Rescreening in cervical cytology for quality control. When bad data is worse than no data or what works, what doesn't, and why

The currently mandated methods to measure the sensitivity of Papanicolaou smear interpretation (including the 5-year look back and review of 10% of negative smears) are misleading. They do not allow one to measure the true sensitivity of the test and allow only a small fraction of errors to be detected and corrected. Rapid prescreening and automated screening are the only methods that seem practically feasible, and will allow the sensitivity of the method to be measured on a routine basis, and, thereby allow a reduction in overall errors. Although emerging technologies, such as HPV testing, may allow alternative methods of measuring sensitivity, the most appropriate way to use and interpret these data in this context are not yet fully developed. Unfortunately, at present there seems to be little desire to change the way things are done, and, therefore, to accurately measure sensitivity in cervical cytology. The first task that needs to be undertaken in fixing a problem is to admit that one exists. At present, most laboratory directors believe that their own laboratory is performing satisfactorily. They may well be, although the laboratories lack an analytic method to demonstrate this, and, therefore, the need for better QA methods does not seem to be acute. There is some educational value to the currently practiced and mandated performance measures, the 5-year look back and review of 10% of negative smears. Most laboratory directors seem to be happy with their QA methods and are not concerned that the data that are derived from the 10% review of negative slides does not reflect their actual sensitivity of screening in any meaningful way. Unfortunately, the forces that are currently in place in the United States ensure that accurate measures of the sensitivity of cervical cytology interpretation are unlikely to be implemented beyond the level of individual experimentation. As long as the expectation of cytologists is that the error rates are significantly less than they actually are; as long as there is significant legal and financial risk to actually measuring the true sensitivity; and as long as fictitious measures of performance are not only advocated but mandated; the confluence of incentives will ensure that the true sensitivity of the test will never be measured on a routine basis. Despite all of this, it is possible that cervical cytology screening may, in fact, already be performing at an optimal level. Being able to measure this operating performance may not effect any improvement to the overall process. The ultimate arbiter in this debate will always be the demonstration of a reduction of cervical cancer morbidity and mortality with any new measure implemented. At the present time, there is only one solution to the quality control issue; a force from outside the system must change the balance of the aforementioned incentives. The promise of data from European experiences with rapid rescreening may show that this method is effective and accurate. Such data might make the current methods that are in use in the United States more open to change. So yes, the answer is that "bad" data may be worse than no data at all. The bad data that we have been collecting for more than a decade is as effective a trap as anyone could have devised to ensure that actually measuring the performance of cervical smear interpretation does not happen. The only question that remains is, "How we will be able to escape?"