This chapter sets out in detail the methods used to generate the recommendations that are presented in the subsequent chapters. This guidance was developed in accordance with the methods outlined in the NICE Guidelines Manual 2009.9
3.1. Developing the review questions and outcomes
Review questions were developed in a PICO framework (patient/population, intervention, comparison and outcome) for intervention reviews, and with a framework of population, index tests, reference standard and target condition for reviews of diagnostic test accuracy (see ). This was to guide the literature searching process and to facilitate the development of recommendations by the GDG. They were drafted by the NCGC technical team and refined and validated by the GDG. The review questions were based on the key clinical areas identified in the scope (Appendix A). The review question protocols can be found in Appendix C. The review questions and outcome measures examined are presented in .
List of guideline review questions.
3.1.1. Clinical outcomes not considered
Patency
The final scope for this guideline identified graft and vessel patency (primary and secondary) as an outcome to be considered in the clinical and cost effectiveness evidence reviews. The use of patency as an outcome measure for PAD was discussed by the GDG at length. The GDG were aware that it has been used in many clinical trials as a surrogate endpoint for studies of treatments for PAD, particularly endovascular treatments. The GDG were of the opinion that patency was not a good surrogate outcome and should not therefore be included as an outcome for most comparisons.
The major concern was that the usefulness of patency as an outcome depended upon clear evidence to make the link between patency and clinical outcomes of relevance to people with PAD. The GDG noted that some treatments that are known to have an effect upon symptoms in people with PAD have no effect upon patency. Their clinical experience and knowledge of the literature suggests that it is common for people to develop recurrent symptoms despite a patent segment of vessel or to develop re-stenosis or re-occlusion without having recurrent symptoms. They therefore considered that the results of treatment were far better measured by outcomes of relevance to patients such as symptoms, quality of life and the need for further interventions.
Another consideration in respect to the use of patency as an outcome is the variability in definitions used in the literature, which may be based upon different modalities of measurement or differing degrees of narrowing. A threshold for degree of narrowing (e.g. 50% based upon a chosen imaging modality) leads to the anomaly that changes in narrowing of a few percent close to the threshold determine “success”, but are likely to have little or no clinical significance. It was also noted that patency focused specifically on technical outcomes for disease at a specific site in an artery, whereas PAD often occurs at multiple sites. The GDG felt that outcomes that consider the impact of disease and treatment on the limb or the patient are of greater relevance.
The use of patency as a surrogate outcome also leads to difficulties in undertaking comparisons with other treatments, such as exercise or drug treatment, where an effect on patency is not to be expected. Even where both treatments aim to increase the diameter of a vessel, such as in the comparison of angioplasty and stents, the initial result that is expected may differ, and thus a threshold for patency based upon a specific degree of stenosis may be less likely to reflect a clinically significant change for one of the treatments. Furthermore, the difference in initial treatment may mean that the clinical implications, for example in terms of the potential modalities and expected outcome of retreatment, may be different.
The only situation where the GDG considered that patency would be a potentially useful outcome was where the two treatments being compared were expected to have identical mechanical effects, such as in comparing similar stents with and without drug elution. Even in this situation clinical outcomes would be preferred where available and the usefulness of the surrogate outcome would depend upon the availability of evidence to link this to clinical outcomes which, for the reasons above, would need to be related to the specific treatment.
3.1.2. Health related quality of life
Two types of instrument are available for measuring health related quality of life: disease specific and generic questionnaires. The former focuses on problems associated with individual diseases, while the latter include questions that span a number of physical and emotional dimensions common to all people. Generic measurements of quality of life can be further divided into two major classes: health profiles and utility measures.
Several disease specific and generic health profiles have been used to measure quality of life in people with IC. These include, but are not limited to: the SF-36; Nottingham Health Profile; Sickness Impact Profile; Walking Impairment Questionnaire; and VascuQol.
Utility measures are designed to reflect preferences for different treatment processes and outcomes and comprise the primary measure of effectiveness in cost-utility analyses. In cost-utility analyses, measures of health benefit are valued in terms of quality adjusted life years (QALYs). The QALY is a measure of a person’s length of life weighted by a valuation of their HRQoL over that period. The utility weighting comprises two elements: the description of changes in HRQoL and an overall valuation of that description. Generic utility measures include: the EQ-5D; HUI 2; and SF-6D.
The different methods of measuring quality of life are not mutually exclusive; each may be useful for under certain circumstances and for specific purposes. Early in the guideline development process, the GDG decided that they wished to inform the economic analyses with health related quality of life obtained directly from the included clinical studies. Changes in disease specific functional disability would be captured by including walking distance as an outcome. The NICE reference case10 specifies that the EQ-5D is the preferred method of QALY measurement. Therefore, only EQ-5D values or health state descriptions which could be mapped to EQ-5D were included as measures of health related quality of life. Disease specific questionnaires and other generic health profiles were not included as outcomes in the review.
3.2. Searching for evidence
3.2.1. Clinical literature search
Systematic literature searches were undertaken to identify evidence within published literature in order to answer the review questions as per the Guidelines Manual 2009.9 Clinical databases were searched using relevant medical subject headings, free-text terms and study type filters where appropriate. Studies published in languages other than English were not reviewed. Where possible, searches were restricted to articles published in English language. All searches were conducted on core databases, MEDLINE, Embase, Cinahl and The Cochrane Library. In addition, PsychInfo database was used for the patient information review question. All searches were updated on the 9th January 2012. No papers after this date were considered.
Search strategies were checked by looking at reference lists of relevant key papers, checking search strategies in other systematic reviews and asking the GDG for known studies. The questions, the study types applied, the databases searched and the years covered can be found in Appendix D.
During the scoping stage, a search was conducted for guidelines and reports on the websites listed below and on organisations relevant to the topic. Searching for grey literature or unpublished literature was not undertaken. All references sent by stakeholders were considered.
National Institute for Health and Clinical Excellence (NICE) (
www.nice.org.uk)
3.2.1.1. Call for evidence
The GDG decided to initiate a ‘call for evidence’ for randomised controlled trials comparing the effectiveness of drug eluting stents to bare metal stents for the treatment of peripheral arterial disease as they believed that important evidence existed that would not be identified by the standard searches. The NCGC contacted all registered stakeholders and asked them to submit any relevant published or unpublished evidence.
3.2.2. Health economic literature search
Systematic literature searches were also undertaken to identify health economic evidence within published literature relevant to the review questions. The evidence was identified by conducting a broad search relating to people with peripheral arterial disease in the NHS economic evaluation database (NHS EED), the Health Economic Evaluations Database (HEED) and health technology assessment (HTA) databases with no date restrictions. Additionally, the search was run on MEDLINE and Embase, with a specific economic filter, from 2010, to ensure recent publications that had not yet been indexed by these databases were identified. Studies published in languages other than English were not reviewed. Where possible, searches were restricted to articles published in English language.
The search strategies for health economics are included in Appendix D. All searches were updated on the 9th January 2012. No papers published after this date were considered.
3.3. Evidence of effectiveness
The research fellow:
Identified potentially relevant studies for each review question from the relevant search results by reviewing titles and abstracts – full papers were then obtained
Reviewed full papers against pre-specified inclusion/exclusion criteria to identify studies that addressed the review question in the appropriate population and reported on outcomes of interest (review protocols are included in
Appendix C)
Critically appraised relevant studies using the appropriate checklist as specified in the Guidelines Manual 2009
9Extracted key information about the study’s methods and results into evidence tables (clinical evidence tables are included in
Appendix H)
Generated summaries of the evidence by outcome (included in the relevant chapter write-ups):
Randomised studies: meta-analysed, where appropriate and reported in GRADE profiles (for clinical studies) – see below for details
Observational studies: data presented as a range of values in GRADE profiles
Diagnostic studies: data presented as a range of values in adapted GRADE profiles
Qualitative studies: each study summarised in adapted GRADE profiles.
3.3.1. Inclusion/exclusion
The inclusion/exclusion of studies was based on the review protocols (Appendix C). The GDG were consulted about any uncertainty regarding inclusion/exclusion of selected studies.
3.3.2. Methods of combining clinical studies
3.3.2.1. Data synthesis for intervention reviews
Where possible, meta-analyses were conducted to combine the results of studies for each review question using Cochrane Review Manager (RevMan5) software. Fixed-effects (Mantel-Haenszel) techniques were used to calculate risk ratios (relative risk) for the binary outcomes: mortality, amputation free survival, cardiovascular events, adverse events, re-intervention rates and withdrawal rates. The continuous outcomes: quality of life, walking distance, exercise level at follow up, change in ABPI pain measures, duration of pain control and patient satisfaction were analysed using an inverse variance method for pooling weighted mean differences and where the studies had different scales, standardised mean differences were used. Where reported, time-to-event data was presented as a hazard ratio.
Three network meta-analyses were considered for the guideline. The three proposed networks were for the outcome of walking distance in the IC population, mortality in the CLI population and amputation free survival in the CLI population. None of the network meta-analyses were methodologically possible to conduct due to lack of evidence to build complete networks for the outcomes proposed.
Statistical heterogeneity was assessed by considering the chi-squared test for significance at p<0.1 or an I-squared inconsistency statistic of >50% to indicate significant heterogeneity. Where significant heterogeneity was present, we carried out sensitivity analysis based on the quality of studies if there were differences, with particular attention paid to allocation concealment, blinding and loss to follow-up (missing data). In cases where there was inadequate allocation concealment, unclear blinding, more than 50% missing data or differential missing data, this was examined in a sensitivity analysis. For the latter, the duration of follow up was also taken into consideration prior to including in a sensitivity analysis.
Assessments of potential differences in effect between subgroups were based on the chi-squared tests for heterogeneity statistics between subgroups. If no sensitivity analysis was found to completely resolve statistical heterogeneity then a random effects (DerSimonian and Laird) model was employed to provide a more conservative estimate of the effect.
For continuous outcomes, the means and standard deviations were required for meta-analysis. However, in cases where standard deviations were not reported, the standard error was calculated if the p-values or 95% confidence intervals were reported and meta-analysis was undertaken with the mean and standard error using the generic inverse variance method in Cochrane Review Manager (RevMan5) software. When the only evidence was based on studies summarised results by only presenting means this information was included in the GRADE tables without calculating the relative and absolute effect.
For binary outcomes, absolute event rates were also calculated using the GRADEpro software using event rate in the control arm of the pooled results.
3.3.2.2. Data synthesis for diagnostic test accuracy review
Evidence for diagnostic data was evaluated by study, using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) checklists.
For diagnostic test accuracy studies, the following data were extracted, either directly from the study report or calculated from other study data: components of the “2×2 table” (true positives, false positives, false negatives and true negatives) and test accuracy parameters: sensitivity, specificity, positive/negative predictive values and positive/negative likelihood ratios (there are other outcomes that can be included such as area under curve (AUC for ROC curves) reproducibility, applicability and inter and intra operative reliability). In cases where the outcomes were not reported, 2×2 tables were constructed from raw data to allow calculation of accuracy measures.
Forest plots of sensitivity and specificity with their 95% confidence intervals were presented side-by-side for individual studies using Cochrane Review Manager (RevMan5) software (for RevMan see Appendix J).
When data from 5 or more studies were available, a diagnostic meta-analysis was carried out. To show the differences between study results, pairs of sensitivity and specificity were plotted for each study on one receiver operating characteristics (ROC) curve in Microsoft EXCEL software (for Excel plots please see Appendix J). A ROC plot shows true positive rate (i.e. sensitivity) as a function of false positive rate (i.e. 1 – specificity). Study results were pooled using the bivariate method for the direct estimation of summary sensitivity and specificity using a random effects approach (in WinBUGS® software - for the program code see Appendix J). This model also assesses the variability by incorporating the precision by which sensitivity and specificity have been measured in each study. A confidence ellipse is shown in the graph that indicates the confidence region around the summary sensitivity/specificity point. A summary ROC curve is also presented. From the WinBUGS® output we report the summary estimate of sensitivity and specificity (plus their 95% confidence intervals) as well as between study variation measured as logit sensitivity and specificity as well as correlations between the two measures of variation. The summary diagnostic odds ratio with its 95% confidence interval is also reported.
3.3.3. Type of studies
For most intervention evidence reviews in this guideline, RCTs were included. Where the GDG believed RCT data would not be appropriate this is detailed in the protocols in Appendix C. RCTs were included as they are considered the most robust type of study design that could produce an unbiased estimate of the intervention effects.
For diagnostic evidence reviews, diagnostic randomised controlled trials, diagnostic cohorts and case controls studies were included in this guideline.
3.3.4. Types of analysis
Estimates of effect from individual studies were based available case analysis (ACA) where possible or intention to treat (ITT) analysis if this was not possible. ITT analysis is where all participants that were randomised are considered in the final analysis based on the intervention and control groups to which they were originally assigned. It was assumed that participants in the trials lost to follow-up did not experience the outcome of interest (categorical outcomes) and they would not considerably change the average scores of their assigned groups (for continuous outcomes).
It is important to note that ITT analyses tend to bias the results towards no difference. ITT analysis is a conservative approach to analyse the data, and therefore the effect may be smaller than in reality.
3.3.5. Appraising the quality of evidence by outcomes
The evidence for outcomes from the included RCTs and observational 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 (GRADEpro) 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 summary of findings was presented as one table in the guideline (called clinical evidence profiles). This includes the details of the quality assessment pooled outcome data, and where appropriate, an absolute measure of intervention effect and the summary of quality of evidence for that outcome. In this table, the columns for intervention and control indicate the sum of the sample size for continuous outcomes. For binary outcomes such as number of patients with an adverse event, the event rates (n/N: number of patients with events divided by sum of number of patients) are shown with percentages. Reporting or publication bias was only taken into consideration in the quality assessment.
Each outcome was examined separately for the quality elements listed and defined in and each graded using the quality levels listed in and . The main criteria considered in the rating of these elements are discussed below (see section 3.3.6 Grading of Evidence). Footnotes were used to describe reasons for grading a quality element as having serious or very serious problems. The ratings for each component were summed to obtain an overall assessment for each outcome.
Description of quality elements in GRADE for intervention studies.
Levels of quality elements in GRADE.
Overall quality of outcome evidence in GRADE.
The GRADE toolbox is currently designed only for RCTs and observational studies but however, for the purposes of this guideline, the quality assessment elements and outcome presentation was adapted for diagnostic accuracy and qualitative studies.
3.3.6. Grading the quality of clinical evidence
After results were pooled, the overall quality of evidence for each outcome was considered. The following procedure was adopted when using GRADE:
A quality rating was assigned, based on the study design. RCTs start HIGH and observational studies as LOW, uncontrolled case series as LOW or VERY LOW.
The rating was then downgraded for the specified criteria: study limitations, inconsistency, indirectness, imprecision and reporting bias. These criteria are detailed below (see ). Observational studies were upgraded if there was: a large magnitude of effect, dose-response gradient, and if all plausible confounding would reduce a demonstrated effect or suggest a spurious effect when results showed no effect. Each quality element considered to have “serious” or “very serious” risk of bias were rated down -1 or -2 points respectively.
The downgraded/upgraded marks were then summed and the overall quality rating was revised. For example, all RCTs started as HIGH and the overall quality became MODERATE, LOW or VERY LOW if 1, 2 or 3 points were deducted respectively.
The reasons or criteria used for downgrading were specified in the footnotes.
Study limitations of randomised controlled trials.
The details of criteria used for each of the main quality element are discussed further in the following sections 3.3.5 to 3.3.10.
3.3.7. Study limitations
The main limitations for RCTs are listed in .
The GDG accepted that investigator blinding in surgical intervention studies was impossible and participant blinding was also difficult to achieve in most situations. Nevertheless, open-label studies for surgery were downgraded to maintain a consistent approach in quality rating across the guideline.
3.3.8. Inconsistency
Inconsistency refers to an unexplained heterogeneity of results. When estimates of the treatment effect across studies differ widely (i.e. heterogeneity or variability in results), this suggests true differences in underlying treatment effect. When heterogeneity exists (Chi square p<0.1 or I-squared inconsistency statistic of >50%), but no plausible explanation can be found, the quality of evidence was downgraded by one or two levels, depending on the extent of uncertainty to the results contributed by the inconsistency in the results. In addition to the I-square and Chi square values, the decision for downgrading was also dependent on factors such as whether the intervention is associated with benefit in all other outcomes or whether the uncertainty about the magnitude of benefit (or harm) of the outcome showing heterogeneity would influence the overall judgment about net benefit or harm (across all outcomes).
If inconsistency could be explained based on pre-specified subgroup analysis, the GDG took this into account and considered whether to make separate recommendations based on the identified explanatory factors, i.e. population and intervention. Where subgroup analysis gives a plausible explanation of heterogeneity, the quality of evidence would not be downgraded.
3.3.9. Indirectness
Directness refers to the extent to which the populations, intervention, comparisons and outcome measures are similar 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.
3.3.10. Imprecision
The minimal important difference (MID) in the outcome between the two groups were the main criteria considered.
The thresholds of important benefits or harms, or the MID for an outcome are important considerations for determining whether there is a “clinically important” difference between intervention and control groups and in assessing imprecision. For continuous outcomes, the MID is defined as “the smallest difference in score in the outcome of interest that informed patients or informed proxies perceive as important, ether beneficial or harmful, and that would lead the patient or clinician to consider a change in the management.11–14 An effect estimate larger than the MID is considered to be “clinically important”.
The difference between two interventions, as observed in the studies, was compared against the MID when considering whether the findings were of “clinical importance”; this is useful to guide decisions. For example, if the effect size was small (less than the MID), this finding suggests that there may not be enough difference to strongly recommend one intervention over the other based on that outcome.
The criteria applied for imprecision are based on the confidence intervals for pooled or the best estimate of effect as outlined in and illustrated in .
Criteria applied to determine precision.
Illustration of precise and imprecise outcomes based on the confidence interval of outcomes in a forest plot. Source: Figure adapted from GRADEPro software.
presents the MID thresholds used for the specified outcomes for this guideline as specified by the GDG.
Minimal important differences (MIDs) for the outcomes used in this guideline.
The MIDs are the threshold for appreciable benefits and harms. The confidence intervals of the top three points of the diagram were considered precise because the upper and lower limits did not cross the MID. Conversely, the bottom three points of the diagram were considered imprecise because all of them crossed the MID and reduced our certainty of the results.
3.4. Evidence of cost-effectiveness
The GDG is required to make decisions based on the best available evidence of both clinical and cost effectiveness. Guideline recommendations should be based on the expected costs of the treatment options in relation to their expected health benefits (that is, their ‘cost effectiveness’), rather than on the total cost or resource impact of implementing them.9 Thus, if the evidence suggests that an intervention provides significant health benefits at an acceptable cost per patient treated, it should be recommended even if it would be expensive to implement across the whole population.
Evidence on cost-effectiveness related to the key clinical issues being addressed in the guideline was sought. The health economist undertook:
3.4.1. Literature review
The health economist:
Identified potentially relevant studies for each review question from the economic search results by reviewing titles and abstracts – full papers were then obtained
Reviewed full papers against pre-specified inclusion/exclusion criteria to identify relevant studies (see below for details)
Critically appraised relevant studies using the economic evaluations checklist as specified in The Guidelines Manual 2009
9Extracted key information about the study’s methods and results into evidence tables (included in
Appendix I)
Generated summaries of the evidence in NICE economic evidence profiles (included in the relevant chapter write-ups) – see below for details.
3.4.1.1. Inclusion/exclusion
Full economic evaluations (studies comparing costs and health consequences of alternative courses of action: cost–utility, cost-effectiveness, cost-benefit and cost-consequence analyses) and comparative costing studies that addressed the review question in the relevant population were considered potentially includable as 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. Abstracts, posters, reviews, letters/editorials, foreign language publications and unpublished studies were excluded. Studies judged to have an applicability rating of ‘not applicable’ were excluded (this included studies that took the perspective of a non-OECD country, except for American studies, which were considered ‘partially applicable’).
Remaining 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 applicable UK analysis was available other less relevant studies may not have been included. Where exclusions occurred on this basis, this is noted in the relevant section and included in the list of excluded studies in Appendix F.
For more details about the assessment of applicability and methodological quality see the economic evaluation checklist.9
When no relevant economic analysis was identified in the economic literature review, relevant UK NHS unit costs related to the compared interventions were presented to the GDG to inform the possible economic implication of the recommendation to make.
3.4.1.2. NICE economic evidence profiles
The NICE economic evidence profile has been used to summarise cost and cost-effectiveness estimates (see ). The economic evidence profile includes an assessment of applicability and methodological quality for each economic study, with footnotes indicating the reasons for each assessment. These assessments were made by the health economist using the economic evaluation checklist from the Guidelines Manual 2009.9 It also shows incremental costs, incremental outcomes (for example, QALYs) and the incremental cost-effectiveness ratio, as well as information about the assessment of uncertainty in the analysis.
Content of NICE economic profile.
Several of the pair wise clinical comparisons conducted in the IC population concerned the same decision question. Due to the nature of the question and the difficulty of considering multiple-comparator evaluations in a pair wise context, the clinical and economic evidence for these questions were presented in separate sections.
All costs converted into 2009/10 pounds sterling using the appropriate purchasing power parity.15
3.4.2. Undertaking new health economic analysis
As well as reviewing the published economic literature for each review question, as described above, new economic analysis was undertaken by the health economist in priority selected areas. Priority areas for new health economic analysis were agreed by the GDG after formation of the review questions and consideration of the available health economic evidence.
The GDG identified the treatment of IC using exercise and endovascular interventions as the highest priority areas for original economic modelling. Specifically, these areas include the cost effectiveness of supervised compared to unsupervised exercise, and exercise compared to angioplasty for the treatment of IC.
The following general principles were adhered to in developing the cost-effectiveness analysis:
Methods were consistent with the NICE reference case
10The GDG 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 was not available GDG 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 NCGC.
Additional data for the analysis was identified as required through additional literature searches undertaken by the health economist and in discussion with the GDG. Model structure, inputs and assumptions were explained to and agreed by the GDG members during meetings, and they commented on subsequent revisions.
Full methods for the original health economic analyses undertaken for this guideline are described in Appendices K and L.
3.4.3. Cost-effectiveness criteria
NICE’s report ‘Social value judgements: principles for the development of NICE guidance’ sets out the principles that GDGs should consider when judging whether an intervention offers good value for money.9,16
In general, an intervention was considered to be cost effective if either of the following criteria applied (given that the estimate was considered plausible):
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.
If the GDG 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 the ‘Social value judgements: principles for the development of NICE guidance’.16
3.4.4. In the absence of cost-effectiveness evidence
When no relevant published studies were found, and a new analysis was not prioritised, the GDG made a qualitative judgement about cost effectiveness by considering expected differences in resource use between comparators and relevant UK NHS unit costs alongside the results of the clinical review of effectiveness evidence.
3.5. Developing recommendations
Over the course of the guideline development process, the GDG was presented with:
Evidence tables of the clinical and economic evidence reviewed from the literature. All evidence tables are in
Appendices H and
ISummary of clinical and economic evidence and quality (as presented in
chapters 5–
12)
Forest plots, diagnostic meta-analysis and summary ROC curves (
Appendix J)
A description of the methods and results of the cost-effectiveness analysis undertaken for the guideline (
Appendix K and
L).
Recommendations were drafted on the basis of the GDG’s interpretation of the available evidence, taking into account the balance of benefits, harms and costs. When clinical and economic evidence was of poor quality, conflicting or absent, the GDG drafted recommendations based on their expert opinion. The considerations for making consensus based recommendations include the balance between potential harms and benefits, economic or implications compared to the benefits, current practices, recommendations made in other relevant guidelines, patient preferences and equality issues. The consensus recommendations were done through discussions in the GDG. The GDG may also consider whether the uncertainty is 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 3.5.1).
The main considerations specific to each recommendation are outlined in the recommendations and link to evidence section following the clinical and economic evidence reviews.
3.5.1. Research recommendations
When areas were identified for which good evidence was lacking, the GDG considered making recommendations for future research. Decisions about inclusion 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.
3.5.2. Validation process
The guidance is subject to a six week public consultation and feedback as part of the quality assurance and peer review the document. All comments received from registered stakeholders are responded to in turn and posted on the NICE website when the pre-publication check of the full guideline occurs.
3.5.3. Updating the guideline
Following publication, and in accordance with the NICE guidelines manual, NICE will ask a National Collaborating Centre or the National Clinical Guideline Centre to advise NICE’s Guidance executive whether the evidence base has progressed significantly to alter the guideline recommendations and warrant an update.
3.5.4. Disclaimer
Health care 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 here must be made by the practitioners in light of individual patient circumstances, the wishes of the patient, clinical expertise and resources.
The National Clinical Guideline Centre disclaims any responsibility for damages arising out of the use or non-use of these guidelines and the literature used in support of these guidelines.
3.5.5. Funding
The National Clinical Guideline Centre was commissioned by the National Institute for Health and Clinical Excellence to undertake the work on this guideline.
