ArticleJournal for immunotherapy of cancer2026
Toward organ preservation in thoracic malignancies: why interpretable multimodal radiopathomics matters in the neoadjuvant immunotherapy era.
Article in Journal for immunotherapy of cancer, 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.
- Causal AI for cancer immunotherapy: a narrative framework review of target trial emulation, treatment-effect learning and clinical translation.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neoadjuvant immunotherapy has increased rates of pathological complete response (pCR) in thoracic malignancies and has renewed interest in organ-preserving strategies. In esophageal squamous cell carcinoma (ESCC), the Surgery As Needed for Oesophageal cancer (SANO) trial has shown that active surveillance may be feasible for selected patients who achieve clinical complete response (cCR) after neoadjuvant chemoradiotherapy. Nevertheless, cCR remains an imperfect surrogate for pCR, and residual disease may still be present despite apparently negative post-treatment assessments. In this context, the recent study by Qi and colleagues is particularly noteworthy. In a multicenter retrospective cohort of 335 patients with ESCC treated with neoadjuvant chemoimmunotherapy followed by surgery, the authors developed and externally validated an interpretable multimodal radiopathomics model integrating pretreatment contrast-enhanced CT radiomics and H&E whole slide image pathomics. Their intermediate fusion model outperformed unimodal radiomics, unimodal pathomics, and a late fusion approach across validation cohorts, while also providing feature-level and case-level interpretability. This work is important because it illustrates why multimodal prediction may better capture treatment response than single-modality assessment alone and because it uses data already generated in routine care. At the same time, challenges related to manual annotation, pathology field selection, digital workflow standardization, and external generalizability remain substantial. We believe this study represents an important step toward biologically informed, clinically usable prediction of pCR and offers a valuable framework for refining organ-preserving strategies in the era of neoadjuvant immunotherapy.
Indexed as
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.