Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study

OBJECTIVE: Clinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA1c. RESEARCH DESIGN AND METHODS: We used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged ≥35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA1c models. RESULTS: A total of 139 626 patients registered in 400 general practices, aged 63±12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3±2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had ≥1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA1c for all outcomes. Findings were consistent in the validation cohort. CONCLUSIONS: Higher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes

Functional outcomes of multi-condition collaborative care and successful ageing: results of randomised trial

Objective To evaluate the effectiveness of integrated care for chronic physical diseases and depression in reducing disability and improving quality of life

Emulator-based Bayesian calibration of the CISNET colorectal cancer models

PURPOSE: To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET) 's SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.METHODS: We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANN) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.RESULTS: The optimal ANN for SimCRC had four hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had one hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 hours for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.CONCLUSIONS: Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, like the CISNET CRC models.</p

Assessing the severity of Type 2 diabetes using clinical data-based measures:a systematic review

Aims To identify and critically appraise measures that use clinical data to grade the severity of Type 2 diabetes. Methods We searched MEDLINE, Embase and PubMed between inception and June 2018. Studies reporting on clinical data‐based diabetes‐specific severity measures in adults with Type 2 diabetes were included. We excluded studies conducted solely in participants with other types of diabetes. After independent screening, the characteristics of the eligible measures including design and severity domains, the clinical utility of developed measures, and the relationship between severity levels and health‐related outcomes were assessed. Results We identified 6798 studies, of which 17 studies reporting 18 different severity measures (32 314 participants in 17 countries) were included: a diabetes severity index (eight studies, 44%); severity categories (seven studies, 39%); complication count (two studies, 11%); and a severity checklist (one study, 6%). Nearly 89% of the measures included diabetes‐related complications and/or glycaemic control indicators. Two of the severity measures were validated in a separate study population. More severe diabetes was associated with increased healthcare costs, poorer cognitive function and significantly greater risks of hospitalization and mortality. The identified measures differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively. Conclusions Health records are suitable for assessment of diabetes severity; however, the clinical uptake of existing measures is limited. The need to advance this research area is fundamental as higher levels of diabetes severity are associated with greater risks of adverse outcomes. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services

Evaluating risk factor assumptions: a simulation-based approach

<p>Abstract</p> <p>Background</p> <p>Microsimulation models are an important tool for estimating the comparative effectiveness of interventions through prediction of individual-level disease outcomes for a hypothetical population. To estimate the effectiveness of interventions targeted toward high risk groups, the mechanism by which risk factors influence the natural history of disease must be specified. We propose a method for evaluating these risk factor assumptions as part of model-building.</p> <p>Methods</p> <p>We used simulation studies to examine the impact of risk factor assumptions on the relative rate (RR) of colorectal cancer (CRC) incidence and mortality for a cohort with a risk factor compared to a cohort without the risk factor using an extension of the CRC-SPIN model for colorectal cancer. We also compared the impact of changing age at initiation of screening colonoscopy for different risk mechanisms.</p> <p>Results</p> <p>Across CRC-specific risk factor mechanisms, the RR of CRC incidence and mortality decreased (towards one) with increasing age. The rate of change in RRs across age groups depended on both the risk factor mechanism and the strength of the risk factor effect. Increased non-CRC mortality attenuated the effect of CRC-specific risk factors on the RR of CRC when both were present. For each risk factor mechanism, earlier initiation of screening resulted in more life years gained, though the magnitude of life years gained varied across risk mechanisms.</p> <p>Conclusions</p> <p>Simulation studies can provide insight into both the effect of risk factor assumptions on model predictions and the type of data needed to calibrate risk factor models.</p

The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort

Background: Presence of additional chronic conditions has significant impact on the treatment and management of type-2 diabetes (T2DM). Little is known about the patterns of comorbidities in this population. The aims of this study are to quantify comorbidity patterns in people with T2DM, to estimate the prevalence of six chronic conditions in 2027 and to identify clusters of similar conditions. Methods: We used the Clinical Practice Research Datalink (CPRD) linked with the Index of Multiple Deprivation (IMD) data to identify patients diagnosed with T2DM between 2007 and 2017. 102,394 people met the study inclusion criteria. We calculated the crude and age-standardised prevalence of 18 chronic conditions present at and after the T2DM diagnosis. We analysed longitudinally the 6 most common conditions and forecasted their prevalence in 2027 using linear regression. We used agglomerative hierarchical clustering to identify comorbidity clusters. These analyses were repeated on subgroups stratified by gender and deprivation. Results: More people living in the most deprived areas had ≥1 comorbidities present at the time of diagnosis (72% of females; 64% of males) compared to the most affluent areas (67% of females; 59% of males). Depression prevalence increased in all strata, and was more common in the most deprived areas. Depression was predicted to affect 33% of females and 15% of males diagnosed with T2DM in 2027. Moderate clustering tendencies were observed, with concordant conditions grouped together and some variations between groups of different demographics. Conclusions: Comorbidities are common in this population and high between-patient variability in comorbidity patterns emphasises the need for patient-centred healthcare. Mental health is a growing concern and there is a need for interventions that target both physical and mental health in this population

Comparative economic evaluation of data from the ACRIN national CT colonography trial with three cancer intervention and surveillance modeling network microsimulations

Purpose: To estimate the cost-effectiveness of computed tomographic (CT) colonography for colorectal cancer (CRC) screening in average-risk asymptomatic subjects in the United States aged 50 years. Materials and Methods: Enrollees in the American College of Radiology Imaging Network National CT Colonography Trial provided informed consent, and approval was obtained from the institutional review board at each site. CT colonography performance estimates from the trial were incorporated into three Cancer Intervention and Surveillance Modeling Network CRC microsimulations. Simulated survival and lifetime costs for screening 50-year-old subjects in the United States with CT colonography every 5 or 10 years were compared with those for guideline-concordant screening with colonoscopy, flexible sigmoidoscopy plus either sensitive unrehydrated fecal occult blood testing (FOBT) or fecal immunochemical testing (FIT), and no screening. Perfect and reduced screening adherence scenarios were considered. Incremental cost-effectiveness and net health benefits were estimated from the U.S. health care sector perspective, assuming a 3% discount rate. Results: CT colonography at 5- and 10-year screening intervals was more costly and less effective than FOBT plus flexible sigmoidoscopy in all three models in both 100% and 50% adherence scenarios. Colonoscopy also was more costly and less effective than FOBT plus flexible sigmoidoscopy, except in the CRC-SPIN model assuming 100% adherence (incremental cost-effectiveness ratio: $26 300 per life-year gained). CT colonography at 5- and 10-year screening intervals and colonoscopy were net beneficial compared with no screening in all model scenarios. The 5-year screening interval was net beneficial over the 10-year interval except in the MISCAN model when assuming 100$50 000 per life-year gained. Conclusion: All three models predict CT colonography to be more costly and less effective than non-CT colonographic screening but net beneficial compared with no screening given model assumptions

Parenting-by-gender interactions in child psychopathology: attempting to address inconsistencies with a Canadian national database

<p>Abstract</p> <p>Background</p> <p>Research has shown strong links between parenting and child psychopathology. The moderating role of child gender is of particular interest, due to gender differences in socialization history and in the prevalence of psychiatric disorders. Currently there is little agreement on how gender moderates the relationship between parenting and child psychopathology. This study attempts to address this lack of consensus by drawing upon two theories (self-salience vs. gender stereotyped misbehaviour) to determine how child gender moderates the role of parenting, if at all.</p> <p>Methods</p> <p>Using generalized estimating equations (GEE) associations between three parenting dimensions (hostile-ineffective parenting, parental consistency, and positive interaction) were examined in relationship to child externalizing (physical aggression, indirect aggression, and hyperactivity-inattention) and internalizing (emotional disorder-anxiety) dimensions of psychopathology. A sample 4 and 5 year olds from the National Longitudinal Survey of Children and Youth (NLSCY) were selected for analysis and followed over 6 years (N = 1214). Two models with main effects (Model 1) and main effects plus interactions (Model 2) were tested.</p> <p>Results</p> <p>No child gender-by-parenting interactions were observed for child physical aggression and indirect aggression. The association between hostile-ineffective parenting and child hyperactivity was stronger for girls, though this effect did not reach conventional levels of statistical significance (<it>p </it>= .059). The associations between parenting and child emotional disorder did vary as a function of gender, where influences of parental consistency and positive interaction were stronger for boys.</p> <p>Discussion</p> <p>Despite the presence of a few significant interaction effects, hypotheses were not supported for either theory (i.e. self-salience or gender stereotyped misbehaviour). We believe that the inconsistencies in the literature regarding child gender-by-parenting interactions is due to the reliance on gender as an indicator of a different variable which is intended to explain the interactions. This may be problematic because there is likely within-gender and between-sample variability in such constructs. Future research should consider measuring and modelling variables that are assumed to explain such interactions when conducting gender-by-parenting research.</p

Improving the utility of evidence synthesis for decision makers in the face of insufficient evidence.

OBJECTIVE: To identify and suggest strategies to make insufficient evidence ratings in systematic reviews more actionable. STUDY DESIGN AND SETTING: A workgroup comprising members from the Evidence-Based Practice (EPC) Program of the Agency for Healthcare Research and Quality convened throughout 2020. We conducted iterative discussions considering information from three data sources: a literature review for relevant publications and frameworks, a review of a convenience sample of past systematic reviews conducted by the EPCs, and an audit of methods used in past EPC technical briefs. RESULTS: We identified five strategies for supplementing systematic review findings when evidence on benefits or harms is expected to be, or found to be, insufficient: 1) reconsider eligible study designs, 2) summarize indirect evidence, 3) summarize contextual and implementation evidence, 4) consider modelling, and 5) incorporate unpublished health system data in the evidence synthesis. While these strategies may not increase the strength of evidence, they may improve the utility of reports for decision makers. Adopting these strategies depends on feasibility, timeline, funding, and expertise of the systematic reviewers. CONCLUSION: Throughout the process of evidence synthesis of early scoping, protocol development, review conduct, and review presentation, authors can consider these five strategies to supplement evidence with insufficient rating to make it more actionable for end-users