NETS Module 8: Lung Malignancies
The NPCR Education and Training Series (NETS) is a series of educational tools for state trainers to support central cancer registries in their role of providing education to staff and reporters. For more information about how you may use the NETS modules, please see Guidelines for Using the NETS Modules.
Note: This module is being updated to meet 2010 specifications. Please remember to check back for current training materials.
The lung cancer advanced abstracting module consists of six parts—
- Parts 1–2: Demographics and Diagnosis [PDF-2.9MB]
- Parts 3–6: Extent of Disease, Treatment, Follow-up and Outcomes, Quality Assurance [PDF-4.1MB]
There are four difficult lung cancer cases consisting of de-identified physician dictation, a basic, blank abstract, and four completed abstracts with codes and rationales/documentation. Also included in this module are two short multiple primary and histology coding exercises to be done at the end of the second part of the presentation.
The abstract for the sample cases follows the FORDS manual in organization and includes the five multiple primary data fields added in 2007. Most of the items should be completed with the appropriate data codes used by NPCR and the CoC. It is suggested that, to facilitate discussion, the AJCC TNM staging items be completed with the actual stage or staging component instead of the code for the stage. Otherwise, participants can enter data on the abstract however their cancer registry software requires. In particular, the coding of unknown dates varies from state to state and software system to software system.
Participants will need a FORDS manual (current version) and copies of the lung cancer sections of the AJCC Cancer Staging Manual, 6th edition, Collaborative Staging manual (current version), Multiple Primaries and Histology Coding Rules (current version) and the SEER Summary Staging Manual 2000. For more information, please see Instructions for Presenters.
Case Studies and Exercise Worksheets
The exercises that follow are taken from actual medical charts that have been de-identified to protect patient privacy and are used as part of the learning process. Drug names are trademarked and listed as they actually appear in their medical records.