ArticleBlood2023
Baseline PET radiomics outperforms the IPI risk score for prediction of outcome in diffuse large B-cell lymphoma.
Article in Blood, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 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
40 citing papers in PubMed.
- Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.BMC medical imaging · 2025Trial
- PET-guided early identification of CAR-T candidates in diffuse large b-cell lymphoma: a multidisciplinary expert consensus.European journal of nuclear medicine and molecular imaging · 2026Article
- Cell-free DNA genomic and fragmentomic features for early outcome prediction in large B cell lymphoma.Cell reports. Medicine · 2026Article
- A machine learning-derived sarcopenia index is associated with survival and nonrelapse mortality in DLBCL.Blood advances · 2026Article
- Splenic FDG PET uptake and CT volume as prognostic biomarkers in diffuse large B cell lymphoma.La Radiologia medica · 2026Article
- Article
- Development and validation of a radiomics nomogram for predicting outcomes following combined radiotherapy and modern chemotherapy in early-stage extranodal nasal-type NK/T-cell lymphoma: a multicenter study.Annals of hematology · 2026Article
- A convolutional neural network for fully automated total metabolic tumor volume delineation in patients with aggressive Non-Hodgkin lymphoma.European journal of nuclear medicine and molecular imaging · 2026Article
- Validation of an AI Method for Automated Lymphoma Metabolic Tumor Volume Segmentation Using a Public Benchmark PET/CT Dataset.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026Article
- A Lesion-adaptive Segmentation Approach for Tumor Delineation on FDG PET/CT in Diffuse Large B-cell Lymphoma Patients.European journal of nuclear medicine and molecular imaging · 2026Article
- BaselineFrontiers in oncology · 2026Article
- Automatic Lugano staging for risk stratification in lymphoma: a multicenter PET radiomics and machine learning study with survival analysis.Nuclear medicine communications · 2025Article
- Divergent prognostic utility of metabolic risk scores in large B-cell lymphoma subtypes: a real-world analysis.European journal of nuclear medicine and molecular imaging · 2025Article
- A prognostic index integrating deep learning baseline PET/CT biomarkers and multi-omics profiling in diffuse large B cell lymphoma.Cell reports. Medicine · 2025Article
- Risk prediction in diffuse large B-cell lymphoma improves when combining baseline PET features with interim PET response.Haematologica · 2025Article
- Large B-cell lymphoma (LBCL): EHA Clinical Practice Guidelines for diagnosis, treatment, and follow-up.HemaSphere · 2025Article
- Integration of [Leukemia · 2025Article
- Summary Report of the SNMMI AI Task Force Radiomics Challenge 2024.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025Article
- Prognostic Value of Multiple Manual Segmentation Methods for Diffuse Large B-Cell Lymphoma withCurrent oncology (Toronto, Ont.) · 2025Article
- Baseline total lesion glycolysis identifies high-risk patients with immunosuppressive signatures in early-stage natural killer/T-cell lymphoma.The oncologist · 2025Article
Corrections and comments
- Commented on by
Authors and funding
21 authors.
Funding
Abstract
The objective of this study is to externally validate the clinical positron emission tomography (PET) model developed in the HOVON-84 trial and to compare the model performance of our clinical PET model using the international prognostic index (IPI). In total, 1195 patients with diffuse large B-cell lymphoma (DLBCL) were included in the study. Data of 887 patients from 6 studies were used as external validation data sets. The primary outcomes were 2-year progression-free survival (PFS) and 2-year time to progression (TTP). The metabolic tumor volume (MTV), maximum distance between the largest lesion and another lesion (Dmaxbulk), and peak standardized uptake value (SUVpeak) were extracted. The predictive values of the IPI and clinical PET model (MTV, Dmaxbulk, SUVpeak, performance status, and age) were tested. Model performance was assessed using the area under the curve (AUC), and diagnostic performance, using the positive predictive value (PPV). The IPI yielded an AUC of 0.62. The clinical PET model yielded a significantly higher AUC of 0.71 (P < .001). Patients with high-risk IPI had a 2-year PFS of 61.4% vs 51.9% for those with high-risk clinical PET, with an increase in PPV from 35.5% to 49.1%, respectively. A total of 66.4% of patients with high-risk IPI were free from progression or relapse vs 55.5% of patients with high-risk clinical PET scores, with an increased PPV from 33.7% to 44.6%, respectively. The clinical PET model remained predictive of outcome in 6 independent first-line DLBCL studies, and had higher model performance than the currently used IPI in all studies.
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.