CsA release (64%) to that of individual particles of CsA, where the release is faster and higher (86%) on 18th day. The attempts to model the encapsulation and release kinetics were successful, offering a possibility to use such models leading to high throughput screening of drugs and their nature, alone or in combination for a particular polymer, if chi-parameters are understood.

This article details the development and methodological characteristics of the Systemic Therapy Inventory of Change (STIC), the first measurement system designed to assess change in family, couple, and individual therapy from a multisystemic and multidimensional perspective. The article focuses specifically on the developmental process that resulted in the five valid and reliable scales that comprise the core measure of the system, the INITIAL STIC, which is administered to clients just before beginning therapy. The scales focus on five systemic domains: individual adult, family of origin, couple, family, and individual child. This article describes the five system scales, the results of the factor analytic process that created them, as well as data on their convergent and discriminant validity.

Objective: To evaluate whether the adult smoking rate changed in Lexington-Fayette County, Kentucky, following the enactment of a smoke-free public places ordinance., Methods: Behavioral Risk Factor Surveillance System (BRFSS) data from 2001-2005 were used to test whether smoking rates changed in Fayette County from the pre- to post-law period, relative to the change in 30 Kentucky counties with similar demographics. The sample consisted of 10,413 BRFSS respondents: 7139 pre-law (40 months) and 3274 post-law (20 months)., Results: There was a 31.9% decline in adult smoking in Fayette County (25.7% pre-law to 17.5% post-law). In the group of 30 Control counties, the rate was 28.4% pre-law and 27.6% post-law. Controlling for seasonality, time trend, age, gender, ethnicity, education, marital status, and income, there was a significant Time (pre- vs. post-law) by Group (Fayette vs. Controls) interaction. There were an estimated 16,500 fewer smokers in Fayette County during post-law compared to pre-law., Conclusion: There was a significant effect of smoke-free legislation on adult smoking rates.

Previous studies documented that human bladder cancer cells are sensitive to the apoptotic effects of quinazoline-derived α1-adrenoreceptor antagonists and bladder tumors exhibit reduced tissue vascularity in response to terazosin. More recent evidence suggests that exposure to quinazoline α1-adrenorecptor antagonists leads to a significant reduction in prostate cancer incidence. This retrospective observational cohort study was conducted to determine whether male patients treated with quinazoline α1-adrenoceptor antagonists for either benign prostate hyperplasia (BPH) or hypertension have a decreased risk of developing bladder cancer. Review of the medical records of all male patients enrolled at the Lexington Veterans Administration (VA) Medical Center identified men exposed to quinazoline-based α1-adrenoceptor antagonists (Jan 1, 1998-Dec 31, 2002) for either hypertension and/or benign prostate obstructive symptoms. The whole group of 27,138 male patients was linked to the Markey Cancer Center's Kentucky Cancer Registry (KCR), part of the NCI's Surveillance, Epidemiology, and End Results (SEER) Program, to identify all incident bladder cancer cases diagnosed in this population. Measures of disease incidence, relative risk, and attributable risk were calculated to compare the risk of developing bladder cancer for α1-blocker-exposed versus unexposed men. A two-by-two contingency table of α1-antagonist exposure versus bladder cancer diagnoses was constructed and the relative risk was calculated. Our analysis revealed a cumulative bladder cancer incidence of 0.24% among the α1-blocker-exposed men compared to 0.42% in the unexposed group. Thus, there was a risk difference of -0.0018, which indicates that 1.8 fewer bladder cancer cases developed per 1000 exposed men. Alternatively stated, 556 men would need to be treated with quinazoline α1-blockers to prevent one case of bladder cancer. Exposure to quinazoline α1-blockers thus may have prevented 7 to 8 bladder cancer cases among the 4173 treated men during the study period. The data yield an unadjusted risk ratio of 0.57 (95% CI: 0.30, 1.08) and therefore, men treated with α1-adrenoreceptor antagonists have a 43% lower relative risk of developing bladder cancer than unexposed men (p=0.083). Our inability to determine person-years at risk of developing bladder cancer for each unexposed control patient, was a limitation for calculating an incidence ratio and rate difference. These results offer an initial indication that exposure to doxazosin and terazosin decreases the incidence of bladder cancer. This is the first epidemiological evidence that the anti-tumor action of quinazoline-based α1-antagonists may potentially translate into a protective effect from bladder cancer development.

Following traumatic injury, patients suffer from compromised immunity increasing their susceptibility to infection. Previous studies from this laboratory demonstrated that female BALB/c mice subjected to a 15% total body surface area (TBSA) scald injury exhibit a decrease in cell-mediated immunity 10 days post-burn. Studies described herein revealed that concanavalin A (Con A; 2 microg/ml)-stimulated splenocytes from sham treated animals produced 3557+/-853 pg/ml of IFN-gamma while splenocytes from burn injured animals released two-fold more cytokine (P<0.05). To determine whether leukocyte production of IFN-gamma was under the influence of macrophages, splenic macrophage supernatants generated from burned animals were incubated with splenic lymphocytes from sham and burn animals. The amount of IFN-gamma released by lymphocytes from sham animals increased when cultured with macrophages from burned mice (P<0.05). This suggests that the increase in IFN-gamma production by unfractionated splenocytes in burned mice relative to sham treated animals is macrophage-dependent. Macrophage supernatants from burned mice released twice as much IL-6 as supernatants from sham animals (P<0.05), and when IL-6 was blocked in vivo, the amount of IFN-gamma production in burned mice decreased to sham levels (P<0.05). Thus, IL-6 mediates IFN-gamma production following burn., (Copyright 2000 Academic Press.)

Background: Previous studies from this laboratory reported that suppression of cell-mediated immune function was coincident with elevated interleukin (IL)-6 production after acute ethanol exposure before burn trauma, compared with either insult alone. The goal of this study was to investigate whether treatment with an anti-IL-6 antibody could restore immunocompetence in mice subjected to burn trauma with previous exposure to alcohol, as assessed by delayed-type hypersensitivity (DTH) and mitogen-induced splenocyte proliferative responses., Methods: Mice given an ethanol treatment designed to reach a blood alcohol level of 100 mg/dl before a 15% total body surface area burn injury were treated with an anti-IL-6 antibody at 30 min and 24 hr postinjury., Results: Burn/ethanol mice exhibited a 91% suppression of the DTH response ( < 0.01) and a 76% suppression of mitogen-induced splenocyte proliferation (p < 0.01) at 48 hr postinjury, along with increased levels of circulating and splenic macrophage-derived IL-6, compared with all other treatment groups. After anti-IL-6 antibody administration to burn/ethanol mice, there was a 25% (p < 0.05) and 63% (p < 0.01) recovery of the DTH and splenocyte proliferative responses, respectively. Addition of exogenous IL-6 to splenocyte cultures isolated from anti-IL-6 antibody-treated burn/ethanol mice resulted in a 70% inhibition of mitogen-induced proliferative responses (p < 0.03)., Conclusions: These data confirm previous findings that burn in combination with acute ethanol exposure suppresses cell-mediated immune function compared with either insult alone. Furthermore, the ability of the anti-IL-6 antibody treatment to improve cellular immune responses in the burn/ethanol group suggests that blocking this cytokine may be beneficial for the ethanol-exposed, thermally injured individual.

This paper deals with determining the optimal level of purchase of intravenous fluids for hospitals by utilizing inventory control concepts. Using the conceptual framework of the economic order quantity (EOQ) model, the hospital administrators can elicit the efficient materials management, thus reducing both the space and capital requirements without compromising the quality of services rendered.

Abnormal inheritance of the sex determining region, normally located on Yp, results in about 1 in 20,000 phenotypic males with a 46,XX genotype. Studies to date indicate that many 46,XX males apparently arise due to a balanced, yet abnormal, nonhomologous interchange of Xp and Yp termini. However, 2 of the 5 XX males we report here have 3 copies of the pseudoautosomal locus, MIC2. Thus, they appear to have inherited the sex determining region as a result of Yp sequences being added onto the X pseudoautosomal region. Such an unequal, extremely nonhomologous interchange could alternatively be considered to arise from an unbalanced translocation of Yp to Xp. Our results suggest that very unequal interchange or translocation of Yp sequences onto the X pseudoautosomal region is not as rare a mechanism for XX males as originally thought. We also suggest that sex vesicle "entrapment" favors the association of a Yp fragment to the X pseudoautosomal region over a translocation to either Xq or an autosome.

Mice provide material for studies of Y-chromosomal and autosomal sequences involved in sex determination. Eicher and coworkers have identified four subregions in the mouse Y chromosome, one of which corresponds to the Sxr fragment. This fragment demonstrates that only a small portion of the Y is necessary for male sex determination. The mouse Y chromosome also shows variants: the BALB/cWt Y chromosome, which causes nondisjunction of the Y in some germ cells leading to XO and XYY cells and resulting in many infertile true hermaphrodites; the YDom, a wild-type chromosome which can result in sex reversal on a C57BL/6J background; and Y-chromosomal variants detected with Y-derived genomic DNA clones among inbred strains. Two different autosomal loci affecting sex differentiation have been identified in the mouse by Eicher and coworkers. The first of these has not been mapped to a particular chromosome and has been designated Tda-1 (Testis-determining autosomal-1). This is the locus in C57BL/6J mice at which animals must be homozygous in order to develop as true hermaphrodites or sex-reversed animals in the presence of YDom. The other locus has been identified on proximal chromosome 17. This locus also caused hermaphrodites on the C57BL/6J background and it is most easily interpreted as a locus deleted in Thp. It is located in a region on chromosome 17 containing other genes or DNA sequences that may be related to sex determination. These include both the Hye (histocompatibility Y expression) locus that affects the amount of male-specific antigen detected by serological and cell-mediated assays and a concentration of Bkm sequences.(ABSTRACT TRUNCATED AT 250 WORDS)

The possible role of GATA/GACA repeated sequences in mammalian sex determination was investigated using Northern analyses of mouse and human RNA. Brain, liver, and gonadal RNA from three developmental stages of mice of both sexes and also human fetal RNA from various tissues were hybridized to both sense and antisense Bkm riboprobes as well as to the synthetic oligonucleotide (GATA)5. At low levels of stringency, putative transcripts of various sizes were observed in all tissue samples with all probes. At high stringency, only a putative transcript of approximately 12 kb was observed, but this was later shown to consist of contaminating DNA. No sex-specific differences were observed in any tissue or developmental stage. Thus, we find no evidence that the GATA/GACA repeated sequences are specifically expressed in quantities detectable by Northern analyses in a manner important to mammalian sex determination.