Karel Maelegheer's research while affiliated with Algemeen Ziekenhuis Sint-Lucas and other places

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Publications (1)


Correlation graph between IC results of UZ Ghent vs. AML
Comparison of CN values of IC signals between the self-collected and clinician-collected samples
Evaluation of the applicability of internal controls on self-collected samples for high-risk human papillomavirus is needed
  • Article
  • Full-text available

November 2023

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19 Reads

BMC Women's Health

Bo Verberckmoes

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Karel Maelegheer

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Background Self-collection of cervical samples to detect high-risk human papillomavirus (hr-HPV) is a trending topic in primary cervical cancer screening. This study evaluates the applicability of a self-sampling device to routine molecular procedures for hr-HPV detection. Methods In a primary health care facility in Kinshasa, Congo, 187 self-collected samples (Evalyn Brush) were gathered and sent to Ghent University Hospital (UZ Ghent) and Algemeen Medisch Labo (AML) in Belgium where routine tests for hr-HPV were applied (Abbott RealTime hr-HPV and qPCR (E6/E7), respectively). Sample type effect was evaluated by comparing the internal control (IC) between the self-collected samples and routine, clinician-taken samples randomly selected from the UZ Ghent archive. Results In UZ Ghent an error was encountered in 9.1% (17/187) of self-collected samples due to a lack of IC signal. The hr-HPV prevalence in the remaining 170 samples was 18,8%. Comparing IC results between the self-collected and clinician-collected groups, a significant difference (p < 0,001) was found, with higher IC signals in the clinician-collected group. In AML, an error was encountered in 17.6% (33/187) of samples, including 16/17 of the UZ Ghent. The remaining sample with IC error gave a negative result in AML. Among the 154 samples without IC error at AML, a correlation of 90% was seen between both laboratories with a 77% negativity rate. Conclusion Testing the self-collected specimens by 2 routine hr-HPV tests gave a high IC error rate (9.1–17.6%). A possible solution would be to differentiate cut-offs for IC values depending on sample type, as currently used cut-offs are set for clinician-taken samples.

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