Spots Global Cancer Trial Database for Verification of Novel Survival Prediction Algorithm for Patients With NSCLC Spinal Metastasis

Study Description

Brief Summary: The purpose of this study is to learn whether our own made predictive algorithm can be used as a clinical practical decision support for patients with NSCLC spinal metastasis. The scoring system consists of the use of EGFR-TKI, KPS, Age, SCC, CA125 and smoking history. By predicting survival doctors could determine which patients are suitable for palliative therapy.

Detailed Description: Investigators have performed a retrospective study on 176 patients with NSCLC spinal metastasis under the oversight of hospital's ethics committee, and investigators found that the use of EGFR-TKI, KPS, Age, SCC, CA125 and smoking history had significant association with survival. Then investigators built a simple, easy to use scoring system based on the features mentioned above. The score was calculated as 1 (for patients didn't receive EGFR-TKI), +2 (for KPS \<50%), +1 (for KPS 50-70%), +1 (Age \>60years), 2 (SCC ≥1.5ng/ml), +3 (CA125 ≥35 U/ml), +1 (smoking history 1-10/day), +2 (smoking history \>10/day), and 0 otherwise. This algorithm was used to divide the patients into low risk (0-3), intermediate risk (4-6), high risk groups (7-10) to predict survival and determine which patients are suitable for palliative therapy. Now investigators wish to register this study to do a further research, in order to verify the accuracy and sensitivity of this algorithm.

Keywords

Eligibility

Minimum Age: 18 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Contact Details

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