Economic evaluation of a hypothetical screening assay for alloimmunization risk among transfused patients with sickle cell disease

Abstract

Background: Prophylactic antigen-matching can reduce alloimmunization rates among chronically transfused patients with sickle cell disease (SCD), but this matching increases costs and may only benefit 30% of patients. We assessed the clinical and financial value of a potential assay for alloimmunization risk that would allow for targeted antigen-matching.

Study design and methods: A Markov-based model evaluated direct medical costs and alloimmunization events over 10 to 20 years among transfused (simple or exchange) patients with SCD. Four matching strategies were evaluated: prospective matching (for all patients), history-based matching (only for patients with prior alloimmunization), perfectly informed matching (assay with 100% sensitivity, 100% specificity), and imperfectly informed matching (reduced accuracy). Under all matching protocols, matching included C, E, K, and any additional alloantibodies present. A hospital perspective was adopted, with costs (2012US$) and events discounted (3%).

Results: Perfectly informed antigen-matching using a $1000 assay is expected to save $82,334 per patient over 10 years, compared to prospective matching. Perfectly informed antigen-matching is more costly than history-based matching, but reduces alloimmunization events by 45.6% over 10 years. Averting each alloimmunization event using this strategy would cost an additional $10,934 per patient. Imperfectly informed antigen-matching using an assay with 75% specificity and 75% sensitivity is less costly than prospective matching, but increases alloimmunization events. Compared to history-based matching, imperfectly informed matching would decrease alloimmunization events by 32.61%, at an additional cost of $147,915 per patient over 10 years. Cost-effectiveness of informed antigen-matching is largely driven by assay specificity.

Conclusions: A sufficiently specific assay to inform antigen-matching may be cost-effective in reducing alloimmunization among transfused patients with SCD.

Figure 1

(A). A Markov-based decision tree (D) model was constructed to evaluate alloimmunization events and costs associated with four alternative strategies of antigen-matching among chronically transfusion patients with SCD. Strategy 1, “History-Based Antigen-Matching,” involved providing blood matched for CEK and any other developed alloantibodies only to patients with a history of alloimmunization. Strategy 2 characterized “Prospective Antigen-Matching,” where all transfused patients received prophylactically C, E, K matched blood. Strategy 3, “Perfectly Informed Antigen-Matching,” was based upon a hypothetical assay with 100% sensitivity and 100% specificity. Patients screening positive would prophylactically receive C, E, K antigen-matched blood. Strategy 4 characterized “Imperfectly Informed Antigen-Matching,” where a screening assay with <100% sensitivity and <100% specificity was used to determine which patients prophylactically received C, E, K matched blood. Patients who had not been identified by the imperfect test but developed alloantibodies would also receive antigen-matched blood after the initial alloimmunization event. Outcomes were evaluated for a cohort of initially transfusion-naïve patients with SCD. A series of chance nodes were used to distinguish between patients with different health-related and financial characteristics. For each strategy evaluated, possible transfusion protocols (Pediatric Simple, Pediatric Exchange, Adult Simple, or Adult Exchange) were distinguished. Each protocol was associated with a different number of units transfused and thus a different annual alloimmunization rate. For Strategies 3 and 4, chance nodes were used to distinguish between alternative assay outcomes (True Positive, False Positive, True Negative, or False Negative). (B) For each path along the decision tree, a Markov model (M) was used to track outcomes over a series of 1 year cycles of chronic transfusion therapy. The model consisted of three nodes, “At Risk of Alloimmunization, No Prior History of Alloimmunization,” “At Risk of Alloimmunization, Prior History of Alloimmunization,” and “Not At Risk of Alloimmunization.” At the beginning of the simulation, the patients identified as “at-risk” occupied the first node (At Risk of Alloimmunization, No Prior History of Alloimmunization), while all patients not at risk occupied the third node (Not At Risk of Alloimmunization). Transitions between nodes, as denoted by arrows, could occur between each cycle.

Figure 2. One-Way Sensitivity Analyses: Cost-Effectiveness of Screening Assay to Identify Patients Likely to be Alloimmunized

Tornado diagram shows the range of incremental cost-effectiveness ratios (ICERs) associated with variation in selected input variables. Ranges of input parameters are noted in parentheses. In the base case scenario, the ICER is calculated using a strategy of informed antigen-matching using a perfect assay (100% sensitivity, 100% specificity, and cost of $1000 per test), with history-based antigen-matching for C, E, and K as a reference strategy. Solid black line indicates the base-case ICER of $10,934 for each alloimmunization event averted. Variation in the ICER associated with varying a single input parameter is shown by each gray bar. Dashed black line reflects a threshold value of $50,000 per alloimmunization event averted. The extensive range of ICERs corresponding to variation in the assay specificity (40–100%) indicates that the cost-effectiveness of a potential assay is highly dependent on assay specificity.