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.

Developing Novel Genomic Risk Stratification Models in Soft Tissue and Uterine Leiomyosarcoma.

Purpose: Leiomyosarcomas (LMS) are clinically and molecularly heterogeneous tumors. Despite recent large-scale genomic studies, current LMS risk stratification is not informed by molecular alterations. We propose a clinically applicable genomic risk stratification model.

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.

Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Adjuvant Therapy Era.

Purpose: Traditional risk stratification schemes in gastrointestinal stromal tumors (GIST) were defined in the pre-imatinib era and rely solely on clinicopathologic metrics. We hypothesize that genomic-based risk stratification is prognostically relevant in the current era of tyrosine kinase inhibitor (TKI) therapeutics.

Experimental Design: Comprehensive mutational and copy-number profiling using MSK-IMPACT was performed.

Histology-Specific Prognostication for Radiation-Associated Soft Tissue Sarcoma.

Purpose: Radiation-associated sarcomas (RAS) are rare but aggressive malignancies. We sought to characterize the histology-specific presentation and behavior of soft tissue RAS to improve individualized prognostication.

Methods: A single-institutional prospectively maintained database was queried for all patients with primary, nonmetastatic RAS treated with surgical resection from 1982 to 2019.

Clinical sequencing of soft tissue and bone sarcomas delineates diverse genomic landscapes and potential therapeutic targets.

The genetic, biologic, and clinical heterogeneity of sarcomas poses a challenge for the identification of therapeutic targets, clinical research, and advancing patient care. Because there are > 100 sarcoma subtypes, in-depth genetic studies have focused on one or a few subtypes. Herein, we report a comparative genetic analysis of 2,138 sarcomas representing 45 pathological entities.

Prognostic stratification of clinical and molecular epithelioid hemangioendothelioma subsets.

Epithelioid hemangioendothelioma is a low-grade malignant vascular tumor with an intermediate clinical behavior between benign hemangiomas and high-grade angiosarcomas. Pathologic or molecular factors to predict this clinical heterogeneity are not well defined. A WWTR1-CAMTA1 fusion is present in most classic epithelioid hemangioendothelioma, regardless of their clinical behavior, suggesting that additional genetic abnormalities might be responsible in driving a more aggressive biology.

Yield of Colonoscopy in Identification of Newly Diagnosed Desmoid-Type Fibromatosis with Underlying Familial Adenomatous Polyposis.

Background: Desmoid-type fibromatosis can arise in patients with familial adenomatous polyposis (FAP), therefore patients with desmoids often undergo colonoscopy to rule out FAP. Because finding FAP is uncommon, we sought to define subsets of desmoid patients in whom colonoscopy frequently identified FAP.

Methods: Patients with desmoid-type fibromatosis were identified from surgery and pathology databases at a single institution, and information on colonoscopy and FAP diagnosis was collected retrospectively.