Assessment tools are used to determine the presence and severity of patient symptoms.
Brief Pain Inventory - BPI
Developed in 1989 by Dr. Charles Cleeland for rapid assessment of the severity and impact of pain in cancer patients. The BPI has since been translated into more than three dozen languages, and is widely used in both research and clinical settings. Read more.
Brief Fatigue Inventory - BFI
A tool to rapidly assess the severity and impact of cancer-related fatigue. An increasing focus on cancer-related fatigue emphasized the need for sensitive tools to assess this most frequently reported symptom. The six inventory items correlate with standard quality-of-life measures. Read more.
The MD Anderson Symptom Inventory - MDASI
Used to assess multiple symptoms experienced by cancer patients and the interference with daily living caused by these symptoms. The MDASI is available in both paper-and-pencil and interactive voice response (IVR) formats, both of which are equally effective. Read more.
MD Anderson Symptom Assessment System (ASAS) (pdf): uses a scale from 0 to 10 to rate the patient's perception of pain, fatigue, nausea, depression, anxiety, drowsiness, shortness of breath, appetite, sleep and feeling of well-being. The scores for each symptom can be marked on a graph and updated daily to follow the patient's progress.
The CAGE Questionnaire (pdf): a screening tool for potential alcohol abuse, that can also determine if alcohol is being used as a coping mechanism. It queries patients on four topics:
- Cutting down on alcohol consumption
- Annoyance from possible criticism about drinking
- Guilty feelings about drinking
- Eye-openers to avoid hangovers ("hair of the dog," etc.)
Labeled Visual Information System (eLVIS) (pdf): a quick graphical representation of the patient's tumor sites (primary and metastatic) and areas of prior surgery and/or radiotherapy. This form can also be used to follow disease progression or treatment response.
Edmonton Staging System: a clinical staging system for cancer pain, used to predict patient outcomes.