Vantage6 algorithm to get TNM statistics

This algorithm was designed for the vantage6 architecture. It computes the following statistics:

• number of patients per centre
• number of patients per overall stage per centre
• number of patients per vital status per centre
• survival rate profile per centre

Input data

The algorithm expects each data node to hold a csv with the following data and adhering to the following standard:

{
    "id": {
        "description": "patient identifier",
        "type": "string"
    },
    "stage": {
        "description": "patient overall stage",
        "type": "categorical"
    }, 
    "date_of_diagnosis": {
        "description": "date the patient was diagnosed",
        "type": "string",
        "format": "%Y-%m-%d"
    },
    "date_of_fu": {
        "description": "date the patient had the last follow up visit",
        "type": "string",
        "format": "%Y-%m-%d"
    },
    "vital_status": {
        "description": "patient vital status",
        "type": "categorical",
        "values": ["alive", "dead"]
    },
    "centre": {
        "description": "hospital identifier",
        "type": "string"
    } 
}

The files data1.csv and data2.csv in the directory v6_healthai_dashboard_py/local are examples.

Using the algorithm

Below you can see an example of how to run the algorithm:

import time
from vantage6.client import Client

# Initialise the client
client = Client('http://127.0.0.1', 5000, '/api')
client.authenticate('username', 'password')
client.setup_encryption(None)

# Define algorithm input
input_ = {
    'method': 'master',
    'master': True,
    'kwargs': {
        'org_ids': [2, 3],  # organisations to compute statistics
        'cutoff': 730,      # cutoff days for survival rate profile
        'delta': 30         # interval between days in the survival rate profile
    }
}

# Send the task to the central server
task = client.task.create(
    collaboration=1,
    organizations=[2, 3],
    name='v6-healthai-dashboard-py',
    image='ghcr.io/maastrichtu-cds/v6-healthai-dashboard-py:latest',
    description='get tnm statistics',
    input=input_,
    data_format='json'
)

# Retrieve the results
task_info = client.task.get(task['id'], include_results=True)
while not task_info.get('complete'):
    task_info = client.task.get(task['id'], include_results=True)
    time.sleep(1)
result_info = client.result.list(task=task_info['id'])
results = result_info['data'][0]['result']

Testing locally

If you wish to test the algorithm locally, you can create a Python virtual environment, using your favourite method, and do the following:

source .venv/bin/activate
pip install -e .
python v6_healthai_dashboard_py/example.py

The algorithm was developed and tested with Python 3.10.

Acknowledgments

This project was financially supported by the AiNed foundation.