Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.

Background: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We aimed to apply state-of-the-art, interpretable artificial intelligence (ie, predictions or prescription logic that can be easily understood) methods on real-world data to establish which groups of patients with GISTs should receive adjuvant imatinib, its optimal treatment duration, and the benefits conferred by this therapy.

Methods: In this observational cohort study, we considered for inclusion all patients who underwent resection of primary, non-metastatic GISTs at the Memorial Sloan Kettering Cancer Center (MSKCC; New York, NY, USA) between Oct 1, 1982, and Dec 31, 2017, and who were classified as intermediate or high risk according to the Armed Forces Institute of Pathology Miettinen criteria and had complete follow-up data with no missing entries.

From Molecular Biology to Novel Immunotherapies and Nanomedicine in Uveal Melanoma.

Molecular biology studies of uveal melanoma have resulted in the development of novel immunotherapy approaches including tebentafusp-a T cell-redirecting bispecific fusion protein. More biomarkers are currently being studied. As a result, combined immunotherapy is being developed as well as immunotherapy with bifunctional checkpoint inhibitory T cell engagers and natural killer cells.

An interpretable AI model for recurrence prediction after surgery in gastrointestinal stromal tumour: an observational cohort study.

Background: There are several models that predict the risk of recurrence following resection of localised, primary gastrointestinal stromal tumour (GIST). However, assessment of calibration is not always feasible and when performed, calibration of current GIST models appears to be suboptimal. We aimed to develop a prognostic model to predict the recurrence of GIST after surgery with both good discrimination and calibration by uncovering and harnessing the non-linear relationships among variables that predict recurrence.

Treatment of Gastrointestinal Stromal Tumors (GISTs): A Focus on Younger Patients.

Gastrointestinal stromal tumors (GISTs) originate from Cajal's cells and are the most common mesenchymal neoplasms of the gastrointestinal tract. GISTs in young adults, i.e.