pysurv 1.0.1
A Python package for plotting Kaplan-Meier survival curves.
Requires Python: >=3.6

# PySurv

[PySurv](https://github.com/pushkarmutha/PySurv) is a Python package for generating and plotting Kaplan-Meier survival curves. It is designed to be simple and intuitive and is inspired from [MatSurv](https://github.com/aebergl/MatSurv).

![KM Curve Example](images/KMCurve.svg)
![Summary Example](images/Summary.png)

## Features

- Generate Kaplan-Meier (KM) survival curves
- Calculate hazard ratios (HR) with 95% confidence intervals using Cox PH method
- Option to show or hide confidence intervals (CI) for KM curves
- Flexible plotting with customizable styles, colors, and labels
- Generate synthetic time-to-event data by specifying hazard ratio and censoring rate.

## Installation

You can install PySurv via PyPI:
```
pip install pysurv
```

## Usage

Here’s a detailed example of how to use PySurv for generating data, plotting KM curves, and customizing the output:
```
import pysurv

# Generate synthetic data
data = pysurv.generate_time_to_event_data(n_samples=2000, hazard_ratio=0.5, censoring_rate=0.3)

# Plot Kaplan-Meier curve with custom labels and colors
pysurv.plot_km_curve(
    data, 
    time_col='time', 
    event_col='event', 
    group_col='group', 
    group_labels=('Control Group', 'Treatment Group'),
    title="Kaplan-Meier Survival Curve",
    y_label="Survival Probability",
    x_label="Time (months)",
    colors=['orange', 'blue'], 
    show_ci=True,
    survival_time_points=[12, 24],  # Show % survival at 12 and 24 months
    return_summary=False,
    savepath='./KMCurve.svg'
)
```

### Output:

- A Kaplan-Meier curve
- Summary statistics, including median survival time and percentage survival at given time point(s)
- Hazard ratio and p-value displayed on the plot

## Function Reference

### plot_km_curve

Plots Kaplan-Meier survival curves and calculates hazard ratios, p-values, and confidence intervals.

#### Parameters:
- **data:** A Pandas DataFrame containing time-to-event data.
- **time_col:** Column name for the time data.
- **event_col:** Column name for the event data (1 for event, 0 for censored).
- **group_col:** Column name for the binary group data.
- **group_labels:** Labels for the groups (default: None).
- **title:** Title for the plot (default: None).
- **y_label:** Label for the y-axis (default: 'Survival Probability').
- **x_label:** Label for the x-axis (default: 'Time (months)').
- **colors:** List of colors for the groups (default: ['r', 'b']). If more than two groups, please manually provide a list of colors.
- **line_styles:** Line styles for the groups (default: ’-‘).
- **fontsize:** Font size for text on KM curve including title, axis labels, and risk tables (default: 18).
- **linewidth:** Line width of KM curves (default: 2.5).
- **show_ci:** Whether to show confidence intervals on the KM curves (default: False).
- **show_inverted_hr:** Whether to show inverted hazard ratio (default: False).
- **survival_time_points:** One or more time point(s) at which to estimate percentage survival (default: None).
- **return_summary:** Whether to return a summary of survival and hazard ratio statistics (default: False).
- **savepath:** Complete path (including filename and extension) to save the KM curve plot (default: None).
- **\*\*kwargs:** Additional matplotlib arguments to pass for plotting KM curves.

#### \*Note:
- PySurv uses a univariable Cox regression model on the 'group_col' variable to compute hazard ratios and p-values. 
- MatSurv deafaults to the 'Mantel-Haenszel' (MH) and 'log rank' method. 
- Under the proportional hazards assumption, Cox regression is equivalent, if not better, to the MH/log-rank method.
- For more information, see [this](https://www.fharrell.com/post/logrank/) and [this](https://discourse.datamethods.org/t/when-is-log-rank-preferred-over-univariable-cox-regression/2344). 

## Maintained by
- Pushkar Mutha
- Email: pmutha@emory.edu
- LinkedIn: https://www.linkedin.com/in/pushkar-mutha/

If you would like to request a new feature, please feel free to raise an issue on [GitHub](https://github.com/pushkarmutha/PySurv) or reach out via email. If you found this code useful, you can support by leaving a star.