We are fortunate that coronavirus resources are increasing daily. I always recommend starting with the most authoritative resources. Some good places to start are listed below, however there are many more resources, assembled by key journals and leading professional and scientific organizations.
US Centers for Disease Control and Prevention
US Food and Drug Administration
The New England Journal of Medicine
Institute for Health Metrics and Evaluation
Genomic information plus clinical information in a large database allows us to identify genes associated with disease variants and truly begin precision medicine. In pharmacoepidemiology this will mean that we can identify patients who benefit most or are at greatest risk of an adverse event from a specific treatment.
The power of linking genomic information with clinical information is demonstrated in a recent study by Karnes et al 2017. They examined variations in major histocompatibility complex (MHC) and human leukocyte antigen (HLA) genes by linking information from DNA biobanks databases with EHR records for almost 30,000 people. Most importantly, they discovered previously unidentified associations between gene variation and disease severity for several conditions. They identified associations with type 1 diabetes and ankylosing spondylitis, among other conditions. Most importantly, they discovered several previously unidentified associations with MS and cervical cancer, as well as associations between gene variation and disease severity for several conditions.
The heatmap crosstabulates HLA alleles with a range of disease diagnoses with darker reds being stronger positive associations (the allele increases the probability of having the disease or phenotype) and darker blues being stronger negative associations (the allele is associated with a protective effect against the disease or phenotype).
The authors note that this is one of the first systematic studies of clinical phenotypes with HLA variation in a single population.
Heatmap of four-digit HLA allelic associations with P < 1 × 10?5.
Data are publicly available www.phewascatalog.org
The recently published text, Drug Utilization Research: Methods and Applications, represents a formidable accomplishment, pulling together a comprehensive range of information on all topics related to this key area. With 48 chapters, it addresses study design, data collection, secondary data sources, classification systems, measurement units, drug expenditures, statistical methods, data visualization, and much more. I was happy to see a chapter addressing issues around pediatric drug utilization, and chapters on drug utilization of pregnant women and older populations, as well.
Drug Utilization Research (DUR) is an eclectic scientific discipline, integrating descriptive and analytical methods for the quantification, understanding and evaluation of the processes of prescribing, dispensing and consumption of medicines and for the testing of interventions to enhance the quality of these processes. The discipline is closely related and linked mainly to the broader field of pharmacoepidemiology, but also to health outcomes research, pharmacovigilance and health economics.
Drug Utilization Research is a unique, practical guide to the assessment and evaluation of prescribing practices and to interventions to improve the use of medicines in populations. Edited by an international expert team from the International Society for Pharmacoepidemiology (ISPE), DUR is the only title to cover both the methodology and applications of drug utilization research and covers areas such as health policy, specific populations, therapeutics and adherence.
The only way to assemble such a book is with a strong group of editors, Monique Elseviers, Björn Wettermark, Anna Birna Almarsdóttir, Morten Andersen, Ria Benko, Marion Bennie, Irene Eriksson, Brian Godman, Janet Krska, Elisabetta Poluzzi, Katja Taxis, Vera Vlahovi?-Pal?evski, Robert Vander Stichele are all accomplished researchers in this field.
One immediate goal of the Precision Medicine Initiative will be to significantly expand efforts in cancer genomics to create prevention and treatment successes for more cancers.
the Initiative will 1) support a national network of scientists who possess the talent and skills to develop new approaches for answering critical scientific and medical questions and 2) launch a national cohort study of a million or more Americans to propel our understanding of health and disease. The goal is to set the foundation for a new way of doing research that fosters open, responsible data sharing with the highest regard to patient privacy, and that puts engaged participants at the center.
You’ll soon recognize the PMI logo
In the process, we will learn about EHRs, mhealth, patient engagement and new research methodologies.
Workshops conducted by the PMI Working Group are open to the public if space is available, and can be viewed on webcasts. The recent workshop on Participant Engagement and Health Equity (July 1 and 2, 2015) was phenomenal, and worthwhile catching the video.
The recent IOM workshop, Comprehensive Cancer Care for Children and their Families, touched on some key issues around use of PROs in children with cancer, and much of what was said is applicable to children with other diseases and conditions. I’m hoping that video of the presentations will be posted (they often are).
Try presentation by Lillian Sung, The Hospital for Sick Children, Toronto has the bland title “Academic Perspective on Clinical Research”, but is a hard hitting overview of the issues around implementing Patient Reported Outcomes (PROs) in pediatric cancer patients, and includes a full list of action items and recommendations. She notes the FDA 2009 Guidance for Industry Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims and its statement,
We discourage proxy-reported outcome measures for this population (i.e., reports by someone who is not the patient responding as if that person were the patient). For patients who cannot respond for themselves (e.g., infant patients), we encourage observer reports that include only those events or behaviors that can be observed.
Bryce Reeve made a critical point in favor of use of PRO’s in pediatric cancers. He presented evidence that there is a low correlation between clinicians’ report and patient report for a range of symptoms. The consequence of relying on clinicians’ report for identifying adverse events is an underestimate of adverse events, something that can be corrected by broader use of PRO’s in cancer research. Presumably this is relevant to other diseases, as well.
