Total Lesion Glycolysis in Oral Squamous Cell Carcinoma As a Biomarker Derived from Pre-operative FDG PET/CT Outperforms Established Prognostic Factors in a Newly Developed Multivariate Prediction Model

Overview

Journal Oncotarget

Specialty Oncology

Date 2021 Jan 18

PMID 33456712

Citations 4

Authors

Gerrit Spanier

Daniela Weidt

Dirk Hellwig

Johannes K H Meier

Torsten E Reichert

Jirka Grosse

Affiliations

Soon will be listed here.

Abstract

Purpose: Retrospective study to investigate the impact of image derived biomarkers from [F]FDG PET/CT prior to surgical resection in patients with initial diagnosis of oral squamous cell carcinoma (OSCC), namely SUV, SUV, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary tumor to predict overall survival (OS).

Materials And Methods: 127 subsequent patients with biopsy-proven OSCC were included who underwent [F]FDG PET/CT before surgery. SUV, SUV, MTV and TLG of the primary tumor were measured. OS was estimated according to Kaplan-Meier and compared between median-splitted groups by the log-rank test. Prognostic parameters were analyzed by uni-/multivariate Cox-regression.

Results: During follow-up 52 (41%) of the patients died. Median OS was longer for patients with lower MTV or lower TLG. SUV and SUV failed to be significant predictors for OS. Univariate Cox-regression identified MTV, TLG, lymph node status and UICC stage as prognostic factors. By multivariate Cox-regression MTV and TLG turned out to be independent prognostic factors for OS.

Conclusions: The pre-therapeutic [F]FDG PET/CT parameters MTV and TLG in the primary tumor are prognostic for OS of patients with an initial diagnosis of OSCC. TLG is the strongest independent prognostic factor for OS and outperforms established prognostic parameters in OSCC.

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References

Shum W, Ding H, Liang J, Yen K, Chen S, Kao C . Use of pretreatment metabolic tumor volumes on PET-CT to predict the survival of patients with squamous cell carcinoma of esophagus treated by curative surgery. Anticancer Res. 2012; 32(9):4163-8. View

Zhang H, Seikaly H, Nguyen N, Abele J, Dziegielewski P, Harris J . Validation of metabolic tumor volume as a prognostic factor for oral cavity squamous cell carcinoma treated with primary surgery. Oral Oncol. 2016; 57:6-14. DOI: 10.1016/j.oraloncology.2016.03.013. View

Higgins K, Hoang J, Roach M, Chino J, Yoo D, Turkington T . Analysis of pretreatment FDG-PET SUV parameters in head-and-neck cancer: tumor SUVmean has superior prognostic value. Int J Radiat Oncol Biol Phys. 2011; 82(2):548-53. DOI: 10.1016/j.ijrobp.2010.11.050. View

Ryu I, Kim J, Roh J, Cho K, Choi S, Nam S . Prognostic significance of preoperative metabolic tumour volume and total lesion glycolysis measured by (18)F-FDG PET/CT in squamous cell carcinoma of the oral cavity. Eur J Nucl Med Mol Imaging. 2013; 41(3):452-61. DOI: 10.1007/s00259-013-2571-z. View

Evangelista L, Cervino A, Chondrogiannis S, Marzola M, Maffione A, Colletti P . Comparison between anatomical cross-sectional imaging and 18F-FDG PET/CT in the staging, restaging, treatment response, and long-term surveillance of squamous cell head and neck cancer: a systematic literature overview. Nucl Med Commun. 2013; 35(2):123-34. DOI: 10.1097/MNM.0000000000000022. View

Chen S, Hsieh T, Yen K, Liang J, Kao C . Pretreatment (18)F-FDG PET/CT in whole-body total lesion glycolysis to predict survival in patients with pharyngeal cancer treated with definitive radiotherapy. Clin Nucl Med. 2013; 39(5):e296-300. DOI: 10.1097/RLU.0000000000000243. View

Fouad Y, Aanei C . Revisiting the hallmarks of cancer. Am J Cancer Res. 2017; 7(5):1016-1036. PMC: 5446472. View

Mettler J, Muller H, Voltin C, Baues C, Klaeser B, Moccia A . Metabolic Tumour Volume for Response Prediction in Advanced-Stage Hodgkin Lymphoma. J Nucl Med. 2018; . PMC: 8833856. DOI: 10.2967/jnumed.118.210047. View

Daisne J, Duprez T, Weynand B, Lonneux M, Hamoir M, Reychler H . Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. Radiology. 2004; 233(1):93-100. DOI: 10.1148/radiol.2331030660. View

10.

Ferris R, Blumenschein Jr G, Fayette J, Guigay J, Colevas A, Licitra L . Nivolumab for Recurrent Squamous-Cell Carcinoma of the Head and Neck. N Engl J Med. 2016; 375(19):1856-1867. PMC: 5564292. DOI: 10.1056/NEJMoa1602252. View

11.

Zhu L, Wang N . 18F-fluorodeoxyglucose positron emission tomography-computed tomography as a diagnostic tool in patients with cervical nodal metastases of unknown primary site: a meta-analysis. Surg Oncol. 2013; 22(3):190-4. DOI: 10.1016/j.suronc.2013.06.002. View

12.

Creff G, Devillers A, Depeursinge A, Palard-Novello X, Acosta O, Jegoux F . Evaluation of the Prognostic Value of FDG PET/CT Parameters for Patients With Surgically Treated Head and Neck Cancer: A Systematic Review. JAMA Otolaryngol Head Neck Surg. 2020; 146(5):471-479. DOI: 10.1001/jamaoto.2020.0014. View

13.

Pavlova N, Thompson C . The Emerging Hallmarks of Cancer Metabolism. Cell Metab. 2016; 23(1):27-47. PMC: 4715268. DOI: 10.1016/j.cmet.2015.12.006. View

14.

Lydiatt W, Patel S, OSullivan B, Brandwein M, Ridge J, Migliacci J . Head and Neck cancers-major changes in the American Joint Committee on cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017; 67(2):122-137. DOI: 10.3322/caac.21389. View

15.

Tang C, Murphy J, Khong B, La T, Kong C, Fischbein N . Validation that metabolic tumor volume predicts outcome in head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2012; 83(5):1514-20. PMC: 3337958. DOI: 10.1016/j.ijrobp.2011.10.023. View

16.

Warnakulasuriya S . Global epidemiology of oral and oropharyngeal cancer. Oral Oncol. 2008; 45(4-5):309-16. DOI: 10.1016/j.oraloncology.2008.06.002. View

17.

Porceddu S, Pryor D, Burmeister E, Burmeister B, Poulsen M, Foote M . Results of a prospective study of positron emission tomography-directed management of residual nodal abnormalities in node-positive head and neck cancer after definitive radiotherapy with or without systemic therapy. Head Neck. 2011; 33(12):1675-82. DOI: 10.1002/hed.21655. View

18.

Kao J, Vu H, Genden E, Mocherla B, Park E, Packer S . The diagnostic and prognostic utility of positron emission tomography/computed tomography-based follow-up after radiotherapy for head and neck cancer. Cancer. 2009; 115(19):4586-94. DOI: 10.1002/cncr.24493. View

19.

Adams M, Turkington T, Wilson J, Wong T . A systematic review of the factors affecting accuracy of SUV measurements. AJR Am J Roentgenol. 2010; 195(2):310-20. DOI: 10.2214/AJR.10.4923. View

20.

Ng S, Chan S, Liao C, Chang J, Ko S, Wang H . Distant metastases and synchronous second primary tumors in patients with newly diagnosed oropharyngeal and hypopharyngeal carcinomas: evaluation of (18)F-FDG PET and extended-field multi-detector row CT. Neuroradiology. 2008; 50(11):969-79. DOI: 10.1007/s00234-008-0426-2. View