IMPORTANCE Emerging evidence suggests that postprandial glycemic responses (PPGRs) to food may be influenced by and predicted according to characteristics unique to each individual, including anthropometric and microbiome variables. Interindividual diversity in PPGRs to food requires a personalized approach for the maintenance of healthy glycemic levels. OBJECTIVES To describe and predict the glycemic responses of individuals to a diverse array of foods using a model that considers the physiology and microbiome of the individual in addition to the characteristics of the foods consumed. DESIGN, SETTING, AND PARTICIPANTS This cohort study using a personalized predictive model enrolled 327 individuals without diabetes from October 11, 2016, to December 13, 2017, in Minnesota and Florida to be part of a study lasting 6 days. The study measured anthropometric variables, described the gut microbial composition, and assessed blood glucose levels every 5 minutes using a continuous glucose monitor. Participants logged their food and activity information for the duration of the study. A predictive model of individualized PPGRs to a diverse array of foods was trained and applied. MAIN OUTCOMES AND MEASURES Glycemic responses to food consumed over 6 days for each participant. The predictive model of personalized PPGRs considered individual features, including the microbiome, in addition to the features of the foods consumed. RESULTS Postprandial response to the same foods varied across 327 individuals (mean [SD] age, 45 [12] years; 78.0% female). A model predicting each individual's responses to food that considers several individual factors in addition to food features had better overall performance (R = 0.62) than current standard-of-care approaches using nutritional content alone (R = 0.34 for calories and R = 0.40 for carbohydrates) to control postprandial glycemic levels. CONCLUSIONS AND RELEVANCE Across the cohort of adults without diabetes who were examined, a personalized predictive model that considers unique features of the individual, such as clinical characteristics, physiological variables, and the microbiome, in addition to nutrient content was more predictive than current dietary approaches that focus only on the calorie or carbohydrate content of foods. Providing individuals with tools to manage their glycemic responses to food based on personalized predictions of their PPGRs may allow them to maintain their blood glucose levels within limits associated with good health.

We noticed an increased number of patients diagnosed with colorectal cancer (CRC) in their 20s, 30s, and 40s. We analyzed all CRC patients aged < 50 at our institutions from 1972 to 2017 and found increasing trends as well as a propensity for more distal location-findings that are hypothesis generating, given the embryologic origin of these tumors. This finding may have implications for screening guidelines. Background: Recent trends have identified increasing number of young individuals with rectal and colon cancers. These individuals, who are younger than 50 years old, in most instances would not meet screening guidelines. We aimed to report the characteristics and trend of the rising proportion of young individuals being diagnosed with rectal and colon cancers at our institutions. Patients and Methods: This study included 3381 rectal and colon cancer patients from the Mayo Clinic cancer registry from 1972 to 2017 who were diagnosed with rectal or colon cancer and who were < 50 years old. Patient and cancer characteristics are described. The Cochran-Armitage trend test was used to see if the change in percentage diagnosed at age < 50 years had a significant trend over the years. A linear regression model was fit to estimate the percentage change per year when the trend was approximately linear. Results: The percentage of patients diagnosed with rectal or colon cancer in different age categories over the years showed a rising trend for individuals aged < 50. Most of these tumors were distal (rectum, left-sided colon, and rightsided colon were 49.8%, 28.8%, and 21.4%, respectively). This was more so for patients < 50 diagnosed with rectal cancer, which showed a linear increase at a rate of 0.26% per year (P < .001). Conclusion: Our study affirms the rising proportion of colorectal cancers found in young individuals, with a linear ongoing rise of rectal cancers in particular. This may have implications for the current screening recommendations for colorectal cancers, which are already being revised.

Outcomes have improved considerably in multiple myeloma (MM), but disparities among racial‐ethnic groups exist. Differences in utilization of novel therapeutics are likely contributing factors. We explored such differences from the SEER‐Medicare database. A utilization analysis of lenalidomide, thalidomide, bortezomib, and stem cell transplant (SCT) was performed for patients diagnosed with MM between 2007 and 2009, including use over time, use by race, time‐dependent trends for each racial subgroup, and survival analysis. A total of 5338 MM patients were included with median 2.4‐year follow‐up. Within the first year of MM diagnosis, utilization of lenalidomide, bortezomib, SCT, and more than one novel agent increased over time while utilization of thalidomide decreased. There was significantly lower utilization of lenalidomide among African‐Americans (P < 0.01), higher thalidomide use among Hispanics and Asians (P < 0.01), and lower bortezomib use among Asians (P < 0.01). Hispanics had the highest median number of days to first dose of bortezomib (P = 0.02) and the lowest utilization of SCT (P < 0.01). Hispanics and Asians were the only groups without notable increases in lenalidomide and bortezomib use, respectively. SCT utilization increased over time for all except African‐Americans. SCT use within the first year after diagnosis was associated with better overall survival (HR 0.52; 95% CI: 0.4–0.68), while bortezomib use was associated with inferior survival (HR 1.14; 95% CI 1.02–1.28). We noted considerable variability in MM therapeutics utilization with seeming inequity for racial‐ethnic minorities. These trends should be considered to eliminate drug access and utilization disparities and achieve equitable benefit of therapeutic advances across all races.

Background: The association between body mass index (BMI) and colorectal cancer is unique. There are several patient- and tumor-related factors that affect this and associations are not entirely clear. The primary aim of this study is to examine the association between BMI and survival after colorectal cancer diagnosis.Methods: Among 26,908 Mayo Clinic patients diagnosed with colorectal cancer between 1972 and 2017, 3,799 patients had information on BMI within 6 months prior to cancer diagnosis. Multivariable Cox regression models were used to assess the differences in overall survival between BMI groups in each cancer stage, controlling for age, gender, year of diagnosis, and cancer location. The impact of change of BMI at 30, 60, and 90 days on survival afterwards were also analyzed.Results: Among 3,799 patients included in the study, there were 29% normal weight, 2% underweight, 36% overweight, and 33% obese patients. With all stages combined together, the overall 5-years survival rates for underweight, normal weight, overweight, and obese patients were 33, 56, 60, and 65%, respectively (p < 0.001). The results show that, the difference in overall survival was not statistically significant when underweight, overweight, and obese patients were compared to normal weight patients in stage 1 and stage 2, although there was a trend that overweight patients had better survival than normal weight group in stage 2 cancer patients (HR = 0.8, p = 0.086). In stage 3 and 4 patients combined, underweight group demonstrated a significant disadvantage (HR = 1.96, p = 0.007) for overall survival compared to the normal weight group. Additionally, post-diagnosis BMI drop more than 10% from either a previous time (HR = 1.88, p = 0.002) or pre-diagnosis time (HR = 1.61, p < 0.001) was associated with worse overall survival after adjusting for baseline variables.Conclusions: BMI is an important consideration in patients with colorectal cancer. Outcomes are stage-dependent where in some situations obesity maybe an advantage. More importantly, being underweight is a significant negative predictor of outcome. The impact of drop in BMI or weight, on survival of CRC patients, needs to be studied further since this is potentially an actionable variable and a dynamic biomarker that may help improve outcome in these patients.