SynthesisInternational journal of molecular sciences2022
Artificial Intelligence for Predicting Microsatellite Instability Based on Tumor Histomorphology: A Systematic Review.
Synthesis in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Radiomics and artificial intelligence-based prediction of tumor response in digestive system neoplasm: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Review
- Deep learning analysis of breast cancer histology predicts ATM pathogenic variant carrier status.NPJ digital medicine · 2026Article
- Digital pathology and artificial intelligence in breast and gynecologic oncology: from molecular prediction to multimodal integration.Frontiers in oncology · 2026Review
- Artificial Intelligence Tools for Supporting Histopathologic and Molecular Characterization of Gynecological Cancers: A Review.Journal of clinical medicine · 2025Review
- Application of deep learning models in gastric cancer pathology image analysis: a systematic scoping review.BMC cancer · 2025Article
- Artificial intelligence as a predictive tool for gastric cancer: Bridging innovation, clinical translation, and ethical considerations.World journal of gastrointestinal oncology · 2025Article
- Integrating AI into Cancer Immunotherapy-A Narrative Review of Current Applications and Future Directions.Diseases (Basel, Switzerland) · 2025Review
- Artificial Intelligence Models for the Detection of Microsatellite Instability from Whole-Slide Imaging of Colorectal Cancer.Diagnostics (Basel, Switzerland) · 2024Review
- Microsatellite instability: A 2024 update.Cancer science · 2024Review
- Detecting microsatellite instability in colorectal cancer using Transformer-based colonoscopy image classification and retrieval.PloS one · 2024Article
- What are microsatellites and how to choose the best tool: a user-friendly review of SSR and 74 SSR mining tools.Frontiers in genetics · 2024Review
- Artificial Intelligence in Predicting Microsatellite Instability and KRAS, BRAF Mutations from Whole-Slide Images in Colorectal Cancer: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Immune Biomarkers in Triple-Negative Breast Cancer: Improving the Predictivity of Current Testing Methods.Journal of personalized medicine · 2023Review
- Diagnostic Performance of Immunohistochemistry Compared to Molecular Techniques for Microsatellite Instability and p53 Mutation Detection in Endometrial Cancer.International journal of molecular sciences · 2023Article
- Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions.Frontiers in oncology · 2023Review
- Accurate diagnostic tissue segmentation and concurrent disease subtyping with small datasets.Journal of pathology informatics · 2023Article
- Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical Review.Journal of personalized medicine · 2022Review
- Learn to Estimate Genetic Mutation and Microsatellite Instability with Histopathology H&E Slides in Colon Carcinoma.Cancers · 2022Article
- Clinicopathological characteristics of high microsatellite instability/mismatch repair-deficient colorectal cancer: A narrative review.Frontiers in immunology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microsatellite instability (MSI)/defective DNA mismatch repair (dMMR) is receiving more attention as a biomarker for eligibility for immune checkpoint inhibitors in advanced diseases. However, due to high costs and resource limitations, MSI/dMMR testing is not widely performed. Some attempts are in progress to predict MSI/dMMR status through histomorphological features on H&E slides using artificial intelligence (AI) technology. In this study, the potential predictive role of this new methodology was reviewed through a systematic review. Studies up to September 2021 were searched through PubMed and Embase database searches. The design and results of each study were summarized, and the risk of bias for each study was evaluated. For colorectal cancer, AI-based systems showed excellent performance with the highest standard of 0.972; for gastric and endometrial cancers they showed a relatively low but satisfactory performance, with the highest standard of 0.81 and 0.82, respectively. However, analyzing the risk of bias, most studies were evaluated at high-risk. AI-based systems showed a high potential in predicting the MSI/dMMR status of different cancer types, and particularly of colorectal cancers. Therefore, a confirmation test should be required only for the results that are positive in the AI test.
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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.