ReviewBlood neoplasia2026
Predictors of sensitivity to immune therapies in classic Hodgkin lymphoma.
Review in Blood neoplasia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune checkpoint blockade, particularly programmed cell death protein 1 inhibition, has redefined the management of classic Hodgkin lymphoma (cHL), achieving unprecedented efficacy in relapsed/refractory settings. Yet, durable benefit is not universal, because mechanisms of primary and acquired resistance remain incompletely understood. This review integrates current knowledge on predictors of sensitivity to immune therapies in cHL across clinical, biological, and technological dimensions. Established predictors, including disease burden, previous treatment exposure, CD30 intensity, programmed death-ligand 1 (PD-L1)/PD-L2 copy number gains, and loss of major histocompatibility complex expression, offer valuable but incomplete prognostic information. Tumor microenvironmental features such as macrophage polarization, T-cell exhaustion, and immune spatial organization further refine response prediction, whereas circulating biomarkers such as soluble PD-L1, circulating tumor DNA kinetics, and cytokine profiles provide noninvasive insights. Molecular and cellular pathways underlying resistance encompass genetic and epigenetic alterations, immune editing, and adaptive checkpoint upregulation. Emerging predictive frameworks, spanning multiomics and spatial profiling, radiomics, artificial intelligence, and microbiome-host cross talk, promise to enhance precision in patient stratification. Finally, the review outlines key challenges and research priorities for translating these multidimensional biomarkers into clinical trials and practice. A unified predictive framework integrating clinical, molecular, and computational indicators may ultimately enable personalized immunotherapy and overcome resistance in cHL.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.