ReviewAcademic radiology2015
Pitfalls in RECIST Data Extraction for Clinical Trials: Beyond the Basics.
Review in Academic radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 37 citations in OpenAlex.
- Treatment of advanced BP-NETS with lanreotide autogel/depot vs placebo: the phase III SPINET study.Endocrine-related cancer · 2024Trial
- AI-Powered Lesion-Level Tumor Growth Inhibition Modeling Improves Model Stability and Prognostic Association With PFS.CPT: pharmacometrics & systems pharmacology · 2026Article
- Parameter efficient fine-tunning of foundation model to facilitate tumor response prediction for ovarian cancer patients.BMC medical imaging · 2025Article
- Article
- Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark.Nature communications · 2024Article
- RECIST 1.1 assessments variability: a systematic pictorial review of blinded double reads.Insights into imaging · 2024Review
- Tumor Response Evaluation Using iRECIST: Feasibility and Reliability of Manual Versus Software-Assisted Assessments.Cancers · 2024Article
- Dissociated response to PD-1 inhibitors combined with radiotherapy in patients with advanced metastatic solid tumors: a single-center experience.World journal of surgical oncology · 2023Article
- Circulating immune response proteins predict the outcome following disease progression of osimertinib treated epidermal growth factor receptor-positive non-small cell lung cancer patients.Translational lung cancer research · 2023Article
- Can we predict discordant RECIST 1.1 evaluations in double read clinical trials?Frontiers in oncology · 2023Article
- iRECIST-based versus non-standardized free text reporting of CT scans for monitoring metastatic renal cell carcinoma: a retrospective comparison.Journal of cancer research and clinical oncology · 2022Article
- Improved Multimodal Tumor Necrosis Imaging with IRDye800CW-DOTA Conjugated to an Albumin-Binding Domain.Cancers · 2022Article
- Radiologists and Clinical Trials: Part 2: Practical Statistical Methods for Understanding and Monitoring Independent Reader Performance.Therapeutic innovation & regulatory science · 2021Review
- Imaging for Response Assessment in Cancer Clinical Trials.Seminars in nuclear medicine · 2020Article
- What scans we will read: imaging instrumentation trends in clinical oncology.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Review
- Tumor growth rate as a metric of progression, response, and prognosis in pancreatic and intestinal neuroendocrine tumors.BMC cancer · 2019Article
- Developing global image feature analysis models to predict cancer risk and prognosis.Visual computing for industry, biomedicine, and art · 2019Article
- Radiologic Modalities and Response Assessment Schemes for Clinical and Preclinical Oncology Imaging.Frontiers in oncology · 2019Review
- Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker.Physics in medicine and biology · 2018Article
- Tumor response assessment: comparison between unstructured free text reporting in routine clinical workflow and computer-aided evaluation based on RECIST 1.1 criteria.Journal of cancer research and clinical oncology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Response Evaluation Criteria in Solid Tumors (RECIST) is a standardized methodology for determining therapeutic response to anticancer therapy using changes in lesion appearance on imaging studies. Many radiologists are now using RECIST in their routine clinical workflow, as part of consultative arrangements, or within dedicated imaging core laboratories. Although basic RECIST methodology is well described in published articles and online resources, inexperienced readers may encounter difficulties with certain nuances and subtleties of RECIST. This article illustrates a set of pitfalls in RECIST assessment considered to be "beyond the basics." These pitfalls were uncovered during a quality improvement review of a recently established cancer imaging core laboratory staffed by radiologists with limited prior RECIST experience. Pitfalls are presented in four categories: (1) baseline selection of lesions, (2) reassessment of target lesions, (3) reassessment of nontarget lesions, and (4) identification of new lesions. Educational and operational strategies for addressing these pitfalls are suggested. Attention to these pitfalls and strategies may improve the overall quality of RECIST assessments performed by radiologists.
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.