Showing papers in "Cancer Cytopathology in 2001"

Immunocytochemistry in effusion cytology

Abstract: BACKGROUND Cytology plays a pivotal role in the diagnosis of pleural effusions. In many cases, immunocytochemistry (ICC) is required to elucidate the etiology of the atypical cells. Effusions are samples that present unique problems for ICC. To date there is no standardization of ICC methods for effusions and cytology in general. METHODS The authors review the most commonly used cytologic preparations, fixatives, and antibodies used in effusion ICC. RESULTS Through the utilization of cell block preparations and a panel of antibodies appropriate for the differential diagnosis in question, ICC conditions utilized in surgical pathology can be most closely replicated. CONCLUSIONS ICC may provide reliable insights into various diagnostic dilemmas in effusion cytology, provided that laboratory standardization practices are followed. Cancer (Cancer Cytopathol) 2001;93:293–308. © 2001 American Cancer Society.

Less medical intervention after sharp demarcation of Grade 1-2 cervical intraepithelial neoplasia smears by neural network screening†

Abstract: BACKGROUND. Neural network technology has been used for the daily screening of cervical smears in The Netherlands since 1992. The authors believe this method might have the potential to demarcate diagnoses of Grade 1-2 cervical intraepithelial neoplasia (CIN 1-2). METHODS. Of 133,196 women who were screened between 1992-1995, there were 2236 CIN 1-2 smears; 1128 of which were detected by means of neural network screening (NNS) (n = 83,404 women) and 1108 of which were diagnosed by conventional screening (n = 49,792 women). Cytologic and clinical outcomes (first cytologic or histologic follow-up diagnosis) were retrieved for all the women in the study population (n = 1920). Stratification based on clinical outcome resulted in the cases being grouped as overdiagnosed, concordant, or underdiagnosed. The smears were performed by general practitioners, whereas the biopsies were obtained by gynecologists. RESULTS. The prevalence rate for CIN 1-2 was 1.15% (95% confidence interval [95% CI], 1.08-1.23%) for NNS and 1.92% (95% CI, 1.80-2.04%) for conventional diagnosis (P <0.001). Concordance with histology was significantly higher for NNS (53.9%; 95% CI, 50.7-57.0%) compared with conventional screening (29.2%; 95% CI, 26.4-32.2%). In addition, overdiagnosis was significantly lower for cases diagnosed by NNS (39.4%; 95% CI, 36.3-42.4%) compared with cases diagnosed by conventional screening (62.4%; 95% CI, 59.3-65.5%). CONCLUSIONS. Neural network-based screening can lead to fewer women being burdened unnecessarily with a cytologic diagnosis of CIN 1-2 by resulting in a sharp demarcation in these diagnoses and a corresponding reduction in unnecessary medical interventions. [See editorial on pages 171-172, this issue.] Cancer (Cancer Cytopathol) 2001;93:173-178. (C) 2001 American Cancer Society.