NEWS.md

In banffIT: Automated Standardized Assignment of the Banff Classification

banffIT 2.1.0 (release : 2025-06-20)

update dependency madshapR

Due to update in madshapR package, the name columns internally used in banff_launcher() have been changed. The rest of the functions are not affected.

banffIT 2.0.0

Implementation of the new parameter ‘version’ which allows the user to select a version of the Banff classification. At the moment of the development, the available versions are 2017 and 2022. The latest version (2022) is the default. The new version includes two new variables in the data dictionary (xm and abo_i) and 4 new diagnostics codes for diag_code_2.

Bug fixes and improvements

• calculate_adequacy() There was an error adressing the proper order of participants, giving occasionally wrong calculation of the adequacy. This has been fixed, using an index to ensure identical order in the output.

banffIT 1.0.1

Error in document. There was a typo in banff_example.xlsx name. Only Read me and vignette were affected.

banffIT 1.0.0

The banffIT package provides functions to assign standardized diagnoses using the Banff Classification (Category 1 to 6 diagnoses, including Acute and Chronic active T-cell mediated rejection as well as Active, Chronic active, and Chronic antibody mediated rejection). The main function banff_launcher()considers a minimal dataset containing biopsies information in a specific format (described by a data dictionary), verifies its content and format (based on the data dictionary), assigns diagnoses, and creates a summary report.

Main functionality

• banff_launcher() This function takes a path string identifying the input file path. The function internally runs a series of tests that assess the input dataset. If any of these tests fails, the user gets information allowing them to correct the input dataset and rerun the process. Once all tests pass, the dataset is given as an output with a diagnosis for each observation (using the function add_diagnoses() internally). The output dataset, along with its associated labels (“label:en” by default) are provided to the user in an Excel format file accessible in the output_folder specified. The output dataset comes with a report that summarizes information about variable distributions and descriptive statistics.

Additional functions (used in the main function, but can be used separately)

• banff_dataset_evaluate() This function takes a dataset and evaluates its format and content based on the accepted format specified in the data dictionary.

• calculate_adequacy() A tibble object with two variables: the calculated adequacy (adequacy_calculated) and the adequacy specified in input (adequacy_input).

• add_diagnoses() This function takes a dataset and returns a diagnosis for each observation. For the function to run, the dataset must not contain any errors that banff_launcher()would have detected. Please prefer using banff_launcher() to run additional tests.

Helper functions

• get_banff_dictionary(), get_banff_example(), get_banff_template() This function gets the data dictionary used to control the consistency of the input dataset, a example dataset and a template.

• function banffIT_website() This function sends the user to the online documentation for the package, which includes a description of the latest version of the package, vignettes, user guides, and a reference list of functions and help pages.

Imported functions from madshapR

• dataset_cat_as_labels()

• dataset_summarize()

banffIT documentation built on Aug. 8, 2025, 7:32 p.m.