Neoplastic cell percentage estimation in tissue samples for molecular oncology: recommendations from a modified Delphi study

. 2019 Sep ; 75 (3) : 312-319. [epub] 20190718

Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid31054167

AIMS: Results from external quality assessment revealed considerable variation in neoplastic cell percentages (NCP) estimation in samples for biomarker testing. As molecular biology tests require a minimal NCP, overestimations may lead to false negative test results. We aimed to develop recommendations to improve the NCP determination in a prototypical entity - colorectal carcinoma - that can be adapted for other cancer types. METHODS AND RESULTS: A modified Delphi study was conducted to reach consensus by 10 pathologists from 10 countries with experience in determining the NCP for colorectal adenocarcinoma. This study included two online surveys and a decision-making meeting. Consensus was defined a priori as an agreement of > 80%. All pathologists completed both surveys. Consensus was reached for 8 out of 19 and 2 out of 13 questions in the first and second surveys, respectively. Remaining issues were resolved during the meeting. Twenty-four recommendations were formulated. Major recommendations resulted as follows: only pathologists should conduct the morphological evaluation; nevertheless molecular biologists/technicians may estimate the NCP, if specific training has been performed and a pathologist is available for feedback. The estimation should be determined in the area with the highest density of viable neoplastic cells and lowest density of inflammatory cells. Other recommendations concerned: the determination protocol itself, needs for micro- and macro-dissection, reporting and interpreting, referral practices and applicability to other cancer types. CONCLUSION: We believe these recommendations may lead to more accurate NCP estimates, ensuring the correct interpretation of test results, and might help in validating digital algorithms in the future.

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