Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy.

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Clinical trials of pharmacological interventions for SARS-CoV-2 published in leading medical journals report adherence but not how it was assessed.

AIMS: Adherence to pharmacological interventions in clinical trials is crucial for accurate identification of beneficial and adverse outcomes. The ways in which adherence to interventions should be reported in trial publications are described in the Template for Intervention Description and Replication (TIDieR), a 12-item extension of the Consolidated Standards of Reporting Trials reporting guidelines. The objective of this study was to assess compliance with TIDieR Items 11 and 12 of randomized controlled trials (RCTs) of interventions in SARS-CoV-2 infection published in 5 selected journals during 2021. METHODS: We assessed pharmacological interventions for SARS-CoV-2 infection reported in RCTs published in 2021 in the Annals of Internal Medicine, The BMJ, JAMA, The Lancet and The New England Journal for Medicine for compliance with TIDieR items addressing intervention adherence (Items 11 and 12). We calculated proportional adherence for pharmacological and comparator interventions where available. RESULTS: We found 75 eligible RCTs. Twenty-eight (37%) reported results of SARS-CoV-2 vaccinations. Compliance with Items 11 and 12 could be assessed in 71 of these 75. Of the 71 RCTs, 37 (52%) reported how adherence was assessed (Item 11), and 70 reported adherence rates (Item 12). Only 1 of the 71 RCTs (1.4%, 0-7.6%) fully complied with TIDieR Items 11 and 12. CONCLUSION: Half of RCTs of SARS-CoV-2 pharmacological interventions published in leading medical journals in 2021 complied with reporting of how adherence assessments were made and almost none complied with both TIDieR Items 11 and 12. The implications for interpretation, application and replication of findings based on these publications warrant consideration.

The British Journal of Clinical Pharmacology: The first 50 years.

The British Journal of Clinical Pharmacology celebrates its 50th anniversary of publication in 2023. Here four previous Editors-in-Chief and the current Editor reflect on the Journal's history and the changes that have occurred during that time.

Medicines legislation and regulation in the United Kingdom 1500-2020.

The initial purposes of regulation of medicines in England, and latterly in the United Kingdom, were principally to raise government revenue, to discourage murder by poisoning and to regulate the activities of pharmacists. It was only much later that regulators sought to ensure that medicines were of good quality, reasonably safe, and at least somewhat effective, and to curtail misuse of drugs. Here we survey the history of the regulation of medicines and poisons in England from the perspective of clinicians with an interest in therapeutics.

Drug shortages. Part 1. Definitions and harms.

Drug shortages are repeatedly in the news. The earliest drug shortages were reported during the First World War, but the numbers of shortages have increased in recent years. In the first part of this two-part review, we discuss definitions of drug shortages and so-called stockouts, which are localized shortages, and the harms that they can cause. Drug shortages make it difficult or impossible to meet the therapeutic needs of individual patients or populations, but we lack an adequate definition. The problems are too complicated to be encompassed in a brief intensional dictionary-style definition, and that is reflected in the many different attempts at definition that have been proposed. We therefore propose an extensional operational definition that incorporates the processes by which products are manufactured, the causes of shortages and the contributory factors. A definition of this sort allows one to identify the main causes of a particular drug shortage and therefore the remedies that might prevent, mitigate or manage it. In the second part of the review we discuss the causes and solutions in more detail. Adverse drug reactions and medication errors attributable to shortages occur but are not often reported. Adverse reactions to substitute medicines are possible, and errors can occur because of unfamiliarity or unnecessary treatment with replacement medicines. Other harmful outcomes include withdrawal reactions, undertreatment, treatment delays and cancellations, failure of alternatives and disruption of clinical trials.

Drug shortages. Part 2: Trends, causes and solutions.

Drug shortages make it difficult or impossible to meet the therapeutic needs of individual patients or populations. In the first part of this review we proposed an operational definition that incorporates the processes by which products are manufactured, the causes of shortages and stock-outs (local shortages), and the contributory factors. Here we discuss causes and possible solutions. Drug shortages have complex causes, and a single cause cannot always be identified. Reasons include lack or shortage of raw materials, manufacturing difficulties, regulatory and political actions, voluntary recalls, just-in-time inventory systems, halts in production for financial or other business reasons, low demand (eg, orphan products, reduced usage), mergers, market shifts (eg, diversion to home markets) and unexpected increases in demand (eg, improved diagnosis, new trial information, epidemics and pandemics, inappropriate use, off-label use). Potential solutions are as diverse as the potential causes. Prevention is hard, because shortages are not easily predicted. Everyone in the supply chain is involved in anticipating and managing shortages, with responsibilities for preventing them or at least trying to mitigate their effects. This includes manufacturers and suppliers, particularly of generic formulations, pharmacists, prescribers, patients and governments. Solutions can therefore be linked to the causes and classified according to where the responsibility for implementing them lies.

A framework for understanding sources of bias in medication adherence research.

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

Preventable deaths involving opioids in England and Wales, 2013-2022: a systematic case series of coroners' reports.

BACKGROUND: Opioid deaths have increased in England and Wales. Coroners' Prevention of Future Deaths reports (PFDs) provide important insights that may enable safer use and avert harms, yet reports implicating opioids have not been synthesized. We aimed to identify opioid-related PFDs and explore coroners' concerns to prevent future deaths. METHODS: In this systematic case series, we screened 3897 coronial PFDs dated between 01 July 2013 and 23 February 2022, obtained by web scraping the UK's Courts and Tribunals Judiciary website. PFDs were included when an opioid was implicated in the death. Included PFDs were descriptively analysed, and content analysis was used to assess concerns reported by coroners. RESULTS: Opioids were involved in 219 deaths reported in PFDs (5·6% of PFDs), equating to 4418 years of life lost (median 33 years/person). Morphine (29%), methadone (23%) and diamorphine (16%) were the most common implicated opioids. Coroners most frequently raised concerns regarding systems and protocols (52%) or safety issues (15%). These concerns were most often addressed to National Health Service (NHS) organizations (51%), but response rates were low overall (47%). CONCLUSIONS: Opioids could be used more safely if coroners' concerns in PFDs were addressed by national organizations such as NHS bodies, government agencies and policymakers, as well as individual prescribing clinicians.

The problem of look-alike, sound-alike name errors: Drivers and solutions.

Look-alike or sound-alike (LASA) medication names may be mistaken for each other, e.g. mercaptamine and mercaptopurine. If an error of this sort is not intercepted, it can reach the patient and may result in harm. LASA errors occur because of shared linguistic properties between names (phonetic or orthographic), and potential for error is compounded by similar packaging, tablet appearance, tablet strength, route of administration or therapeutic indication. Estimates of prevalence range from 0.00003 to 0.0022% of all prescriptions, 7% of near misses, and between 6.2 and 14.7% of all medication error events. Solutions to LASA errors can target people or systems, and include reducing interruptions or distractions during medication administration, typographic tweaks, such as selective capitalization (Tall Man letters) or boldface, barcoding, and computerized physician order entry.

The Oxford Catalogue of Opioids: A systematic synthesis of opioid drug names and their pharmacology.

AIM: The growing demand for analgesia, coupled with an increasing need to treat opioid dependence and overdose, has escalated the development of novel opioids. We aimed to quantify the number of opioid drugs developed and to catalogue them based on their pharmacology. METHODS: We conducted a systematic search of seven sources in November 2020, including the WHO's Anatomical Therapeutic Classification index, the British National Formulary, the IUPHAR/BPS Guide to Pharmacology, the International Narcotics Control Board Index of Names of Narcotic Drugs, the WHO's International Nonproprietary Names MedNet service, Martindale's Extra Pharmacopoeia and the Merck Index, to include opioid drugs that targeted or had an effect or coeffect at one or more opioid receptors. We extracted chemical and nonproprietary names, drug stems, molecular formulas, molecular weights, receptor targets, actions at opioid receptors and classes based on their origins. We used descriptive statistics and calculated medians and interquartile ranges where appropriate. RESULTS: We identified 233 opioid drugs and created an online resource (https://www.catalogueofopioids.net/). There were 10 unique drug stems, and "-fentanil" accounted for one-fifth (20%) of all opioids. Most of the drugs (n = 133) targeted mu-opioid receptors and the majority (n = 191) were agonists at one or more receptors. Most (82%) were synthetic opioids, followed by semisynthetic opioids (16%) and alkaloids (3%). CONCLUSION: This catalogue centralizes and disseminates information that could assist researchers, prescribers and the public to improve the safe use of opioids.

A systematic literature review of LASA error interventions.

AIMS: The aim of this systematic review was to explore and evaluate the efficacy of interventions to reduce the prevalence of look-alike, sound-alike (LASA) medication name errors. METHODS: We conducted a systematic review of the literature, searching PubMed, EMBASE, Scopus and Web of Science up to December 2016, and re-ran the search in February 2020 for later results. We included studies of interventions to reduce LASA errors and included randomized controlled trials, controlled before-and-after studies, and interrupted time series. Details were registered in Prospero (ID: CRD42016048198). RESULTS: We identified six studies that fulfilled our inclusion criteria. All were conducted in laboratories. Given the diversity in the included studies, we did not conduct a meta-analysis and instead report the findings narratively. The only intervention explored in RCTs was capitalization of selected letters ("Tall Man"), for which we found limited efficacy and no consensus. CONCLUSIONS: Tall Man lettering is a marginally effective intervention to reduce LASA errors, with a number of caveats. We suggest that Tall Man gives rise to a "quasi-placebo effect", whereby a user derives more benefit from Tall Man lettering if they are aware of its purpose.

Factors associated with the prescribing of high-dose opioids in primary care: a systematic review and meta-analysis.

BACKGROUND: The risks of harms from opioids increase substantially at high doses, and high-dose prescribing has increased in primary care. However, little is known about what leads to high-dose prescribing, and studies exploring this have not been synthesized. We, therefore, systematically synthesized factors associated with the prescribing of high-dose opioids in primary care. METHODS: We conducted a systematic review of observational studies in high-income countries that used patient-level primary care data and explored any factor(s) in people for whom opioids were prescribed, stratified by oral morphine equivalents (OME). We defined high doses as ≥ 90 OME mg/day. We searched MEDLINE, Embase, Web of Science, reference lists, forward citations, and conference proceedings from database inception to 5 April 2019. Two investigators independently screened studies, extracted data, and appraised the quality of included studies using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. We pooled data on factors using random effects meta-analyses and reported relative risks (RR) or mean differences with 95% confidence intervals (CI) where appropriate. We also performed a number needed to harm (NNTH) calculation on factors when applicable. RESULTS: We included six studies with a total of 4,248,119 participants taking opioids, of whom 3.64% (n = 154,749) were taking high doses. The majority of included studies (n = 4) were conducted in the USA, one in Australia and one in the UK. The largest study (n = 4,046,275) was from the USA. Included studies were graded as having fair to good quality evidence. The co-prescription of benzodiazepines (RR 3.27, 95% CI 1.32 to 8.13, I2 = 99.9%), depression (RR 1.38, 95% CI 1.27 to 1.51, I2 = 0%), emergency department visits (RR 1.53, 95% CI 1.46 to 1.61, I2 = 0%, NNTH 15, 95% CI 12 to 20), unemployment (RR 1.44, 95% CI 1.27 to 1.63, I2 = 0%), and male gender (RR 1.21, 95% CI 1.14 to 1.28, I2 = 78.6%) were significantly associated with the prescribing of high-dose opioids in primary care. CONCLUSIONS: High doses of opioids are associated with greater risks of harms. Associated factors such as the co-prescription of benzodiazepines and depression identify priority areas that should be considered when selecting, identifying, and managing people taking high-dose opioids in primary care. Coordinated strategies and services that promote the safe prescribing of opioids are needed. STUDY REGISTRATION: PROSPERO, CRD42018088057.

Me-too pharmaceutical products: History, definitions, examples, and relevance to drug shortages and essential medicines lists.

We define a me-too drug as a pharmacologically active compound that is structurally related to a first-in-class compound, regarded as belonging to the same therapeutic class as the original compound, and used for the same therapeutic purposes, but which may differ in some respects, such as specificity of pharmacological action, adverse reactions profile, or drug-drug interactions. We also offer definitions of related terms, including follow-on drug and first-in-class. The therapeutic advantages of me-too drugs may include improved target specificity, reduced risks of off-target adverse reactions and drug-drug interactions, increased chance of benefit in some patients, and improved drug delivery and pharmacokinetics. Me-too drugs can also demonstrate incremental innovation. Their availability may help in coping with drug shortages. However, they may occasionally cause unexpected adverse reactions that are not class effects. Tricyclic antidepressants, ß-blockers, and statins illustrate the diversity of me-too drugs. Earlier compounds may be as effective as later ones, or more so. Tricyclic antidepressants have similar chemical structures, and compounds introduced after the first-in-class compound (imipramine) mostly offered little in the way of innovative features, but continue to be prescribed. In contrast, me-too ß-blockers introduced after the first-in-class compound, pronethalol, have diverse structures and display several innovative features. Stereoisomers and biosimilars/biobetters provide special examples of me-too drugs. Although many me-too drugs offer no significant advantages over their predecessors, over 60% of the drugs listed on the World Health Organization's essential list are me-toos. Different countries may choose different me-too drugs when constructing essential medicines lists, partly explaining transnational differences between them.

Naltrexone-bupropion (Mysimba) in management of obesity: A systematic review and meta-analysis of unpublished clinical study reports.

AIMS: To compare the benefits and harms of naltrexone-bupropion using evidence from clinical study reports. METHODS: We searched Food and Drug Administration and European Medicines Agency websites, PubMed, and Clinicaltrials.gov (May 2016) to identify pivotal trials; we then sent a freedom of information request to the European Medicines Agency (July 2016). We included pivotal, phase III placebo-controlled trials. We assessed the risks of bias using the Cochrane criteria, and the quality of the evidence using GRADE. We used a random-effects model for meta-analyses. RESULTS: Over a 27-month period (July 2016 to August 2018), we received 31 batches of clinical study report documents containing over 65 000 pages of data from 4 pivotal trials (n = 4536). Significantly more participants who took naltrexone-bupropion achieved ≥5% reduction in body weight: risk ratio (RR) = 2.1 (95% confidence interval 1.35-3.28), P = .001, GRADE = low, number needed to treat (NNT) to benefit = 5 (3-17); this represents a 2.53 kg (1.85-3.21) reduction in baseline body weight compared with placebo. Naltrexone-bupropion had significantly beneficial effects on other cardiovascular risk factors; however, the true effect sizes for these are uncertain because of incomplete outcome data. Naltrexone-bupropion significantly increased the risk of adverse events: RR = 1.11 (1.05-1.18, P = .0004, GRADE = low, NNT to harm = 12 7-27); serious adverse events: RR = 1.70 (1.38-2.1, P < .00001, GRADE = moderate, NNT to harm = 21 13-38); and discontinuation because of adverse events: RR = 1.92 (1.65-2.24, P < .00001, GRADE = moderate, NNT to discontinue treatment = 9 8-13). CONCLUSIONS: Naltrexone-bupropion significantly reduces body weight by a small amount but significantly increases the risk of adverse events. A rigorous process of postmarketing surveillance is required.

Correction to: Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature.

The original article [1] contains a minor error whereby the dates for year of first launch and year of first report of adverse reaction for iophendylate in e-Appendix Table 1 are mistakenly presented as 1946 and 1975 respectively.

Comparison of essential medicines lists in 137 countries.

OBJECTIVE: To compare the medicines included in national essential medicines lists with the World Health Organization's (WHO's) Model list of essential medicines, and assess the extent to which countries' characteristics, such as WHO region, size and health care expenditure, account for the differences. METHODS: We searched the WHO's Essential Medicines and Health Products Information Portal for national essential medicines lists. We compared each national list of essential medicines with both the 2017 WHO model list and other national lists. We used linear regression to determine whether differences were dependent on WHO Region, population size, life expectancy, infant mortality, gross domestic product and health-care expenditure. FINDINGS: We identified 137 national lists of essential medicines that collectively included 2068 unique medicines. Each national list contained between 44 and 983 medicines (median 310: interquartile range, IQR: 269 to 422). The number of differences between each country's essential medicines list and WHO's model list ranged from 93 to 815 (median: 296; IQR: 265 to 381). Linear regression showed that only WHO region and health-care expenditure were significantly associated with the number of differences (adjusted R2 : 0.33; P < 0.05). Most medicines (1248; 60%) were listed by no more than 10% (14) of countries. CONCLUSION: The substantial differences between national lists of essential medicines are only partly explained by differences in country characteristics and thus may not be related to different priority needs. This information helps to identify opportunities to improve essential medicines lists.

Susceptibility to adverse drug reactions.

The pharmacological effects of a drug depend on its concentration at the site of action, and therefore on the concentration in blood and on the dose. The relationship between the concentration or dose and the corresponding effect can usually be represented mathematically as a rectangular hyperbola; when effect is plotted against log concentration or log dose, the curve is sigmoidal. Inevitably, the effect size and the doses causing benefit and harm will differ among individuals, since they are biological phenomena: some individuals are more likely than others to suffer harm at any given dose. Some harmful effects can occur at much lower doses than those used in therapeutics; that is, the log dose-response curve for harm lies far to the left of the log dose-response curve for benefit. Those who suffer such reactions are hypersusceptible. When the dose-response curves for harm and therapeutic effect are in the same range, dose cannot separate the harmful effects from the therapeutic effects, and adverse reactions are collateral. Toxic effects occur when harmful doses are above the doses needed for benefit. In this review we consider factors that influence a subject's susceptibility to adverse drug reactions. Determinants of susceptibility include Immunological, Genetic, demographic (Age and Sex), Physiological and Exogenous factors (drug-drug interactions, for example), and Diseases and disorders such as renal failure, giving the mnemonic I GASPED. Some susceptibility factors are discrete (for example, all-or-none) and some are continuous; susceptibility can therefore be discrete or continuous; and the factors can interact to determine a person's overall susceptibility to harm.

The British Pharmacological Society's WDM Paton Memorial Lecture 2019: How doctors were informed about pharmaceutical products through advertising in the British Medical Journal from 1955/6 to 1985/6.

We have reviewed pharmaceutical advertisements in every available issue of the British Medical Journal (BMJ) in 12-month periods during 1955/6, 1965/6, 1975/6, and 1985/6. We have determined the amount of advertising, the therapeutic areas covered, and whether adverts reflected the large number of New Chemical Entities (NCEs) launched during that time. For each product we recorded the therapeutic indications, the marketing company, and the number of adverts appearing. The total number of products advertised fell from 340 in 1955/6 to 260 in 1965/6, 70 in 1975/6, and 16 in 1985/6. Advertisement numbers and companies advertising also fell. Antimicrobial drugs and cardiovascular drugs were the top products advertised over the 30 years, with respiratory, analgesic, and gastrointestinal drugs also in the top five. The number of different drugs advertised by individual companies fell from around eight per company in 1955/6 to one or two in 1985/6. There was good concordance between the most advertised therapeutic areas and NCEs entering the market. From the 1950s to the 1980s prescribers were extensively informed about pharmacological advances in therapeutics through BMJ advertisements. Many novel drugs that were advertised proved to be of lasting value. The Medicines Act 1968 introduced product licensing, regulations requiring demonstration of quality, efficacy, and safety, and restrictions on advertising. Subsequently many companies reduced their advertising or stopped altogether. Since advertising influences prescribing, and since antimicrobial drugs were the most commonly advertised products during 1955-86, we speculate that advertising, resulting in excess use, may have, at least partly, driven bacterial drug resistance.

Adverse events in people taking macrolide antibiotics versus placebo for any indication.

BACKGROUND: Macrolide antibiotics (macrolides) are among the most commonly prescribed antibiotics worldwide and are used for a wide range of infections. However, macrolides also expose people to the risk of adverse events. The current understanding of adverse events is mostly derived from observational studies, which are subject to bias because it is hard to distinguish events caused by antibiotics from events caused by the diseases being treated. Because adverse events are treatment-specific, rather than disease-specific, it is possible to increase the number of adverse events available for analysis by combining randomised controlled trials (RCTs) of the same treatment across different diseases. OBJECTIVES: To quantify the incidences of reported adverse events in people taking macrolide antibiotics compared to placebo for any indication. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), which includes the Cochrane Acute Respiratory Infections Group Specialised Register (2018, Issue 4); MEDLINE (Ovid, from 1946 to 8 May 2018); Embase (from 2010 to 8 May 2018); CINAHL (from 1981 to 8 May 2018); LILACS (from 1982 to 8 May 2018); and Web of Science (from 1955 to 8 May 2018). We searched clinical trial registries for current and completed trials (9 May 2018) and checked the reference lists of included studies and of previous Cochrane Reviews on macrolides. SELECTION CRITERIA: We included RCTs that compared a macrolide antibiotic to placebo for any indication. We included trials using any of the four most commonly used macrolide antibiotics: azithromycin, clarithromycin, erythromycin, or roxithromycin. Macrolides could be administered by any route. Concomitant medications were permitted provided they were equally available to both treatment and comparison groups. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted and collected data. We assessed the risk of bias of all included studies and the quality of evidence for each outcome of interest. We analysed specific adverse events, deaths, and subsequent carriage of macrolide-resistant bacteria separately. The study participant was the unit of analysis for each adverse event. Any specific adverse events that occurred in 5% or more of any group were reported. We undertook a meta-analysis when three or more included studies reported a specific adverse event. MAIN RESULTS: We included 183 studies with a total of 252,886 participants (range 40 to 190,238). The indications for macrolide antibiotics varied greatly, with most studies using macrolides for the treatment or prevention of either acute respiratory tract infections, cardiovascular diseases, chronic respiratory diseases, gastrointestinal conditions, or urogynaecological problems. Most trials were conducted in secondary care settings. Azithromycin and erythromycin were more commonly studied than clarithromycin and roxithromycin.Most studies (89%) reported some adverse events or at least stated that no adverse events were observed.Gastrointestinal adverse events were the most commonly reported type of adverse event. Compared to placebo, macrolides caused more diarrhoea (odds ratio (OR) 1.70, 95% confidence interval (CI) 1.34 to 2.16; low-quality evidence); more abdominal pain (OR 1.66, 95% CI 1.22 to 2.26; low-quality evidence); and more nausea (OR 1.61, 95% CI 1.37 to 1.90; moderate-quality evidence). Vomiting (OR 1.27, 95% CI 1.04 to 1.56; moderate-quality evidence) and gastrointestinal disorders not otherwise specified (NOS) (OR 2.16, 95% CI 1.56 to 3.00; moderate-quality evidence) were also reported more often in participants taking macrolides compared to placebo.The number of additional people (absolute difference in risk) who experienced adverse events from macrolides was: gastrointestinal disorders NOS 85/1000; diarrhoea 72/1000; abdominal pain 62/1000; nausea 47/1000; and vomiting 23/1000.The number needed to treat for an additional harmful outcome (NNTH) ranged from 12 (95% CI 8 to 23) for gastrointestinal disorders NOS to 17 (9 to 47) for abdominal pain; 19 (12 to 33) for diarrhoea; 19 (13 to 30) for nausea; and 45 (22 to 295) for vomiting.There was no clear consistent difference in gastrointestinal adverse events between different types of macrolides or route of administration.Taste disturbances were reported more often by participants taking macrolide antibiotics, although there were wide confidence intervals and moderate heterogeneity (OR 4.95, 95% CI 1.64 to 14.93; I² = 46%; low-quality evidence).Compared with participants taking placebo, those taking macrolides experienced hearing loss more often, however only four studies reported this outcome (OR 1.30, 95% CI 1.00 to 1.70; I² = 0%; low-quality evidence).We did not find any evidence that macrolides caused more cardiac disorders (OR 0.87, 95% CI 0.54 to 1.40; very low-quality evidence); hepatobiliary disorders (OR 1.04, 95% CI 0.27 to 4.09; very low-quality evidence); or changes in liver enzymes (OR 1.56, 95% CI 0.73 to 3.37; very low-quality evidence) compared to placebo.We did not find any evidence that appetite loss, dizziness, headache, respiratory symptoms, blood infections, skin and soft tissue infections, itching, or rashes were reported more often by participants treated with macrolides compared to placebo.Macrolides caused less cough (OR 0.57, 95% CI 0.40 to 0.80; moderate-quality evidence) and fewer respiratory tract infections (OR 0.70, 95% CI 0.62 to 0.80; moderate-quality evidence) compared to placebo, probably because these are not adverse events, but rather characteristics of the indications for the antibiotics. Less fever (OR 0.73, 95% 0.54 to 1.00; moderate-quality evidence) was also reported by participants taking macrolides compared to placebo, although these findings were non-significant.There was no increase in mortality in participants taking macrolides compared with placebo (OR 0.96, 95% 0.87 to 1.06; I² = 11%; low-quality evidence).Only 24 studies (13%) provided useful data on macrolide-resistant bacteria. Macrolide-resistant bacteria were more commonly identified among participants immediately after exposure to the antibiotic. However, differences in resistance thereafter were inconsistent.Pharmaceutical companies supplied the trial medication or funding, or both, for 91 trials. AUTHORS' CONCLUSIONS: The macrolides as a group clearly increased rates of gastrointestinal adverse events. Most trials made at least some statement about adverse events, such as "none were observed". However, few trials clearly listed adverse events as outcomes, reported on the methods used for eliciting adverse events, or even detailed the numbers of people who experienced adverse events in both the intervention and placebo group. This was especially true for the adverse event of bacterial resistance.