Minimal Residual Disease Evaluation in Childhood Acute Lymphoblastic Leukemia: An Economic Analysis.
Bibliographic record
Abstract
BACKGROUND: Minimal residual disease (MRD) testing by higher performance techniques such as flow cytometry and polymerase chain reaction (PCR) can be used to detect the proportion of remaining leukemic cells in bone marrow or peripheral blood during and after the first phases of chemotherapy in children with acute lymphoblastic leukemia (ALL). The results of MRD testing are used to reclassify these patients and guide changes in treatment according to their future risk of relapse. We conducted a systematic review of the economic literature, cost-effectiveness analysis, and budget-impact analysis to ascertain the cost-effectiveness and economic impact of MRD testing by flow cytometry for management of childhood precursor B-cell ALL in Ontario. METHODS: A systematic literature search (1998-2014) identified studies that examined the incremental cost-effectiveness of MRD testing by either flow cytometry or PCR. We developed a lifetime state-transition (Markov) microsimulation model to quantify the cost-effectiveness of MRD testing followed by risk-directed therapy to no MRD testing and to estimate its marginal effect on health outcomes and on costs. Model input parameters were based on the literature, expert opinion, and data from the Pediatric Oncology Group of Ontario Networked Information System. Using predictions from our Markov model, we estimated the 1-year cost burden of MRD testing versus no testing and forecasted its economic impact over 3 and 5 years. RESULTS: In a base-case cost-effectiveness analysis, compared with no testing, MRD testing by flow cytometry at the end of induction and consolidation was associated with an increased discounted survival of 0.0958 quality-adjusted life-years (QALYs) and increased discounted costs of $4,180, yielding an incremental cost-effectiveness ratio (ICER) of $43,613/QALY gained. After accounting for parameter uncertainty, incremental cost-effectiveness of MRD testing was associated with an ICER of $50,249/QALY gained. In the budget-impact analysis, the 1-year cost expenditure for MRD testing by flow cytometry in newly diagnosed patients with precursor B-cell ALL was estimated at $340,760. We forecasted that the province would have to pay approximately $1.3 million over 3 years and $2.4 million over 5 years for MRD testing by flow cytometry in this population. CONCLUSIONS: Compared with no testing, MRD testing by flow cytometry in newly diagnosed patients with precursor B-cell ALL represents good value for money at commonly used willingness-to-pay thresholds of $50,000/QALY and $100,000/QALY.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".