Читать книгу Cobert's Manual Of Drug Safety And Pharmacovigilance (Third Edition) - William Gregory - Страница 55

Disproportionality (proportional reporting ratio (PRR) as an example): There are various methods employed, and all more or less revolve around the concept of expected proportional reporting, and observed detection of disproportionate reporting applied to large databases. They look at the AEs for a particular drug and compare the count of these same AEs for the remaining drugs in a PV database.

This basic PRR is simple and uses a 2 × 2 table:

Note: PRR = A(A + C)/B(B + C).

Note: PRR = 345/6901 (345 + 6901)/291 (291 + 14556) = 1.67.

In words, the proportion of a particular AE divided by all AEs seen with the drug of interest is divided by the proportion of this AE divided by all AEs seen with all drugs in the database. In the previous example, if 3.28% of all AEs seen with drug X are chest pain and 1.96% of all AEs seen with all the other drugs in the database (excluding drug X and its AEs) are chest pain, then the PRR is 3.278%/1.96% or 1.67. This means that there are (dis)proportionately more chest pain AEs with drug X compared with all the other drugs in the database, and this is noteworthy as a possible signal.

Since it is unusual that the PRR will be exactly 1.0, when the PRR is calculated for all AEs in the database, every PRR will either be below 1.0 or above 1.0. In theory, values above 1.0 would suggest an AE that is more frequently reported to drug X than other drugs in the data. One must be careful not to over interpret the data, especially since there are more than 80,000 terms in MedDRA®, and one could theoretically calculate some 80,000 PRRs. In practice, one sets a threshold above which the PRR is considered noteworthy, such as a value of, for example, 3.0. Any AE that has a PRR above 3.0 will be considered a signal and will be further examined. The higher the PRR, the greater the specificity but the lower the sensitivity. Alternatively, one might simply take the 10 or 20 highest PRRs and evaluate those regardless of how high the PRR is above 1.0.

There are other issues with using this score. When the database is small, problems can occur.

For example, for serious rare AEs adding or subtracting one case can markedly alter the PRR results. For example, if there is one myocardial infarct (MI) in the four-patient database of drug X, this gives an incidence of 1/4 or 25%. Taking away the one case or adding one more MI would change the rate to 0% (0/3) or 40% (2/5). If the database had 1,000/4,000 cases, adding one or taking one away would have a negligible effect.

Another problem may occur if the databases are inappropriate. It may not be appropriate to compare the reporting frequency of a particular AE in the population treated with drug X against the frequency of that AE in the whole AE database. If the treatment for drug X is for, say, breast cancer, and is given only to elderly women, then comparing the frequency of an AE in the elderly female population versus the whole database in which elderly women are not predominant may give misleading results.

Another problem may occur if drug X is frequently prescribed with drug Y and drug Y (“bystander”) is known to produce a particular AE. Unless this is accounted for, it may appear in a simple PRR that drug X caused the AE when it was probably due to drug Y.

Similarly, certain common comorbid conditions or diseases may produce a high number of AEs that are due to the disease and not the drug.

Finally, if the safety database used for the denominator of the PRR is small or has a high proportion of a particular type of patient or disease this may also produce flawed PRRs. Various other statistical methods, or filters, may be added to this calculation to refine the technique to attempt to increase sensitivity. Some have adopted a rule of thumb that signals are worth pursuing if the PRR is more than 3.0, the chi-squared value is more than 4, and that there are at least three of the particular AE in question. Thus, if one has a sufficiently large database, the PRR could be programmed to run periodically (e.g., monthly or quarterly) using the filters as noted to generate possible signals. This method will be less useful if MedDRA coding is not crisp and correct. As always, the issue here is generating too many signals with too many false positives for the personnel available to review the signals.