ArticleJournal of statistical science and application
Building Classification Models with Combined Biomarker Tests: Application to Early Detection of Liver Cancer.
Article in Journal of statistical science and application. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed.
- Article
- Early detection of pancreatic cancer: Study design and analytical considerations in biomarker discovery and early phase validation studies.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2024Review
- Urine DNA biomarkers for hepatocellular carcinoma screening.British journal of cancer · 2022Article
- Preoperative Combined Prediction Models Have Superior Capability in Predicting Survival as the Child-Pugh Grade in Patients with HCC after Interventional Embolotherapy.Cancer management and research · 2020Article
- Development and Evaluation of Novel Statistical Methods in Urine Biomarker-Based Hepatocellular Carcinoma Screening.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Early detection of hepatocellular carcinoma (HCC) is critical for the effective treatment. Alpha fetoprotein (AFP) serum level is currently used for HCC screening, but the cutoff of the AFP test has limited sensitivity (~50%), indicating a high false negative rate. We have successfully demonstrated that cancer derived DNA biomarkers can be detected in urine of patients with cancer and can be used for the early detection of cancer (Jain et al., 2015; Lin et al., 2011; Song et al., 2012; Su, Lin, Song, & Jain, 2014; Su, Wang, Norton, Brenner, & Block, 2008). By combining urine biomarkers (uBMK) values and serum AFP (sAFP) level, a new classification model has been proposed for more efficient HCC screening. Several criterions have been discussed to optimal the cutoff for uBMK score and sAFP score. A joint distribution of sAFP and uBMK with point mass has been fitted using maximum likelihood method. Numerical results show that the sAFP data and uBMK data are very well described by proposed model. A tree-structured sequential test can be optimized by selecting the cutoffs. Bootstrap simulations also show the robust classification results with the optimal cutoff.
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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.