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Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article’s cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH’s GSS principles.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has rapidly involved the entire world and exposed the pressing need for collaboration between public health and other stakeholders from the clinical, scientific, regulatory, pharmaceutical, and medical device and technology communities. To discuss how to best protect people with diabetes from serious outcomes from COVID-19, Diabetes Technology Society, in collaboration with Sansum Diabetes Research Institute, hosted the “International COVID-19 and Diabetes Virtual Summit” on August 26-27, 2020. This unique, unprecedented real-time conference brought together physicians, scientists, government officials, regulatory experts, industry representatives, and people with diabetes from six continents to review and analyze relationships between COVID-19 and diabetes. Over 800 attendees logged in. The summit consisted of five sessions: (I) Keynotes, (II) Preparedness, (III) Response, (IV) Recovery, and (V) Surveillance; eight parts: (A) Background, (B) Resilience, (C) Outpatient Care, (D) Inpatient Care, (E) Resources, (F) High-Risk Groups, (G) Regulation, and (H) The Future; and 24 sections: (1) Historic Pandemics and Impact on Society, (2) Pathophysiology/Risk Factors for COVID-19, (3) Social Determinants of COVID-19, (4) Preparing for the Future, (5) Medications and Vaccines, (6) Psychology of Patients and Caregivers, (7) Outpatient Treatment of Diabetes Mellitus and Non-Pharmacologic Intervention, (8) Technology and Telehealth for Diabetes Outpatients, (9) Technology for Inpatients, (10) Management of Diabetes Inpatients with COVID-19, (11) Ethics, (12) Accuracy of Diagnostic Tests, (13) Children, (14) Pregnancy, (15) Economics of Care for COVID-19, (16) Role of Industry, (17) Protection of Healthcare Workers, (18) People with Diabetes, (19) International Responses to COVID-19, (20) Government Policy, (21) Regulation of Tests and Treatments, (22) Digital Health Technology, (23) Big Data Statistics, and 24) Patient Surveillance and Privacy. The two keynote speeches were entitled (1) COVID-19 and Diabetes—Meeting the Challenge and (2) Knowledge Gaps and Research Opportunities for Diabetes and COVID-19. While there was an emphasis on diabetes and its interactions with COVID-19, the panelists also discussed the COVID-19 pandemic in general. The meeting generated many novel ideas for collaboration between experts in medicine, science, government, and industry to develop new technologies and disease treatment paradigms to fight this global pandemic.

The prevalence of Lynch syndrome (LS) varies significantly in different populations, suggesting that ethnic features might play an important role. We enrolled 3330 consecutive Chinese patients who had surgical resection for newly diagnosed colorectal cancer. Universal screening for LS was implemented, including immunohistochemistry for mismatch repair (MMR) proteins, BRAFV600E mutation test and germline sequencing. Among the 3250 eligible patients, MMR protein deficiency (dMMR) was detected in 330 (10.2%) patients. Ninety‐three patients (2.9%) were diagnosed with LS. Nine (9.7%) patients with LS fulfilled Amsterdam criteria II and 76 (81.7%) met the revised Bethesda guidelines. Only 15 (9.7%) patients with absence of MLH1 on IHC had BRAFV600E mutation. One third (33/99) of the MMR gene mutations have not been reported previously. The age of onset indicates risk of LS in patients with dMMR tumors. For patients older than 65 years, only 2 patients (5.7%) fulfilling revised Bethesda guidelines were diagnosed with LS. Selective sequencing of all cases with dMMR diagnosed at or below age 65 years and only of those dMMR cases older than 65 years who fulfill revised Bethesda guidelines results in 8.2% fewer cases requiring germline testing without missing any LS diagnoses. While the prevalence of LS in Chinese patients is similar to that of Western populations, the spectrum of constitutional mutations and frequency of BRAFV600E mutation is different. Patients older than 65 years who do not meet the revised Bethesda guidelines have a low risk of LS, suggesting germline sequencing might not be necessary in this population.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low‐density lipoprotein (LDL), and high‐density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP‐CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20–1.79, p = 1.68 × 10−4). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92–1.18, p = 0.49), 0.94 (95% CI: 0.84–1.05, p = 0.27), and 0.98 (95% CI: 0.85–1.12, p = 0.75) respectively. A genetic risk score for 3‐hydoxy‐3‐methylglutaryl‐coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR = 0.69, 95% CI: 0.49–0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.

Purpose Factors associated with early mortality after surgery and treatment with adjuvant chemotherapy in colon cancer are poorly understood. We aimed to characterize the determinants of early mortality in a large cohort of colon cancer trial participants. Methods A pooled analysis of 37,568 patients in 25 randomized trials of adjuvant systemic therapy was conducted. Multivariable logistic regression models with several definitions of early mortality (30, 60, and 90 days, and 6 months) were constructed, adjusting for clinically and statistically significant variables. A nomogram for 6-month mortality was developed and validated. Results Median age among patients was 61 years, patient demographics included 54% men and 90% White, 29% and 71% had stage II and III disease, respectively, and 79%, 20%, and 1% had an Eastern Cooperative Oncology Group performance status (PS) of 0, 1, and ≥ 2, respectively. Early mortality was low: 0.3% at 30 days, 0.6% at 60 days, 0.8% at 90 days, and 1.4% at 6 months. Of those patients who died by 6 months post–random assignment, 40% had documented disease recurrence prior to death. Early disease recurrence was associated with a markedly increased risk of death during the first 6 months post-treatment (hazard ratio, 82.6; 95%CI, 66.9 to 102.1). In prognostic analyses, advanced age, male sex, poorer PS, increasing ratio of positive to examined lymph nodes, earlier decade of enrollment, and higher tumor stage and grade predicted a greater likelihood of early mortality, whereas treatment received was not strongly predictive. A multivariable model for 6-month mortality showed strong optimism-adjusted discrimination (concordance index, 0.73) and calibration. Conclusion Early mortality was infrequent but more prevalent in patients with advanced age and a PS of ≥ 2, underscoring the need to carefully consider the risk-to-benefit ratio when making treatment decisions in these subgroups.

Purpose The traditional end point for colon adjuvant clinical trials is overall survival (OS). We previously validated disease-free survival (DFS) after 3-year follow-up as an excellent predictor of 5-year OS results. Here we explore shorter term DFS and OS end points, as well as stage dependency. Methods Individual patient data from 18 phase III trials including 43 arms and 20,898 patients were pooled. Association measures included correlation of event rates within arms, correlation of hazard ratios (HRs) between arms, trial level significance comparisons (via log-rank testing), and a formal surrogacy model. Results DFS at earlier times was less accurate in predicting OS than 3-year DFS, but 2-year DFS remained a strong predictor. DFS with 1-year minimum follow-up demonstrated perfect negative predicted value; all trials negative at 1 year for DFS were negative for 5-year OS. OS with 3-year minimum follow-up was also an excellent predictor for 5-year OS; OS at earlier time points provided inaccurate prediction. The association between 3-year DFS and 5-year OS was greater for stage III patients; correlation of HR within trials was 0.92 (95% CI, 0.85 to 0.95) for stage III patients and 0.70 (95% CI, 0.44 to 0.80) for stage II patients. Conclusion DFS outcomes after 2- or 3-year median follow-up are excellent predictors of 5-year OS. DFS outcomes are appropriate for trials in which the majority of patients are stage III. DFS after 2- or 3-year median follow-up should be considered as the primary end point in future colon adjuvant trials.

Purpose A traditional end point for colon adjuvant clinical trials is overall survival (OS), with 5 years demonstrating adequate follow-up. A shorter-term end point providing convincing evidence to allow treatment comparisons could significantly speed the translation of advances into practice. Methods Individual patient data were pooled from 18 randomized phase III colon cancer adjuvant clinical trials. Trials included 43 arms, with a pooled sample size of 20,898 patients. The primary hypothesis was that disease-free survival (DFS), with 3 years of follow-up, is an appropriate primary end point to replace OS with 5 years of follow-up. Results The recurrence rates for years 1 through 5 were 12%, 14%, 8%, 5%, and 3%, respectively. Median time from recurrence to death was 12 months. Eighty percent of recurrences were in the first 3 years; 91% of patients with recurrence by 3 years died before 5 years. Correlation between 3-year DFS and 5-year OS was 0.89. Comparing control versus experimental arms within each trial, the correlation between hazard ratios for DFS and OS was 0.92. Within-trial log-rank testing using both DFS and OS provided the same conclusion in 23 (92%) of 25 cases. Formal measures of surrogacy were satisfied. Conclusion In patients treated on phase III adjuvant colon clinical trials, DFS and OS are highly correlated, both within patients and across trials. These results suggest that DFS after 3 years of median follow-up is an appropriate end point for adjuvant colon cancer clinical trials of fluorouracil-based regimens, although marginally significant DFS improvements may not translate into significant OS benefits.