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Exploring Statistical Models for Endometrial Cancer Survival Data
Abstract
The main objective of this paper is to explore a suitable statistical model for endometrial cancer survival data.
Several parametric life time distributions have been considered for this analysis. Also, non-parametric Kaplan-
Meier used to validate our chosen model. Further, log rank test has been used to compare the survival
experience between age groups (< 60 and ≥ 60 years) and different grades of endometrial cancer patients. The
log-logistic survival distribution is chosen as most suitable model based on its lowest AIC and BIC values.
There is no significant difference of survival experience between age groups (< 60 and ≥ 60 years) and different
grades of the tumor. The overall five-year survival of the endometrial cancer patients is found to be 45.6% with
95% confidence interval (25.8%, 80.6%). This knowledge would be quite helpful in predicting survival of
endometrial cancer patients.
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References
1. A.M. Fedorko; T.H. Kim; R. Broaddus; R. Schmandt; G.V. Chandramouli; H. Kim; J.W. Jeong and J.I.
Risinger; An Immune Competent Orthotopic Model of Endometrial Cancer with Metastasis. Heliyon, 6(5),
p. e04075 (2020).
2. A.S. Malik and S.P. Ahmad; An Extension of Log-Logistic Distribution for Analyzing Survival Data.
Pakistan Journal of Statistics and Operation Research, 16(4), 789-801 (2020).
3. D. Collett; Modelling Survival Data for Medical Research. 2nd Edition, London, UK, CRC Press (2003).
4. E.L. Kaplan and P. Meier; Nonparametric Estimation from Incomplete Observations. Journal of the
American Statistical Association, 53(282), 457-481 (1958).
5. E.T. Lee and J. Wang; Statistical Methods for Survival Data Analysis, 3rd Edition, John Wiley & Sons
(2003).
6. G. Balasubramaniam; S. Sushama; B. Rasika and U. Mahantshetty; Hospital-based Study of Endometrial
Cancer Survival in Mumbai, India. Asian Pacific Journal of Cancer Prevention, 14(2), 977-980 (2013).
7. G. Schwarz; Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464 (1978).
8. Globocan Report; International Agency for Research on Cancer, WHO (2020). Retrieved from
https://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf.
9. H. Akaike; A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control,
19(6),716-723 (1974).
10. I. Saha; P. Singh; S.K. Medda and R.N. Das; Associations between Body Mass Index and Breast Cancer
Markers. Journal of Oncology Research, 2(1), 1-7 (2020).
11. J. Dey; S. Roy; S. Basak and S. Pundir; Some Applications of the Intervened Exponential Distribution in
Survival Analysis. International Journal of Statistics and Reliability Engineering, 9(3), 353-363 (2022).
12. J.E. Frandsen; W.T. Sause; M.K. Dodson; A.P. Soisson; T.W. Belnap and D.K. Gaffney; Survival Analysis
of Endometrial Cancer Patients with Cervical Stromal Involvement. Journal of Gynecologic Oncology,
25(2), 105-110 (2014).
13. J. Ferlay; I. Soerjomataram; R. Dikshit; S. Eser; C. Mathers; M. Rebelo; D.M. Parkin; D. Forman and F.
Bray; Cancer Incidence and Mortality Worldwide: Sources, Methods and Major Patterns in GLOBOCAN
2012. International Journal of Cancer, 136(5), E359-E386 (2015).
14. J.L. Hecht and G.L. Mutter; Molecular and Pathologic Aspects of Endometrial Carcinogenesis. Journal of
Clinical Oncology, 24(29), 4783-4791 (2006).
15. J. Wang; N. Jia; Q. Li; C. Wang; X. Tao; K. Hua and W. Feng; Analysis of Recurrence and Survival Rates
in Grade 3 Endometrioid Endometrial Carcinoma. Oncology Letters, 12(4), 2860-2867 (2016).
16. K. Bertelsen; G. Ortoft and E.S. Hansen; Survival of Danish Patients with Endometrial Cancer in the
Intermediate-risk Group not Given Postoperative Radiotherapy: The Danish Endometrial Cancer Study
(DEMCA). International Journal of Gynecologic Cancer, 21(7), 1191-1199 (2011).
17. M. Ahajeeth; M. Mohiuddin and R. Kannan; The Area Biased Amarendra Distribution with Its Application
to Model Lifetime Data. International Journal of Statistics and Reliability Engineering, 8(3), 428-438,
(2021).
18. M.G. Kelly; D. O'Malley; P. Hui; J. McAlpine; J. Dziura; T.J. Rutherford; M. Azodi; S.K. Chambers and
P.E. Schwartz; Patients with Uterine Papillary Serous Cancers may benefit from Adjuvant Platinum-based
Chemoradiation. Gynecologic Oncology, 95(3), 469-473 (2004).
19. M. Kumar; S.K. Maurya; S.K. Singh; U. Singh and A. Pathak; Model Suitability Analysis of Survival
Time to Ovarian Cancer Patients Data. Journal of Statistics Applications and Probability, 9(3), 609-620
(2019).
20. M. Kyrgiou; I. Kalliala; G. Markozannes; M.J. Gunter; E. Paraskevaidis; H. Gabra; P. Martin-Hirsch and
K.K. Tsilidis; Adiposity and Cancer at Major Anatomical Sites: Umbrella Review of the Literature. BMJ,
356, 1-10 (2017).
21. P.B. Clement and R.H. Young; Non-endometrioid Carcinomas of the Uterine Corpus: A Review of their
Pathology with Emphasis on Recent Advances and Problematic Aspects. Advances in Anatomic
Pathology, 11(3), 117-142 (2004).
22. P. Morice; A. Leary; C. Creutzberg; N. Abu-Rustum and E. Darai; Endometrial Cancer. The Lancet,
387(10023),1094-1108 (2016).
23. P.K. Swain; M.R. Tripathy, P.K. Sarangi and S.S. Pattnaik; Modelling of Lymph Node Count in
Endometrial Cancer Patients using Zero Inflated Generalized Poisson Model. International Journal of
Statistics and Reliability Engineering, 9(2), 246-254 (2022).
24. R.A. Ganaie; V. Rajagopalan; V.P. Soumya and R. Shenbagaraja; Characterizations and Some
Contribution to New Quasi Sujatha Distribution with Applications in Blood Cancer, Covid 19 and Survival
Times. International Journal of Statistics and Reliability Engineering, 10(2), 446-455 (2023).
25. R.L. Siegel; K.D. Miller and A. Jemal; Cancer statistics. CA: A Cancer Journal for Clinicians, 68(1), 7-30
(2018).
26. Report of National Cancer Registry Program (NCRP), India, ICMR and NCDIR (2020),
url:https://www.ncdirindia.org/All_Reports/Report_2020/resources/NCRP_2020_2012_16.pdf.
27. T. Chen; L. Jansen; A. Gondos; M. Ressing; B. Holleczek; A. Katalinic and H. Brenner; GEKID Cancer
Survival Working Group. Survival of Endometrial Cancer Patients in Germany in the Early 21st Century: A
Period Analysis by Age, Histology, and Stage. BMC Cancer, 12, 1-9 (2012).
28. T. Toptas; T. Simsek and S. Karaveli; Prognostic Risk Factors for Lymph Node Involvement in Patients
with Endometrial Cancer. Turkish Journal of Obstetrics and Gynecology, 14(1), 52-57 (2017).
29. T.V. Nyen; C.P. Moiola; E. Colas; D. Annibali and F. Amant; Modeling Endometrial Cancer: Past,
Present, and Future. International Journal of Molecular Sciences, 19(8), p. 2348 (2018).
30. U. Solmaz; A. Ekin; E. Mat; C. Gezer; A. Dogan; A. Biler; N. Peker; P.S. Hasdemir and M. Sanci;
Analysis of Clinical and Pathological Characteristics, Treatment Methods, Survival, and Prognosis of
Uterine Papillary Serous Carcinoma. Tumori Journal, 102(6), 593-599 (2016).
31. V. Rajagopalan; A.A. Rather and R.A. Ganaie; A New Generalized Power Akash Distribution with
Properties and Applications in Survival Times Data. International Journal of Statistics and Reliability
Engineering, 8(1), 16-28 (2021).

ISSN(P) 2350-0174

ISSN(O) 2456-2378

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