ArticleTechnology in cancer research & treatment
Development and Validation of a Prediction Model for Venous Thrombus Embolism (VTE) in Patients With Colorectal Cancer.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Chronic Venous Disease and In-Hospital Venous Thromboembolism in Critically Ill Patients: A Retrospective Cohort Study of the MIMIC-IV Database.Journal of clinical medicine · 2026Article
- Development and Validation of a Predictive Nomogram for Venous Thromboembolism Risk in Multiple Myeloma Patients: A Single-Center Cohort Study in China.Biomedicines · 2025Article
- Emerging Biomarkers for Assessing Thrombotic Risk in Patients Receiving Direct Oral Anticoagulants (DOACs).Cardiovascular & hematological agents in medicinal chemistry · 2025Review
- Simple, Effective and Validated. VTE CASE Risk Assessment Score for Venous Thromboembolism in Metastatic Germ Cell Tumour Patients Before First-Line Chemotherapy.Cancer medicine · 2024Article
- Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms.Frontiers in oncology · 2024Article
- Construction and Validation of a Nomogram to Predict the Postoperative Venous Thromboembolism Risk in Patients with HGSOC.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer patients are at high risk of developing venous thromboembolism (VTE). The risk of VTE could be mitigated with the administration of prophylactic anticoagulants. Therefore, risk assessment models would be a useful tool in order to identify those patients who are at higher risk and will be benefited more by prophylactic anticoagulants. This study retrospectively examined 528 newly diagnosed colorectal cancer patients from January 2019 to January 2021. Specified logistic regression models were employed to screen the factors and establish prediction tools based on nomograms according to the final included variables. Discrimination, calibration, and clinical applicability were used to assess the performance of screening tools. In addition, internal verifications were conducted through 10-fold cross-verification, leave-one-out cross-validation, and Bootstrap verification. Four risk factors, closely related to the occurrence of VTE in colorectal cancer patients, were identified after univariate and multivariate logistic regression, including age, body mass index, activated partial thromboplastin time, and D-Dimer value. Besides, the risk assessment model named ABAD was built on the basis, displaying good discriminations and calibrations. The area under the curve was 0.705 (95% confidence interval [CI], 0.644 to 0.766). According to Hosmer-Lemeshow goodness-of-fit test, a good agreement between the predicted and observed VTE events in patients with newly-diagnosed gastrointestinal cancer was observed for χ2 = 6.864, P = .551. Internal validation was applied with a C-index of 0.669 in the 10-fold cross-verification, 0.658 in the leave-one-out cross verification and 0.684 in the bootstrap verification. We developed a prediction model called ABAD for newly diagnosed colorectal cancer patients, which can be used to predict the risk of VTE. After evaluation and internal verification, we believe that ABAD exhibited high predictive performance and availability and could be recommended.
Indexed as
Identifiers
What 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.