Determining the conclusiveness of a meta-analysis.

The pursuit of conclusive evidence related to an unanswered foreground (decision-making) question has been the driving factor behind multiple ongoing and planned randomized controlled trials as well as meta-analyses. However, a fundamental challenge lies in establishing robust methods for ascertaining whether a collection of synthesized trials has yielded a definitive answer to that foreground question through the process of meta-analysis. This article explores the evolution of methods that attempt to address this challenge. These methods have primarily focused on defining and measuring the sufficiency and stability of evidence within a meta-analytic context. Cumulative meta-analysis and trial sequential analysis are the tools currently used, but they both come with limitations and challenges. We further discuss methods aimed at evaluating the evolution of effects over time more directly, such as the recursive cumulative meta-analysis. The latter method can be considered a better alternative, as it serves to demonstrate whether there is a true underlying treatment effect to which the meta-analysis is converging. However, recursive cumulative meta-analysis falls short of a specific indicator that establishes whether convergence has been reached. We coin the term exit for a meta-analysis where convergence can be demonstrated. Developing methods to determine the exit status of a meta-analysis is the next priority in research synthesis methods, as it will indicate that the research journey has concluded on a particular foreground question with no expectation of a different result with the addition of future trials.

Influence of lack of blinding on the estimation of medication-related harms: a retrospective cohort study of randomized controlled trials.

BACKGROUND: Empirical evidence suggests that lack of blinding may be associated with biased estimates of treatment benefit in randomized controlled trials, but the influence on medication-related harms is not well-recognized. We aimed to investigate the association between blinding and clinical trial estimates of medication-related harms. METHODS: We searched PubMed from January 1, 2015, till January 1, 2020, for systematic reviews with meta-analyses of medication-related harms. Eligible meta-analyses must have contained trials both with and without blinding. Potential covariates that may confound effect estimates were addressed by restricting trials within the comparison or by hierarchical analysis of harmonized groups of meta-analyses (therefore harmonizing drug type, control, dosage, and registration status) across eligible meta-analyses. The weighted hierarchical linear regression was then used to estimate the differences in harm estimates (odds ratio, OR) between trials that lacked blinding and those that were blinded. The results were reported as the ratio of OR (ROR) with its 95% confidence interval (CI). RESULTS: We identified 629 meta-analyses of harms with 10,069 trials. We estimated a weighted average ROR of 0.68 (95% CI: 0.53 to 0.88, P < 0.01) among 82 trials in 20 meta-analyses where blinding of participants was lacking. With regard to lack of blinding of healthcare providers or outcomes assessors, the RORs were 0.68 (95% CI: 0.53 to 0.87, P < 0.01 from 81 trials in 22 meta-analyses) and 1.00 (95% CI: 0.94 to 1.07, P = 0.94 from 858 trials among 155 meta-analyses) respectively. Sensitivity analyses indicate that these findings are applicable to both objective and subjective outcomes. CONCLUSIONS: Lack of blinding of participants and health care providers in randomized controlled trials may underestimate medication-related harms. Adequate blinding in randomized trials, when feasible, may help safeguard against potential bias in estimating the effects of harms.

Comparison of bias adjustment in meta-analysis using data-based and opinion-based methods.

INTRODUCTION: Several methods exist for bias adjustment of meta-analysis results, but there has been no comprehensive comparison with unadjusted methods. We compare 6 bias-adjustment methods with 2 unadjusted methods to examine how these different methods perform. METHODS: We re-analyzed a meta-analysis that included 10 randomized controlled trials. Two data-based methods (Welton's data-based approach and Doi's quality effects model) and 4 opinion-informed methods (opinion-based approach, opinion-based distributions combined statistically with data-based distributions, numerical opinions informed by data-based distributions, and opinions obtained by selecting areas from data-based distributions) were used to incorporate methodological quality information into the meta-analytical estimates. The results of these 6 methods were compared with 2 unadjusted models: the DerSimonian-Laird random effects model and Doi's inverse variance heterogeneity model. RESULTS: The 4 opinion-based methods returned the random effects model estimates with wider uncertainty. The data-based and quality effects methods returned different results and aligned with the inverse variance heterogeneity method with some minor downward bias adjustment. CONCLUSION: Opinion-based methods seem to only add uncertainty rather than bias adjust.

Use of conditional estimates of effect in cancer epidemiology: An application to lung cancer treatment.

BACKGROUND: In oncology clinical trials, there is the assumption that randomization sufficiently balances confounding covariates and therefore average treatment effects are usually reported. This paper explores the wider benefits provided by conditioning on covariates for reasons other than mitigation of confounding. METHODS: We reanalyzed the data from primary randomized controlled trials listed in two meta-analyses to explore the significance of conditioning on smoking status in terms of the effect magnitude of treatment on progression free survival in non-small cell lung cancer. RESULTS: The reanalysis revealed that conditioning on smoking status using sub-group analyses provided the closest empiric estimate of individual treatment effect based on smoking status and significantly reduced the heterogeneity of treatment effect observed across studies. In addition, smoking status was determined to be a modifier of the effect of treatment. CONCLUSION: Conditioning on prognostic covariates in randomized trials in oncology helps generate the closest empiric estimates of individual treatment benefit, addresses heterogeneity due to varying covariate distributions across trials and facilitates future decision making as well as evidence synthesis. Conditioning using sub-group analyses also allows examination for effect modification in meta-analysis.

Data extraction error in pharmaceutical versus non-pharmaceutical interventions for evidence synthesis: Study protocol for a crossover trial.

Background: Data extraction is the foundation for research synthesis evidence, while data extraction errors frequently occur in the literature. An interesting phenomenon was observed that data extraction error tend to be more common in trials of pharmaceutical interventions compared to non-pharmaceutical ones. The elucidation of which would have implications for guidelines, practice, and policy. Methods and analyses: We propose a crossover, multicenter, investigator-blinded trial to elucidate the potential variants on the data extraction error rates. Eligible 90 participants would be 2nd year or above post-graduate students (e.g., masters, doctoral program). Participants will be randomized to one of the two groups to complete pre-defined data extraction tasks: 1) group A will contain 10 randomized controlled trials (RCTs) of pharmaceutical interventions; 2) group B will contain 10 RCTs of non-pharmaceutical interventions. Participants who finish the data extraction would then be assigned to the alternative group for another round of data extraction after a 30 min washout period. Finally, those participants assigned to A or B group will be further 1:1 randomly matched based on a random-sequenced number for the double-checking process on the extracted data. The primary outcome will be the data extract error rates of the pharmaceutical intervention group and non-pharmaceutical group, before the double-checking process, in terms of the cell level, study level, and participant level. The secondary outcome will be the data error rates of the pharmaceutical intervention group and non-pharmaceutical group after the double-checking process, again, in terms of the cell level, study level, and participant level. A generalized linear mixed effects model (based on the above three levels) will be used to estimate the potential differences in the error rates, with a log link function for binomial data. Subgroup analyses will account for the experience of individuals on systematic reviews and the time used for the data extraction. Discussion: This trial will provide useful evidence for further systematic review of data extraction practices, improved data extraction strategies, and better guidelines. Trial registration: Chinese Clinical Trial Register Center (Identifier: ChiCTR2200062206).

Clinical Phenotypes of PCOS: a Cross-Sectional Study.

This cross-sectional study examines the Doi-Alshoumer PCOS clinical phenotype classification in relation to measured clinical and biochemical characteristics of women with polycystic ovary syndrome (PCOS). Two cohorts of women (Kuwait and Rotterdam) diagnosed with PCOS (FAI > 4.5%) were examined. These phenotypes were created using neuroendocrine dysfunction (IRMA LH/FSH ratio > 1 or LH > 6 IU/L) and menstrual cycle status (oligo/amenorrhea) to create three phenotypes: (A) neuroendocrine dysfunction and oligo/amenorrhea, (B) without neuroendocrine dysfunction but with oligo/amenorrhea, and (C) without neuroendocrine dysfunction and with regular cycles. These phenotypes were compared in terms of hormonal, biochemical, and anthropometric measures. The three suggested phenotypes (A, B, and C) were shown to be sufficiently distinct in terms of hormonal, biochemical, and anthropometric measures. Patients who were classified as phenotype A had neuroendocrine dysfunction, excess LH (and LH/FSH ratio), irregular cycles, excess A4, infertility, excess T, highest FAI and E2, and excess 17αOHPG when compared to the other phenotypes. Patients classified as phenotype B had irregular cycles, no neuroendocrine dysfunction, obesity, acanthosis nigricans, and insulin resistance. Lastly, patients classified as phenotype C had regular cycles, acne, hirsutism, excess P4, and the highest P4 to E2 molar ratio. The differences across phenotypes suggested distinct phenotypic expression of this syndrome, and the biochemical and clinical correlates of each phenotype are likely to be useful in the management of women with PCOS. These phenotypic criteria are distinct from criteria used for diagnosis.

Dynamics of Anti-S IgG Antibodies Titers after the Second Dose of COVID-19 Vaccines in the Manual and Craft Worker Population of Qatar.

There is limited seroepidemiological evidence on the magnitude and long-term durability of antibody titers of mRNA and non-mRNA vaccines in the Qatari population. This study was conducted to generate evidence on long-term anti-S IgG antibody titers and their dynamics in individuals who have completed a primary COVID-19 vaccination schedule. A total of 300 male participants who received any of the following vaccines BNT162b2/Comirnaty, mRNA-1273, ChAdOx1-S/Covishield, COVID-19 Vaccine Janssen/Johnson, or BBIBP-CorV or Covaxin were enrolled in our study. All sera samples were tested by chemiluminescent microparticle immunoassay (CMIA) for the quantitative determination of IgG antibodies to SARS-CoV-2, receptor-binding domain (RBD) of the S1 subunit of the spike protein of SARS-CoV-2. Antibodies against SARS-CoV-2 nucleocapsid (SARS-CoV-2 N-protein IgG) were also determined. Kaplan-Meier survival curves were used to compare the time from the last dose of the primary vaccination schedule to the time by which anti-S IgG antibody titers fell into the lowest quartile (range of values collected) for the mRNA and non-mRNA vaccines. Participants vaccinated with mRNA vaccines had higher median anti-S IgG antibody titers. Participants vaccinated with the mRNA-1273 vaccine had the highest median anti-S-antibody level of 13,720.9 AU/mL (IQR 6426.5 to 30,185.6 AU/mL) followed by BNT162b2 (median, 7570.9 AU/mL; IQR, 3757.9 to 16,577.4 AU/mL); while the median anti-S antibody titer for non-mRNA vaccinated participants was 3759.7 AU/mL (IQR, 2059.7-5693.5 AU/mL). The median time to reach the lowest quartile was 3.53 months (IQR, 2.2-4.5 months) and 7.63 months (IQR, 6.3-8.4 months) for the non-mRNA vaccine recipients and Pfizer vaccine recipients, respectively. However, more than 50% of the Moderna vaccine recipients did not reach the lowest quartile by the end of the follow-up period. This evidence on anti-S IgG antibody titers should be considered for informing decisions on the durability of the neutralizing activity and thus protection against infection after the full course of primary vaccination in individuals receiving different type (mRNA verus non-mRNA) vaccines and those with natural infection.

Methodological quality assessment should move beyond design specificity.

OBJECTIVE: This study aimed to assess the utility of a unified tool (MASTER) for bias assessment against design-specific tools in terms of content and coverage. METHODS: Each of the safeguards in the design-specific tools was compared and matched to safeguards in the unified MASTER scale. The design-specific tools were the JBI, Scottish Intercollegiate Guidelines Network (SIGN), and the Newcastle-Ottawa Scale (NOS) tools for analytic study designs. Duplicates, safeguards that could not be mapped to the MASTER scale, and items not applicable as safeguards against bias were flagged and described. RESULTS: Many safeguards across the JBI, SIGN, and NOS tools were common, with a minimum of 10 to a maximum of 23 unique safeguards across various tools. These 3 design-specific toolsets were missing 14 to 26 safeguards from the MASTER scale. The MASTER scale had complete coverage of safeguards within the 3 toolsets for analytic designs. CONCLUSIONS: The MASTER scale provides a unified framework for bias assessment of analytic study designs, has good coverage, avoids duplication, has less redundancy, and is more convenient when used for methodological quality assessment in evidence synthesis. It also allows assessment across designs that cannot be done using a design-specific tool.

Diagnostic accuracy of multiplex nucleic acid amplification tests for Campylobacter infection: a systematic review and meta-analysis.

Campylobacter infection is one of the most frequently reported foodborne diseases with approximately 230,000 and 1.5 million cases each year in Europe and the USA, respectively. Culture methods are the reference for the diagnosis of Campylobacter infections; however, these methods are complex and time-consuming. Multiplex nucleic acid amplification test is favored due to its rapidity, automatization in the procedure followed and the quick simultaneous testing of numerous foodborne pathogens. The aim of this meta-analysis was to evaluate the accuracy of these tests for the diagnosis of Campylobacter infection. Scopus, Science Direct, PubMed, Web of Science, and Mendeley were searched for peer-reviewed articles. The split component synthesis method with the use of the inverse variance heterogeneity model was chosen for the quantitative meta-analysis. Sensitivity analysis was performed by age category and index test. The literature search found 34 studies involving 28,105 patients with suspected gastroenteritis. The sensitivity and specificity were 95.3% (92.3; 97.1) and 97.1% (95.1; 98.3), respectively, and AUC (area under the curve) was 0.963 (0.947; 0.974). Pediatric patients had a lower sensitivity (87.4, 48.2; 98.1) and higher specificity (99.2, 91.6; 99.9) estimate compared to all ages category (sensitivity 95.3, 91.3; 97.5, specificity 96.7, 93.7; 98.3). Among the various index tests, Seeplex/Allplex and Amplidiag/Novodiag had the lowest estimate for sensitivity (88.9, 73.8; 95.8) and specificity (95.2, 86; 98.4), respectively. BDMax had the highest (sensitivity 98.1, 96.1; 99 and specificity 98.5, 97; 99.3). Multiplex nucleic acid tests showed excellent accuracy and could play an influential role in diagnosing Campylobacter infections.

The Economic Impact of Optimizing a COVID-19 Management Protocol in Pre-Existing Cardiovascular Disease Patients.

This study answers the question of whether the health care costs of managing COVID-19 in preexisting cardiovascular diseases (CVD) patients increased or decreased as a consequence of evidence-based efforts to optimize the initial COVID-19 management protocol in a CVD group of patients. A retrospective cohort study was conducted in preexisting CVD patients with COVID-19 in Hamad Medical Corporation, Qatar. From the health care perspective, only direct medical costs were considered, adjusted to their 2021 values. The impact of revising the protocol was a reduction in the overall costs in non-critically ill patients from QAR15,447 (USD 4243) to QAR4337 (USD 1191) per patient, with an economic benefit of QAR11,110 (USD 3051). In the critically ill patients, however, the cost increased from QAR202,094 (USD 55,505) to QAR292,856 (USD 80,433) per patient, with added cost of QAR90,762 (USD 24,928). Overall, regardless of critical care status, the optimization of the initial COVID-19 protocols in patients with preexisting CVD did not reduce overall health care costs, but increased it by QAR80,529 (USD 22,117) per patient.

Data reproducibility issues and their potential impact on conclusions from evidence syntheses of randomized controlled trials in sleep medicine.

In this study, we examined the data reproducibility issues in systematic reviews in sleep medicine. We searched for systematic reviews of randomized controlled trials published in sleep medicine journals. The metadata in meta-analyses among the eligible systematic reviews were collected. The original sources of the data were reviewed to see if the components used in the meta-analyses were correctly extracted or estimated. The impacts of the data reproducibility issues were investigated. We identified 48 systematic reviews with 244 meta-analyses of continuous outcomes and 54 of binary outcomes. Our results suggest that for continuous outcomes, 20.03% of the data used in meta-analyses cannot be reproduced at the trial level, and 43.44% of the data cannot be reproduced at the meta-analysis level. For binary outcomes, the proportions were 14.14% and 40.74%. In total, 83.33% of the data cannot be reproduced at the systematic review level. Our further analysis suggested that these reproducibility issues would lead to as much as 6.52% of the available meta-analyses changing the direction of the effects, and 9.78% changing the significance of the P-values. Sleep medicine systematic reviews and meta-analyses face serious issues in terms of data reproducibility, and further efforts are urgently needed to improve this situation.

Does the Sex of the Firstborn Child Affect the Breast Cancer Risk and Survival: A Systematic Review and Meta-analysis of Over 1 Million Cases

Background: Reports on the risk and prognosis of breast cancer in relation to the sex of a child have been conflicting. Since medical sciences play an important role in informing sociocultural understandings of health and illness, evidence-based studies have the potential to foster or counter stigma and shape social attitudes toward a newborn's sex. Aims: To pool all available evidence to provide the highest level of evidence on the association between the sex of the first child and breast cancer risk or prognosis. Study Design: Systematic review and meta-analyses. Methods: A comprehensive search using three databases was conducted from inception until May 2020. Titles and abstracts of all papers identified were independently screened by two authors. Data extraction and quality assessment were also performed independently by two researchers. The breast cancer risk was quantified using the odds ratio, and the prognosis (i.e., mortality) was measured using the risk ratio. Results: In the meta-analysis, 11 studies with more than 1 million participants were included. The pooled estimate from the five studies on risk and the six studies on prognosis were odds ratio 0.99 (95% confidence interval, 0.95-1.03) and risk ratio 1.00 (95% confidence interval, 0.80-1.26), respectively. Conclusion: When we pooled all available evidence, the sex of the firstborn child was neither associated with risk nor prognosis in breast cancer. Clinically, our findings are reassuring and important, especially in light of previous studies that recommended differential treatment and counseling based on the sex of the first child. Socially, our findings challenge conventional social stereotypes that regard male children as biologically superior to female children.

Duration of COVID-19 mRNA Vaccine Effectiveness against Severe Disease.

Waning immunity following administration of mRNA-based COVID-19 vaccines remains a concern for many health systems. We undertook a study to determine if recent reports of waning for severe disease could have been attributed to design-related bias by conducting a study only among those detected with a first SARS-CoV-2 infection. We used a matched case-control study design with the study base being all individuals with first infection with SARS-CoV-2 reported in the State of Qatar between 1 January 2021 and 20 February 2022. Cases were those detected with first SARS-CoV-2 infection requiring intensive care (hard outcome), while controls were those detected with first SARS-CoV-2 infection who recovered without the need for intensive care. Cases and controls were matched in a 1:30 ratio for the calendar month of infection and the comorbidity category. Duration and magnitude of conditional vaccine effectiveness against requiring intensive care and the number needed to vaccinate (NNV) to prevent one more case of COVID-19 requiring intensive care was estimated for the mRNA (BNT162b2/mRNA-1273) vaccines. Conditional vaccine effectiveness against requiring intensive care was 59% (95% confidence interval (CI), 50 to 76) between the first and second dose, and strengthened to 89% (95% CI, 85 to 92) between the second dose and 4 months post the second dose in persons who received a primary course of the vaccine. There was no waning of vaccine effectiveness in the period from 4 to 6, 6 to 9, and 9 to 12 months after the second dose. This study demonstrates that, contrary to mainstream reports using hierarchical measures of effectiveness, conditional vaccine effectiveness against requiring intensive care remains robust till at least 12 months after the second dose of mRNA-based vaccines.

Perspectives of Persons With Type 2 Diabetes Toward Diabetes Self-Management: A Qualitative Study.

Background. The global increase in type 2 diabetes (T2D) poses a significant public health challenge worldwide. Due to the chronic and complex nature of the disease, management does not depend on pharmacotherapy alone; rather, a comprehensive medical and self-management plan is required. Diabetes Self-Management Education programs should address diabetes-specific behaviors and be grounded in patients' perceptions of their disease and its consequences. Aim. The study aims to understand perceptions of diabetes self-management (DSM) among persons of different nationalities with T2D living in Qatar. Method. A phenomenological qualitative study was implemented using four focus group interviews using Triandis Interpersonal Behavior Model to understand factors influencing DSM perceptions and behaviors. Therefore, deductive content analysis was used, also inductive content analysis used to find new emerging themes. Twenty-nine participants with T2D of 12 different nationalities were recruited. Results. Content analyses revealed that participants were mainly motivated to manage their diabetes by fear of future health complications-and the resulting impact on their families-triggered by witnessing these complications on other family members and friends. Factors that influenced DSM included cultural factors such as food content and holidays' customs, weather conditions, psychological distress, and social factors such as lack of family support. Furthermore, access to healthy food, number of working hours and time, and cost of DSM supplies were found to be among the barriers to DSM. Conclusion. Understanding and considering patients' perspectives is a core component of culturally competent and evidence-based DSM programs, and it should be considered in any DSM program.

A Delphi consensus study introducing a Problem And attRibutes-bAsed DIabetes self-manaGeMent (PARADIGM) intervention for patients with type 2 diabetes.

AIM: Encouraging patients to improve their self-management behavior based on a strict definition of the intervention is important for a standardized delivery but, until recently, there was no consensus on the core attributes that define such an intervention. The purpose of this study is to generate a core-attribute based and stakeholder-informed problem-based curriculum for promotion of type 2 diabetes self-management structured around five core attributes derived from a previous concept analysis that defined the intervention. METHODS: Using a Delphi process for consensus achievement, physicians, clinical epidemiologists and allied health care professionals completed eleven rounds of online meetings over 6 months. RESULTS: Core self-management skills were identified by consensus for each of the five attributes and then used to design a model case and interactions of a problem-based self-management education intervention for delivery in a health care setting. Five model cases and associated interactions were developed by consensus for delivery in group-based and problem-based learning sessions. CONCLUSIONS: The final structured curriculum will be useful to inform and standardize diabetes self-management based on a clear conceptual definition of the intervention and can thus help make the latter more effective tools for encouraging persons with type 2 diabetes to self manage their condition.