Forest Plot

This repo contains a JavaScript library that allows users to dynamically explorer adverse event results data in real time. A typical forest plot can be found here - it looks like this:

Data Specifications

The chart is created using a analysis results data (as opposed to raw adverse even data). The data set should have one record per test type (e.g. odds ratio) per class of adverse event (e.g. system organ class/preferred term). The following columns are required (chart mapping variable names are in parenthesis).

Column	Setting	Default	Description
High Level Classification	high_level_col	AEBODSYS	High Level Adverse Event Class
Low Level Classification	low_level_col	AEDECOD	Low Level Adverse Event Class
Group 1	group1_col	Group1	Name of first group in comparison (e.g. “Treatmemt”)
Group 2	group2_col	Group2	Name of second group in comparison (e.g. “Placebo”)
Group 1 Numerator	numerator1_col	n1	Number of cases (numerator) for group 1
Group 2 Numerator	numerator2_col	n2	Number of cases (numerator) for group 2
Group 1 Denominator	denominator1_col	N1	Number of participants (denominator) for group 1
Group 2 Denominator	denominator2_col	N2	Number of participants (denominator) for group 2
Test Type	test_col	Test	Type of test (e.g. “Odds Ratio”)
Test Result	result_col	Res	Result of Test
Test Result - Upper Limit of Normal	result_upper_col	CI_Upper	Upper Limit of Normal for Test Result
Test Result - Lower Limit of Normal	result_lower_col	CI_Lower	Lower Limit of Normal for Test Result
Test Result - p-value	p_col	Pvalue	P value for Test Result

A sample data set using the default column mappings described is used to generate the example above and can be found here.

Technical Specification

To generate a forest plot, simply load the data set, provide a configuration object with mappings, and initialize the chart using the forestPlot() function, like so:

d3.csv('forest_plot_test_data.csv', function (data) {
    let settings = {
        high_level_col:"AEBODSYS",
        low_level_col:"AEDECOD",
        group1_col:"Group1",
        group2_col:"Group2",
        numerator1_col: "n1",
        numerator2_col:"n2",
        denominator1_col:"N1",
        denominator2_col:"N2",
        test_col: "Test",
        result_col:"Res",
        result_upper_col:"CI_Upper",
        result_lower_col:"CI_Lower",
        p_col:"Pvalue"
    }
    forestPlot(data, "#container", settings)
});

See here for the full code used to generate our example graphic.