Estimating Breakfast Characteristics Using Continuous Glucose Monitoring and Machine Learning in Adults With or at Risk of Type 2 Diabetes.

BACKGROUND: Continuous glucose monitoring (CGM) systems allow detailed assessment of postprandial glucose responses (PPGR), offering new insights into food choices' impact on dysglycemia. However, current approaches to analyze PPGR using a CGM require manual meal logging, limiting the scalability of CGM-driven applications like personalized nutrition and at-home diabetes risk assessment. OBJECTIVE: We propose a machine learning (ML) framework to automatically identify and characterize breakfast-related PPGRs from CGM profiles in adults at risk of or living with noninsulin-treated type 2 diabetes (T2D). METHODS: Our PPGR estimation framework uses a random forest ML algorithm trained on 15 adults without diabetes who wore a CGM for up to four weeks. The algorithm performance was evaluated on a held-out subset of the participants' CGM data as well as on an external validation data set of 36 individuals at risk for or with noninsulin-treated T2D. RESULTS: Our algorithm's estimations of breakfast PPGRs displayed no statistically significant differences to annotated PPGRs, in terms of incremental area under the curve and glucose rise (P > .05 for both data sets), while a small difference in prebreakfast glucose was found in the nondiabetes data set (P = .005) but not in the validation T2D data set (P = .18). CONCLUSIONS: We designed an ML framework to automatically estimate the timing of meal events from CGM data in individuals without diabetes and in individuals at risk or with T2D. This could provide a more scalable approach for analyzing postprandial glycemia, increasing the feasibility of CGM-based precision nutrition and diabetes risk assessment applications.

Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer.

Testing for DNA mismatch repair deficiency (MMRd) is recommended for all colorectal cancers (CRCs). Automating this would enable precision medicine, particularly if providing information on etiology not captured by deep learning (DL) methods. We present AIMMeR, an AI-based method for determination of mismatch repair (MMR) protein expression at a single-cell level in routine pathology samples. AIMMeR shows an area under the receiver-operator curve (AUROC) of 0.98, and specificity of ≥75% at 98% sensitivity against pathologist ground truth in stage II/III in two trial cohorts, with positive predictive value of ≥98% for the commonest pattern of somatic MMRd. Lower agreement with microsatellite instability (MSI) testing (AUROC 0.86) reflects discordance between MMR and MSI PCR rather than AIMMeR misclassification. Analysis of the SCOT trial confirms MMRd prognostic value in oxaliplatin-treated patients; while MMRd does not predict differential benefit of chemotherapy duration, it correlates with difference in relapse by regimen (PInteraction = 0.04). AIMMeR may help reduce pathologist workload and streamline diagnostics in CRC.

Prospective Intergenerational Associations between Parents' and Children's Illicit Substance Use During Adolescence.

OBJECTIVE: Intergenerational studies have identified relations between adolescents' and their future offspring's cannabis and alcohol use, but rarely have examined the association for other illicit drug use. Given the low prevalence of such use in community populations, we pooled data from three prospective intergenerational studies to test this link. METHOD: Participants were 1,060 children of 937 parents who had been repeatedly assessed since early adolescence. Children and parents reported on their use of cocaine, stimulants, hallucinogens, sedatives/tranquilizers, and opiates/narcotics from ages 10 to 18 years. Intergenerational similarities in any versus no use of these drugs were formally modeled using logistic regression. Patterns also were descriptively analyzed. RESULTS: Parent illicit substance use was associated with significantly higher odds of child use (adjusted odds ratio [95% confidence interval] = 2.682 [1.328-5.416], p = 0.006). However, intergenerational continuity was modest; 87% of children whose parent used illicit drugs in adolescence did not use such drugs, and 77% of parents of children who used illicit drugs had not themselves used these drugs during adolescence. CONCLUSIONS: The use of illicit substances by parents during their teenage years poses a risk for their offspring's similar behaviors. However, the discontinuity of these behaviors across generations implies children are largely resilient to or protected from this risk, and conversely that other aspects of parents' and children's experiences or characteristics may be more powerful risks for children's illicit drug use than this transgenerational influence.

(a) Parents' use of illicit drugs during adolescence significantly increased risk that their adolescent children would use such drugs. (b) However, most parents who used illicit drugs did not have children who used illicit drugs, and conversely, the majority of adolescents who used illicit drugs did not have parents who had used such drugs in their adolescence.

Behavioral Engagement and Activation Model Study (BEAMS): A latent class analysis of adopters and non-adopters of digital health technologies among people with Type 2 diabetes.

Many people with Type 2 diabetes (T2D) who could benefit from digital health technologies (DHTs) are either not using DHTs or do use them, but not for long enough to reach their behavioral or metabolic goals. We aimed to identify subgroups within DHT adopters and non-adopters and describe their unique profiles to better understand the type of tailored support needed to promote effective and sustained DHT use across a diverse T2D population. We conducted latent class analysis of a sample of adults with T2D who responded to an internet survey between December 2021 and March 2022. We describe the clinical and psychological characteristics of DHT adopters and non-adopters, and their attitudes toward DHTs. A total of 633 individuals were characterized as either DHT "Adopters" (n = 376 reporting any use of DHT) or "Non-Adopters" (n = 257 reporting never using any DHT). Within Adopters, three subgroups were identified: 21% (79/376) were "Self-managing Adopters," who reported high health activation and self-efficacy for diabetes management, 42% (158/376) were "Activated Adopters with dropout risk," and 37% (139/376) were "Non-Activated Adopters with dropout risk." The latter two subgroups reported barriers to using DHTs and lower rates of intended future use. Within Non-Adopters, two subgroups were identified: 31% (79/257) were "Activated Non-Adopters," and 69% (178/257) were "Non-Adopters with barriers," and were similarly distinguished by health activation and barriers to using DHTs. Beyond demographic characteristics, psychological, and clinical factors may help identify different subgroups of Adopters and Non-Adopters.

In this study, we characterized subgroups of adopters and non-adopters of digital health technologies (DHTs) for managing Type 2 diabetes, such as apps to track nutrition, continuous glucose monitors, and activity monitors like Fitbit. Self-efficacy for diabetes management, health activation, and perceived barriers to use DHT emerged as characteristics that distinguished subgroups. Notably, subgroups of adopters differed in their interest to use these technologies in the next 3 months; groups with low levels of self-efficacy and health activation were least interested in using them and thus at risk of discontinuing use. The ability to identify these subgroups can inform strategies tailored to each subgroup that motivate adoption of DHTs and promote long-term engagement.

Digital Interventions for Self-Management of Type 2 Diabetes Mellitus: Systematic Literature Review and Meta-Analysis.

BACKGROUND: The proliferation of digital technology has the potential to transform diabetes management. One of the critical aspects of modern diabetes management remains the achievement of glycemic targets to avoid acute and long-term complications. OBJECTIVE: This study aims to describe the landscape of evidence pertaining to the relative effectiveness or efficacy and safety of various digital interventions for the self-management of type 2 diabetes mellitus (T2DM), with a primary focus on reducing glycated hemoglobin A1c (HbA1c) levels. METHODS: A systematic literature review (SLR) was conducted by searching Embase, MEDLINE, and CENTRAL on April 5, 2022. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. Eligibility criteria for the SLR included randomized controlled trials (RCTs) and comparative observational studies evaluating interventions containing both human (eg, coaching) and digital components (eg, glucose meter) in adult patients with T2DM. The primary meta-analysis was restricted to studies that reported laboratory-measured HbA1c. In secondary analyses, meta-regression was performed with the intensity of coaching in the digital intervention as a categorical covariate. RESULTS: In total, 28 studies were included in this analysis. Most studies (23/28, 82%) used the reduction of HbA1c levels as the primary end point, either directly or as a part of a multicomponent outcome. In total, 21 studies reported statistically significant results with this primary end point. When stratified into 3 intervention categories by the intensity of the intervention supporting the digital health technology (analyzing all 28 studies), the success rate appeared to be proportional to the coaching intensity (ie, higher-intensity studies reported higher success rates). When the analysis was restricted to RCTs using the comparative improvement of HbA1c levels, the effectiveness of the interventions was less clear. Only half (12/23, 52%) of the included RCTs reported statistically significant results. The meta-analyses were broadly aligned with the results of the SLR. The primary analysis estimated a greater reduction in HbA1c associated with digital interventions compared with usual care (-0.31%, 95% CI -0.45% to -0.16%; P<.001). Meta-regression estimated reductions of -0.45% (95% CI -0.81% to -0.09%; P=.02), -0.29% (95% CI -0.48% to -0.11%; P=.003), and -0.28% (95% CI -0.65% to 0.09%; P=.20) associated with high-, medium-, and low-intensity interventions, respectively. CONCLUSIONS: These findings suggest that reducing HbA1c levels in individuals with T2DM with the help of digital interventions is feasible, effective, and acceptable. One common feature of effective digital health interventions was the availability of timely and responsive personalized coaching by a dedicated health care professional.

Unification of Efforts to Improve Global Access to Cancer Therapeutics: Report From the 2022/2023 Access to Essential Cancer Medicines Stakeholder Summit.

PURPOSE: There is an urgent need to improve access to cancer therapy globally. Several independent initiatives have been undertaken to improve access to cancer medicines, and additional new initiatives are in development. Improved sharing of experiences and increased collaboration are needed to achieve substantial improvements in global access to essential oncology medicines. METHODS: The inaugural Access to Essential Cancer Medicines Stakeholder Meeting was organized by ASCO and convened at the June 2022 ASCO Annual Meeting in Chicago, IL, with two subsequent meetings, Union for International Cancer Control World Cancer Congress held in Geneva, Switzerland, in October 2022 and at the ASCO Annual Meeting in June of 2023. Invited stakeholders included representatives from cancer institutes, physicians, researchers, professional societies, the pharmaceutical industry, patient advocacy organizations, funders, cancer organizations and foundations, policy makers, and regulatory bodies. The session was moderated by ASCO. Past efforts and current and upcoming initiatives were initially discussed (2022), updates on progress were provided (2023), and broad agreement on resulting action steps was achieved with participants. RESULTS: Summit participants recognized that while much work was ongoing to enhance access to cancer therapeutics globally, communication and synergy across projects and organizations could be enhanced by providing a platform for collaboration and shared expertise. CONCLUSION: The summit resulted in new cross-stakeholder insights and planned collaboration addressing barriers to accessing cancer medications. Specific actions and timelines for implementation and reporting were established.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Risks of peri- and postoperative complications with glucagon-like peptide-1 receptor agonists.

AIM: To assess whether adults with diabetes on oral hypoglycaemic agents undergoing general endotracheal anaesthesia during nine common surgical procedures who are glucagon-like peptide-1 receptor agonist (GLP1-RA) users, compared with non-users, are at increased risk of six peri- and post-procedure complications. MATERIALS AND METHODS: A retrospective observational cohort analysis of over 130 million deidentified US adults with diabetes (defined as being on oral hypoglycaemic agents) from a nationally representative electronic health dataset between 1 January 2015 and 1 April 2023 was analysed. Cohorts were matched by high-dimensionality propensity scoring. We compared the odds of six peri- and postoperative complications in GLP1-RA users and non-users. A sensitivity analysis compared these odds in GLP1-RA users to non-users with diabetes and obesity. We measured the odds of (a) a composite outcome of postoperative decelerated gastric emptying, including antiemetic use, ileus within 7 days post-procedure, gastroparesis diagnosis, gastric emptying study; (b) postoperative aspiration or pneumonitis; (c) severe respiratory failure; (d) postoperative hypoglycaemia; (e) inpatient mortality; and (f) 30-day mortality. RESULTS: Among 13 361 adults with diabetes, 16.5% were treated with a GLP1-RA. In the high-dimensionality propensity score-matched cohort, GLP1-RA users had a lower risk of peri- and postoperative complications for decelerated gastric emptying and antiemetic use compared with non-users. The risk of ileus within 7 days, aspiration/pneumonitis, hypoglycaemia and 30-day mortality were not different. A sensitivity analysis showed similar findings in patients with diabetes and obesity. CONCLUSION: No increased risk of peri- and postoperative complications in GLP1-RA users undergoing surgery with general endotracheal anaesthesia was identified.

Chondrocyte Invasion May Be a Mechanism for Persistent Staphylococcus Aureus Infection In Vitro.

BACKGROUND: Recurrent bone and joint infection with Staphylococcus aureus is common. S. aureus can invade and persist in osteoblasts and fibroblasts, but little is known about this mechanism in chondrocytes. If S. aureus were able to invade and persist within chondrocytes, this could be a difficult compartment to treat. QUESTION/PURPOSE: Can S. aureus infiltrate and persist intracellularly within chondrocytes in vitro? METHODS: Cell lines were cultured in vitro and infected with S. aureus. Human chondrocytes (C20A4) were compared with positive controls of human osteoblasts (MG63) and mouse fibroblasts (NIH3T3), which have previously demonstrated S. aureus invasion and persistence (human fibroblasts were not available to us). Six replicates per cell type were followed for 6 days after infection. Cells were treated daily with antibiotic media for extracellular killing. To determine whether S. aureus can infiltrate chondrocytes, fluorescence microscopy was performed to qualitatively assess the presence of intracellular bacteria, and intracellular colony-forming units (CFU) were enumerated 2 hours after infection. To determine whether S. aureus can persist within chondrocytes, intracellular CFUs were enumerated from infected host cells each day postinfection. RESULTS: S. aureus invaded human chondrocytes (C20A4) at a level (2.8 x 10 5 ± 5.5 x 10 4 CFUs/mL) greater than positive controls of human osteoblasts (MG63) (9.5 x 10 2 ± 2.5 x 10 2 CFUs/mL; p = 0.01) and mouse fibroblasts (NIH3T3) (9.1 x 10 4 ± 2.5 x 10 4 CFUs/mL; p = 0.02). S. aureus also persisted within human chondrocytes (C20A4) for 6 days at a level (1.4 x 10 3 ± 5.3 x 10 2 CFUs/mL) greater than that of human osteoblasts (MG63) (4.3 x 10 2 ± 3.5 x 10 1 CFUs/mL; p = 0.02) and mouse fibroblasts (NIH3T3) (0 CFUs/mL; p < 0.01). S. aureus was undetectable within mouse fibroblasts (NIH3T3) after 4 days. There were 0 CFUs yielded from cell media, confirming extracellular antibiotic treatment was effective. CONCLUSION: S. aureus readily invaded human chondrocytes (C20A4) in vitro and persisted viably for 6 days after infection, evading extracellular antibiotics. Chondrocytes demonstrated a greater level of intracellular invasion and persistence by S. aureus than positive control human osteoblast (MG63) and mouse fibroblast (NIH3T3) cell lines. CLINICAL RELEVANCE: Chondrocyte invasion and persistence may contribute to recurrent bone and joint infections. Additional research should assess longer periods of persistence and whether this mechanism is present in vivo.

Is Risk-Stratifying Patients with Colorectal Cancer Using a Deep Learning-Based Prognostic Biomarker Cost-Effective?

OBJECTIVES: Accurate risk stratification of patients with stage II and III colorectal cancer (CRC) prior to treatment selection enables limited health resources to be efficiently allocated to patients who are likely to benefit from adjuvant chemotherapy. We aimed to investigate the cost-effectiveness of a recently developed deep learning-based prognostic method, Histotyping, from the perspective of the Norwegian healthcare system. METHODS: Two partitioned survival models were developed to assess the cost-effectiveness of Histotyping for two treatment cohorts: patients with CRC stage II and III. For each of the two cohorts, Histotyping was used for risk stratification to assign adjuvant chemotherapy and was compared with the standard of care (SOC) (adjuvant chemotherapy to all patients). Health outcomes measured in the model were quality-adjusted life years (QALYs) and life years (LYs) gained. Deterministic and probabilistic sensitivity analyses were performed to determine the impact of uncertainty. Scenario analyses were performed to assess the impact of the parameters with the greatest uncertainty. RESULTS: Risk-stratifying patients with CRC stage II and III using Histotyping was dominant (less costly and more effective) compared to SOC. In patients with CRC stage II, the net monetary benefit of Histotyping was 270,934 Norwegian kroners (NOK) (year of valuation is 2021), and the net health benefit of Histotyping was 0.99. In stage III, the net monetary benefit of Histotyping was 195,419 NOK, and the net health benefit of Histotyping was 0.71. CONCLUSIONS:  Risk-stratifying patients with CRC using Histotyping prior to the administration of adjuvant chemotherapy is likely to be a cost-effective strategy in Norway.

Diabetes Technology Meeting 2023.

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Latent profile analysis of college students' alcohol and cannabis co-use patterns after recreational cannabis legalization.

OBJECTIVE: Evidence is mixed on how young adults' cannabis and alcohol use and co-use patterns have changed following recreational cannabis legalization (RCL). Incorporating measures of frequency and intensity of use we examined changes in college students' use and co-use patterns following RCL. METHOD: Four-year college students (n = 845,589) ages 18-24 years participated in the National College Health Assessment between 2008 and 2018, including students from 7 states that enacted RCL and 42 that did not. Latent profile analyses identified six patterns of use from four indicator variables tapping frequency of cannabis use and frequency and intensity of alcohol use: Abstainers, Light Alcohol Only, Heavy Alcohol Only, Predominantly Heavy Cannabis Use, Moderate Co-use, and Heavy Co-use. RESULTS: Regression models that adjusted for time and person- and institution-level covariates indicated that students' exposure to RCL was associated with lower odds of being in the two alcohol-only use classes, higher odds of being in the Predominantly Heavy Cannabis Use, Heavy Co-Use and Abstainers classes, and was not significantly related to Moderate Co-Use class membership. CONCLUSIONS: RCL was positively associated with patterns of frequent cannabis use and frequent and intense co-use but also with abstinence. Use of alcohol-only became less prevalent after RCL. Research on how RCL influences the prevalence of problematic patterns of substance use will inform and improve prevention efforts.

Advanced Glycation Endproducts: A Marker of Long-term Exposure to Glycemia.

This article examines the importance of advanced glycation endproducts (AGEs) and summarizes the structure of AGEs, pathological changes associated with AGEs, the contribution of AGEs to metabolic memory, and the value of AGEs as a predictor of diabetic complications and cardiovascular disease in people with and without diabetes. As a practical focus, skin autofluorescence (SAF) is examined as an attractive approach for estimating AGE burden. The measurement of AGEs may be of significant value to specific individuals and groups, including Black and Hispanic/Latino Americans, as they appear to have higher concentrations of hemoglobin A1c (HbA1c) than would be predicted by other metrics of mean glycemia. We hypothesize that if the amount of glycation of HbA1c is greater than expected from measured glucose levels, and if AGEs are accumulating, then this accumulation of AGEs might account for the increased rate of complications of diabetes in populations with high rates of vascular disease and other complications. Thus, identifying and modifying the burden of AGEs based on measurement of AGEs by SAF may turn out to be a worthwhile metric to determine individuals who are at high risk for the complications of diabetes as well as others without diabetes at risk of vascular disease. We conclude that available evidence supports SAF as both a clinical measurement and as a means of evaluating interventions aimed at reducing the risks of vascular disease and diabetic complications.

A probabilistic computation framework to estimate the dawn phenomenon in type 2 diabetes using continuous glucose monitoring.

In type 2 diabetes (T2D), the dawn phenomenon is an overnight glucose rise recognized to contribute to overall glycemia and is a potential target for therapeutic intervention. Existing CGM-based approaches do not account for sensor error, which can mask the true extent of the dawn phenomenon. To address this challenge, we developed a probabilistic framework that incorporates sensor error to assign a probability to the occurrence of dawn phenomenon. In contrast, the current approaches label glucose fluctuations as dawn phenomena as a binary yes/no. We compared the proposed probabilistic model with a standard binary model on CGM data from 173 participants (71% female, 87% Hispanic/Latino, 54 ± 12 years, with either a diagnosis of T2D for six months or with an elevated risk of T2D) stratified by HbA1c levels into normal but at risk for T2D, with pre-T2D, or with non-insulin-treated T2D. The probabilistic model revealed a higher dawn phenomenon frequency in T2D [49% (95% CI 37-63%)] compared to pre-T2D [36% (95% CI 31-48%), p = 0.01] and at-risk participants [34% (95% CI 27-39%), p < 0.0001]. While these trends were also found using the binary approach, the probabilistic model identified significantly greater dawn phenomenon frequency than the traditional binary model across all three HbA1c sub-groups (p < 0.0001), indicating its potential to detect the dawn phenomenon earlier across diabetes risk categories.

Youth Exposure to Recreational Cannabis Legalization: Moderation of Effects by Sex and Parental Cannabis Use during Adolescence.

OBJECTIVE: Few studies of recreational cannabis legalization (RCL) have assessed adolescents both before and after RCL or considered moderators of RCL effects. The present study tested whether RCL was more strongly associated with cannabis use for girls and among youth whose parents had a history of cannabis use during adolescence. METHOD: Data were pooled from 940 adolescents from three intergenerational studies that began in Washington (where RCL was enacted in 2012), Oregon (RCL year = 2015), and New York (RCL year = 2021). Youth were assessed repeatedly from ages 13 to 18 years (k = 3,650 person-years) from 1999 to 2020 (prior to RCL in New York). Parent cannabis use at or before age 18 years (yes/no) was assessed prospectively during the parent's adolescence. Multilevel models focused on the between-subjects effects of years of youth exposure to RCL on adolescents' mean cannabis use likelihood, and interactions with child sex and parent use history. RESULTS: Child exposure to RCL was associated with a higher likelihood of cannabis use if their parents had a history of adolescent use, (Estimate [SE] = 0.67 [0.25], p = 0.008), versus no such history (Estimate [SE] = -0.05 [0.28], p = 0.855). RCL effects were not moderated by child sex. CONCLUSIONS: The effects of RCL on adolescents' cannabis use may depend on their parents' history of using the drug. Identifying other moderators of RCL effects, and understanding the mechanisms of these risks and the ways that parents and communities can offset them, are prevention priorities.

(1) Adolescents' use of cannabis may have intergenerational consequences, making it more likely their future offspring will use cannabis. (2) Whether or not recreational cannabis legalization influences adolescents' cannabis use may depend on their parents' cannabis use history. (3) Parenting in a state with liberalized cannabis policies may present new challenges and require that novel prevention resources be developed.

Multiplex analysis of intratumoural immune infiltrate and prognosis in patients with stage II-III colorectal cancer from the SCOT and QUASAR 2 trials: a retrospective analysis.

BACKGROUND: Tumour-infiltrating CD8+ cytotoxic T cells confer favourable prognosis in colorectal cancer. The added prognostic value of other infiltrating immune cells is unclear and so we sought to investigate their prognostic value in two large clinical trial cohorts. METHODS: We used multiplex immunofluorescent staining of tissue microarrays to assess the densities of CD8+, CD20+, FoxP3+, and CD68+ cells in the intraepithelial and intrastromal compartments from tumour samples of patients with stage II-III colorectal cancer from the SCOT trial (ISRCTN59757862), which examined 3 months versus 6 months of adjuvant oxaliplatin-based chemotherapy, and from the QUASAR 2 trial (ISRCTN45133151), which compared adjuvant capecitabine with or without bevacizumab. Both trials included patients aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-1. Immune marker predictors were analysed by multiple regression, and the prognostic and predictive values of markers for colorectal cancer recurrence-free interval by Cox regression were assessed using the SCOT cohort for discovery and QUASAR 2 cohort for validation. FINDINGS: After exclusion of cases without tissue microarrays and with technical failures, and following quality control, we included 2340 cases from the SCOT trial and 1069 from the QUASAR 2 trial in our analysis. Univariable analysis of associations with recurrence-free interval in cases from the SCOT trial showed a strong prognostic value of intraepithelial CD8 (CD8IE) as a continuous variable (hazard ratio [HR] for 75th vs 25th percentile [75vs25] 0·73 [95% CI 0·68-0·79], p=2·5 × 10-16), and of intrastromal FoxP3 (FoxP3IS; 0·71 [0·64-0·78], p=1·5 × 10-13) but not as strongly in the epithelium (FoxP3IE; 0·89 [0·84-0·96], p=1·5 × 10-4). Associations of other markers with recurrence-free interval were moderate. CD8IE and FoxP3IS retained independent prognostic value in bivariable and multivariable analysis, and, compared with either marker alone, a composite marker including both markers (CD8IE-FoxP3IS) was superior when assessed as a continuous variable (adjusted [a]HR75 vs 25 0·70 [95% CI 0·63-0·78], p=5·1 × 10-11) and when categorised into low, intermediate, and high density groups using previously published cutpoints (aHR for intermediate vs high 1·68 [95% CI 1·29-2·20], p=1·3 × 10-4; low vs high 2·58 [1·91-3·49], p=7·9 × 10-10), with performance similar to the gold-standard Immunoscore. The prognostic value of CD8IE-FoxP3IS was confirmed in cases from the QUASAR 2 trial, both as a continuous variable (aHR75 vs 25 0·84 [95% CI 0·73-0·96], p=0·012) and as a categorical variable for low versus high density (aHR 1·80 [95% CI 1·17-2·75], p=0·0071) but not for intermediate versus high (1·30 [0·89-1·88], p=0·17). INTERPRETATION: Combined evaluation of CD8IE and FoxP3IS could help to refine risk stratification in colorectal cancer. Investigation of FoxP3IS cells as an immunotherapy target in colorectal cancer might be merited. FUNDING: Medical Research Council, National Institute for Health Research, Cancer Research UK, Swedish Cancer Society, Roche, and Promedica Foundation.

Evaluating Patient and Provider Preferences for a Once-Weekly Basal Insulin in Adults with Type 2 Diabetes.

Purpose: The global burden of disease of type 2 diabetes (T2D) is significant, and insulin currently plays a central role in T2D management. This study sought to assess the preferences of patients with T2D and healthcare providers (HCPs) involved in T2D care regarding a hypothetical once-weekly basal insulin in comparison to current basal insulin options. Patients and Methods: In a survey-based study in the United States that included a discrete choice experiment (DCE), patients with T2D (insulin naïve and current insulin users) and providers who treat individuals with T2D were asked to evaluate current basal insulins and identify attributes of importance regarding a hypothetical once-weekly basal insulin. A regression analysis was conducted to identify drivers of preference by relevant demographics, attitudes, and behaviors. Results: Most respondents (91% of patients with T2D and 89% of HCPs in the base case scenario) would choose a once-weekly basal insulin product over another type of basal insulin. Both patients with T2D and HCPs rated insulin type and delivery method to be attributes of highest importance in the discrete choice exercise. Current basal insulin users ("insulin experienced") reported higher levels of confidence that a once-weekly insulin would help them to achieve their desired blood sugar levels compared to their current basal insulin (5.7 vs 5.2 on a 7-point Likert scale). Most insulin-experienced respondents (88%) were likely to inquire about once-weekly basal insulin, and most HCPs (85%) indicated willingness to educate patients on management of their T2D using a once-weekly basal insulin. Conclusion: Discussing preferences for T2D medication management is important for patients and HCPs to ensure treatments are offered for patients based on their preferences. This study showed that patient and provider preferences are similar towards a once-weekly basal insulin over current basal insulin preparations.

Prioritizing Patient Experiences in the Management of Diabetes and Its Complications: An Endocrine Society Position Statement.

Diabetes can be an arduous journey both for people with diabetes (PWD) and their caregivers. While the journey of every person with diabetes is unique, common themes emerge in managing this disease. To date, the experiences of PWD have not been fully considered to successfully implement the recommended standards of diabetes care in practice. It is critical for health-care providers (HCPs) to recognize perspectives of PWD to achieve optimal health outcomes. Further, existing tools are available to facilitate patient-centered care but are often underused. This statement summarizes findings from multistakeholder expert roundtable discussions hosted by the Endocrine Society that aimed to identify existing gaps in the management of diabetes and its complications and to identify tools needed to empower HCPs and PWD to address their many challenges. The roundtables included delegates from professional societies, governmental organizations, patient advocacy organizations, and social enterprises committed to making life better for PWD. Each section begins with a clinical scenario that serves as a framework to achieve desired health outcomes and includes a discussion of resources for HCPs to deliver patient-centered care in clinical practice. As diabetes management evolves, achieving this goal will also require the development of new tools to help guide HCPs in supporting PWD, as well as concrete strategies for the efficient uptake of these tools in clinical practice to minimize provider burden. Importantly, coordination among various stakeholders including PWD, HCPs, caregivers, policymakers, and payers is critical at all stages of the patient journey.

Multimodal digital phenotyping of diet, physical activity, and glycemia in Hispanic/Latino adults with or at risk of type 2 diabetes.

Digital phenotyping refers to characterizing human bio-behavior through wearables, personal devices, and digital health technologies. Digital phenotyping in populations facing a disproportionate burden of type 2 diabetes (T2D) and health disparities continues to lag compared to other populations. Here, we report our study demonstrating the application of multimodal digital phenotyping, i.e., the simultaneous use of CGM, physical activity monitors, and meal tracking in Hispanic/Latino individuals with or at risk of T2D. For 14 days, 36 Hispanic/Latino adults (28 female, 14 with non-insulin treated T2D) wore a continuous glucose monitor (CGM) and a physical activity monitor (Actigraph) while simultaneously logging meals using the MyFitnessPal app. We model meal events and daily digital biomarkers representing diet, physical activity choices, and corresponding glycemic response. We develop a digital biomarker for meal events that differentiates meal events into normal and elevated categories. We examine the contribution of daily digital biomarkers of elevated meal event count and step count on daily time-in-range 54-140 mg/dL (TIR54-140) and average glucose. After adjusting for step count, a change in elevated meal event count from zero to two decreases TIR54-140 by 4.0% (p = 0.003). An increase in 1000 steps in post-meal step count also reduces the meal event glucose response by 641 min mg/dL (p = 0.0006) and reduces the odds of an elevated meal event by 55% (p < 0.0001). The proposed meal event digital biomarkers may provide an opportunity for non-pharmacologic interventions for Hispanic/Latino adults facing a disproportionate burden of T2D.

Technology and health inequities in diabetes care: How do we widen access to underserved populations and utilize technology to improve outcomes for all?

Digital health technologies are being utilized increasingly in the modern management of diabetes. These include tools such as continuous glucose monitoring systems, connected blood glucose monitoring devices, hybrid closed-loop systems, smart insulin pens, telehealth, and smartphone applications (apps). Although many of these technologies have a solid evidence base, from the perspective of a person living with diabetes, there remain multiple barriers preventing their optimal use, creating a digital divide. In this article, we describe many of the origins of these barriers and offer recommendations on widening access to digital health technologies for underserved populations living with diabetes to improve their health outcomes.