ArticleJournal of personalized medicine2023
Nomogram for Predicting Recurrence-Free Survival of Primary Localized Gastrointestinal Stromal Tumor.
Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Performance of Survival Prediction Tools in Patients With Gastrointestinal Stromal Tumors: A Systematic Review and Meta-Analysis.Journal of surgical oncology · 2026Pooled it
- Comparison of nomograms and predictive tools in gastrointestinal stromal tumor.Journal of gastrointestinal oncology · 2026Article
- Correction: Ran et al. Nomogram for Predicting Recurrence-Free Survival of Primary Localized Gastrointestinal Stromal Tumor.Journal of personalized medicine · 2024Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to establish a new nomogram that predicts recurrence-free survival (RFS) after a complete surgical resection of primary localized gastrointestinal stromal tumors (GISTs); it also aimed to evaluate the discrimination, calibration, and clinical utility of the decision-making nomogram.
methodsThe clinicopathological data of patients with primary localized GISTs at the First Affiliated Hospital of Chongqing Medical University from January 2000 to June 2022 were retrospectively analyzed. The clinicopathological data were randomly split into two sets (7:3 ratio) for training and validation. Suitable variables for the construction of a nomogram for the 1-, 3-, and 5-year RFS were selected using univariate and multivariate Cox regression analyses. Receiver operating characteristic (ROC) analysis and a concordance index (C-index) were used to quantify the discrimination of the nomogram and were compared with four commonly used prognostic scoring systems: Memorial Sloan Kettering Cancer Center prognostic nomogram, National Institutes of Health-Fletcher staging system, Chen's prognostic nomogram, and Air Forces Institute of Pathology risk criteria-Miettinen staging system. The calibration and clinical utility for the decision-making nomogram were validated using calibration curves and decision curves, respectively.
resultsIn total, 641 patients were screened and analyzed in this retrospective, observational study. RFS was significantly related to tumor size, mitotic count, gender, DOG-1, and adjuvant therapy with imatinib according to the results of the multivariate and univariate Cox analyses. The nomogram was constructed using the above variables (all
conclusionsThe newly constructed nomogram based on tumor size, gender, mitotic count, DOG-1, and adjuvant treatment with imatinib exhibited an excellent performance and may serve as a prognostic scoring system to support therapeutic decision-making and individualized treatment for GISTs in China.
Indexed as
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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.