PloS one · 2026
Immunohistochemistry for c-MET, HLA class II, and CD68 does not show prognostic value in early-stage classic Hodgkin lymphoma patients in the EORTC-GELA H9 intergroup randomised trial.
СтатьяРандомизированное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Martinez Alcala Rodrigo, Visser Lydia, Fortpied Catherine, Fermé Christophe, Henry-Amar Michel, Aleman Berthe, Arens Anne, Juul Sidsel, Hayat Amjad, Hude Dragičević Ida, Hutchings Martin, Meijnders Paul, Mutsaers Pim, Paszkiewicz-Kozik Ewa, Rossetti Sára, Sureda Anna, Syrykh Charlotte, Tonino Sanne, Plattel Wouter, Diepstra Arjan
Аннотация
BACKGROUND: In classic Hodgkin lymphoma (cHL), identifying high-risk patients is crucial for tailored treatment. Clinical risk factors are useful, but there is room for improvement. Although many diagnostic tissue-based biomarkers have been described to correlate with prognosis, none have achieved the accuracy to be included into daily clinical practice.
METHODS: The most promising tissue biomarkers, c-MET, HLA class II, and CD68, were tested in early-stage cHL for prognostic validation, individually and in combination with each other and established clinical risk factors. All biomarkers were assessed by immunohistochemistry in diagnostic tissue of patients included in the EORTC-GELA H9 trial. A case-cohort design was used, with progression-free survival (PFS) as the primary endpoint (n = 257; 105 PFS events). Hazard ratios (HRs) were estimated using Cox regression models with Barlow weighting to account for the case-cohort structure.
RESULTS: c-MET expression was detected in the tumor cells in 67% (108/162) of evaluable cases, and cell-surface expression of HLA class II was observed in 51% (70/137), consistent with earlier studies. CD68 expression was scored as the percentage of tissue surface area stained, with scores above the median (9.4%) designated high. In univariate Cox regression analyses, the HRs for PFS were: 0.752 for c-MET (95% confidence interval (CI): 0.456-1.241); 0.854 for HLA class II (95% CI: 0.503-1.448); and 0.864 for CD68 (95% CI: 0.518-1.440). Since none of the biomarkers were significantly associated with PFS in univariate analysis, no further analyses combining the three biomarkers were performed.
CONCLUSIONS: Using a rigorous statistical approach, we found that none of the three candidate biomarkers correlated with patient outcomes. While this lack of validation may be explained by trial-specific factors, such as risk-adapted treatment, the exclusion of advanced-stage patients, or challenges in scoring, these biomarkers provide insufficient prognostic value for implementation in clinical practice.
REGISTRATION: NCT00005584 (https://clinicaltrials.gov/study/NCT00005584).
METHODS: The most promising tissue biomarkers, c-MET, HLA class II, and CD68, were tested in early-stage cHL for prognostic validation, individually and in combination with each other and established clinical risk factors. All biomarkers were assessed by immunohistochemistry in diagnostic tissue of patients included in the EORTC-GELA H9 trial. A case-cohort design was used, with progression-free survival (PFS) as the primary endpoint (n = 257; 105 PFS events). Hazard ratios (HRs) were estimated using Cox regression models with Barlow weighting to account for the case-cohort structure.
RESULTS: c-MET expression was detected in the tumor cells in 67% (108/162) of evaluable cases, and cell-surface expression of HLA class II was observed in 51% (70/137), consistent with earlier studies. CD68 expression was scored as the percentage of tissue surface area stained, with scores above the median (9.4%) designated high. In univariate Cox regression analyses, the HRs for PFS were: 0.752 for c-MET (95% confidence interval (CI): 0.456-1.241); 0.854 for HLA class II (95% CI: 0.503-1.448); and 0.864 for CD68 (95% CI: 0.518-1.440). Since none of the biomarkers were significantly associated with PFS in univariate analysis, no further analyses combining the three biomarkers were performed.
CONCLUSIONS: Using a rigorous statistical approach, we found that none of the three candidate biomarkers correlated with patient outcomes. While this lack of validation may be explained by trial-specific factors, such as risk-adapted treatment, the exclusion of advanced-stage patients, or challenges in scoring, these biomarkers provide insufficient prognostic value for implementation in clinical practice.
REGISTRATION: NCT00005584 (https://clinicaltrials.gov/study/NCT00005584).