Article Data

  • Views 380
  • Dowloads 150

Original Research

Open Access

Development of a novel web-based calculator for predicting overall survival in early-onset cervical cancer patients with positive lymph node metastasis

  • Zhe Wu1,†
  • Qiangting Deng2,†
  • Ya Pang3
  • Mujun Liu1
  • Yuxin Zou1
  • Shengxian Peng3
  • Zhou Xu1
  • Yi Wu1,*,

1Department of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), 400038 Chongqing, China

2Department of Health Statistics, School of Preventive Medicine, Army Medical University (Third Military Medical University), 400038 Chongqing, China

3First People’s Hospital of Zigong City, 643000 Zigong, Sichuan, China

DOI: 10.22514/ejgo.2025.018 Vol.46,Issue 2,February 2025 pp.20-29

Submitted: 21 June 2023 Accepted: 21 July 2023

Published: 15 February 2025

*Corresponding Author(s): Yi Wu E-mail: wuy1979@tmmu.edu.cn

† These authors contributed equally.

Abstract

Background: Cervical cancer (CC) is a malignant tumor affecting the female genital system and ranks as second most common cancer among younger women. This study aimed to identify key clinicopathological and lymph nodal characteristics associated with the overall survival (OS) of CC patients aged <45 years and develop an interactive web-based calculator to assess patient prognosis. Methods: The Surveillance, Epidemiology and End Results (SEER) database was searched for cases diagnosed with CC from 2004 to 2015, which were then randomly divided into a training (n = 3720, 70%) and a validation (n = 1661, 30%) set. Least absolute shrinkage and selection operator (LASSO) regression was used to identify relevant predictors and construct a nomogram incorporating the most significant variables. In addition, its performance was assessed using C-index values, area under curve (AUC) values, calibration plots and Kaplan-Meier curves, and an online prediction tool was constructed. Results: In the training cohort, the C-index for the proposed nomogram was 0.809 (95% Confidence Interval (CI): 0.802–0.816), and in the validation set, it was 0.811 (95% CI: 0.801–0.821). The AUC values for 1-, 3- and 5-year OS were 0.880, 0.856 and 0.842 in the training set and 0.911, 0.843 and 0.829 in the validation set, respectively. The calibration curves demonstrated the reliable predictive performance of the nomogram, with the nomogram demonstrating good calibration and discrimination abilities in the validation set. Conclusions: The developed nomogram and online tool for CC patients aged <45 years demonstrated promising utility in potentially assisting clinicians to predict patient prognosis and develop more informed treatment strategies for these patients.


Keywords

Nomogram; Early-onset patients; Cervical cancer; SEER database; Web-based calculator


Cite and Share

Zhe Wu,Qiangting Deng,Ya Pang,Mujun Liu,Yuxin Zou,Shengxian Peng,Zhou Xu,Yi Wu. Development of a novel web-based calculator for predicting overall survival in early-onset cervical cancer patients with positive lymph node metastasis. European Journal of Gynaecological Oncology. 2025. 46(2);20-29.

References

[1] Pankaj S, Nazneen S, Kumari S, Kumari A, Kumari A, Kumari J, et al. Comparison of conventional Pap smear and liquid-based cytology: a study of cervical cancer screening at a tertiary care center in Bihar. Indian Journal of Cancer. 2018; 55: 80.

[2] Arbyn M, Weiderpass E, Bruni L, de Sanjosé S, Saraiya M, Ferlay J, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. The Lancet Global Health. 2020; 8: e191–e203.

[3] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA: A Cancer Journal for Clinicians. 2020; 70: 7–30.

[4] Zahid A, Shakoori A R. Frequency of E6 and E7 oncogenes of human papillomavirus types 16 and 18 in cervical cancer patients in Pakistani women. Pakistan Journal of Zoology. 2016; 48: 1911–1917.

[5] Arbyn M, Walker A, Meijer CJ. HPV-based cervical-cancer screening in China. The Lancet Oncology. 2010; 11: 1112–1113.

[6] Chen C, Wang L, Lin J, Jan J. The prognostic factors for locally advanced cervical cancer patients treated by intensity-modulated radiation therapy with concurrent chemotherapy. Journal of the Formosan Medical Association. 2015; 114: 231–237.

[7] Winer I, Alvarado-Cabrero I, Hassan O, Ahmed QF, Alosh B, Bandyopadhyay S, et al. The prognostic significance of histologic type in early stage cervical cancer—a multi-institutional study. Gynecologic Oncology. 2015; 137: 474–478.

[8] Cui L, Shi Y, Zhang GN. Perineural invasion as a prognostic factor for cervical cancer: a systematic review and meta-analysis. Archives of Gynecology and Obstetrics. 2015; 292: 13–19.

[9] Jiang K, Ai Y, Li Y, Jia L. Nomogram models for the prognosis of cervical cancer: a SEER-based study. Frontiers in Oncology. 2022; 12: 961678.

[10] Chen B, Zeng Y, Liu B, Lu G, Xiang Z, Chen J, et al. Risk factors, prognostic factors, and nomograms for distant metastasis in patients with newly diagnosed osteosarcoma: a population-based study. Frontiers in Endocrinology. 2021; 12: 672024.

[11] Wu J, Lu L, Chen H, Lin Y, Zhang H, Chen E, et al. Prognostic nomogram to predict the overall survival of patients with early-onset colorectal cancer: a population-based analysis. International Journal of Colorectal Disease. 2021; 36: 1981–1993.

[12] Touijer K, Scardino PT. Nomograms for staging, prognosis, and predicting treatment outcomes. Cancer. 2009; 115: 3107–3111.

[13] Liu Q, Li W, Xie M, Yang M, Xu M, Yang L, et al. Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years. Bosnian Journal of Basic Medical Sciences. 2021; 21: 620–631.

[14] Gao B, Zhou D, Qian X, Jiang Y, Liu Z, Zhang W, et al. Number of positive lymph nodes is superior to LNR and LODDS for predicting the prognosis of pancreatic neuroendocrine neoplasms. Frontiers in Endocrinology. 2021; 12: 613755.

[15] Yan J, He Y, Wang M, Wu Y. Prognostic nomogram for overall survival of patients aged 50 years or older with cervical cancer. International Journal of General Medicine. 2021; 14: 7741–7754.

[16] Huai J, Ye X, Ding J. Nomogram for the prediction of delayed colorectal post-polypectomy bleeding. Turkish Journal of Gastroenterology. 2021; 32: 727–734.

[17] Schafer JL, Graham JW. Missing data: Our view of the state of the art. Psychological Methods. 2002; 7: 147–177.

[18] Zhang S, Wang X, Li Z, Wang W, Wang L. Score for the overall survival probability of patients with first-diagnosed distantly metastatic cervical cancer: a novel nomogram-based risk assessment system. Frontiers in Oncology. 2019; 9: 1106.

[19] Wright JD, Matsuo K, Huang Y, Tergas AI, Hou JY, Khoury-Collado F, et al. Prognostic performance of the 2018 international federation of gynecology and obstetrics cervical cancer staging guidelines. Obstetrics & Gynecology. 2019; 134: 49–57.

[20] Yang J, Tian G, Pan Z, Zhao F, Feng X, Liu Q, et al. Nomograms for predicting the survival rate for cervical cancer patients who undergo radiation therapy: a SEER analysis. Future Oncology. 2019; 15: 3033–3045.

[21] Joo JH, Kim YS, Nam J. Prognostic significance of lymph node ratio in node-positive cervical cancer patients. Medicine. 2018; 97: e11711.

[22] Olthof EP, Mom CH, Snijders MLH, Wenzel HHB, van der Velden J, van der Aa MA. The prognostic value of the number of positive lymph nodes and the lymph node ratio in early‐stage cervical cancer. Acta Obstetricia et Gynecologica Scandinavica. 2022; 101: 550–557.

[23] Zhou J, Zhang WW, Wu SG, He ZY, Sun JY, Wang Y, et al. The impact of examined lymph node count on survival in squamous cell carcinoma and adenocarcinoma of the uterine cervix. Cancer Management and Research. 2017; 9: 315–322.

[24] Wang C, Yang C, Wang W, Xia B, Li K, Sun F, et al. A prognostic nomogram for cervical cancer after surgery from SEER database. Journal of Cancer. 2018; 9: 3923–3928.

[25] Kwon J, Eom K, Kim IA, Kim J, Kim Y, No JH, et al. Prognostic value of log odds of positive lymph nodes after radical surgery followed by adjuvant treatment in high-risk cervical cancer. Cancer Research and Treatment. 2016; 48: 632–640.

[26] Guo Q, Zhu J, Wu Y, Wen H, Xia L, Yu M, et al. Comparison of different lymph node staging systems in patients with node-positive cervical squamous cell carcinoma following radical surgery. Journal of Cancer. 2020; 11: 7339–7347.

[27] Xie S, Pan S, Zou S, Zhu H, Zhu X. Characteristics and treatments of patients aged 65 years or over with cervical cancer. Clinical Interventions in Aging. 2020; 15: 841–851.

[28] Narin MA, Karalok A, Basaran D, Turkmen O, Turan T, Tulunay G. Embryonal rhabdomyosarcoma of the cervix in young women. Journal of Adolescent and Young Adult Oncology. 2016; 5: 261–266.

[29] Mancebo G, Miralpeix E, Solé-Sedeño J, Tió G, Rodrigo-Calvo T, Lloveras B, et al. Influence of age on treatment and prognosis of invasive cervical cancer. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2021; 262: 68–72.

[30] Barben J, Kamga AM, Dabakuyo-Yonli TS, Hacquin A, Putot A, Manckoundia P, et al. Cervical cancer in older women: does age matter? Maturitas. 2022; 158: 40–46.

[31] Pan S, Jiang W, Xie S, Zhu H, Zhu X. Clinicopathological features and survival of adolescent and young adults with cervical cancer. Cancer Control. 2021; 28: 107327482110515.

[32] Rogers L, Siu SS, Luesley D, Bryant A, Dickinson HO. Radiotherapy and chemoradiation after surgery for early cervical cancer. Cochrane Database of Systematic Reviews. 2012; 5: CD007583.

[33] Meng X, Jiang Y, Chang X, Zhang Y, Guo Y. Conditional survival analysis and real-time prognosis prediction for cervical cancer patients below the age of 65 years. Frontiers in Oncology. 2023; 12: 1049531.

[34] Li Z, Lin Y, Cheng B, Zhang Q, Cai Y. Prognostic model for predicting overall and cancer-specific survival among patients with cervical squamous cell carcinoma: a SEER based study. Frontiers in Oncology. 2021; 11: 651975.

[35] Yang N, Xu L, Wang Q, Chen F, Zhou Y. Construction and validation of a prognostic nomogram for anal squamous cell carcinoma. Cancer Medicine. 2022; 11: 392–405.

[36] Zhang R, Xu M, Liu X, Wang M, Jia Q, Wang S, et al. Establishment and validation of a nomogram model for predicting the survival probability of differentiated thyroid carcinoma patients: a comparison with the eighth edition AJCC cancer staging system. Endocrine. 2021; 74: 108–119.

[37] Zhou Z, Li W, Zhang F, Hu K. The value of squamous cell carcinoma antigen (SCCa) to determine the lymph nodal metastasis in cervical cancer: a meta-analysis and literature review. PLOS ONE. 2017; 12: e0186165.

[38] Ataseven B, Harter P, Grimm C, Heitz F, Heikaus S, Traut A, et al. The revised 2014 FIGO staging system for epithelial ovarian cancer: is a subclassification into FIGO stage IVA and IVB justified? Gynecologic Oncology. 2016; 142: 243–247.


Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,500 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Biological Abstracts Easily discover critical journal coverage of the life sciences with Biological Abstracts, produced by the Web of Science Group, with topics ranging from botany to microbiology to pharmacology. Including BIOSIS indexing and MeSH terms, specialized indexing in Biological Abstracts helps you to discover more accurate, context-sensitive results.

Google Scholar Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.

JournalSeek Genamics JournalSeek is the largest completely categorized database of freely available journal information available on the internet. The database presently contains 39226 titles. Journal information includes the description (aims and scope), journal abbreviation, journal homepage link, subject category and ISSN.

Current Contents - Clinical Medicine Current Contents - Clinical Medicine provides easy access to complete tables of contents, abstracts, bibliographic information and all other significant items in recently published issues from over 1,000 leading journals in clinical medicine.

BIOSIS Previews BIOSIS Previews is an English-language, bibliographic database service, with abstracts and citation indexing. It is part of Clarivate Analytics Web of Science suite. BIOSIS Previews indexes data from 1926 to the present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Submission Turnaround Time

Conferences

Top