Pap Smear Refined
Pap Smear Refined
The high proportion of false negatives associated with Pap smears spurred the development of more effective collection and diagnostic techniques for cervical cells. The Pap smear, a universal standard in the detection of cervical cancer, has recently been refined by two new approaches that greatly reduce the incidence of false negatives.
At the annual meeting of the Society of Gynecologic Oncologists, study data was presented that showed that cervical cancer and precancer detection can be enhanced by the use of neural network (artificial intelligence) computer technology. More than 16,000 smears, reprocessed by the computer-based PAPNET test, found many pre-cancerous abnormalities that had been missed by conventional screening. These slides were originally reported as negative despite presenting with an abnormality. PAPNET testing was shown to identify 10 times more false-negative smears than would have been detected by manually rescreening an equal number of smears.
The study was conducted by Laurie J. Mango, MD, of Neuromedical Systems, Inc. developer of the PAPNET test, and Gary L. Goldberg, MD and Irwin R. Merkatz, MD, both of the Albert Einstein College of Medicine. "Negative" smears were reviewed and reclassified across four categories: ASCUS/AGUS (atypical), LGSIL (low-grade squamous intraepithelial lesion), HGSIL (high grade), and carcinoma. Three academic laboratory sites provided the archived smears for review.
Mead Johnson and company recently agreed to copromote another refinement to the Pap smear. Cytyc corporation launched its ThinPrep Pap Test in January, 1997. In clinical trials , the test has proven to be significantly more effective than the conventional smear for the detection of low-grade and more severe lesions and to markedly improve specimen quality. Mead Johnson signed on to distribute and market the test to obstetricians and gynecologists throughout the United States. Currently, over 400 laboratories in the United States employ the ThinPrep system for use in the diagnosis of various cancers. The ThinPrep System consists of the ThinPrep 2000 Processor and related reagents, filters and other supplies.