J Neurol Surg B Skull Base 2017; 78(06): 497-505
DOI: 10.1055/s-0037-1604347
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Age and Tumor Volume Predict Growth of Carotid and Vagal Body Paragangliomas

Berdine L. Heesterman
1   Department of Otorhinolaryngology, Leiden University Medical Center, Leiden, The Netherlands
,
Lisa M. H. de Pont
1   Department of Otorhinolaryngology, Leiden University Medical Center, Leiden, The Netherlands
,
Berit M. Verbist
2   Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
,
Andel G. L. van der Mey
1   Department of Otorhinolaryngology, Leiden University Medical Center, Leiden, The Netherlands
,
Eleonora P. M. Corssmit
3   Department of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
,
Frederik J. Hes
4   Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
,
Peter Paul G. van Benthem
1   Department of Otorhinolaryngology, Leiden University Medical Center, Leiden, The Netherlands
,
Jeroen C. Jansen
1   Department of Otorhinolaryngology, Leiden University Medical Center, Leiden, The Netherlands
› Author Affiliations
Further Information

Publication History

11 March 2017

08 June 2017

Publication Date:
31 July 2017 (online)

Abstract

Objective Treatment for head and neck paragangliomas (HNGPL) can be more harmful than the disease. After diagnosis, an initial period of surveillance is often indicated, and surgery or radiotherapy is reserved for progressive disease. With the aim to optimize this “wait and scan” strategy, we studied growth and possible predictors.

Design A retrospective cohort study was conducted.

Setting This study was conducted at a tertiary referral center for patients with HNGPL.

Methods Tumor volume was estimated for 184 SDHD-related carotid and vagal body paragangliomas using sequential magnetic resonance imaging. Cox regression was used to study predictors of tumor growth.

Results The estimated fraction of growing tumors ranged from 0.42 after 1 year of follow-up to 0.85 after 11 years. A median growth rate of 10.4 and 12.0% per year was observed for carotid and vagal body tumors, respectively. Tumor location, initial volume, and age (p < 0.05) were included in our prediction model. The probability of growth decreased with increasing age and volume, indicating a decelerating growth pattern.

Conclusions We created a prediction model (available online), enabling a more individualized “wait and scan” strategy. The favorable natural course of carotid and vagal body paragangliomas was confirmed; although with long follow-up growth will be observed in most cases.

Supplementary Material

 
  • References

  • 1 Baysal BE, Ferrell RE, Willett-Brozick JE. , et al. Mutations in SDHD, a mitochondrial complex II gene, in hereditary paraganglioma. Science 2000; 287 (5454): 848-851
  • 2 Neumann HPH, Erlic Z, Boedeker CC. , et al. Clinical predictors for germline mutations in head and neck paraganglioma patients: cost reduction strategy in genetic diagnostic process as fall-out. Cancer Res 2009; 69 (08) 3650-3656
  • 3 Badenhop RF, Jansen JC, Fagan PA. , et al. The prevalence of SDHB, SDHC, and SDHD mutations in patients with head and neck paraganglioma and association of mutations with clinical features. J Med Genet 2004; 41 (07) e99
  • 4 Benn DE, Robinson BG, Clifton-Bligh RJ. 15 years of paraganglioma: Clinical manifestations of paraganglioma syndromes types 1-5. Endocr Relat Cancer 2015; 22 (04) T91-T103
  • 5 van Hulsteijn LT, Dekkers OM, Hes FJ, Smit JW, Corssmit EP. Risk of malignant paraganglioma in SDHB-mutation and SDHD-mutation carriers: a systematic review and meta-analysis. J Med Genet 2012; 49 (12) 768-776
  • 6 Jansen JC, van den Berg R, Kuiper A, van der Mey AG, Zwinderman AH, Cornelisse CJ. Estimation of growth rate in patients with head and neck paragangliomas influences the treatment proposal. Cancer 2000; 88 (12) 2811-2816
  • 7 Langerman A, Athavale SM, Rangarajan SV, Sinard RJ, Netterville JL. Natural history of cervical paragangliomas: outcomes of observation of 43 patients. Arch Otolaryngol Head Neck Surg 2012; 138 (04) 341-345
  • 8 Carlson ML, Sweeney AD, Wanna GB, Netterville JL, Haynes DS. Natural history of glomus jugulare: a review of 16 tumors managed with primary observation. Otolaryngol Head Neck Surg 2015; 152 (01) 98-105
  • 9 Prasad SC, Mimoune HA, D'Orazio F. , et al. The role of wait-and-scan and the efficacy of radiotherapy in the treatment of temporal bone paragangliomas. Otol Neurotol 2014; 35 (05) 922-931
  • 10 Sniezek JC, Netterville JL, Sabri AN. Vagal paragangliomas. Otolaryngol Clin North Am 2001; 34 (05) 925-939 , vi
  • 11 Moore MG, Netterville JL, Mendenhall WM, Isaacson B, Nussenbaum B. Head and Neck Paragangliomas: An Update on Evaluation and Management. Otolaryngol Head Neck Surg 2016; 154 (04) 597-605
  • 12 Gilbo P, Morris CG, Amdur RJ. , et al. Radiotherapy for benign head and neck paragangliomas: a 45-year experience. Cancer 2014; 120 (23) 3738-3743
  • 13 Heesterman BL, Bayley JP, Tops CM. , et al. High prevalence of occult paragangliomas in asymptomatic carriers of SDHD and SDHB gene mutations. Eur J Hum Genet 2013; 21 (04) 469-470
  • 14 Michałowska I, Ćwikła JB, Michalski W. , et al. Growth rate of paragangliomas related to germline mutations of the SDHX genes. Endocr Pract 2017; 23 (03) 342-352
  • 15 Heesterman BL, Verbist BM, van der Mey AGL. , et al. Measurement of head and neck paragangliomas: is volumetric analysis worth the effort? A method comparison study. Clin Otolaryngol 2016; 41 (05) 571-578
  • 16 van den Berg R. Imaging and management of head and neck paragangliomas. Eur Radiol 2005; 15 (07) 1310-1318
  • 17 R Development Core Team. A Language and Environment for Statistical Computing. Vienna, Austria: the R Foundation for Statistical Computing; 2016
  • 18 Therneau TM. A Package for Survival Analysis in S (2015). Available at: http://cran.irsn.fr/web/packages/survival/survival.pdf . Accessed July 20, 2017
  • 19 Wang JT-Y, Wang AY-Y, Cheng S, Gomes L, Da Cruz M. Growth rate analysis of an untreated glomus vagale on MRI. Case Rep Otolaryngol 2016; 2016: 8756940
  • 20 Mogensen UB, Ishwaran H, Gerds TA. Evaluating random forests for survival analysis using prediction error curves. J Stat Softw 2012; 50 (11) 1-23
  • 21 Heagerty PJ, Saha-Chaudhuri P. Time-dependent ROC curve estimation from censored survival data (2013). Available at: https://cran.r-project.org/web/packages/survivalROC/survivalROC.pdf . Accessed July 20, 2017
  • 22 Allison PD. Survival Analysis: The Reviewer's Guide to Quantitative Methods in the Social Sciences. New York, NY: Routledge; 2010: 413-424
  • 23 Stensjøen AL, Solheim O, Kvistad KA, Håberg AK, Salvesen Ø, Berntsen EM. Growth dynamics of untreated glioblastomas in vivo. Neuro-oncol 2015; 17 (10) 1402-1411
  • 24 Talkington A, Durrett R. Estimating tumor growth rates in vivo. Bull Math Biol 2015; 77 (10) 1934-1954
  • 25 Collins VP, Loeffler RK, Tivey H. Observations on growth rates of human tumors. Am J Roentgenol Radium Ther Nucl Med 1956; 76 (05) 988-1000
  • 26 van der Bogt KEA, Vrancken Peeters M-PFM, van Baalen JM, Hamming JF. Resection of carotid body tumors: results of an evolving surgical technique. Ann Surg 2008; 247 (05) 877-884
  • 27 Suárez C, Rodrigo JP, Mendenhall WM. , et al. Carotid body paragangliomas: a systematic study on management with surgery and radiotherapy. Eur Arch Otorhinolaryngol 2014; 271 (01) 23-34
  • 28 Suárez C, Rodrigo JP, Bödeker CC. , et al. Jugular and vagal paragangliomas: Systematic study of management with surgery and radiotherapy. Head Neck 2013; 35 (08) 1195-1204
  • 29 Burnichon N, Rohmer V, Amar L. , et al; PGL.NET network. The succinate dehydrogenase genetic testing in a large prospective series of patients with paragangliomas. J Clin Endocrinol Metab 2009; 94 (08) 2817-2827