AIDSI example

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from pymsm.datasets import load_aidssi, prep_aidssi, plot_aidssi
from pymsm.plotting import competingrisks_stackplot

%load_ext autoreload
%autoreload 2

The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

From Data Analysis with Competing Risks and Intermediate States, Book by Ronald B. Geskus:

The data contains information on two event types, “AIDS” and “SI”, which compete to be the first to occur. Time is given in years since HIV infection. There are two different representations of the information on the event type that occurred first.
In the cause column, the event type is described in words, whereas in the status column a numeric respresentation is used.
The ccr5 column contains the information on the presence of the deletion CCR5-∆32. Individuals that don’t have the deletion have the value WW (W stands for “wild type”). Individuals that have the deletion on one of the chromosomes have the value WM (M stands for “mutation”)

See also: https://www.rdocumentation.org/packages/mstate/versions/0.3.1/topics/aidssi

data = load_aidssi()
data.head()

	patnr	time	status	cause	ccr5
1	1	9.106	1	AIDS	WW
2	2	11.039	0	event-free	WM
3	3	2.234	1	AIDS	WW
4	4	9.878	2	SI	WM
5	5	3.819	1	AIDS	WW

competing_risk_dataset, covariate_cols, state_labels = prep_aidssi(data)
competing_risk_dataset.head()

	sample_id	time_entry_to_origin	origin_state	target_state	time_transition_to_target	ccr5_WW
0	1	0	1	2	9.106	1
1	2	0	1	0	11.039	0
2	3	0	1	2	2.234	1
3	4	0	1	3	9.878	0
4	5	0	1	2	3.819	1

plot_aidssi(competing_risk_dataset, state_labels)

competingrisks_stackplot(
    data=competing_risk_dataset,
    duration_col='time_transition_to_target',
    event_col ='target_state',
    order_top= [2],
    order_bottom = [3],
    state_labels = state_labels);