Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Baseline characteristics of patients enrolled in the AZIMUTH trial: an e-health-integrated, smartphone app-based model of care for heart failure patients.

European heart journal open·2026
Same author

An Interactive Digital Dashboard for Patient Monitoring and Management in a Continuity of Care Centre: Development and Preliminary Usability Evaluation Study.

JMIR formative research·2026
Same author

Building the adult growth hormone deficiency data mart: a Real-World model of AI-driven clinical data extraction in a single Italian center.

Journal of endocrinological investigation·2026
Same author

Digital GO: A Clinical Decision-Support Dashboard for Gynecologic Oncology Tumor Board.

Studies in health technology and informatics·2026
Same author

From Report to Record: Prompt-Based Information Extraction from Gynecology Oncology Reports Using LLMs.

Studies in health technology and informatics·2026
Same author

A Real-Time Clinical Text Information Extractor via LLM.

Studies in health technology and informatics·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Enhancing Tumor Content through Tumor Macrodissection
10:04

Enhancing Tumor Content through Tumor Macrodissection

Published on: February 12, 2022

Building an RWD Oncology Data Mart for Diffuse Large B-Cell Lymphoma: From Data Integration to Clinical Insight.

Laura Antenucci1,2, Edoardo Pompei3, Carlotta Masciocchi1

  • 1Real World Data Facility, Gemelli Generator, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

A new Diffuse Large B-Cell Lymphoma (DLBCL) Data Mart integrates diverse patient data for comprehensive analysis. This tool enhances understanding of DLBCL progression and treatment effectiveness using real-world data.

Keywords:
Data MartDiffuse Large B-Cell Lymphoma (DLBCL)OncologyPatient journeyReal-Word Evidence (RWE)Real-World Data (RWD)

More Related Videos

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

Related Experiment Videos

Last Updated: May 24, 2026

Enhancing Tumor Content through Tumor Macrodissection
10:04

Enhancing Tumor Content through Tumor Macrodissection

Published on: February 12, 2022

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

Area of Science:

  • Oncology
  • Hematology
  • Data Science

Background:

  • Diffuse Large B-Cell Lymphoma (DLBCL) is an aggressive, heterogeneous non-Hodgkin lymphoma with variable clinical presentations and outcomes.
  • Real World Data (RWD) offer valuable insights into patient characteristics, disease progression, and treatment effectiveness in routine clinical practice.

Purpose of the Study:

  • To develop a standardized framework for integrating heterogeneous data relevant to DLBCL.
  • To create a system for automated treatment line identification and longitudinal patient history reconstruction.
  • To establish a platform for analyzing DLBCL patient trajectories and generating Real World Evidence (RWE).

Main Methods:

  • Development of a DLBCL-specific Data Mart integrating demographics, laboratory, histopathological, therapeutic, and progression data.
  • Implementation of automated systems for identifying treatment lines and reconstructing patient histories, including chemotherapy, radiotherapy, relapse, and mortality.
  • Creation of an interactive dashboard for visualizing individual disease trajectories over time.

Main Results:

  • The Data Mart successfully integrates data from 1,235 DLBCL patients.
  • Facilitates systematic analysis of therapies, patient responses, and disease progression.
  • Provides a reproducible and scalable platform for RWE generation.

Conclusions:

  • The DLBCL Data Mart effectively leverages RWD to support research and clinical decision-making.
  • Demonstrates the potential of standardized data integration for advancing oncology research.
  • Serves as a model for developing similar data resources in other cancer domains.