Background
Viral load (VL) testing in people living with HIV (PLHIV) helps to monitor antiretroviral therapy (ART). VL is still largely tested using central laboratory‐based platforms, which have ...long test turnaround times and involve sophisticated equipment. VL tests with point‐of‐care (POC) platforms capable of being used near the patient are potentially easy to use, give quick results, are cost‐effective, and could replace central or reference VL testing platforms.
Objectives
To estimate the diagnostic accuracy of POC tests to detect high viral load levels in PLHIV attending healthcare facilities.
Search methods
We searched eight electronic databases using standard, extensive Cochrane search methods, and did not use any language, document type, or publication status limitations. We also searched the reference lists of included studies and relevant systematic reviews, and consulted an expert in the field from the World Health Organization (WHO) HIV Department for potentially relevant studies. The latest search was 23 November 2020.
Selection criteria
We included any primary study that compared the results of a VL test with a POC platform to that of a central laboratory‐based reference test to detect high viral load in PLHIV on HIV/AIDS care or follow‐up. We included all forms of POC tests for VL as defined by study authors, regardless of the healthcare facility in which the test was conducted. We excluded diagnostic case‐control studies with healthy controls and studies that did not provide sufficient data to create the 2 × 2 tables to calculate sensitivity and specificity. We did not limit our study inclusion to age, gender, or geographical setting.
Data collection and analysis
Two review authors independently screened the titles, s, and full texts of the search results to identify eligible articles. They also independently extracted data using a standardized data extraction form and conducted risk of bias assessment using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS‐2) tool. Using participants as the unit of analysis, we fitted simplified univariable models for sensitivity and specificity separately, employing a random‐effects model to estimate the summary sensitivity and specificity at the current and commonly reported World Health Organization (WHO) threshold (≥ 1000 copies/mL). The bivariate models did not converge to give a model estimate.
Main results
We identified 18 studies (24 evaluations, 10,034 participants) defining high viral loads at main thresholds ≥ 1000 copies/mL (n = 20), ≥ 5000 copies/mL (n = 1), and ≥ 40 copies/mL (n = 3). All evaluations were done on samples from PLHIV retrieved from routine HIV/AIDS care centres or health facilities. For clinical applicability, we included 14 studies (20 evaluations, 8659 participants) assessing high viral load at the clinical threshold of ≥ 1000 copies/mL in the meta‐analyses. Of these, sub‐Saharan Africa, Europe, and Asia contributed 16, three, and one evaluation respectively. All included participants were on ART in only nine evaluations; in the other 11 evaluations the proportion of participants on ART was either partial or not clearly stated. Thirteen evaluations included adults only (n = 13), five mixed populations of adults and children, whilst in the remaining two the age of included populations was not clearly stated. The majority of evaluations included commercially available tests (n = 18). Ten evaluations were POC VL tests conducted near the patient in a peripheral or onsite laboratory, whilst the other 10 were evaluations of POC VL tests in a central or reference laboratory setting. The test types evaluated as POC VL tests included Xpert HIV‐1 Viral Load test (n = 8), SAMBA HIV‐1 Semi‐Q Test (n = 9), Alere Q NAT prototype assay for HIV‐1 (n = 2) and m‐PIMA HIV‐1/2 Viral Load test (n = 1). The majority of evaluations (n = 17) used plasma samples, whilst the rest (n = 3) utilized whole blood samples.
Pooled sensitivity (95% confidence interval (CI)) of POC VL at a threshold of ≥ 1000 copies/mL was 96.6% (94.8 to 97.8) (20 evaluations, 2522 participants), and pooled specificity (95% CI) was 95.7% (90.8 to 98.0) (20 evaluations, 6137 participants). Median prevalence for high viral load (≥ 1000 copies/mL) (n = 20) was 33.4% (range 6.9% to 88.5%).
Limitations
The risk of bias was mostly assessed as unclear across the four domains due to incomplete reporting.
Authors' conclusions
We found POC VL to have high sensitivity and high specificity for the diagnosis of high HIV viral load in PLHIV attending healthcare facilities at a clinical threshold of ≥ 1000 copies/mL.
Background
The clinical implications of SARS‐CoV‐2 infection are highly variable. Some people with SARS‐CoV‐2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID‐19 ...and COVID‐19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID‐19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020.
Objectives
To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID‐19 clinics, has COVID‐19.
Search methods
For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID‐19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
Studies were eligible if they included patients with clinically suspected COVID‐19, or if they recruited known cases with COVID‐19 and controls without COVID‐19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS‐CoV‐2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.
Data collection and analysis
Pairs of review authors independently selected all studies, at both title and stage and full‐text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS‐2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random‐effects meta‐analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable.
Main results
We identified 44 studies including 26,884 participants in total. Prevalence of COVID‐19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID‐19, so we present the results for all disease severities together.
Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies.
The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID‐19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults.
We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93).
Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09).
Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%).
Authors' conclusions
The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID‐19. The presence of anosmia or ageusia may be useful as a red flag for COVID‐19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing.
Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID‐19, are still urgently needed. Results from such studies could inform subsequent management decisions.
Background
Male circumcision is defined as the surgical removal of all or part of the foreskin of the penis and may be practiced as part of a religious ritual, as a medical procedure, or as part of a ...traditional ritual performed as an initiation into manhood. Since the 1980s, over 30 observational studies have suggested a protective effect of male circumcision on HIV acquisition in heterosexual men. In 2002, three randomised controlled trials to assess the efficacy of male circumcision for preventing HIV acquisition in men commenced in Africa. This review evaluates the results of these trials, which analysed the effectiveness and safety of male circumcision for preventing acquisition of HIV in heterosexual men.
Objectives
To assess the evidence of an interventional effect of male circumcision for preventing acquisition of HIV‐1 and HIV‐2 by men through heterosexual intercourse
Search methods
We formulated a comprehensive and exhaustive search strategy in an attempt to identify all relevant studies regardless of language or publication status (published, unpublished, in press, and in progress). In June 2007 we searched the following electronic journal and trial databases: MEDLINE, EMBASE, and CENTRAL. We also searched the electronic conference databases NLM Gateway and AIDSearch and the trials registers ClinicalTrials.gov and Current Controlled Trials. We contacted researchers and relevant organizations and checked reference lists of all included studies.
Selection criteria
Randomised controlled trials of male circumcision versus no circumcision in HIV‐negative heterosexual men with HIV incidence as the primary outcome.
Data collection and analysis
Two review authors independently assessed study eligibility, extracted data, and graded methodological quality. Data extraction and methodological quality were checked by a third author who resolved differences when these arose. Data were considered clinically homogeneous and meta‐analyses and sensitivity analyses were performed.
Main results
Three large RCTs of men from the general population were conducted in South Africa (N = 3 274), Uganda (N = 4 996) and Kenya (N = 2 784) between 2002 and 2006. All three trials were stopped early due to significant findings at interim analyses. We combined the survival estimates for all three trials at 12 months and also at 21 or 24 months in a meta‐analysis using available case analyses using the random effects model. The resultant incidence risk ratio (IRR) was 0.50 at 12 months with a 95% confidence interval (CI) of 0.34 to 0.72; and 0.46 at 21 or 24 months (95% CI: 0.34 to 0.62). These IRRs can be interpreted as a relative risk reduction of acquiring HIV of 50% at 12 months and 54% at 21 or 24 months following circumcision. There was little statistical heterogeneity between the trial results (χ² = 0.60; df = 2; p = 0.74 and χ² = 0.31; df = 2; p = 0.86) with the degree of heterogeneity quantified by the I² at 0% in both analyses. We investigated the sensitivity of the calculated IRRs and conducted meta‐analyses of the reported IRRs, the reported per protocol IRRs, and reported full intention‐to‐treat analysis. The results obtained did not differ markedly from the available case meta‐analysis, with circumcision displaying significant protective effects across all analyses.
We conducted a meta‐analysis of the secondary outcomes measuring sexual behaviour for the Kenyan and Ugandan trials and found no significant differences between circumcised and uncircumcised men. For the South African trial the mean number of sexual contacts at the 12‐month visit was 5.9 in the circumcision group versus 5 in the control group, which was a statistically significant difference (p < 0.001). This difference remained statistically significant at the 21‐month visit (7.5 versus 6.4; p = 0.0015). No other significant differences were observed.
Incidence of adverse events following the surgical circumcision procedure was low in all three trials.
Reporting of methodological quality was variable across the three trials, but overall, the potential for significant biases affecting the trial results was judged to be low to moderate given the large sample sizes of the trials, the balance of possible confounding variables across randomised groups at baseline in all three trials, and the employment of acceptable statistical early stopping rules.
Authors' conclusions
There is strong evidence that medical male circumcision reduces the acquisition of HIV by heterosexual men by between 38% and 66% over 24 months. Incidence of adverse events is very low, indicating that male circumcision, when conducted under these conditions, is a safe procedure. Inclusion of male circumcision into current HIV prevention measures guidelines is warranted, with further research required to assess the feasibility, desirability, and cost‐effectiveness of implementing the procedure within local contexts.
Background
Some people with SARS‐CoV‐2 infection remain asymptomatic, whilst in others the infection can cause mild to moderate COVID‐19 disease and COVID‐19 pneumonia, leading some patients to ...require intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever or cough, and signs such as oxygen saturation or lung auscultation findings, are the first and most readily available diagnostic information. Such information could be used to either rule out COVID‐19 disease, or select patients for further diagnostic testing.
Objectives
To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID‐19 clinics, has COVID‐19 disease or COVID‐19 pneumonia.
Search methods
On 27 April 2020, we undertook electronic searches in the Cochrane COVID‐19 Study Register and the University of Bern living search database, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
Studies were eligible if they included patients with suspected COVID‐19 disease, or if they recruited known cases with COVID‐19 disease and controls without COVID‐19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies including patients who contracted SARS‐CoV‐2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards including reverse transcription polymerase chain reaction (RT‐PCR), clinical expertise, imaging, serology tests and World Health Organization (WHO) or other definitions of COVID‐19.
Data collection and analysis
Pairs of review authors independently selected all studies, at both title and stage and full‐text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the QUADAS‐2 checklist. Analyses were descriptive, presenting sensitivity and specificity in paired forest plots, in ROC (receiver operating characteristic) space and in dumbbell plots. We did not attempt meta‐analysis due to the small number of studies, heterogeneity across studies and the high risk of bias.
Main results
We identified 16 studies including 7706 participants in total. Prevalence of COVID‐19 disease varied from 5% to 38% with a median of 17%. There were no studies from primary care settings, although we did find seven studies in outpatient clinics (2172 participants), and four studies in the emergency department (1401 participants). We found data on 27 signs and symptoms, which fall into four different categories: systemic, respiratory, gastrointestinal and cardiovascular. No studies assessed combinations of different signs and symptoms and results were highly variable across studies. Most had very low sensitivity and high specificity; only six symptoms had a sensitivity of at least 50% in at least one study: cough, sore throat, fever, myalgia or arthralgia, fatigue, and headache. Of these, fever, myalgia or arthralgia, fatigue, and headache could be considered red flags (defined as having a positive likelihood ratio of at least 5) for COVID‐19 as their specificity was above 90%, meaning that they substantially increase the likelihood of COVID‐19 disease when present.
Seven studies carried a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional four studies, we were unable to assess the risk for selection bias. These factors make it very difficult to determine the diagnostic properties of these signs and symptoms from the included studies.
We also had concerns about the applicability of these results, since most studies included participants who were already admitted to hospital or presenting to hospital settings. This makes these findings less applicable to people presenting to primary care, who may have less severe illness and a lower prevalence of COVID‐19 disease. None of the studies included any data on children, and only one focused specifically on older adults. We hope that future updates of this review will be able to provide more information about the diagnostic properties of signs and symptoms in different settings and age groups.
Authors' conclusions
The individual signs and symptoms included in this review appear to have very poor diagnostic properties, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out disease. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID‐19 disease, are urgently needed. Results from such studies could inform subsequent management decisions such as self‐isolation or selecting patients for further diagnostic testing. We also need data on potentially more specific symptoms such as loss of sense of smell. Studies in older adults are especially important.
Background
Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and the resulting COVID‐19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to ...identify or rule out current infection, identify people in need of care escalation, or to test for past infection and immune response. Point‐of‐care antigen and molecular tests to detect current SARS‐CoV‐2 infection have the potential to allow earlier detection and isolation of confirmed cases compared to laboratory‐based diagnostic methods, with the aim of reducing household and community transmission.
Objectives
To assess the diagnostic accuracy of point‐of‐care antigen and molecular‐based tests to determine if a person presenting in the community or in primary or secondary care has current SARS‐CoV‐2 infection.
Search methods
On 25 May 2020 we undertook electronic searches in the Cochrane COVID‐19 Study Register and the COVID‐19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
We included studies of people with suspected current SARS‐CoV‐2 infection, known to have, or not to have SARS‐CoV‐2 infection, or where tests were used to screen for infection. We included test accuracy studies of any design that evaluated antigen or molecular tests suitable for a point‐of‐care setting (minimal equipment, sample preparation, and biosafety requirements, with results available within two hours of sample collection). We included all reference standards to define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction (RT‐PCR) tests and established clinical diagnostic criteria).
Data collection and analysis
Two review authors independently screened studies and resolved any disagreements by discussion with a third review author. One review author independently extracted study characteristics, which were checked by a second review author. Two review authors independently extracted 2x2 contingency table data and assessed risk of bias and applicability of the studies using the QUADAS‐2 tool. We present sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots. We pooled data using the bivariate hierarchical model separately for antigen and molecular‐based tests, with simplifications when few studies were available. We tabulated available data by test manufacturer.
Main results
We included 22 publications reporting on a total of 18 study cohorts with 3198 unique samples, of which 1775 had confirmed SARS‐CoV‐2 infection. Ten studies took place in North America, two in South America, four in Europe, one in China and one was conducted internationally. We identified data for eight commercial tests (four antigen and four molecular) and one in‐house antigen test. Five of the studies included were only available as preprints.
We did not find any studies at low risk of bias for all quality domains and had concerns about applicability of results across all studies. We judged patient selection to be at high risk of bias in 50% of the studies because of deliberate over‐sampling of samples with confirmed COVID‐19 infection and unclear in seven out of 18 studies because of poor reporting. Sixteen (89%) studies used only a single, negative RT‐PCR to confirm the absence of COVID‐19 infection, risking missing infection. There was a lack of information on blinding of index test (n = 11), and around participant exclusions from analyses (n = 10). We did not observe differences in methodological quality between antigen and molecular test evaluations.
Antigen tests
Sensitivity varied considerably across studies (from 0% to 94%): the average sensitivity was 56.2% (95% CI 29.5 to 79.8%) and average specificity was 99.5% (95% CI 98.1% to 99.9%; based on 8 evaluations in 5 studies on 943 samples). Data for individual antigen tests were limited with no more than two studies for any test.
Rapid molecular assays
Sensitivity showed less variation compared to antigen tests (from 68% to 100%), average sensitivity was 95.2% (95% CI 86.7% to 98.3%) and specificity 98.9% (95% CI 97.3% to 99.5%) based on 13 evaluations in 11 studies of on 2255 samples. Predicted values based on a hypothetical cohort of 1000 people with suspected COVID‐19 infection (with a prevalence of 10%) result in 105 positive test results including 10 false positives (positive predictive value 90%), and 895 negative results including 5 false negatives (negative predictive value 99%).
Individual tests
We calculated pooled results of individual tests for ID NOW (Abbott Laboratories) (5 evaluations) and Xpert Xpress (Cepheid Inc) (6 evaluations). Summary sensitivity for the Xpert Xpress assay (99.4%, 95% CI 98.0% to 99.8%) was 22.6 (95% CI 18.8 to 26.3) percentage points higher than that of ID NOW (76.8%, (95% CI 72.9% to 80.3%), whilst the specificity of Xpert Xpress (96.8%, 95% CI 90.6% to 99.0%) was marginally lower than ID NOW (99.6%, 95% CI 98.4% to 99.9%; a difference of −2.8% (95% CI −6.4 to 0.8))
Authors' conclusions
This review identifies early‐stage evaluations of point‐of‐care tests for detecting SARS‐CoV‐2 infection, largely based on remnant laboratory samples. The findings currently have limited applicability, as we are uncertain whether tests will perform in the same way in clinical practice, and according to symptoms of COVID‐19, duration of symptoms, or in asymptomatic people. Rapid tests have the potential to be used to inform triage of RT‐PCR use, allowing earlier detection of those testing positive, but the evidence currently is not strong enough to determine how useful they are in clinical practice.
Prospective and comparative evaluations of rapid tests for COVID‐19 infection in clinically relevant settings are urgently needed. Studies should recruit consecutive series of eligible participants, including both those presenting for testing due to symptoms and asymptomatic people who may have come into contact with confirmed cases. Studies should clearly describe symptomatic status and document time from symptom onset or time since exposure. Point‐of‐care tests must be conducted on samples according to manufacturer instructions for use and be conducted at the point of care. Any future research study report should conform to the Standards for Reporting of Diagnostic Accuracy (STARD) guideline.
Hierarchical models such as the bivariate and hierarchical summary receiver operating characteristic (HSROC) models are recommended for meta-analysis of test accuracy studies. These models are ...challenging to fit when there are few studies and/or sparse data (for example zero cells in contingency tables due to studies reporting 100% sensitivity or specificity); the models may not converge, or give unreliable parameter estimates. Using simulation, we investigated the performance of seven hierarchical models incorporating increasing simplifications in scenarios designed to replicate realistic situations for meta-analysis of test accuracy studies. Performance of the models was assessed in terms of estimability (percentage of meta-analyses that successfully converged and percentage where the between study correlation was estimable), bias, mean square error and coverage of the 95% confidence intervals. Our results indicate that simpler hierarchical models are valid in situations with few studies or sparse data. For synthesis of sensitivity and specificity, univariate random effects logistic regression models are appropriate when a bivariate model cannot be fitted. Alternatively, an HSROC model that assumes a symmetric SROC curve (by excluding the shape parameter) can be used if the HSROC model is the chosen meta-analytic approach. In the absence of heterogeneity, fixed effect equivalent of the models can be applied.
The role of T cells in mediating heterosubtypic protection against natural influenza illness in humans is uncertain. The 2009 H1N1 pandemic (pH1N1) provided a unique natural experiment to determine ...whether crossreactive cellular immunity limits symptomatic illness in antibody-naive individuals. We followed 342 healthy adults through the UK pandemic waves and correlated the responses of pre-existing T cells to the pH1N1 virus and conserved core protein epitopes with clinical outcomes after incident pH1N1 infection. Higher frequencies of pre-existing T cells to conserved CD8 epitopes were found in individuals who developed less severe illness, with total symptom score having the strongest inverse correlation with the frequency of interferon-γ (IFN-γ)(+) interleukin-2 (IL-2)(-) CD8(+) T cells (r = -0.6, P = 0.004). Within this functional CD8(+)IFN-γ(+)IL-2(-) population, cells with the CD45RA(+) chemokine (C-C) receptor 7 (CCR7)(-) phenotype inversely correlated with symptom score and had lung-homing and cytotoxic potential. In the absence of crossreactive neutralizing antibodies, CD8(+) T cells specific to conserved viral epitopes correlated with crossprotection against symptomatic influenza. This protective immune correlate could guide universal influenza vaccine development.
Publication bias and other sample size effects are issues for meta-analyses of test accuracy, as for randomized trials. We investigate limitations of standard funnel plots and tests when applied to ...meta-analyses of test accuracy and look for improved methods.
Type I and type II error rates for existing and alternative tests of sample size effects were estimated and compared in simulated meta-analyses of test accuracy.
Type I error rates for the Begg, Egger, and Macaskill tests are inflated for typical diagnostic odds ratios (DOR), when disease prevalence differs from 50% and when thresholds favor sensitivity over specificity or vice versa. Regression and correlation tests based on functions of effective sample size are valid, if occasionally conservative, tests for sample size effects. Empirical evidence suggests that they have adequate power to be useful tests. When DORs are heterogeneous, however, all tests of funnel plot asymmetry have low power.
Existing tests that use standard errors of odds ratios are likely to be seriously misleading if applied to meta-analyses of test accuracy. The effective sample size funnel plot and associated regression test of asymmetry should be used to detect publication bias and other sample size related effects.
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