In the three months prior to the drug’s launch, both investigator and control physicians wrote a mean of 2.2% of all their prescriptions from the pharmaceutical company launching the new drug (SD ± 6.0 for the investigators, SD 4.3 for the control physicians). During this time, investigators wrote a mean total of 677 prescriptions (SD ± 758); the control physicians wrote 653 prescriptions (SD ± 715). In addition, the investigators wrote a mean of 24 prescriptions (SD ±64) for the drug class of the new drug; control physicians wrote 22 prescriptions (SD ± 42).
The average age of both types of physicians was 53 years. The SD was ±8.5 for the investigators and 10.9 for the control physicians. Apcalis Oral Jelly
Because geography was a sample control variable, there was no statistically significant difference in the geographic distribution of the two sets of physicians.
Roughly three-quarters of both groups of physicians were specialists (76% of the investigators and 74% of the control physicians).
A higher percentage of investigators (92%) were men, compared with the control group, in which 83% were men. Similarly, more investigators were board-certified (91%) compared with the control physicians (80%).
Most of the professional activity for both investigators (77%) and control physicians (82%) was office-based; however, more investigators (17%) were based in medical schools, conducted medical research outside of medical schools, or concentrated on teaching, compared with the control physicians (5%).
For all indications in the database, investigators prescribed the study drug more often than control physicians did. Three months after product launch of the new drug, the number of prescriptions for the clinical trial drug written by the investigators accounted for a statistically significant higher USC share than did the number of prescriptions written by controls (26% vs. 16%; P < .001), even with controlling for the additional variables used in the multiple analysis-of-covariance model reported. There were no statistically significant second-order interactions. This difference in prescribing behavior between the case and control physicians remained virtually unchanged over the next 15 months.
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Prescribing behaviors did vary, however, according to the nature and type of the physicians’ practice. At three months after product launch, in every comparison except for research-based or medical teaching-based physicians, the investigators’ prescriptions made up a larger USC share than the controls’ prescriptions did. Overall, prescribing behaviors barely changed over the 18-month analysis period for physicians based in offices or hospitals.
At three months, the number of research-based or medical teaching-based investigators’ prescriptions was similar to that of the controls. However, the difference between the groups became apparent at six months after product launch and increased over the next year, with prescriptions of investigators accounting for 23% of the USC share at 18 months and those of the controls decreasing to 12%.
Investigators were more likely than controls to prescribe a first-in-class new drug. The average number of drugs within a new class was two during the 18 months of the study data. None of the first-in-class drugs entered existing classes, and an average of six other drugs were present in previously existing drug classes. The absolute USC share figures for “me too” (follow-on) drugs were substantially lower than for first-in-class drugs simply because there were more drugs in the class.
Investigators also tended to prescribe new “me too” drugs. The percentage difference between the investigator and control physician USC share was greater for first-in-class drugs than for “me too” drugs. The difference never exceeded nine share percentage points for “me too” drugs and never dropped below 16 share percentage points for first-in-class drugs.
LIMITATIONS OF THE STUDY
The data were limited to U.S. results in a specific number of indications, but the results may differ for other indications or in other countries. As with any case-control study, there is the potential for confounding variables not matched or included in the analysis.