Clinical trial · Observational
PLA for HCC and Esophageal ca Serum
Serum Biomarker Study for the Prognosis of Patients With Hepatocellular Carcinoma and Esophageal Cancer Undergoing Radiotherapy Using Multiplex Proximity Ligation Assay
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The primary goal of this study is to quantify the biomarkers of pre-radiation therapy(RT), during-RT, and post-RT serum samples from hepatocellular carcinoma (HCC) and esophageal cancer patients undergoing definitive or neoadjuvant RT, and to correlate them with tumor response, patterns of failure, survival outcome, and RT-related lung or liver toxicity. The secondary goal of this study is to set up the PLA platform in our institute for future biomarker test.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Esophageal Cancer | Malignant Esophageal Neoplasm | CURATED_EXACT | 0.92 |
| Hepatocellular Carcinoma | Hepatocellular Carcinoma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (1)
- label
- Hepatocellular Carcinoma and Esophageal Cancer
Primary outcomes (1)
- measure
- BIOMARKER PANEL SELECTION AND MODELING
- timeFrame
- 3 years
- description
- All statistical analyses completed in this study are executed using the R statistical computing environment. To select the discrete set of biomarkers used to fit models of HCC or esophageal cancer diagnosis, we use the R distribution of the Prediction Analysis of Microarrays statistical technique, PAMR. Logistic regression models are fit using the generalized linear model function in R.
Secondary outcomes (1)
- measure
- SURVIVAL AND RT-RELATED TOXICITY ANALYSIS AND MODELING
- timeFrame
- 3 years
- description
- Survival data are fit to a right-censored model using the Survival function in the R statistical computing environment. Univariate and multivariate Cox proportional hazards models are fit onto survival data using the coxph function. Hazard ratios are calculated as the ratios of risk by the increase or decrease of 1 log2 PLA unit (2-fold increase or decrease in serum concentration of a biomarker). Lung or liver toxicity is graded by Common Toxicity Criteria version 3.0. Grade of toxicity is defined as the categorical variable and is correlated with the ratios of risk by the increase or decrease of 1 log2 PLA unit.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 20 Years
- Maximum age
- 90 Years
Show eligibility criteria text
Inclusion Criteria: * Clinical diagnosis of locally advanced esophageal cancer or Hepatocellular Carcinoma, RT is indicated * Informed consent signed Exclusion Criteria: * not completed RT
References
Publications (0)
Data not yet available