Diagnostic Performance of Immunohistochemistry Compared to Molecular Techniques for Microsatellite Instability and p53 Mutation Detection in Endometrial Cancer.
Sylvie StreelAlixe SalmonAdriane DheurVincent BoursNatacha LeroiLionel HabranKatty DelbecqueFrédéric GoffinClémence PleyersAthanasios KakkosElodie GonneLaurence SeidelFrédéric KridelkaChristine GennigensPublished in: International journal of molecular sciences (2023)
Molecular algorithms may estimate the risk of recurrence and death for patients with endometrial cancer (EC) and may impact treatment decisions. To detect microsatellite instabilities (MSI) and p53 mutations, immunohistochemistry (IHC) and molecular techniques are used. To select the most appropriate method, and to have an accurate interpretation of their results, knowledge of the performance characteristics of these respective methods is essential. The objective of this study was to assess the diagnostic performance of IHC versus molecular techniques (gold standard). One hundred and thirty-two unselected EC patients were enrolled in this study. Agreement between the two diagnostic methods was assessed using Cohen's kappa coefficient. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the IHC were calculated. For MSI status, the sensitivity, specificity, PPV and NPV were 89.3%, 87.3%, 78.1% and 94.1%, respectively. Cohen's kappa coefficient was 0.74. For p53 status, the sensitivity, specificity, PPV, and NPV were 92.3%, 77.1%, 60.0% and 96.4%, respectively. Cohen's kappa coefficient was 0.59. For MSI status, IHC presented a substantial agreement with the polymerase chain reaction (PCR) approach. For the p53 status, the moderate agreement observed between IHC and next generation sequencing (NGS) methods implies that they cannot be used interchangeably.
Keyphrases
- endometrial cancer
- nuclear factor
- machine learning
- healthcare
- ejection fraction
- newly diagnosed
- toll like receptor
- prognostic factors
- magnetic resonance
- computed tomography
- immune response
- magnetic resonance imaging
- deep learning
- dna methylation
- chronic kidney disease
- combination therapy
- real time pcr
- high intensity
- replacement therapy
- contrast enhanced