Impact of individual and environmental factors on dietary or lifestyle interventions to prevent type 2 diabetes development: a systematic review

BACKGROUND

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D.

METHODS

We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier.

RESULTS

The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition.

CONCLUSIONS

We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Who benefits most from outpatient lifestyle intervention? An IMI-SOPHIA study on pediatric individuals living with overweight and obesity

OBJECTIVE

The first-line approach for childhood obesity is lifestyle intervention (LI); however, success varies. This study aimed first to identify distinct subgroups of response in children living with overweight and obesity and second to elucidate predictors for subclusters.

METHODS

Based on the obesity patient follow-up registry the APV (Adipositas-Patienten-Verlaufsdokumentation) initiative, a total of 12,453 children and adolescents (median age: 11.5 [IQR: 9.7-13.2] years; BMI z score [BMIz]: 2.06 [IQR: 1.79-2.34]; 52.6% girls) living with overweight/obesity and participating in outpatient LI were studied. Longitudinal k-means clustering was used to identify individual BMIz response curve for up to 2 years after treatment initiation. Multinomial logistic regression was used to elucidate predictors for cluster membership.

RESULTS

A total of 36.3% of children and adolescents experienced "no BMIz loss." The largest subcluster (44.8%) achieved "moderate BMIz loss," with an average delta-BMIz of -0.23 (IQR: -0.33 to -0.14) at study end. A total of 18.9% had a "pronounced BMIz loss" up to -0.61 (IQR: -0.76 to -0.49). Younger age and lower BMIz at LI initiation, larger initial BMIz loss, and less social deprivation were linked with higher likelihood for moderate or pronounced BMIz loss compared with the no BMIz loss cluster (all p < 0.05).

CONCLUSIONS

These results support the importance of patient-tailored intervention and earlier treatment escalation in high-risk individuals who have little chance of success.

Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Race/Ethnicity and Gender Representation in Hematology and Oncology Editorial Boards: What is the State of Diversity?

INTRODUCTION

Women and underrepresented groups in medicine hold few academic leadership positions in the field of hematology/oncology. In this study, we assessed gender and race/ethnicity representation in editorial board positions in hematology/oncology journals.

MATERIALS AND METHODS

Editorial leadership board members from 60 major journals in hematology and oncology were reviewed; 54 journals were included in the final analysis. Gender and race/ethnicity were determined based on publicly available data for Editor-in-Chief (EiC) and Second-in-Command (SiC) (including deputy, senior, or associate editors). Descriptive statistics and chi-squared were estimated. In the second phase of the study, editors were emailed a 4-item survey to self-identify their demographics.

RESULTS

Out of 793 editorial board members, 72.6% were men and 27.4% were women. Editorial leadership were non-Hispanic white (71.1%) with Asian editorial board members representing the second largest majority at 22.5%. Women comprised only 15.9% of the EiC positions (90% White and 10% Asian). Women were about half as likely to be in the EiC position compared with men [pOR 0.47 (95% CI, 0.23-0.95, P = .03)]. Women represented 28.3% of SiC editorial positions. Surgical oncology had the lowest female representation at 2.3%.

CONCLUSION

Women and minorities are significantly underrepresented in leadership roles on Editorial Boards in hematology/oncology journals. Importantly, the representation of minority women physicians in EiC positions is at an inexorable zero.

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.

Evaluating the quality of clinical evidence in gastrointestinal cancers PubMed searches: How relevant are the results?

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Background: Bibliographic repositories have become increasingly important as clinical evidence is more accessible on the internet. Often, oncologists rely on published literature to guide patient care. However, with the proliferation of journals and increasing number of peer reviewed papers, current search strategies have the potential to retrieve large numbers of irrelevant or misleading articles. Moreover, access to current best evidence may require paid subscriptions. Here, we assessed the quality of retrieved medical literature pertaining to treatment of gastrointestinal cancers using the PubMed database. Methods: We interrogated 6 focused-therapy questions in 3 categories: medical oncology (MedOnc), surgical oncology (SurgOnc), and alternative medicine (AltMed). We extracted journal metrics of the first two pages (40 results) from each search. We defined the composite outcome “relevant result” as the product of removing results from 1) predatory journals (Beall’s list), 2) non-English language, and 3) no free access publications. As a sensitivity analysis, we defined 2007 as a cutoff for “relevant” publications and Impact Factor (IF) > 3 or H-index > 50. Results: Two hundred and forty results were retrieved (80 per search type). Forty-eight percent of the journals were European (n = 115), 40% US-based (n = 96), and 94% were in English (n = 225). Most journals (n = 170; 70.8%) had an IF between 1-10, followed by ̃21% with an IF > 10 (n = 51); yet ̃45% (n = 107) were in the Clarivate Analytics top quartile. Sixty percent (n = 139) of articles were free to access. The articles had a median H-index of 117 [IR 59, 168]. When modelling the multivariate association with “relevant result”, year of publication after 2007 had an OR = 1.07 (95% CI = 1.01-1.14; p< 0.02) and availability through GOLD Open Access by Clarivate Analytics had an OR = 1.09 (95% CI = 1.03-1.15; p< 0.0008). MedOnc retrieved more papers published in journals with IF > 10 (n = 31; 38.8%) than SurgOnc searches (n = 12; 15%; p< 0.001). Only the AltMed searches included non-peer reviewed publications (n = 4; 5%) and 4 results were from “predatory journals”, all in MedOnc. Conclusions: Articles had a 7% higher chance of being considered a “relevant result” if they were published after 2007 and a 9% higher chance if available under GOLD Open Access. Publications identified as “relevant results” with an IF or H-index above the established cutoffs, had a 6% higher chance to be in the top 40 PubMed search results. In the sensitivity analysis the results remain virtually unchanged. Importantly, nearly 40% of papers indexed in PubMed do not have free full-text articles, making them unavailable to oncologists without access to a medical library or paid subscription. These results highlight the imperative to deliver relevant, freely accessible information that can impact the care of the cancer patients.

Internal medicine residents’ awareness on cancer survivorship care plan: A cross sectional study

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Background: Survivorship care plans (SCPs) is recommended as a tool for communication between oncologists and primary care physicians. According to the Institute of Medicine, it is necessary to lead a cultural shift to provide SCPs to all cancer survivors to improve the transition from the oncology clinic to primary care practices. Studies suggest residency training curriculums for internal medicine (IM) are lacking education about cancer survivorship and SCPs. We aimed to assess the awareness of trainees toward SCPs. Methods: A survey was distributed to IM trainees in an outpatient setting. We stratified the descriptive analyses by program type (transitional [TY] and categorical [CT] trainees) and year of training. Differences in the proportions were tested appropriately. Analyses were conducted in R v3.6.2. Results: 37 trainees were interviewed; 32.4% were TY and 67.6% CT trainees. A 54% were PGY-1, 21.6% PGY-2, and 24.3% PGY-3. None of the trainees reported following a SCP for cancer-free patients nor to use SCP as a source to obtain cancer-related information. 78.3% and 92.6% reported that they were not taught during residency or medical school about SCPs, respectively. 84.8% informed that cancer-related information was inaccessible during the encounter with patients; sources cancer diagnosis and treatment information included: patients/family members (97.3%), outside records (83.8%), and oncology notes (86.5%). By program type, there was a statistically significant difference between TY v. CT groups (p = 0.017) regarding how often cancer-related issues were discussed with patients; the TY group mainly reported ‘Not at all’ whether CT were more likely to engage in discussion about cancer. Differences in the trainees’ comfort level answering patients concerns about cancer recurrence were observed between TY v. CT trainees but was not statistically significant (p = 0.864). Most common barriers to discuss cancer history and/or SCP were insufficient information from patients (83.8%), perceived inaccuracy from patients’ information (81.1%), unclear if patient has a SCP (81.1%), lack of SCP in medical record (75.7%), and trainees’ low medical knowledge about side effects of cancer therapies (70.3%). Conclusions: The awareness of cancer SCP among the IM trainees is limited, and many have not accessed or received training in SCPs. Efforts intended to facilitate SCP use and educate residents about cancer survivorship may be effective to increase the comfort level of trainees managing the growing number of survivors and improve transition from oncology to primary care clinics.[Table: see text]

Next-generation epidemiology: the role of high-resolution molecular phenotyping in diabetes research

Epidemiologists have for many decades reported on the patterns and distributions of diabetes within and between populations and have helped to elucidate the aetiology of the disease. This has helped raise awareness of the tremendous burden the disease places on individuals and societies; it has also identified key risk factors that have become the focus of diabetes prevention trials and helped shape public health recommendations. Recent developments in affordable high-throughput genetic and molecular phenotyping technologies have driven the emergence of a new type of epidemiology with a more mechanistic focus than ever before. Studies employing these technologies have identified gene variants or causal loci, and linked these to other omics data that help define the molecular processes mediating the effects of genetic variation in the expression of clinical phenotypes. The scale of these epidemiological studies is rapidly growing; a trend that is set to continue as the public and private sectors invest heavily in omics data generation. Many are banking on this massive volume of diverse molecular data for breakthroughs in drug discovery and predicting sensitivity to risk factors, response to therapies and susceptibility to diabetes complications, as well as the development of disease-monitoring tools and surrogate outcomes. To realise these possibilities, it is essential that omics technologies are applied to well-designed epidemiological studies and that the emerging data are carefully analysed and interpreted. One might view this as next-generation epidemiology, where complex high-dimensionality data analysis approaches will need to be blended with many of the core principles of epidemiological research. In this article, we review the literature on omics in diabetes epidemiology and discuss how this field is evolving. Graphical abstract.

An investigation of causal relationships between prediabetes and vascular complications

Prediabetes is a state of glycaemic dysregulation below the diagnostic threshold of type 2 diabetes (T2D). Globally, ~352 million people have prediabetes, of which 35-50% develop full-blown diabetes within five years. T2D and its complications are costly to treat, causing considerable morbidity and early mortality. Whether prediabetes is causally related to diabetes complications is unclear. Here we report a causal inference analysis investigating the effects of prediabetes in coronary artery disease, stroke and chronic kidney disease, complemented by a systematic review of relevant observational studies. Although the observational studies suggest that prediabetes is broadly associated with diabetes complications, the causal inference analysis revealed that prediabetes is only causally related with coronary artery disease, with no evidence of causal effects on other diabetes complications. In conclusion, prediabetes likely causes coronary artery disease and its prevention is likely to be most effective if initiated prior to the onset of diabetes.