Table 2.

Association between industry payments and Medicare spending for cancer drugs, 2014-2018.

Association	N (%)	Estimate (95% CI)	P value
Log-transformed industry payments
Medicare spending	n/a	−0.001 (−0.005 to 0.004)	.79
Generic within 3 years	35 (9.7)	−0.938 (−1.384 to −0.492)	<.0001
Transformed (lambda = 0.25) industry payments
Medicare spending	n/a	−0.01 (−0.030 to 0.011)	.35
Generic within 3 years	35 (9.7)	−4.219 (−5.429 to −3.009)	<.0001

Individual observations were unique drug-calendar year pairs (N = 361, unique drugs = 89). Generalized estimating equations were used to estimate the outcome of mean industry payments per prescribing physician in that calendar year, with clustering on the level of the unique drug. Independent variables were Medicare spending (modeled as mean spending per prescribing physician in that calendar year, $thousands USD) and whether during the observed calendar year the drug was within 3 years of the market entrance of the first generic competitor. Two modeling approaches were applied: (1) OLS modeling log-transformed industry payments, estimating the log change in the dollar value industry payments associated with a $1000 increase in spending, and (2) OLS modeling transformed (lambda = 0.25) industry payments, estimating the change in transformed industry payments associated with a $1000 increase in spending.