Clinical Utility of Pre-Therapeutic [18F]FDG PET/CT Imaging for Predicting Outcomes in Breast Cancer.

PET/CT imaging breast cancer neoadjuvant chemotherapy pathological complete response total metabolic tumor volume

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
24 Aug 2023
Historique:
received: 26 06 2023
revised: 17 08 2023
accepted: 22 08 2023
medline: 9 9 2023
pubmed: 9 9 2023
entrez: 9 9 2023
Statut: epublish

Résumé

[18F]FDG PET/CT is used for staging and could also provide information associated with clinical outcomes. The objective of this study was to determine the clinical utility of biomarkers measured using [18F]FDG PET/CT to predict the absence of pathological complete response (no-pCR) and recurrence. In this retrospective study, we included patients with non-special-type breast carcinoma who underwent [18F]FDG PET/CT before neoadjuvant chemotherapy between 2011 and 2019. Clinicopathological data were collected. Tumor SUVmax and total metabolic tumor volume (TMTV) were measured from PET images. The association between biomarkers and no-pCR was studied using logistic regression. The cut-off value was determined using the area under the ROC Curve. To predict 3-year recurrence-free survival (RFS), we used a multivariable Cox model, and the cut-off value was determined using time-dependent ROC and predictiveness curves. Two hundred and eighty-six patients were included in the analysis. One hundred and twelve patients had a pCR (39.2%). The pCR rate was significantly higher in patients with a high nuclear grade ( High TMTV in pre-therapeutic imaging is associated with no-pCR and recurrence. It can help in identifying high-risk patients and be considered as an intensified or alternative adjuvant therapy for closely monitoring patients.

Sections du résumé

BACKGROUND BACKGROUND
[18F]FDG PET/CT is used for staging and could also provide information associated with clinical outcomes. The objective of this study was to determine the clinical utility of biomarkers measured using [18F]FDG PET/CT to predict the absence of pathological complete response (no-pCR) and recurrence.
METHODS METHODS
In this retrospective study, we included patients with non-special-type breast carcinoma who underwent [18F]FDG PET/CT before neoadjuvant chemotherapy between 2011 and 2019. Clinicopathological data were collected. Tumor SUVmax and total metabolic tumor volume (TMTV) were measured from PET images. The association between biomarkers and no-pCR was studied using logistic regression. The cut-off value was determined using the area under the ROC Curve. To predict 3-year recurrence-free survival (RFS), we used a multivariable Cox model, and the cut-off value was determined using time-dependent ROC and predictiveness curves.
RESULTS RESULTS
Two hundred and eighty-six patients were included in the analysis. One hundred and twelve patients had a pCR (39.2%). The pCR rate was significantly higher in patients with a high nuclear grade (
CONCLUSION CONCLUSIONS
High TMTV in pre-therapeutic imaging is associated with no-pCR and recurrence. It can help in identifying high-risk patients and be considered as an intensified or alternative adjuvant therapy for closely monitoring patients.

Identifiants

pubmed: 37685551
pii: jcm12175487
doi: 10.3390/jcm12175487
pmc: PMC10488013
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

World J Nucl Med. 2018 Oct-Dec;17(4):275-280
pubmed: 30505226
Eur J Nucl Med Mol Imaging. 2016 May;43(5):983-993
pubmed: 26758726
Mod Pathol. 2015 Sep;28(9):1185-201
pubmed: 26205180
Eur J Cancer (1965). 1980 Mar;16(3):351-6
pubmed: 7371690
Eur J Nucl Med Mol Imaging. 2011 Mar;38(3):426-35
pubmed: 21057787
Ann Oncol. 2011 Aug;22(8):1736-47
pubmed: 21709140
Breast Cancer Res Treat. 2018 Aug;170(3):559-567
pubmed: 29693228
J Clin Oncol. 2007 Oct 1;25(28):4414-22
pubmed: 17785706
J Nucl Med. 2007 Jun;48(6):932-45
pubmed: 17504879
Lancet Oncol. 2014 Dec;15(13):1415-1416
pubmed: 25456356
Virchows Arch. 2018 May;472(5):697-703
pubmed: 29380126
J Natl Compr Canc Netw. 2020 Sep;18(9):1240-1246
pubmed: 32886897
N Engl J Med. 2022 Feb 10;386(6):556-567
pubmed: 35139274
CA Cancer J Clin. 2021 May;71(3):209-249
pubmed: 33538338
Biom J. 2011 Mar;53(2):217-36
pubmed: 21308725
Lancet Oncol. 2018 Jan;19(1):27-39
pubmed: 29242041
Eur J Nucl Med Mol Imaging. 2017 Jul;44(7):1145-1154
pubmed: 28188325
J Cheminform. 2015 Nov 04;7:52
pubmed: 26539250
Eur J Radiol. 2018 Aug;105:1-7
pubmed: 30017264
J Clin Oncol. 2009 Mar 10;27(8):1160-7
pubmed: 19204204
Rev Esp Med Nucl Imagen Mol. 2016 Nov - Dec;35(6):365-372
pubmed: 26948652
Eur J Nucl Med Mol Imaging. 2020 May;47(5):1116-1126
pubmed: 31982990
Cancers (Basel). 2022 Nov 29;14(23):
pubmed: 36497351
J Natl Compr Canc Netw. 2020 Nov 02;18(11):1510-1517
pubmed: 33152704
Lancet. 2014 Jul 12;384(9938):164-72
pubmed: 24529560
PLoS One. 2017 Sep 8;12(9):e0184508
pubmed: 28886153
Ann Surg Oncol. 2019 Jul;26(7):2175-2183
pubmed: 30941655
Ann Oncol. 2019 Aug 1;30(8):1194-1220
pubmed: 31161190
Eur J Nucl Med Mol Imaging. 2021 Oct;48(11):3560-3570
pubmed: 33774685
Eur J Nucl Med Mol Imaging. 2015 Feb;42(2):328-54
pubmed: 25452219

Auteurs

Sophia Najid (S)

Institut Curie, Inserm U900, 92210 Saint-Cloud, France.

Romain-David Seban (RD)

Department of Nuclear Medicine, Institut Curie, 92210 Saint-Cloud, France.

Laurence Champion (L)

Department of Nuclear Medicine, Institut Curie, 92210 Saint-Cloud, France.

Alexandre De Moura (A)

Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France.
UVSQ, Paris Saclay University, 92210 Saint-Cloud, France.

Clara Sebbag (C)

Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France.
UVSQ, Paris Saclay University, 92210 Saint-Cloud, France.

Hélène Salaün (H)

Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France.
UVSQ, Paris Saclay University, 92210 Saint-Cloud, France.

Luc Cabel (L)

Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France.
UVSQ, Paris Saclay University, 92210 Saint-Cloud, France.

Claire Bonneau (C)

Department of Surgery, Institut Curie, 92210 Saint-Cloud, France.

Classifications MeSH