Cost-effectiveness of intrapleural use of tissue plasminogen activator and DNase in pleural infection: evidence from the MIST2 randomised controlled trial
Bibliographic record
Abstract
The MIST2 (Second Multicentre Intrapleural Sepsis Trial) trial showed that combined intrapleural use of tissue plasminogen activator (t-PA) and recombinant human DNase was effective when compared with single agents or placebo. However, the treatment costs are significant and overall cost-effectiveness of combined therapy remains unclear.An economic evaluation of the MIST2 trial was performed to assess the cost-effectiveness of combined therapy. Costs included were those related to study medications, initial hospital stay and subsequent hospitalisations. Outcomes were measured in terms of life-years gained. All costs were reported in euro and in 2016 prices.Mean annual costs were lowest in the t-PA-DNase group (EUR 10 605 for t-PA, EUR 17 856 for DNase, EUR 13 483 for placebo and EUR 7248 for t-PA-DNase; p=0.209). Mean 1-year life expectancy was 0.988 for t-PA, 0.923 for DNase, and 0.969 for both placebo and t-PA-DNase (p=0.296). Both DNase and placebo were less effective, in terms of life-years gained, and more costly than t-PA. When placebo was compared with t-PA-DNase, the incremental cost per life-year gained of placebo was EUR 1.6 billion, with a probability of 0.85 of t-PA-DNase being cost-effective.This study demonstrates that combined t-PA-DNase is likely to be highly cost-effective. In light of this evidence, a definitive trial designed to facilitate a thorough economic evaluation is warranted to provide further evidence on the cost-effectiveness of this promising combined intervention.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".