STAR Standard Transplant Analysis and Research Files - onetomapanalytics/Meta_Data GitHub Wiki

STAR - Standard Transplant Analysis and Research Files

General description

  1. Database primary purpose - Provide data regarding patient waiting list, organ donation and matching, as well as transplantation occurring on the OPTN. OPTN is the nation's organ transplant network, STAR allowing requesters to perform their own analysis, or to go through static reports.
  2. Overall data type - Health outcomes
  3. Dataset type - Longitudinal
  4. Data source - Registry
  5. Data level - Patient level
  6. Geographic location of the data collection sites - United States
  7. Sponsor, manager, or home institution - Organ Procurement and Transplantation Network (OPTN), a unique public-private partnership administered by the United Network for Organ Sharing (UNOS)
  8. Date range - 1987 - 2014
  9. Geolocation data - Country and state of candidate/recipient residence and donor home state
  10. Dates - MMDDYY date for qualifying criteria first entered, admission and discharge from TX center, placed and removed from waiting list, graft failure, transplant, and death (from social security death file)
  11. Longitudinal tracking - STAR files do not include any patient or transplant hospital identifiers. However, there is a synthetic patient identification number, unique to each patient that allows researchers to track patients through multiple waiting lists and transplant events. Additionally, there are synthetic transplant and donor hospital/OPO identifiers for tracking purposes.
  12. Clinical areas of interest - Transplant; kidney transplant; pancreas transplant; liver transplant; lung transplant; heart transplant; stomach transplant; intestine transplant
  13. Variables that are uniquely present in this dataset - STAR files contain information on transplant recipients, deceased and living donors, and waiting list candidates in the U.S. reported to the OPTN since October 1, 1987. There is one record per transplant, and each record includes the most recent follow-up information.
  14. Database caveats and limitations - Linkages are not allowed under the Data Use Agreement (DUA).
  15. Other - Researchers can also request (1) custom STAR files, including specific variables or records; (2) Patient-Identified Dataset (PII), which includes patient identifiers or possibly identifiable information that may be linked to other data sources; and (3) aggregated data, a non-patient level data that summarize statistics, counts, routine and complex tabulations

Applicable methods

  1. Association, such as Cox-regression analyses (1), ANOVA (2), multivariable linear regression (3), chi-square (2, 3), multilevel logistic regression model (4), Fine-Gray competing risk regression (5, 6), Cox proportional hazards model (7, 8), multilevel models (9)
  2. Machine learning (10)
  3. Propensity scores (11)

High-impact designs

  • Assess the impact of an intervention (12)

  • Determine the age risk for graft loss (13)

Data dictionary

To access STAR data dictionary, click here

Variable categories

  1. Patient and donor demographics (e.g., age, race, ethnicity, sex, educational level, state of residence, citizenship)
  2. Patient information (e.g., antigen, blood type, acute rejection episodes, BMI, test results, complications)
  3. Donor information (e.g., living or deceased, blood type, test results, drug history, health history, follow-up visits)
  4. Transplant information (e.g., organ, if simultaneous organs, procedure type)
  5. Follow-ups (e.g., visits, death, graft failures)
  6. Death (e.g., recipient and donor cause of death, data files also provide the results of linkage between the OPTN database and additional external sources of deaths)