Oncology Survival Trial

Name: Oncology Survival Trial
Creator: Syntherx

Synthetic oncology trial with overall survival and progression-free survival endpoints. Designed for cancer treatment efficacy simulation.

This resource represents a fully synthetic cohort patterned after oncology scenarios: there are no real patients or protected health information, only statistically plausible records for method development and reproducible benchmarks.

Rows include variables such as patient_id, age, sex, treatment_arm, survival_time, event_observed. You can inspect the full schema and representative preview below before downloading or generating a fresh cohort with the Syntherx SDK.

Teams use datasets like this for AI and statistical modeling, digital twin and pathway simulation, curriculum and sandbox environments, and cross-institutional collaborations where sharing real data is impractical.

Research Dataset — $99

Secure checkout via Stripe.

Includes CSV, JSON, and Parquet — ready for ML pipelines

Variable Schema

Column Name	Type	Description
patient_id	string	Unique synthetic patient identifier
age	number	Synthetic patient age
sex	string	Synthetic patient sex
treatment_arm	string	Treatment or control arm
survival_time	number	Time to event or censoring
event_observed	number	1 if event observed, 0 if censored

Data Preview

First 9 rows (preview only)

Includes CSV, JSON, and Parquet — ready for ML pipelines

patient_id	age	sex	treatment_arm	survival_time	event_observed
P000001	64	Female	treatment	18.2	1
P000002	59	Male	control	12.5	1
P000003	71	Female	treatment	22.1	0
P000004	67	Male	control	9.8	1
P000005	52	Female	treatment	25.4	0
P000006	60	Male	control	14.3	1
P000007	55	Female	treatment	19.7	0
P000008	69	Male	control	11.2	1
P000009	62	Female	treatment	21.5	0

Reproduce This Dataset

Recreate this dataset in Python (Jupyter, Kaggle, or Google Colab) using the Syntherx SDK.

# Install Syntherx SDK
pip install syntherx

from syntherx import generate_dataset

df = generate_dataset(
    blueprint="oncology_survival_trial",
    rows=5000
)

df.to_csv("oncology_survival_trial.csv")

Use Cases

Build and validate AI/ML pipelines for Oncology scenarios without using real patient data.
Train and evaluate models on structured fields such as patient_id, age, sex, treatment_arm.
Run simulations, power analyses, and exploratory analytics in a privacy-safe sandbox.
Prototype dashboards, ETL flows, and feature stores before touching production systems.

Dataset Characteristics

Fully synthetic — no PHI; suitable for sharing, teaching, and external collaboration.
Schema includes 6 variables: patient_id, age, sex, treatment_arm, survival_time, event_observed
Delivered in researcher-friendly formats (CSV, JSON, Parquet) for downstream tooling.
Generated with the Syntherx simulation engine for reproducible cohort-scale draws.

Privacy-Safe Synthetic Dataset

Contains no real patient data
Generated using statistical simulation
Designed for machine learning research

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