ArticleClinical drug investigation2024
Prediction Model for Severe Thrombocytopenia Induced by Gemcitabine Plus Cisplatin Combination Therapy in Patients with Urothelial Cancer.
Article in Clinical drug investigation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting adverse drug event using machine learning based on electronic health records: a systematic review and meta-analysis.Frontiers in pharmacology · 2024Pooled it
- Optimizing Systemic Therapy for Advanced Sarcomas: Outcomes With Gemcitabine, Docetaxel, Cisplatin, and Everolimus in a Retrospective Single-Center Study.Cancer medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundChemotherapy-induced thrombocytopenia is often a use-limiting adverse reaction to gemcitabine and cisplatin (GC) combination chemotherapy, reducing therapeutic intensity, and, in some cases, requiring platelet transfusion.
objectiveA retrospective cohort study was conducted on patients with urothelial cancer at the initiation of GC combination therapy and the objective was to develop a prediction model for the incidence of severe thrombocytopenia using machine learning.
methodsWe performed receiver operating characteristic analysis to determine the cut-off values of the associated factors. Multivariate analyses were conducted to identify risk factors associated with the occurrence of severe thrombocytopenia. The prediction model was constructed from an ensemble model and gradient-boosted decision trees to estimate the risk of an outcome using the risk factors associated with the occurrence of severe thrombocytopenia.
resultsOf 186 patients included in this study, 46 (25%) experienced severe thrombocytopenia induced by GC therapy. Multivariate analyses revealed that platelet count ≤ 21.4 (×10
conclusionsPlatelet count, hemoglobin level, lymphocyte count, and gemcitabine dose contributed to the development of a novel prediction model to identify the incidence of GC-induced severe thrombocytopenia.
Indexed as
Identifiers
38684605What 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.