Systematic review, meta-analysis and economic modelling of ...
Systematic review, meta-analysis and economic modelling of ... Systematic review, meta-analysis and economic modelling of ...
Assessment of cost-effectiveness evidenceThe following strategies were tested in the main analysis:1. Cheapest and least effective Discharge all patients home immediately without testing or treatment.2. Most effective and expensive Measure troponin level after 10 hours has elapsed from the worstsymptoms, admit to hospital and treat if troponin assay is positive, discharge home without treatmentis troponin assay is negative.3. Troponin testing on arrival Measure troponin level on arrival, manage according to strategy 2 ifpositive (i.e. measure troponin level again after 10 hours from worst symptoms), discharge homewithout treatment if negative. This strategy was tested using different initial troponin assays andthresholds for positivity.In each strategy we assumed that there was a 2-hour delay from the time at which sampling could beperformed to the time at which results became available and a decision made. If the results were availablewithin 4 hours of patient presentation to hospital we assumed that the patient was still in the ED anda decision could be made immediately. If not, we assumed that they had moved to another location(a ward or clinical decision unit) and managed according to one of the three scenarios outlined below.We also assumed that there was a 1-hour delay between arrival at hospital and biomarker assessmentcommencing. This effectively meant that only decisions made on presentation biomarkers could be actedon in the ED.With regard to patient management after the ED, we tested the model in three different scenarios:1. The ‘doctor on demand’ scenario, in which medical staff were available 24 hours a day to make adisposition decision within 1 hour of the results being available.2. The twice-daily ward round scenario, in which medical staff were only available at twice-daily wardrounds (9 am and 6 pm) to make disposition decisions.3. The once-daily ward round scenario, in which medical staff were only available at one daily wardround (2 pm) to make disposition decisions.We took this approach because it was possible that different strategies may have different levels of costeffectivenessin different settings. For example, early discharge strategies may be less cost-effective if theLoS associated with delayed testing strategies is controlled by efficient patient review. Users of the resultsare thus able to decide which scenario best reflects their local practice.We also undertook a secondary analysis that involved adding other biomarkers to troponin at presentationto determine whether adding an alternative biomarker was cost-effective compared with troponin alone atpresentation or a 10-hour troponin test. This analysis was undertaken using data from primary studies thatcompared the sensitivity and specificity of troponin alone to troponin with the biomarker (with elevationof either biomarker being considered positive). We assumed that the additional biomarker would incuran additional cost, but otherwise the model would follow the main analysis. For each study the modelcompared the following strategies:1. discharge without testing or treatment2. presentation troponin alone3. presentation troponin in combination with the other biomarkers4. 10-hour troponin test.Diagnostic parameters of each strategyEach strategy specified how the biomarker(s) should be interpreted and what decision would be made onthe basis of each biomarker result. The options were:1. MI ruled out: discharge with no further testing84NIHR Journals Library
DOI: 10.3310/hta17010 Health Technology Assessment 2013 Vol. 17 No. 12. MI ruled in: admit for MI treatment3. MI uncertain: wait and repeat biomarker testing.Option 1 relates to strategy sensitivity. Although the strategy may define MI as having been ruled out, thepatient may actually have MI that is missed owing to suboptimal sensitivity.We stipulated that option 2 could only be applied on the basis of a standard modern troponin assay resultabove the 99th percentile. We assumed that this provided definitive evidence of MI and that strategieswould only recommend MI treatment on the basis of this evidence. Every strategy, (except no testing ortreatment), therefore had to include troponin at some point to diagnose MI.For option 3, the strategy defined when further testing was performed, what test would be performedand how this test would be interpreted. In most strategies the next test was a 10-hour troponin and in allstrategies the MI uncertain option ended when a 10-hour troponin test was performed. We stipulated thatthe 10-hour troponin test would use a standard modern assay with the 99th percentile as the thresholdfor positivity, thus allowing MI to be definitively ruled in or ruled out.Table 34 shows the estimates of sensitivity and specificity for MI for each strategy tested and the sourcesfor these estimates. We selected meta-analysis data for TnT because the point estimates of sensitivity andspecificity varied in the expected manner when different thresholds and assays were used, i.e. a lowerthreshold and/or high-sensitivity assay had higher sensitivity and lower specificity. This allowed us toexplore the influence of varying the diagnostic threshold upon cost-effectiveness. The median values of theposterior distributions for sensitivity and specificity were used in the deterministic analysis.We also undertook two sensitivity analyses:1. Replacing presentation HsTnT with the ADVIA Centaur Ultra troponin I assay. Our meta-analysissuggested that this assay has lower sensitivity and higher specificity than HsTnT, so this analysis testedwhether or not findings were dependent on the high estimated sensitivity of TnT. The estimates forsensitivity and specificity for the ADVIA Centaur Ultra troponin I assay were 0.86 (95% predictiveinterval 0.26 to 0.99) and 0.89 (95% predictive interval 0.40 to 0.99), respectively.2. Additional inclusion of a strategy using measurement of high-sensitivity TnI at presentation and3 hours later. Recent analysis 154 has suggested that this provides better sensitivity than presentationtesting. We assumed that additional costs were incurred providing care until 3-hour results wereavailable but that a doctor would be available on demand to act on the results. The estimates ofsensitivity and specificity were 0.982 [95% confidence interval (CI) 0.959 to 0.994] and 0.904 (95% CI0.884 to 0.922), respectively. 154TABLE 34 Estimates of sensitivity and specificity used in the modelStrategySensitivity (95%predictive interval)Specificity (95%predictive interval)SourceDischarge without testing or treatment 0 1 Theoretical10-hour troponin test 1 1 TheoreticalPresentation TnT using 10% CV threshold(0.03 µg/l)Presentation TnT using 99th percentilethreshold (0.01 µg/l)Presentation HsTnT using 99th percentilethreshold (0.014 µg/l)0.74 (0.35 to 0.94) 0.96 (0.76 to 0.99) Meta-analysis0.80 (0.30 to 0.97) 0.91 (0.53 to 0.99) Meta-analysis0.96 (0.27 to 1.00) 0.72 (0.03 to 0.99) Meta-analysis© Queen’s Printer and Controller of HMSO 2013. This work was produced by Goodacre et al. under the terms of a commissioning contract issued by the Secretary of Statefor Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journalsprovided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should beaddressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton SciencePark, Southampton SO16 7NS, UK.85
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Assessment <strong>of</strong> cost-effectiveness evidenceThe following strategies were tested in the main <strong>analysis</strong>:1. Cheapest <strong>and</strong> least effective Discharge all patients home immediately without testing or treatment.2. Most effective <strong>and</strong> expensive Measure troponin level after 10 hours has elapsed from the worstsymptoms, admit to hospital <strong>and</strong> treat if troponin assay is positive, discharge home without treatmentis troponin assay is negative.3. Troponin testing on arrival Measure troponin level on arrival, manage according to strategy 2 ifpositive (i.e. measure troponin level again after 10 hours from worst symptoms), discharge homewithout treatment if negative. This strategy was tested using different initial troponin assays <strong>and</strong>thresholds for positivity.In each strategy we assumed that there was a 2-hour delay from the time at which sampling could beperformed to the time at which results became available <strong>and</strong> a decision made. If the results were availablewithin 4 hours <strong>of</strong> patient presentation to hospital we assumed that the patient was still in the ED <strong>and</strong>a decision could be made immediately. If not, we assumed that they had moved to another location(a ward or clinical decision unit) <strong>and</strong> managed according to one <strong>of</strong> the three scenarios outlined below.We also assumed that there was a 1-hour delay between arrival at hospital <strong>and</strong> biomarker assessmentcommencing. This effectively meant that only decisions made on presentation biomarkers could be actedon in the ED.With regard to patient management after the ED, we tested the model in three different scenarios:1. The ‘doctor on dem<strong>and</strong>’ scenario, in which medical staff were available 24 hours a day to make adisposition decision within 1 hour <strong>of</strong> the results being available.2. The twice-daily ward round scenario, in which medical staff were only available at twice-daily wardrounds (9 am <strong>and</strong> 6 pm) to make disposition decisions.3. The once-daily ward round scenario, in which medical staff were only available at one daily wardround (2 pm) to make disposition decisions.We took this approach because it was possible that different strategies may have different levels <strong>of</strong> costeffectivenessin different settings. For example, early discharge strategies may be less cost-effective if theLoS associated with delayed testing strategies is controlled by efficient patient <strong>review</strong>. Users <strong>of</strong> the resultsare thus able to decide which scenario best reflects their local practice.We also undertook a secondary <strong>analysis</strong> that involved adding other biomarkers to troponin at presentationto determine whether adding an alternative biomarker was cost-effective compared with troponin alone atpresentation or a 10-hour troponin test. This <strong>analysis</strong> was undertaken using data from primary studies thatcompared the sensitivity <strong>and</strong> specificity <strong>of</strong> troponin alone to troponin with the biomarker (with elevation<strong>of</strong> either biomarker being considered positive). We assumed that the additional biomarker would incuran additional cost, but otherwise the model would follow the main <strong>analysis</strong>. For each study the modelcompared the following strategies:1. discharge without testing or treatment2. presentation troponin alone3. presentation troponin in combination with the other biomarkers4. 10-hour troponin test.Diagnostic parameters <strong>of</strong> each strategyEach strategy specified how the biomarker(s) should be interpreted <strong>and</strong> what decision would be made onthe basis <strong>of</strong> each biomarker result. The options were:1. MI ruled out: discharge with no further testing84NIHR Journals Library