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Non-inferior efficacy of non-surgical treatment to surgical treatment in patients with nonmetastatic head and neck rhabdomyosarcoma: a SEER-based study

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Abstract

Purpose

Head and neck rhabdomyosarcoma (HNRMS) is a rare but aggressive malignant neoplasm. Given the young patient age and critical anatomy of the head and neck, performing surgery on the primary tumor still remains debatable. This study aimed to evaluate the impact of the non-surgery-based treatment versus surgery-based treatment on patients with nonmetastatic HNRMS.

Methods

Patients diagnosed with nonmetastatic HNRMS between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in our study. Inverse probability treatment weighting (IPTW) method was employed to balance confounding factors between surgery and non-surgery groups. Kaplan–Meier methods and COX regression analyses were used to analyze survival outcomes of overall survival (OS) and cancer-specific survival (CSS). Prognostic nomogram was established to predict survival.

Results

A total of 260 eligible patients were extracted from the SEER database. Kaplan–Meier survival curves revealed that there was no significant difference in OS and CSS between the surgery and non-surgery groups both before and after IPTW (p > 0.05). Cox regression analyses and IPTW-adjusted Cox regression analyses for both OS and CSS showed similar survival between the two groups. Prognostic factors were explored and a nomogram for patients in the surgery group was constructed. Risk stratification based on the nomogram indicated that patients in surgery-high-risk group did not benefit from primary surgery. While those in surgery-low-risk group had an equal survival outcome to those in non-surgery group.

Conclusions

Our study revealed that compared to patients receiving surgery, those not receiving surgery had similar survival outcomes for nonmetastatic HNRMS. Our established nomogram may serve as a practical tool for individual prognostic evaluations.

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Data availability statement

The data and materials that supported the findings of this study are available from the corresponding author upon reasonable request. Original data are available at Surveillance Epidemiology and End Results (SEER) database (https://seer.cancer.gov/data/).

References

  1. Rhabdomyosarcoma. Nat Rev Dis Primers. 2019, 5(1):2.

  2. Collignon C, Carton M, Brisse HJ, Pannier S, Gauthier A, Sarnacki S, et al. Soft tissue sarcoma in children, adolescents and young adults: outcomes according to compliance with international initial care guidelines. Eur J Surg Oncol. 2020;46(7):1277–86.

    Article  CAS  PubMed  Google Scholar 

  3. Agaram NP. Evolving classification of rhabdomyosarcoma. Histopathology. 2022;80(1):98–108.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Glosli H, Bisogno G, Kelsey A, Chisholm JC, Gaze M, Kolb F, et al. Non-parameningeal head and neck rhabdomyosarcoma in children, adolescents, and young adults: experience of the European paediatric soft tissue sarcoma study group (EpSSG) - RMS2005 study. Eur J Cancer. 2021;151:84–93.

    Article  PubMed  Google Scholar 

  5. Casey DL, Wexler LH, Wolden SL. Worse outcomes for head and neck rhabdomyosarcoma secondary to reduced-dose cyclophosphamide. Int J Radiat Oncol Biol Phys. 2019;103(5):1151–7.

    Article  PubMed  Google Scholar 

  6. Merks JH, De Salvo GL, Bergeron C, Bisogno G, De Paoli A, Ferrari A, et al. Parameningeal rhabdomyosarcoma in pediatric age: results of a pooled analysis from North American and European cooperative groups. Ann Oncol. 2014;25(1):231–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Radzikowska J, Kukwa W, Kukwa A, Czarnecka AM, Kawecki M, Lian F, et al. Management of pediatric head and neck rhabdomyosarcoma: a case-series of 36 patients. Oncol Lett. 2016;12(5):3555–62.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Chen C, Dorado Garcia H, Scheer M, Henssen AG. Current and future treatment strategies for rhabdomyosarcoma. Front Oncol. 2019;9:1458.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Stevens MC, Rey A, Bouvet N, Ellershaw C, Flamant F, Habrand JL, et al. Treatment of nonmetastatic rhabdomyosarcoma in childhood and adolescence: third study of the international society of paediatric oncology–SIOP malignant mesenchymal tumor 89. J Clin Oncol. 2005;23(12):2618–28.

    Article  PubMed  Google Scholar 

  10. Oberlin O, Rey A, de Sanchez TJ, Martelli H, Jenney ME, Scopinaro M, et al. Randomized comparison of intensified six-drug versus standard three-drug chemotherapy for high-risk nonmetastatic rhabdomyosarcoma and other chemotherapy-sensitive childhood soft tissue sarcomas: long-term results from the international society of pediatric oncology MMT95 study. J Clin Oncol. 2012;30(20):2457–65.

    Article  CAS  PubMed  Google Scholar 

  11. Yunteng W, Xuhui M, Guoxin R, Wei G. Radical surgery for head and neck rhabdomyosarcoma failed primary chemotherapy. J Craniofac Surg. 2019;30(2):e113–6.

    Article  PubMed  Google Scholar 

  12. Vaarwerk B, Schoot RA, Maurice-Stam H, Slater O, Hartley B, Saeed P, et al. Psychosocial well-being of long-term survivors of pediatric head-neck rhabdomyosarcoma. Pediatr Blood Cancer. 2019;66(2): e27498.

    Article  PubMed  Google Scholar 

  13. Wiener ES. Head and neck rhabdomyosarcoma. Semin Pediatr Surg. 1994;3(3):203–6.

    CAS  PubMed  Google Scholar 

  14. Machavoine R, Helfre S, Bernier V, Bolle S, Leseur J, Corradini N, et al. Locoregional control and survival in children, adolescents, and young adults with localized head and neck alveolar rhabdomyosarcoma-the French experience. Front Pediatr. 2021;9: 783754.

    Article  PubMed  Google Scholar 

  15. Daya H, Chan HS, Sirkin W, Forte V. Pediatric rhabdomyosarcoma of the head and neck: is there a place for surgical management? Arch Otolaryngol Head Neck Surg. 2000;126(4):468–72.

    Article  CAS  PubMed  Google Scholar 

  16. Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res. 2004;10(21):7252–9.

    Article  CAS  PubMed  Google Scholar 

  17. Firth D. Bias reduction of maximum likelihood estimates. Biometrika. 1993;80:27–38.

    Article  Google Scholar 

  18. Steyerberg EW. Frank E. Harrell, Jr., Regression Modeling Strategies: With Applications, to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, 2nd ed. Heidelberg: Springer. Biometrics. (2016). 72(3):1006–1007.

  19. Rao BN, Santana VM, Fleming ID, Pratt CB, Shapiro D, Fontanesi J, et al. Management and prognosis of head and neck sarcomas. Am J Surg. 1989;158(4):373–7.

    Article  CAS  PubMed  Google Scholar 

  20. Dombrowski ND, Wolter NE, Robson CD, Kawai K, Irace AL, Vargas SO, et al. Role of surgery in rhabdomyosarcoma of the head and neck in children. Laryngoscope. 2021;131(3):E984-e992.

    Article  PubMed  Google Scholar 

  21. Lee RJ, Lee KK, Lin T, Arshi A, Lee SA, Christensen RE. Rhabdomyosarcoma of the head and neck: impact of demographic and clinicopathologic factors on survival. Oral Surg Oral Med Oral Pathol Oral Radiol. 2017;124(3):271–9.

    Article  PubMed  Google Scholar 

  22. Wurm J, Constantinidis J, Grabenbauer GG, Iro H. Rhabdomyosarcomas of the nose and paranasal sinuses: treatment results in 15 cases. Otolaryngol Head Neck Surg. 2005;133(1):42–50.

    Article  PubMed  Google Scholar 

  23. Ben-Arush M, Minard-Colin V, Scarzello G, Fajardo RD, Van Terwisscha SS, Bernier V, et al. Therapy and prognostic significance of regional lymph node involvement in embryonal rhabdomyosarcoma: a report from the European paediatric soft tissue sarcoma study group. Eur J Cancer. 2022;172:119–29.

    Article  CAS  PubMed  Google Scholar 

  24. Newton WA Jr, Gehan EA, Webber BL, Marsden HB, van Unnik AJ, Hamoudi AB, et al. Classification of rhabdomyosarcomas and related sarcomas. Pathologic aspects and proposal for a new classification–an intergroup rhabdomyosarcoma study. Cancer. 1995;76(6):1073–85.

    Article  PubMed  Google Scholar 

  25. Panda SP, Chinnaswamy G, Vora T, Prasad M, Bansal D, Kapoor G, et al. Diagnosis and management of rhabdomyosarcoma in children and adolescents: ICMR consensus document. Indian J Pediatr. 2017;84(5):393–402.

    Article  PubMed  Google Scholar 

  26. Chesnaye NC, Stel VS, Tripepi G, Dekker FW, Fu EL, Zoccali C, et al. An introduction to inverse probability of treatment weighting in observational research. Clin Kidney J. 2022;15(1):14–20.

    Article  PubMed  Google Scholar 

  27. Austin PC. The performance of different propensity score methods for estimating marginal hazard ratios. Stat Med. 2013;32(16):2837–49.

    Article  PubMed  Google Scholar 

  28. Liu YT, Wang CW, Hong RL, Kuo SH. Prognostic factors and treatment outcomes of adult patients with rhabdomyosarcoma after multimodality treatment. Anticancer Res. 2019;39(3):1355–64.

    Article  CAS  PubMed  Google Scholar 

  29. Ferrari A, Chisholm JC, Jenney M, Minard-Colin V, Orbach D, Casanova M, et al. Adolescents and young adults with rhabdomyosarcoma treated in the European paediatric soft tissue sarcoma study group (EpSSG) protocols: a cohort study. Lancet Child Adolesc Health. 2022;6(8):545–54.

    Article  PubMed  Google Scholar 

  30. Gradoni P, Giordano D, Oretti G, Fantoni M, Ferri T. The role of surgery in children with head and neck rhabdomyosarcoma and Ewing’s sarcoma. Surg Oncol. 2010;19(4):e103-109.

    Article  CAS  PubMed  Google Scholar 

  31. Wolden SL, Wexler LH, Kraus DH, Laquaglia MP, Lis E, Meyers PA. Intensity-modulated radiotherapy for head-and-neck rhabdomyosarcoma. Int J Radiat Oncol Biol Phys. 2005;61(5):1432–8.

    Article  PubMed  Google Scholar 

  32. Loya AC, Prayaga AK, Arora A, Sundaram C, Rao IS, Uppin SG, et al. Lymph node metastasis of soft tissue tumors: a cytomorphologic study. Acta Cytol. 2007;51(2):153–60.

    Article  PubMed  Google Scholar 

  33. Behranwala KA, A’Hern R, Omar AM, Thomas JM. Prognosis of lymph node metastasis in soft tissue sarcoma. Ann Surg Oncol. 2004;11(7):714–9.

    Article  PubMed  Google Scholar 

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Acknowledgements

We would like to thank the staff of the SEER database for their kind work in data collection and delivery.

Funding

This work was supported by a Grant from the Oncology Science and Technology Innovation Cultivation Program of Zhongnan Hospital of Wuhan University (No. 2020-B-06).

Author information

Author notes

  1. Wenjing Liang and Langman Li have contributed equally to this work as co-first authors.

Authors and Affiliations

  1. Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumour Biological Behaviors, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China

    Wenjing Liang, Miao Wang, Yixin Liu, Ye Qiu, Boyu Zhang, Qiuji Wu & Yongchang Wei

  2. Department of Medical Record Management, Beijing South Medical District, Chinese PLA General Hospital, Beijing, China

    Langman Li

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Contributions

YW, QW, WL, and LL were responsible for study conception and design; WL, YQ, and BZ were responsible for acquisition of data; WL, LL, MW, and YL were responsible for data analysis; WL was responsible for drafting of the manuscript; YW, QW, WL, and LL were responsible for revision of the manuscript.

Corresponding authors

Correspondence to Qiuji Wu or Yongchang Wei.

Ethics declarations

Conflict of interest

All authors have declared that they have no conflicts of interest with regard to this work.

Ethical approval

All personal identifying information for patients was anonymized by Surveillance, Epidemiology, and End Results, so ethical approval and informed consent were waived.

Informed consent

Informed consent was waived due to approved use of publically accessible database and retrospective nature of the study.

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Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 19 KB)

Supplementary file2 (DOCX 11 KB)

12094_2023_3076_MOESM3_ESM.eps

Supplementary Fig. 1 The flowchart demonstrating the inclusion and exclusion criteria of the study population using the SEER 18 population-based cancer registry. Supplementary file3 (EPS 993 KB)

12094_2023_3076_MOESM4_ESM.eps

Supplementary Fig. 2 X-tile analysis for the optimal cutoff values. (A) Optimal cut-off values of age at diagnosis were identified as <12, 12-31, and >31 years old based on OS. (B) Kaplan-Meier survival curve developed based on cutoff values of age at diagnosis. (C) Optimal cut-off values of tumor size were identified as < 4, 4-6, >6 cm based on OS. (D) Kaplan-Meier survival curve developed based on cutoff values of tumor size. Supplementary file4 (EPS 1552 KB)

12094_2023_3076_MOESM5_ESM.eps

Supplementary Fig. 3 X-tile analysis and Kaplan-Meier curves for overall survival. (A) Histogram of the surgery cohort, optimal cut-off value of total score was identified as 210.7 based on OS. (B) Kaplan-Meier survival curve developed based on the cutoff values. Supplementary file5 (EPS 891 KB)

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Liang, W., Li, L., Wang, M. et al. Non-inferior efficacy of non-surgical treatment to surgical treatment in patients with nonmetastatic head and neck rhabdomyosarcoma: a SEER-based study. Clin Transl Oncol 25, 1779–1792 (2023). https://doi.org/10.1007/s12094-023-03076-x

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