Evidence map›Paper›PMID 30850971›Full record

ArticleMolecular imaging and biology2019

How Often Do We Fail to Classify the Treatment Response with [

Maria Vittoria Mattoli, Maria Lucia Calcagni, Silvia Taralli, Luca Indovina, Bruce S Spottiswoode, Alessandro Giordano

Abstract read
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In one paragraph

Article in Molecular imaging and biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

6 authors.

Maria Vittoria MattoliNuclear Medicine Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo F. Vito 1, 00168, Rome, Italy. mvittoriamattoli@yahoo.it.ORCID http://orcid.org/0000-0002-2785-5514
Maria Lucia CalcagniNuclear Medicine Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo F. Vito 1, 00168, Rome, Italy.
Silvia TaralliNuclear Medicine Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo F. Vito 1, 00168, Rome, Italy.
Luca IndovinaMedical Physics Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Bruce S SpottiswoodeSiemens Medical Solutions USA, Inc., Knoxville, TN, USA.
Alessandro GiordanoNuclear Medicine Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo F. Vito 1, 00168, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTumor response evaluated by 2-deoxy-2-[ PROCEDURES: We retrospectively identified 95 PET pairs (pre- and post-treatment) performed on different scanners (Biograph mCT, Siemens; GEMINI GXL, Philips) in 73 oncological patients (52F; 57.8 ± 16.3 years). An 8-mm Gaussian filter was applied for the Biograph protocol to meet the EANM/EARL harmonization standard; no filter was needed for GXL. SUVmax and SUVmaxEQ of the same target lesion in the pre- and post-treatment PET/CT were noted. For each PET pair, the metabolic response classification (responder/non-responder), derived from combining the EORTC response categories, was evaluated twice (with and without harmonization). In discordant cases, the association of each metabolic response classification with final clinical response assessment and survival data (2-year disease-free survival, DFS) was assessed.

resultsOn Biograph, SUVmaxEQ of all target lesions was significantly lower (p = 0.001) than SUVmax (8.5 ± 6.8 vs 12.5 ± 9.6; - 38.6 %). A discordance between the two metabolic response classifications (harmonized and non-harmonized) was found in 19/95 (20 %) PET pairs. In this subgroup (n = 19; mean follow-up, 33.9 ± 9 months), responders according to harmonized classification (n = 9) had longer DFS (47.5 months, 88.9 %) than responders (n = 10) according to non-harmonized classification (26.3 months, 50.0 %; p = 0.01). Moreover, harmonized classification showed a better association with final clinical response assessment (17/19 PET pairs).

conclusionsThe harmonized metabolic response classification is more associated with the final clinical response assessment, and it is able to better predict the DFS than the non-harmonized classification. EQ·PET is a useful harmonization tool for evaluating metabolic tumor response using different PET/CT scanners, also in different departments or for multicenter studies.

Indexed as

Medical OncologyAgedAutomationDisease-Free SurvivalFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedPositron Emission Tomography Computed TomographyTreatment OutcomeFluorodeoxyglucose F18[18F]FDGEORTCEQ·PETHarmonizationPETTherapy response

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Textmetadata
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Registered trials

None linked

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.