Lung Cancer - Non Small Cell
Conditions
Keywords
lung cancer, machine learning, non-small cell neuroendocrine tumor
Brief summary
This study was based on public use data from the SEER database. The study did not require informed consent from the SEER registered cases, and the authors obtained Limited-Use Data Agreements from SEER.
Detailed description
This study utilized publicly available data from the SEER (Surveillance, Epidemiology, and End Results) database, which is a comprehensive source of information on cancer statistics in the United States. The authors did not need to obtain informed consent from individuals whose cases are registered in the SEER database because the data is anonymized and is meant for public use. Instead, the authors acquired Limited-Use Data Agreements with SEER, which are legal contracts that allow researchers to access and use specific datasets under certain conditions while ensuring that the privacy of the individuals in the database is maintained. This agreement outlines the terms of data use, ensuring that the researchers adhere to guidelines for the ethical handling of data while still enabling them to conduct their research.
Interventions
Surgery
Sponsors
Study design
Eligibility
Inclusion criteria
* Pathologic Diagnosis of Non-Small Cell Neuroendocrine Carcinoma * Known Surgical Information
Exclusion criteria
* Small cell lung cancer * Age less than 18 years
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Overall survival | The estimated time period for assessing events was January 2000 through December 2021. It is the time from random assignment to death from any cause (last follow-up for lost patients; end of follow-up for patients still alive at the end of the study). | Overall survival refers to the duration of time from the start of diagnosis until death from any cause. It is a common endpoint used in clinical trials and medical research, particularly in oncology, to measure the effectiveness of a treatment or intervention. Overall survival provides a comprehensive picture of how well patients are doing and is often expressed as a percentage or a median time (e.g., the median overall survival time). |