Dark Mode
Thyroid Cancer Recurrence Prediction Data
Patient Health Records & Digital Health
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Data explores thyroid cancer recurrence in patients who have undergone Radioactive Iodine (RAI) therapy. This product is derived from clinical patient records and includes essential demographic, staging, and pathology details. The information is highly suitable for statistical studies and developing predictive algorithms focused on forecasting cancer recurrence, evaluating risk factors, and assessing the efficacy of specific treatment protocols.
Columns
The dataset contains 13 essential attributes detailing patient history and tumour characteristics:
- Age: The age of the patient recorded in years (ranging from 15 to 82).
- Gender: Patient's gender, categorized as Male or Female, with females accounting for 81% of records.
- Hx Radiotherapy: Indicates history of prior radiotherapy (Yes or No).
- Adenopathy: Presence or absence of lymph node involvement.
- Pathology: The specific type of thyroid cancer (e.g., Papillary, Micropapillary).
- Focality: Describes the tumour focality (Uni-Focal or Multi-Focal).
- Risk: The cancer risk classification (Low, Intermediate, or High), with Low risk being the most frequent classification (65%).
- T: Tumour classification (T1, T2, etc.).
- N: Lymph node classification (N0, N1, etc.).
- M: Metastasis classification (M0 or M1).
- Stage: The overall cancer staging (Stage I, II, III, IV), with Stage I representing 87% of records.
- Response: The patient's response to treatment (e.g., Excellent, Indeterminate, Structural Incomplete).
- Recurred: A binary indicator showing whether the cancer recurred (Yes or No).
Distribution
The structure includes 383 distinct patient records and 13 attributes. The data is often provided in a structured format such as CSV. The data quality is excellent, with zero missing values across all records and attributes.
Usage
This data product is ideal for several analytical applications:
- Machine Learning Models: Building predictive models to forecast recurrence probability in thyroid cancer patients.
- Statistical Analysis: Conducting rigorous studies on cancer progression, examining how factors like age and pathology influence outcomes.
- Medical Research: Investigating clinical questions, such as the relationship between treatment response (e.g., Excellent response) and long-term recurrence rates.
Coverage
The scope covers clinical patient records related to differentiated thyroid cancer. Patient demographics show a wide age distribution, spanning from 15 to 82 years, with a strong prevalence of female patients (81%). The data focuses exclusively on patients post-RAI therapy. Specific geographical origin or exact time ranges for data collection are not detailed.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
The dataset is intended for users engaged in medical data analysis:
- Data Scientists: To train classification models for recurrence risk.
- Oncology Researchers: To test hypotheses regarding clinical variables and long-term outcomes.
- Healthcare Analysts: To evaluate the effectiveness and predictive power of existing cancer staging and risk classifications.
Dataset Name Suggestions
- Thyroid Cancer Recurrence Prediction Data
- RAI Therapy Outcome Metrics
- Clinical Thyroid Cancer Staging and Response
- Differentiated Thyroid Cancer Patient Cohort
Attributes
Original Data Source: Thyroid Cancer Recurrence Prediction Data
QUALITYLoading...