Actuarial Modelling for Patients with Acute Lymphoblastic Leukaemia (ALL) based on CNS1 Status

  • Gurprit Grover Department of Statistics, University of Delhi, Delhi, India.
  • Parmeet Kumar Vinit Department of Statistics, University of Delhi, Delhi, India. https://orcid.org/0000-0002-1779-6522
Keywords: ALL, CNS, Insurance, Premium, Finance

Abstract

Introduction: Worldwide, Acute Lymphoblastic Leukaemia (ALL) is the most frequent cancer in children. One of the major clinical challenges is adequate diagnosis and treatment of Central Nervous System (CNS) involvement in this disease. CNS relapse has been a barrier to the successful treatment of ALL for many years. Recent studies have shown encouraging results in the survival of these patients for a long time. However, their long-term survival depends upon the cost of therapy toxicity and financial distress. The primitive aim of the paper is to propose a yearly insurance plan to assist these patients financially during the diagnosis period.

Method: Based on the CNS status 110 patients are categorised to estimate their long-term survival. Survival times of CNS1 status and for all the patients cumulatively are estimated by Kaplan-Meier and Cox- PH model in presence of the prognostic factors. The survival estimates are used to estimate the premium cost. The premium cost is estimated using a deterministic model which is advantageous for the patient and serviceable for the insurance provider.

Result: Both the methods Kaplan-Meier and Cox-PH gave higher survival estimates for ALL patients cumulatively as compared to CNS1. Survival estimate from Cox-PH is 0.998 and 0.997 of first year of follow-up for patients taken cumulatively and in CNS1 respectively. For the fifth year the survival estimates are 0.802 and 0.783 respectively. The estimated premium cost for a 100 rupees of sum insured is rupees 4.7 for the first year and rupees 26.69 for the fifth year for patients taken cumulatively. Same for CNS1, it is rupees 6.24 and 29.42.

Conclusion: Cox-PH model for estimating the survival is recommended since it includes the prognostic factors. The insurance plan suggests to opt for the premium as early as possibly since it costs less and increases later.

How to cite this article:
Grover G, Vinit PK. Actuarial Modelling for Patients with Acute Lymphoblastic Leukaemia (ALL) based on CNS1 Status. J Commun Dis. 2021;53(3):23-32.

DOI: https://doi.org/10.24321/0019.5138.202136

References

Bhutani M, Kochupillai V, Bakhshi S. Childhood acute lymphoblastic leukemia: Indian experience. Ind J Med

Ped Onco. 2004;25(2). [Google Scholar]

Howard SC, Gajjar AJ, Cheng C, Kritchevsky SB, Somes GW, Harrison PL, Ribeiro RC, Rivera GK, Rubnitz JE,

Sandlund JT, de Armendi AJ, Razzouk BI, Pui CH. Risk factors for traumatic and bloody lumbar puncture in

children with acute lymphoblastic leukemia. JAMA. 2002 Oct;288(16):2001-7. [PubMed] [Google Scholar]

Devita VT, Chu E. A history of cancer chemotherapy. Cancer Res. 2008 Nov;68(21):8643-53. [PubMed]

[Google Scholar]

Pui CH, Mahmoud HH, Rivera GK, Hancock ML, Sandlund JT, Behm FG, Head DR, Relling MV, Ribeiro RC, Rubnitz

JE, Kun LE, Evans WE. Early intensification of intrathecal chemotherapy virtually eliminates central nervous

system relapse in children with acute lymphoblastic leukemia. Blood. 1998 Jul;92(2):411-5. [PubMed]

[Google Scholar]

Pui CH. Childhood leukemias. N Engl J Med. 1995 Jun;332(24):1618-30. [PubMed] [Google Scholar]

Pinkel D, Hernandez K, Borella L, Holton C, Aur R, Samoy G, Pratt C. Drug dosage and remission duration

in childhood lymphocytic leukemia. Cancer. 1971 Feb;27(2):247-56. [PubMed] [Google Scholar]

Mahmoud HH, Rivera GK, Hancock ML, Krance RA, Kun LE, Behm FG, Ribeiro RC, Sandlund JT, Crist WM,

Pui CH. Low leukocyte counts with blast cells in cerebrospinal fluid of children with newly diagnosed

acute lymphoblastic leukemia. N Engl J Med. 1993 Jul;329(5):314-9. [PubMed] [Google Scholar]

Arora RS, Arora B. Acute leukemia in children: A review of the current Indian data. South Asian J Cancer. 2016

Jul-Sep;5(3):155-60. [PubMed] [Google Scholar]

Pui CH, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med. 2004;350(15):1535-48.

[PubMed] [Google Scholar]

Pui CH, Cheng C, Leung W, Rai SN, Rivera GK, Sandlund JT, Ribeiro RC, Relling MV, Kun LE, Evans WE, Hudson

MM. Extended follow-up of long-term survivors of childhood acute lymphoblastic leukemia. N Engl J Med.

Aug;349(7):640-9. [PubMed] [Google Scholar]

Grover G, Vinit PK, Thakur AK. Actuarial modelling of insurance premium for patients with acute

lymphoblastic leukemia (ALL). J Appl Quant Methods. 2018;13(4). [Google Scholar]

Grover G, Thakur AK, Garg B. Cure fraction estimation for traumatic lumbar puncture in patients with acute

lymphoblastic leukemia. Res Rev J Oncol Hematol. 2018;7(3):12-21.

Cancela CSP, Murao M, Viana MB, Oliveira BMD. Incidence and risk factors for central nervous system

relapse in children and adolescents with acute lymphoblastic leukemia. Rev Bras Hematol Hemoter.

;34(6):436-41. [PubMed] [Google Scholar]

Chiang CL. A stochastic study of the life table and its applications: I. Probability distributions of the biometric

functions. Biometrics. 1960;16(4):618-35. [Google Scholar]

Bowers NL, Gerber HU, Hickman JC, Jones DA, Nesbitt CJ. Actuarial mathematics. Transactions of the Faculty

of Actuaries. 1987;41:91-4. [Google Scholar]

Published
2021-09-30