OBJECTIVES

In 2018, there were 13,500 new cases and 11,300 deaths from leukemia in Indonesia. Leukemia alone costed Indonesia over Rp328 billion (US$20 million). Effective treatment for acute leukemia is only possible with accurate disease lineage classification. This study aims to compare the clinical and economic value of diagnosing patients by current local diagnostics standard (morphology) versus proposed diagnostics (flow cytometry) for acute leukemia classification in Indonesia class A hospitals.

METHODS

A decision tree reflecting current referral pathway based on morphology and another for proposed referral pathway using flow cytometry were developed in Microsoft Excel. Budget impact analysis was conducted comparing cost outcomes of the two decision trees. Due to the lack of publicly available data, local oncology and pathology experts were interviewed for proportion of patients going through the referral pathway, diagnosis accuracy of morphology (78%) and flow cytometry (95%), treatment response rates (60–80%), test cost (morphology: Rp450,000; flow cytometry: Rp933,300) and treatment cost (acute myeloid leukemia: Rp100 million; acute lymphocytic leukemia: Rp60 million). Global peer-reviewed data were used for classification accuracy of both tests. Outcomes estimated and compared include patients accurately diagnosed, average time to diagnosis, average prognosis and costs.

RESULTS

With the adoption of flow cytometry, for 100,000 symptomatic patients, the model estimated 25,000 more patients receiving accurate diagnosis; average time to diagnosis can be shortened by one week and average probability of death can be reduced by 9%. Total diagnostics and treatment cost is estimated to be Rp25 billion lower. Rp17 million can be avoided from unnecessary treatment due to morphological inaccuracies. On average, additional Rp453,000 may be required for each patient’s diagnosis but Rp439,000 can be saved from treatment.

CONCLUSIONS

With flow cytometry, more patients can be diagnosed accurately and treated appropriately earlier, thus improving acute leukemia survival. Cost savings can be expected due to reduction of unnecessary treatment.