Methodological outlines for assessing the costs of cancer patients care

Introduction. The planning of funding in the public health system and specifically in cancer care remains a challenge for the medical community. Some issues of cancer cost analysis are still not entirely resolved.

Aims. To review the options for analysis of direct cancer costs based on registered follow-up data. 

Methods. The targeting and consensus search methodology was applied to collect the relevant papers from PubMed, Cochrane, E-library (RSCI). 

Results and Discussion. The following options have been identified: 1) using incidence data; 2) using prevalence data; 3) system net and total costs approach; 4) phase approach; 5) cost estimation using censored data. The incidence costs are related to the time of diagnosis. The prevalence costs represent the costs over a fixed calendar period. The net costs can be calculated by subtracting the mean costs across non-cancer patients from the total mean costs across comparable cancer patients. Total costs are defined as the summated costs for cancer patients regardless of whether they are associated with cancer or not. Phase analysis is a variant of estimates based on morbidity data and includes identifying specific periods from the diagnosis when the costs significantly change. Cost estimation using censored data provides for the application of mathematical modeling methods.

Conclusion. The availability of combined cost analysis methods makes it possible to obtain a comprehensive economic assessment for cancer treatment approaches.

1. Karitskiy A.P. Main improvement organizations of federal specia-lized (oncologic) institute as a unit of health system. Pediatr. 2015; 6(4): 116-23. https://doi.org/10.17816/PED64116-123 (in Russian)

2. Voda A.I., Bostan I. Public health care financing and the costs of cancer care: a cross-national analysis. Cancers (Basel). 2018; 10(4): 117. https://doi.org/10.3390/cancers10040117

3. National Cancer Institute. Cancer Trends Progress Report. Available at: https://progressreport.cancer.gov (Accessed 20.11.19)

4. Lipscomb J. Estimating the cost of cancer care in the United States: a work very much in progress. J. Natl. Cancer Inst. 2008; 100(9): 607-10. https://doi.org/10.1093/jnci/djn132

5. Campos N.G., Kim J.J., Castle P.E., Ortendahl J.D., O’Shea M., Diaz M., et al. Health and economic impact of HPV 16/18 vaccination and cervical cancer screening in Eastern Africa. Int. J. Cancer. 2012; 130(11): 2672-84. https://doi.org/10.1002/ijc.26269

6. Goldie S.J., Kim J.J., Kobus K., Goldhaber-Fiebert J.D., Salomon J., O’Shea M.K., et al. Cost-effectiveness of HPV 16, 18 vaccination in Brazil. Vaccine. 2007; 25(33): 6257-70. https://doi.org/10.1016/j.vaccine.2007.05.058

7. Campos N.G., Castle P.E., Wright T.C., Kim J.J. Cervical cancer screening in low-resource settings: A cost-effectiveness framework for valuing tradeoffs between test performance and program coverage. Int. J. Cancer. 2015; 137(9): 2208-19. https://doi.org/10.1002/ijc.29594

8. Hoyle M., Crathorne L., Peters J., Jones-Hughes T., Cooper C., Napier M., et al. The clinical effectiveness and cost-effectiveness of cetuximab (mono- or combination chemotherapy), bevacizumab (combination with non-oxaliplatin chemotherapy) and panitumumab (monotherapy) for the treatment of metastatic colorectal cancer after first-line chemotherapy (review of technology appraisal No.150 and part review of technology appraisal No. 118): a systematic review and economic model. Health Technol. Assess. 2013; 17(14): 1-237. https://doi.org/10.3310/hta17140

9. Collins R., Fenwick E., Trowman R., Perard R., Norman G., Light K., et al. A systematic review and economic model of the clinical effectiveness and cost-effectiveness of docetaxel in combination with prednisone or prednisolone for the treatment of hormone-refractory metastatic prostate cancer. Health Technol. Assess. 2007; 11(2): iii-iv, xv-xviii, 1-179. https://doi.org/10.3310/hta11020

10. Jacobs V.R., Thoedtmann J., Brunner B., Kiechle M. An economic model to reduce the cost of chemotherapy for gynecologic cancer. Int. J. Fertil Womens Med. 2004; 49(6): 274-7.

11. Lipscomb J., Donaldson M.S., Hiatt R.A. Cancer outcomes research and the arenas of application. J. Natl. Cancer Inst. Monogr. 2004; (33): 1-7. https://doi.org/10.1093/jncimonographs/lgh038

12. You C.H., Kang S., Kwon Y.D. The economic burden of breast cancer survivors in Korea: A descriptive study using a 26-month micro-costing cohort approach. Asian Pac. J. Cancer Prev. 2019; 20(7): 2131-7. https://doi.org/10.31557/APJCP.2019.20.7.2131

13. Lairson D.R., Wu C.F., Chan W., Fu S., Hoffman K.E., Pettaway C.A. Mean treatment cost of incident cases of penile cancer for privately insured patients in the United States. Urol. Oncol. 2019; 37(4): 294.e17-294.e25. https://doi.org/10.1016/j.urolonc.2019.01.004

14. Khatiwoda S.R., Dhungana R.R., Sapkota V.P., Singh S. Estimating the direct cost of cancer in Nepal: a cross-sectional study in a tertiary cancer hospital. Front. Public Health. 2019; 7: 160. https://doi.org/10.3389/fpubh.2019.00160

15. Jeon S.M., Kwon J.W., Choi S.H., Park H.Y. Economic burden of lung cancer: A retrospective cohort study in South Korea, 2002-2015. PLoS One. 2019; 14(2): e0212878. https://doi.org/10.1371/journal.pone.0212878

16. McGuire A., Martin M., Lenz C., Sollano J.A. Treatment cost of non-small cell lung cancer in three European countries: comparisons across France, Germany, and England using administrative databases. J. Med. Econ. 2015; 18(7): 525-32. https://doi.org/10.3111/13696998.2015.1032974

17. Carrera P.M., Kantarjian H.M., Blinder V.S. The financial burden and distress of patients with cancer: Understanding and stepping-up action on the financial toxicity of cancer treatment. CA Cancer J. Clin. 2018; 68(2): 153-65. https://doi.org/10.3322/caac.21443

18. Bonakdar Tehrani A., Carroll N.V. The medicaid rebate: chan-ges in oncology drug prices after the affordable care act. Appl. Health Econ. Health Policy. 2017; 15(4): 513-20. https://doi.org/10.1007/s40258-017-0314-1

19. Baker M.S., Kessler L.G., Urban N., Smucker R.C. Estimating the treatment costs of breast and lung cancer. Med. Care. 1991; 29(1): 40-9. https://doi.org/10.1097/00005650-199101000-00004

20. Brown M.L., Riley G.F., Schussler N., Etzioni R. Estimating health care costs related to cancer treatment from SEER-Medicare data. Med. Care. 2002; 40(8 Suppl.): IV-104-17. https://doi.org/10.1097/00005650-200208001-00014

21. Taplin S.H., Barlow W., Urban N., Mandelson M.T., Timlin D.J., Ichikawa L., et al. Stage, age, comorbidity, and direct costs of colon, prostate, and breast cancer care. J. Natl. Cancer Inst. 1995; 87(6): 417-26. https://doi.org/10.1093/jnci/87.6.417

22. Attema A.E., Brouwer W.B.F., Claxton K. Discounting in economic evaluations. Pharmacoeconomics. 2018; 36(7): 745-58. https://doi.org/10.1007/s40273-018-0672-z

23. Barlow W.E. Overview of methods to estimate the medical costs of cancer. Med. Care. 2009; 47(7 Suppl. 1): S33-6. https://doi.org/10.1097/MLR.0b013e3181a2d847

24. Lin D.Y., Feuer E.J., Etzioni R., Wax Y. Estimating medical costs from incomplete follow-up data. Biometrics. 1997; 53(2): 419-34.

25. Piccinni C., Dondi L., Ronconi G., Calabria S., Pedrini A., Esposito I., et al. HR+/HER2- metastatic breast cancer: epidemiology, prescription patterns, healthcare resource utilisation and costs from a Large Italian Real-World Database. Clin. Drug Investig. 2019; 39(10): 945-51. https://doi.org/10.1007/s40261-019-00822-4

26. Shih Y.T., Xu Y., Chien C.R., Kim B., Shen Y., Li L., et al. Rising economic burden of renal cell carcinoma among elderly patients in the USA: Part II-an updated analysis of SEER-Medicare data. Pharmacoeconomics. 2019; 37(12): 1495-507. https://doi.org/10.1007/s40273-019-00824-2

27. Chang S., Long S.R., Kutikova L., Bowman L., Finley D., Crown W.H., et al. Estimating the cost of cancer: results on the basis of claims data analyses for cancer patients diagnosed with seven types of cancer during 1999 to 2000. J. Clin. Oncol. 2004; 22(17): 3524-30. https://doi.org/10.1200/JCO.2004.10.170

28. Alefan Q., Malhees R., Mhaidat N. Direct medical cost associated with colorectal cancer in north of Jordan. Curr. Probl. Cancer. 2017; 41(5): 371-81. https://doi.org/10.1016/j.currproblcancer.2017.05.001

29. Joseph A.K., Mark T.L., Mueller C. The period prevalence and costs of treating nonmelanoma skin cancers in patients over 65 years of age covered by medicare. Dermatol. Surg. 2001; 27(11): 955-9. https://doi.org/10.1046/j.1524-4725.2001.01106.x

30. Pisu M., Henrikson N.B., Banegas M.P., Yabroff K.R. Costs of cancer along the care continuum: What we can expect based on recent literature. Cancer. 2018; 124(21): 4181-91. https://doi.org/10.1002/cncr.31643

31. Deshmukh A.A., Zhao H., Franzini L., Lairson D.R., Chiao E.Y., Das P., et al. Total lifetime and cancer-related costs for elderly patients diagnosed with anal cancer in the United States. Am. J. Clin. Oncol. 2018; 41(2): 121-7. https://doi.org/10.1097/COC.0000000000000238

32. Calhoun E.A., Bennett C.L. Evaluating the total costs of cancer. The Northwestern University Costs of Cancer Program. Onco-logy (Williston Park). 2003; 17(1): 109-14; discussion 19-21.

33. Boltz M.M., Hollenbeak C.S., Schaefer E., Goldenberg D., Saunders B.D. Attributable costs of differentiated thyroid cancer in the elderly Medicare population. Surgery. 2013; 154(6): 1363-9; discussion 9-70. https://doi.org/10.1016/j.surg.2013.06.042

34. Yli-Uotila T., Kaunonen M., Pylkkanen L., Suominen T. The need for social support provided by the non-profit cancer societies throughout different phases in the cancer trajectory and its integration into public healthcare. Eur. J. Oncol. Nurs. 2016; 21: 97-104. https://doi.org/10.1016/j.ejon.2016.02.004

35. Sheehan D.F., Criss S.D., Chen Y., Eckel A., Palazzo L., Tramontano A.C., et al. Lung cancer costs by treatment strategy and phase of care among patients enrolled in Medicare. Cancer Med. 2019; 8(1): 94-103. https://doi.org/10.1002/cam4.1896

36. Tramontano A.C., Chen Y., Watson T.R., Eckel A., Hur C., Kong C.Y. Esophageal cancer treatment costs by phase of care and treatment modality, 2000-2013. Cancer Med. 2019; 8(11): 5158-72. https://doi.org/10.1002/cam4.2451

37. Adams M. Information and education across the phases of cancer care. Semin. Oncol. Nurs. 1991; 7(2): 105-11. https://doi.org/10.1016/0749-2081(91)90088-7

38. Bercow A.S., Chen L., Chatterjee S., Tergas A.I., Hou J.Y., Burke W.M., et al. Cost of care for the initial management of ovarian cancer. Obstet. Gynecol. 2017; 130(6): 1269-75. https://doi.org/10.1097/AOG.0000000000002317

39. Vyas A., Madhavan S.S., Sambamoorthi U., Pan X.L., Regier M., Hazard H., et al. Healthcare utilization and costs during the initial phase of care among elderly women with breast cancer. J. Natl. Compr. Canc. Netw. 2017; 15(11): 1401-9. https://doi.org/10.6004/jnccn.2017.0167

40. de Oliveira C., Pataky R., Bremner K.E., Rangrej J., Chan K.K., Cheung W.Y., et al. Phase-specific and lifetime costs of cancer care in Ontario, Canada. BMC Cancer. 2016; 16(1): 809. https://doi.org/10.1186/s12885-016-2835-7

41. Liu N., Mittmann N., Coyte P.C., Hancock-Howard R., Seung S.J., Earle C.C. Phase-specific healthcare costs of cervical cancer: estimates from a population-based study. Am. J. Obstet. Gynecol. 2016; 214(5): 615.e1-615.e11. https://doi.org/10.1016/j.ajog.2015.11.021

42. Rozman L.M., Campolina A.G., Lopez R.M., Chiba T., De Soarez P.C. Palliative cancer care: costs in a Brazilian quaternary hospital. BMJ Support. Palliat. Care. 2019; bmjspcare-2019-001809. https://doi.org/10.1136/bmjspcare-2019-001809

43. Yennurajalingam S., Lu Z., Reddy S.K., Rodriguez E.C., Nguyen K., Waletich-Flemming M.J., et al. Patterns of opioid prescription, use, and costs among patients with advanced cancer and inpatient palliative care between 2008 and 2014. J. Oncol. Pract. 2019; 15(1): e74-e83. https://doi.org/10.1200/JOP.18.00205

44. Kaye D.R., Min H.S., Herrel L.A., Dupree J.M., Ellimoottil C., Miller D.C. Costs of cancer care across the disease continuum. Oncologist. 2018; 23(7): 798-805. https://doi.org/10.1634/theoncologist.2017-0481

45. Thein H.H., Jembere N., Thavorn K., Chan K.K.W., Coyte P.C., de Oliveira C., et al. Estimates and predictors of health care costs of esophageal adenocarcinoma: a population-based cohort study. BMC Cancer. 2018; 18(1): 694. https://doi.org/10.1186/s12885-018-4620-2

46. Brown M.L., Riley G.F., Potosky A.L., Etzioni R.D. Obtaining long-term disease specific costs of care: application to Medicare enrollees diagnosed with colorectal cancer. Med. Care. 1999; 37(12): 1249-59. https://doi.org/10.1097/00005650-199912000-00008

47. Yabroff K.R., Lamont E.B., Mariotto A., Warren J.L., Topor M., Meekins A., et al. Cost of care for elderly cancer patients in the United States. J. Natl. Cancer Inst. 2008; 100(9): 630-41. https://doi.org/10.1093/jnci/djn103

48. Bashlakova E.E., Andreev D.A., Khachanova N.V., Davydovskaya M.V. Registries. Types of registries. Registries of Hemophilia (review). Vrach i informatsionnye tekhnologii. 2018; (1): 33-42. (in Russian)

49. Andreev D.A., Khachanova N.V., Kokushkin K.A., Davydovskaya M.V. Multiple sclerosis registries as a vital element in the transition to the value-vased healthcare. Problemy standartizatsii v zdravookhranenii. 2018; (3-4): 35-45. https://doi.org/10.26347/1607-2502201803-04035-045 (in Russian)

50. Andreev D.A., Bashlakova E.E., Khachanova N.V., Davydovskaya M.V. Cystic fibrosis patient registries: domestic and foreign experience. Pediatricheskaya farmakologiya. 2017; 14(2): 115-26. https://doi.org/10.15690/rf.v14i2.1726 (in Russian)

51. Zhao H., Bang H., Wang H., Pfeifer P.E. On the equivalence of some medical cost estimators with censored data. Stat. Med. 2007; 26(24): 4520-30. https://doi.org/10.1002/sim.2882

52. Quick H. Estimating county-level mortality rates using highly censored data from CDC WONDER. Prev. Chronic Dis. 2019; 16: E76. https://doi.org/10.5888/pcd16.180441

53. Hsu C.Y., Chen C.H., Hsu K.N., Lu Y.H. A useful design utilizing the information fraction in a group sequential clinical trial with censored survival data. Biometrics. 2019; 75(1): 133-43. https://doi.org/10.1111/biom.12925

54. Costa S., Scott D.W., Steidl C., Peacock S.J., Regier D.A. Real-world costing analysis for diffuse large B-cell lymphoma in British Columbia. Curr. Oncol. 2019; 26(2): 108-13. https://doi.org/10.3747/co.26.4565

55. Sun L., Legood R., Dos-Santos-Silva I., Gaiha S.M., Sadique Z. Global treatment costs of breast cancer by stage: A systematic review. PLoS One. 2018; 13(11): e0207993. https://doi.org/10.1371/journal.pone.0207993

56. Lairson D.R., Fu S., Chan W., Xu L., Shelal Z., Ramondetta L. Mean direct medical care costs associated with cervical cancer for commercially insured patients in Texas. Gynecol. Oncol. 2017; 145(1): 108-13. https://doi.org/10.1016/j.ygyno.2017.02.011

57. Andreev D.A., Khachanova N.V., Stepanova V.N., Bashlakova E.E., Evdoshenko E.P., Davydovskaya M.V. Standardized modeling of the chronic disease progression (review). Problemy standartizatsii v zdravookhranenii. 2017; (9-10): 12-24. https://doi.org/10.26347/1607-2502201709-10012-024 (in Russian)

58. Yu T., Wu L., Gilbert P. New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies. Lifetime Data Anal. 2019; 25(2): 229-58. https://doi.org/10.1007/s10985-018-9434-7

59. Hwang J.S., Hu T.H., Lee L.J., Wang J.D. Estimating lifetime medical costs from censored claims data. Health Econ. 2017; 26(12): e332-e44. https://doi.org/10.1002/hec.3512

60. Zhao H., Tian L. On estimating medical cost and incremental cost-effectiveness ratios with censored data. Biometrics. 2001; 57(4): 1002-8. https://doi.org/10.1111/j.0006-341x.2001.01002.x

61. Basu A., Manning W.G. Estimating lifetime or episode-of-illness costs under censoring. Health Econ. 2010; 19(9): 1010-28. DOI: http://doi.org/10.1002/hec.1640

62. Yoon G., Jiang W., Liu L., Shih Y.T. Simple quasi-Bayes approach for modeling mean medical costs. Int. J. Biostat. 2019; 16(1): /j/ijb.2020.16.issue-1/ijb-2018-0122/ijb-2018-0122.xml. https://doi.org/10.1515/ijb-2018-0122

63. O’Hagan A., Stevens J.W. On estimators of medical costs with censored data. J. Health Econ. 2004; 23(3): 615-25. https://doi.org/10.1016/j.jhealeco.2003.06.006

64. Wang X., Beste L.A., Maier M.M., Zhou X.H. Double robust estimator of average causal treatment effect for censored medical cost data. Stat. Med. 2016; 35(18): 3101-16. https://doi.org/10.1002/sim.6876

65. Goldie S.J., Daniels N. Model-based analyses to compare health and economic outcomes of cancer control: inclusion of disparities. J. Natl. Cancer Inst. 2011; 103(18): 1373-86. https://doi.org/10.1093/jnci/djr303

66. Jabbour E.J., Mendiola M.F., Lingohr-Smith M., Lin J., Makenbaeva D. Economic modeling to evaluate the impact of chronic myeloid leukemia therapy management on the oncology care model in the US. J. Med. Econ. 2019; 22(11): 1113-8. https://doi.org/10.1080/13696998.2019.1618316

67. Wijeysundera H.C., Wang X., Tomlinson G., Ko D.T., Krahn M.D. Techniques for estimating health care costs with censored data: an overview for the health services researcher. Clinicoecon. Outcomes Res. 2012; 4: 145-55. https://doi.org/10.2147/CEOR.S31552

68. Vock D.M., Wolfson J., Bandyopadhyay S., Adomavicius G., Johnson P.E., Vazquez-Benitez G., et al. Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting. J. Biomed. Inform. 2016; 61: 119-31. https://doi.org/10.1016/j.jbi.2016.03.009