Evidence map›Paper›PMID 31011689›Full record

ArticleAdvances in radiation oncology

Increases in Serial Pretreatment

Nicolas D Prionas, Rie von Eyben, Esther Yi, Sonya Aggarwal, Jenny Shaffer, Jose Bazan, David Eastham, Peter G Maxim, Edward E Graves, Maximilian Diehn and 2 more

Abstract read
In one paragraph

Article in Advances in radiation oncology. 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

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

12 authors.

Nicolas D PrionasDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Rie von EybenDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Esther YiDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Sonya AggarwalDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Jenny ShafferSt. Anthony's Radiation Oncology Specialists, St. Anthony's Medical Center, St Louis, Missouri.
Jose BazanDepartment of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, Columbus, Ohio.
David EasthamDavid Grant Medical Center Radiation Oncology, Travis Air Force Base, Fairfield, California.
Peter G MaximDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Edward E GravesDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Maximilian DiehnDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Michael F GensheimerDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
Billy W LooDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeQuantitative changes in positron emission tomography with computed tomography imaging metrics over serial scans may be predictive biomarkers. We evaluated the relationship of pretreatment metabolic tumor growth rate (MTGR) and standardized uptake value velocity (SUVV) with disease recurrence or death in patients with early-stage non-small cell lung cancer treated with stereotactic ablative radiation therapy (SABR). METHODS AND MATERIALS: Under institutional review board approval, we retrospectively identified patients who underwent positron emission tomography with computed tomography at diagnosis and staging and simulation for SABR. Two cohorts underwent SABR between November 2005 to October 2012 (discovery) and January 2012 to April 2016 (validation). MTGR and SUVV were calculated as the daily change in metabolic tumor volume and maximum standardized uptake value, respectively. Cox proportional hazard models identified predictors of local, regional, and distant recurrence and death for the combined cohort. MTGR and SUVV thresholds dichotomizing risk of death in the discovery cohort were applied to the validation cohort.

resultsA total of 152 lesions were identified in 143 patients (92 lesions in 83 discovery cohort patients). In multivariable models, increasing MTGR trended toward increased hazard of distant recurrence (hazard ratio, 6.98; 95% confidence interval, 0.67-72.61;

conclusionsMTGR greater than 0.04 mL/d is prognostic of death in patients with non-small cell lung cancer treated with SABR. Increasing SUVV trends, nonsignificantly, toward increased risk of recurrence and death. MTGR and SUVV may be candidate imaging biomarkers to study in trials evaluating systemic therapy with SABR for patients at high risk of out-of-field recurrence.

Identifiers

PMID31011689
PMCPMC6460103

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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.