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Bladder Cancer Recurrence Study
Patient Health Records & Digital Health
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About
Data on the recurrences of bladder cancer, which has been widely used to demonstrate methodology for recurrent event modelling. The information contains records from a clinical study involving different treatments and tracks initial tumour characteristics as well as subsequent recurrences over time. It is structured to support various analytical approaches, including competing risks and Anderson-Gill style models.
Columns
- id: A unique identifier for each patient.
- treatment: The treatment received by the patient, which could be a placebo, pyridoxine (vitamin B6), or thiotepa. In some formats, this is coded numerically (e.g., 1 for placebo, 2 for thiotepa).
- number: The initial count of tumours a patient had. A value of 8 signifies 8 or more tumours.
- size: The size in centimetres (cm) of the largest initial tumour.
- recur: The total number of recurrences observed for a patient.
- start: The beginning time of an observation interval.
- stop: The end time of an observation interval, representing either a recurrence or censoring time.
- status: A code indicating the event at the end of an interval: 0 for censored, 1 for recurrence, 2 for death from bladder disease, and 3 for death from other or unknown causes.
- rtumor: The number of tumours identified at the time of recurrence.
- rsize: The size of the largest tumour found at recurrence.
- enum: The sequential number of the event or observation for a patient.
- rx: A numeric code for the treatment received (e.g., 1 for placebo, 2 for thiotepa).
- event: A binary indicator where 1 represents a recurrence and 0 represents censoring.
Distribution
The data is available in CSV format and is organised into multiple datasets (Bladder, Bladder1, Bladder2) reflecting different patient subsets and data structures. For instance, one common version includes 340 valid records across 8 columns, covering 85 patients with up to four recurrences each. Another version includes the full study data for 118 subjects.
Usage
This data is ideal for survival analysis and modelling recurrent events. It can be used to demonstrate and compare different statistical methodologies, such as the Wei, Lin, and Weissfeld (WLW) competing risks format and the Anderson-Gill (AG) style for time-to-event analysis. It is also suitable for research into the efficacy of different bladder cancer treatments.
Coverage
The data originates from a clinical study. It covers patients who received one of three treatments: placebo, pyridoxine (vitamin B6), or thiotepa. The temporal scope is defined by patient follow-up times, tracking multiple recurrences over the study period.
License
CC0: Public Domain
Who Can Use It
- Statisticians and Data Scientists: For developing and testing models for recurrent event and survival data.
- Medical Researchers: To analyse the effectiveness of different bladder cancer treatments and understand tumour recurrence patterns.
- Students and Academics: As a classic teaching and demonstration dataset for biostatistics and epidemiology courses.
- Healthcare Analysts: To explore methodologies for predicting patient outcomes in oncology.
Dataset Name Suggestions
- Bladder Cancer Recurrence Study
- Clinical Trial Data for Bladder Cancer
- Recurrent Event Modelling: Bladder Cancer
- Survival Analysis Dataset for Cancer Recurrence
Attributes
Original Data Source: Bladder Cancer Recurrence Study
QUALITY