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BackgroundThe World Health Organization’s End TB Strategy envisions a world free of tuberculosis (TB)—free of deaths, disease, and suffering due to TB—by 2035. Nonadherence reduces cure rates, prolongs infectiousness, and contributes to the emergence of multidrug-resistant TB (MDR-TB). Moreover, MDR-TB is a growing, complex, and costly problem that presents a major obstacle to TB control. Directly observed therapy (DOT) for treatment adherence monitoring is the recommended standard; however, it is challenging to implement at scale because it is labor-intensive. Mobile health interventions can facilitate remote adherence monitoring and minimize the costs and inconveniences associated with standard DOT. ObjectiveThe study aims to evaluate the effectiveness of using video directly observed therapy (VDOT) plus incentives to improve medication adherence in TB treatment versus usual-care DOT in an African context. MethodsThe DOT Selfie study is an open-label, randomized controlled trial (RCT) with 2 parallel groups, in which 144 adult patients with TB aged 18-65 years will be randomly assigned to receive the usual-care DOT monitoring or VDOT as the intervention. The intervention will consist of a smartphone app, a weekly internet subscription, translated text message reminders, and incentives for those who adhere. The participant will use a smartphone to record and send time-stamped encrypted videos showing their daily medication ingestion. This video component will directly substitute the need for daily face-to-face meetings between the health provider and patients. We hypothesize that the VDOT intervention will be more effective because it allows patients to swallow their pills anywhere, anytime. Moreover, patients will receive mobile-phone–based “social bundle” incentives to motivate adherence to continued daily submission of videos to the health system. The health providers will log into a secured computer system to verify treatment adherence, document missed doses, investigate the reasons for missed doses, and follow prespecified protocol measures to re-establish medication adherence. The primary endpoint is the adherence level as measured by the fraction of expected doses observed over the treatment period. The main secondary outcome will be time-to-treatment completion in both groups. ResultsThis study was funded in 2019. Enrollment began in July and is expected to be completed by November 2020. Data collection and follow-up are expected to be completed by June 2021. Results from the analyses based on the primary endpoint are expected to be submitted for publication by December 2021. ConclusionsThis random control trial will be among the first to evaluate the effectiveness of VDOT within an African setting. The results will provide robust scientific evidence on the implementation and adoption of mobile health (mHealth) tools, coupled with incentives to motivate TB medication adherence. If successful, VDOT will apply to other low-income settings and a range of chronic diseases with lifelong treatment, such as HIV/AIDs. Trial RegistrationClinicalTrials.gov NCT04134689; http://clinicaltrials.gov/ct2/show/NCT04134689 International Registered Report Identifier (IRRID)DERR1-10.2196/18029

Introduction:Nonadherence to treatment remains an obstacle to tuberculosis (TB) control worldwide. The aim of this study was to evaluate the feasibility of using video directly observed therapy (VDOT) for supporting TB treatment adherence in Uganda. Methods:From May to December 2018, we conducted a pilot cohort study at a TB clinic in Kampala City. We enrolled patients aged 18-65 years with ≥3 months remaining of their TB treatment. Participants were trained to use a smartphone app to record videos of medication intake and submit them to a secured system. Trained health workers logged into the system to watch the submitted videos. The primary outcome was adherence measured as the fraction of expected doses observed (FEDO). In a secondary analysis, we examined differences in FEDO by sex, age, phone ownership, duration of follow-up, reasons for missed videos and patients' satisfaction at study exit. Results:Of 52 patients enrolled, 50 were analysed. 28 (56%) were male, the mean age was 31 years (range 19-50 years) and 35 (70%) owned smartphones. Of the 5150 videos expected, 4231 (82.2%) were received. The median FEDO was 85% (interquartile range 66%-94%) and this significantly differed by follow-up duration. Phone malfunction, uncharged battery and VDOT app malfunctions were the commonest reasons for missed videos. 92% of patients reported being very satisfied with using VDOT. Conclusion:VDOT was feasible and acceptable for monitoring and supporting TB treatment. It resulted in high levels of adherence, suggesting that digital technology holds promise in improving patient monitoring in Uganda.

Background Individual symptoms and signs of infectious mononucleosis (IM) are of limited value for diagnosis. Objective To develop and validate risk scores based on signs and symptoms with and without haematologic parameters for the diagnosis of IM. Design and setting Data were extracted from electronic health records of a university health centre and were divided into derivation (9/1/2015–10/31/2017) and a prospective temporal internal validation (11/1/2017–1/31/2019) cohort. Method Independent predictors for the diagnosis of IM were identified in univariate analysis using the derivation cohort. Logistic regression models were used to develop 2 risk scores: 1 with only symptoms and signs (IM-NoLab) and 1 adding haematologic parameters (IM-Lab). Point scores were created based on the regression coefficients, and patients were grouped into risk groups. Primary outcomes were area under the receiver operating characteristic curve (AUROCC) and classification accuracy. Results The IM-NoLab model had 4 predictors and identified a low-risk group (7.9% with IM) and a high-risk group (22.2%) in the validation cohort. The AUROCC was 0.75 in the derivation cohort and 0.69 in the validation cohort. The IM-Lab model had 3 predictors and identified a low-risk group (3.6%), a moderate-risk group (12.5%), and a high-risk group (87.6%). The AUROCC was 0.97 in the derivation cohort and 0.93 in the validation cohort. Conclusion We derived and internally validated the IM-NoLab and IM-Lab risk scores. The IM-Lab score in particular had very good discrimination and have the potential to reduce the need for diagnostic testing for IM. [ABSTRACT FROM AUTHOR]

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas., In the United States and in many Western countries, lung cancer represents the leading cause of cancer-related death (1). The 5-year, overall survival rate is 15% and has not improved [...]

We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard biomarkers are both measured on a set of patient samples, or adopting replicated measures of the error-contaminated standard biomarkers in the original study. This approach is easier to conduct and much less expensive than studies that require new samples from patients randomized to the intervention. In addition, it makes it possible to perform the estimation of the clinical performance quickly, since there will be no requirement to wait for events to occur as would be the case with prospective validation. The treatment selection is assessed via a working model, but the proposed estimator of the mean restricted lifetime is valid even if the working model is misspecified. The proposed approach is assessed through simulation studies and applied to a cancer study. [ABSTRACT FROM AUTHOR]