Publications by authors named "Keith Humphreys"

345 Publications

Lymph node metastases in breast cancer: Investigating associations with tumor characteristics, molecular subtypes and polygenic risk score using a continuous growth model.

Int J Cancer 2021 09 21;149(6):1348-1357. Epub 2021 Jun 21.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

We investigate the association between rate of breast cancer lymph node spread and grade, estrogen receptor (ER) status, progesteron receptor status, decision tree derived PAM50 molecular subtype and a polygenic risk score (PRS), using data on 10 950 women included from two different data sources. Lymph node spread was analyzed using a novel continuous tumor progression model that adjusts for tumor volume in a biologically motivated way and that incorporates covariates of interest. Grades 2 and 3 tumors, respectively, were associated with 1.63 and 2.17 times faster rates of lymph node spread than Grade 1 tumors (P < 10 ). ER/PR negative breast cancer was associated with a 1.25/1.19 times faster spread than ER/PR positive breast cancer, respectively (P = .0011 and .0012). Among the molecular subtypes luminal A, luminal B, Her2-enriched and basal-like, Her2-enriched breast cancer was associated with 1.53 times faster spread than luminal A cancer (P = .00072). PRS was not associated with the rate of lymph node spread. Continuous growth models are useful for quantifying associations between lymph node spread and tumor characteristics. These may be useful for building realistic progression models for microsimulation studies used to design individualized screening programs.
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http://dx.doi.org/10.1002/ijc.33704DOI Listing
September 2021

College programming for students in addiction recovery: A PRISMA-guided scoping review.

Addict Behav 2021 10 24;121:106992. Epub 2021 May 24.

Stanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, 401 Quarry Rd, Stanford, CA 94305, United States; Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Ave (152-MPD), Palo Alto, CA 94304, United States.

Background: The health and well-being of students in recovery from substance use disorder are increasingly being recognized as a priority on college campuses. This scoping review maps the state of the existing literature evaluating collegiate recovery programming to highlight research gaps and inform policy.

Method: We conducted a systematic search of articles related to collegiate recovery programming published before August 2020. The 15 extracted study characteristics included publication type, study design, primary outcomes, reporting of behavioral addictions, mutual-help group attendance, sample demographic information, school size, ownership, and funding source.

Results: The PRISMA-guided search strategy identified 357 articles for abstract review; of 113 articles retained for full-text review, 54 studies met criteria for inclusion. Primary outcomes were coded into four domains: clinical, recovery experience, program characterization, and stigma. Most (57%) used quantitative observational designs and 41% employed qualitative research designs. Government or foundation grants funded 11% of the studies.

Conclusion: The domains identified offer a framework for healthcare providers, college administrators, and researchers to understand and improve programs, thereby better serving this vulnerable student group.
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http://dx.doi.org/10.1016/j.addbeh.2021.106992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259809PMC
October 2021

Comparison of Treatments for Cocaine Use Disorder Among Adults: A Systematic Review and Meta-analysis.

JAMA Netw Open 2021 May 3;4(5):e218049. Epub 2021 May 3.

Department of Neurosurgery, Stanford University, Stanford, California.

Importance: In the US and the United Kingdom, cocaine use is the second leading cause of illicit drug overdose death. Psychosocial treatments for cocaine use disorder are limited, and no pharmacotherapy is approved for use in the US or Europe.

Objective: To compare treatments for active cocaine use among adults.

Data Sources: PubMed and the Cochrane Database of Systematic Reviews were searched for clinical trials published between December 31, 1995, and December 31, 2017.

Study Selection: This meta-analysis was registered on Covidence.org (study 8731) on December 31, 2015. Clinical trials were included if they (1) had the term cocaine in the article title; (2) were published between December 31, 1995, and December 31, 2017; (3) were written in English; (4) enrolled outpatients 18 years or older with active cocaine use at baseline; and (5) reported treatment group size, treatment duration, retention rates, and urinalysis results for the presence of cocaine metabolites. A study was excluded if (1) more than 25% of participants were not active cocaine users or more than 80% of participants had negative test results for the presence of cocaine metabolites at baseline and (2) it reported only pooled urinalysis results indicating the presence of multiple substances and did not report the specific proportion of positive test results for cocaine metabolites. Multiple reviewers reached criteria consensus. Of 831 records screened, 157 studies (18.9%) met selection criteria and were included in the analysis.

Data Extraction And Synthesis: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline. Search results were imported from PubMed XML into Covidence.org then Microsoft Excel. Data extraction was completed in 2 iterations to ensure fidelity. Analyses included a multilevel random-effects model, a multilevel mixed-effects meta-regression model, and sensitivity analyses. Treatments were clustered into 11 categories (psychotherapy, contingency management programs, placebo, opioids, psychostimulants, anticonvulsants, dopamine agonists, antidepressants, antipsychotics, miscellaneous medications, and other therapies). Missing data were imputed using multiple imputation by chained equations. The significance threshold for all analyses was P = .05. Data were analyzed using the metafor and mice packages in R software, version 3.3.2 (R Foundation for Statistical Computing). Data were analyzed from January 1, 2018, to February 28, 2021.

Main Outcomes And Measures: The primary outcome was the intention-to-treat logarithm of the odds ratio (OR) of having a negative urinalysis result for the presence of cocaine metabolites at the end of each treatment period compared with baseline. The hypothesis, which was formulated after data collection, was that no treatment category would have a significant association with objective reductions in cocaine use.

Results: A total of 157 studies comprising 402 treatment groups and 15 842 participants were included. Excluding other therapies, the largest treatment groups across all studies were psychotherapy (mean [SD] number of participants, 40.04 [36.88]) and contingency management programs (mean [SD] number of participants, 37.51 [25.51]). Only contingency management programs were significantly associated with an increased likelihood of having a negative test result for the presence of cocaine (OR, 2.13; 95% CI, 1.62-2.80), and this association remained significant in all sensitivity analyses.

Conclusions And Relevance: In this meta-analysis, contingency management programs were associated with reductions in cocaine use among adults. Research efforts and policies that align with this treatment modality may benefit those who actively use cocaine and attenuate societal burdens.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.8049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105751PMC
May 2021

Cost-effectiveness of Treatments for Opioid Use Disorder.

JAMA Psychiatry 2021 07;78(7):767-777

Center for Innovation to Implementation, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, California.

Importance: Opioid use disorder (OUD) is a significant cause of morbidity and mortality in the US, yet many individuals with OUD do not receive treatment.

Objective: To assess the cost-effectiveness of OUD treatments and association of these treatments with outcomes in the US.

Design And Setting: This model-based cost-effectiveness analysis included a US population with OUD.

Interventions: Medication-assisted treatment (MAT) with buprenorphine, methadone, or injectable extended-release naltrexone; psychotherapy (beyond standard counseling); overdose education and naloxone distribution (OEND); and contingency management (CM).

Main Outcomes And Measures: Fatal and nonfatal overdoses and deaths throughout 5 years, discounted lifetime quality-adjusted life-years (QALYs), and costs.

Results: In the base case, in the absence of treatment, 42 717 overdoses (4132 fatal, 38 585 nonfatal) and 12 660 deaths were estimated to occur in a cohort of 100 000 patients over 5 years, and 11.58 discounted lifetime QALYs were estimated to be experienced per person. An estimated reduction in overdoses was associated with MAT with methadone (10.7%), MAT with buprenorphine or naltrexone (22.0%), and when combined with CM and psychotherapy (range, 21.0%-31.4%). Estimated deceased deaths were associated with MAT with methadone (6%), MAT with buprenorphine or naltrexone (13.9%), and when combined with CM, OEND, and psychotherapy (16.9%). MAT yielded discounted gains of 1.02 to 1.07 QALYs per person. Including only health care sector costs, methadone cost $16 000/QALY gained compared with no treatment, followed by methadone with OEND ($22 000/QALY gained), then by buprenorphine with OEND and CM ($42 000/QALY gained), and then by buprenorphine with OEND, CM, and psychotherapy ($250 000/QALY gained). MAT with naltrexone was dominated by other treatment alternatives. When criminal justice costs were included, all forms of MAT (with buprenorphine, methadone, and naltrexone) were associated with cost savings compared with no treatment, yielding savings of $25 000 to $105 000 in lifetime costs per person. The largest cost savings were associated with methadone plus CM. Results were qualitatively unchanged over a wide range of sensitivity analyses. An analysis using demographic and cost data for Veterans Health Administration patients yielded similar findings.

Conclusions And Relevance: In this cost-effectiveness analysis, expanded access to MAT, combined with OEND and CM, was associated with cost-saving reductions in morbidity and mortality from OUD. Lack of widespread MAT availability limits access to a cost-saving medical intervention that reduces morbidity and mortality from OUD. Opioid overdoses in the US likely reached a record high in 2020 because of COVID-19 increasing substance use, exacerbating stress and social isolation, and interfering with opioid treatment. It is essential to understand the cost-effectiveness of alternative forms of MAT to treat OUD.
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http://dx.doi.org/10.1001/jamapsychiatry.2021.0247DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8014209PMC
July 2021

Evaluation of State Cannabis Laws and Rates of Self-harm and Assault.

JAMA Netw Open 2021 03 1;4(3):e211955. Epub 2021 Mar 1.

Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.

Importance: State cannabis laws are changing rapidly. Research is inconclusive about their association with rates of self-harm and assault. Existing studies have not considered variations in cannabis commercialization across states over time.

Objective: To evaluate the association of state medical and recreational cannabis laws with self-harm and assault, overall and by age and sex, while considering varying degrees of commercialization.

Design, Setting, And Participants: Using a cohort design with panel fixed-effects analysis, within-state changes in claims for self-harm and assault injuries before and after changes in cannabis laws were quantified in all 50 US states and the District of Columbia. Comprehensive claims data on commercial and Medicare Advantage health plan beneficiaries from January 1, 2003, to December 31, 2017, grouped by state and month, were evaluated. Data analysis was conducted from January 31, 2020, to January 21, 2021.

Exposures: Categorical variable that indexed the degree of cannabis legalization in each state and month based on law type (medical or recreational) and operational status of dispensaries (commercialization).

Main Outcomes And Measures: Claims for self-harm and assault injuries based on International Classification of Diseases codes.

Results: The analysis included 75 395 344 beneficiaries (mean [SD] age, 47 [22] years; 50% female; and median follow-up, 17 months [interquartile range, 8-36 months]). During the study period, 29 states permitted use of medical cannabis and 11 permitted recreational cannabis. Point estimates for populationwide rates of self-harm and assault injuries were higher in states legalizing recreational cannabis compared with states with no cannabis laws, but these results were not statistically significant (adjusted rate ratio [aRR] assault, recreational dispensaries: 1.27; 95% CI, 0.79-2.03;self-harm, recreational dispensaries aRR: 1.15; 95% CI, 0.89-1.50). Results varied by age and sex with no associations found except for states with recreational policies and self-harm among males younger than 40 years (aRR <21 years, recreational without dispensaries: 1.70; 95% CI, 1.11-2.61; aRR aged 21-39 years, recreational dispensaries: 1.46; 95% CI, 1.01-2.12). Medical cannabis was generally not associated with self-harm or assault injuries populationwide or among age and sex subgroups.

Conclusions And Relevance: Recreational cannabis legalization appears to be associated with relative increases in rates of claims for self-harm among male health plan beneficiaries younger than 40 years. There was no association between cannabis legalization and self-harm or assault, for any other age and sex group or for medical cannabis. States that legalize but still constrain commercialization may be better positioned to protect younger male populations from unintended harms.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.1955DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7974641PMC
March 2021

Random effects models of lymph node metastases in breast cancer: quantifying the roles of covariates and screening using a continuous growth model.

Biometrics 2021 Jan 26. Epub 2021 Jan 26.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

We recently described a joint model of breast cancer tumor size and number of affected lymph nodes, which conditions on screening history, mammographic density, and mode of detection, and can be used to infer growth rates, time to symptomatic detection, screening sensitivity, and rates of lymph node spread. The model of lymph node spread can be estimated in isolation from measurements of tumor volume and number of affected lymph nodes, giving inference identical to the joint model. Here, we extend our model to include covariate effects. We also derive theoretical results in order to study the role of screening on lymph node metastases at diagnosis. We analyze the association between hormone replacement therapy (HRT) and breast cancer lymph node spread, using data from a case-control study designed specifically to study the effects of HRT on breast cancer. Using our method, we estimate that women using HRT at time of diagnosis have a 36% lower rate of lymph node spread than nonusers (95% confidence interval [CI] =(8%,58%)). This can be contrasted with the effect of HRT on the tumor growth rate, estimated here to be 15% slower in HRT users (95% CI = (-34%,+7%)). For screen-detected cancers, we illustrate how lead time can relate to lymph node spread; and using symptomatic cancers, we illustrate the potential consequences of false negative screens in terms of lymph node spread.
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http://dx.doi.org/10.1111/biom.13430DOI Listing
January 2021

Policy Responses to the Addiction Crisis.

J Health Polit Policy Law 2021 08;46(4):585-597

University of Chicago.

The COVID-19 pandemic is just one of two public health crises the new Biden administration will confront. The addiction crisis is the other. The opioid epidemic has already killed more Americans than World Wars I and II combined. And it is but the most visible sign of a broader population health challenge that includes methamphetamine, cocaine, benzodiazepines, and alcohol. This article presents practical legislative and executive actions that are required for addressing these challenges. The authors focus on two broad policy challenges: (1) improving financing and delivery of treatment for substance use disorders, and (2) reducing population exposure to addictive and lethal substances. Through both of these channels, a portfolio of well-implemented, evidence-informed policies can save many thousands of lives every year.
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http://dx.doi.org/10.1215/03616878-8970796DOI Listing
August 2021

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

N Engl J Med 2021 02 20;384(5):428-439. Epub 2021 Jan 20.

The authors' affiliations are as follows: the Centre for Cancer Genetic Epidemiology, Departments of Public Health and Primary Care (L.D., S. Carvalho, J.A., K.A.P., Q.W., M.K.B., J.D., B.D., N. Mavaddat, K. Michailidou, A.C.A., P.D.P.P., D.F.E.) and Oncology (C.L., P.A.H., C. Baynes, D.M.C., L.F., V.R., M. Shah, P.D.P.P., A.M.D., D.F.E.), University of Cambridge, Cambridge, the Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A. Campbell, D.J.P.), and the Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology (D.J.P.), University of Edinburgh, the Cancer Research UK Edinburgh Centre (D.A.C., J.F.), and the Usher Institute of Population Health Sciences and Informatics, University of Edinburgh Medical School (A. Campbell, J.F.), Edinburgh, the Divisions of Informatics, Imaging, and Data Sciences (E.F.H.), Cancer Sciences (A. Howell), Population Health, Health Services Research, and Primary Care (A. Lophatananon, K. Muir), and Evolution and Genomic Sciences, School of Biological Sciences (W.G.N., E.M.V., D.G.E.), University of Manchester, the NIHR Manchester Biomedical Research Unit (E.F.H.) and the Nightingale Breast Screening Centre, Wythenshawe Hospital (E.F.H., H.I.), Academic Health Science Centre and North West Genomics Laboratory Hub, and the Manchester Centre for Genomic Medicine, St. Mary's Hospital, Manchester University NHS Foundation Trust (W.G.N., E.M.V., D.G.E.), Manchester, the School of Cancer and Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London (E.J.S.), the Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham (I.T.), and the Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford (I.T.) - all in the United Kingdom; the Human Genotyping-CEGEN Unit, Human Cancer Genetic Program (A.G.-N., M.R.A., N.Á., B.H., R.N.-T.), and the Human Genetics Group (V.F., A.O., J.B.), Spanish National Cancer Research Center, Centro de Investigación en Red de Enfermedades Raras (A.O., J.B.), Servicio de Oncología Médica, Hospital Universitario La Paz (M.P.Z.), and Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (M. de la Hoya), Madrid, the Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago (A. Carracedo, M.G.-D.), and Centro de Investigación en Red de Enfermedades Raras y Centro Nacional de Genotipado, Universidad de Santiago de Compostela (A. Carracedo), Santiago de Compostela, the Oncology and Genetics Unit, Instituto de Investigacion Sanitaria Galicia Sur, Xerencia de Xestion Integrada de Vigo-Servizo Galeo de Saúde, Vigo (J.E.C.), and Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo (J.I.A.P.) - all in Spain; the Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund (C. Wahlström, J.V., M.L., T. Törngren, Å.B., A.K.), the Department of Oncology, Örebro University Hospital, Örebro (C. Blomqvist), and the Departments of Medical Epidemiology and Biostatistics (K.C., M.E., M.G., P. Hall, W.H., K.H.), Oncology, Södersjukhuset (P. Hall, S. Margolin), Molecular Medicine and Surgery (A. Lindblom), and Clinical Science and Education, Södersjukhuset (S. Margolin, C. Wendt), Karolinska Institutet, and the Department of Clinical Genetics, Karolinska University Hospital (A. Lindblom), Stockholm - all in Sweden; the Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD (M.T.P., C.F., G.C.-T., A.B.S.), the Cancer Epidemiology Division, Cancer Council Victoria (G.G.G., R.J.M., R.L.M.), the Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (G.G.G., R.J.M., R.L.M.), and the Department of Clinical Pathology (M.C.S.), University of Melbourne, Anatomical Pathology, Alfred Hospital (C.M.), and the Cancer Epidemiology Division, Cancer Council Victoria (M.C.S.), Melbourne, VIC, and Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC (G.G.G., M.C.S., R.L.M.) - all in Australia; the Division of Molecular Pathology (R.K., S. Cornelissen, M.K.S.), Family Cancer Clinic (F.B.L.H., L.E.K.), Department of Epidemiology (M.A.R.), and Division of Psychosocial Research and Epidemiology (M.K.S.), the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, Division Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center, Utrecht (M.G.E.M.A.), the Department of Clinical Genetics, Erasmus University Medical Center (J.M.C., A.M.W.O.), and the Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute (B.A.M.H.-G., A. Hollestelle, M.J.H.), Rotterdam, the Department of Clinical Genetics, Maastricht University Medical Center, Maastricht (E.B.G.G.), the Departments of Human Genetics (I.M.M.L., M.P.G.V., P.D.), Clinical Genetics (C.J.A.), and Pathology (P.D.), Leiden University Medical Center, Leiden, the Department of Human Genetics, Radboud University Medical Center, Nijmegen (A.R.M.), and the Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen (J.C.O.) - all in the Netherlands; the Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute (B.D.), and the Division of Cancer Epidemiology and Genetics, National Cancer Institute (T.A., S.J.C., X.R.Y., M.G.-C.), National Institutes of Health, Bethesda, MD; the Department of Pathology, Brigham and Women's Hospital, Harvard Medical School (B.D.), and the Department of Nutrition, Harvard T.H. Chan School of Public Health (R.M.V.D.), Boston; the Departments of Clinical Genetics (K.A.), Oncology (C. Blomqvist), and Obstetrics and Gynecology (H.N., M. Suvanto), Helsinki University Hospital, University of Helsinki, Helsinki, and the Unit of Clinical Oncology, Kuopio University Hospital (P. Auvinen), the Institute of Clinical Medicine, Oncology (P. Auvinen), the Translational Cancer Research Area (J.M.H., V.-M.K., A. Mannermaa), and the Institute of Clinical Medicine, Pathology, and Forensic Medicine (J.M.H., V.-M.K., A. Mannermaa), University of Eastern Finland, and the Biobank of Eastern Finland, Kuopio University Hospital (V.-M.K., A. Mannermaa), Kuopio - both in Finland; the N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus (N.N.A., N.V.B.); the Department of Gynecology and Obstetrics and Institute of Clinical Molecular Biology, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Kiel (N.A.), the Institute of Medical Biometry and Epidemiology (H. Becher) and Cancer Epidemiology Group (T.M., J.C.-C.), University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, the Department of Gynecology and Obstetrics (M.W.B., P.A.F., L.H.) and Institute of Human Genetics (A.B.E.), University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Erlangen, the Division of Cancer Epidemiology (S.B., A. Jung, P.M.K., J.C.-C.), Molecular Epidemiology Group, C080 (B. Burwinkel, H.S.), Division of Pediatric Neurooncology (A.F.), and Molecular Genetics of Breast Cancer (U.H., M.M., M.U.R., D.T.), German Cancer Research Center, Molecular Biology of Breast Cancer, University Women's Clinic Heidelberg, University of Heidelberg (B. Burwinkel, A.S., H.S.), Hopp Children's Cancer Center (A.F.), Faculty of Medicine, University of Heidelberg (P.M.K.), and National Center for Tumor Diseases, University Hospital and German Cancer Research Center (A.S., C.S.), Heidelberg, the Department of Radiation Oncology (N.V.B., M. Bremer, H.C.) and the Gynecology Research Unit (N.V.B., T.D., P. Hillemanns, T.-W.P.-S., P.S.), Hannover Medical School, Hannover, the Institute of Human Genetics, University of Münster, Münster (N.B.-M.), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart (H. Brauch, W.-Y.L.), iFIT-Cluster of Excellence, University of Tübingen, and the German Cancer Consortium, German Cancer Research Center, Partner Site Tübingen (H. Brauch), and the University of Tübingen (W.-Y.L.), Tübingen, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum (T.B.), Institute for Medical Informatics, Statistics, and Epidemiology, University of Leipzig, Leipzig (C.E.), Center for Hereditary Breast and Ovarian Cancer (E.H., R.K.S.) and Center for Integrated Oncology (E.H., R.K.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, the Department of Internal Medicine, Evangelische Kliniken Bonn, Johanniter Krankenhaus, Bonn (Y.-D.K.), the Department of Gynecology and Obstetrics, University of Munich, Campus Großhadern, Munich (A. Meindl), and the Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe (T.R.) - all in Germany; the Gynecological Cancer Registry, Centre Georges-François Leclerc, Dijon (P. Arveux), and the Center for Research in Epidemiology and Population Health, Team Exposome and Heredity, INSERM, University Paris-Saclay, Villejuif (E.C.-D., P.G., T. Truong) - both in France; the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences (M. Bermisheva, E.K.), the Department of Genetics and Fundamental Medicine, Bashkir State University (E.K., D.P., Y.V.), and the Ufa Research Institute of Occupational Health and Human Ecology (Y.V.), Ufa, Russia; the Department of Genetics and Pathology (K.B., A. Jakubowska, J. Lubiński, K.P.) and the Independent Laboratory of Molecular Biology and Genetic Diagnostics (A. Jakubowska), Pomeranian Medical University, Szczecin, Poland; the Copenhagen General Population Study, the Department of Clinical Biochemistry (S.E.B., B.G.N.), and the Department of Breast Surgery (H.F.), Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, and the Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen (S.E.B., B.G.N.) - both in Denmark; the Division of Cancer Prevention and Genetics, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) (B. Bonanni), the Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (S. Manoukian), the Genome Diagnostics Program, FIRC Institute of Molecular Oncology (P.P.), and the Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (P.R.), Milan; the Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet (A.-L.B.-D., G.I.G.A., V.N.K.), and the Institute of Clinical Medicine, Faculty of Medicine, University of Oslo (A.-L.B.-D., V.N.K.), Oslo; Medical Faculty, Universidad de La Sabana (I.B.), and the Clinical Epidemiology and Biostatistics Department (F.G.) and Institute of Human Genetics (D.T.), Pontificia Universidad Javeriana, Bogota, Colombia; the Department of Internal Medicine and Huntsman Cancer Institute, University of Utah (N.J.C., M.J.M., J.A.W.), and the Intermountain Healthcare Biorepository and Department of Pathology, Intermountain Healthcare (M.H.C.), Salt Lake City; the David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California, Los Angeles (P.A.F.), and Moores Cancer Center (M.G.-D., M.E.M.) and the Department of Family Medicine and Public Health (M.E.M.), University of California San Diego, La Jolla; the Departments of Medical Oncology (V.G., D.M.) and Pathology (M.T.), University Hospital of Heraklion, Heraklion, and the Department of Oncology, University Hospital of Larissa, Larissa (E.S.) - both in Greece; the Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital (G.G., I.L.A.), the Departments of Laboratory Medicine and Pathobiology (A.M.M.) and Molecular Genetics (I.L.A.), University of Toronto, and the Laboratory Medicine Program, University Health Network (A.M.M.), Toronto, and the Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Québec City, QC (J.S.) - both in Canada; the Department of Electron Microscopy and Molecular Pathology (A. Hadjisavvas, K.K., M.A.L.), the Cyprus School of Molecular Medicine (A. Hadjisavvas, K.K., M.A.L., K. Michailidou), and the Biostatistics Unit (K. Michailidou), Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus; the Saw Swee Hock School of Public Health (M. Hartman, R.M.V.D.) and the Department of Medicine, Yong Loo Lin School of Medicine (R.M.V.D.), National University of Singapore, the Department of Surgery, National University Health System (M. Hartman, J. Li), and the Human Genetics Division, Genome Institute of Singapore (J. Li), Singapore; the Department of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia (W.K.H.), and the Breast Cancer Research Programme, Cancer Research Malaysia (W.K.H., P.S.N., S.-Y.Y., S.H.T.), Selangor, and the Breast Cancer Research Unit, Cancer Research Institute (N.A.M.T.), and the Department of Surgery, Faculty of Medicine (N.A.M.T., P.S.N., S.H.T.), University Malaya, Kuala Lumpur - both in Malaysia; Surgery, School of Medicine, National University of Ireland, Galway (M.J.K., N. Miller); the Department of Surgery, Daerim Saint Mary's Hospital (S.-W.K.), the Department of Surgery, Ulsan University College of Medicine and Asan Medical Center (J.W.L.), the Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital (M.H.L.), Integrated Major in Innovative Medical Science, Seoul National University College of Medicine (S.K.P.), and the Cancer Research Institute, Seoul National University (S.K.P.), Seoul, South Korea; the Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore, Pakistan (M.U.R.); and the National Cancer Institute, Ministry of Public Health, Nonthaburi, Thailand (S.T.).

Background: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

Methods: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

Results: Protein-truncating variants in 5 genes (, , , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (, , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in and , odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in , , , , , and , odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in , , and were associated with a risk of breast cancer overall with a P value of less than 0.001. For , , and , missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

Conclusions: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).
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http://dx.doi.org/10.1056/NEJMoa1913948DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611105PMC
February 2021

Primary Care Physicians and Spending on Low-Value Care.

Ann Intern Med 2021 06 19;174(6):875-878. Epub 2021 Jan 19.

Center for Professionalism and Value in Health Care, Washington, DC.

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http://dx.doi.org/10.7326/M20-6257DOI Listing
June 2021

Analysis of unused prescription opioids and benzodiazepines remaining after death among Medicare decedents.

Drug Alcohol Depend 2021 02 2;219:108502. Epub 2021 Jan 2.

Icahn School of Medicine at Mount Sinai, United States.

Background: Millions of opioid and benzodiazepine prescriptions are dispensed near end-of-life. After death, patients' unused prescription pills belong to family members, who often save rather than dispose of them. We sought to quantify this exposure in Medicare beneficiaries.

Methods: We estimated the share of decedent Medicare beneficiaries who potentially left behind opioid or benzodiazepine pills at the time of death using Part D claims of a 20 % national sample of Medicare beneficiaries between 2006-2015 linked to the National Death Index.

Results: We estimated that 1 in 6 Medicare beneficiaries who died between 2006-2015 potentially left behind opioid pills, and 1 in 10 who died between 2013-2015 potentially left benzodiazepines as well. Leftover pills were more common among younger, dually enrolled, and lower-income beneficiaries, as well as beneficiaries living in non-urban areas and those with a history of mental illness, drug use disorders, and chronic pain. North American Natives and Non-Hispanic Whites had higher proportions than Black, Hispanic, and Asian decedents.

Conclusions: Opioids and benzodiazepines are commonly left behind at death. Policies and interventions that encourage comprehensive and safe medication disposal after death may reduce risk for intra-household diversion and misuse of prescription opioids and benzodiazepines.
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http://dx.doi.org/10.1016/j.drugalcdep.2020.108502DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914112PMC
February 2021

Emerging Characteristics of Isotonitazene-Involved Overdose Deaths: A Case-Control Study.

J Addict Med 2020 Nov 23. Epub 2020 Nov 23.

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (CLS); Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA (TOF); Brown University, Providence, RI (RBF); Veterans Affairs Palo Alto Health Care System, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA (KH).

Objectives: Case reports of fatal overdoses involving the novel synthetic opioid isotonitazene have prompted the U.S. Drug Enforcement Administration to consider an emergency scheduling of the drug in June 2020. We aimed to epidemiologically characterize deaths involving isotonitazene.

Methods: We conducted a case control study using publicly available mortality records from January 1, 2020 to July 31, 2020 in Cook County, IL and Milwaukee County, WI. Cases (all deaths involving isotonitazene) and controls (all deaths involving other synthetic opioids) were compared on demographic characteristics, number of substances involved in fatal overdose, and co-involvement of other substances.

Results: We identified 40 fatal overdoses involving isotonitazene and 981 fatal overdoses involving other synthetic opioids. Isotonitazene deaths involved a significantly greater number of substances, and were significantly more likely to involve the designer benzodiazepine flualprazolam.

Discussion: Isotonitazene was involved in a substantial minority of synthetic opioid overdose deaths in the first 7 months of 2020. Future studies characterizing its prevalence in other markets are warranted. Emergence of highly potent novel synthetic opioids underscore the need for comprehensive health services for people with opioid use disorder.
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http://dx.doi.org/10.1097/ADM.0000000000000775DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141068PMC
November 2020

Depression, Alcoholics Anonymous Involvement, and Daily Drinking Among Patients with co-occurring Conditions: A Longitudinal Parallel Growth Mixture Model.

Alcohol Clin Exp Res 2020 12 26;44(12):2570-2578. Epub 2020 Oct 26.

From the, Department of Psychiatry and Behavioral Sciences (NAV, KH, CT), Stanford University School of Medicine, Stanford, California, USA.

Background: Patients with cooccurring mental health and substance use disorders often find it difficult to sustain long-term recovery. One predictor of recovery may be how depression symptoms and Alcoholics Anonymous (AA) involvement influence alcohol consumption during and after inpatient psychiatric treatment. This study utilized a parallel growth mixture model to characterize the course of alcohol use, depression, and AA involvement in patients with cooccurring diagnoses.

Methods: Participants were adults with cooccurring disorders (n = 406) receiving inpatient psychiatric care as part of a telephone monitoring clinical trial. Participants were assessed at intake, 3-, 9-, and 15-month follow-up.

Results: A 3-class solution was the most parsimonious based upon fit indices and clinical relevance of the classes. The classes identified were high AA involvement with normative depression (27%), high stable depression with uneven AA involvement (11%), and low AA involvement with normative depression (62%). Both the low and high AA classes reduced their drinking across time and were drinking at less than half their baseline levels at all follow-ups. The high stable depression class reported an uneven pattern of AA involvement and drank at higher daily frequencies across the study timeline. Depression symptoms and alcohol use decreased substantially from intake to 3 months and then stabilized for 90% of patients with cooccurring disorders following inpatient psychiatric treatment.

Conclusions: These findings can inform future clinical interventions among patients with cooccurring mental health and substance use disorders. Specifically, patients with more severe symptoms of depression may benefit from increased AA involvement, whereas patients with less severe symptoms of depression may not.
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http://dx.doi.org/10.1111/acer.14474DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863278PMC
December 2020

Will hope triumph over experience in pharmacotherapy research on cocaine use disorder?

Authors:
Keith Humphreys

Addiction 2021 04 19;116(4):712-714. Epub 2020 Oct 19.

VA Palo Alto Health Care System and Stanford University, Palo Alto, CA, USA.

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http://dx.doi.org/10.1111/add.15266DOI Listing
April 2021

Steep increases in fentanyl-related mortality west of the Mississippi River: Recent evidence from county and state surveillance.

Drug Alcohol Depend 2020 11 28;216:108314. Epub 2020 Sep 28.

Dept of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA, 94305, USA; Veterans Affairs Palo Alto Health Care System, 795 Willow Rd., Menlo Park, CA, 94025, USA. Electronic address:

Background: Overdose deaths from synthetic opioids (e.g., fentanyl) increased 10-fold in the United States from 2013 to 2018, despite such opioids being rare in illicit drug markets west of the Mississippi River. Public health professionals have feared a "fentanyl breakthrough" in western U.S. drug markets could further accelerate overdose mortality. We evaluated the number and nature of western U.S. fentanyl deaths using the most recent data available.

Methods: We systematically searched jurisdictions west of the Mississippi River for publicly available data on fentanyl-related deaths since 2018, the most recent Centers for Disease Control and Prevention (CDC) statistics. Using mortality data from 2019 and 2020, we identified changes in fentanyl-related mortality rate and proportion of fatal heroin-, stimulant, and prescription pill overdoses involving fentanyl.

Results: Seven jurisdictions had publicly available fentanyl death data through December 2019 or later: Arizona; California; Denver County, CO; Harris County, TX; King County, WA; Los Angeles County, CA; and Dallas-Fort Worth, TX (Denton, Johnson, Parker, and Tarrant counties). All reported increased fentanyl deaths over the study period. Their collective contribution to national synthetic narcotics mortality increased 371 % from 2017 to 2019. Available 2020 data shows a 63 % growth in fentanyl-mortality over 2019. Fentanyl-involvement in heroin, stimulant, and prescription pill deaths has substantially grown.

Discussion: Fentanyl has spread westward, increasing deaths in the short-term and threatening to dramatically worsen the nation's already severe opioid epidemic in the long-term. Increasing the standard dose of naloxone, expanding Medicaid, improving coverage of addiction treatment, and public health educational campaigns should be prioritized.
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http://dx.doi.org/10.1016/j.drugalcdep.2020.108314DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521591PMC
November 2020

Mammography features for early markers of aggressive breast cancer subtypes and tumor characteristics: A population-based cohort study.

Int J Cancer 2021 03 6;148(6):1351-1359. Epub 2020 Oct 6.

Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna, Sweden.

Current breast cancer risk models identify mostly less aggressive tumors, although only women developing fatal breast cancer will greatly benefit from early identification. Here, we evaluated the use of mammography features (microcalcification clusters, computer-generated Breast Imaging Reporting and Data System [cBIRADS] density and lack of breast density reduction) as early markers of aggressive subtypes and tumor characteristics. Mammograms were retrieved from a population-based cohort of women that were diagnosed with breast cancer from 2001 to 2008 in Stockholm-Gotland County, Sweden. Tumor and patient characteristics were obtained from Stockholm Breast Cancer Quality Register and the Swedish Cancer Registry. Multinomial logistic regression was used to individually model each mammographic feature as a function of molecular subtypes, tumor characteristics and detection mode. A total of 4546 women with invasive breast cancer were included in the study. Women with microcalcification clusters in the affected breast were more likely to have human epidermal growth factor receptor 2 subtype (odds ratio [OR] 1.78; 95% confidence interval [CI] 1.24-2.54) and potentially less likely to have basal subtype (OR 0.54; 0.30-0.96) compared to Luminal A subtype. High mammographic cBIRADS showed association with larger tumor size and interval vs screen-detected cancers. Lack of density reduction was associated with interval vs screen-detected cancers (OR 1.43; 1.11-1.83) and potentially of Luminal B subtype vs Luminal A subtype (OR 1.76; 1.04-2.99). In conclusion, microcalcification clusters, cBIRADS density and lack of breast density reduction could serve as early markers of particular subtypes and tumor characteristics of breast cancer. This information has the potential to be integrated into risk models to identify women at risk for developing aggressive breast cancer in need of supplemental screening.
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http://dx.doi.org/10.1002/ijc.33309DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891615PMC
March 2021

Mammography features for early markers of aggressive breast cancer subtypes and tumor characteristics: A population-based cohort study.

Int J Cancer 2021 03 6;148(6):1351-1359. Epub 2020 Oct 6.

Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna, Sweden.

Current breast cancer risk models identify mostly less aggressive tumors, although only women developing fatal breast cancer will greatly benefit from early identification. Here, we evaluated the use of mammography features (microcalcification clusters, computer-generated Breast Imaging Reporting and Data System [cBIRADS] density and lack of breast density reduction) as early markers of aggressive subtypes and tumor characteristics. Mammograms were retrieved from a population-based cohort of women that were diagnosed with breast cancer from 2001 to 2008 in Stockholm-Gotland County, Sweden. Tumor and patient characteristics were obtained from Stockholm Breast Cancer Quality Register and the Swedish Cancer Registry. Multinomial logistic regression was used to individually model each mammographic feature as a function of molecular subtypes, tumor characteristics and detection mode. A total of 4546 women with invasive breast cancer were included in the study. Women with microcalcification clusters in the affected breast were more likely to have human epidermal growth factor receptor 2 subtype (odds ratio [OR] 1.78; 95% confidence interval [CI] 1.24-2.54) and potentially less likely to have basal subtype (OR 0.54; 0.30-0.96) compared to Luminal A subtype. High mammographic cBIRADS showed association with larger tumor size and interval vs screen-detected cancers. Lack of density reduction was associated with interval vs screen-detected cancers (OR 1.43; 1.11-1.83) and potentially of Luminal B subtype vs Luminal A subtype (OR 1.76; 1.04-2.99). In conclusion, microcalcification clusters, cBIRADS density and lack of breast density reduction could serve as early markers of particular subtypes and tumor characteristics of breast cancer. This information has the potential to be integrated into risk models to identify women at risk for developing aggressive breast cancer in need of supplemental screening.
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http://dx.doi.org/10.1002/ijc.33309DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891615PMC
March 2021

Computer-delivered brief alcohol intervention for patients with liver disease: a randomized controlled trial.

Addiction 2021 05 6;116(5):1076-1087. Epub 2020 Oct 6.

Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, CA, USA.

Background And Aims: Reducing alcohol consumption by liver disease patients can reduce morbidity and mortality. This study compared a computer-delivered brief alcohol intervention (cBAI) with standard care in a sample of US military veterans with liver disease.

Design: Multi-site, randomized controlled trial of a cBAI plus standard care (n = 67) versus standard care only (n = 71). Participants were assessed at baseline and 3- and 6-month follow-up.

Setting: US Veterans Health Administration liver clinics.

Participants: Participants were mostly male and diagnosed with hepatitis C.

Interventions And Comparators: A cBAI tailored to veterans with liver disease and consisting of assessment and personalized feedback. Standard care was brief education and advice about alcohol and liver disease.

Measurement: Primary outcomes were self-reported number of drinking days and unhealthy drinking days (defined as more than two drinks for men and more than one for women) in the past 30 days at 6-month follow-up. Secondary outcomes were these two variables at 3-month follow-up, and drinks consumed per drinking day, depression and overall health at 3- and 6-month follow-ups. Missing data were imputed using multiple imputation.

Findings: Compared with standard care, cBAI participants reported significantly fewer drinking days at 6-month follow-up and fewer unhealthy drinking days at both 3- and 6-month follow-ups. Least square means (LS-means) for number of drinking days were 3.78 for the cBAI condition and 6.89 for the standard care condition at 6 months [LS-mean ratio = 3.78/6.89 = 0.55, 95% confidence interval (CI) = 0.34, 0.89]. LS-means for number of unhealthy drinking days were 1.04 for the cBAI condition and 2.57 for the standard care condition at 3-month follow-up (LS-mean ratio = 1.04/2.57 = 0.41, 95% CI = 0.19, 0.85). At 6-months follow-up, LS-means were 1.18 for the cBAI condition and 2.75 for the standard care condition (LS-mean ratio = 1.18/2.75 = 0.43, 95% CI = 0.20, 0.91).

Conclusions: A computer-delivered brief alcohol intervention reduced drinking days and unhealthy drinking days at 6-month follow up in military veterans with liver disease compared with brief education and advice to reduce consumption.
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http://dx.doi.org/10.1111/add.15263DOI Listing
May 2021

Association between breast cancer risk and disease aggressiveness: Characterizing underlying gene expression patterns.

Int J Cancer 2021 02 5;148(4):884-894. Epub 2020 Sep 5.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

The association between breast cancer risk defined by the Tyrer-Cuzick score (TC) and disease prognosis is not well established. Here, we investigated the relationship between 5-year TC and disease aggressiveness and then characterized underlying molecular processes. In a case-only study (n = 2474), we studied the association of TC with molecular subtypes and tumor characteristics. In a subset of patients (n = 672), we correlated gene expression to TC and computed a low-risk TC gene expression (TC-Gx) profile, that is, a profile expected to be negatively associated with risk, which we used to test for association with disease aggressiveness. We performed enrichment analysis to pinpoint molecular processes likely to be altered in low-risk tumors. A higher TC was found to be inversely associated with more aggressive surrogate molecular subtypes and tumor characteristics (P < .05) including Ki-67 proliferation status (P < 5 × 10 ). Our low-risk TC-Gx, based on the weighted sum of 37 expression values of genes strongly correlated with TC, was associated with basal-like (P < 5 × 10 ), HER2-enriched subtype (P < 5 × 10 ) and worse 10-year breast cancer-specific survival (log-rank P < 5 × 10 ). Associations between low-risk TC-Gx and more aggressive molecular subtypes were replicated in an independent cohort from The Cancer Genome Atlas database (n = 975). Gene expression that correlated with low TC was enriched in proliferation and oncogenic signaling pathways (FDR < 0.05). Moreover, higher proliferation was a key factor explaining the association with worse survival. Women who developed breast cancer despite having a low risk were diagnosed with more aggressive tumors and had a worse prognosis, most likely driven by increased proliferation. Our findings imply the need to establish risk factors associated with more aggressive breast cancer subtypes.
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http://dx.doi.org/10.1002/ijc.33270DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818270PMC
February 2021

Impact of 12 step mutual help groups on drug use disorder patients across six clinical trials.

Drug Alcohol Depend 2020 10 4;215:108213. Epub 2020 Aug 4.

Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, 795 Willow Road (152), Menlo Park, CA, 94025 USA; Department of Surgery, Stanford University School of Medicine, 291 Campus Drive, Li Ka Shing Building, Stanford, CA, 94305 USA.

Background: 12 step mutual help groups are widely accessed by people with drug use disorder but infrequently subjected to rigorous evaluation. Pooling randomized trials containing a condition in which mutual help group attendance is actively facilitated presents an opportunity to assess the effectiveness of 12 step groups in large, diverse samples of drug use disorder patients.

Methods: Data from six federally-funded randomized trials were pooled (n = 1730) and subjected to two-stage instrumental variables modelling, and, fixed and random effects regression models. All trials included a 12 step group facilitation condition and employed the Addiction Severity Index as a core measure.

Results: The ability of 12 step facilitation to increase mutual help group participation among drug use disorder patients was minimal, limiting ability to employ two-stage instrumental variable models that correct for selection bias. However, traditional fixed and random effect regression models found that greater 12 step mutual help group attendance by drug use disorder patients predicted reduced use of and problems with illicit drugs and also with alcohol.

Conclusion: Facilitating significant and lasting involvement in 12 step groups may be more challenging for drug use disorder patients than for alcohol use disorder patients, which has important implications for clinical work and for effectiveness evaluations. Though selection bias could explain part of the results of traditional regression models, the finding that participation in 12 step mutual help groups predicts lower illicit drug and alcohol use and problems in a large, diverse, sample of drug use disorder patients is encouraging.
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http://dx.doi.org/10.1016/j.drugalcdep.2020.108213DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7502458PMC
October 2020

Debunking Cannabidiol as a Treatment for COVID-19: Time for the FDA to Adopt a Focused Deterrence Model?

Cureus 2020 Jun 17;12(6):e8671. Epub 2020 Jun 17.

Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, USA.

Many cannabidiol (CBD) retailers make unsupported medical claims about their product. In recent years, the U.S. Food and Drug Administration (FDA) has sent warning letters to CBD retailers who promoted CBD to treat Alzheimer's disease, cancer, diabetes, and other serious conditions for which there is no evidence of its efficacy as a treatment or preventive. Compliance with these warning letters has been low. During the novel coronavirus disease 2019 (COVID-19) pandemic, the FDA has begun sending more strongly worded warning letters that appear to have better compliance in that most of these companies have removed COVID-19-related claims. However, many continue to present other unsupported medical claims on other serious medical conditions like cancer, depression, addiction, and bone fractures, among many others. We argue that adopting a strategy of focused deterrence where the FDA prioritizes enforcement related to COVID-19 claims - but when COVID-19-related claims are found, pursues all other violations by that company - would present an opportunity to efficiently cut down on harmful claims overstating CBD's benefits.
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http://dx.doi.org/10.7759/cureus.8671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370674PMC
June 2020

Association of State Policies Allowing Medical Cannabis for Opioid Use Disorder With Dispensary Marketing for This Indication.

JAMA Netw Open 2020 07 1;3(7):e2010001. Epub 2020 Jul 1.

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California.

Importance: Misinformation about cannabis and opioid use disorder (OUD) may increase morbidity and mortality if it leads individuals with OUD to forego evidence-based treatment. It has not been systematically evaluated whether officially designating OUD as a qualifying condition for medical cannabis is associated with cannabis dispensaries suggesting cannabis as a treatment for OUD.

Objective: To examine whether state-level policies designating OUD a qualifying condition for medical cannabis are associated with more dispensaries claiming cannabis can treat OUD.

Design, Setting, And Participants: This cross-sectional, mixed-methods study of 208 medical dispensary brands was conducted in 2019 using the brands' online content. The study included dispensaries operating in New Jersey, New York, and Pennsylvania, where OUD is a qualifying condition for medical cannabis, and in Connecticut, Delaware, Maryland, Ohio, and West Virginia, where this policy does not exist.

Exposures: Presence of OUD on the list of qualifying conditions for a state's medical cannabis program.

Main Outcomes And Measures: Binary indicators of whether online content from the brand said cannabis can treat OUD, can replace US Food and Drug Administration-approved medications for OUD, can be an adjunctive therapy to Food and Drug Administration-approved medications for OUD, or can be used as a substitute for opioids to treat other conditions (eg, chronic pain).

Results: After excluding duplicates, listings for nonexistent dispensaries, and those without online content, 167 brands across 7 states were included in the analysis (44 [26.3%] in states where OUD was a qualifying condition and 123 [73.7%] in adjacent states). A dispensary listed in a directory for West Virginia was not operational; therefore, comparison states were Connecticut, Delaware, Maryland, and Ohio. In policy-exposed states, 39% (95% CI, 23%-55%) more dispensaries claimed cannabis could treat OUD compared with unexposed states (P < .001). For replacing medications for OUD and being an adjunctive therapy, the differences were 14% (95% CI, 2%-26%; P = .002) and 28% (95% CI, 14%-42%; P < .001), respectively. The suggestion that cannabis could substitute for opioids (eg, to treat chronic pain) was made by 25% (95% CI, 9%-41%) more brands in policy-exposed states than adjacent states (P = .002).

Conclusions And Relevance: In this study, state-level policies designating OUD as a qualifying condition for medical cannabis were associated with more dispensaries claiming cannabis can treat OUD. In the current policy environment, in which medical claims by cannabis dispensaries are largely unregulated, these advertisements could harm patients. Future research linking these policies to patient outcomes is warranted.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.10001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361653PMC
July 2020

Alcoholics Anonymous and 12-Step Facilitation Treatments for Alcohol Use Disorder: A Distillation of a 2020 Cochrane Review for Clinicians and Policy Makers.

Alcohol Alcohol 2020 Oct;55(6):641-651

Veterans Affairs and Stanford University Medical Centers, Stanford University Stanford School of Medicine, Stanford, CA, USA.

Aims: A recently completed Cochrane review assessed the effectiveness and cost-benefits of Alcoholics Anonymous (AA) and clinically delivered 12-Step Facilitation (TSF) interventions for alcohol use disorder (AUD). This paper summarizes key findings and discusses implications for practice and policy.

Methods: Cochrane review methods were followed. Searches were conducted across all major databases (e.g. Cochrane Drugs and Alcohol Group Specialized Register, PubMed, Embase, PsycINFO and ClinicalTrials.gov) from inception to 2 August 2019 and included non-English language studies. Randomized controlled trials (RCTs) and quasi-experiments that compared AA/TSF with other interventions, such as motivational enhancement therapy (MET) or cognitive behavioral therapy (CBT), TSF treatment variants or no treatment, were included. Healthcare cost offset studies were also included. Studies were categorized by design (RCT/quasi-experimental; nonrandomized; economic), degree of manualization (all interventions manualized versus some/none) and comparison intervention type (i.e. whether AA/TSF was compared to an intervention with a different theoretical orientation or an AA/TSF intervention that varied in style or intensity). Random-effects meta-analyses were used to pool effects where possible using standard mean differences (SMD) for continuous outcomes (e.g. percent days abstinent (PDA)) and the relative risk ratios (RRs) for dichotomous.

Results: A total of 27 studies (21 RCTs/quasi-experiments, 5 nonrandomized and 1 purely economic study) containing 10,565 participants were included. AA/TSF interventions performed at least as well as established active comparison treatments (e.g. CBT) on all outcomes except for abstinence where it often outperformed other treatments. AA/TSF also demonstrated higher health care cost savings than other AUD treatments.

Conclusions: AA/TSF interventions produce similar benefits to other treatments on all drinking-related outcomes except for continuous abstinence and remission, where AA/TSF is superior. AA/TSF also reduces healthcare costs. Clinically implementing one of these proven manualized AA/TSF interventions is likely to enhance outcomes for individuals with AUD while producing health economic benefits.
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http://dx.doi.org/10.1093/alcalc/agaa050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060988PMC
October 2020

Investing in Community Health Centers to Expand Addiction Treatment.

Psychiatr Serv 2020 07;71(7):647

College of Social Work, University of South Carolina, Columbia (Andrews); Stanford University School of Medicine and Center for Innovation to Implementation, U.S. Department of Veterans Affairs Palo Alto, Menlo Park, California (Humphreys).

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http://dx.doi.org/10.1176/appi.ps.71704DOI Listing
July 2020

Using peers to increase veterans' engagement in a smartphone application for unhealthy alcohol use: A pilot study of acceptability and utility.

Psychol Addict Behav 2020 Jun 29. Epub 2020 Jun 29.

Department of Clinical and Community Psychology, University of Alaska Anchorage.

Mobile apps can only increase access to alcohol treatment if patients actively engage with them. Peers may be able to facilitate such engagement by providing supportive accountability and instruction and encouragement for app use. We developed a protocol for peers to support engagement in the Stand Down app for unhealthy alcohol use in veterans and tested the acceptability and utility of the protocol. Thirty-one veteran primary care patients who screened positive for unhealthy alcohol use and were not currently in addiction treatment were given access to Stand Down for four weeks and concurrently received weekly phone support from a Department of Veterans Affairs peer specialist to facilitate engagement with the app. App usage was extracted daily, and pre/post treatment assessments measured changes in drinking patterns, via the Timeline Followback interview, and satisfaction with care, via quantitative and qualitative approaches. A priori benchmarks for acceptability were surpassed: time spent in the app (M = 93.89 min, SD = 92.1), days of app use (M = 14.05, SD = 8.0), and number of daily interviews completed for tracking progress toward a drinking goal (M = 12.64, SD = 9.7). Global satisfaction, per the Client Satisfaction Questionnaire, was high (M = 26.4 out of 32, SD = 4.5). Pre to post, total standard drinks in the prior 30 days (MPre = 142.7, MPost = 85.6), Drinks Per Drinking Day (MPre = 5.4, MPost = 4.0), and Percent Heavy Drinking Days (MPre = 35.3%, MPost = 20.1%) decreased significantly (ps < .05). Findings indicate that Peer-Supported Stand Down is highly acceptable to veteran primary care patients and may help reduce drinking in this population. A larger controlled trial of this intervention is warranted. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/adb0000598DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769861PMC
June 2020

Predicting relapse after alcohol use disorder treatment in a high-risk cohort: The roles of anhedonia and smoking.

J Psychiatr Res 2020 07 30;126:1-7. Epub 2020 Apr 30.

Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. Electronic address:

On average, two-thirds of individuals treated for alcohol use disorder (AUD) relapse within six months. There is a critical need to identify modifiable risk factors associated with relapse that can be addressed during AUD treatment. Candidate factors include mood disorders and cigarette smoking, which frequently co-occur with AUD. We predicted that co-occurrence of mood disorders, cigarette smoking, and other modifiable conditions will predict relapse within six months of AUD treatment. Ninety-five Veterans, 23-91 years old, completed assessments of multiple characteristics including demographic information, co-occurring psychiatric disorders, and medical conditions during residential treatment for AUD. Participants' alcohol consumption was monitored over six months after participation. Logistic regression was used to determine if, mood disorders, cigarette smoking status, alcohol consumption, educational level, and comorbid general medical conditions are associated with relapse after AUD treatment. Sixty-nine percent of Veterans (n = 66) relapsed within six months of study while 31% remained abstinent (n = 29). While education, comorbid general medical conditions, and mood disorder diagnoses were not predictors of relapse, Veterans with greater symptoms of anhedonia, active smokers, and fewer days of abstinence prior to treatment showed significantly greater odds for relapse within six months. Anhedonia and cigarette smoking are modifiable risk factors, and effective treatment of underlying anhedonic symptoms and implementation of smoking cessation concurrent with AUD-focused interventions may decrease risk of relapse.
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July 2020

Alcoholics Anonymous and other 12-step programs for alcohol use disorder.

Cochrane Database Syst Rev 2020 03 11;3:CD012880. Epub 2020 Mar 11.

European Monitoring Centre for Drugs and Drug Addiction, Best practices, knowledge exchange and economic issues, Cais do Sodre' 1249-289 Lisbon, Lisbon, Portugal.

Background: Alcohol use disorder (AUD) confers a prodigious burden of disease, disability, premature mortality, and high economic costs from lost productivity, accidents, violence, incarceration, and increased healthcare utilization. For over 80 years, Alcoholics Anonymous (AA) has been a widespread AUD recovery organization, with millions of members and treatment free at the point of access, but it is only recently that rigorous research on its effectiveness has been conducted.

Objectives: To evaluate whether peer-led AA and professionally-delivered treatments that facilitate AA involvement (Twelve-Step Facilitation (TSF) interventions) achieve important outcomes, specifically: abstinence, reduced drinking intensity, reduced alcohol-related consequences, alcohol addiction severity, and healthcare cost offsets.

Search Methods: We searched the Cochrane Drugs and Alcohol Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, CINAHL and PsycINFO from inception to 2 August 2019. We searched for ongoing and unpublished studies via ClinicalTrials.gov and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) on 15 November 2018. All searches included non-English language literature. We handsearched references of topic-related systematic reviews and bibliographies of included studies.

Selection Criteria: We included randomized controlled trials (RCTs), quasi-RCTs and non-randomized studies that compared AA or TSF (AA/TSF) with other interventions, such as motivational enhancement therapy (MET) or cognitive behavioral therapy (CBT), TSF treatment variants, or no treatment. We also included healthcare cost offset studies. Participants were non-coerced adults with AUD.

Data Collection And Analysis: We categorized studies by: study design (RCT/quasi-RCT; non-randomized; economic); degree of standardized manualization (all interventions manualized versus some/none); and comparison intervention type (i.e. whether AA/TSF was compared to an intervention with a different theoretical orientation or an AA/TSF intervention that varied in style or intensity). For analyses, we followed Cochrane methodology calculating the standard mean difference (SMD) for continuous variables (e.g. percent days abstinent (PDA)) or the relative risk (risk ratios (RRs)) for dichotomous variables. We conducted random-effects meta-analyses to pool effects wherever possible.

Main Results: We included 27 studies containing 10,565 participants (21 RCTs/quasi-RCTs, 5 non-randomized, and 1 purely economic study). The average age of participants within studies ranged from 34.2 to 51.0 years. AA/TSF was compared with psychological clinical interventions, such as MET and CBT, and other 12-step program variants. We rated selection bias as being at high risk in 11 of the 27 included studies, unclear in three, and as low risk in 13. We rated risk of attrition bias as high risk in nine studies, unclear in 14, and low in four, due to moderate (> 20%) attrition rates in the study overall (8 studies), or in study treatment group (1 study). Risk of bias due to inadequate researcher blinding was high in one study, unclear in 22, and low in four. Risks of bias arising from the remaining domains were predominantly low or unclear. AA/TSF (manualized) compared to treatments with a different theoretical orientation (e.g. CBT) (randomized/quasi-randomized evidence) RCTs comparing manualized AA/TSF to other clinical interventions (e.g. CBT), showed AA/TSF improves rates of continuous abstinence at 12 months (risk ratio (RR) 1.21, 95% confidence interval (CI) 1.03 to 1.42; 2 studies, 1936 participants; high-certainty evidence). This effect remained consistent at both 24 and 36 months. For percentage days abstinent (PDA), AA/TSF appears to perform as well as other clinical interventions at 12 months (mean difference (MD) 3.03, 95% CI -4.36 to 10.43; 4 studies, 1999 participants; very low-certainty evidence), and better at 24 months (MD 12.91, 95% CI 7.55 to 18.29; 2 studies, 302 participants; low-certainty evidence) and 36 months (MD 6.64, 95% CI 1.54 to 11.75; 1 study, 806 participants; low-certainty evidence). For longest period of abstinence (LPA), AA/TSF may perform as well as comparison interventions at six months (MD 0.60, 95% CI -0.30 to 1.50; 2 studies, 136 participants; low-certainty evidence). For drinking intensity, AA/TSF may perform as well as other clinical interventions at 12 months, as measured by drinks per drinking day (DDD) (MD -0.17, 95% CI -1.11 to 0.77; 1 study, 1516 participants; moderate-certainty evidence) and percentage days heavy drinking (PDHD) (MD -5.51, 95% CI -14.15 to 3.13; 1 study, 91 participants; low-certainty evidence). For alcohol-related consequences, AA/TSF probably performs as well as other clinical interventions at 12 months (MD -2.88, 95% CI -6.81 to 1.04; 3 studies, 1762 participants; moderate-certainty evidence). For alcohol addiction severity, one study found evidence of a difference in favor of AA/TSF at 12 months (P < 0.05; low-certainty evidence). AA/TSF (non-manualized) compared to treatments with a different theoretical orientation (e.g. CBT) (randomized/quasi-randomized evidence) For the proportion of participants completely abstinent, non-manualized AA/TSF may perform as well as other clinical interventions at three to nine months follow-up (RR 1.71, 95% CI 0.70 to 4.18; 1 study, 93 participants; low-certainty evidence). Non-manualized AA/TSF may also perform slightly better than other clinical interventions for PDA (MD 3.00, 95% CI 0.31 to 5.69; 1 study, 93 participants; low-certainty evidence). For drinking intensity, AA/TSF may perform as well as other clinical interventions at nine months, as measured by DDD (MD -1.76, 95% CI -2.23 to -1.29; 1 study, 93 participants; very low-certainty evidence) and PDHD (MD 2.09, 95% CI -1.24 to 5.42; 1 study, 286 participants; low-certainty evidence). None of the RCTs comparing non-manualized AA/TSF to other clinical interventions assessed LPA, alcohol-related consequences, or alcohol addiction severity. Cost-effectiveness studies In three studies, AA/TSF had higher healthcare cost savings than outpatient treatment, CBT, and no AA/TSF treatment. The fourth study found that total medical care costs decreased for participants attending CBT, MET, and AA/TSF treatment, but that among participants with worse prognostic characteristics AA/TSF had higher potential cost savings than MET (moderate-certainty evidence).

Authors' Conclusions: There is high quality evidence that manualized AA/TSF interventions are more effective than other established treatments, such as CBT, for increasing abstinence. Non-manualized AA/TSF may perform as well as these other established treatments. AA/TSF interventions, both manualized and non-manualized, may be at least as effective as other treatments for other alcohol-related outcomes. AA/TSF probably produces substantial healthcare cost savings among people with alcohol use disorder.
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http://dx.doi.org/10.1002/14651858.CD012880.pub2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065341PMC
March 2020
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