Laboratories
Liver cancer staging project
Hepatocellular carcinoma (HCC), the primary form of liver cancer, is one of the leading cancer-related causes of death worldwide. There are many complex treatment strategies; the populations are heterogeneous, with different genetic, lifestyle, and comorbity differences.
Here we describe the algorithm used to identify HCC liver cancer stages for AJCC, BCLC, and CLIP liver cancer staging systems.
Algorithm:
Step 1) Patient files and laboratories
Non-alcoholic fatty liver disease (NALFD) & Alcoholic Fatty Liver Disease (ALD)
Non-alcoholic fatty liver disease (NAFLD)
Opioid-exposed infants
Objective
Observational studies examining outcomes among opioid-exposed infants are limited by phenotype algorithms that may under identify opioid-exposed infants without neonatal opioid withdrawal syndrome (NOWS). We developed and validated the performance of different phenotype algorithms to identify opioid-exposed infants using electronic health record (EHR) data.
Ovarian/Uterine Cancer (OvUtCa)
The KPWA/UW-led ovarian/uterine cancer phenotype has been validated at Mayo Clinic, the secondary phenotype development site. Validation results at both the primary and secondary sites were strong and the phenotype is ready for network wide implementation. The pseudo code document posted 11/30/2017 is correct as is and should be used by network sites for phenotype implementation. A validated data dictionary of covariates for this phenotype will be added to PheKB by 2/15/2018, but sites are encouraged to begin implementing the phenotype algorithm now.
Peanut Allergy
Food allergy is defined as an immune response that occurs reproducibly to a given food, typically an immunoglobulin E (IgE)-mediated clinical reaction to specific protein epitopes. Over the last 20-30 years, food allergy has grown into a major public health problem. Peanut allergy is a common type of food allergy that accounts for a disproportionate number of fatal and near-fatal anaphylactic events amongst all the common food allergens.
Peripheral Arterial Disease - 2012
Peripheral Arterial Disease (PAD) is prevalent with approximately 10-12 million adults in US affected. For those with PAD, morbidity and mortality are high and quality of life is markedly impaired. The genetic basis of PAD is poorly understood and is the focus of the Mayo Clinic Electronic Medical Records and Genomics (eMERGE) Network study.
PhEMA BPH (Benign Prostatic Hyperplasia) cases
This is PhEMA (Phenotype Execution Modeling Architecture, projectphema.org)'s implementation of the following BPH (Benign Prostatic Hyperplasia) case algorithm from the following BPH case and control algorithm on PheKB:
https://phekb.org/phenotype/benign-prostatic-hyperplasia-bph
Artifacts for this phenotype, inc. an HQMF representation, a KNIME workflow that can run against an i2b2 instance, and a snapshot of the PhAT graphical representation, are posted on GitHub:
Red Blood Cell Indices
Laboratory results for ESR and RBC indices (hemoglobin, MCV, MCH, RDW… etc) should be extracted from the Laboratory databases. For Mayo, from January 1994 till October 2009, ESR and RBC test results were populated for our 3336 participants. All samples were collected on an outpatient basis. Samples collected during an inpatient hospitalization (admit date ≤ collection date ≤ discharge date) should be excluded unless this sample was the only one available for a patient.
Resistant hypertension
This algorithm describes the ongoing resistant hypertension algorithm used in eMERGE, which was a network phenotype within the eMERGE-I and eMERGE-II sites.