AIM: A comparison of conventional pairwise propensity score matching (PSM) and generalized PSM method was applied to the comparative effectiveness of multiple treatment options for lung cancer. MATERIALS & METHODS: Deidentified data were analyzed. Covariate balances between compared treatments were assessed before and after PSM. Cox proportional hazards regression compared overall survival after PSM. RESULTS & CONCLUSION: The generalized PSM analyses were able to retain 61.2% of patients, while the conventional PSM analyses were able to match from 24.1 to 77.1% of patients from each treatment comparison. The generalized PSM achieved statistical significance (p < 0.05) in 8/10 comparisons, whereas conventional pairwise PSM achieved 1/10. The noted differences arose from different matched patient samples and the size of the samples.
AIM: A comparison of conventional pairwise propensity score matching (PSM) and generalized PSM method was applied to the comparative effectiveness of multiple treatment options for lung cancer. MATERIALS & METHODS: Deidentified data were analyzed. Covariate balances between compared treatments were assessed before and after PSM. Cox proportional hazards regression compared overall survival after PSM. RESULTS & CONCLUSION: The generalized PSM analyses were able to retain 61.2% of patients, while the conventional PSM analyses were able to match from 24.1 to 77.1% of patients from each treatment comparison. The generalized PSM achieved statistical significance (p < 0.05) in 8/10 comparisons, whereas conventional pairwise PSM achieved 1/10. The noted differences arose from different matched patient samples and the size of the samples.