Title: Delayed antibiotic prescribing for respiratory tract infections - an evidence synthesis of individual patient data
Funder: Department of Health and Social Care

Abstract: Background: Between 2010 and 2013, antibiotic prescribing in primary care rose by 4.1%. Antibiotic prescribing in primary care for respiratory tract infections is common, and mostly unjustifiable since most infections are self- limiting, symptomatic benefit from antibiotics is modest and complications are rare. With major public health concerns about anti-microbial resistance and calls to prevent the overuse of antibiotics, suitable strategies are needed to reduce especially antibiotic use in primary care which is where most antibiotic are prescribed. Delayed prescribing can be a useful strategy, as it allows the patient to collect an antibiotic prescription if their symptoms do not improve in the days following the consultation. This &ldquo;wait and see&rdquo; approach can strike a balance between reducing antibiotic prescribing and providing a safety net for those patients who do not improve or worsen. A recent Cochrane review concluded that a delayed prescribing strategy was not significantly different to immediate prescribing in terms of clinical outcomes for cough and cold. For acute otitis media and sore throat immediate antibiotics were more effective than delayed for fever, pain and malaise in some studies. But the review noted a high level of heterogeneity between studies made combining them in a meta-analysis difficult and did not allow sufficient power for the examination of subgroups (Spurling et al). Moreover the review included only randomised trials, not observational studies. An individual patient data (IPD) meta-analysis is considered the gold standard" for meta-analysis and undertaking such an analysis would allow questions to be answered that cannot be answered using aggregate data or any single dataset. Design: Individual patient data meta-analysis of both randomised controlled trials and observational studies. Objectives: 1) To use individual patient data from both RCTs and observational studies to calculate key outcome measures (duration of illness, severity of illness, probability of developing complications/requiring reconsultation side effects and patient satisfaction), giving more robust estimates of the clinical effectiveness of a delayed prescribing strategy. 2) To explore whether there are interactions between the treatment group and certain key subgroups, informed by the literature. This will enable us to determine whether there are subgroups of patients who can be identified by their baseline presentation as not being suitable candidates for delayed or no prescribing and therefore assisting GPs in making more appropriate prescribing decisions for individual patients presenting with an RTI. 3) To determine symptom trajectories in patients who do not take antibiotics, allowing GPs to better advise patients on the average duration of time until symptoms settle 4) To estimate the costs of antibiotic use for patient with respiratory trace infection and investigate any potential cost savings of delayed antibiotic prescriptions"

Lay abstract: Resistance to antibiotics is rising and there is concern that in future antibiotics may not be effective to treat life threatening infections. We need to look for ways to reduce antibiotic prescribing, whilst still ensuring that patients who really need treatment get it. One of the ways to do this is by issuing a patient with a &ldquo;delayed&rdquo; or &ldquo;just in case&rdquo; prescription. In this case the doctor issues a prescription but asks the patient to wait to see whether they start to feel better before taking it to the pharmacy to fill it. Some studies have shown that this is safe and effective at reducing the number of antibiotic prescriptions issued when we look at the general population. However, these studies are too small to look at subgroups of patients, such as children, older people, and those with long term health conditions. Our proposal is to combine all the studies that have been done in a single analysis, called an individual patient data (IPD) meta-analysis. This approach provides the highest standard of evidence. The resulting large dataset will enable us to look at these key subgroups to see whether delayed prescriptions were as safe for them as not getting any prescription or being given a prescription to fill immediately. We will also be able to describe the average time to recovery in patients who were not given a prescription. With this research we can help ensure that GPs only prescribe antibiotics, and potentially expose people to side effects, if they truly would benefit. We can help patients to better understand how long it is likely to take them to feel better without antibiotics. By targeting antibiotics at those patients who need them most, when they need them, we can help to ensure that antibiotics remain effective into the future.

Research activity codes: 8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: INFECTION