Imprecision in tuberculosis infection outcomes; implications for non-inferiority vaccine trials
Grint, D. J.; White, R. G.; Chruchyard, G.; Fiore-Gartland, A.; Rangaka, M. X.; Garcia-Basteiro, A. L.; Cobelens, F.
Show abstract
IntroductionRandomised trials comparing new vaccines against tuberculosis for use in neonates and infants, for whom Bacille Calmette-Guerin (BCG) vaccination is established practice, are using tuberculosis infection as the primary endpoint in a non-inferiority design. Markers of tuberculosis infection have imperfect sensitivity and specificity. Flaws in the non-inferiority trial design typically bias towards the null, which may result in falsely declaring non-inferiority. MethodsWe conducted a statistical simulation study to assess the impact of imperfect markers of tuberculosis infection on the interpretation of tuberculosis vaccine trials testing a non-inferiority hypothesis of an infection primary outcome in a two-arm randomized comparison. Data were generated in three 2-year cumulative risk of tuberculosis infection scenarios (2%, 5%, and 8%). The specificity of tests of tuberculosis infection was assumed to range from 100% to 85%, while the sensitivity was assumed to range from 100% to 64%. Log-binomial regression was used to estimate the relative risk of tuberculosis infection. ResultsWith 100% sensitivity and specificity, type-I and type-II error were both approximately equal to the expected values (2.5% and 80%, respectively) in all three cumulative tuberculosis risk scenarios. With modest deviations from perfect sensitivity and specificity (95% for both), the risk of falsely declaring non-inferiority was 96.8%, 53.2%, and 27.8% in the 2%, 5%, and 8% cumulative tuberculosis risk infection scenarios, respectively. DiscussionTuberculosis vaccine non-inferiority trials using an infection primary outcome must be designed and interpreted accounting for the specificity of the tools used to measure infection, otherwise they risk declaring non-inferiority by default. Key messagesO_LIWe conducted a statistical simulation study to assess the impact of imperfect sensitivity and specificity, in the primary outcome definition of tuberculosis infection, in vaccine trials testing a non-inferiority hypothesis. C_LIO_LIWith only modest departures from perfect specificity in tuberculosis infection markers, the risk of falsely declaring non-inferiority is substantial. C_LIO_LIVaccine trials testing a non-inferiority hypothesis with an infection primary outcome must account for the imprecision in the tools used to define the outcome, otherwise vaccines may be falsely declared non-inferior. C_LI
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Protection of prior natural infection compared to mRNA vaccination against SARS-CoV-2 infection and severe COVID-19 in Qatar 91%
- Artemether-lumefantrine with or without single-dose primaquine and sulfadoxine-pyrimethamine plus amodiaquine with or without single-dose tafenoquine to reduce Plasmodium falciparum transmission: a phase 2 single-blind randomised clinical trial in Ouelessebougou, Mali 91%
- Mortality of Drug-resistant Tuberculosis in High-burden Countries: Comparison of Routine Drug Susceptibility Testing with Whole-genome Sequencing 89%
Similar papers in this journal
- Treatment for radiographically active, sputum culture-negative pulmonary tuberculosis: a systematic review and meta-analysis 93%
- Same-day versus rapid ART initiation in HIV-positive individuals presenting with symptoms of tuberculosis: protocol for an open-label randomized non-inferiority trial in Lesotho and Malawi 92%
- Using numerical modelling and simulation to assess the ethical burden in clinical trials and how it relates to the proportion of responders in a trial sample 92%
Similar papers in this journal
- Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya 92%
- Global and regional burden of attributable and associated bacterial antimicrobial resistance avertable by vaccination: modelling study 92%
- Modelling the epidemiological and economic impact of digital adherence technologies with differentiated care for tuberculosis treatment in Ethiopia 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.