ArticleClinical and translational science2016
Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling.
Article in Clinical and translational science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 12 citations in OpenAlex.
- Quantitative Lesion-Level Modeling Reveals Organ-Dependent Therapeutic Response.Clinical pharmacology and therapeutics · 2026Article
- Clinical impact of circulating tumor DNA to track minimal residual disease in colorectal cancer patients. Hopes and limitations.ESMO gastrointestinal oncology · 2024Review
- Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Article
- Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Review
- A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.CPT: pharmacometrics & systems pharmacology · 2019Review
- A PK/PD Analysis of Circulating Biomarkers and Their Relationship to Tumor Response in Atezolizumab-Treated non-small Cell Lung Cancer Patients.Clinical pharmacology and therapeutics · 2019Article
- Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology.JCO clinical cancer informatics · 2018Article
- Transforming Translation: Impact of Clinical and Translational Science.Clinical and translational science · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 8 institutions in 1 country.
Funding
Abstract
Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model-based parameters of tumor burden change were estimated and compared with similarly sized samples from separate trials. Time-to-tumor growth (TTG) was computed from measurements recorded on case report forms and a second radiologist blinded to the form data. Response Evaluation Criteria in Solid Tumors (RECIST)-based progression-free survival (PFS) measures were perfectly concordant between the original forms data and the blinded radiologist re-evaluation (intraclass correlation coefficient = 1), but these routine interrater differences in the identification and measurement of target lesions were associated with an average 18-week delay (range, -20 to 55 weeks) in TTG (intraclass correlation coefficient = 0.32). To exploit computational metrics for improving statistical power in small clinical trials will require increased precision of tumor burden assessments.
Indexed as
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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.