Perceived glucose levels matter more than CGM-based data in predicting diabetes distress in type 1 or type 2 diabetes: a precision mental health approach using n-of-1 analyses.

AIMS/HYPOTHESIS: Diabetes distress is one of the most frequent mental health issues identified in people with type 1 and type 2 diabetes. Little is known about the role of glucose control as a potential contributor to diabetes distress and whether the subjective perception of glucose control or the objective glycaemic parameters are more important for the experience. With the emergence of continuous glucose monitoring (CGM), this is a relevant question as glucose values are now visible in real-time. We employed a precision monitoring approach to analyse the independent associations of perceived and measured glucose control with diabetes distress on a daily basis. By using n-of-1 analyses, we aimed to identify individual contributors to diabetes distress per person and analyse the associations of these individual contributors with mental health at a 3 month follow-up. METHODS: In this prospective, observational study, perceived (hypoglycaemia/hyperglycaemia/glucose variability burden) and measured glucose control (time in hypoglycaemia and hyperglycaemia, CV) were assessed daily for 17 days using an ecological momentary assessment (EMA) approach with a special EMA app and CGM, respectively. Mixed-effect regression analysis was performed, with daily diabetes distress as the dependent variable and daily perceived and CGM-measured metrics of glucose control as random factors. Individual regression coefficients of daily distress with perceived and CGM-measured metrics were correlated with levels of psychosocial well-being at a 3 month follow-up. RESULTS: Data from 379 participants were analysed (50.9% type 1 diabetes; 49.6% female). Perceived glucose variability (t=14.360; p<0.0001) and perceived hyperglycaemia (t=13.637; p<0.0001) were the strongest predictors of daily diabetes distress, while CGM-based glucose variability was not significantly associated (t=1.070; p=0.285). There was great heterogeneity between individuals in the associations of perceived and measured glucose parameters with diabetes distress. Individuals with a stronger association between perceived glucose control and daily distress had more depressive symptoms (ß=0.32), diabetes distress (ß=0.39) and hypoglycaemia fear (ß=0.34) at follow-up (all p<0.001). Individuals with a stronger association between CGM-measured glucose control and daily distress had higher levels of psychosocial well-being at follow-up (depressive symptoms: ß=-0.31; diabetes distress: ß=-0.33; hypoglycaemia fear: ß=-0.27; all p<0.001) but also higher HbA1c (ß=0.12; p<0.05). CONCLUSIONS/INTERPRETATION: Overall, subjective perceptions of glucose seem to be more influential on diabetes distress than objective CGM parameters of glycaemic control. N-of-1 analyses showed that CGM-measured and perceived glucose control had differential associations with diabetes distress and psychosocial well-being 3 months later. The results highlight the need to understand the individual drivers of diabetes distress to develop personalised interventions within a precision mental health approach.

Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial.

Background: Mental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI). Methods: A total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests. Results: The acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p < 0.001), social influence (γ = 0.23, p = .032) and trust (γ = 0.27, p = .040) were identified as potential determinants of acceptance, explaining 84% of the variance. SEM model fit was acceptable (RMSEA = 0.073, SRMR = 0.059). The intervention did not significantly impact acceptance (γ = 0.25, 95%-CI: -0.16-0.65, p = .233), interest (OR = 0.76, 95% CI: 0.38-1.52, p = .445) or app installation rates (OR = 1.13, 95% CI: 0.47-2.73, p = .777). Discussion: The high variance in acceptance supports a need for acceptance facilitating procedures. The analyzed model supported performance expectancy, social influence, and trust as potential determinants of smart sensing acceptance; perceived benefit was the most influential factor towards acceptance. The AFI was not significant. Future research should further explore factors contributing to smart sensing acceptance and address implementation barriers.

Validation of the Portuguese version of the diabetes self-management questionnaire-revised (DSMQ-R) in people with type 2 diabetes mellitus.

BACKGROUND: Reflecting people with diabetes' self-management activities is often required in both research and clinical practice. This study evaluated the measurement properties of the Portuguese version of the Diabetes Self-Management Questionnaire-Revised (DSMQ-R) on a sample of people with type 2 diabetes mellitus (T2DM). METHODS: Translation and cultural adaptation were conducted according to guidelines for cross-cultural adaptation and validation of healthcare measurement instruments. A cross-sectional study was performed including 365 people with T2DM in primary care. Reliability, construct validity, and criterion validity were analyzed. RESULTS: The total scale of the translated DSMQ-R revealed sufficient internal consistency (alpha = 0.82), and most of the subscales performed adequately. The exploratory factor structure was robust, and confirmatory analysis showed a good model fit with the scale structure of the original scale. The scale scores correlated with the participants' last HbA1c estimates, supporting convergent validity, and convergence was confirmed by the adequate average variance extracted. CONCLUSIONS: The Portuguese version of the DSMQ-R is a reliable and valid tool for gauging self-management behaviors in people with T2DM and their relationship with glycemic values.

Anatomic versus non-anatomic liver resection for hepatocellular carcinoma-A European multicentre cohort study in cirrhotic and non-cirrhotic patients.

BACKGROUND: The incidence of hepatocellular carcinoma (HCC) is increasing in the western world over the past decades. As liver resection (LR) represents one of the most efficient treatment options, advantages of anatomic (ALR) versus non-anatomic liver resection (NALR) show a lack of consistent evidence. Therefore, the aim of this study was to investigate complications and survival rates after both resection types. METHODS: This is a multicentre cohort study using retrospectively and prospectively collected data. We included all patients undergoing LR for HCC between 2009 and 2020 from three specialised centres in Switzerland and Germany. Complication and survival rates after ALR versus NALR were analysed using uni- and multivariate Cox regression models. RESULTS: Two hundred and ninety-eight patients were included. Median follow-up time was 52.76 months. 164/298 patients (55%) underwent ALR. Significantly more patients with cirrhosis received NALR (n = 94/134; p < 0.001). Complications according to the Clavien Dindo classification were significantly more frequent in the NALR group (p < 0.001). Liver failure occurred in 13% after ALR versus 8% after NALR (p < 0.215). Uni- and multivariate cox regression models showed no significant differences between the groups for recurrence free survival (RFS) and overall survival (OS). Furthermore, cirrhosis had no significant impact on OS and RFS. CONCLUSION: No significant differences on RFS and OS rates could be observed. Post-operative complications were significantly less frequent in the ALR group while liver specific complications were comparable between both groups. Subgroup analysis showed no significant influence of cirrhosis on the post-operative outcome of these patients.

Strength of Statistical Evidence for the Efficacy of Cancer Drugs: A Bayesian Re-Analysis of Randomized Trials Supporting FDA Approval.

OBJECTIVE: To quantify the strength of statistical evidence of randomised controlled trials (RCTs) for novel cancer drugs approved by the Food and Drug Administration (FDA) in the last two decades. STUDY DESIGN AND SETTING: We used data on overall survival (OS), progression-free survival (PFS), and tumour response (TR) for novel cancer drugs approved for the first time by the FDA between January 2000 and December 2020. We assessed strength of statistical evidence by calculating Bayes Factors (BFs) for all available endpoints, and we pooled evidence using Bayesian fixed-effect meta-analysis for indications approved based on two RCTs. Strength of statistical evidence was compared between endpoints, approval pathways, lines of treatment, and types of cancer. RESULTS: We analysed the available data from 82 RCTs corresponding to 68 indications supported by a single RCT and seven indications supported by two RCTs. Median strength of statistical evidence was ambiguous for OS (BF = 1.9; IQR 0.5-14.5), and strong for PFS (BF = 24,767.8; IQR 109.0-7.3*106) and TR (BF = 113.9; IQR 3.0-547,100). Overall, 44 indications (58.7%) were approved without clear statistical evidence for OS improvements and seven indications (9.3%) were approved without statistical evidence for improvements on any endpoint. Strength of statistical evidence was lower for accelerated approval compared to non-accelerated approval across all three endpoints. No meaningful differences were observed for line of treatment and cancer type. LIMITATIONS: This analysis is limited to statistical evidence. We did not consider non-statistical factors (e.g., risk of bias, quality of the evidence). CONCLUSION: BFs offer novel insights into the strength of statistical evidence underlying cancer drug approvals. Most novel cancer drugs lack strong statistical evidence that they improve OS, and a few lack statistical evidence for efficacy altogether. These cases require a transparent and clear explanation. When evidence is ambiguous, additional post-marketing trials could reduce uncertainty.

Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19 from an international collaborative meta-analysis of randomized trials

Investimento substancial em pesquisa COVID-19 foi alocado para ensaios clínicos randomizados (ECRs) sobre hidroxicloroquina/cloroquina, que atualmente enfrentam desafios de recrutamento ou descontinuação precoce. Nosso objetivo é estimar os efeitos da hidroxicloroquina e da cloroquina sobre a sobrevivência em COVID-19 de todas as evidências de RCT atualmente disponíveis, publicadas e não publicadas. Apresentamos uma rápida meta-análise de ECRs em andamento, concluídos ou descontinuados em tratamento com hidroxicloroquina ou cloroquina para qualquer paciente com COVID-19 (protocolo: : https://osf.io/QESV4/). Identificamos sistematicamente ECRs não publicados (ClinicalTrials.gov, WHO Plataforma Internacional de Registro de Ensaios Clínicos, registro Cochrane COVID até 11 de junho de 2020), e ECRs publicados (PubMed, medRxiv e bioRxiv até 16 de outubro de 2020). Todas as causas mortalidade foi extraída (publicações/pré-impressões) ou solicitada aos investigadores e combinados em meta-análises de efeitos aleatórios, calculando odds ratio (ORs) com intervalos de confiança de 95% (ICs), separadamente para hidroxicloroquina e cloroquina. Pré-especificado as análises de subgrupo incluem configuração do paciente, confirmação de diagnóstico, tipo de controle e status de publicação. Sessenta e três estudos eram potencialmente elegíveis. Incluímos 14 ensaios não publicados (1308 pacientes) e 14 publicações/preprints (9011 pacientes). Resultados para hidroxicloroquina são dominados por RECOVERY e WHO SOLIDARITY, dois ensaios altamente pragmáticos, que empregaram doses relativamente altas e incluíram 4.716 e 1.853 pacientes, respectivamente (67% dos o tamanho total da amostra). O OR combinado na mortalidade por todas as causas para hidroxicloroquina é 1,11 (IC 95%: 1,02, 1,20; I² = 0%; 26 ensaios; 10.012 pacientes) e para cloroquina 1,77 (IC 95%: 0,15, 21,13, I² = 0%; 4 ensaios; 307 pacientes). Não identificamos efeitos de subgrupo. Nós achamos isso tratamento com hidroxicloroquina está associado ao aumento da mortalidade na COVID-19 pacientes, e não há benefício da cloroquina. Os achados não têm generalização clara para ambulatorial, crianças, gestantes e pessoas com comorbidades.