Tweeting Bias in Diagnostic Test Accuracy Research: Does Title or Conclusion Positivity Influence Dissemination?

PURPOSE: To examine if tweeting bias exists within imaging literature by determining if diagnostic test accuracy (DTA) studies with positive titles or conclusions are tweeted more than non-positive studies. METHODS: DTA studies published between October 2011 to April 2016 were included. Positivity of titles and conclusions were assessed independently and in duplicate, with disagreements resolved by consensus. A negative binomial regression analysis controlling for confounding variables was performed to assess the relationship between title or conclusion positivity and tweets an article received in the 100 days post-publication. RESULTS: 354 DTA studies were included. Twenty-four (7%) titles and 300 (85%) conclusions were positive (or positive with qualifier); 1 (0.3%) title and 23 (7%) conclusions were negative; and 329 (93%) titles and 26 (7%) conclusions were neutral. Studies with positive, negative, and neutral titles received a mean of 0.38, 0.00, and 0.45 tweets per study; while those with positive, negative, and neutral conclusions received a mean of 0.44, 0.61, and 0.38 tweets per study. Regression coefficients were -0.05 (SE 0.46) for positive relative to non-positive titles, and -0.09 (SE 0.31) for positive relative to non-positive conclusions. The positivity of the title (P = 0.91) or conclusion (P = 0.76) was not significantly associated with the number of tweets an article received. CONCLUSIONS: The positivity of the title or conclusion for DTA studies does not influence the amount of tweets it receives suggesting that tweet bias is not present among imaging diagnostic accuracy studies. Study protocol available at https://osf.io/hdk2m/.

Publication bias and the tourism-led growth hypothesis.

This study attempts to solve the publication bias suggested by recent review articles in the tourism-growth literature. Publication bias is the tendency to report favourable and significant results. Method and data triangulation, and the Solow-Swan model are applied. A sample from 1995 to 2018 is considered with Tonga as a case study. The approach consists of multiple methods, data frequencies, exchange rates, structural breaks, and an overall tourism index developed using principal component analysis (PCA). Consistent results across these dimensions are obtained with the PCA models. Tourism has small, positive, and statistically significant economic growth effects. Theoretically consistent values of the capital share and exchange rates are obtained. The results indicate the importance of multiple methods and the overall tourism index in assessing the tourism-growth relationship and minimising publication biases. The practical implication is the provision of robust elasticity estimates and better economic policies.

Non-inferiority in cancer clinical trials was associated with more lenient margins and higher hypothesized outcome event rates.

OBJECTIVE: To identify potential bias in non-inferiority design of published cancer trials, and to provide suggestions for future practice. STUDY DESIGN AND SETTING: We systematically searched MEDLINE, Embase and CENTRAL databases (until April 17, 2020) to obtain non-inferiority phase III cancer trials and protocols. Distribution of essential characteristics and study design parameters was compared between trials with and without concluding non-inferiority using multivariable logistic regression. RESULTS: A total of 291 eligible trials were included. We observed that increased odds of concluding non-inferiority was significantly associated with more lenient non-inferiority margins (OR = 1•94, 95% CI 1•02-3•69) and higher hypothesized event rate (OR = 1•24, 95% CI 1•06-1•47). Trials that established non-inferiority adopted margins that were more dispersedly distributed (dispersion OR = 2•90, 95% CI 1•88-4.48). CONCLUSION: Although limited by the exploratory nature, our study demonstrated existence of possible distorted non-inferiority design which could incur excess non-inferiority in cancer clinical trials. Pre-registration and transparent reporting of detailed non-inferiority design is imperative for future research.

High frequency of spin bias in controlled trials of cannabis derivatives and their synthetic analogues: A meta-epidemiologic study.

OBJECTIVE: To investigate the frequency and perform a qualitative analysis of spin bias in publications of controlled trials assessing the therapeutic use of cannabis derivatives and their synthetic analogues. STUDY DESIGN AND SETTING: Meta-epidemiologic study carried out at the Universidade Federal de São Paulo, Brazil. RESULTS: A total of 65 publications with at least one efficacy primary outcome were considered. The results analysis for the primary outcome indicated statistically significant effects in 44.6% (29/65) of the publications, and 70.7% (45/65) of the conclusions were considered favorable to the intervention. Among the 36 publications that found statistically nonsignificant results for the primary outcome, 44.4% (16/36) presented conclusions favorable to or recommending the intervention, which represents spin bias according to the definition adopted in this study. Qualitative analysis of the 16 studies with spin bias showed selective outcomes reporting (elevating secondary outcomes that had positive results or reporting only subgroup results), deviations from the planned statistical analysis, and failure to consider or report uncertainty in the estimates of treatment effects. CONCLUSION: The frequency of spin bias among publications of controlled trials with statistically nonsignificant results assessing the therapeutic use of cannabis derivatives and their synthetic analogues reached 44.4%. When not observed by readers, such deviation can lead to misconduct in clinical practice through the adoption of interventions that are not effective or whose effectiveness is uncertain.

Cluster randomized trials of individual-level interventions were at high risk of bias.

OBJECTIVES: To describe the prevalence of risks of bias in cluster-randomized trials of individual-level interventions, according to the Cochrane Risk of Bias tool. STUDY DESIGN AND SETTING: Review undertaken in duplicate of a random sample of 40 primary reports of cluster-randomized trials of individual-level interventions. RESULTS: The most common reported reasons for adopting cluster randomization were the need to avoid contamination (17, 42.5%) and practical considerations (14, 35%). Of the 40 trials all but one was assessed as being at risk of bias. A majority (27, 67.5%) were assessed as at risk due to the timing of identification and recruitment of participants; many (21, 52.5%) due to an apparent lack of adequate allocation concealment; and many due to selectively reported results (22, 55%), arising from a mixture of reasons including lack of documentation of primary outcome. Other risks mostly occurred infrequently. CONCLUSION: Many cluster-randomized trials evaluating individual-level interventions appear to be at risk of bias, mostly due to identification and recruitment biases. We recommend that investigators carefully consider the need for cluster randomization; follow recommended procedures to mitigate risks of identification and recruitment bias; and adhere to good reporting practices including clear documentation of primary outcome and allocation concealment methods.

A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases.

OBJECTIVES: To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses. STUDY DESIGN AND SETTING: We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using seven key items: (1) title transparency; (2) protocol pre-registration; (3) date of data extraction and analysis; (4) outcome, population, exposure and comparator definitions; (5) adjustment and stratification of results; (6) method and threshold for signal detection; (7) secondary and sensitivity analyses. RESULTS: We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation. CONCLUSION: Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses.

The Effect of Meal Replacement on Weight Loss According to Calorie-Restriction Type and Proportion of Energy Intake: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Portion control is a useful component of weight reduction interventions and meal replacement (MR) plans represent a promising strategy for portion control. Research performed with pooled data on the effect of MR plans according to various characteristics of MR interventions remains scarce. OBJECTIVE: Our aim was to assess the effects of MR-based diets compared with food-based diets on weight loss, according to calorie-restriction types and energy intake proportions from MR. METHODS: Electronic databases (Cochrane Central Register of Controlled Trials, PubMed, Embase, and Research Information Sharing Service) were searched for randomized controlled trials on weight loss results of MR-based calorie-restricted diets compared with food-based calorie-restricted diets from January 2000 to May 2020. Standardized mean differences (Hedges' g) from all study outcomes were calculated using a random-effects model. Heterogeneity was quantified by Q test and I2. Publication bias was assessed using a funnel plot and a trim and fill method. Both interventions (MR and control) were separated into very-low-energy diets and low-energy diets (LEDs). A meta-analysis of variance was conducted by dividing patient-related factors and treatment-related factors into subgroups. In multivariable meta-regressions, background variables were selected first, after which main independent variables were included. RESULTS: Twenty-two studies involving 24 interventions and 1,982 patients who were overweight or obese were included. The effect size in which MR-based LED was compared with food-based LED for weight loss was small, favoring MR (Hedges' g = 0.261; 95% CI 0.156 to 0.365; I2 = 21.9; 95% CI 0.0 to 53.6). Diets including ≥60% of total daily energy intake from MR had a medium effect size favoring MR with regard to weight loss among the groups (Hedges' g = 0.545; 95% CI 0.260 to 0.830; I2 = 42.7; 95% CI 0.0 to 80.8). CONCLUSIONS: The effect of MR-based LED on weight loss was superior to the effect of food-based LED, and receiving ≥60% of total daily energy intake from MR had the greatest effect on weight loss.

High prevalence of spin was found in pharmacovigilance studies using disproportionality analyses to detect safety signals: a meta-epidemiological study.

OBJECTIVE: To systematically review and appraise misinterpretation of pharmacovigilance disproportionality analysis results in published studies. STUDY DESIGN AND SETTING: We randomly selected 100 studies that performed disproportionality analyses and indexed in Medline identified during a systematic literature search. Titles, abstracts and main texts (results, discussion and conclusion) were evaluated for spin independently by two reviewers. Spin in pharmacovigilance studies was classified according to three main categories: inappropriate interpretation, inappropriate extrapolations and misleading reporting. RESULTS: Of the 100 studies evaluated, we found that 63%, 56% and 51% had at least one type of spin in their abstract, main text or conclusion respectively, and 40% used causal language to interpret their results in the abstract or conclusion. Spin in titles and results were exclusively represented by inappropriate interpretations of findings (12% and 21% respectively), with terms such as "risk of" or "risks associated with" or results erroneously presented as regular Odds Ratios. Spin in discussion sections mostly concerned inappropriate interpretations (38%)and misleading reporting (12%). Misleading reporting, notably failing to acknowledge the limitations of disproportionality analyses, was the most frequent type of spin in abstracts (55%) and conclusion sections (37%). CONCLUSION: We found that spin is frequent in publications of pharmacovigilance disproportionality analyses, notably in abstracts. This consisted notably in an over-interpretation of the results suggesting a proven causative link between a drug use and the risk of an event.

Noncollapsibility, confounding, and sparse-data bias. Part 1: The oddities of odds.

To prevent statistical misinterpretations, it has long been advised to focus on estimation instead of statistical testing. This sound advice brings with it the need to choose the outcome and effect measures on which to focus. Measures based on odds or their logarithms have often been promoted due to their pleasing statistical properties, but have an undesirable property for risk summarization and communication: Noncollapsibility, defined as a failure of the measure when taken on a group to equal a simple average of the measure when taken on the group's members or subgroups. The present note illustrates this problem with a basic numeric example involving the odds, which is not collapsible when the odds vary across individuals and are not low in all subgroups. Its sequel will illustrate how this problem is amplified in odds ratios and logistic regression.

Noncollapsibility, confounding, and sparse-data bias. Part 2: What should researchers make of persistent controversies about the odds ratio?

A previous note illustrated how the odds of an outcome have an undesirable property for risk summarization and communication: Noncollapsibility, defined as a failure of a group measure to represent a simple average of the measure over individuals or subgroups. The present sequel discusses how odds ratios amplify odds noncollapsibility and provides a basic numeric illustration of how noncollapsibility differs from confounding of effects (with which it is often confused). It also draws a connection of noncollapsibility to sparse-data bias in logistic, log-linear, and proportional-hazards regression.

Spin occurs in bariatric surgery randomized controlled trials with a statistically nonsignificant primary outcome: A systematic review.

OBJECTIVES: To systematically identify the strategy and frequency of spin in reports of bariatric surgery randomized controlled trials (RCTs) with statistically nonsignificant primary endpoint. STUDY DESIGN AND SETTING: The use of specific reporting strategies to highlight the beneficial effect of an experimental treatment can affect the reader interpretation of trial results, particularly when the primary endpoint is not statistically significant. A literature search was performed to identify RCTs publications assessing the impact of bariatric surgery on obesity-related comorbidities published over the past 10 years (from January 2020 till December 2020) in MEDLINE and EMBASE. RCTs publications with statistically non-significant primary outcomes were included. RESULTS: Of 46 576 reports screened for title and abstract inclusion, 29 RCT reports met the inclusion criteria for spin analysis. In total, 16 abstracts (55%) and 18 main texts (62%) were classified as having a spin. In abstract results and conclusion sections, the spin was identified in 69% of reports. In main text results, discussion, and conclusion sections, the spin was recognized in 37%, 72%, and 76% of reports respectively. The spin consisted mainly of focusing on within-group improvements and the interpretation of statistically nonsignificant results as showing treatment equivalence. CONCLUSION: Spin occurred in a high proportion of bariatric surgery RCTs with a statistically nonsignificant primary endpoint.

GRADE Guidance: 31. Assessing the certainty across a body of evidence for comparative test accuracy.

OBJECTIVES: This article provides GRADE guidance on how authors of evidence syntheses and health decision makers, including guideline developers, can rate the certainty across a body of evidence for comparative test accuracy questions. STUDY DESIGN AND SETTING: This guidance extends the previously published GRADE guidance for assessing certainty of evidence for test accuracy to scenarios in which two or more index tests are compared. Through an iterative brainstorm-discussion-feedback process within the GRADE working group, we developed a guidance accompanied by practical examples. RESULTS: Rating the certainty of evidence for comparative test accuracy shares many concepts and ideas with the existing GRADE guidance for test accuracy. The rating in comparisons of test accuracy requires additional considerations, such as the selection of appropriate comparative study designs, additional criteria for judging risk of bias, and the consequences of using comparative measures of test accuracy. Distinct approaches to rating certainty are required for comparative test accuracy studies and between-study (indirect) comparisons. CONCLUSION: This GRADE guidance will support transparent assessment of the certainty for a body of comparative test accuracy evidence.

Misreporting of Results of Research in Psychiatry.

Few studies address publication and outcome reporting biases of randomized controlled trials (RCTs) in psychiatry. The objective of this study was to determine publication and outcome reporting bias in RCTs funded by the Stanley Medical Research Institute (SMRI), a U.S. based, non-profit organization funding RCTs in schizophrenia and bipolar disorder. We identified all RCTs (n = 280) funded by SMRI between 2000 and 2011, and using non-public, final study reports and published manuscripts, we classified the results as positive or negative in terms of the drug compared to placebo. Design, outcome measures and statistical methods specified in the original protocol were compared to the published manuscript. Of 280 RCTs funded by SMRI between 2000 and 2011, at the time of this writing, three RCTs were ongoing and 39 were not performed. Among the 238 completed RCTs, 86 (36.1%) reported positive and 152 (63.9%) reported negative results: 86% (74/86) of those with positive findings were published in contrast to 53% (80/152) of those with negative findings (P < .001). In 70% of the manuscripts published, there were major discrepancies between the published manuscript and the original RCT protocol (change in the primary outcome measure or statistics, change in a number of patient groups, 25% or more reduction in sample size). We conclude that publication bias and outcome reporting bias is common in papers reporting RCTs in schizophrenia and bipolar disorder. These data have major implications regarding the validity of the reports of clinical trials published in the literature.

Weak evidence of country- and institution-related status bias in the peer review of abstracts.

Research suggests that scientists based at prestigious institutions receive more credit for their work than scientists based at less prestigious institutions, as do scientists working in certain countries. We examined the extent to which country- and institution-related status signals drive such differences in scientific recognition. In a preregistered survey experiment, we asked 4,147 scientists from six disciplines (astronomy, cardiology, materials science, political science, psychology and public health) to rate abstracts that varied on two factors: (i) author country (high status vs lower status in science); (ii) author institution (high status vs lower status university). We found only weak evidence of country- or institution-related status bias, and mixed regression models with discipline as random-effect parameter indicated that any plausible bias not detected by our study must be small in size.

Citation bias in otolaryngology systematic reviews.

OBJECTIVE: Reproducibility of systemic reviews (SRs) can be hindered by the presence of citation bias. Citation bias may occur when authors of SRs conduct hand-searches of included study reference lists to identify additional studies. Such a practice may lead to exaggerated SR summary effects. The purpose of this paper is to examine the prevalence of hand-searching reference lists in otolaryngology SRs. METHODS: The authors searched for systematic reviews published in eight clinical otolaryngology journals using the Cochrane Library and PubMed, with the date parameter of January 1, 2008, to December 31, 2017. Two independent authors worked separately to extract data from each SR for the following elements: whether reference lists were hand-searched, other kinds of supplemental searching, PRISMA adherence, and funding source. Following extraction, the investigators met to review discrepancies and achieve consensus. RESULTS: A total of 539 systemic reviews, 502 from clinical journals and 37 from the Cochrane library, were identified. Of those SRs, 72.4% (390/539) hand-searched reference lists, including 97.3% (36/37) of Cochrane reviews. For 228 (58.5%) of the SRs that hand-searched reference lists, no other supplemental search (e.g., search of trial registries) was conducted. CONCLUSIONS: These findings indicate that hand-searching reference lists is a common practice in otolaryngology SRs. Moreover, a majority of studies at risk of citation bias did not attempt to mitigate the bias by conducting additional supplemental searches. The implication is that summary effects in otolaryngology systematic reviews may be biased toward statistically significant findings.

Behavioural interventions for smoking cessation: an overview and network meta-analysis.

BACKGROUND: Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness. OBJECTIVES: To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary. METHODS: This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components. MAIN RESULTS: We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies. AUTHORS' CONCLUSIONS: Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.

ANTECEDENTES: El tabaquismo es una causa principal de enfermedad y muerte en todo el mundo. En las personas que fuman, dejar de fumar puede revertir gran parte del daño. Muchas personas utilizan intervenciones conductuales para ayudarles a dejar de fumar y estas intervenciones pueden variar considerablemente en contenido y efectividad. OBJETIVOS: Resumir la evidencia de las revisiones Cochrane que evaluaron el efecto de las intervenciones conductuales diseñadas para apoyar los intentos de abandono del hábito de fumar y realizar un metanálisis en red para determinar cómo las modalidades de prestación; la persona que administra la intervención; y la naturaleza, el enfoque y la intensidad de las intervenciones conductuales para el abandono del hábito de fumar influyen en la probabilidad de lograr la abstinencia seis meses después de intentar dejar de fumar; y si los efectos de las intervenciones conductuales dependen de otras características, como la población, el contexto y la administración de farmacoterapia. Resumir la disponibilidad y los hallazgos principales de las evaluaciones económicas de intervenciones conductuales para dejar de fumar, en términos de costes y coste­efectividad, mediante un breve comentario económico. MÉTODOS: Este artículo comprende dos elementos principales. 1. Se realizó una revisión global Cochrane de revisiones según los métodos estándar de Cochrane. Mediante una búsqueda en la Biblioteca Cochrane en julio de 2020 se identificaron las revisiones Cochrane de intervenciones conductuales (incluidas todas las intervenciones no farmacológicas, p.ej., orientación, ejercicio, hipnoterapia, materiales de autoayuda) para el abandono del hábito de fumar. La calidad metodológica de las revisiones se evaluó mediante AMSTAR 2 y los datos de las revisiones se resumieron de manera narrativa. 2. Las revisiones incluidas se utilizaron para identificar los ensayos controlados aleatorizados de intervenciones conductuales para el abandono del hábito de fumar en comparación con otras intervenciones conductuales o ninguna intervención para el abandono del hábito de fumar. Para ser incluidos, los estudios debían incluir a fumadores adultos y medir la abstinencia de fumar a los seis meses o más. La selección, la extracción de los datos y la evaluación del riesgo de sesgo siguieron los métodos Cochrane estándar. Los datos se resumieron mediante un metanálisis en red de componentes (MARC) bayesiano, y se examinaron los efectos de 38 componentes diferentes en comparación con una intervención mínima. Los componentes incluyeron elementos conductuales y motivacionales, proveedores de la intervención, modos de administración, naturaleza, enfoque e intensidad de la intervención conductual. Se utilizó la metarregresión en red de componentes (MRRC) para evaluar la influencia de las características de la población, la administración de farmacoterapia y la intensidad de la intervención sobre los efectos de los componentes. La certeza de la evidencia se evaluó mediante los dominios de GRADE. Se presupuso un efecto aditivo para los componentes individuales. RESULTADOS PRINCIPALES: Se incluyeron 33 revisiones Cochrane, de las cuales 312 ensayos controlados aleatorizados, que representaban a 250 563 participantes y 845 grupos de estudio distintos, cumplieron los criterios para su inclusión en el metanálisis en red de componentes. Esto representó 437 combinaciones diferentes de componentes. De las 33 revisiones, la confianza en los hallazgos de la revisión fue alta en cuatro y moderada en nueve, medida con la herramienta de lectura crítica AMSTAR 2. Las 20 revisiones restantes tuvieron una confianza baja o críticamente baja debido a una o más deficiencias graves, las más habituales fueron una investigación o discusión (o ambas) insuficiente acerca del impacto del sesgo de publicación. Cabe señalar que las debilidades críticas identificadas no afectaron los elementos de la búsqueda, la selección o la extracción de los datos del proceso de revisión, que mantienen una relación directa en este MARC. Entre los estudios incluidos, 125/312 tuvieron un riesgo general de sesgo bajo, 50 un riesgo de sesgo alto y el resto un riesgo de sesgo poco claro. Los análisis de las revisiones contribuyentes y de este MARC mostraron que las intervenciones conductuales para dejar de fumar pueden aumentar las tasas de abandono del hábito, pero la efectividad varía según las características del apoyo proporcionado. Hubo evidencia de certeza alta de un efecto beneficioso de la prestación de orientación (odds ratio [OR] 1,44; intervalo de credibilidad [ICr] del 95%: 1,22 a 1,70, 194 estudios, n = 72 273) y de los incentivos económicos garantizados (OR 1,46; ICr del 95% 1,15 a 1,85, 19 estudios, n = 8877). La evidencia de un efecto beneficioso se mantuvo cuando se eliminaron los estudios con alto riesgo de sesgo. Estos hallazgos fueron concordantes con los metanálisis pareados de las revisiones contribuyentes. Hubo evidencia de certeza moderada de un efecto beneficioso de las intervenciones administradas a través de mensajes de texto (la certeza se disminuyó debido a una heterogeneidad estadística inexplicada en la comparación pareada), y de los siguientes componentes en los que las estimaciones puntuales indicaron un efecto beneficioso pero los ICr no incorporaron una diferencia clínicamente significativa: personalización; contenido de la intervención con componentes motivacionales; contenido de la intervención centrado en cómo dejar de fumar. Los otros componentes de la intervención tuvieron evidencia de certeza muy baja a baja, y sus problemas principales fueron la imprecisión y el riesgo de sesgo. No hubo evidencia que indicara un aumento de los efectos perjudiciales en los grupos que recibieron apoyo conductual para dejar de fumar. Los efectos de la intervención no cambiaron al ajustar las características de la población, pero los datos fueron limitados. El aumento de la intensidad del apoyo conductual, medido a través del número de contactos, la duración de cada contacto y la duración del programa, tuvo estimaciones puntuales asociadas con un modesto aumento de las posibilidades de dejar de fumar, pero los ICr no incluyeron una diferencia. El efecto del apoyo conductual para dejar de fumar pareció ser ligeramente menos pronunciado cuando las personas ya recibían farmacoterapias para dejar de fumar. CONCLUSIONES DE LOS AUTORES: El apoyo conductual para dejar de fumar puede aumentar las tasas de abandono a los seis meses o más, sin evidencia de que este apoyo aumente los efectos perjudiciales. Esto es así tanto si se proporciona una farmacoterapia para dejar de fumar como si no, pero el efecto es ligeramente más pronunciado sin farmacoterapia. La evidencia de un efecto beneficioso es más sólida para la prestación de cualquier tipo de orientación y de incentivos económicos garantizados. La evidencia indicó un posible efecto beneficioso, pero la necesidad de realizar más estudios para evaluar: la personalización; la administración mediante mensajes de texto, correos electrónicos y grabaciones de audio; la administración por parte de un asesor de salud no profesional; y el contenido de la intervención con componentes motivacionales y centrada en cómo dejar de fumar. Se identificaron 23 evaluaciones económicas; la evidencia no indicó de manera homogénea que un tipo de intervención conductual para el abandono del hábito de fumar fuera más coste­efectiva que otra. Las revisiones futuras deberían examinar a fondo el sesgo de publicación. Se necesitan herramientas para investigar el sesgo de publicación y evaluar la certeza en MARC.

Epidemiology of COVID-19 infection in young children under five years: A systematic review and meta-analysis.

INTRODUCTION: Emerging evidence suggests young children are at greater risk of COVID-19 infection than initially predicted. However, a comprehensive understanding of epidemiology of COVID-19 infection in young children under five years, the most at-risk age-group for respiratory infections, remain unclear. We conducted a systematic review and meta-analysis of epidemiological and clinical characteristics of COVID-19 infection in children under five years. METHOD: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses , we searched several electronic databases (Pubmed, EMBASE, Web of Science, and Scopus) with no language restriction for published epidemiological studies and case-reports reporting laboratory-confirmed COVID-19 infection in children under five years until June 4, 2020. We assessed pooled prevalence for key demographics and clinical characteristics using Freeman-Tukey double arcsine random-effects model for studies except case-reports. We evaluated risk of bias separately for case-reports and other studies. RESULTS: We identified 1,964 articles, of which, 65 articles were eligible for systematic review that represented 1,214 children younger than five years with laboratory-confirmed COVID-19 infection. The pooled estimates showed that 50% young COVID-19 cases were infants (95% CI: 36% - 63%, 27 studies); 53% were male (95% CI: 41% - 65%, 24 studies); 43% were asymptomatic (95% CI: 15% - 73%, 9 studies) and 7% (95% CI: 0% - 30%, 5 studies) had severe disease that required intensive-care-unit admission. Of 139 newborns from COVID-19 infected mothers, five (3.6%) were COVID-19 positive. There was only one death recorded. DISCUSSION: This systematic review reports the largest number of children younger than five years with COVID-19 infection till date. Our meta-analysis shows nearly half of young COVID-19 cases were asymptomatic and half were infants, highlighting the need for ongoing surveillance to better understand the epidemiology, clinical pattern, and transmission of COVID-19 to develop effective preventive strategies against COVID-19 disease in young paediatric population.

Citation bias and other determinants of citation in biomedical research: findings from six citation networks.

OBJECTIVES: When the probability of being cited depends on the outcome of that study, this is called citation bias. The aim of this study is to assess the determinants of citation and how these compare across six different biomedical research fields. STUDY DESIGN AND SETTING: Citation network analyses were performed for six biomedical research questions. After identifying all relevant publications, all potential citations were mapped together with the actually performed citations in each network. As determinants of citation we assessed the following: study outcome, study design, sample size, journal impact factor, gender, affiliation, authority and continent of the corresponding author, funding source, title of the publication, number of references, and self-citation. Random effect logistic regression analysis was used to assess these factors. RESULTS: Four out of six networks showed evidence for citation bias. Self-citation, authority of the author, and journal impact factor were also positively associated with the probability of citation in all networks. CONCLUSION: The probability of being cited seems associated with positive study outcomes, the authority of its authors, and the journal in which that article is published. In addition, each network showed specific characteristics that impact the citation dynamics and that need to be considered when performing and interpreting citation analyses.