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Impact of a Modified HistoGel Method for Processing Endocervical Curettage Specimens on Diagnostic Yield.

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OBJECTIVES Endocervical curettage (ECC) specimens may be limited by scant tissue. We evaluated whether a cellular concentration processing method could improve their diagnostic quality. METHODS Between October 2018 and June… Click to show full abstract

OBJECTIVES Endocervical curettage (ECC) specimens may be limited by scant tissue. We evaluated whether a cellular concentration processing method could improve their diagnostic quality. METHODS Between October 2018 and June 2019, ECC specimens were assigned chronologically to one of two groups: nonconcentrated ECC (NECC) or concentrated ECC (CECC). NECC specimens underwent routine histologic processing. CECC specimens were processed using a published HistoGel-based cell block method. We reviewed diagnoses for ECCs, concurrent cervical biopsies and/or loop electrosurgical excision procedures (LEEPs), and preceding Papanicolaou (Pap) smears. We performed multivariate logistic regression analyses to evaluate the impact of processing method on ECC adequacy and discordance between Pap smear and worst tissue diagnoses. RESULTS NECC and CECC adequacy was 88.2% and 84.7% (P = .06). ECC adequacy was greater if concurrent biopsy/LEEP was performed (odds ratio [OR] = 1.76, P < .01). Discordance between Pap smear and worst tissue diagnoses was 9.5% and 13.3% (P = .04) for cases with NECC and CECC processing, although processing method was not significant in multivariate analysis (OR = 0.74, P = .11). Adequate ECC sampling and concurrent biopsy/LEEP were independently associated with concordance between Pap smear and worst tissue diagnosis (OR = 0.46, P < .01 and OR = 0.65, P = .02). CONCLUSIONS ECC processing method did not significantly affect either specimen adequacy (P = .06) or diagnostic discordance (P = .11) when controlled for other factors.

Keywords: processing method; ecc; method; endocervical curettage

Journal Title: American journal of clinical pathology
Year Published: 2020

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