If these statistical measures were not available then the methods described in section 16.1.3 of the Cochrane Handbook (version 5.1.0, updated March 2011) were applied. 4.3.3.1.1 Generic inverse variance If a study reported only the summary statistic and 95% CI the generic-inverse variance method was used to enter data into RevMan5.283 If the control event rate was reported this was used to generate the absolute risk difference in GRADEpro.138 If multivariate analysis was used to derive the summary statistic but no adjusted control event rate was reported no absolute risk difference was calculated. Statistical heterogeneity was assessed for each meta-analysis estimate by considering the chi- squared test for significance at p<0.1 or an I-squared (I2 ) inconsistency statistic (with an I-squared value of more than 50% indicating significant heterogeneity) as well as the distribution of effects. Where significant heterogeneity was present, predefined subgrouping of studies was carried out as specified a priori in the review protocols (appendix A). If the subgroup analysis resolved heterogeneity within all of the derived subgroups, then each of the derived subgroups were adopted as separate outcomes (providing at least 1 study remained in each subgroup. Assessments of potential differences in effect between subgroups were based on the chi- squared tests for heterogeneity statistics between subgroups. Any subgroup differences were interpreted with caution as separating the groups breaks the study randomisation and as such is subject to uncontrolled confounding. For some questions additional subgrouping was applied, and this is documented in the individual review question protocols (see appendix A). These additional subgrouping strategies were applied independently, so subunits of subgroups were not created, unlike the situation with strata. Other subgrouping strategies were only used if the age category subgroup was unable to explain heterogeneity, then these further subgrouping strategies were applied in order of priority.


Other subgrouping strategies were only used if the age category subgroup was unable to explain heterogeneity, then these further subgrouping strategies were applied in order of priority. Again, once a subgrouping strategy was found to explain heterogeneity from all derived subgroups, further subgrouping strategies were not used. If all predefined strategies of subgrouping were unable to explain statistical heterogeneity within each derived subgroup, then a random effects (DerSimonian and Laird) model was employed to the entire group of studies in the meta-analysis. A random-effects model assumes a distribution of populations, rather than a single population. This leads to a widening of the confidence interval around the overall estimate, thus providing a more realistic interpretation of the true distribution of effects across more than 1 population. If, however, the committee considered the heterogeneity was so large that meta-analysis was inappropriate, then the results were described narratively. 4.3.3.1.3 Complex analysis Where studies had used a crossover design, paired continuous data were extracted where possible, and forest plots were generated in RevMan5283 with the generic inverse variance function. When a crossover study had categorical data and the number of subjects with an event in both interventions Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 was known, the standard error (of the log of the risk ratio) was calculated using the simplified Mantel-Haenszel method for paired outcomes. Forest plots were also generated in RevMan5283 with the generic inverse variance function. If paired continuous or categorical data were not available from the crossover studies, the separate group data were analysed in the same way as data from parallel groups, on the basis that this approach would overestimate the confidence intervals and thus artificially reduce study weighting resulting in a conservative effect.


If paired continuous or categorical data were not available from the crossover studies, the separate group data were analysed in the same way as data from parallel groups, on the basis that this approach would overestimate the confidence intervals and thus artificially reduce study weighting resulting in a conservative effect. Where a meta-analysis included a mixture of studies using both paired and parallel group approaches, all data were entered into using the generic inverse variance function. 4.3.3.2 Data synthesis for diagnostic test accuracy reviews Two separate review protocols were produced to reflect the 2 different diagnostic study designs. 4.3.3.2.1 Diagnostic RCTs Diagnostic RCTs (sometimes referred to as test and treat trials) are a randomised comparison of 2 diagnostic tests, with study outcomes being clinically important consequences of the diagnosis (patient-related outcome measures similar to those in intervention trials, such as mortality). Patients are randomised to receive test A or test B, followed by identical therapeutic interventions based on the results of the test (so someone with a positive result would receive the same treatment regardless of whether they were diagnosed by test A or test B). Downstream patient outcomes are then compared between the 2 groups. As treatment is the same in both arms of the trial, any differences in patient outcomes will reflect the accuracy of the tests in correctly establishing who does and does not have the condition. Data were synthesised using the same methods for intervention reviews (see section 4.3.3.1 above). 4.3.3.2.2 Diagnostic accuracy studies For diagnostic test accuracy studies, a positive result on the index test was found if the patient had values of the measured quantity above or below a threshold value, and different thresholds could be used.


4.3.3.2.2 Diagnostic accuracy studies For diagnostic test accuracy studies, a positive result on the index test was found if the patient had values of the measured quantity above or below a threshold value, and different thresholds could be used. The thresholds were prespecified by the committee including whether or not data could be pooled across a range of thresholds. Diagnostic test accuracy measures used in the analysis were: area under the receiver operating characteristics (ROC) curve (AUC), and, for different thresholds (if appropriate), sensitivity and specificity. The threshold of a diagnostic test is defined as the value at which the test can best differentiate between those with and without the target condition. In practice this varies amongst studies. If a test has a high sensitivity then very few people with the condition will be missed (few false negatives). For example, a test with a sensitivity of 97% will only miss 3% of people with the condition. Conversely, if a test has a high specificity then few people without the condition would be incorrectly diagnosed (few false positives). For example, a test with a specificity of 97% will only incorrectly diagnose 3% of people who do not have the condition as positive. For this guideline, sensitivity or specificity was considered more important depending on the test threshold value being considered. For example at standard diagnostic thresholds of BNP and NT-proBNP sensitivity was prioritised as failing to diagnose people who have heart failure may delay the initiation of treatment and increase the risk of unplanned hospitalisations and mortality. While at much higher rule-in thresholds specificity was prioritised as minimising false positives is more important in this context.


While at much higher rule-in thresholds specificity was prioritised as minimising false positives is more important in this context. Coupled forest plots of sensitivity and specificity with their 95% CIs across studies (at various thresholds) were produced for each test, using RevMan5.283 In order to do this, 2 2 tables (the number of true positives, false positives, true negatives and false negatives) were directly taken from the study if given, or else were derived from raw data or calculated from the set of test accuracy statistics. Diagnostic meta-analysis was conducted where appropriate, that is, when 3 or more studies were available per threshold. Test accuracy for the studies was pooled using the bivariate method for the direct estimation of summary sensitivity and specificity using a random-effects approach in WinBUGS Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 The advantage of this approach is that it produces summary estimates of sensitivity and specificity that account for the correlation between the 2 statistics. Other advantages of this method The bivariate method uses logistic regression on the true positives, true negatives, false positives and false negatives reported in the studies. Overall sensitivity and specificity and confidence regions were plotted (using methods outlined by Novielli 2010.284 ) Pooled sensitivity and specificity and their 95% CIs were reported in the clinical evidence summary tables. For scores with fewer than 3 studies, each study s sensitivity and the paired specificity were reported where possible. Heterogeneity or inconsistency amongst studies was visually inspected in the forest plots and pooled diagnostic meta-analysis plots. The following criteria were used for evaluating AUCs: 0.50: worse than chance 0.50 0.60: very poor 0.61 0.70: poor 0.71 0.80: moderate 0.81 0.90: good 0.91 1.00: excellent or perfect test.


The following criteria were used for evaluating AUCs: 0.50: worse than chance 0.50 0.60: very poor 0.61 0.70: poor 0.71 0.80: moderate 0.81 0.90: good 0.91 1.00: excellent or perfect test. 4.3.3.3 Data synthesis for risk prediction rules Evidence reviews on risk prediction rules or risk prediction tool results were presented separately for discrimination and calibration. The discrimination data were analysed according to the principles of data synthesis for diagnostic accuracy studies as outlined in section 4.3.3.2.2. Calibration data such as ),if reported,were presented separately to the discrimination data. The results were presented for each study separately along with the quality rating for the study and modified GRADE assessment. 4.3.3.4 Data synthesis for qualitative study reviews The main findings for each included paper were identified and thematic analysis methods were used to synthesise this information into broad overarching themes which were summarised into the main review findings. The evidence was presented in the form of a narrative summary detailing the evidence from the relevant papers and how this informed the overall review finding plus a statement on the level of confidence for that review finding. Considerable limitations and issues around relevance were listed. A summary evidence table with the succinct summary statements for each review finding was produced including the associated quality assessment. 4.3.4 Appraising the quality of evidence by outcomes 4.3.4.1 Intervention reviews The evidence for outcomes from the included RCTs and, where appropriate, non-randomised intervention studies, were evaluated and presented using an adaptation of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) toolbox developed by the international GRADE working group (http://www.gradeworkinggroup.org/). The software ) developed by the GRADE working group was used to assess the quality of each outcome, taking into account individual study quality and the meta-analysis results.


The software ) developed by the GRADE working group was used to assess the quality of each outcome, taking into account individual study quality and the meta-analysis results. Each outcome was first examined for each of the quality elements listed and defined in Table 2. Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Table 2: Description of quality elements in GRADE for intervention studies Quality element Description Risk of bias Limitations in the study design and implementation may bias the estimates of the treatment effect. Major limitations in studies decrease the confidence in the estimate of the effect. Examples of such limitations are selection bias (often due to poor allocation concealment), performance and detection bias (often due to a lack of blinding of the patient, healthcare professional or assessor) and attrition bias (due to missing data causing systematic bias in the analysis). Indirectness Indirectness refers to differences in study population, intervention, comparator and outcomes between the available evidence and the review question. Inconsistency Inconsistency refers to an unexplained heterogeneity of effect estimates between studies in the same meta-analysis. Imprecision Results are imprecise when studies include relatively few patients and few events (or highly variable measures) and thus have wide confidence intervals around the estimate of the effect relative to clinically important thresholds. 95% confidence intervals denote the possible range of locations of the true population effect at a 95% probability, and so wide confidence intervals may denote a result that is consistent with conflicting interpretations (for example a result may be consistent with both clinical benefit AND clinical harm) and thus be imprecise. Publication bias Publication bias is a systematic underestimate or overestimate of the underlying beneficial or harmful effect due to the selective publication of studies.


Publication bias Publication bias is a systematic underestimate or overestimate of the underlying beneficial or harmful effect due to the selective publication of studies. A closely related phenomenon is where some papers fail to report an outcome that is inconclusive, thus leading to an overestimate of the effectiveness of that outcome. Other issues Sometimes randomisation may not adequately lead to group equivalence of confounders, and if so this may lead to bias, which should be taken into account. Potential conflicts of interest, often caused by excessive pharmaceutical company involvement in the publication of a study, should also be noted. Details of how the 4 main quality elements (risk of bias, indirectness, inconsistency and imprecision) were appraised for each outcome are given below. Publication or other bias was only taken into consideration in the quality assessment if it was apparent. 4.3.4.1.1 Risk of bias The main domains of bias for RCTs are listed in Table 3. Each outcome had its risk of bias assessed within each study first. For each study, if there were no risks of bias in any domain, the risk of bias was given a rating of 0. If there was risk of bias in just 1 domain, the risk of bias was given a serious rating of 1, but if there was risk of bias in 2 or more domains the risk of bias was given a very serious rating of 2. A weighted average score was then calculated across all studies contributing to the outcome, by taking into account the weighting of studies according to study precision. For example if the most precise studies tended to each have a score of 1 for that outcome, the overall score for that outcome would tend towards 1.


For example if the most precise studies tended to each have a score of 1 for that outcome, the overall score for that outcome would tend towards 1. Table 3: Principle domains of bias in randomised controlled trials Limitation Explanation Selection bias (sequence generation and allocation concealment) If those enrolling patients are aware of the group to which the next enrolled patient will be allocated, either because of a non-random sequence that is predictable, or because a truly random sequence was not concealed from the researcher, this may translate into systematic selection bias. This may occur if the researcher chooses not to recruit a participant into that specific group because of: knowledge of that participant s likely prognostic characteristics, and a desire for one group to do better than the other. Performance and Patients, caregivers, those adjudicating or recording outcomes, and data analysts Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Limitation Explanation detection bias (lack of blinding of patients and healthcare professionals) should not be aware of the arm to which patients are allocated. Knowledge of the group can influence: the experience of the placebo effect performance in outcome measures the level of care and attention received, and the methods of measurement or analysis all of which can contribute to systematic bias. Attrition bias Attrition bias results from an unaccounted for loss of data beyond a certain level (a differential of 10% between groups). Loss of data can occur when participants are compulsorily withdrawn from a group by the researchers (for example, when a per- protocol approach is used) or when participants do not attend assessment sessions.


Loss of data can occur when participants are compulsorily withdrawn from a group by the researchers (for example, when a per- protocol approach is used) or when participants do not attend assessment sessions. If the missing data are likely to be different from the data of those remaining in the groups, and there is a differential rate of such missing data from groups, systematic attrition bias may result. Selective outcome reporting Reporting of some outcomes and not others on the basis of the results can also lead to bias, as this may distort the overall impression of efficacy. Other limitations For example: Stopping early for benefit observed in randomised trials, in particular in the absence of adequate stopping rules. Use of unvalidated patient-reported outcome measures. Lack of washout periods to avoid carry-over effects in crossover trials. Recruitment bias in cluster-randomised trials. Indirectness refers to the extent to which the populations, interventions, comparisons and outcome measures are dissimilar to those defined in the inclusion criteria for the reviews. Indirectness is important when these differences are expected to contribute to a difference in effect size, or may affect the balance of harms and benefits considered for an intervention. As for the risk of bias, each outcome had its indirectness assessed within each study first. For each study, if there were no sources of indirectness, indirectness was given a rating of 0. If there was indirectness in just 1 source (for example in terms of population), indirectness was given a serious rating of 1, but if there was indirectness in 2 or more sources (for example, in terms of population and treatment) the indirectness was given a very serious rating of 2. A weighted average score was then calculated across all studies contributing to the outcome by taking into account study precision.


A weighted average score was then calculated across all studies contributing to the outcome by taking into account study precision. For example, if the most precise studies tended to have an indirectness score of 1 each for that outcome, the overall score for that outcome would tend towards 1. Inconsistency refers to an unexplained heterogeneity of results for an outcome across different studies. When estimates of the treatment effect across studies differ widely, this suggests true differences in the underlying treatment effect, which may be due to differences in populations, settings or doses. When heterogeneity existed within an outcome (chi-squared p<0.1, or I2 no plausible explanation could be found, the quality of evidence for that outcome was downgraded. Inconsistency for that outcome was given a serious score of 1 if the I2 was 50 74%, and a very serious score of 2 if the I2 was 75% or more. If inconsistency could be explained based on prespecified subgroup analysis (that is, each subgroup had an I2 <50%), the committee took this into account and considered whether to make separate recommendations on new outcomes based on the subgroups defined by the assumed explanatory Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 factors. In such a situation the quality of evidence was not downgraded for those emergent outcomes. Since the inconsistency score was based on the meta-analysis results, the score represented the whole outcome and so weighted averaging across studies was not necessary. The criteria applied for imprecision were based on the 95% CIs for the pooled estimate of effect, and the minimal important differences (MID) for the outcome.


The criteria applied for imprecision were based on the 95% CIs for the pooled estimate of effect, and the minimal important differences (MID) for the outcome. The MIDs are the threshold for appreciable benefits and harms, separated by a zone either side of the line of no effect where there is assumed to be no clinically important effect. If either end of the 95% CI of the overall estimate of effect crossed 1 of the MID lines, imprecision was regarded as serious and a serious score of 1 was given. This was because the overall result, as represented by the span of the confidence interval, was consistent with 2 interpretations as defined by the MID (for example, both no clinically important effect and clinical benefit were possible interpretations). If both MID lines were crossed by either or both ends of the 95% CI then imprecision was regarded as very serious and a very serious score of 2 was given. This was because the overall result was consistent with all 3 interpretations defined by the MID (no clinically important effect, clinical benefit and clinical harm). This is illustrated in Figure 4. As for inconsistency, since the imprecision score was based on the meta-analysis results, the score represented the whole outcome and so weighted averaging across studies was not necessary. The position of the MID lines is ideally determined by values reported in the literature. Anchor- based methods aim to establish clinically meaningful changes in a continuous outcome variable by relating or anchoring them to patient-centred measures of clinical effectiveness that could be regarded as gold standards with a high level of face validity.


Anchor- based methods aim to establish clinically meaningful changes in a continuous outcome variable by relating or anchoring them to patient-centred measures of clinical effectiveness that could be regarded as gold standards with a high level of face validity. For example, a MID for an outcome could be defined by the minimum amount of change in that outcome necessary to make patients feel their quality of life had significantly improved . MIDs in the literature may also be based on expert clinician or consensus opinion concerning the minimum amount of change in a variable deemed to affect quality of life or health. For binary variables, any MIDs reported in the literature will inevitably be based on expert consensus, as such MIDs relate to all-or-nothing population effects rather than measurable effects on an individual, and so are not amenable to patient-centred anchor methods. The GC agreed to use these published values for quality of life scores: EQ-5D 0.03 (from Sf-36 mapping),Kansas City 5 (taken from literature) and SF-36 5 (taken from literature). The GC did not support the use of other MIDs as the measures were perceived as unreliable. The GC agreed that it was appropriate to use a reduction of 10 unplanned hospitilisation per 1000 as a clinically important benefit. In the absence of values identified in the literature, the alternative approach to deciding on MID levels is the default method, as follows: For categorical outcomes the MIDs were taken to be RRs of 0.75 and 1.25. For positive outcomes such as patient satisfaction , the RR of 0.75 is taken as the line denoting the boundary between no clinically important effect and a clinically significant harm, whilst the RR of 1.25 is taken as the line denoting the boundary between no clinically important effect and a clinically significant benefit.


For positive outcomes such as patient satisfaction , the RR of 0.75 is taken as the line denoting the boundary between no clinically important effect and a clinically significant harm, whilst the RR of 1.25 is taken as the line denoting the boundary between no clinically important effect and a clinically significant benefit. For negative outcomes such as bleeding , the opposite occurs, so the RR of 0.75 is taken as the line denoting the boundary between no clinically important effect and a clinically significant benefit, whilst the RR of 1.25 is taken as the line denoting the boundary between no clinically important effect and a clinically significant harm. For mortality any change was considered to be clinically important and the imprecision was assessed on the basis of the whether the confidence intervals crossed the line of no effect, that is whether the result was consistent with both benefit and harm. For continuous outcome variables the MID was taken as half the median baseline standard deviation of that variable, across all studies in the meta-analysis. Hence the MID denoting the Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 minimum clinically significant benefit was positive for a positive outcome (for example, a quality of life measure where a higher score denotes better health), and negative for a negative outcome (for example, a visual analogue scale [VAS] pain score). Clinically significant harms will be the converse of these. If baseline values are unavailable, then half the median comparator group standard deviation of that variable will be taken as the MID. If standardised mean differences have been used, then the MID will be set at the absolute value of +0.5.


If standardised mean differences have been used, then the MID will be set at the absolute value of +0.5. This follows because standardised mean differences are mean differences normalised to the pooled standard deviation of the 2 groups, and are thus effectively expressed in units of numbers of standard deviations . The 0.5 MID value in this context therefore indicates half a standard deviation, the same definition of MID as used for non-standardised mean differences. The default MID value was subject to amendment after discussion with the committee. If the committee decided that the MID level should be altered, after consideration of absolute as well as relative effects, this was allowed, provided that any such decision was not influenced by any bias towards making stronger or weaker recommendations for specific outcomes. Figure 4: Illustration of precise and imprecise outcomes based on the 95% CI of dichotomous outcomes in a forest plot (Note that all 3 results would be pooled estimates, and would not, in practice, be placed on the same forest plot) 4.3.4.1.5 Overall grading of the quality of clinical evidence Once an outcome had been appraised for the main quality elements, as above, an overall quality grade was calculated for that outcome. The scores (0, 1 or 2) from each of the main quality elements were summed to give a score that could be anything from 0 (the best possible) to 8 (the worst possible). However scores were capped at 3. This final score was then applied to the starting grade that had originally been applied to the outcome by default, based on study design. All RCTs started as High and the overall quality became Moderate, Low or Very Low if the overall score was 1, 2 or 3 points respectively.


All RCTs started as High and the overall quality became Moderate, Low or Very Low if the overall score was 1, 2 or 3 points respectively. The significance of these overall ratings is explained in Table 4. The reasons for downgrading in each case were specified in the footnotes of the GRADE tables. Non-randomised intervention studies started at Low, and so a score of 1 would be enough to take the grade to the lowest level of Very Low. Non-randomised intervention studies could, however, be upgraded if there was a large magnitude of effect or a dose-response gradient. Table 4: Overall quality of outcome evidence in GRADE Level Description High Further research is very unlikely to change our confidence in the estimate of effect Moderate Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate Low Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate Very low Any estimate of effect is very uncertain 4.3.4.2 Prognostic reviews Risk of bias and applicability of evidence for prognostic risk data were evaluated per study using the Prediction study Risk of Bias Assessment Tool (PROBAST) draft checklist. Risk of bias and applicability were evaluated using of these 5 domains: Patient selection o appropriate data sources, inclusion and exclusion criteria and comparability of baseline values in the participants Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights.


Risk of bias and applicability were evaluated using of these 5 domains: Patient selection o appropriate data sources, inclusion and exclusion criteria and comparability of baseline values in the participants Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Predictors o Defined and assessed same way for all participants, blinding to outcome data,all relevant predictors analysed Outcome o Pre specified definition, predictors excluded from the outcome definition, outcome defined and determined in a similar way for all participants, blinding to predictor information Sample size and participant flow o Adequate number of outcome events, time interval between predictor assessment and outcome , appropriate missing data handling Analysis o non-binary predictors handled appropriately, univariable analysis avoided, model overfitting accounted for, complexities in the data (e.g. competing risks,) accounted for, assigned weights to predictors match the results from multivariable analysis, relevant performance measures are evaluated, e.g. calibration, discrimination, recalibrated if needed If data were meta-analysed, the quality for pooled studies was presented. If the data were not pooled, then the quality rating was presented for each study. Inconsistency was assessed as for intervention studies. Imprecision was assessed according to the range of point estimates of the primary measure. The evidence was downgraded by 1 increment when there was more than 20% range of the confidence interval around the point estimate and downgraded by 2 increments when there was a range of more than 40%. Imprecision was not estimable where studies did not report confidence intervals. 4.3.4.2.3 Overall grading Quality rating started at High for prospective and retrospective studies, and each major limitation brought the rating down by 1 increment to a minimum grade of Very Low, as explained for interventional reviews.


4.3.4.2.3 Overall grading Quality rating started at High for prospective and retrospective studies, and each major limitation brought the rating down by 1 increment to a minimum grade of Very Low, as explained for interventional reviews. 4.3.4.3 Diagnostic studies Risk of bias and indirectness of evidence for diagnostic data were evaluated by study using the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) checklists (see appendix H in the NICE guidelines manual 2014236 ). Risk of bias and applicability in primary diagnostic accuracy studies in QUADAS-2 consists of 4 domains (see Table 5: Summary of QUADAS-2 with list of signalling, risk of bias and applicability questions.): patient selection index test reference standard flow and timing. Table 5: Summary of QUADAS-2 with list of signalling, risk of bias and applicability questions. Domain Patient selection Index test Reference standard Flow and timing Description Describe methods Describe the index Describe the Describe any patients Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Domain Patient selection Index test Reference standard Flow and timing of patient selection. Describe included patients (prior testing, presentation, intended use of index test and setting) test and how it was conducted and interpreted reference standard and how it was conducted and interpreted who did not receive the index test(s) and/or reference standard or who were excluded from the 2 2 table (refer to flow diagram). Describe the time interval and any interventions between index test(s) and reference standard Signalling questions (yes/no/ unclear) Was a consecutive or random sample of patients enrolled? Were the index test results interpreted without knowledge of the results of the reference standard? Is the reference standard likely to correctly classify the target condition? Was there an appropriate interval between index test(s) and reference standard?


Was there an appropriate interval between index test(s) and reference standard? Was a case control design avoided? If a threshold was used, was it pre- specified? Were the reference standard results interpreted without knowledge of the results of the index test? Did all patients receive a reference standard? Did the study avoid inappropriate exclusions? Did all patients receive the same reference standard? Were all patients included in the analysis? Risk of bias; (high/low/ unclear) Could the selection of patients have introduced bias? Could the conduct or interpretation of the index test have introduced bias? Could the reference standard, its conduct or its interpretation have introduced bias? Could the patient flow have introduced bias? Concerns regarding applicability (high/low/ unclear) Are there concerns that the included patients do not match the review question? Are there concerns that the index test, its conduct, or interpretation differ from the review question? Are there concerns that the target condition as defined by the reference standard does not match the review question? Inconsistency refers to an unexplained heterogeneity of results for an outcome across different studies. Inconsistency was assessed by inspection of the sensitivity and specificity (based on the primary measure) using the point estimates and 95% CIs of the individual studies on the forest plots. Particular attention was placed on values above or below 50% (diagnosis based on chance alone) and the threshold set by the committee (the threshold above which it would be acceptable to recommend a test). For example, the committee might have set a threshold of 90% as an acceptable level to recommend a test.


For example, the committee might have set a threshold of 90% as an acceptable level to recommend a test. The evidence was downgraded by 1 increment if the individual studies varied across 2 areas [(for example, 50 90% and 90 100%)] and by 2 increments if the individual studies varied across 3 areas [(for example, 0 50%, 50 90% and 90 100%)]. The judgement of precision was based on visual inspection of the confidence region around the summary sensitivity and specificity point from the diagnostic meta-analysis, if a diagnostic meta- analysis was conducted. Where a diagnostic meta-analysis was not conducted, imprecision was assessed according to the range of point estimates or, if only one study contributed to the evidence, Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 the 95% CI around the single study. As a general rule (after discussion with the committee) a variation of 0 20% was considered precise, 20 40% serious imprecision, and >40% very serious imprecision. Imprecision was assessed on the primary outcome measure for decision-making. 4.3.4.3.3 Overall grading Quality rating started at High for prospective and retrospective cross-sectional studies, and each major limitation (risk of bias, indirectness, inconsistency and imprecision) brought the rating down by 1 increment to a minimum grade of Very Low, as explained for intervention reviews. 4.3.4.4 Qualitative reviews Review findings from the included qualitative studies were evaluated and presented using the Confidence in the Evidence from Reviews of Qualitative Research (CERQual) Approach developed by the GRADE-CERQual Project Group, a subgroup of the GRADE Working Group. The CERQual Approach assesses the extent to which a review finding is a reasonable representation of the phenomenon of interest (the focus of the review question).


The CERQual Approach assesses the extent to which a review finding is a reasonable representation of the phenomenon of interest (the focus of the review question). Each review finding was assessed for each of the 4 quality elements listed and defined below in Table 6. Table 6: Description of quality elements in GRADE-CERQual for qualitative studies Quality element Description Methodological limitations The extent of problems in the design or conduct of the included studies that could decrease the confidence that the review finding is a reasonable representation of the phenomenon of interest. Assessed at the study level using an NGC checklist. Coherence The extent to which the reviewer is able to identify a clear pattern across the studies included in the review. Relevance The extent to which the body of evidence from the included studies is applicable to the context (study population, phenomenon of interest, setting) specified in the protocol. Adequacy The degree of the confidence that the review finding is being supported by sufficient data. This is an overall determination of the richness (depth of analysis) and quantity of the evidence supporting a review finding or theme. Details of how the 4 quality elements (methodological limitations, coherence, relevance and adequacy) were appraised for each review finding are given below. 4.3.4.4.1 Methodological limitations Each review finding had its methodological limitations assessed within each study first using an NGC checklist. Based on the degree of methodological limitations studies were evaluated as having minor, moderate or severe limitations. The questions to be answered in the checklist below included: Was qualitative design an appropriate approach? Was the study approved by an ethics committee? Was the study clear in what it sought to do? Is the context clearly described? Is the role of the researcher clearly described? Are the research design and methods rigorous?


Is the role of the researcher clearly described? Are the research design and methods rigorous? Was the data collection rigorous? Was the data analysis rigorous? Are the data rich? Are the findings relevant to the aims of the study? Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Are the findings and conclusions convincing? The overall assessment of the methodological limitations of the evidence was based on the primary studies contributing to the review finding. The relative contribution of each study to the overall review finding and of the type of methodological limitation(s) were taken into account when giving an overall rating. Coherence is the extent to which the reviewer is able to identify a clear pattern across the studies included in the review, and if there is variation present (contrasting or disconfirming data) whether this variation is explained by the contributing study authors. If a review finding in 1 study does not support the main finding and there is no plausible explanation for this variation, then the confidence that the main finding reasonably reflects the phenomenon of interest is decreased. Each review finding was given a rating of minor, moderate or major concerns about coherence. Relevance is the extent to which the body of evidence from the included studies is applicable to the context (study population, phenomenon of interest, setting) specified in the protocol. As such, relevance is dependent on the individual review and discussed with the guideline committee. Relevance is categorised in 3 ways: partial relevance, indirect relevance and no concerns about relevance. The judgement of adequacy is based on the confidence of the finding being supported by sufficient data.


The judgement of adequacy is based on the confidence of the finding being supported by sufficient data. This is an overall determination of the richness (depth of analysis) and quantity of the evidence supporting a review finding or theme. Rich data provide sufficient detail to gain an understanding of the theme or review finding, whereas thin data do not provide enough detail for an adequate understanding. Quantity of data is the second pillar of the assessment of adequacy. For review findings that are only supported by 1 study or data from only a small number of participants, the confidence that the review finding reasonable represents the phenomenon of interest might be decreased. As with richness of data, quantity of data is review dependent. Based on the overall judgement of adequacy, a rating of no concerns, minor concerns, or substantial concerns about adequacy was given. 4.3.4.4.5 Overall judgement of the level of confidence for a review finding GRADE-CERQual is used to assess the body of evidence as a whole through a confidence rating representing the extent to which a review finding is a reasonable representation of the phenomenon of interest. The 4 components (methodological limitations, coherence, relevance and adequacy) are used in combination to form an overall judgement. GRADE-CERQual uses 4 levels of confidence: high, moderate, low and very low confidence. The significance of these overall ratings is explained in Table 7: Overall level of confidence for a review finding in GRADE-CERQual. Each review finding starts at a high level of confidence and is downgraded based on the concerns identified in any 1 or more of the 4 components. Quality assessment of qualitative reviews is a subjective judgement by the reviewer based on the concerns that have been noted.


Quality assessment of qualitative reviews is a subjective judgement by the reviewer based on the concerns that have been noted. A detailed explanation of how such a judgement had been made was included in the narrative summary. Table 7: Overall level of confidence for a review finding in GRADE-CERQual Level Description High confidence It is highly likely that the review finding is a reasonable representation of the phenomenon of interest. Moderate It is likely that the review finding is a reasonable representation of the phenomenon of Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Level Description confidence interest. Low confidence It is possible that the review finding is a reasonable representation of the phenomenon of interest. Very low confidence It is not clear whether the review finding is a reasonable representation of the phenomenon of interest. 4.3.5 Publication bias Funnel plots were constructed using RevMan5(RevMan5283 software to assess against potential publication bias for outcomes containing more than 5 studies in intervention reviews (appendix F). This was taken into consideration when assessing the quality of the evidence. 4.3.6 Assessing clinical importance The committee assessed the evidence by outcome in order to determine if there was, or potentially was, a clinically important benefit, a clinically important harm or no clinically important difference between interventions. To facilitate this, binary outcomes were converted into absolute risk differences (ARDs) using GRADEpro138 software: the median control group risk across studies was used to calculate the ARD and its 95% CI from the pooled risk ratio. The assessment of clinical benefit, harm, or no benefit or harm was based on the point estimate of absolute effect for intervention studies, which was standardised across the reviews.


The assessment of clinical benefit, harm, or no benefit or harm was based on the point estimate of absolute effect for intervention studies, which was standardised across the reviews. The committee considered for most of the outcomes in the intervention reviews that if at least 100 more participants per 1000 (10%) achieved the outcome of interest in the intervention group compared to the comparison group for a positive outcome then this intervention was considered beneficial. The same point estimate but in the opposite direction applied for a negative outcome. For the critical outcome of mortality any reduction represented a clinical benefit. For adverse events 50 events or more per 1000 (5%) represented clinical harm. For continuous outcomes if the mean difference was greater than the minimally important difference (MID) then this resented a clinical benefit or harm. For outcomes such as mortality any reduction or increase was considered to be clinically important. This assessment was carried out by the committee for each critical outcome, and an evidence summary table was produced to compile the committee s assessments of clinical importance per outcome, alongside the evidence quality and the uncertainty in the effect estimate (imprecision). 4.3.7 Clinical evidence statements Clinical evidence statements are summary statements that are included in each review chapter, and which summarise the key features of the clinical effectiveness evidence presented. The wording of the evidence statements reflects the certainty or uncertainty in the estimate of effect. The evidence statements are presented by outcome and encompass the following key features of the evidence: The number of studies and the number of participants for a particular outcome. An indication of the direction of clinical importance (if one treatment is beneficial or harmful compared to the other, or whether there is no difference between the 2 tested treatments).


An indication of the direction of clinical importance (if one treatment is beneficial or harmful compared to the other, or whether there is no difference between the 2 tested treatments). A description of the overall quality of the evidence (GRADE overall quality). 4.3.8 Appendix D-Practical notes The 2010 guideline included practical recommendations which covered aspects of clinical management that were not included in the evidence reviewed but which the committee considered important. In updating the guideline the committee reviewed the information included within this Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 appendix and agreed that where appropriate these practical notes should be absorbed into the treatment and monitoring recommendations. 4.4 Identifying and analysing evidence of cost effectiveness The committee is required to make decisions based on the best available evidence of both clinical effectiveness and cost effectiveness. Guideline recommendations should be based on the expected costs of the different options in relation to their expected health benefits (that is, their cost effectiveness ) rather than the total implementation cost. However, the committee will also need to be increasingly confident in the cost effectiveness of a recommendation as the cost of implementation increases. Therefore, the committee may require more robust evidence on the effectiveness and cost effectiveness of any recommendations that are expected to have a substantial impact on resources; any uncertainties must be offset by a compelling argument in favour of the recommendation. The cost impact or savings potential of a recommendation should not be the sole reason for the committee s decision.236 Health economic evidence was sought relating to the key clinical issues being addressed in the guideline. Health economists: Undertook a systematic review of the published economic literature. Undertook new cost-effectiveness analysis in priority areas.


Health economists: Undertook a systematic review of the published economic literature. Undertook new cost-effectiveness analysis in priority areas. 4.4.1 Literature review The health economists: Identified potentially relevant studies for each review question from the health economic search results by reviewing titles and abstracts. Full papers were then obtained. Reviewed full papers against prespecified inclusion and exclusion criteria to identify relevant studies (see below for details). Critically appraised relevant studies using economic evaluations checklists as specified in the NICE Extracted key information about the studies methods and results into health economic evidence tables (included in appendix G). Generated summaries of the evidence in NICE health economic evidence profile tables (included in the relevant chapter for each review question) see below for details. 4.4.1.1 Inclusion and exclusion criteria Full economic evaluations (studies comparing costs and health consequences of alternative courses of action: cost utility, cost-effectiveness, cost benefit and cost consequences analyses) and comparative costing studies that addressed the review question in the relevant population were considered potentially includable as health economic evidence. Studies that only reported cost per hospital (not per patient), or only reported average cost effectiveness without disaggregated costs and effects were excluded. Literature reviews, abstracts, posters, letters, editorials, comment articles, unpublished studies and studies not in English were excluded. Studies published before 2001 and studies from non-OECD countries or the USA were also excluded, on the basis that the applicability of such studies to the present UK NHS context is likely to be too low for them to be helpful for decision-making. Remaining health economic studies were prioritised for inclusion based on their relative applicability to the development of this guideline and the study limitations. For example, if a high quality, directly Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights.


For example, if a high quality, directly Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 applicable UK analysis was available, then other less relevant studies may not have been included. Where exclusions occurred on this basis, this is noted in the relevant section. For more details about the assessment of applicability and methodological quality see Table 8 below and the economic evaluation checklist (appendix H of the NICE guidelines manual236 ) and the health economics review protocol in appendix B. When no relevant health economic studies were found from the economic literature review, relevant UK NHS unit costs related to the compared interventions were presented to the committee to inform the possible economic implications of the recommendations. 4.4.1.2 NICE health economic evidence profiles NICE health economic evidence profile tables were used to summarise cost and cost-effectiveness estimates for the included health economic studies in each review chapter. The health economic evidence profile shows an assessment of applicability and methodological quality for each economic study, with footnotes indicating the reasons for the assessment. These assessments were made by the health economist using the economic evaluation checklist from the NICE guidelines manual.236 It also shows the incremental costs, incremental effects (for example, quality-adjusted life years [QALYs]) and incremental cost-effectiveness ratio (ICER) for the base case analysis in the study, as well as information about the assessment of uncertainty in the analysis. See Table 8 for more details. When a non-UK study was included in the profile, the results were converted into pounds sterling using the appropriate purchasing power parity.249 Table 8: Content of NICE health economic evidence profile Item Description Study Surname of first author, date of study publication and country perspective with a reference to full information on the study.


When a non-UK study was included in the profile, the results were converted into pounds sterling using the appropriate purchasing power parity.249 Table 8: Content of NICE health economic evidence profile Item Description Study Surname of first author, date of study publication and country perspective with a reference to full information on the study. Applicability An assessment of applicability of the study to this guideline, the current NHS situation and NICE decision-making:(a) Directly applicable the study meets all applicability criteria, or fails to meet 1 or more applicability criteria but this is unlikely to change the conclusions about cost effectiveness. Partially applicable the study fails to meet 1 or more applicability criteria, and this could change the conclusions about cost effectiveness. Not applicable the study fails to meet 1 or more of the applicability criteria, and this is likely to change the conclusions about cost effectiveness. Such studies would usually be excluded from the review. Limitations An assessment of methodological quality of the study:(a) Minor limitations the study meets all quality criteria, or fails to meet 1 or more quality criteria, but this is unlikely to change the conclusions about cost effectiveness. Potentially serious limitations the study fails to meet 1 or more quality criteria, and this could change the conclusions about cost effectiveness. Very serious limitations the study fails to meet 1 or more quality criteria, and this is highly likely to change the conclusions about cost effectiveness. Such studies would usually be excluded from the review. Other comments Information about the design of the study and particular issues that should be considered when interpreting it. Incremental cost The mean cost associated with one strategy minus the mean cost of a comparator strategy.


Incremental cost The mean cost associated with one strategy minus the mean cost of a comparator strategy. Incremental effects The mean QALYs (or other selected measure of health outcome) associated with Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Item Description one strategy minus the mean QALYs of a comparator strategy. Cost effectiveness Incremental cost-effectiveness ratio (ICER): the incremental cost divided by the incremental effects (usually in per QALY gained). Uncertainty A summary of the extent of uncertainty about the ICER reflecting the results of deterministic or probabilistic sensitivity analyses, or stochastic analyses of trial data, as appropriate. (a) Applicability and limitations were assessed using the economic evaluation checklist in appendix H of the NICE guidelines 4.4.2 Undertaking new health economic analysis As well as reviewing the published health economic literature for each review question, as described above, new health economic analysis was undertaken by the health economist in selected areas. Priority areas for new analysis were agreed by the committee after formation of the review questions and consideration of the existing health economic evidence. The committee identified determining a natriuretic peptide threshold for referral for echocardiography as the highest priority area for original health economic modelling. This was due to concerns that the current natriuretic peptide thresholds may be too high, resulting in delayed diagnosis, whilst also acknowledging that there could be significant increase in cost if the threshold were to be lowered and more patients were referred for echocardiography. The following general principles were adhered to in developing the cost-effectiveness analysis: Methods were consistent with the NICE reference case for interventions with health outcomes in The committee was involved in the design of the model, selection of inputs and interpretation of the results.


The following general principles were adhered to in developing the cost-effectiveness analysis: Methods were consistent with the NICE reference case for interventions with health outcomes in The committee was involved in the design of the model, selection of inputs and interpretation of the results. Model inputs were based on the systematic review of the clinical literature supplemented with other published data sources where possible. When published data were not available committee expert opinion was used to populate the model. Model inputs and assumptions were reported fully and transparently. The results were subject to sensitivity analysis and limitations were discussed. The model was peer-reviewed by another health economist at the NGC. The model methods were also peer-reviewed by Professor Martin Cowie because of his expertise in heart failure, knowledge of the literature and health economic modelling methodologies. Full methods for the cost-effectiveness analysis of natriuretic peptide thresholds are described in appendix O. 4.4.3 Cost-effectiveness criteria NICE s report Social value judgements: principles for the development of NICE guidance sets out the principles that committees should consider when judging whether an intervention offers good value In general, an intervention was considered to be cost effective (given that the estimate was considered plausible) if either of the following criteria applied: the intervention dominated other relevant strategies (that is, it was both less costly in terms of resource use and more clinically effective compared with all the other relevant alternative strategies), or the intervention cost less than 20,000 per QALY gained compared with the next best strategy. Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights.


Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 If the committee recommended an intervention that was estimated to cost more than 20,000 per QALY gained, or did not recommend one that was estimated to cost less than 20,000 per QALY gained, the reasons for this decision are discussed explicitly in the Recommendations and link to evidence section of the relevant chapter, with reference to issues regarding the plausibility of the estimate or to the factors set out in Social value judgements: principles for the development of NICE When QALYs or life years gained are not used in the analysis, results are difficult to interpret unless one strategy dominates the others with respect to every relevant health outcome and cost. 4.4.4 In the absence of health economic evidence When no relevant published health economic studies were found, and a new analysis was not prioritised, the committee made a qualitative judgement about cost effectiveness by considering expected differences in resource use between options and relevant UK NHS unit costs, alongside the results of the review of clinical effectiveness evidence. The UK NHS costs reported in the guideline are those that were presented to the committee and were correct at the time recommendations were drafted. They may have changed subsequently before the time of publication. However, we have no reason to believe they have changed substantially. 4.5 Developing recommendations Over the course of the guideline development process, the committee was presented with: Evidence tables of the clinical and health economic evidence reviewed from the literature. All evidence tables are in appendices F and G. Summaries of clinical and health economic evidence and quality (as presented in chapters 5-10). Forest plots and summary ROC curves (appendix E).


All evidence tables are in appendices F and G. Summaries of clinical and health economic evidence and quality (as presented in chapters 5-10). Forest plots and summary ROC curves (appendix E). A description of the methods and results of the cost-effectiveness analyses undertaken for the guideline (appendix O). Recommendations were drafted on the basis of the committee s interpretation of the available evidence, taking into account the balance of benefits, harms and costs between different courses of action. This was either done formally in an economic model, or informally. Firstly, the net clinical benefit over harm (clinical effectiveness) was considered, focusing on the critical outcomes. When this was done informally, the committee took into account the clinical benefits and harms when one intervention was compared with another. The assessment of net clinical benefit was moderated by the importance placed on the outcomes (the committee s values and preferences), and the confidence the committee had in the evidence (evidence quality). Secondly, the committee assessed whether the net clinical benefit justified any differences in costs between the alternative interventions. When clinical and health economic evidence was of poor quality, conflicting or absent, the committee drafted recommendations based on its expert opinion. The considerations for making consensus-based recommendations include the balance between potential harms and benefits, the economic costs compared to the economic benefits, current practices, recommendations made in other relevant guidelines, patient preferences and equality issues. The consensus recommendations were agreed through discussions in the committee. The committee also considered whether the uncertainty was sufficient to justify delaying making a recommendation to await further research, taking into account the potential harm of failing to make a clear recommendation (see section 4.5.1 below). Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights.


Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 The committee considered the appropriate strength of each recommendation. This takes into account the quality of the evidence but is conceptually different. Some recommendations are strong in that the committee believes that the vast majority of healthcare and other professionals and patients would choose a particular intervention if they considered the evidence in the same way that the committee has. This is generally the case if the benefits clearly outweigh the harms for most people and the intervention is likely to be cost effective. However, there is often a closer balance between benefits and harms, and some patients would not choose an intervention whereas others would. This may happen, for example, if some patients are particularly averse to some side effect and others are not. In these circumstances the recommendation is generally weaker, although it may be possible to make stronger recommendations about specific groups of patients. The committee focused on the following factors in agreeing the wording of the recommendations: The actions health professionals need to take. The information readers need to know. The strength of the recommendation (for example the word offer was used for strong recommendations and consider for weaker recommendations). The involvement of patients (and their carers if needed) in decisions on treatment and care. Consistency with NICE s standard advice on recommendations about drugs, waiting times and ineffective interventions (see section 9.2 in the NICE guidelines manual236 ). The main considerations specific to each recommendation are outlined in the Recommendations and link to evidence sections within each chapter. 4.5.1 Research recommendations When areas were identified for which good evidence was lacking, the committee considered making recommendations for future research.


4.5.1 Research recommendations When areas were identified for which good evidence was lacking, the committee considered making recommendations for future research. Decisions about the inclusion of a research recommendation were based on factors such as: the importance to patients or the population national priorities potential impact on the NHS and future NICE guidance ethical and technical feasibility. 4.5.2 Validation process This guidance is subject to a 6-week public consultation and feedback as part of the quality assurance and peer review of the document. All comments received from registered stakeholders are responded to in turn and posted on the NICE website. 4.5.3 Updating the guideline Following publication, and in accordance with the NICE guidelines manual, NICE will undertake a review of whether the evidence base has progressed significantly to alter the guideline recommendations and warrant an update. Healthcare providers need to use clinical judgement, knowledge and expertise when deciding whether it is appropriate to apply guidelines. The recommendations cited here are a guide and may not be appropriate for use in all situations. The decision to adopt any of the recommendations cited Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 here must be made by practitioners in light of individual patient circumstances, the wishes of the patient, clinical expertise and resources. The National Guideline Centre disclaims any responsibility for damages arising out of the use or non- use of this guideline and the literature used in support of this guideline. The National Guideline Centre was commissioned by the National Institute for Health and Care Excellence to undertake the work on this guideline. Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights.


Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 5 Diagnosing heart failure The update to the heart failure guideline includes topics where new evidence has emerged since the publication in 2010. A review of new evidence published after 2010 was carried out in order to determine whether any changes to current recommendations where likely to be required. The decision on which topics to include in the update of the guideline was made following consultation of the scope. The following topics were not within the scope of the update. For more information refer to the 2010 Guideline: Symptoms, signs and investigation. Natriuretic peptides versus echocardiography See section 5.1 and 5.5 of 2010 guideline (Appendix R). 5.1 BNP and NT-proBNP in diagnosing heart failure The diagnosis of heart failure can be challenging because of the frequent overlap of the symptoms of breathlessness and fluid retention with other conditions, because the patient may already have a condition that produces similar symptoms, for example chronic obstructive pulmonary disease, and because the presence of co-morbidities may delay the diagnosis of heart failure. Furthermore, the demonstration of a structural or functional cardiac abnormality on imaging may not necessarily be the cause of the presenting symptoms. There is no single diagnostic test for heart failure, and the diagnosis relies on clinical judgement based on a combination of history, physical examination and appropriate investigations. Biomarkers are substances measurable in the blood stream which can be used to diagnose and monitor disease. Natriuretic peptides are released from the myocardium in response to fluid overload. The two main natriuretic peptides used in clinical practice are amino-terminal pro-B-type natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP).


The two main natriuretic peptides used in clinical practice are amino-terminal pro-B-type natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP). The levels of natriuretic peptides correlate with prognosis in patients with heart failure and they may also be useful in patients with some other cardiovascular morbidities. The measurement of natriuretic peptides is recommended for the diagnosis of HF in previous NICE guidance. However, further evidence on the diagnostic efficiency of natriuretic peptides for heart failure in community settings has accumulated since that review, and the underlying prevalences of heart failure with reduced ejection fraction (HFREF) and with preserved ejection fraction (HFREF) are changing. The suggestion has been made that previous diagnostic threshold defined by natriuretic peptide levels may need to be revised. This question reviewed whether the diagnostic process for heart failure by the use of the appropriate combination of clinical signs, echocardiographic imaging and natriuretic peptide levels ought to be changed. Please note that natriuretic peptide levels have been reported in pg/ml throughout this review. However, the recommendations made have been converted to ng/L as this is more commonly recognised in practice (1pg/ml = 1ng/L). 5.1.2 Review question: In people with suspected heart failure, what thresholds of pro-B-type natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) are most accurate in identifying heart failure (as indicated by the reference standard)? For full details see review protocol in appendix A. Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Table 9: Characteristics of review question Population People with suspected heart failure in a community or outpatient setting.


ISBN: 978-1-4731-3093-7 Table 9: Characteristics of review question Population People with suspected heart failure in a community or outpatient setting. Target condition Heart failure Index test(s) NT-proBNP BNP Reference standard(s) A clinical diagnosis based on the opinion of at least one cardiologist, considering symptoms (potentially with some signs) and objective evidence of cardiac dysfunction (either structural or functional). Statistical measures Diagnostic accuracy of BNP and NT-proBNP: 2x2 tables Specificity Sensitivity PPV/NPV ROC curve or Area under Curve Study design Single gate studies (cohort/cross-sectional) 5.1.3 Review question: In people with suspected heart failure, what is the clinical and cost effectiveness of N-terminus pro-B-type natriuretic peptide (NT-proBNP) compared to B- type natriuretic peptide (BNP), when each is followed by the appropriate patient pathway, in order to improve patient outcomes? Table 10: PICO characteristics of review question Population People with suspected heart failure in a community or outpatient setting. Index diagnostic test + treatment NT-proBNP assay (at any reported threshold) Treatment/next step in pathway: Echocardiography Comparator index diagnostic tests + treatment BNP assay (at any reported threshold) Treatment/next step in pathway: Echocardiography Outcomes Efficacy outcomes: All-cause mortality Quality of life Unplanned hospitalisation Process outcomes: Number of people receiving echocardiography, i.e., including people who may not have needed it such as those with false positive results Repeat testing / additional testing Secondary accuracy outcomes: Sensitivity / specificity and other test accuracy measures Study design Systematic Review RCT 5.1.4 Clinical evidence A search was conducted for single gate studies assessing the diagnostic test accuracy of BNP or NT- proBNP to identify the presence of heart failure (as indicated by the reference standard) in people suspected of heart failure in a community or outpatient setting. A search was also conducted for diagnostic RCTs comparing outcomes in people tested with BNP versus NT-proBNP.


A search was also conducted for diagnostic RCTs comparing outcomes in people tested with BNP versus NT-proBNP. The search dates were limited to studies published from 2009 onwards, as this review was an update of a review within CG108 (the 2010 CHF guideline). The 2010 update included Mant 2009212 . Mant Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 conducted a meta-analysis of studies investigating the accuracy of BNP and/or NT-proBNP in diagnosing heart failure in a range of settings and populations, and using a range of reference standards. Only those studies from Mant 2009212 that matched the current protocol were included in this review. which used echocardiography as the reference standard, these papers have been excluded within the current update as the committee agreed that echocardiography was not an appropriate reference standard for the diagnosis of heart failure. In total, 8 diagnostic accuracy studies were included in the review79,173,243,245,330, 359,379,380 these are summarised in Table 11 below. Evidence from these studies is summarised in the clinical evidence summary. See also the study selection flow chart in Appendix C, sensitivity/specificity forest plots in Appendix E, study evidence tables in Appendix F and excluded studies list in Appendix I. No diagnostic RCTs meeting the protocol were identified. Table 11: Summary of studies included in the review Study Population Target condition Index test Reference standard Comments People with suspected heart failure Age range: 24- Gender (M:F): UK Heart failure BNP ESC criteria, assessed by panel of three cardiologists People with suspected heart failure Age (mean Gender (M:F): The Netherlands Heart failure BNP NT-proBNP ESC criteria and Heart Failure Society of America assessed by panel of cardiologist, pulmonologist and a GP. Full diagnostic accuracy results not reported.


Table 11: Summary of studies included in the review Study Population Target condition Index test Reference standard Comments People with suspected heart failure Age range: 24- Gender (M:F): UK Heart failure BNP ESC criteria, assessed by panel of three cardiologists People with suspected heart failure Age (mean Gender (M:F): The Netherlands Heart failure BNP NT-proBNP ESC criteria and Heart Failure Society of America assessed by panel of cardiologist, pulmonologist and a GP. Full diagnostic accuracy results not reported. People complaining of dyspnoea of at Heart failure NT-proBNP ESC criteria Results stratified by age and sex. High risk of bias Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Population Target condition Index test Reference standard Comments least 2 weeks duration. Not all participants were suspected to have heart failure, and a small number already had a clinical diagnosis of heart failure. Age (median; Gender (M:F): Denmark Serious indirectness people completed the study) People presenting with dyspnoea, or oedema and a working diagnosis of heart failure Age (median; Gender (M:F): Ireland Heart failure BNP Clinical assessment and objective evidence based on echocardiography, assessed by a single cardiologist Very high risk of bias Serious indirectness People with symptoms suggestive of heart failure Age (mean Heart failure NT-proBNP ESC criteria, assessed by a panel of three cardiology specialists Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights.


Age (median; Gender (M:F): Denmark Serious indirectness people completed the study) People presenting with dyspnoea, or oedema and a working diagnosis of heart failure Age (median; Gender (M:F): Ireland Heart failure BNP Clinical assessment and objective evidence based on echocardiography, assessed by a single cardiologist Very high risk of bias Serious indirectness People with symptoms suggestive of heart failure Age (mean Heart failure NT-proBNP ESC criteria, assessed by a panel of three cardiology specialists Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Population Target condition Index test Reference standard Comments Gender (M:F): UK People with suspected heart failure Age (mean Gender (M:F): Spain Heart failure NT-proBNP ESC criteria, assessed by a single cardiologist People with suspected heart failure based on new symptoms Age (median; Gender (M:F): UK Heart failure BNP NT-proBNP ESC criteria, assessed by a single cardiologist People with suspected heart failure based on symptoms and clinical examination Age (mean Gender (M:F): Heart failure BNP NT-proBNP Presence of HF symptoms/signs and either: (a) an EF < 50%, according to the ESC criteria or (b) elevated LV filling pressure. Assessed by one of seven cardiologists. Full diagnostic accuracy results not reported. Very high risk of bias Serious indirectness Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Population Target condition Index test Reference standard Comments Switzerland Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: 978-1-4731-3093-7 Study Population Target condition Index test Reference standard Comments Switzerland Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Table 12: Clinical evidence summary: diagnostic test accuracy for index test(s) BNP and NT-proBNP Index Test (Threshold) No of studies n Quality Sensitivity % Specificity % Positive Predictive Value (PPV) % Negative Predictive Value (NPV) % AUC Plasma BNP BNP - 100 pg/mL 2e Axsym Centaur BNP - 178 pg/mL 1 105 VERY LOWa,c,d due to serious risk of bias, serious indirectness, serious imprecision BNP - 400 pg/mL 1e Axsym Centaur [Threshold data not accurately reported] due to serious risk of bias, serious indirectness - - - - 0.69 Plasma NT-proBNP NT-pro BNP Age specific thresholds NT-pro BNP Women 50 years due to serious risk of bias, serious indirectness Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Index Test (Threshold) No of studies n Quality Sensitivity % Specificity % Positive Predictive Value (PPV) % Negative Predictive Value (NPV) % AUC NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP due to serious inconsistency, serious imprecision Pooledf: Pooledf: NT-pro BNP Women 50 years due to serious risk of bias, serious indirectness NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP NT-pro BNP Women 50 years due to serious risk of bias, serious indirectness, serious imprecision NT-pro BNP due to serious inconsistency, very serious imprecision Pooledf: Pooledf: Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: Index Test (Threshold) No of studies n Quality Sensitivity % Specificity % Positive Predictive Value (PPV) % Negative Predictive Value (NPV) % AUC NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP due to serious inconsistency, serious imprecision Pooledf: Pooledf: NT-pro BNP Women 50 years due to serious risk of bias, serious indirectness NT-pro BNP Men 50 years due to serious risk of bias, serious indirectness NT-pro BNP NT-pro BNP Women 50 years due to serious risk of bias, serious indirectness, serious imprecision NT-pro BNP due to serious inconsistency, very serious imprecision Pooledf: Pooledf: Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Index Test (Threshold) No of studies n Quality Sensitivity % Specificity % Positive Predictive Value (PPV) % Negative Predictive Value (NPV) % AUC NT-pro BNP g VERY LOWb,d due to serious inconsistency, very serious imprecision Pooledf: Pooledf: NT-pro BNP [Threshold data not accurately reported] due to serious risk of bias, serious indirectness - - 0.74 The assessment was conducted with an emphasis on test sensitivity as this was identified by the GC as the primary measure in guiding decision making (except for the very high rule in thresholds of 400 ng/mL BNP and 2000 ng/mL NT-proBNP where specificity was the emphasis). The GC set the sensitivity threshold of 95% as an acceptable level to recommend a test. (a) Risk of bias was assessed using the QUADAS-2 checklist. The evidence was downgraded by 1 increment if the majority of studies were rated at high risk of bias, and downgraded by 2 increments if the majority of studies were rated at very high risk of bias.


The evidence was downgraded by 1 increment if the majority of studies were rated at high risk of bias, and downgraded by 2 increments if the majority of studies were rated at very high risk of bias. (b) Inconsistency was assessed by inspection of the sensitivity/specificity plots. Particular attention was placed on the sensitivity threshold(s) set by the GC as an acceptable level to recommend a test. The evidence was: downgraded by 1 increment if the individual study values varied across 2 areas, where values of individual studies are above/below 50%, or above/below the acceptable threshold 95%. downgraded by 2 increments if the individual study values varied across 3 areas, where values of individual studies are above/below 50%, and above/below the acceptable threshold 95%. (c) Indirectness was assessed using the QUADAS-2 checklist items referring to applicability. The evidence was downgraded by 1 increment if the majority of studies are seriously indirect, and downgraded by 2 increments if the majority of studies are very seriously indirect. (d) Imprecision was assessed based on inspection of the confidence region for sensitivity in the diagnostic meta-analysis. The evidence was downgraded by 1 increment when there was a 20- 40% range of the confidence interval around the point estimate, and downgraded by 2 increments when there was a range of >40%. (e) One study reported the results of two BNP tests at this threshold: Axsym & Centaur (reported in that order in the table above). (f) Pooled sensitivity/specificity from diagnostic meta-analysis. (g) Three studies (n= 826) included in pooled analysis (one study only reported NPV and AUC and could not be pooled). Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights.


Chronic Heart Failure Diagnosing heart failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 5.1.5 Economic evidence 5.1.5.1 Published literature No economic evaluations were identified comparing NT-proBNP thresholds and BNP thresholds. One relevant economic evaluation was identified and included in this review. This is summarised in the health economic profile below (Table 13) and the health economic tables in Appendix G. See also the economic article selection flow diagram in Appendix D. Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Table 13: Health economic evidence profile Study Applicabilit y Limitations Other comments Costs (c) Effects (QALYs) (c) Incrementa l cost (d) Incrementa l effects (d) Cost- effectiveness (d) Uncertainty Monahan [UK] Directly applicable(a ) Potentially serious limitations (b) Cost-utility analysis (health outcome: QALYs) Decision tree used to categorise patients according to diagnostic Population: Primary care patients aged 55years or over presenting to GP with symptoms suggestive of HF recruited across 28 central England practices in the UK. Interventions: 1. MICE clinical decision rule, upper cut-off 2. MICE clinical decision rule, lower cut-off guideline recommended strategy 4. Echo all sensitivity analysis showed that the probability that Intervention 3 is the optimal strategy at 99.9%. remains the most cost effective strategy in a number of scenario analyses. However, when proportion of HF-REF is the most cost effective strategy. When proportion of HF-REF is 100% became the most cost effective strategy. effects) is higher than for 2 vs 3) Diagnosing heart failure Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Study Applicabilit y Limitations Other comments Costs (c) Effects (QALYs) (c) Incrementa l cost (d) Incrementa l effects (d) Cost- effectiveness (d) Uncertainty 6.


ISBN: Study Applicabilit y Limitations Other comments Costs (c) Effects (QALYs) (c) Incrementa l cost (d) Incrementa l effects (d) Cost- effectiveness (d) Uncertainty 6. Do nothing Lifetime horizon Abbreviations: ICER: incremental cost-effectiveness ratio; MICE: Male, Infarction, Crepitations, Edema; QALY: quality-adjusted life years; RCT: randomised controlled trial (a) Recent UK study from a NHS and PSS perspective. (b) The analysis used diagnostic accuracy data where the level of NT-proBNP was used as a criterion in determining whether or not the patient had heart failure, therefore introducing incorporation bias to the diagnostic accuracy results. The committee were concerned that the hospitalisation rates applied in the model were overestimated compared to current clinical practice. The model does not report the outcomes for those who do not have heart failure and no assumptions have been reported for this population (c) Incremental cost/QALYs compared to do nothing (intervention 6) (d) Incremental cost/QALYs/cost effectiveness ratio compared to next most effect treatment option that is not ruled out by dominance or extended dominance. An option is ruled out by dominance when another option has higher QALYs and lower costs. An option is ruled out by extended dominance when it has a higher ICER than the next, more effective, option and so this option can never be the most cost effective. ICERs reported rounded to the nearest 100. Chronic Heart Failure Diagnosing heart failure 5.1.5.2 Unit costs The unit costs of BNP and NT-proBNP are provided below to aid committee discussion. Test costs were sought from a range of hospital trusts. Three sites provided unit cost information for BNP, and five sites provided unit cost information for NTproBNP. The average of these are reported below.


Three sites provided unit cost information for BNP, and five sites provided unit cost information for NTproBNP. The average of these are reported below. Table 14: Cost of natriuretic peptide tests Test Unit cost 5.1.5.3 New cost-effectiveness analysis The committee identified this area as a priority for original economic analysis. The committee sought to determine whether natriuretic peptide testing is cost-effective and if so what the most cost- effective diagnostic threshold should to refer for echocardiography and specialist clinical assessment. In recent years the European Society of Cardiology (ESC) has lowered their recommended natriuretic peptide thresholds from 100pg/ml for BNP and 400pg/ml for NT-proBNP to 35pg/ml (BNP) and 125pg/ml respectively, due to concern that previously recommended thresholds were too high. The committee also raised concerns that the threshold recommended in the 2010 Chronic Heart Failure (CHF) guideline (which was in line with the previous ESC thresholds) may be too high, resulting in some patients with heart failure receiving a delayed diagnosis and either re-presenting to primary care at a later date with worsening symptoms or presenting to hospital due to a decompensation. Lowering the threshold could also allow for earlier diagnosis and a better prognosis of these patients. However, the committee also noted that lowering the threshold may greatly increase cost to the NHS due to the greater number of referrals for echocardiography and specialist clinical assessment, many of which are unlikely to lead to a diagnosis of heart failure and therefore the diagnosis of other possible underlying conditions could be delayed. Therefore, original cost-effectiveness modelling was undertaken for this question. A summary is included here. Evidence statements summarising the results of the analysis can be found below. The full analysis can be found in Appendix O.


Evidence statements summarising the results of the analysis can be found below. The full analysis can be found in Appendix O. A cost-utility analysis was undertaken to determine the most cost effective threshold level of natriuretic peptide for referral from primary care for echocardiography and specialist clinical assessment. A decision tree with an attached Markov model was used to estimate lifetime quality- adjusted life years (QALYs) and costs from a current UK NHS and personal social services perspective. The analysis was conducted in accordance with the NICE reference case unless otherwise stated including discounting at 3.5% for costs and QALYs. The population entering the model are those presenting to primary care with signs and symptoms of heart failure, including breathlessness, fatigue or ankle swelling and upon clinical examination the general practitioner (GP) suspects that the patient has heart failure. The NICE 2010 Chronic Heart Failure guideline (CG108) recommendations state that patients with a previous history of myocardial infarction (MI) should be referred for echocardiography without a natriuretic peptide test. However, the committee decided that this was no longer appropriate as the definition of MI has changed over time and now includes many scenarios that differ from what was included in the Mant et al. 2009 HTA which formed the basis of the recommendation in the 2010 guideline212 . People who first Chronic Heart Failure Diagnosing heart failure present to an acute emergency setting were excluded as this population is covered by the Acute Heart Failure guideline (CG187). The committee decided to exclude BNP testing from this analysis for the multiple reasons. The most important factor is that the clinical review demonstrates that NT-proBNP has a greater sensitivity over a range of thresholds compared to BNP.


The most important factor is that the clinical review demonstrates that NT-proBNP has a greater sensitivity over a range of thresholds compared to BNP. The committee emphasised the clinical importance of sensitivity over specificity as the test is used as a rule out for heart failure. Secondly, on a practical level and since the test will be requested mainly by primary care and be sent to the laboratories with inherent delay in transport, NT-proBNP has a longer stability in blood samples than BNP (days versus 4-6 hours), therefore NT-proBNP is more appropriate for testing in primary care. Thirdly, although it is unlikely at this stage for a patient not diagnosed with heart failure to be on Sacubitril Valsartan which interferes with BNP physiology (TA388), natriuretic peptides can also be used for monitoring heart failure patients, therefore it would be more useful to have NT-proBNP as the baseline peptide in case monitoring was needed in a patient with heart failure who is subsequently treated with this new drug. The following NT-proBNP thresholds were chosen as comparators: 400pg/ml 2010 NICE recommended threshold and previous 2012 ESC threshold 125pg/ml 2016 ESC threshold 280pg/ml the optimal threshold found in one study included in clinical review359 , and also lies close to the middle of the other 2 thresholds. As a reference, a diagnostic strategy was also included where no NT-proBNP test is undertaken and all patients with suspected heart failure are referred for echocardiography plus specialist clinical assessment. The model is structured in 2 parts: A decision tree is used to calculate the proportion of the population that fall into one of a number of cohorts according to their underlying condition and test result.


The model is structured in 2 parts: A decision tree is used to calculate the proportion of the population that fall into one of a number of cohorts according to their underlying condition and test result. The decision tree calculates the proportion of patients who will receive a false negative (FN), false positive (FP), true negative (TN), or true positive (TP) NT-proBNP test result according to the sensitivity, specificity and prevalence data. Patients with a positive test result (levels above the chosen threshold) are then referred for echocardiography and specialist clinical assessment to determine if they have heart failure or not. A Markov model then evaluates patients health and cost outcomes according to their cohort once the initial NT-proBNP test result is determined accounting for waiting times for diagnostic tests. For more detailed explanation of the model structure, please refer to the technical report in Appendix O. A number of assumptions were made when developing the model. The key assumptions are outlined below but are also discussed in more detail in Appendix O: Echocardiography plus specialist clinical assessment is 100% accurate. False negative patients are subsequently correctly diagnosed through 1 of 2 possible channels: A patient is hospitalised due their undiagnosed heart failure and are diagnosed during admission A patient re-presents to their GP within 6 months where the NT-proBNP test is repeated. The committee considered that after this we could assume that their NT- proBNP levels would be over 400pg/ml and therefore the patient would be referred for an echocardiogram and specialist clinical assessment and be correctly diagnosed. Chronic Heart Failure Diagnosing heart failure There is no mortality or morbidity benefit of treatment for HF-PEF patients.


Chronic Heart Failure Diagnosing heart failure There is no mortality or morbidity benefit of treatment for HF-PEF patients. Heart failure for those with a NT-proBNP level < 400pg/ml will be less severe compared to those above the threshold and therefore mortality and hospitalisation rates will be lower than those reported in the literature. The cost and disutility consequences of missing these patients is therefore likely to be lower than for those with higher NT-proBNP levels. An individual s NT-proBNP level does not affect the rate of hospitalisation or mortality for other (non-HF) conditions. In heart failure patients with NT-proBNP levels <400pg/ml (treated or untreated) a hospitalisation causes their NT-proBNP levels to permanently be raised over 400pg/ml due to a worsening in their heart failure. Untreated heart failure patients (both HF-REF and HF-PEF) progress to having NT-proBNP levels >400pg/ml after 6 months if they have not already progressed due to hospitalisation. As HF-PEF patients are considered as untreated, all HF-PEF patients therefore progress to higher severity 6 months after first presentation. Treated low severity HF-REF patients who do not experience a hospitalisation progress to having NT-proBNP levels >400pg/ml 5 years after first presentation. The most common alternative diagnoses if a patient does not have heart failure are COPD, myocardial ischaemia, and obesity. The committee considered that the percentage of patients with these conditions would be 35% and 15%, and 50%, respectively. Patients do not have multiple-morbidities. Model inputs were based on clinical evidence identified in the systematic review undertaken for the guideline, supplemented by additional data sources as required. These are described in full in the technical report in Appendix O. All model inputs and assumptions were validated by the guideline committee. Sensitivity analyses were also undertaken in areas of uncertainty to see how robust the model results are.


Sensitivity analyses were also undertaken in areas of uncertainty to see how robust the model results are. The base-case results are presented below. For a full write up of the model results and sensitivity analyses see Appendix O. In the base-case analysis 400pg/ml was found to be the most cost effective NT-proBNP threshold. Results are summarised below in Table 15 with regards to costs, QALYs and cost-effectiveness (net monetary benefit, and probability of cost effective at 20,000 per QALY threshold), and Table 16 with regards to ranking of the strategies. A threshold of 400pg/ml produces both the highest incremental QALYs and the highest incremental cost versus echo all, and has the highest net monetary benefit at 20,000 per QALY and is therefore the most cost effective diagnostic threshold for referral to echocardiography. The probability of 400pg/ml being the most cost effective option at 20,000 per QALY is 77%. Table 15: Base case analysis results (probabilistic analysis) Diagnostic strategy Mean per patient NMB at threshold Probability most CE option at 20,000 per QALY Costs QALYs Chronic Heart Failure Diagnosing heart failure Diagnostic strategy Mean per patient NMB at threshold Probability most CE option at 20,000 per QALY Costs QALYs Abbreviations: CE = cost effective; QALYS: quality adjusted life years;.NMB: net monetary benefit. Table 16: Base case analysis ranking results Diagnostic strategy Probability Probability Probability Probability The mean costs and QALYs from the probabilistic analysis have also been presented graphically on the cost-effectiveness plane in Figure 5. The cost-effectiveness ratio of 400pg/ml versus echo all is 5,496. Figure 5: Base-case cost-effectiveness plane showing incremental costs and QALYs of each diagnostic strategy Chronic Heart Failure Diagnosing heart failure The disaggregated costs and QALYs from the probabilistic base case analysis are summarised inTable 17, Table 18 and Table 19 below.