Skip to main content

Python translation of survRM2 for Restricted Mean Survival Time (RMST) analysis

Project description

survRM2py

PyPI version License: GPL v3

survRM2py is a Python reimplementation of the popular R package survRM2 for Restricted Mean Survival Time (RMST) analysis. It is designed to achieve absolute mathematical parity with the R reference implementation.

RMST is a robust alternative to the hazard ratio for comparing survival curves, representing the average survival time up to a pre-specified time point (tau).


Installation

Standard Python Environment

You can install the package directly from PyPI:

pip install survrm2py

Quick Start Example

import numpy as np
import pandas as pd
from survrm2py import rmst

# 1. Create mock survival data
np.random.seed(42)
n = 200
data = pd.DataFrame({
    "time": np.random.exponential(scale=10, size=n),
    "event": np.random.binomial(n=1, p=0.7, size=n),
    "arm": np.random.binomial(n=1, p=0.5, size=n),
    "age": np.random.normal(loc=60, scale=10, size=n)
})

# 2. Run unadjusted and covariate-adjusted RMST at tau = 8.0
results = rmst(
    df=data,
    time_col="time",
    event_col="event",
    arm_col="arm",
    tau=8.0,
    formula="age", # the formula api instead of covariates list used in the original R package for flexibility
    method="ipcw_rmst2"
)

# 3. Print unadjusted differences
print(f"RMST Arm 1: {results['rmst_arm1']:.4f}")
print(f"RMST Arm 0: {results['rmst_arm0']:.4f}")
print(f"Unadjusted Diff: {results['rmst_diff_unadjusted']:.4f} (p={results['p_unadjusted']:.4f})")

# 4. View adjusted covariate summary table
print("\nAdjusted IPCW Regression Summary:")
print(results["adjusted_summary"])

Developer Guide (Pixi)

This package uses a unified pyproject.toml with tool.pixi environment manager.

Prerequisites

Make sure you have Pixi installed:

curl -fsSL https://pixi.sh/install.sh | bash

Running Tests

The test environment automatically sets up Python, R, and installs the reference survRM2 package from CRAN.

pixi run -e test test

Building Package Distribution Files

To build the distribution packages (.whl and .tar.gz) locally in a clean sandboxed environment:

pixi run -e test build

Built files will be generated under the dist/ directory.


License

This package is licensed under the GNU General Public License v3 or later (GPLv3+), which maintains consistency with CRAN's survRM2 licensing.

References

Uno H, Claggett B, Tian L, Inoue E, Gallo P, Miyata T, Schrag D, Takeuchi M, Uyama Y, Zhao L, Skali H, Solomon S, Jacobus S, HughesM, Packer M, Wei LJ. Moving beyond the hazard ratio in quantifying the between-group difference in survival analysis. Journal of clinical Oncology 2014, 32, 2380-2385. doi:10.1200/JCO.2014.55.2208.

Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject's baseline covariates in survival analysis. Biostatistics 2014, 15, 222-233. doi:10.1093/biostatistics/kxt050.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

survrm2py-0.1.5.tar.gz (97.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

survrm2py-0.1.5-py3-none-any.whl (20.8 kB view details)

Uploaded Python 3

File details

Details for the file survrm2py-0.1.5.tar.gz.

File metadata

  • Download URL: survrm2py-0.1.5.tar.gz
  • Upload date:
  • Size: 97.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for survrm2py-0.1.5.tar.gz
Algorithm Hash digest
SHA256 f1962aa9d9b51396d630c004e25698cef71240fcb3722ab8fd6b49ac5aeb00d9
MD5 ca1735fa87f8c994fae0c050e1116130
BLAKE2b-256 ede0d5ffc492c33ceba04ae38c77a0543ba877fc08b9fbac6ec9d19c3651eb2f

See more details on using hashes here.

Provenance

The following attestation bundles were made for survrm2py-0.1.5.tar.gz:

Publisher: publish.yml on j-bac/survRM2py

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file survrm2py-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: survrm2py-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 20.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for survrm2py-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 de67f1168572b6bfce71773899dac3779f0a96135662b27ad845f9888722e545
MD5 b49242257bb90e9d8abacfc8b1e205c7
BLAKE2b-256 c29f337198c5455bab680ec1e2d483fd97a576162d99513a99356dc7a8184128

See more details on using hashes here.

Provenance

The following attestation bundles were made for survrm2py-0.1.5-py3-none-any.whl:

Publisher: publish.yml on j-bac/survRM2py

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page