Economic Evaluations of Hematological Malignancies Compared with Solid Tumors

Abstract

Introduction: Cancer care costs escalated with the introduction of novel therapies. Therefore, cancer-related Cost Utility Analyses (CUAs) are used to guide policy makers. Since numerous methods (criteria) exist to evaluate CUAs, we compared these criteria between CUAs of solid tumors and those of hematological malignancies. Methods:A systemic MEDLINE search of English-language publications between 2001 and 2012 was performed. Strict inclusion criteria were limited to CUAs examining one single intervention and one single study comparator. Standard data of 66 variables, based on the Drummond criteria, were collected to review each CUA for clarity, completeness, and health economic methodological quality.Results: Among 8,515 screened papers on Pubmed, 177 cancer-related CUAs (2%) were eligible. Solid tumors and hematological malignancies CUAs constituted 161(91%) and 16(9%). Among the standardized methods for evaluating CUAs, those of solid tumors reported more frequently the presentation of cost-effectiveness acceptability curve (p=0.02) and the use of threshold value to interpret study results (p=0.024) than those of hematological malignancies. Further, CUAs of solid tumors were more frequently multicenter-based (p=0.014); however, CUAs of hematological malignancies listed differential quality adjusted life year separately more frequently (p=0.02). Outcomes of CUAs of solid tumors were more frequently reported as significant (p=0.014). Conclusions:CUAs of solid tumors abided more frequently with the standardized methods (criteria) than those of hematological malignancies, which may be due in part to their multiple study sites. CUAs of hematological malignancies may warrant more methodological standardization and incorporate more study sites. MethodsA systemic MEDLINE search by the keywords: CUAs and cancer of English-language manuscripts published between 2001 and 2012 was performed. Eligibility criteria consisted of including only CUAs that examined one single intervention and one single study comparator. For example, adding rituximab to fludarabine and cyclophosphamide for the treatment of previously untreated chronic lymphocytic leukemia [15]. Exclusion criteria included CUAs that examined more than one intervention, more than one comparator or more than one study population or type of malignancy. The study population was not limited by age; therefore, CUAs examining children, adult or geriatric populations were included.

A Need of Metrics in Cancer Economics: Myth or Hope

“…Dr Wetzler's work suggested that a drug such as decitabine may be arguably considered for elderly newly diagnosed AML patients given the economic pressures in the US health system; however, this is not a criterion for drug approval [3]. However, as certain cancers are rare; applying economic model to clinical outcome to demonstrate which drug is more cost effective in an era of increasing economic pressures is reasonable [4]. Especially those cancer patients who express fear of bankruptcy in light of the costly cancer care [5].…”

How to Calculate Better Our Financial Risk in Oncology?

“…However, in the paucity of patients in certain rare tumors researchers may consider speculative models to wisely pilot our allocation of our scarcely earned dollar on a specific treatment. The advantage of such models in rare tumors may ensue from considering a significant large patient population in each arm of the analysis while adopting real-time survival probabilities and cost data [4].…”