Evidence map›Paper›PMID 27052524›Full record

ArticleAcademic radiology2016

The Attenuation Distribution Across the Long Axis (ADLA): Preliminary Findings for Assessing Response to Cancer Treatment.

Nikita Lakomkin, Hakmook Kang, Bennett Landman, M Shane Hutson, Richard G Abramson

Abstract read
In one paragraph

Article in Academic radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nikita LakomkinDepartment of Radiology and Radiological Sciences, 1161 21st Ave. Nashville, TN 37232, Vanderbilt University, Nashville, TN 37235-3779, USA.
Hakmook KangDepartment of Biostatistics, Vanderbilt University, Nashville, Tennessee, USA.
Bennett LandmanCollege of Arts and Science, Vanderbilt University, Nashville, Tennessee, USA.
M Shane HutsonCollege of Arts and Science, Vanderbilt University, Nashville, Tennessee, USA.
Richard G AbramsonDepartment of Radiology and Radiological Sciences, 1161 21st Ave. Nashville, TN 37232, Vanderbilt University, Nashville, TN 37235-3779, USA; Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA. Electronic address: richard.abramson@vanderbilt.edu.

Funding

TISSUE CoreP50CA098131 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PARK, BEN HO, PIETENPOL, JENNIFER A · 2003 to 2024
$48.7M
NCI NIH HHS P50 CA098131
6 · The paper itself

Abstract

RATIONALE AND

objectivesNovel image analysis methods may be useful adjuncts to standard cancer treatment response assessment techniques. The attenuation distribution across the long axis (ADLA) is a simple measure of lesion heterogeneity that can be obtained while measuring the long axis diameter of a target lesion. The purpose of this study was to obtain preliminary validation of the ADLA method for predicting treatment response in a small clinical trial. MATERIALS AND

methodsUnder an Institutional Review Board waiver, we obtained de-identified imaging and clinical data from a phase 2 trial of an investigational anticancer therapy at our institution. We retrospectively analyzed all patients with at least one liver metastasis measuring ≥15 mm on baseline contrast-enhanced computed tomography. For each patient at every imaging time point, up to two target liver lesions were evaluated using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and ADLA measurements. The ADLA was obtained as the standard deviation of the post-contrast computed tomography attenuation values in the portal venous phase across a linear function spanning the long-axis diameter. Using Kaplan-Meier survival analysis, the log-rank test was used to evaluate the ability of RECIST 1.1 and ADLA measurements to discriminate patients with longer overall survival (OS).

resultsFifteen patients met inclusion criteria. Median survival was 149 days (range 57-487). Best overall response by the ADLA method successfully separated patients with longer OS (p = .04). Best overall response by RECIST 1.1 did not discriminate patients with longer survival (P > .05).

conclusionIn retrospective data analysis from a phase 2 clinical trial, the ADLA method was more predictive of OS than RECIST 1.1. Further studies are needed to explore the utility of this measurement in predicting response to cancer treatment.

Indexed as

Response Evaluation Criteria in Solid TumorsColorectal NeoplasmsContrast MediaHumansImage Processing, Computer-AssistedKaplan-Meier EstimateLiver NeoplasmsPortal VeinRetrospective StudiesTomography, X-Ray ComputedTreatment OutcomeContrast Mediabevacizumabcancer imagingImaging biomarkeroverall survivalquantitative imagingresponse assessment

Identifiers

PMID27052524
PMCPMC5826561

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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.