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Polish Archives of Internal Medicine Sep 2023Although it is well established that 2 doses of COVID‑19 vaccines are associated with reduced immune responses in liver transplant recipients (LTRs), studies regarding... (Meta-Analysis)
Meta-Analysis
INTRODUCTION
Although it is well established that 2 doses of COVID‑19 vaccines are associated with reduced immune responses in liver transplant recipients (LTRs), studies regarding their immunogenicity and tolerability after a booster dose are limited.
OBJECTIVES
We aimed to review the available literature data regarding antibody responses and safety of the third dose of COVID‑19 vaccines in LTRs.
METHODS
We searched PubMed and Google Scholar for eligible studies. The primary outcome was to compare the rates of seroconversion after the second and third dose of COVID‑19 vaccine in LTRs. This meta‑analysis was performed using a generalized linear mixed model and the Clopper and Pearson method was employed to calculate the 2‑sided CIs.
RESULTS
Six prospective studies involving 596 LTRs met the inclusion criteria. The pooled rate of antibody response before the third dose was 71% (95% CI, 56%-83%; heterogeneity, I2 = 90%; P <0.001), while after the third dose it was 94% (95% CI, 91%-96%; heterogeneity, I2 = 17%; P = 0.31). There was no difference in antibody responses after the third dose in relation to the use of calcineurin inhibitors (P = 0.44) or mammalian target of rapamycin inhibitors (P = 0.33), while the pooled rate of antibody responses in the patients on mycophenolate mofetil (MMF) was 88% (95% CI, 83%-92%; heterogeneity, I2 = 0%; P = 0.57). It was significantly lower (P <0.001), as compared with those on MMF‑free immunosuppression (pooled rate, 97%; 95% CI, 95%-98%; heterogeneity, I2 = 30%; P = 0.22). No safety concerns were reported for the booster dose.
CONCLUSIONS
Our meta‑analysis demonstrated that the third dose of COVID‑19 vaccines induced adequate humoral and cellular immune responses in LTRs, while MMF remained a negative predictor of immunologic responses.
Topics: Humans; COVID-19 Vaccines; Seroconversion; COVID-19; Liver Transplantation; Prospective Studies; Mycophenolic Acid
PubMed: 36876925
DOI: 10.20452/pamw.16455 -
PLoS Pathogens Apr 2024Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing...
Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.
Topics: Humans; Mycobacterium tuberculosis; Tuberculosis, Multidrug-Resistant; Models, Theoretical; Antitubercular Agents
PubMed: 38598556
DOI: 10.1371/journal.ppat.1011574 -
The Journal of Arthroplasty Mar 2024
Meta-Analysis
Topics: Humans; Rifampin; Arthroplasty
PubMed: 38341235
DOI: 10.1016/j.arth.2023.11.015 -
The Journal of Arthroplasty Mar 2024
Meta-Analysis
Topics: Humans; Rifampin; Arthroplasty; Arthroplasty, Replacement, Knee
PubMed: 38341234
DOI: 10.1016/j.arth.2023.10.061 -
The Journal of Infectious Diseases May 2024Adaptive platform trials can be more efficient than classic trials for developing new treatments. Moving from culture-based to simpler- or faster-to-measure biomarkers...
Adaptive platform trials can be more efficient than classic trials for developing new treatments. Moving from culture-based to simpler- or faster-to-measure biomarkers as efficacy surrogates may enhance this advantage. We performed a systematic review of treatment efficacy biomarkers in adults with tuberculosis. Platform trials can span different development phases. We grouped biomarkers as: α, bacterial load estimates used in phase 2a trials; β, early and end-of treatment end points, phase 2b-c trials; γ, posttreatment or trial-level estimates, phase 2c-3 trials. We considered as analysis unit (biomarker entry) each combination of biomarker, predicted outcome, and their respective measurement times or intervals. Performance metrics included: sensitivity, specificity, area under the receiver-operator curve (AUC), and correlation measures, and classified as poor, promising, or good. Eighty-six studies included 22 864 participants. From 1356 biomarker entries, 318 were reported with the performance metrics of interest, with 103 promising and 41 good predictors. Group results were: α, mycobacterial RNA and lipoarabinomannan (LAM) in sputum, and host metabolites in urine; β, mycobacterial RNA and host transcriptomic or cytokine signatures for early treatment response; and γ, host transcriptomics for recurrence. A combination of biomarkers from different categories could help in designing more efficient platform trials. Efforts to develop efficacy surrogates should be better coordinated.
Topics: Humans; Biomarkers; Tuberculosis; Mycobacterium tuberculosis; Bacterial Load; Treatment Outcome; Antitubercular Agents; Clinical Trials as Topic
PubMed: 37956107
DOI: 10.1093/infdis/jiad482 -
Current Drug Safety 2024Tuberculosis is still one of the top causes of infection-related death globally. Drug-resistant tuberculosis has a high mortality rate and is still a serious public...
BACKGROUND
Tuberculosis is still one of the top causes of infection-related death globally. Drug-resistant tuberculosis has a high mortality rate and is still a serious public health concern around the world. The appearance of multidrug-resistant and extensively drug-resistant strains of tuberculosis has increased the need for new therapeutic options against these strains. Most of the drugs used to treat them have been poorly tested and have serious negative effects. Patients with drug-resistant tuberculosis have been fighting for access to experimental medications, particularly bedaquiline.
OBJECTIVE
The study aimed to summarise the existing evidence of bedaquiline's safety on drugresistant tuberculosis treatment outcome and look for bedaquiline-related adverse drug reactions in the Pharmacovigilance Programme of India and World Health Organisation - Uppsala Monitoring Centre database.
METHODS
We searched the PubMed database for relevant studies on the safety profile of bedaquiline used in the treatment of drug-resistant tuberculosis and bedaquiline-related adverse drug reactions in the Pharmacovigilance Programme of India and World Health Organisation - Uppsala Monitoring Centre database published up to April 25, 2022.
RESULTS
A total of 190 abstracts were identified through the Pubmed database. In a list of 157 fulltext eligible articles assessed, 149 were excluded as they did not meet the inclusion criteria. The complete articles of the remaining 8 studies were further evaluated. There were 4 prospective cohorts, 2 retrospective cohorts, and 2 case series.
CONCLUSION
Pharmacovigilance and medication safety monitoring of newer treatments, like bedaquiline, are critical for enhancing treatment support and adherence, especially among drugresistant tuberculosis patients.
Topics: Humans; Antitubercular Agents; Retrospective Studies; Prospective Studies; Tuberculosis, Multidrug-Resistant; Tuberculosis; Drug-Related Side Effects and Adverse Reactions; India
PubMed: 36655524
DOI: 10.2174/1574886318666230119102506 -
BMJ Open Respiratory Research Feb 2024The burden of non-adherence to anti-tuberculosis (TB) treatment is poorly understood. One type is early discontinuation, that is, stopping treatment early. Given the...
BACKGROUND
The burden of non-adherence to anti-tuberculosis (TB) treatment is poorly understood. One type is early discontinuation, that is, stopping treatment early. Given the implications of early discontinuation for treatment outcomes, we undertook a systematic review to estimate its burden, using the timing of loss to follow-up (LFU) as a proxy measure.
METHODS
Web of Science, Embase and Medline were searched up to 14 January 2021 using terms covering LFU, TB and treatment. Studies of adults (≥ 18 years) on the standard regimen for drug-sensitive TB reporting the timing of LFU (WHO definition) were included. A narrative synthesis was conducted and quality assessment undertaken using an adapted version of Downs and Black. Papers were grouped by the percentage of those who were ultimately LFU who were LFU by 2 months. Three groups were created: <28.3% LFU by 2 months, ≥28.3-<38.3%, ≥38.3%). The percentage of dose-months missed due to early discontinuation among (1) those LFU, and (2) all patients was calculated.
RESULTS
We found 40 relevant studies from 21 countries. The timing of LFU was variable within and between countries. 36/40 papers (90.0%) reported the percentage of patients LFU by the end of 2 months. 31/36 studies (86.1%) reported a higher than or as expected percentage of patients becoming LFU by 2 months. The percentage of dose-months missed by patients who became LFU ranged between 37% and 77% (equivalent to 2.2-4.6 months). Among all patients, the percentage of dose-months missed ranged between 1% and 22% (equivalent to 0.1-1.3 months).
CONCLUSIONS
A larger than expected percentage of patients became LFU within the first 2 months of treatment. These patients missed high percentages of dose months of treatment due to early discontinuation. Interventions to promote adherence and retain patients in care must not neglect the early months of treatment.
PROSPERO REGISTRATION NUMBER
CRD42021218636.
Topics: Adult; Humans; Follow-Up Studies; Treatment Outcome; Clinical Protocols; Antitubercular Agents
PubMed: 38359965
DOI: 10.1136/bmjresp-2023-001894