The infection fatality rate of COVID-19 can vary substantially across different locations and this may reflect differences in population age structure and case-mix of infected and deceased patients and other factors. The inferred infection fatality rates tended to be much lower than estimates made earlier in the pandemic.
Editorials21 February 2006Adverse Events: The More You Search, the More You FindJohn P.A. Ioannidis, MD, Cynthia D. Mulrow, MD, MSc, Deputy Editor, and Steven N. Goodman, MD, PhDJohn P.A. Ioannidis, MDFrom the University of Ioannina School of Medicine, Ioannina 45110, Greece; American College of Physicians, Philadelphia, PA 19106; and Johns Hopkins School of Medicine, Baltimore, MD 21205., Cynthia D. Mulrow, MD, MSc, Deputy EditorFrom the University of Ioannina School of Medicine, Ioannina 45110, Greece; American College of Physicians, Philadelphia, PA 19106; and Johns Hopkins School of Medicine, Baltimore, MD 21205., and Steven N. Goodman, MD, PhDFrom the University of Ioannina School of Medicine, Ioannina 45110, Greece; American College of Physicians, Philadelphia, PA 19106; and Johns Hopkins School of Medicine, Baltimore, MD 21205.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-144-4-200602210-00013 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail People want reliable information about potential harms of medications. Concerns about possible adverse effects guide therapy selections, and unpleasant surprises about unsuspected harms cause anxiety and make headlines (1). We often rely on compendia and product inserts for information about such effects. These materials offer litanies of possible adverse events, sometimes accompanied by an estimate of how often those events might occur. From whence are these estimates derived? What do they really mean? How can we better measure and understand how many and what kinds of harms may be caused by medications?Sources of Evidence about Medication-Related HarmsWe can ...References1. Topol EJ. Failing the public health—rofecoxib, Merck, and the FDA. N Engl J Med. 2004;351:1707-9. [PMID: 15470193] CrossrefMedlineGoogle Scholar2. Kaufman DW, Shapiro S. Epidemiological assessment of drug-induced disease. Lancet. 2000;356:1339-43. [PMID: 11073036] CrossrefMedlineGoogle Scholar3. Papanikolaopu PN, Christidi G, Ioannidis JPA. Large-scale evidence on harms of medical interventions: randomized, controlled trials versus observational studies. CMAJ [In press]. Google Scholar4. Lasser KE, Allen PD, Woolhandler SJ, Himmelstein DU, Wolfe SM, Bor DH. Timing of new black box warnings and withdrawals for prescription medications. JAMA. 2002;287:2215-20. [PMID: 11980521] CrossrefMedlineGoogle Scholar5. Bent S, Padula A, Avins AL. Brief communication: better ways to question patients about adverse medical events. A randomized, controlled trial. Ann Intern Med. 2006;144:257-61. LinkGoogle Scholar6. Hammer SM, Squires KE, Hughes MD, Grimes JM, Demeter LM, Currier JS, et al. A controlled trial of two nucleoside analogues plus indinavir in persons with human immunodeficiency virus infection and CD4 cell counts of 200 per cubic millimeter or less. AIDS Clinical Trials Group 320 Study Team. N Engl J Med. 1997;337:725-33. [PMID: 9287227] CrossrefMedlineGoogle Scholar7. Staszewski S, Morales-Ramirez J, Tashima KT, Rachlis A, Skiest D, Stanford J, et al. Efavirenz plus zidovudine and lamivudine, efavirenz plus indinavir, and indinavir plus zidovudine and lamivudine in the treatment of HIV-1 infection in adults. Study 006 Team. N Engl J Med. 1999;341:1865-73. [PMID: 10601505] CrossrefMedlineGoogle Scholar8. Götzsche PC. Non-steroidal anti-inflammatory drugs. BMJ. 2000;320:1058-61. [PMID: 10764369] CrossrefMedlineGoogle Scholar9. Ioannidis JP, Lau J. Completeness of safety reporting in randomized trials: an evaluation of 7 medical areas. JAMA. 2001;285:437-43. [PMID: 11242428] CrossrefMedlineGoogle Scholar10. Ioannidis JP, Evans SJ, Götzsche PC, O'Neill RT, Altman DG, Schulz K, et al. Better reporting of harms in randomized trials: an extension of the CONSORT statement. Ann Intern Med. 2004;141:781-8. [PMID: 15545678] LinkGoogle Scholar11. Jonville-Béra AP, Giraudeau B, Autret-Leca E. Reporting of drug tolerance in randomized clinical trials: when data conflict with authors' conclusions. Ann Intern Med. 2006;144:306-7. LinkGoogle Scholar12. Papanikolaou PN, Ioannidis JP. Availability of large-scale evidence on specific harms from systematic reviews of randomized trials. Am J Med. 2004;117:582-9. [PMID: 15465507] CrossrefMedlineGoogle Scholar13. Strand CV, Simon LS, Tugwell P, Brooks P, Boers M. OMERACT 7 International Consensus Conference on Outcome Measures in Rheumatology Clinical Trials. Introduction. Accessed at jrheum.com/archives/oct05.html on 10 January 2006. Google Scholar14. Bonhoeffer J, Kohl K, Chen R, Duclos P, Heijbel H, Heininger U, et al. The Brighton Collaboration: addressing the need for standardized case definitions of adverse events following immunization (AEFI). Vaccine. 2002;21:298-302. [PMID: 12450705] CrossrefMedlineGoogle Scholar15. Trotti A, Colevas AD, Setser A, Rusch V, Jaques D, Budach V, et al. CTCAE v3.0: development of a comprehensive grading system for the adverse effects of cancer treatment. Semin Radiat Oncol. 2003;13:176-81. [PMID: 12903007] CrossrefMedlineGoogle Scholar16. Venning GR. Identification of adverse reactions to new drugs. II—How were 18 important adverse reactions discovered and with what delays? Br Med J (Clin Res Ed). 1983;286:289-92. [PMID: 6218859] CrossrefMedlineGoogle Scholar17. Centers for Education and Research on Therapeutics Risk Assessment Workshop. Risk assessment of drugs, biologics and therapeutic devices: present and future issues. Pharmacoepidemiol Drug Saf. 2003;12:653-62. [PMID: 14762981] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From the University of Ioannina School of Medicine, Ioannina 45110, Greece; American College of Physicians, Philadelphia, PA 19106; and Johns Hopkins School of Medicine, Baltimore, MD 21205.Disclosures: None disclosed.Corresponding Author: John P.A. Ioannidis, MD, Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece; e-mail, [email protected]uoi.gr.Current Author Addresses: Dr. Ioannidis: Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece.Dr. Mulrow: American College of Physicians, 190 N. Independence Mall West, Philadelphia, PA 19106.Dr. Goodman: Division of Biostatistics, Johns Hopkins Sidney Kimmel Cancer Center, Suite 1103, 550 North Broadway, Baltimore, MD 21205. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoBrief Communication: Better Ways To Question Patients about Adverse Medical Events Stephen Bent , Amy Padula , and Andrew L. Avins Reporting of Drug Tolerance in Randomized Clinical Trials: When Data Conflict with Authors' Conclusions Annie Pierre Jonville-Béra , Bruno Giraudeau , and Elisabeth Autret-Leca Metrics Cited byProne position for acute respiratory failure in adultsInterpretation of chronic pain clinical trial outcomes: IMMPACT recommended considerationsCollecting dataSafety and risks of shiatsu: Protocol for a systematic reviewUnpleasant meditation-related experiences in regular meditators: Prevalence, predictors, and conceptual considerationsThe MethodsComparing Long-term Mortality After Carotid Endarterectomy vs Carotid Stenting Using a Novel Instrumental Variable Method for Risk Adjustment in Observational Time-to-Event DataThe reporting of harms in publications on randomized controlled trials funded by the "Programme Hospitalier de Recherche Clinique," a French academic funding schemeAdverse Events Following Cervical Disc Arthroplasty: A Systematic ReviewIdentifying Bias in Clinical Cancer ResearchWorking towards consensus on methods used to elicit participant-reported safety data in uncomplicated malaria clinical drug studies: a Delphi technique studyHyaluronic acid injection therapy for osteoarthritis of the knee: concordant efficacy and conflicting serious adverse events in two systematic reviewsAdverse Event Reporting in Clinical Trials of Intravenous and Invasive Pain Treatments: An ACTTION Systematic ReviewAdverse Effects of Psychotropic MedicationsVariation in adverse drug reactions listed in product information for antidepressants and anticonvulsants, between the USA and Europe: a comparison review of paired regulatory documentsReporting of adverse events and statistical details of efficacy estimates in randomized clinical trials of pain in temporomandibular disordersUnwirksamkeit, Schaden und nicht intendierte Folgen der Implementierung von InterventionenIntroductionSafety monitoringAdverse event reporting in nonpharmacologic, noninterventional pain clinical trials: ACTTION systematic reviewSunitinib adverse events in metastatic renal cell carcinoma: a meta-analysisHow experiences become data: the process of eliciting adverse event, medical history and concomitant medication reports in antimalarial and antiretroviral interaction trialsComparison of Pooled Risk Estimates for Adverse Effects from Different Observational Study Designs: Methodological OverviewAdverse event assessment, analysis, and reporting in recent published analgesic clinical trials: ACTTION systematic review and recommendationsOpen Issues in Intelligent Personal Health Record – An Updated Status Report for 2012Adverse event reporting in randomised controlled trials of neuropathic pain: Considerations for future practiceThiazolidinedione use and cancer incidence in type 2 diabetes: A systematic review and meta-analysisAdherence to CONSORT harms-reporting recommendations in publications of recent analgesic clinical trials: An ACTTION systematic reviewAnalysis of the three United States Food and Drug Administration investigational device exemption cervical arthroplasty trialsSafety and Tolerability of Varenicline Tartrate (Champix ® /Chantix ® ) for Smoking Cessation in HIV-Infected Subjects: A Pilot Open-Label StudyReal-life versus package insert: A post-marketing study on adverse-event rates of the virosomal hepatitis A vaccine Epaxal® in healthy travellersDifferent Black Box Warning Labeling for Same-Class DrugsMeta-analyses of Adverse Effects Data Derived from Randomised Controlled Trials as Compared to Observational Studies: Methodological OverviewPublikationsbias in Studien jenseits RCTSources of information on adverse effects: a systematic reviewMonitoring self-reported adverse events: A prospective, pilot study in a UK osteopathic teaching clinicWhy Most Discovered True Associations Are InflatedEvaluation of Early and Late Toxicities in Chemoradiation TrialsTAME: development of a new method for summarising adverse events of cancer treatment by the Radiation Therapy Oncology GroupStopping at Nothing? Some Dilemmas of Data Monitoring in Clinical TrialsSteven N. Goodman, MD, MHS, PhDThe safety of etanercept for the treatment of plaque psoriasisAdverse-event rates: journals versus databasesAntimicrobial-Associated QT Interval Prolongation: Pointes of InterestCurrent awareness: Pharmacoepidemiology and drug safetyHypothyroidism Associated with Quetiapine Therapy; Paradoxical Bronchospasm Associated with Albuterol; Alcohol Cravings with Paroxetine Therapy?; Lamotrigine-Induced Toxic Epidermal Necrolysis – Three Cases; Acute Lung Injury with Vinorelbine; Adverse Events Related to Epinephrine Use in Asthma Patients Seen in the Emergency Department; Collecting Information from Patients Having Adverse Events; New Anticonvulsants – New Adverse EffectsRecent Publications on Medications and PharmacySystemic Therapy for Breast Cancer: Using Toxicity Data to Inform Decisions 21 February 2006Volume 144, Issue 4Page: 298-300KeywordsAdverse eventsAdverse reactionsClinical epidemiologyClinical trialsDrugsEvidence based medicineObservational studiesToxicity ePublished: 21 February 2006 Issue Published: 21 February 2006 Copyright & PermissionsCopyright © 2006 by American College of Physicians. 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Abnormal urodynamic findings are common in boys with a history of posterior urethral valves. However, to our knowledge there are few reports on the results of treating these abnormal findings. We analyzed the treatment of abnormal urodynamic parameters and its outcome in 21 boys who underwent valve ablation.After valve ablation multichannel urodynamic studies were performed in 31 boys, including 21 in whom studies were done before and after therapy was started for abnormal parameters. Detrusor instability and impaired bladder compliance were treated with anticholinergics or augmentation cystoplasty, and impaired detrusor contractility was managed with clean intermittent catheterization.Before therapy 17 of 21 boys had impaired compliance and detrusor instability, 2 had impaired compliance without instability and 2 had instability alone. After treatment 8 boys had impaired compliance and 4 had detrusor instability. After anticholinergics were initiated new onset myogenic failure in 2 boys necessitated clean intermittent catheterization. Of the 13 patients who presented with urinary incontinence 10 became dry and 3 had improvement with therapy. Vesicoureteral reflux in 10 boys at the time of the initial urodynamic study resolved in 7 with anticholinergic medication and in 1 after clean intermittent catheterization was begun for severely impaired compliance. All 21 boys were treated with anticholinergics and 2 were ultimately treated with augmentation cystoplasty. Clean intermittent catheterization was also instituted in 5 patients, including the 2 who required clean intermittent catheterization after myogenic failure developed. Five boys with high voiding pressures were found to have outlet obstruction due to residual valve tissue in 2, bladder neck obstruction in 2 and urethral stricture in 1 despite normal flow rates in 2.Urodynamic studies are helpful in guiding therapy in boys after valve ablation. Anticholinergic therapy can improve compliance, decrease detrusor instability, improve continence and eliminate vesicoureteral reflux in the majority of boys, although there is an associated risk of myogenic failure. Flow rates and fluoroscopic voiding studies are often unable to detect outlet obstruction and must be obtained in conjunction with voiding pressure measurements to make this diagnosis.
Abstract Objectives To describe the differences between European Medicine Agency (EMA) Good Clinical Practice (GCP) inspection reports and medical literature on drugs with withdrawn or refused applications. Design A retrospective study comparing studies included in European Public Assessment Reports (EPARs) and the corresponding articles published in the medical literature. Data sources We screened all EPARs released by the EMA from inception to April 2024 for drugs that were refused or had a withdrawn application. In those EPARs, we looked for mentions of GCP inspections and details about them, then we searched for related publications on the inspected studies on bibliographic databases. Eligibility criteria All EPARs mentioning good clinical practice inspection were included in this survey. Data extracted Two reviewers independently gathered information on the GCP inspections and their findings, including the EMA’s opinion on their impact on the study data. The reviewers checked related publications for mentions of the inspection and any subsequent correction, retraction, or expressions of concern related to its findings. Main outcome measures The main outcome was the mention of the GCP inspection findings in the publication of the inspected studies. We also assessed whether there was any mention of these findings in a correction, retraction, or expression of concern. Results Out of 285 EPARs screened, 57 (20%) mentioned a GCP inspection. 58 distinct studies with inspections had 61 publications. For 17 publications the inspection occurred after the publication, for 20 the inspection happened before the publication, and for 24 the date of the inspection was unknown. Only 1 publication (2%) addressed the inspection findings. Moreover, there were no corrections, retractions, or expressions of concern related to inspection findings. Among the 61 publications, 26 (43%) were related with 24 distinct studies that had an inspection that casted doubts on data reliability, but none mentioned the inspections at or after the time of publication. Conclusions This meta-research survey indicates that health authorities’ GCP inspections are not reflected in the published literature, even when the inspections have put the data reliability in doubt. Journals should clearly specify which aspects of those studies are trustworthy and which ones are not. Trial registration osf.io/pa9fq/
We agree with Dr. Hiatt that epidemiology belongs at the epicenter of translation (1), especially when integration of knowledge across disciplines is required to create the scientific basis for societal change. Although we recognize his concern that the “proliferation of T's” could get out of hand, we believe that our more granular description of translation helps to highlight epidemiology's role beyond the identification of risk factors (2). Unfortunately, the thesis that epidemiology is at the epicenter of translation science is not universally shared. Although it is difficult to think of any medical progress that really saved lives and has not required a key contribution from epidemiology, no Nobel Prize has ever been awarded to an epidemiologist (3). In a recent 37-chapter authoritative textbook entitled Clinical and Translational Science (4), we had to wait until chapter 35 to read an introduction to epidemiology, which relegates the contributions of epidemiology to an afterthought in the translational sciences. One wonders whether the oft-lamented lack of successes in translational research is due to the lack of wider understanding of epidemiologic methods among researchers of diverse disciplines. As Hiatt affirms, the point is that epidemiology has a central role throughout the translation continuum, regardless of what the overlapping phases are called. Epidemiologists come in all kinds of flavors. Some practice discovery research almost exclusively; others focus on development of evidence-based guidelines. Still more are engaged in clinical and public health practice, developing and implementing programs and measuring health impact at the national, state, and local levels. Their work is to measure factors that facilitate and impede the integration of proven interventions into practice (T3) and to assess the effectiveness of interventions in reducing morbidity and mortality at the population level (T4). Because both process and outcome measures are needed to evaluate interventions, T3 and T4 obviously overlap. Often T3 data are available years, if not decades, before T4 data, and the sources of data and methods used may differ. For example, surveillance systems are mainstays of public health programs that evaluate both process indicators, such as trends in the prevalence of cigarette smoking in the Behavioral Risk Factor Surveillance System (5), and outcome indicators, such as trends in lung cancer incidence using Surveillance, Epidemiology, and End Results (SEER) or state-based cancer registries (6). Many discoveries may look promising, managing to survive through T1 and T2 evaluations, and become widely accepted in medicine and public health only to be proven ineffective and harmful (7, 8). T3 assessments alone (collecting process indicators) would simply enhance wasted efforts, while T4 research can offer valuable hints that we have been misled and/or inform new discoveries (T0). Our reason for highlighting T3 and T4 is not to create new niches or to divide disciplines but to spotlight epidemiology as a common thread along the entire translation continuum. Our quick review of the Journal publications suggests much less emphasis on T3 and T4 compared with discovery and early translation. Our bottom line is simple. The road to translation is long and arduous. We need to cross all the T's even though we may disagree on what to call them. Epidemiologists should play a much larger role in this enterprise in academic, clinical, or public health practice settings.
ABSTRACT Space medicine is a vital discipline with often time-intensive and costly projects and constrained opportunities for studying various elements such as space missions, astronauts, and simulated environments. Moreover, private interests gain increasing influence in this discipline. In scientific disciplines with these features, transparent and rigorous methods are essential. Here, we undertook an evaluation of transparency indicators in publications within the field of space medicine. A meta-epidemiological assessment of PubMed Central Open Access (PMC OA) eligible articles within the field of space medicine was performed for prevalence of code sharing, data sharing, pre-registration, conflicts of interest, and funding. Text mining was performed with the rtransparent text mining algorithms with manual validation of 200 random articles to obtain corrected estimates. Across 1215 included articles, 39 (3%) shared code, 258 (21%) shared data, 10 (1%) were registered, 110 (90%) contained a conflict-of-interest statement, and 1141 (93%) included a funding statement. After manual validation, the corrected estimates for code sharing, data sharing, and registration were 5%, 27%, and 1%, respectively. Data sharing was 32% when limited to original articles and highest in space/parabolic flights (46%). Overall, across space medicine we observed modest rates of data sharing, rare sharing of code and almost non-existent protocol registration. Enhancing transparency in space medicine research is imperative for safeguarding its scientific rigor and reproducibility.
The language and conceptual framework of "research reproducibility" are nonstandard and unsettled across the sciences.In this Perspective, we review an array of explicit and implicit definitions of reproducibility and related terminology, and discuss how to avoid potential misunderstandings when these terms are used as a surrogate for "truth.
• The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. • The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. • Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. • A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. • These recommendations aim to enhance the transparency, quality and completeness of study reporting and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
In Reply.—We thank Best et al for their comments. We fully agree that safety aspects in randomized trials of aminoglycoside dosing, as in the vast majority of biomedical fields,1 is suboptimal and that the situation needs to be improved.2 Large-scale studies on the ototoxicity profile of single daily doses would be welcome. However, realistically, these studies are likely to be mostly, if not exclusively, nonrandomized at this point.We disagree that the current evidence does not suggest that we can confidently recommend universal change in aminoglycoside dosing for children. Of course, evidence can never be final, but there are few topics in pediatrics for which so many trials have been done with uniformly reassuring results. We disagree about the fear of an “incomplete evidence base.” The incomplete evidence base pertains mostly to the inappropriate continued use of multiple daily doses in children. In fact, multiple daily dosing of aminoglycosides was universally adopted for both adults and children a long time ago based on absolutely no evidence. Multiple daily dosing has remained a common, if not prevalent, strategy for both children and adults despite the fact that evidence from many dozens of randomized trials and meta-analyses has failed to show its superiority and have even suggested its inferiority.3As far as subgroup populations are concerned, there is no evidence to suggest that multiple daily dosing is indicated in any patient subgroup. Perpetuating emphasis on spurious subgroup differences4 is only likely to inappropriately delay the wider adoption of single daily dosing.Finally, therapeutic dose monitoring is a different question, and robust evidence is needed to decide when (or if ever) it is indeed indicated to optimize single daily dosing.5 Single daily dosing translates to lower trough values and should simplify the need for monitoring anyhow.6
Pushback is a mechanism for defending against distributed denial-of-service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets (hence the term Pushback) in order that the router's resources be used to route legitimate traffic. In this paper we present an architecture for Pushback, its implementation under FreeBSD, and suggestions for how such a system can be implemented in core routers.
