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This is an example of a study where biomarker's of exposure biomarkers were collected. All subjects participated in a baseline biomarker assessment and smokers were then switched to exclusive use of their assigned product. Subjects were directed to use their assigned product exclusively for 6 months with collection of samples for biomarker assessment at Day day 1 (Visit visit 1, baseline), Day day 90 (Visit visit 2), and Day day 180 (Visit visit 3). Blood and 24-hour urine samples were collected at each visit. 

Many biomarkers were measured, ; only a few representative biomarkers are shown belowin this example. Note , that a value derived by a central lab according to the lab's procedures is considered collected rather than derived. Sometimes these biomarkers are normalized by dividing the concentration of the biomarker of interest by the urine creatinine concentration obtained in the same urine sample. The results then may be reported as the concentration of biomarker of interest per creatinine. This normalization process is usually represented in an ADaM dataset shown (see below). Normalization may also be done using the total urine volume in the collected sample. 

Controlled terminology was developed for the test names of the majority of biomarkers used in Tobacco Ttbacco studies, including biomarkers of exposure or potential harm. 

The variables LBORNRLO, LBORNRHI, LBSTNRLO, LBSTNRHI, LBNRIND and LBLOBXFL are expected variables. but are typically not used in these types of studies. Hence these variables are included in the datset dataset but the values may be are null. These variables are not included below to save space.  

For lab tests where the specimen is collected over time (e.g., 24-hour urine collection), the start date/time of the collection is represented in LBDTC and the end date/time of collection is represented in LBENDTC. LBDTC and LBENDTC dates are based on the specimen collection date. If the date of the assay is needed, it can be added as a non-standard variablean NSV.  

Selected rows are included for illustration purposes only, in order to save space. The LOINC code, if included, should be provided by the testing laboratory. The sponsor applicant may also include the method used for testing if it is of interest.   

The biomarkers were categorized using LBCAT and LBSCAT. These categories were based on the scientific classification of the type of  biomarker and the associated constituent being evaluated by the biomarker test. Other categorization may be done by the sponssorapplicant, based on the study design. These may include using Biomarker biomarkers of Tobacco Exposuretobacco exposure, Biomarkers of Harm harm or Potential Harmpotential harm, Biomarkers of Compliancecompliance, etcand so on. The LBSCAT can be used to provide the type of markers (e.g., Tobacco Alkaloid, Polynuclear Aromatic Hydrocarbons, Tobacco Specific Nitrosamminestobacco alkaloid, polynuclear aromatic hydrocarbons, tobacco-specific nitrosamines) or the health impact of the biomarker (e.g., cancer, cardiovascular disease, respiratory effects, reproductive problems, and addiction).

Total Nicotine equivalents TNE (TNE-7) were calculated by the sponsor applicant based on the data below and represented in an ADaM dataset. Total Nicotine equivalents TNE are the sum of nicotine, cotinine, 3-hydroxycotinine and their glucuronide conjugates. Other estimates of TNE can be used and are typically denoted using terms like TE-2, TE-3. For example TE-2 is the sum of cotinine + 3'-hydroxycotinine.  

The 2 rows of supplb.xpt the SUPPLB dataset add qualifying information to the laboratory data collected (RDOMAIN = "LB"). IDVAR defines the key variable used to link this information to the LB data (LBSEQ). IDVARVAL specifies the value of the key variable within the parent LB record to which the SUPPLB record applies. The remaining columns specify the supplemental variables’ names (variable names

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