In tobacco studies, biomarkers to assess exposure or potential harm are both of interest. Biomarkers of exposure are tobacco constituents or their metabolites in a biological fluid, tissue, hair, nails, or exhaled breath. TOBA-166 - Getting issue details... STATUS They are not measurements of how these constituents interact with the body process/functions. Biomarkers of harm or potential harm are measurements of an effect from exposure. These biomarkers could be indicative of exposure to tobacco products or could be related to diet or environmental exposure.
The FDA has established a list of harmful and potentially harmful constituents (HPHCs) in tobacco products and tobacco smoke. Additionally, There is a list of 20 HPHCs, selected from the full list of HPHCs, for which testing methods are well established and widely available. The HPHC list focuses on chemicals that are linked to the five most serious health effects of tobacco use (cancer, cardiovascular disease, respiratory effects, reproductive problems, and addiction.)
The use of tobacco products result in the uptake of nicotine and a wide range of other chemicals. Biomarkers of exposure to tobacco and nicotine delivery products are limited to the chemicals taken up during product use or during exposure to product emissions. Total nicotine equivalents (TNE) is a biomarker of nicotine consumption, defined as the molar sum of the urinary concentrations of nicotine and all of its known metabolites. Typically, this includes total nicotine, total cotinine, total 3-hydroxycotinine, and nicotine N-oxide (NNO). Cotinine is a metabolite of nicotine and is a widely used biomarker of nicotine exposure. Nicotine replacement therapy and tobacco use can be distinguished by the detection of a tobacco-specific alkaloid, such as anabasine. Cotinine has 6 notable metabolites including: 3-hydroxycotinine, cotinine glucuronide, 5-hydroxycotinine, cotinine N-oxide, cotinine methonium ion, and norcotinine.
Biomarkers of tobacco exposure are typically measured in blood (serum or plasma) and urine. Urine testing is usually recommended to detect chronic use because analytes are detectable for a longer period of time in urine than in serum or plasma. TOBA-165 - Getting issue details... STATUS
Biomarkers of exposure may be used to evaluated the pharmacokinetics of tobacco products. After the specific tobacco product is used, these biomarkers are measured serially to determine well-defined pharmacokinetic parameters ( e.g., AUC, TMX, T 1/2 ), the concentration level at the pre-specified timepoints would be represented in the PC/PK SDTM domains (Section 3.3.3.2 Pharmacokinetics Concentration and Parameters (PC, PP)). Otherwise, these biomarkers would be represented in the Laboratory Testing Results (LB) domain.
Example
This is an example of a study where 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 1 (visit 1, baseline), day 90 (visit 2), and day 180 (visit 3). Blood and 24-hour urine samples were collected at each visit.
Many biomarkers were measured; only a few representative biomarkers are shown in 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 (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 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 dataset but the values 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 an 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 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 applicant, based on the study design. These may include using biomarkers of tobacco exposure, of harm or potential harm, of compliance, and so on. LBSCAT can be used to provide the type of markers (e.g., tobacco alkaloid, polynuclear aromatic hydrocarbons, tobacco-specific nitrosamines) or the health impact of the biomarker (e.g., cancer, cardiovascular disease, respiratory effects, reproductive problems, addiction).
TNE (TNE-7) were calculated by the applicant based on the data below and represented in an ADaM dataset. 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.
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The 2 rows of 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 variable names TOBA-339 - Getting issue details... STATUS LBNVOID and LBNMVIOD, labels, values, origin.
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Please add a row column to your dataset.
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