BQL Object

Data analysis, tabulation, plotting, and summarization are problematic when the data contain concen­trations that fall below the lower limit of quantification (LLOQ) of the assay. The LLOQ is the concen­tration whose lower bound (of variability in the assay) includes zero. An analyte may be detectable below this concentration even though it is not quantifiable.The BQL object allows users to define rule sets to filter out unusable data in a dataset using a BQL (Below Quantifiable Limit) rule set.

Standard laboratory procedures can require that such data be reported as a character string rather than a numerical value. Representing such a concentration as zero is not always appropriate, as doing so can introduce a statistical bias or misrepresentation in some analyses. Different substitution rules are required depending on the intended use of the data, and substitution rules vary between companies and departments. As a result, it may be necessary to perform a custom transformation of the BQL column in your dataset. Refer to the “Data Wizard” section, specifically the “Example custom functions” has several example functions used for BQL columns.

The BQL object is used to create useful datasets by substituting different non-numerical codes for concentration levels too low to be used in an analysis.

Use one of the following to add a BQL object to a Workflow:

Right-click menu for a Workflow object: New > Data > BQL.
Or Main menu: Insert > Data > BQL.
Or right-click menu for a worksheet: Send To > Data > BQL.

Note:To view the object in its own window, select it in the Object Browser and double-click it or press ENTER. All instructions for setting up and execution are the same whether the object is viewed in its own window or in Phoenix view.

This section contains information about the following:

User interface description

General BQL rules

BQL output

User interface description

Main Mappings panel

Use the Main Mappings panel to identify how input variables are used in a BQL object. Required input is highlighted orange in the interface.

None: Data types mapped to this context are not included in any analysis or output.

Sort: Categorical variable(s) identifying individual data profiles, such as subject ID and treatment in a crossover study. A separate computation is done for each unique combination of sort variable values.

Time: Nominal time or actual time (time that a study dose or observation actually happened) col­lection points in a study.

Concentration: Drug concentration values in the blood.

Status Code: (Optional) Column containing the non-numeric status codes associated with each datum in the Concentration column; determines transformation of the concentration values.

LLOQ: (Optional) Column containing the lower limit of quantification (LLOQ) associated with each measurement in the concentration variable.

Carry Along: Variables that are not required for the current analysis, but are copied and included in the output dataset.

Rule Set panel

The Rule Set panel allows users to map a BQL rule set to the BQL object, or define their own BQL rules using the internal BQL Rule Set worksheet. See “General BQL rules” for more information on BQL rules.

There are two ways to create a BQL rule set: create a rule set in Rule Set panel in the BQL object or in the BQL Rules folder.

Use the Rule Set panel

Select the Rule Set panel in the Setup tab.

Check the Use internal BQL Rule Set box.

Users can now define their own rule set as an internal worksheet in the Rule Set panel.

Use the BQL Rules folder

Select the BQL Rules folder in the Object Browser.

Right-click BQL Rules and select New > Rule Set.

A new rule set called Rule Set is added to the BQL Rules folder.

Rename the rule set or leave the default name.

Define a rule set

Note:The steps and interface used to define a BQL rule set are the same whether the BQL Rules folder or the Rule Set panel is used.

BQL_internal_Rule_Set.png 

Enter the following information to define the rules:

Note:Phoenix models with censored data (BQL? option) use the log of the probabilities between 0 and the censored number in the log likelihoods. If the censoring numbers are very small, the loglikeli­hood might overflow, resulting in a Fortran error. This seems to be more often the case when using multiplicative error models. If the error occurs, try increasing the BQL value if possible or change error types.

Note:When a static LLOQ value is specified the static value is always used, even if a dataset column is mapped to the LLOQ context in the BQL object.

Additional status codes can be entered under Non-numeric Code. Each new status code that is entered creates a new row in the rule set. To remove a row, left-click the row number to select the entire row and press the Delete key.

Syntax for the rules: The status rules are not case-sensitive. The values entered can include numbers, operators, and the variable LLOQ, if an LLOQ value or data column is assigned.

General BQL rules

Common substitution rules

Some common substitution rules for BQL samples are presented in the table below.

 

 

 

Conditional substitution

Use data for:

Nonnumeric code

Unconditional substitution

Before Tmax

After Tmax

First consecutive after Tmax

After first consecutive after Tmax

PK analysis

BQL

 

0

Missing

LLOQ/2

Missing

Summary statistics

BQL

0

 

 

 

 

Listing of individual data

BQL

*BQL

 

 

 

Plotting of individual data on log-scale

BQL

LLOQ/2

 

 

 

 

Plotting of individual data on linear scale

BQL

0

 

 

 

 

The substitution rules are typically defined in standard operating procedures or method sheets for a given company or department. The rules can become more complex when a user wishes to make a distinction between concentrations that are below the quantification limit (BQL) and below the detec­tion limit (BDL). In general, a substitution rule is defined by the list of possible non-numeric represen­tations for concentration and the values to be substituted for each. One possible substitution rule for PK analyses is presented below:

Non-numeric code

Unconditional substitution

Before Tmax

After Tmax

First consecutive after Tmax

After first consecutive after Tmax

BQL

 

0

Missing

LLOQ/2

Missing

NS

Missing

 

ISV

Missing

NA

Missing

The BQL object transforms observation values from non-numeric status codes to number values for use in analyses and plots. It can also convert unusable concentration values to non-numeric status codes. The BQL object creates a new worksheet based on an existing one, by copying over selected columns.

It transforms values in the input worksheet as specified by user-defined rules. Numeric concentration data and the non-numeric concentration status codes can be in the same or different columns in the dataset.

The BQL object also stores information about the lower limit of quantification (LLOQ) for one or more sampling assays. Users can specify an LLOQ and the new column header into which it is placed, or identify an existing column containing the LLOQ for each observed concentration. The LLOQ, if any, can be used to define how status codes are transformed.

BQL output

The BQL object generates one worksheet and one text file.

Output: The worksheet with the updated concentration column.

Settings: The input worksheet used and the options selected.


Last modified date:6/26/19
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