NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.
National Clinical Guideline Centre (UK). Blood Transfusion. London: National Institute for Health and Care Excellence (NICE); 2015 Nov. (NICE Guideline, No. 24.)
22.1. Methodology glossary
| Term | Definition |
|---|---|
| Abstract | Summary of a study, which may be published alone or as an introduction to a full scientific paper. |
| Algorithm (in guidelines) | A flow chart of the clinical decision pathway described in the guideline, where decision points are represented with boxes, linked with arrows. |
| Allocation concealment | The process used to prevent advance knowledge of group assignment in an RCT. The allocation process should be impervious to any influence by the individual making the allocation, by being administered by someone who is not responsible for recruiting participants. |
| Applicability | How well the results of a study or NICE evidence review can answer a clinical question or be applied to the population being considered. |
| Arm (of a clinical study) | Subsection of individuals within a study who receive one particular intervention, for example placebo arm. |
| Association | Statistical relationship between 2 or more events, characteristics or other variables. The relationship may or may not be causal. |
| Base case analysis | In an economic evaluation, this is the main analysis based on the most plausible estimate of each input. In contrast, see Sensitivity analysis. |
| Baseline | The initial set of measurements at the beginning of a study (after run-in period where applicable), with which subsequent results are compared. |
| Bayesian analysis | A method of statistics, where a statistic is estimated by combining established information or belief (the ‘prior’) with new evidence (the ‘likelihood’) to give a revised estimate (the ‘posterior’). |
| Before-and-after study | A study that investigates the effects of an intervention by measuring particular characteristics of a population both before and after taking the intervention, and assessing any change that occurs. |
| Bias | Influences on a study that can make the results look better or worse than they really are (Bias can even make it look as if a treatment works when it does not). Bias can occur by chance, deliberately or as a result of systematic errors in the design and execution of a study. It can also occur at different stages in the research process, for example, during the collection, analysis, interpretation, publication or review of research data. For examples see selection bias, performance bias, information bias, confounding factor, and publication bias. |
| Blinding | A way to prevent researchers, doctors and patients in a clinical trial from knowing which study group each patient is in so they cannot influence the results. The best way to do this is by sorting patients into study groups randomly. The purpose of ‘blinding’ or ‘masking’ is to protect against bias. A single-blinded study is one in which patients do not know which study group they are in (for example, whether they are taking the experimental drug or a placebo). A double-blinded study is one in which neither patients nor the researchers and doctors know which study group the patients are in. A triple blind study is one in which neither the patients, clinicians or the people carrying out the statistical analysis know which treatment patients received. |
| Carer (caregiver) | Someone who looks after family, partners or friends in need of help because they are ill, frail or have a disability. |
| Case–control study | A study to find out the cause(s) of a disease or condition. This is done by comparing a group of patients who have the disease or condition (cases) with a group of people who do not have it (controls) but who are otherwise as similar as possible (in characteristics thought to be unrelated to the causes of the disease or condition). This means the researcher can look for aspects of their lives that differ to see if they may cause the condition. For example, a group of people with lung cancer might be compared with a group of people the same age that do not have lung cancer. The researcher could compare how long both groups had been exposed to tobacco smoke. Such studies are retrospective because they look back in time from the outcome to the possible causes of a disease or condition. |
| Case series | Report of a number of cases of a given disease, usually covering the course of the disease and the response to treatment. There is no comparison (control) group of patients. |
| Clinical efficacy | The extent to which an intervention is active when studied under controlled research conditions. |
| Clinical effectiveness | How well a specific test or treatment works when used in the ‘real world’ (for example, when used by a doctor with a patient at home), rather than in a carefully controlled clinical trial. Trials that assess clinical effectiveness are sometimes called management trials. Clinical effectiveness is not the same as efficacy. |
| Clinician | A healthcare professional who provides patient care. For example, a doctor, nurse or physiotherapist. |
| Cochrane Review | The Cochrane Library consists of a regularly updated collection of evidence-based medicine databases including the Cochrane Database of Systematic Reviews (reviews of randomised controlled trials prepared by the Cochrane Collaboration). |
| Cohort study | A study with 2 or more groups of people – cohorts – with similar characteristics. One group receives a treatment, is exposed to a risk factor or has a particular symptom and the other group does not. The study follows their progress over time and records what happens. See also observational study. |
| Comorbidity | A disease or condition that someone has in addition to the health problem being studied or treated. |
| Comparability | Similarity of the groups in characteristics likely to affect the study results (such as health status or age). |
| Concordance | This is a recent term whose meaning has changed. It was initially applied to the consultation process in which doctor and patient agree therapeutic decisions that incorporate their respective views, but now includes patient support in medicine taking as well as prescribing communication. Concordance reflects social values but does not address medicine-taking and may not lead to improved adherence. |
| Confidence interval (CI) | There is always some uncertainty in research. This is because a small group of patients is studied to predict the effects of a treatment on the wider population. The confidence interval is a way of expressing how certain we are about the findings from a study, using statistics. It gives a range of results that is likely to include the ‘true’ value for the population. The CI is usually stated as ‘95% CI’, which means that the range of values has a 95 in a 100 chance of including the ‘true’ value. For example, a study may state that ‘based on our sample findings, we are 95% certain that the ‘true’ population blood pressure is not higher than 150 and not lower than 110’. In such a case the 95% CI would be 110 to 150. A wide confidence interval indicates a lack of certainty about the true effect of the test or treatment – often because a small group of patients has been studied. A narrow confidence interval indicates a more precise estimate (for example, if a large number of patients have been studied). |
| Confounding factor | Something that influences a study and can result in misleading findings if it is not understood or appropriately dealt with. For example, a study of heart disease may look at a group of people that exercises regularly and a group that does not exercise. If the ages of the people in the 2 groups are different, then any difference in heart disease rates between the 2 groups could be because of age rather than exercise. Therefore age is a confounding factor. |
| Consensus methods | Techniques used to reach agreement on a particular issue. Consensus methods may be used to develop NICE guidance if there is not enough good quality research evidence to give a clear answer to a question. Formal consensus methods include Delphi and nominal group techniques. |
| Control group | A group of people in a study who do not receive the treatment or test being studied. Instead, they may receive the standard treatment (sometimes called ‘usual care’) or a dummy treatment (placebo). The results for the control group are compared with those for a group receiving the treatment being tested. The aim is to check for any differences. Ideally, the people in the control group should be as similar as possible to those in the treatment group, to make it as easy as possible to detect any effects due to the treatment. |
| Cost–benefit analysis (CBA) | Cost–benefit analysis is one of the tools used to carry out an economic evaluation. The costs and benefits are measured using the same monetary units (for example, pounds sterling) to see whether the benefits exceed the costs. |
| Cost–consequences analysis (CCA) | Cost–consequences analysis is one of the tools used to carry out an economic evaluation. This compares the costs (such as treatment and hospital care) and the consequences (such as health outcomes) of a test or treatment with a suitable alternative. Unlike cost–benefit analysis or cost-effectiveness analysis, it does not attempt to summarise outcomes in a single measure (like the quality-adjusted life year) or in financial terms. Instead, outcomes are shown in their natural units (some of which may be monetary) and it is left to decision-makers to determine whether, overall, the treatment is worth carrying out. |
| Cost-effectiveness analysis (CEA) | Cost-effectiveness analysis is one of the tools used to carry out an economic evaluation. The benefits are expressed in non-monetary terms related to health, such as symptom-free days, heart attacks avoided, deaths avoided or life-years gained (that is, the number of years by which life is extended as a result of the intervention). |
| Cost-effectiveness model | An explicit mathematical framework, which is used to represent clinical decision problems and incorporate evidence from a variety of sources in order to estimate the costs and health outcomes. |
| Cost–utility analysis (CUA) | Cost–utility analysis is one of the tools used to carry out an economic evaluation. The benefits are assessed in terms of both quality and duration of life, and expressed as quality-adjusted life years (QALYs). See also utility. |
| Credible interval (CrI) | The Bayesian equivalent of a confidence interval. |
| Decision analysis | An explicit quantitative approach to decision-making under uncertainty, based on evidence from research. This evidence is translated into probabilities, and then into diagrams or decision trees which direct the clinician through a succession of possible scenarios, actions and outcomes. |
| Deterministic analysis | In economic evaluation, this is an analysis that uses a point estimate for each input. In contrast, see Probabilistic analysis. |
| Diagnostic odds ratio | The diagnostic odds ratio is a measure of the effectiveness of a diagnostic test. It is defined as the ratio of the odds of the test being positive if the subject has a disease relative to the odds of the test being positive if the subject does not have the disease. |
| Discounting | Costs and perhaps benefits incurred today have a higher value than costs and benefits occurring in the future. Discounting health benefits reflects individual preference for benefits to be experienced in the present rather than the future. Discounting costs reflects individual preference for costs to be experienced in the future rather than the present. |
| Disutility | The loss of quality of life associated with having a disease or condition. See Utility |
| Dominance | A health economics term. When comparing tests or treatments, an option that is both less effective and costs more is said to be ‘dominated’ by the alternative. |
| Drop-out | A participant who withdraws from a trial before the end. |
| Economic evaluation | An economic evaluation is used to assess the cost-effectiveness of healthcare interventions (that is, to compare the costs and benefits of a healthcare intervention to assess whether it is worth doing). The aim of an economic evaluation is to maximise the level of benefits – health effects – relative to the resources available. It should be used to inform and support the decision-making process; it is not supposed to replace the judgement of healthcare professionals. There are several types of economic evaluation: cost–benefit analysis, cost–consequences analysis, cost-effectiveness analysis, cost–minimisation analysis and cost–utility analysis. They use similar methods to define and evaluate costs, but differ in the way they estimate the benefits of a particular drug, programme or intervention. |
| Effect (as in effect measure, treatment effect, estimate of effect, effect size) | A measure that shows the magnitude of the outcome in one group compared with that in a control group. For example, if the absolute risk reduction is shown to be 5% and it is the outcome of interest, the effect size is 5%. The effect size is usually tested, using statistics, to find out how likely it is that the effect is a result of the treatment and has not just happened by chance (that is, to see if it is statistically significant). |
| Effectiveness | How beneficial a test or treatment is under usual or everyday conditions, compared with doing nothing or opting for another type of care. |
| Efficacy | How beneficial a test, treatment or public health intervention is under ideal conditions (for example, in a laboratory), compared with doing nothing or opting for another type of care. |
| Epidemiological study | The study of a disease within a population, defining its incidence and prevalence and examining the roles of external influences (for example, infection, diet) and interventions. |
| EQ-5D (EuroQol 5 dimensions) | A standardised instrument used to measure health-related quality of life. It provides a single index value for health status. |
| Evidence | Information on which a decision or guidance is based. Evidence is obtained from a range of sources including randomised controlled trials, observational studies, expert opinion (of clinical professionals or patients). |
| Exclusion criteria (literature review) | Explicit standards used to decide which studies should be excluded from consideration as potential sources of evidence. |
| Exclusion criteria (clinical study) | Criteria that define who is not eligible to participate in a clinical study. |
| Extended dominance | If Option A is both more clinically effective than Option B and has a lower cost per unit of effect, when both are compared with a do-nothing alternative, then Option A is said to have extended dominance over Option B. Option A is therefore more cost-effective and should be preferred, other things remaining equal. |
| Extrapolation | An assumption that the results of studies of a specific population will also hold true for another population with similar characteristics. |
| Follow-up | Observation over a period of time of an individual, group or initially defined population whose appropriate characteristics have been assessed in order to observe changes in health status or health-related variables. |
| Generalisability | The extent to which the results of a study hold true for groups that did not participate in the research. See also external validity. |
| Gold standard | A method, procedure or measurement that is widely accepted as being the best available to test for or treat a disease. |
| GRADE, GRADE profile | A system developed by the GRADE Working Group to address the shortcomings of present grading systems in healthcare. The GRADE system uses a common, sensible and transparent approach to grading the quality of evidence. The results of applying the GRADE system to clinical trial data are displayed in a table known as a GRADE profile. |
| Harms | Adverse effects of an intervention. |
| Health economics | Study or analysis of the cost of using and distributing healthcare resources. |
| Health-related quality of life (HRQoL) | A measure of the effects of an illness to see how it affects someone's day-to-day life. |
| Heterogeneity or Lack of homogeneity | The term is used in meta-analyses and systematic reviews to describe when the results of a test or treatment (or estimates of its effect) differ significantly in different studies. Such differences may occur as a result of differences in the populations studied, the outcome measures used or because of different definitions of the variables involved. It is the opposite of homogeneity. |
| Imprecision | Results are imprecise when studies include relatively few patients and few events and thus have wide confidence intervals around the estimate of effect. |
| Inclusion criteria (literature review) | Explicit criteria used to decide which studies should be considered as potential sources of evidence. |
| Incremental analysis | The analysis of additional costs and additional clinical outcomes with different interventions. |
| Incremental cost | The extra cost linked to using one test or treatment rather than another. Or the additional cost of doing a test or providing a treatment more frequently. |
| Incremental cost-effectiveness ratio (ICER) | The difference in the mean costs in the population of interest divided by the differences in the mean outcomes in the population of interest for one treatment compared with another. |
| Incremental net benefit (INB) | The value (usually in monetary terms) of an intervention net of its cost compared with a comparator intervention. The INB can be calculated for a given cost-effectiveness (willingness to pay) threshold. If the threshold is £20,000 per QALY gained then the INB is calculated as: (£20,000 × QALYs gained) – Incremental cost. |
| Indirectness | The available evidence is different to the review question being addressed, in terms of PICO (population, intervention, comparison and outcome). |
| Intention-to-treat analysis (ITT) | An assessment of the people taking part in a clinical trial, based on the group they were initially (and randomly) allocated to. This is regardless of whether or not they dropped out, fully complied with the treatment or switched to an alternative treatment. Intention-to-treat analyses are often used to assess clinical effectiveness because they mirror actual practice: that is, not everyone complies with treatment and the treatment people receive may be changed according to how they respond to it. |
| Intervention | In medical terms this could be a drug treatment, surgical procedure, diagnostic or psychological therapy. Examples of public health interventions could include action to help someone to be physically active or to eat a more healthy diet. |
| Intra-operative | The period of time during a surgical procedure. |
| Kappa statistic | A statistical measure of inter-rater agreement that takes into account the agreement occurring by chance. |
| Length of stay | The total number of days a participant stays in hospital. |
| Licence | See ‘Product licence’. |
| Life years gained | Mean average years of life gained per person as a result of the intervention compared with an alternative intervention. |
| Likelihood ratio | The likelihood ratio combines information about the sensitivity and specificity. It tells you how much a positive or negative result changes the likelihood that a patient would have the disease. The likelihood ratio of a positive test result (LR+) is sensitivity divided by (1 minus specificity). |
| Long-term care | Residential care in a home that may include skilled nursing care and help with everyday activities. This includes nursing homes and residential homes. |
| Logistic regression or Logit model | In statistics, logistic regression is a type of analysis used for predicting the outcome of a binary dependent variable based on one or more predictor variables. It can be used to estimate the log of the odds (known as the ‘logit’). |
| Loss to follow-up | A patient, or the proportion of patients, actively participating in a clinical trial at the beginning, but whom the researchers were unable to trace or contact by the point of follow-up in the trial |
| Markov model | A method for estimating long-term costs and effects for recurrent or chronic conditions, based on health states and the probability of transition between them within a given time period (cycle). |
| Meta-analysis | A method often used in systematic reviews. Results from several studies of the same test or treatment are combined to estimate the overall effect of the treatment. |
| Multivariate model | A statistical model for analysis of the relationship between 2 or more predictor (independent) variables and the outcome (dependent) variable. |
| Net monetary benefit (NMB) | The value in monetary terms of an intervention net of its cost. The NMB can be calculated for a given cost-effectiveness threshold. If the threshold is £20,000 per QALY gained then the NMB for an intervention is calculated as: (£20,000 × mean QALYs) – mean cost. The most preferable option (that is, the most clinically effective option to have an ICER below the threshold selected) will be the treatment with the highest NMB. |
| Network meta-analysis | A network meta-analysis is a method for simultaneously comparing multiple treatments in a single meta-analysis. |
| Number needed to treat (NNT) | The average number of patients who need to be treated to get a positive outcome. For example, if the NNT is 4, then 4 patients would have to be treated to ensure 1 of them gets better. The closer the NNT is to 1, the better the treatment. For example, if you give a stroke prevention drug to 20 people before 1 stroke is prevented, the number needed to treat is 20. See also number needed to harm, absolute risk reduction. |
| Observational study | Individuals or groups are observed or certain factors are measured. No attempt is made to affect the outcome. For example, an observational study of a disease or treatment would allow ‘nature’ or usual medical care to take its course. Changes or differences in one characteristic (for example, whether or not people received a specific treatment or intervention) are studied without intervening. There is a greater risk of selection bias than in experimental studies. |
| Odds ratio | Odds are a way to represent how likely it is that something will happen (the probability). An odds ratio compares the probability of something in one group with the probability of the same thing in another. An odds ratio of 1 between 2 groups would show that the probability of the event (for example a person developing a disease, or a treatment working) is the same for both. An odds ratio greater than 1 means the event is more likely in the first group. An odds ratio less than 1 means that the event is less likely in the first group. Sometimes probability can be compared across more than 2 groups – in this case, one of the groups is chosen as the ‘reference category’, and the odds ratio is calculated for each group compared with the reference category. For example, to compare the risk of dying from lung cancer for non-smokers, occasional smokers and regular smokers, non-smokers could be used as the reference category. Odds ratios would be worked out for occasional smokers compared with non-smokers and for regular smokers compared with non-smokers. See also confidence interval, relative risk, risk ratio. |
| Opportunity cost | The loss of other healthcare programmes displaced by investment in or introduction of another intervention. This may be best measured by the health benefits that could have been achieved had the money been spent on the next best alternative healthcare intervention. |
| Outcome | The impact that a test, treatment, policy, programme or other intervention has on a person, group or population. Outcomes from interventions to improve the public's health could include changes in knowledge and behaviour related to health, societal changes (for example, a reduction in crime rates) and a change in people's health and wellbeing or health status. In clinical terms, outcomes could include the number of patients who fully recover from an illness or the number of hospital admissions, and an improvement or deterioration in someone's health, functional ability, symptoms or situation. Researchers should decide what outcomes to measure before a study begins. |
| P value | The p value is a statistical measure that indicates whether or not an effect is statistically significant. For example, if a study comparing 2 treatments found that one seems more effective than the other, the p value is the probability of obtaining these results by chance. By convention, if the p value is below 0.05 (that is, there is less than a 5% probability that the results occurred by chance) it is considered that there probably is a real difference between treatments. If the p value is 0.001 or less (less than a 1% probability that the results occurred by chance), the result is seen as highly significant. If the p value shows that there is likely to be a difference between treatments, the confidence interval describes how big the difference in effect might be. |
| Peri-operative | The period from admission through surgery until discharge, encompassing the pre-operative and post-operative periods. |
| Placebo | A fake (or dummy) treatment given to participants in the control group of a clinical trial. It is indistinguishable from the actual treatment (which is given to participants in the experimental group). The aim is to determine what effect the experimental treatment has had – over and above any placebo effect caused because someone has received (or thinks they have received) care or attention. |
| Polypharmacy | The use or prescription of multiple medications. |
| Posterior distribution | In Bayesian statistics this is the probability distribution for a statistic based after combining established information or belief (the prior) with new evidence (the likelihood). |
| Post-operative | Pertaining to the period after patients leave the operating theatre, following surgery. |
| Power (statistical) | The ability to demonstrate an association when one exists. Power is related to sample size; the larger the sample size, the greater the power and the lower the risk that a possible association could be missed. |
| Pre-operative | The period before surgery commences. |
| Pre-test probability | In diagnostic tests: the proportion of people with the target disorder in the population at risk at a specific time point or time interval. Prevalence may depend on how a disorder is diagnosed. |
| Prevalence | See Pre-test probability. |
| Prior distribution | In Bayesian statistics, this is the probability distribution for a statistic based on previous evidence or belief. |
| Primary care | Healthcare delivered outside hospitals. It includes a range of services provided by GPs, nurses, health visitors, midwives and other healthcare professionals and allied health professionals such as dentists, pharmacists and opticians. |
| Primary outcome | The outcome of greatest importance, usually the one in a study that the power calculation is based on. |
| Probabilistic analysis | In economic evaluation, this is an analysis that uses a probability distribution for each input. In contrast, see Deterministic analysis. |
| Product licence | An authorisation from the MHRA to market a medicinal product. |
| Prognosis | A probable course or outcome of a disease. Prognostic factors are patient or disease characteristics that influence the course. Good prognosis is associated with low rate of undesirable outcomes; poor prognosis is associated with a high rate of undesirable outcomes. |
| Prospective study | A research study in which the health or other characteristic of participants is monitored (or ‘followed up’) for a period of time, with events recorded as they happen. This contrasts with retrospective studies. |
| Publication bias | Publication bias occurs when researchers publish the results of studies showing that a treatment works well and don't publish those showing it did not have any effect. If this happens, analysis of the published results will not give an accurate idea of how well the treatment works. This type of bias can be assessed by a funnel plot. |
| Quality of life | See ‘Health-related quality of life’. |
| Quality-adjusted life year (QALY) | A measure of the state of health of a person or group in which the benefits, in terms of length of life, are adjusted to reflect the quality of life. One QALY is equal to 1 year of life in perfect health. QALYS are calculated by estimating the years of life remaining for a patient following a particular treatment or intervention and weighting each year with a quality of life score (on a scale of 0 to 1). It is often measured in terms of the person's ability to perform the activities of daily life, freedom from pain and mental disturbance. |
| Randomisation | Assigning participants in a research study to different groups without taking any similarities or differences between them into account. For example, it could involve using a random numbers table or a computer-generated random sequence. It means that each individual (or each group in the case of cluster randomisation) has the same chance of receiving each intervention. |
| Randomised controlled trial (RCT) | A study in which a number of similar people are randomly assigned to 2 (or more) groups to test a specific drug or treatment. One group (the experimental group) receives the treatment being tested, the other (the comparison or control group) receives an alternative treatment, a dummy treatment (placebo) or no treatment at all. The groups are followed up to see how effective the experimental treatment was. Outcomes are measured at specific times and any difference in response between the groups is assessed statistically. This method is also used to reduce bias. |
| RCT | See ‘Randomised controlled trial’. |
| Receiver operated characteristic (ROC) curve | A graphical method of assessing the accuracy of a diagnostic test. Sensitivity is plotted against 1 minus specificity. A perfect test will have a positive, vertical linear slope starting at the origin. A good test will be somewhere close to this ideal. |
| Reference standard | The test that is considered to be the best available method to establish the presence or absence of the outcome – this may not be the one that is routinely used in practice. |
| Relative risk (RR) | The ratio of the risk of disease or death among those exposed to certain conditions compared with the risk for those who are not exposed to the same conditions (for example, the risk of people who smoke getting lung cancer compared with the risk for people who do not smoke). If both groups face the same level of risk, the relative risk is 1. If the first group had a relative risk of 2, subjects in that group would be twice as likely to have the event happen. A relative risk of less than one means the outcome is less likely in the first group. Relative risk is sometimes referred to as risk ratio. |
| Reporting bias | See ‘Publication bias’. |
| Resource implication | The likely impact in terms of finance, workforce or other NHS resources. |
| Retrospective study | A research study that focuses on the past and present. The study examines past exposure to suspected risk factors for the disease or condition. Unlike prospective studies, it does not cover events that occur after the study group is selected. |
| Review question | In guideline development, this term refers to the questions about treatment and care that are formulated to guide the development of evidence-based recommendations. |
| Secondary outcome | An outcome used to evaluate additional effects of the intervention deemed a priori as being less important than the primary outcomes. |
| Selection bias | Selection bias occurs if:
|
| Sensitivity | How well a test detects the thing it is testing for. If a diagnostic test for a disease has high sensitivity, it is likely to pick up all cases of the disease in people who have it (that is, give a ‘true positive’ result). But if a test is too sensitive it will sometimes also give a positive result in people who don't have the disease (that is, give a ‘false positive’). For example, if a test were developed to detect if a woman is 6 months pregnant, a very sensitive test would detect everyone who was 6 months pregnant, but would probably also include those who are 5 and 7 months pregnant. If the same test were more specific (sometimes referred to as having higher specificity), it would detect only those who are 6 months pregnant, and someone who was 5 months pregnant would get a negative result (a ‘true negative’). But it would probably also miss some people who were 6 months pregnant (that is, give a ‘false negative’). Breast screening is a ‘real-life’ example. The number of women who are recalled for a second breast screening test is relatively high because the test is very sensitive. If it were made more specific, people who don't have the disease would be less likely to be called back for a second test but more women who have the disease would be missed. |
| Sensitivity analysis | A means of representing uncertainty in the results of economic evaluations. Uncertainty may arise from missing data, imprecise estimates or methodological controversy. Sensitivity analysis also allows for exploring the generalisability of results to other settings. The analysis is repeated using different assumptions to examine the effect on the results. One-way simple sensitivity analysis (univariate analysis): each parameter is varied individually in order to isolate the consequences of each parameter on the results of the study. Multi-way simple sensitivity analysis (scenario analysis): 2 or more parameters are varied at the same time and the overall effect on the results is evaluated. Threshold sensitivity analysis: the critical value of parameters above or below which the conclusions of the study will change are identified. Probabilistic sensitivity analysis: probability distributions are assigned to the uncertain parameters and are incorporated into evaluation models based on decision analytical techniques (for example, Monte Carlo simulation). |
| Significance (statistical) | A result is deemed statistically significant if the probability of the result occurring by chance is less than 1 in 20 (p<0.05). |
| Specificity | The proportion of true negatives that are correctly identified as such. For example in diagnostic testing the specificity is the proportion of non-cases correctly diagnosed as non-cases. See related term ‘Sensitivity’. In terms of literature searching a highly specific search is generally narrow and aimed at picking up the key papers in a field and avoiding a wide range of papers. |
| Stakeholder | An organisation with an interest in a topic that NICE is developing a clinical guideline or piece of public health guidance on. Organisations that register as stakeholders can comment on the draft scope and the draft guidance. Stakeholders may be:
|
| State transition model | See Markov model |
| Systematic review | A review in which evidence from scientific studies has been identified, appraised and synthesised in a methodical way according to predetermined criteria. It may include a meta-analysis. |
| Time horizon | The time span over which costs and health outcomes are considered in a decision analysis or economic evaluation. |
| Transition probability | In a state transition model (Markov model), this is the probability of moving from one health state to another over a specific period of time. |
| Treatment allocation | Assigning a participant to a particular arm of a trial. |
| Univariate | Analysis which separately explores each variable in a data set. |
| Utility | In health economics, a ‘utility’ is the measure of the preference or value that an individual or society places upon a particular health state. It is generally a number between 0 (representing death) and 1 (perfect health). The most widely used measure of benefit in cost–utility analysis is the quality-adjusted life year, but other measures include disability-adjusted life years (DALYs) and healthy year equivalents (HYEs). |
22.2. Clinical Glossary
| Term | Definition |
|---|---|
| Active bleeding | Also known as or related to haemorrhage, loss of blood, bleeding (finding), haemorrhage, bleeding |
| Acute coronary syndrome | An acute coronary syndrome occurs when coronary blood flow cannot meet the heart’s oxygen requirement, either because a coronary blood vessel is occluded or when coronary blood flow is insufficient. This can occur in patients with a primary cardiac event, but might also affect patients with chronic coronary disease in whom other factors decrease coronary blood flow, such as shock or hypotension. |
| Allogeneic | From another member of the same species |
| Antifibrinolytics | Antifibrinolytics inhibit the activation of plasminogen to plasmin, prevent the break-up of fibrin and maintain clot stability. They are used to prevent excessive bleeding. |
| Autologous | Obtained from the same individual. |
| Allogenic | A transplant where the donated material comes from different (although often related) individuals than the recipients. |
| Anaemia | A condition where a lack of iron in the body leads to a reduction in the number of red blood cells. |
| Aplastic anaemia | Inability of stem cells to generate mature blood cells, resulting in deficiency of red blood cells, white blood cells and platelets |
| Arthroplasty | Surgical repair of a joint |
| Autoimmune thrombocytopenia | A disorder of low blood platelet counts in which platelets are destroyed by antibodies produced by the immune system. |
| Bacteraemia | The presence of bacteria in the blood. |
| Blood component | A therapeutic component of human blood (red cells, white cells, platelets, plasma and cryoprecipitate) |
| Blood product | Any therapeutic product derived from human whole blood or plasma donations (for example, prothrombin complex concentrate) |
| Cell salvage | Cell salvage is a process that collects blood from an operating site. This blood is then processed in a cell salvage machine and given back to the patient. This type of blood transfusion where the patient receives their own blood back is called autologous transfusion. |
| Cryoprecipitate | A source of fibrinogen, vital to blood clotting. |
| Erythropoietin | A glycoprotein hormone that controls erythropoiesis, or red blood cell production. |
| Fibrinogen | A glycoprotein that helps in the formation of blood clots. |
| Fibrinolysis | A process within the body that prevents blood clots that occur naturally from growing and causing problems. |
| Fresh frozen plasma | The remaining serum of human blood that is frozen after the cellular component has been removed for blood transfusion. |
| Functional Iron Deficiency | An inadequate iron supply to the bone marrow in the presence of storage iron. Seen in patients with renal failure who require parenteral iron therapy to respond to administered erythropoietin to correct anaemia. |
| Genitourinary | The organ system of the reproductive organs and the urinary system. |
| Haematemesis | The vomiting of blood. |
| Haematuria | The presence of red blood cells (erythrocytes) in the urine. |
| Haemoglobin | The iron-containing oxygen-transport metalloprotein in red blood cells. |
| Haemolysis | The rupturing of erythrocytes (red blood cells) and the release of their contents (cytoplasm) into surrounding fluid. |
| Haemopoietic stem cell transplant | IV infusion of autologous or allogeneic stem cells collected from the bone marrow, peripheral blood or umbilical cord blood to replenish haematopoietic function in patients whose bone marrow or immune system is damaged or ineffective. |
| Haemoptysis | Haemoptysis is the coughing of blood originating from the respiratory tract below the level of the larynx. |
| Haemostatic | Retarding or stopping the flow of blood within the blood vessels. |
| Haemostasis | A process which causes bleeding to stop, meaning to keep blood within a damaged blood vessel |
| International normalised ratio (INR) | A laboratory test measure of blood coagulation, based on prothrombin time. |
| Iron deficiency anaemia | A condition where a lack of iron in the body leads to a reduction in the number of red blood cells. |
| Major haemorrhage | The loss of more than 1 blood volume within 24 hours (around 70 mL/kg, or more than 5 litres in a 70 kg adult). |
| Myelodysplasia | Ineffective production of red blood cells, white blood cells and platelets. |
| Myocardial infarction | Heart attack. |
| Nosocomial infections | Infections occurring within 48 hours of hospital admission, 3 days of discharge or 30 days of an operation. |
| Platelets | Blood cells whose function (along with coagulation factors) is to stop bleeding. |
| Pulmonary oedema | An excess collection of watery fluid in the lungs. |
| Septicaemia | Septicaemia (another name for blood poisoning) refers to invasion of bacteria into the bloodstream and this occurs as part of sepsis. |
| Severe bleeding | Bleeding which includes blood gushing or spraying from the wound and not clotting. |
| Thrombocytopenic | A disorder in which there is a relative decrease of thrombocytes, commonly known as platelets, present in the blood. |
| Thromboembolism | Formation in a blood vessel of a clot (thrombus) that breaks loose and is carried by the blood stream to plug another vessel. |
| Thrombosis | The formation of a blood clot inside a blood vessel, obstructing the flow of blood through the circulatory system. |
| Thrombotic thrombocytopenic purpura | A rare disorder of the blood-coagulation system, causing extensive microscopic clots to form in the small blood vessels throughout the body. |
| Tranexamic acid | An antifibrinolytic agent which promotes blood clotting. |
| Variant Creutzfeldt-Jakob disease | A rare, degenerative, fatal brain disorder. |
| Vascular | The body's network of blood vessels. |
| WHO Grade 1 | Grade 1 petechial (broken capillary blood vessels) bleeding. |
| WHO Grade 2 | Grade 2 mild blood loss (clinically significant). |
| WHO Grade 3 | Grade 3 gross blood loss, requires transfusion (severe). |
| WHO Grade 4 | Grade 4 debilitating blood loss, retinal or cerebral, associated with fatality. |
- Glossary - Blood TransfusionGlossary - Blood Transfusion
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