Statistical modelling and forecasting of cervix cancer cases in radiation oncology treatment

A hospital based study from Western Nepal

Brijesh Sathian, Abul Fazil, Jayadevan Sreedharan, Sadip Pant, Anjali Kakria, Krishna Sharan, E. Rajesh, K. V. Vishrutha, Soumya B. Shetty, Shameema Shahnavaz, Jyothi H. Rao, Vijaya Marakala

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between 28th September 2000 and 31st December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curvefitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with R2=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focusand resource allocation on cervical cancer screening and treatment.

Original languageEnglish
Pages (from-to)2097-2100
Number of pages4
JournalAsian Pacific Journal of Cancer Prevention
Volume14
Issue number3
DOIs
Publication statusPublished - 01-01-2013
Externally publishedYes

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Nepal
Radiation Oncology
Uterine Cervical Neoplasms
Teaching Hospitals
Therapeutics
Resource Allocation
Early Detection of Cancer
Radiotherapy
Retrospective Studies
Growth

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Oncology
  • Public Health, Environmental and Occupational Health
  • Cancer Research

Cite this

Sathian, Brijesh ; Fazil, Abul ; Sreedharan, Jayadevan ; Pant, Sadip ; Kakria, Anjali ; Sharan, Krishna ; Rajesh, E. ; Vishrutha, K. V. ; Shetty, Soumya B. ; Shahnavaz, Shameema ; Rao, Jyothi H. ; Marakala, Vijaya. / Statistical modelling and forecasting of cervix cancer cases in radiation oncology treatment : A hospital based study from Western Nepal. In: Asian Pacific Journal of Cancer Prevention. 2013 ; Vol. 14, No. 3. pp. 2097-2100.
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Sathian, B, Fazil, A, Sreedharan, J, Pant, S, Kakria, A, Sharan, K, Rajesh, E, Vishrutha, KV, Shetty, SB, Shahnavaz, S, Rao, JH & Marakala, V 2013, 'Statistical modelling and forecasting of cervix cancer cases in radiation oncology treatment: A hospital based study from Western Nepal', Asian Pacific Journal of Cancer Prevention, vol. 14, no. 3, pp. 2097-2100. https://doi.org/10.7314/APJCP.2013.14.3.2097

Statistical modelling and forecasting of cervix cancer cases in radiation oncology treatment : A hospital based study from Western Nepal. / Sathian, Brijesh; Fazil, Abul; Sreedharan, Jayadevan; Pant, Sadip; Kakria, Anjali; Sharan, Krishna; Rajesh, E.; Vishrutha, K. V.; Shetty, Soumya B.; Shahnavaz, Shameema; Rao, Jyothi H.; Marakala, Vijaya.

In: Asian Pacific Journal of Cancer Prevention, Vol. 14, No. 3, 01.01.2013, p. 2097-2100.

Research output: Contribution to journalArticle

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T1 - Statistical modelling and forecasting of cervix cancer cases in radiation oncology treatment

T2 - A hospital based study from Western Nepal

AU - Sathian, Brijesh

AU - Fazil, Abul

AU - Sreedharan, Jayadevan

AU - Pant, Sadip

AU - Kakria, Anjali

AU - Sharan, Krishna

AU - Rajesh, E.

AU - Vishrutha, K. V.

AU - Shetty, Soumya B.

AU - Shahnavaz, Shameema

AU - Rao, Jyothi H.

AU - Marakala, Vijaya

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between 28th September 2000 and 31st December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curvefitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with R2=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focusand resource allocation on cervical cancer screening and treatment.

AB - Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between 28th September 2000 and 31st December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curvefitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with R2=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focusand resource allocation on cervical cancer screening and treatment.

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